980 resultados para Particle Level Set


Relevância:

30.00% 30.00%

Publicador:

Resumo:

The main purpose of this work is to report the presence of spurious discontinuities in the pattern of diurnal variation of sea level pressure of the three reanalysis datasets from: the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Science (R1), the NCEP and Department of Energy (R2), and the European Centre for Medium Range Weather Forecasting (ERA-40). Such discontinuities can be connected to the major changes in the global observing system that have occurred throughout reanalyses years. In the R1, the richest period in discontinuities is 1956-1958, coinciding with the start of modern radiosonde observation network. Rapid increase in the density of surface-based observations from 1967 also had an important impact on both R1 and ERA-40, with larger impact on R1. The reanalyses show discontinuities in the 1970s related to the assimilation of radiances measured by the Vertical Temperature Profile Radiometer and TIROS-N Operational Vertical Sounders onboard satellites. In the ERA-40, which additionally assimilated Special Sensor Microwave/Imager data, there are discontinuities in 1987-1989. The R1 also presents further discontinuities, in 1988-1993 likely connected to replacement/introduction of NOAA-series satellites with different biases, and to the volcanic eruption of Mount Pinatubo in June 1991, which is known to have severely affected measurements of infrared radiances for several years. The discontinuities in 1996-1998 might be partially connected to change in the type of radiosonde, from VIZ-B to VIZ-B2. The R2, which covers only satellite era (1979-on), shows discontinuities mainly in 1992, 1996-1997, and 2001. The discontinuities in 1992 and 2001 might have been caused by change in the satellite measurements and those in 1996-1997 by some changes in land-based observations network. © 2012 Springer-Verlag.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Results are presented from a search for a W' boson using a dataset corresponding to 5.0fb-1 of integrated luminosity collected during 2011 by the CMS experiment at the LHC in pp collisions at s=7TeV. The W' boson is modeled as a heavy W boson, but different scenarios for the couplings to fermions are considered, involving both left-handed and right-handed chiral projections of the fermions, as well as an arbitrary mixture of the two. The search is performed in the decay channel W'→tb, leading to a final state signature with a single electron or muon, missing transverse energy, and jets, at least one of which is identified as a b-jet. A W' boson that couples to the right-handed (left-handed) chiral projections of the fermions with the same coupling constants as the W is excluded for masses below 1.85 (1.51) TeV at the 95% confidence level. For the first time using LHC data, constraints on the W' gauge couplings for a set of left- and right-handed coupling combinations have been placed. These results represent a significant improvement over previously published limits. © 2012 CERN.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Low-level laser therapy (LLLT) has been used for the treatment of dentinal hypersensitivity. However, the specific LLL dose and the response mechanisms of these cells to transdentinal irradiation have not yet been demonstrated. Therefore, this study evaluated the transdentinal effects of different LLL doses on stressed odontoblast-like pulp cells MDPC-23 seeded onto the pulpal side of dentin discs obtained from human third molars. The discs were placed in devices simulating in vitro pulp chambers and the whole set was placed in 24-well plates containing plain culture medium (DMEM). After 24 h incubation, the culture medium was replaced by fresh DMEM supplemented with either 5% (simulating a nutritional stress condition) or 10% fetal bovine serum (FBS). The cells were irradiated with doses of 15 and 25 J cm-2 every 24 h, totaling three applications over three consecutive days. The cells in the control groups were removed from the incubator for the same times as used in their respective experimental groups for irradiation, though without activating the laser source (sham irradiation). After 72 h of the last active or sham irradiation, the cells were evaluated with respect to succinic dehydrogenase (SDH) enzyme production (MTT assay), total protein (TP) expression, alkaline phosphatase (ALP) synthesis, reverse transcriptase polymerase chain reaction (RT-PCR) for collagen type 1 (Col-I) and ALP, and morphology (SEM). For both tests, significantly higher values were obtained for the 25 J cm-2 dose. Regarding SDH production, supplementation of the culture medium with 5% FBS provided better results. For TP and ALP expression, the 25 J cm-2 presented higher values, especially for the 5% FBS concentration (Mann-Whitney p < 0.05). Under the tested conditions, near infrared laser irradiation at 25 J cm -2 caused transdentinal biostimulation of odontoblast-like MDPC-23 cells. © 2013 Astro Ltd.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

A search is performed for heavy resonances decaying to two long-lived massive neutral particles, each decaying to leptons. The experimental signature is a distinctive topology consisting of a pair of oppositely charged leptons originating at a separated secondary vertex. Events were collected by the CMS detector at the LHC during pp collisions at √s = 7 TeV, and selected from data samples corresponding to 4.1 (5.1) fb-1 of integrated luminosity in the electron (muon) channel. No significant excess is observed above standard model expectations, and an upper limit is set with 95% confidence level on the production cross section times the branching fraction to leptons, as a function of the long-lived massive neutral particle lifetime. Copyright CERN.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Neste estudo descreve-se as características da estrutura vertical de um episódio de Jatos de Baixos Níveis (JBN) ocorrido no litoral do Pará, utilizando-se para tal, dados das radiossondagens de Ajuruteua, Município de Bragança coletados durante o experimento DESMATA (Impacto do Desmatamento Junto ao Litoral Atlântico da Amazônia) realizado no período de 08 a 22 de abril de 2002. Dentre os casos detectados no período chuvoso, selecionou-se um que se manteve por 12 horas com velocidade média de 15m/s e que estava direcionado de Nordeste para Leste, no ponto de máxima velocidade. Os resultados observacionais indicaram que, este JBN localizado no litoral Paraense foi resultado da ação combinada de dois fatores: (1) oscilação inercial e (2) baroclinia superficial. Estes dois fatores combinados sustentaram este JBN com intensidades entre 10 e 13m/s durante o dia e entre 14 e 16m/s durante a noite, localizado a uma altitude média de 800m acima da superfície.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The largest losses in mechanical harvesting of peanuts occur during the stage of digging, and its assessment is still incipient in Brazil. Therefore, the aim of this study was to evaluate the quantitative losses and the performance of the tractor-digger-inverter, according to soil water content and plant populations. The experiment was conducted in a completely randomized block design with a factorial scheme 2 x 3, in which the treatments consisted of two soil, water content (19.3 and 24.8%) and three populations of plants (86,111, 127,603 and 141,144 plants ha-1), with four replications. The quantitative digging losses and the set mechanized performance were evaluated. The largest amount of visible and total losses was found in the population of 141.144 plants ha-1 for the 19.3% soil water content. The harvested material flow and the tractor-digger-inverter performance were not influenced by soil water content and plant population. The water content in the pods was higher in 24.8% soil water content only for the population of 86,111 plants ha-1; the yield was higher in the populations of 141.144 and 127.603 plants ha-1, in the 19.3 e 24.8% soil water content, respectively.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.