924 resultados para Markov Switching
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Este trabalho tem como objetivo o estudo do comportamento assintótico da estatística de Pearson (1900), que é o aparato teórico do conhecido teste qui-quadrado ou teste x2 como também é usualmente denotado. Inicialmente estudamos o comportamento da distribuição da estatística qui-quadrado de Pearson (1900) numa amostra {X1, X2,...,Xn} quando n → ∞ e pi = pi0 , 8n. Em seguida detalhamos os argumentos usados em Billingley (1960), os quais demonstram a convergência em distribuição de uma estatística, semelhante a de Pearson, baseada em uma amostra de uma cadeia de Markov, estacionária, ergódica e com espaço de estados finitos S
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In this work we study the Hidden Markov Models with finite as well as general state space. In the finite case, the forward and backward algorithms are considered and the probability of a given observed sequence is computed. Next, we use the EM algorithm to estimate the model parameters. In the general case, the kernel estimators are used and to built a sequence of estimators that converge in L1-norm to the density function of the observable process
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In this work we studied the consistency for a class of kernel estimates of f f (.) in the Markov chains with general state space E C Rd case. This study is divided into two parts: In the first one f (.) is a stationary density of the chain, and in the second one f (x) v (dx) is the limit distribution of a geometrically ergodic chain
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Os Algoritmos Genético (AG) e o Simulated Annealing (SA) são algoritmos construídos para encontrar máximo ou mínimo de uma função que representa alguma característica do processo que está sendo modelado. Esses algoritmos possuem mecanismos que os fazem escapar de ótimos locais, entretanto, a evolução desses algoritmos no tempo se dá de forma completamente diferente. O SA no seu processo de busca trabalha com apenas um ponto, gerando a partir deste sempre um nova solução que é testada e que pode ser aceita ou não, já o AG trabalha com um conjunto de pontos, chamado população, da qual gera outra população que sempre é aceita. Em comum com esses dois algoritmos temos que a forma como o próximo ponto ou a próxima população é gerada obedece propriedades estocásticas. Nesse trabalho mostramos que a teoria matemática que descreve a evolução destes algoritmos é a teoria das cadeias de Markov. O AG é descrito por uma cadeia de Markov homogênea enquanto que o SA é descrito por uma cadeia de Markov não-homogênea, por fim serão feitos alguns exemplos computacionais comparando o desempenho desses dois algoritmos
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In this work, we present a risk theory application in the following scenario: In each period of time we have a change in the capital of the ensurance company and the outcome of a two-state Markov chain stabilishs if the company pays a benece it heat to one of its policyholders or it receives a Hightimes c > 0 paid by someone buying a new policy. At the end we will determine once again by the recursive equation for expectation the time ruin for this company
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In this work, we studied the strong consistency for a class of estimates for a transition density of a Markov chain with general state space E ⊂ Rd. The strong ergodicity of the estimates for the density transition is obtained from the strong consistency of the kernel estimates for both the marginal density p(:) of the chain and the joint density q(., .). In this work the Markov chain is supposed to be homogeneous, uniformly ergodic and possessing a stationary density p(.,.)
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The central objective of a study Non-Homogeneous Markov Chains is the concept of weak and strong ergodicity. A chain is weak ergodic if the dependence on the initial distribution vanishes with time, and it is strong ergodic if it is weak ergodic and converges in distribution. Most theoretical results on strong ergodicity assume some knowledge of the limit behavior of the stationary distributions. In this work, we collect some general results on weak and strong ergodicity for chains with space enumerable states, and also study the asymptotic behavior of the stationary distributions of a particular type of Markov Chains with finite state space, called Markov Chains with Rare Transitions
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The aim of this study was to evaluate the influence of the platform-switching technique on stress distribution in implant, abutment, and pen-implant tissues, through a 3-dimensional finite element study. Three 3-dimensional mandibular models were fabricated using the Solid Works 2006 and InVesalius software. Each model was composed of a bone block with one implant 10 mm long and of different diameters (3.75 and 5.00 mm). The UCLA abutments also ranged in diameter from 5.00 mm to 4.1 mm. After obtaining the geometries, the models were transferred to the software FEMAP 10.0 for pre- and postprocessing of finite elements to generate the mesh, loading, and boundary conditions. A total load of 200 N was applied in axial (0 degrees), oblique (45 degrees), and lateral (90) directions. The models were solved by the software NeiNastran 9.0 and transferred to the software FEMAP 10.0 to obtain the results that were visualized through von Mises and maximum principal stress maps. Model A (implants with 3.75 mm/abutment with 4.1 mm) exhibited the highest area of stress concentration with all loadings (axial, oblique, and lateral) for the implant and the abutment. All models presented the stress areas at the abutment level and at the implant/abutment interface. Models B (implant with 5.0 mm/abutment with 5.0 mm) and C (implant with 5.0 mm/abutment with 4.1 mm) presented minor areas of stress concentration and similar distribution pattern. For the cortical bone, low stress concentration was observed in the pen-implant region for models B and C in comparison to model A. The trabecular bone exhibited low stress that was well distributed in models B and C. Model A presented the highest stress concentration. Model B exhibited better stress distribution. There was no significant difference between the large-diameter implants (models B and C).
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The aim of this study was to evaluate the stress distribution of platform switching implants using a photoelastic method. Three models were constructed of the photoelastic resin PL-2, with a single implant and a screw-retained implant-supported prosthesis. These models were Model A, platform 5.0 mm/abutment 4.1 mm; Model B, platform 4.1 mm/abutment 4.1 mm; and Model C, platform 5.00 mm/abutment 5.00 mm. Axial and oblique (45 degrees) loads of 100 N were applied using a Universal Testing Machine (EMIC DL 3000). Images were photographed with a digital camera and visualized with software (AdobePhotoshop) to facilitate the qualitative analysis. The highest stress concentrations were observed at the apical third of the 3 models. With the oblique load, the highest stress concentrations were located at the implant apex, opposite the load application. Stress concentrations decreased in the cervical region of Model A (platform switching), and Models A (platform switching) and C (conventional/wide-diameter) displayed similar stress magnitudes. Finally, Model B (conventional/regular diameter) displayed the highest stress concentrations of the models tested.
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Purpose: The objective of this study was to evaluate, using three-dimensional finite element analysis (3D FEA), the stress distribution in peri-implant bone tissue, implants, and prosthetic components of implant-supported single crowns with the use of the platform-switching concept. Materials and Methods: Three 3D finite element models were created to replicate an external-hexagonal implant system with peri-implant bone tissue in which three different implant-abutment configurations were represented. In the regular platform (RP) group, a regular 4.1-mm-diameter abutment (UCLA) was connected to regular 4.1-mm-diameter implant. The platform-switching (PS) group was simulated by the connection of a wide implant (5.0 mm diameter) to a regular 4.1-mm-diameter UCLA abutment. In the wide-platform (WP) group, a 5.0-mm-diameter UCLA abutment was connected to a 5.0-mm-diameter implant. An occlusal load of 100 N was applied either axially or obliquely on the models using ANSYS software. Results: Both the increase in implant diameter and the use of platform switching played roles in stress reduction. The PS group presented lower stress values than the RP and WP groups for bone and implant. In the peri-implant area, cortical bone exhibited a higher stress concentration than the trabecular bone in all models and both loading situations. Under oblique loading, higher intensity and greater distribution of stress were observed than under axial loading. Platform switching reduced von Mises (17.5% and 9.3% for axial and oblique loads, respectively), minimum (compressive) (19.4% for axial load and 21.9% for oblique load), and maximum (tensile) principal stress values (46.6% for axial load and 26.7% for oblique load) in the peri-implant bone tissue. Conclusion: Platform switching led to improved biomechanical stress distribution in peri-implant bone tissue. Oblique loads resulted in higher stress concentrations than axial loads for all models. Wide-diameter implants had a large influence in reducing stress values in the implant system. INT J ORAL MAXILLOFAC IMPLANTS 2011;26:482-491
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In implant therapy, a peri-implant bone resorption has been noticed mainly in the first year after prosthesis insertion. This bone remodeling can sometimes jeopardize the outcome of the treatment, especially in areas in which short implants are used and also in aesthetic cases. To avoid this occurrence, the use of platform switching (PS) has been used. This study aimed to evaluate the biomechanical concept of PS with relation to stress distribution using two-dimensional finite element analysis. A regular matching diameter connection of abutment-implant (regular platform group [RPG]) and a PS connection (PS group [PSG]) were simulated by 2 two-dimensional finite element models that reproduced a 2-piece implant system with peri-implant bone tissue. A regular implant (prosthetic platform of 4.1 mm) and a wide implant (prosthetic platform of 5.0 mm) were used to represent the RPG and PSG, respectively, in which a regular prosthetic component of 4.1 mm was connected to represent the crown. A load of 100 N was applied on the models using ANSYS software. The RPG spreads the stress over a wider area in the peri-implant bone tissue (159 MPa) and the implant (1610 MPa), whereas the PSG seems to diminish the stress distribution on bone tissue (34 MPa) and implant (649 MPa). Within the limitation of the study, the PS presented better biomechanical behavior in relation to stress distribution on the implant but especially in the bone tissue (80% less). However, in the crown and retention screw, an increase in stress concentration was observed.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We investigated the mechanisms responsible for increased blood pressure and sympathetic nerve activity (SNA) caused by 2-3 days dehydration (DH) both in vivo and in situ preparations. In euhydrated (EH) rats, systemic application of the AT(1) receptor antagonist Losartan and subsequent pre-collicular transection (to remove the hypothalamus) significantly reduced thoracic (t) SNA. In contrast, in DH rats, Losartan, followed by pre-collicular and pontine transections, failed to reduce tSNA, whereas transection at the medulla-spinal cord junction massively reduced tSNA. In DH but not EH rats, selective inhibition of the commissural nucleus tractus solitarii (cNTS) significantly reduced tSNA. Comparable data were obtained in both in situ and in vivo (anaesthetized/conscious) rats and suggest that following chronic dehydration, the control of tSNA transfers from supra-brainstem structures (e. g. hypothalamus) to the medulla oblongata, particularly the cNTS. As microarray analysis revealed up-regulation of AP1 transcription factor JunD in the dehydrated cNTS, we tested the hypothesis that AP1 transcription factor activity is responsible for dehydration-induced functional plasticity. When AP1 activity was blocked in the cNTS using a viral vector expressing a dominant negative FosB, cNTS inactivation was ineffective. However, tSNA was decreased after pre-collicular transection, a response similar to that seen in EHrats. Thus, the dehydration-induced switch in control of tSNA from hypothalamus to cNTS seems to be mediated via activation of AP1 transcription factors in the cNTS. If AP1 activity is blocked in the cNTS during dehydration, sympathetic activity control reverts back to forebrain regions. This unique reciprocating neural structure-switching plasticity between brain centres emphasizes the multiple mechanisms available for the adaptive response to dehydration.