A CASE tool for the modeling of methods and information systems

MODSI is a multi-models tool for information systems modeling. A modeling process in MODSI can be driven according to three different approaches: informal, semi-formal and formal. The MODSI tool is therefore based on the linked usage of these three modeling approaches. It can be employed at two different levels: the meta-modeling of a method and the modeling of an information system.In this paper we start presenting different types of modeling by making an analysis of their particular features. Then, we introduce the meta-model defined in our tool, as well as the tool functional architecture. Finally, we describe and illustrate the various usage levels of this tool.

Finanças comportamentais e modelos baseados em agentes

Pós-graduação em Economia - FCLAR

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Modelagem do escoamento transiente ao longo de trocadores de calor tubo capilar-linha de sucção

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelagem de nicho ecológico de anuros da Mata Atlântica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise Bayesiana de dados composicionais na presença de covariáveis

Pós-graduação em Matematica Aplicada e Computacional - FCT

Methodological Difficulties of Conducting Agroecological Studies from a Statistical Perspective

Statistical methods for analyzing agroecological data might not be able to help agroecologists to solve all of the current problems concerning crop and animal husbandry, but such methods could well help them assess, tackle, and resolve several agroecological issues in a more reliable and accurate manner. Therefore, our goal in this article is to discuss the importance of statistical tools for alternative agronomic approaches, because alternative approaches, such as organic farming, should not only be promoted by encouraging farmers to deploy agroecological techniques, but also by providing agroecologists with robust analyses based on rigorous statistical procedures.

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.

Comparative effects of photodynamic therapy mediated by curcumin on standard and clinical isolate of Streptococcus mutans

Aim: The aim of this study was investigate the effect of photodynamic therapy (PDT) using curcumin (C) as a photosensitizing agent irradiated with an LED (L) in the blue wavelength as a light source on a standard and clinical isolate of Streptococcus mutans (S. mutans) in a planktonic suspension model. Materials and methods: Suspensions of both strains were divided into 4 groups as follows: absence of C and L (control group: C–L–), with C and without L (C group: C+L–), absence of C with L (L group: C–L+) and presence of C and L (PDT group: C+L+). Three different concentrations of curcumin (0.75 mg/ml, 1.5 mg/ml and 3 mg/ml) and three light fluences of studied light source (24, 48 and 72 J cm–2) were tested. Aliquots of each studied group was plated in BHI agar and submitted to colony forming units counting (CFU/ml) and the data transformed into logarithmical scale. Results: A high photoinactivation rate of more than 70% was verified to standard S. mutans strain submitted to PDT whereas the clinical isolate showed a lower sensitivity to all the associations of curcumin and LED. A slight bacterial reduction was verified to C+L– and C–L+, demonstrating no toxic effects to the isolated application of light and photosensitizer to both S. mutans strains tested. Conclusion: Photodynamic therapy using a combination of curcumin and blue LED presented a substantial antimicrobial effect on S. mutans standard strain in a planktonic suspension model with a less pronounced effect on its clinical isolate counterparts due to resistance to this alternative approach. Clinical significance: Alternative antimicrobial approaches, as photodynamic therapy, should be encouraged due to optimal results against cariogenic bacteria aiming to prevent or treat dental caries.

3D superimposition and understanding temporomandibular joint arthritis

Structured AbstractObjectivesTo investigate the 3D morphological variations in 169 temporomandibular ioint (TMJ) condyles, using novel imaging statistical modeling approaches.Setting and sample populationThe Department of Orthodontics and Pediatric Dentistry at the University of Michigan. Cone beam CT scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA, mean age 39.115.7years), 15 subjects at initial consult diagnosis of OA (mean age 44.914.8years), and seven healthy controls (mean age 4312.4years).Materials and methods3D surface models of the condyles were constructed, and homologous correspondent points on each model were established. The statistical framework included Direction-Projection-Permutation (DiProPerm) for testing statistical significance of the differences between healthy controls and the OA groups determined by clinical and radiographic diagnoses.ResultsCondylar morphology in OA and healthy subjects varied widely with categorization from mild to severe bone degeneration or overgrowth. DiProPerm statistics supported a significant difference between the healthy control group and the initial diagnosis of OA group (t=6.6, empirical p-value=0.006) and between healthy and long-term diagnosis of OA group (t=7.2, empirical p-value=0). Compared with healthy controls, the average condyle in OA subjects was significantly smaller in all dimensions, except its anterior surface, even in subjects with initial diagnosis of OA.ConclusionThis new statistical modeling of condylar morphology allows the development of more targeted classifications of this condition than previously possible.

Molecular approaches for structural characterization of Bothrops L-amino acid oxidases with antiprotozoal activity: cDNA cloning, comparative sequence analysis, and molecular modeling

Two L-amino acid oxidases (LAAOs) were identified by random sequencing of cDNA libraries from the venom glands of Bothrops moojeni (BmooLAAO) and Bothrops jararacussu (Bjussu LAAO). Phylogenetic analysis involving other SV-LAAOs showed sequence identities within the range 83-87% being closely related to those from Agkistrodon and Trimeresurus. Molecular modeling experiments indicated the FAD-binding, substrate-binding, and helical domains of Bmoo and Bjussu LAAOs. The RMS deviations obtained by the superposition of those domains and that from Calloselasma rhodostoma LAAO crystal structure confirm the high degree of structural similarity between these enzymes. Purified BjussuLAAO-I and BmooLAAO-I exhibited antiprotozoal activities which were demonstrated to be hydrogen-peroxide mediated. This is the first report on the isolation and identification of cDNAs encoding LAAOs from Bothrops venom. The findings here reported contribute to the overall structural elucidation of SV-LAAOs and will advance the understanding on their mode of action. (c) 2006 Elsevier B.V. All rights reserved.

Study of alternative schemes for the parameterization step of the continuation power flow method based on physical parameters, part I: Mathematical modeling

The conventional power flow method is considered to be inadequate to obtain the maximum loading point because of the singularity of Jacobian matrix. Continuation methods are efficient tools for solving this kind of problem since different parameterization schemes can be used to avoid such ill-conditioning problems. This paper presents the details of new schemes for the parameterization step of the continuation power flow method. The new parameterization options are based on physical parameters, namely, the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, and transmission line power losses (real and reactive). The simulation results obtained with the new approach for the IEEE test systems (14, 30, 57, and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are not only preserved but also improved.

Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

GPS/VRS positioning using atmospheric modeling

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

Chromogenic in situ hybridization compared with other approaches to evaluate HER2/neu status in breast carcinomas

Human epidermal growth factor receptor 2 (HER2) has been evaluated in breast cancer patients to identify those most likely to benefit from herceptin-targeted therapy. HER2 amplification, detected in 20-30% of invasive breast tumors, is associated with reduced survival and metastasis. The most frequently used technique for evaluating HER2 protein status as a routine procedure is immunohistochemistry (IHC). HER2 copy number alterations have also been evaluated by fluorescence in situ hybridization (FISH) in moderate immunoexpression (IHC 2+) cases. An alternative procedure to evaluate gene amplification is chromogenic in situ hybridization (CISH), which has some advantages over FISH, including the correlation between HER2 status and morphological features. Other methodologies have also been used, such as silver-enhanced in situ hybridization (SISH) and quantitative real-time RT-PCR, to determine the number of HER2 gene copies and expression, respectively. Here we will present a short and comprehensive review of the current advances concerning HER2 evaluation in human breast cancer.