Conexão entre as redes complexas e estatística de Kaniadakis e busca eficiente das propriedades críticas do processo epidêmico difusivo 1D

In this work we study a connection between a non-Gaussian statistics, the Kaniadakis statistics, and Complex Networks. We show that the degree distribution P(k)of a scale free-network, can be calculated using a maximization of information entropy in the context of non-gaussian statistics. As an example, a numerical analysis based on the preferential attachment growth model is discussed, as well as a numerical behavior of the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive epidemic process (DEP) on a regular lattice one-dimensional. The model is composed of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This model belongs to the category of non-equilibrium systems with an absorbing state and a phase transition between active an inactive states. We investigate the critical behavior of the DEP using an auto-adaptive algorithm to find critical points: the method of automatic searching for critical points (MASCP). We compare our results with the literature and we find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases DA =DB, DA DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.

Simulação de Fluxo no Meio Poroso Utilizando o Fluent

The complexity of the Phenomenon of fluid flow in porous way causes a difficulty in its explicit description. Different in the cases where the flow is given through a pipe, where it is possible to measure the length and diameter of the pipe and to determine their ability to flow as a function of pressure, which is a complicated task in porous way. However, we try to approach clearly the equations used to conjecture the behavior of fluid flow in porous way. We made use of the Gambit to create a fractal geometry with the fluent we give the contour´s conditions we would want to analyze the data. The triangular mesh was created; it makes interactions with the discs of different rays, as barriers putted in the geometry. This work presents the results of a simulation with a flow of viscous fluids (oilliquid). The oil flows in a porous way constructed in 2D. The behavior evaluation of the fluid flow inside the porous way was realized with graphics, images and numerical results used for different datas analysis. The study was aimed in relation at the behavior of permeability (k) for different fractal dimensions. Taking into account the preservation of porosity and increasing the fractal distribution of the discs. The results showed that k decreases when we increase the numbers of discs, although the porosity is the same for all generations of the first simulation, in other words, the permeability decreases when we increase the fractality. Well, there are strong turbulence in the flow each time we increase the number of discs and this hinders the passage of the same to the exit. These results permitted to put in evidence how the permeability (k) is affected in a porous way with obstacles distributed in a diversified form. We also note that k decreases when we increase the pressure variation (P) within geometry. So, in front of the results and the absence of bibliographic subsidies about other theories, the work realized here can possibly by considered the unpublished form to explain and reflect on how the permeability is changed when increasing the fractal dimension in a porous way

Frequência e significado clínico da expressão da glicoproteína P e da proteína relacionada a resistência a múltiplas drogas na leucemia mielóide aguda

Despite the advances in the cure rate for acute myeloid leukemia, a considerable number of patients die from their disease due to the occurrence of multidrug resistance (MDR). Overexpression of the transporter proteins P-glycoprotein (Pgp) and multidrug resistance-associated protein (MRP) confer resistance to the treatment these leukemias. OBJECTIVE: To analyze the expression of the Gpp and MRP1 in patients with AML by flow cytometry (FC) and to determine the correlation between expression and demographic and also clinical and laboratorial variables. METHODS: Bone marrow and peripheral blood samples from 346 patients with a diagnosis of AML were assessed for the expression of Pgp and MRP1 by FC. RESULTS: The expression of Pgp and MRP1 was found in 111 (32.1%) and 133 (38.4%) patients, respectively, with greater prevalence in older patients and lower in adolescents, observing also a high incidence in patients with refractory disease, recurrence and secondary in comparison with the cases of de novo AML. Regarding the laboratory findings, we observed a higher correlation statistically significant between the expression of Pgp and MRP1 in AML CD34+ and FAB AML M7, M5A and M2 and lower the M3 subtype, not observed statistically significant correlation between the phenotype MDR and other laboratory data such with hemoglobin, leukocyte count, platelet count, aberrant expression of lymphoid antigens (CD2, CD7 and CD19) and clinical signs related to the disease. CONCLUSIONS: The results showed that the detection of MDR phenotype by flow cytometry can be a molecular marker for prognosis independent patients diagnosed with AML.

Registro global de nuvens de pontos RGB-D em tempo real usando fluxo óptico e marcadores

Registration of point clouds captured by depth sensors is an important task in 3D reconstruction applications based on computer vision. In many applications with strict performance requirements, the registration should be executed not only with precision, but also in the same frequency as data is acquired by the sensor. This thesis proposes theuse of the pyramidal sparse optical flow algorithm to incrementally register point clouds captured by RGB-D sensors (e.g. Microsoft Kinect) in real time. The accumulated errorinherent to the process is posteriorly minimized by utilizing a marker and pose graph optimization. Experimental results gathered by processing several RGB-D datasets validatethe system proposed by this thesis in visual odometry and simultaneous localization and mapping (SLAM) applications.