O Modelo de Ising inomogêneo: uma interrupção contínua entre as redes quadrada e triangular.

The ferromagnetic and antiferromagnetic Ising model on a two dimensional inhomogeneous lattice characterized by two exchange constants (J1 and J2) is investigated. The lattice allows, in a continuous manner, the interpolation between the uniforme square (J2 = 0) and triangular (J2 = J1) lattices. By performing Monte Carlo simulation using the sequential Metropolis algorithm, we calculate the magnetization and the magnetic susceptibility on lattices of differents sizes. Applying the finite size scaling method through a data colappse, we obtained the critical temperatures as well as the critical exponents of the model for several values of the parameter α = J2 J1 in the [0, 1] range. The ferromagnetic case shows a linear increasing behavior of the critical temperature Tc for increasing values of α. Inwhich concerns the antiferromagnetic system, we observe a linear (decreasing) behavior of Tc, only for small values of α; in the range [0.6, 1], where frustrations effects are more pronunciated, the critical temperature Tc decays more quickly, possibly in a non-linear way, to the limiting value Tc = 0, cor-responding to the homogeneous fully frustrated antiferromagnetic triangular case.

Interações físicas e psicossociais em mulheres com fibromialgia

Fibromyalgia (FM) is a non-inflammatory rheumatic syndrome of unknown etiology, with symptoms of diffuse musculoskeletal pain and presence of specific anatomic sites called tender points. The symptoms are often associated with fatigue, sleep disturbances, morning stiffness, alterations in pain perception, anxiety and depression. Fibromyalgia exhibits a correlation between physical and behavioral symptoms, which have a negative influence on the quality of life of patients. Emotional skills are important factors since they are related to subjective well-being, personal productivity, social interaction and interpersonal relationships. We aim to describe the physical and psychosocial interactions in women with FM, showing the association between perceived social support and affect with symptoms of pain, functionality and mood. We will also describe a body representation of pain in women with FM. Data were collected over 3 years and the sample size ranged between studies. This is an exploratory cross-sectional study conducted with a convenience sample of 63 women with FM and 42 healthy women as a control group (CT), aged 20-76 years, recruited through spontaneous demand at Onofre Lopes University Hospital (HUOL) and the Clinical School of Physiotherapy of Universidade Potiguar (UNP). The Fibromyalgia Impact Questionnaire (FIQ), Beck Depression Inventory (BDI), Social Support Scale (MOS), Hamilton Anxiety Scale and Scale of Positive and Negative Affect Schedule (PANAS), in addition to pressure algometry were used. For data analysis, we used parametric and non-parametric tests and a general linear model with adjustment variables and analysis of variance. A significant difference was found between pain threshold and tolerance, functionality, depression, anxiety, social support, and positive and negative affect between the groups. Affective states and social support were associated with anxiety, depression and functionality. A body was drawn representing pain with higher incidences in trapeze, supraspinatus and second ribs. The reason for studying sensory aspects, affective behavior and social support in FM patients opens perspectives for scientific and clinical research of this syndrome. Women with chronic pain such as FM appear to have altered mood states, less social support and affective dysfunctions, influencing the other symptoms of the syndrome

Espectroscopia no infravermelho próximo e métodos de calibração multivariada aplicados à determinação simultânea de parâmetros bioquímicos em plasma sanguíneo

In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

Estudos de adsorção de tetraciclina em partículas de quitosana

Due to its physico-chemical and biological properties, related to the abundance and low cost of raw material, chitosan has been recognized as a material of wide application in various fields, such as in drug delivery systems. Many of these properties are associated with the presence of amino groups in its polymer chain. A proper determination of these amino groups is very important, in order to properly specify if a given chitosan sample can be used in a particular application. Thus, in this work, initially, a comparison between the determination of the deacetylation degree by conductometry and elemental analysis was carried out using a detailed analysis of error propagation. It was shown that the conductometric analysis resulted in a simple and safe method for the determining the degree of deacetylation of chitosan. Subsequently, experiments were performed to monitor and characterize the adsorption of tetracycline on chitosan particles through kinetic and equilibrium studies. The main models of kinetics and adsorption isotherms, widely used to describe the adsorption on wastewater treatment systems and the drug loading, were used to treat the experimental data. Firstly, it was shown that an apparent linear t/q(t) × t relationship did not imply in a pseudo-second-order adsorption kinetics, differently of what has been repeatedly reported in the literature. It was found that this misinterpretation can be avoided by using non-linear regression. Finally, the adsorption of tetracycline on chitosan particles was analyzed using insights obtained from theoretical analysis, and the parameters generated were used to analyze the kinetics of adsorption, the isotherm of adsorption and to ropose a mechanism of adsorption