Bright solitons in quasi-one-dimensional dipolar condensates with spatially modulated interactions

We introduce a model for the condensate of dipolar atoms or molecules, in which the dipole-dipole interaction (DDI) is periodically modulated in space due to a periodic change of the local orientation of the permanent dipoles, imposed by the corresponding structure of an external field (the necessary field can be created, in particular, by means of magnetic lattices, which are available to the experiment). The system represents a realization of a nonlocal nonlinear lattice, which has a potential to support various spatial modes. By means of numerical methods and variational approximation (VA), we construct bright one-dimensional solitons in this system and study their stability. In most cases, the VA provides good accuracy and correctly predicts the stability by means of the Vakhitov-Kolokolov criterion. It is found that the periodic modulation may destroy some solitons, which exist in the usual setting with unmodulated DDI and can create stable solitons in other cases, not verified in the absence of modulations. Unstable solitons typically transform into persistent localized breathers. The solitons are often mobile, with inelastic collisions between them leading to oscillating localized modes. © 2013 American Physical Society.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Green-Markov models - new optimization strategies: a case study for user allocation in co-channel macro/femto networks

ABSTRACT: The femtocell concept aims to combine fixed-line broadband access with mobile telephony using the deployment of low-cost, low-power third and fourth generation base stations in the subscribers' homes. While the self-configuration of femtocells is a plus, it can limit the quality of service (QoS) for the users and reduce the efficiency of the network, based on outdated allocation parameters such as signal power level. To this end, this paper presents a proposal for optimized allocation of users on a co-channel macro-femto network, that enable self-configuration and public access, aiming to maximize the quality of service of applications and using more efficiently the available energy, seeking the concept of Green networking. Thus, when the user needs to connect to make a voice or a data call, the mobile phone has to decide which network to connect, using the information of number of connections, the QoS parameters (packet loss and throughput) and the signal power level of each network. For this purpose, the system is modeled as a Markov Decision Process, which is formulated to obtain an optimal policy that can be applied on the mobile phone. The policy created is flexible, allowing different analyzes, and adaptive to the specific characteristics defined by the telephone company. The results show that compared to traditional QoS approaches, the policy proposed here can improve energy efficiency by up to 10%.

Green markov - uma abordagem híbrida de política markoviana e simulação discreta para planejamento de alocação de usuários em redes macro-femto

O uso da comunicação de voz e dados através de dispositivos móveis vem aumentando significativamente nos últimos anos. Tal expansão traz algumas dificuldades inerentes, tais como: ampliação constante de capacidade das redes e eficiência energética. Neste contexto, vem se consolidando o conceito de Green networks, que se concentra no esforço para economia de energia e redução de CO2. Neste sentido, este trabalho propõe validar um modelo de uma política baseado em processo markoviano de decisão, visando a otimizar o consumo de energia, QoS e QoE, na alocação de usuários em redes macrocell e femtocell. Para isso o modelo foi inserido no simulador NS-2, aliando a solução analítica markoviana à flexibilidade característica da simulação discreta. A partir dos resultados apresentados na simulação, a política obteve uma economia significativa no consumo energético, melhorando a eficiência energética em até 4%, além de melhorar a qualidade de serviço em relação às redes macrocell e femtocell, demonstrando-se eficaz, de modo a alterar diretamente as métricas de QoS e de QoE.

Evolução das disparidades da extração vegetal e da silvicultura na Amazônia Legal: uma aplicação da cadeia de Markov

O artigo analisa a convergência municipal da produtividade vegetal (extração vegetal e silvicultura) na região da Amazônia Legal entre os anos de 1996 e 2006. Para analisar a convergência, optou-se pela metodologia da matriz de transição de Markov (Processo Estacionário de Primeira Ordem de Markov). Os resultados mostram a existência de 13 classes de convergência da produtividade vegetal. No longo prazo, a hipótese de convergência absoluta não se mantém, visto que 68,23% dos municípios encontram-se numa classe inferior à média municipal, 33,54% em uma classe intermediária acima da média e 13,41% em uma classe superior acima da média.

Wide vector solitons in systems with time- and space-modulated nonlinearities

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

RANKL expression is differentially modulated by TLR2 and TLR4 signaling in fibroblasts and osteoblasts

Resident, non-immune cells express various pattern-recognition receptors and produce inflammatory cytokines in response to microbial antigens, during the innate immune response. Alveolar bone resorption is the hallmark of destructive periodontitis and it is caused by the host response to bacteria and their mediators present on the biofilm. The balance between the expression levels of receptor activator of nuclear factorkappa B ligand (RANKL) and osteoprotegerin (OPG) is pivotal for osteoclast differentiation and activity and has been implicated in the progression of bone loss in periodontitis. To assess the contribution of resident cells to the bone resorption mediated by innate immune signaling, we stimulated fibroblasts and osteoblastic cells with LPS from. Escherichia coli (TLR4 agonist), Porphyromonas gingivalis (TLR2 and -4 agonist), and interleukin-1 beta (as a control for cytokine signaling through Toll/IL-1receptor domain) in time-response experiments. Expression of RANKL and OPG mRNA was studied by RT-PCR, whereas the production of RANKL protein and the activation of p38 MAPK and NF-kB signaling pathways were analyzed by western blot. We used biochemical inhibitors to assess the relative contribution of p38 MAPK and NF-kB signaling to the expression of RANKL and OPG induced by TLR2, -4 and IL1β in these cells. Both p38 MAPK and NFkB pathways were activated by these stimuli in fibroblasts and osteoblasts, but the kinetics of this activation varied in each cell type and with the nature of the stimulation. E. coli LPS was a stronger inducer of RANKL mRNA in fibroblasts, whereas LPS from P. gingivalis downregulated RANKL mRNA in periodontal ligament cells but increased its expression in osteoblasts. IL-1β induced RANKL in both cell types and without a marked effect on OPG expression. p38 MAPK was more relevant than NF-kB for the expression of RANKL and OPG in these cell types.

Electrophysiological properties of rostral ventrolateral medulla presympathetic neurons modulated by the respiratory network in rats

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

Antihypertensive therapy in preeclampsia is not modulated by VEGF polymorphisms

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

Feeding increasing concentrate to Tifton 85 hay ratios modulated rumen fermentation and microbiota in Nellore feedlot steers

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

The receptor-like kinase SlSOBIR1 is differentially modulated by virus infection but its overexpression in tobacco has no significant impact on virus accumulation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aplicações das Cadeias de Markov para o Ensino Médio

Pós-graduação em Matemática em Rede Nacional - IBILCE

Simulations of the Frequency Modulated Atomic Force Microscope (FM-AFM) nonlinear control system

The Frequency Modulated - Atomic Force Microscope (FM-AFM) is apowerful tool to perform surface investigation with true atomic resolution. The controlsystem of the FM-AFM must keep constant both the frequency and amplitude ofoscillation of the microcantilever during the scanning process of the sample. However,tip and sample interaction forces cause modulations in the microcantilever motion.A Phase-Locked Loop (PLL) is used as a demodulator and to generate feedback signalto the FM-AFM control system. The PLL performance is vital to the FM-AFMperformace since the image information is in the modulated microcantilever motion.Nevertheless, little attention is drawn to PLL performance in the FM-AFM literature.Here, the FM-AFM control system is simulated, comparing the performancefor di erent PLL designs.