Algorithm to determine the intersection curves between bezier surfaces by the solution of multivariable polynomial system and the differential marching method

The determination of the intersection curve between Bézier Surfaces may be seen as the composition of two separated problems: determining initial points and tracing the intersection curve from these points. The Bézier Surface is represented by a parametric function (polynomial with two variables) that maps a point in the tridimensional space from the bidimensional parametric space. In this article, it is proposed an algorithm to determine the initial points of the intersection curve of Bézier Surfaces, based on the solution of polynomial systems with the Projected Polyhedral Method, followed by a method for tracing the intersection curves (Marching Method with differential equations). In order to allow the use of the Projected Polyhedral Method, the equations of the system must be represented in terms of the Bernstein basis, and towards this goal it is proposed a robust and reliable algorithm to exactly transform a multivariable polynomial in terms of power basis to a polynomial written in terms of Bernstein basis .

Substitution-Newton-Raphson method applied to the modeling of a vapour compression refrigeration system using different representations of the thermodynamic properties of R-134a

This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.

Structural changes in latosols of the cerrado region: II - soil compressive behavior and modeling of additional compaction

Currently in Brazil, as in other parts of the world, the concern is great with the increase of degraded agricultural soil, which is mostly related to the occurrence of soil compaction. Although soil texture is recognized as a very important component in the soil compressive behaviors, there are few studies that quantify its influence on the structural changes of Latosols in the Brazilian Cerrado region. This study aimed to evaluate structural changes and the compressive behavior of Latosols in Rio Verde, Goiás, through the modeling of additional soil compaction. The study was carried out using five Latosols with very different textures, under different soil compaction levels. Water retention and soil compression curves, and bearing capacity models were determined from undisturbed samples collected on the B horizons. Results indicated that clayey and very clayey Latosols were more susceptible to compression than medium-textured soils. Soil compression curves at density values associate with edaphic functions were used to determine the beneficial pressure (σ b) , i.e., pressure with optimal water retention, and critical pressure (σcrMAC), i.e., pressure with macroporosity below critical levels. These pressure values were higher than the preconsolidation pressure (σp), and therefore characterized as additional compaction. Based on the compressive behavior of these Latosols, it can be concluded that the combined preconsolidation pressure, beneficial pressure and critical pressure allow a better understanding of compression processes of Latosols.

Assessment of pedotransfer functions for estimating soil water retention curves for the amazon region

Knowledge of the soil water retention curve (SWRC) is essential for understanding and modeling hydraulic processes in the soil. However, direct determination of the SWRC is time consuming and costly. In addition, it requires a large number of samples, due to the high spatial and temporal variability of soil hydraulic properties. An alternative is the use of models, called pedotransfer functions (PTFs), which estimate the SWRC from easy-to-measure properties. The aim of this paper was to test the accuracy of 16 point or parametric PTFs reported in the literature on different soils from the south and southeast of the State of Pará, Brazil. The PTFs tested were proposed by Pidgeon (1972), Lal (1979), Aina & Periaswamy (1985), Arruda et al. (1987), Dijkerman (1988), Vereecken et al. (1989), Batjes (1996), van den Berg et al. (1997), Tomasella et al. (2000), Hodnett & Tomasella (2002), Oliveira et al. (2002), and Barros (2010). We used a database that includes soil texture (sand, silt, and clay), bulk density, soil organic carbon, soil pH, cation exchange capacity, and the SWRC. Most of the PTFs tested did not show good performance in estimating the SWRC. The parametric PTFs, however, performed better than the point PTFs in assessing the SWRC in the tested region. Among the parametric PTFs, those proposed by Tomasella et al. (2000) achieved the best accuracy in estimating the empirical parameters of the van Genuchten (1980) model, especially when tested in the top soil layer.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography

Abstract Objective: Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods: Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results: Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion: The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.

Synthesis, characterization and thermal behaviour of solid-state compounds of benzoates with some bivalent transition metal ions

Solid-state MBz compounds, where M stands for bivalent Mn, Fe, Co, Ni, Cu and Zn and Bz is benzoate, have been synthesized. Simultaneous thermogravimetry and differential thermal analysis (TG-DTA), differential scanning calorimetry (DSC), infrared spectroscopy and complexometry were used to characterize and to study the thermal behaviour of these compounds. The procedure used in the preparation of the compounds via reaction of basic carbonates with benzoic acid is not efficient in eliminating excess acid. However the TG-DTA curves permitted to verify that the binary compounds can be obtained by thermosynthesis, because the benzoic acid can be eliminated before the thermal decomposition of these compounds. The results led to information about the composition, dehydration, thermal stability, thermal decomposition and structure of the isolated compounds. On heating, these compounds decompose in two (Mn, Co, Ni, Zn) or three (Fe, Cu) steps with formation of the respective oxide (Mn3O4, Fe2O3, Co3O4, NiO, CuO and ZnO) as final residue. The theoretical and experimental spectroscopic studies suggest a covalent bidentate bond between ligand and metallic center.

Improvement of genistein content in solid genistein/-cyclodextrin complexes β

Genistein:β-cyclodextrin complexes with high drug loading (19.22%) were prepared by freeze-drying and characterized by differential scanning calorimetry and hydrogen nuclear magnetic resonance spectroscopy. The spatial configuration of the complex was proposed by means of 2D-NOESY experiment combined with molecular modeling. According to the results obtained, the interaction of genistein with β -cyclodextrin in a 1:1 complex is supposed to occur mainly through the insertion of the guest A-ring in cyclodextrin cavity, without rule out the possibility of inclusion through the B-ring, as previously reported in the literature.

Dehydration and volatilization non isothermic kinetic of the solid state aluminium 8-hydroxyquinolinate

Al(C9H6ON)3.2.5H2O was precipitated from the mixture of an aqueous solution of aluminium ion and an acid solution of 8-hydroxyquinoline, by increasing the pH value to 9.5 with ammonia aqueous solution. The TG curves in nitrogen atmosphere present mass losses due to dehydration, partial volatilisation (sublimation plus vaporisation) of the anhydrous compound followed by thermal decomposition with the formation of a mixture of carbonaceous and residues. The relation between sublimation and vaporisation depends on the heating rate used. The non isothermic integral isoconventional methods as linear equations of Ozawa-Flynn-Wall and Kissinger-Akahira-Sunose (KAS) were used to obtain the kinetic parameters from TG and DTA curves, respectively. Despite the fact that both dehydration and volatilisation reactions follow the linearity by using both methods, only for the volatilisation reaction the validity condition, 20<= E/RT<= 50, was verified.

Thermoanalytical study of the complexes of 4-dimetilaminocinnamylidenepiruvate with manganese (II), cobalt (II), nickel (II), cupper (II), zinc (II) and lead (II), in the solid state

Solid state compounds M-4-DMCP, where 4-DMCP is 4-dimethylaminocinnamylidenepyruvate and M represents Mn (II), Co (II), Ni (II), Cu (II), Zn (II) and Pb (II) were prepared. These compounds were studied by thermoanalitycal techniques: thermogravimetry (TG), derivative thermogravimetry (DTG), differential scanning calorimetry (DSC), X-ray diffraction powder patterns and complexometric titration with EDTA. From the results obtained by the complexometric titration with EDTA, TG, DTG and DSC curves, was possible to establish the hydration degree, stoichiometry and thermal stability of the prepared compounds.

Comparison of the dehydration kinetics of solid state compounds of 2-methoxybenzylidenepyruvate with some divalent metal ions

Divalent metal complexes of ligand 2-methoxybenzylidenepyruvate with Fe, Co, Ni, Cu and Zn as well as sodium salt were synthesized and investigated in the solid state. TG curves of these compounds were obtained with masses sample of 1 and 5mg under nitrogen atmosphere. Different heating rates were used to characterize and study these compounds from the kinetic point of view. The activation energy and pre-exponential factor were obtained applying the Wall-Flynn-Ozawa method to the TG curves. The obtained data were evaluated and the values of activation energy (Ea / kJ mol-1) was plotted in function of the conversion degree (α). The results show that due to mass sample, different activation energies were obtained. The results are discussed mainly taking into account the linear dependence between the activation energy and the pre exponential factor, where was verified the effect of kinetic compensation (KCE) and possible linear relations between the dehydrations steps of these compounds.

Modeling the pressure inactivation dynamics of Escherichia coli

Escherichia coli, as a model microorganism, was treated in phosphate-buffered saline under high hydrostatic pressure between 100 and 300 MPa, and the inactivation dynamics was investigated from the viewpoint of predictive microbiology. Inactivation data were curve fitted by typical predictive models: logistic, Gompertz and Weibull functions. Weibull function described the inactivation curve the best. Two parameters of Weibull function were calculated for each holding pressure and their dependence on holding pressure was obtained by interpolation. With the interpolated parameters, inactivation curves were simulated and compared with the experimental data sets.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Multicomponent diffusion during Prato cheese ripening: mathematical modeling using the finite element method

The partial replacement of NaCl by KCl is a promising alternative to produce a cheese with lower sodium content since KCl does not change the final quality of the cheese product. In order to assure proper salt proportions, mathematical models are employed to control the product process and simulate the multicomponent diffusion during the reduced salt cheese ripening period. The generalized Fick's Second Law is widely accepted as the primary mass transfer model within solid foods. The Finite Element Method (FEM) was used to solve the system of differential equations formed. Therefore, a NaCl and KCl multicomponent diffusion was simulated using a 20% (w/w) static brine with 70% NaCl and 30% KCl during Prato cheese (a Brazilian semi-hard cheese) salting and ripening. The theoretical results were compared with experimental data, and indicated that the deviation was 4.43% for NaCl and 4.72% for KCl validating the proposed model for the production of good quality, reduced-sodium cheeses.

Mathematical modeling of dehydration of 'Fuji' and 'Gala' apples slices using infrared

The objective of this work was to determine and model the infrared dehydration curves of apple slices - Fuji and Gala varieties. The slices were dehydrated until constant mass, in a prototype dryer with infrared heating source. The applied temperatures ranged from 50 to 100 °C. Due to the physical characteristics of the product, the dehydration curve was divided in two periods, constant and falling, separated by the critical moisture content. A linear model was used to describe the constant dehydration period. Empirical models traditionally used to model the drying behavior of agricultural products were fitted to the experimental data of the falling dehydration period. Critical moisture contents of 2.811 and 3.103 kgw kgs-1 were observed for the Fuji and Gala varieties, respectively. Based on the results, it was concluded that the constant dehydration rates presented a direct relationship with the temperature; thus, it was possible to fit a model that describes the moisture content variation in function of time and temperature. Among the tested models, which describe the falling dehydration period, the model proposed by Midilli presented the best fit for all studied conditions.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.