869 resultados para Search Nearest Neighbor
Resumo:
The LiHoxY1−xF4 Ising magnetic material subject to a magnetic field perpendicular to the Ho3+ Ising direction has shown over the past 20 years to be a host of very interesting thermodynamic and magnetic phenomena. Unfortunately, the availability of other magnetic materials other than LiHoxY1−xF4 that may be described by a transverse-field Ising model remains very much limited. It is in this context that we use here a mean-field theory to investigate the suitability of the Ho(OH)3, Dy(OH)3, and Tb(OH)3 insulating hexagonal dipolar Ising-type ferromagnets for the study of the quantum phase transition induced by a magnetic field, Bx, applied perpendicular to the Ising spin direction. Experimentally, the zero-field critical (Curie) temperatures are known to be Tc≈2.54, 3.48, and 3.72 K, for Ho(OH)3, Dy(OH)3, and Tb(OH)3, respectively. From our calculations we estimate the critical transverse field, Bxc, to destroy ferromagnetic order at zero temperature to be Bxc=4.35, 5.03, and 54.81 T for Ho(OH)3, Dy(OH)3, and Tb(OH)3, respectively. We find that Ho(OH)3, similarly to LiHoF4, can be quantitatively described by an effective S=1/2 transverse-field Ising model. This is not the case for Dy(OH)3 due to the strong admixing between the ground doublet and first excited doublet induced by the dipolar interactions. Furthermore, we find that the paramagnetic (PM) to ferromagnetic (FM) transition in Dy(OH)3 becomes first order for strong Bx and low temperatures. Hence, the PM to FM zero-temperature transition in Dy(OH)3 may be first order and not quantum critical. We investigate the effect of competing antiferromagnetic nearest-neighbor exchange and applied magnetic field, Bz, along the Ising spin direction ẑ on the first-order transition in Dy(OH)3. We conclude from these preliminary calculations that Ho(OH)3 and Dy(OH)3 and their Y3+ diamagnetically diluted variants, HoxY1−x(OH)3 and DyxY1−x(OH)3, are potentially interesting systems to study transverse-field-induced quantum fluctuations effects in hard axis (Ising-type) magnetic materials.
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Cell membranes are composed of two-dimensional bilayers of amphipathic lipids, which allow a lateral movement of the respective membrane components. These components are arranged in an inhomogeneous manner as transient micro- and nanodomains, which are believed to be crucially involved in the regulation of signal transduction pathways in mammalian cells. Because of their small size (diameter 10-200 nm), membrane nanodomains cannot be directly imaged using conventional light microscopy. Here, we present direct visualization of cell membrane nanodomains by helium ion microscopy (HIM). We show that HIM is capable to image biological specimens without any conductive coating, and that HIM images clearly allow the identification of nanodomains in the ultrastructure of membranes with 1.5 nm resolution. The shape of these nanodomains is preserved by fixation of the surrounding unsaturated fatty acids while saturated fatty acids inside the nanodomains are selectively removed. Atomic force microscopy, fluorescence microscopy, 3D structured illumination microscopy and direct stochastic optical reconstruction microscopy provide additional evidence that the structures in the HIM images of cell membranes originate from membrane nanodomains. The nanodomains observed by HIM have an average diameter of 20 nm and are densely arranged with a minimal nearest neighbor distance of ~15 nm.
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We study a symplectic chain with a non-local form of coupling by means of a standard map lattice where the interaction strength decreases with the lattice distance as a power-law, in Such a way that one can pass continuously from a local (nearest-neighbor) to a global (mean-field) type of coupling. We investigate the formation of map clusters, or spatially coherent structures generated by the system dynamics. Such clusters are found to be related to stickiness of chaotic phase-space trajectories near periodic island remnants, and also to the behavior of the diffusion coefficient. An approximate two-dimensional map is derived to explain some of the features of this connection. (C) 2008 Elsevier Ltd. All rights reserved.
Resumo:
We investigate the bilayer pre-transition exhibited by some lipids at temperatures below their main phase transition, and which is generally associated to the formation of periodic ripples in the membrane. Experimentally we focus on the anionic lipid dipalmytoylphosphatidylglycerol (DPPG) at different ionic strengths, and on the neutral lipid dipalmytoylphosphatidylcholine (DPPC). From the analysis of differential scanning calorimetry traces of the two lipids we find that both pre- and main transitions are part of the same melting process. Electron spin resonance of spin labels and excitation generalized polarization of Laurdan reveal the coexistence of gel and fluid domains at temperatures between the pre- and main transitions of both lipids, reinforcing the first finding. Also, the melting process of DPPG at low ionic strength is found to be less cooperative than that of DPPC. From the theoretical side, we introduce a statistical model in which a next-nearest-neighbor competing interaction is added to the usual two-state model. For the first time, modulated phases (ordered and disordered lipids periodically aligned) emerge between the gel and fluid phases as a natural consequence of the competition between lipid-lipid interactions. (C) 2009 Elsevier B.V. All rights reserved.
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(i) The electronic and structural properties of boron doped graphene sheets, and (ii) the chemisorption processes of hydrogen adatoms on the boron doped graphene sheets have been examined by ab initio total energy calculations. In (i) we find that the structural deformations are very localized around the boron substitutional sites, and in accordance with previous studies (Endo et al 2001 J. Appl. Phys. 90 5670) there is an increase of the electronic density of states near the Fermi level. Our simulated scanning tunneling microscope (STM) images, for occupied states, indicate the formation of bright (triangular) spots lying on the substitutional boron (center) and nearest-neighbor carbon (edge) sites. Those STM images are attributed to the increase of the density of states within an energy interval of 0.5 eV below the Fermi level. For a boron concentration of similar to 2.4%, we find that two boron atoms lying on the opposite sites of the same hexagonal ring (B1-B2 configuration) represents the energetically most stable configuration, which is in contrast with previous theoretical findings. Having determined the energetically most stable configuration for substitutional boron atoms on graphene sheets, we next considered the hydrogen adsorption process as a function of the boron concentration, (ii). Our calculated binding energies indicate that the C-H bonds are strengthened near boron substitutional sites. Indeed, the binding energy of hydrogen adatoms forming a dimer-like structure on the boron doped B1-B2 graphene sheet is higher than the binding energy of an isolated H(2) molecule. Since the formation of the H dimer-like structure may represent the initial stage of the hydrogen clustering process on graphene sheets, we can infer that the formation of H clusters is quite likely not only on clean graphene sheets, which is in consonance with previous studies (Hornekaer et al 2006 Phys. Rev. Lett. 97 186102), but also on B1-B2 boron doped graphene sheets. However, for a low concentration of boron atoms, the formation of H dimer structures is not expected to occur near a single substitutional boron site. That is, the formation (or not) of H clusters on graphene sheets can be tuned by the concentration of substitutional boron atoms.
Resumo:
The growth and magnetic properties of Tin Selenide (SnSe) doped with Eu(2+) Sn(1-x)Eu(x)Se (x=2.5%) were investigated. Q-band (34 GHz) electron paramagnetic resonance measurements show that the site symmetry of Eu(2+) at 4.2 K is orthorhombic and the Lande factor was determined to be g=1.99 +/- 0.01. The exchange coupling between nearest-neighbor (NN) Eu(2+) ions was estimated from magnetization and magnetic-susceptibility measurements using a model that takes into account the magnetic contributions of single ions, pairs and triplets. The exchange interaction between Eu(2+) nearest neighbors was found to be antiferromagnetic with an estimated average value of J(p)/k(B) =-0.18 +/- 0.03 K. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Impurity-interstitial dipoles in calcium fluoride solutions with Al3+, Yb3+ and La3+ fluorides were studied using the thermally stimulated depolarization current (TSDC) technique. The dipolar complexes are formed by substitutional trivalent ions in Ca2+ sites and interstitial fluorine in nearest neighbor sites. The relaxations observed at 150 K are assigned to dipoles nnR(S)(3+)- F-i(-) (R-S = La or Yb). The purpose of this work is to study the processes of energy storage in the fluorides following X-ray and gamma irradiation. Computer modelling techniques are used to obtain the formation energy of dipole defects. (C) 2007 Elsevier Ltd. All rights reserved.
Resumo:
We consider a random walks system on Z in which each active particle performs a nearest-neighbor random walk and activates all inactive particles it encounters. The movement of an active particle stops when it reaches a certain number of jumps without activating any particle. We prove that if the process relies on efficient particles (i.e. those particles with a small probability of jumping to the left) being placed strategically on Z, then it might survive, having active particles at any time with positive probability. On the other hand, we may construct a process that dies out eventually almost surely, even if it relies on efficient particles. That is, we discuss what happens if particles are initially placed very far away from each other or if their probability of jumping to the right tends to I but not fast enough.
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Transport coefficients have been measured as a function of the concentration of sulfur dioxide, SO(2), dissolved in 1-butyl-2,3-dimethylimidazolium bis(trifluoromethylsulfonyl)-imide, [BMMI][Tf(2)N], as well as in its lithium salt solution, Li[Tf(2)N]. The SO(2) reduces viscosity and density and increases conductivity and diffusion coefficients in both the neat [BMMI] [Tf(2)N] and the [BMMI][Tf(2)N]-Li[Tf(2)N] solution. The conductivity enhancement is not assigned to a simple viscosity effect; the weakening of ionic interactions upon SO(2) addition also plays a role. Microscopic details of the SO(2) effect were unraveled using Raman spectroscopy and molecular dynamics (MD) simulations. The Raman spectra suggest that the Li(+)-[Tf(2)N] interaction is barely affected by SO(2), and the SO(2)-[Tf(2)N] interaction is weaker than previously observed in an investigation of an ionic liquid containing the bromide anion. Transport coefficients calculated by MD simulations show the same trend as the experimental data with respect to SO(2) content. The MD simulations provide structural information on SO(2) molecules around [Tf(2)N], in particular the interaction of the sulfur atom of SO(2) with oxygen and fluorine atoms of the anion. The SO(2)-[BMMI] interaction is also important because the [BMMI] cations with above-average mobility have a larger number of nearest-neighbor SO(2) molecules.
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This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.
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Objective: To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT). Background: The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced. Methods: A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT. The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged. Results: A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments. Conclusions: The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings
O impacto do trabalho infantil sobre o desempenho escolar: uma avaliação para o Brasil metropolitano
Resumo:
O objetivo deste trabalho é avaliar o seguinte contra factual: como teria sido o desempenho escolar das crianças que trabalham, caso tivessem sido efetivamente proibidas de trabalhar? Uma vez que não é possível observar as crianças que trabalham na situação de não-trabalho, a estratégia adotada consistiu em. construir um grupo de controle através do matching do propensity score (nearest-neighbor matching). Os dados utilizados neste estudo foram obtidos a partir de uma amostra da PME (Pesquisa Mensal de Emprego) para seis regiões metropolitanas do Brasil - constituída por crianças com idade entre 1 O e 14 anos acompanhadas por dois anos consecutivos ao longo do período de 1984 à 1997. Os resultados obtidos apontam para um impacto negativo do trabalho sobre o desempenho escolar das crianças que trabalham - embora em intensidade diferenciada segundo o indicador de desempenho utilizado. As estimativas para probabilidade de aprovação e para o progresso escolar sugerem um efeito negativo do trabalho, porém bem menor do que é geralmente observado. O que não ocorre com para a probabilidade de evasão - o trabalho explica quase a totalidade da diferença observada na probabilidade de evasão entre as crianças que trabalham e as demais. Os resultados sugerem, portanto, que se a legislação que proíbe o trabalho infantil fosse rigorosamente cumprida as crianças que trabalham apresentariam em média um melhor desempenho escolar
Resumo:
The pair contact process - PCP is a nonequilibrium stochastic model which, like the basic contact process - CP, exhibits a phase transition to an absorbing state. While the absorbing state CP corresponds to a unique configuration (empty lattice), the PCP process infinitely many. Numerical and theoretical studies, nevertheless, indicate that the PCP belongs to the same universality class as the CP (direct percolation class), but with anomalies in the critical spreading dynamics. An infinite number of absorbing configurations arise in the PCP because all process (creation and annihilation) require a nearest-neighbor pair of particles. The diffusive pair contact process - PCPD) was proposed by Grassberger in 1982. But the interest in the problem follows its rediscovery by the Langevin description. On the basis of numerical results and renormalization group arguments, Carlon, Henkel and Schollwöck (2001), suggested that certain critical exponents in the PCPD had values similar to those of the party-conserving - PC class. On the other hand, Hinrichsen (2001), reported simulation results inconsistent with the PC class, and proposed that the PCPD belongs to a new universality class. The controversy regarding the universality of the PCPD remains unresolved. In the PCPD, a nearest-neighbor pair of particles is necessary for the process of creation and annihilation, but the particles to diffuse individually. In this work we study the PCPD with diffusion of pair, in which isolated particles cannot move; a nearest-neighbor pair diffuses as a unit. Using quasistationary simulation, we determined with good precision the critical point and critical exponents for three values of the diffusive probability: D=0.5 and D=0.1. For D=0.5: PC=0.89007(3), β/v=0.252(9), z=1.573(1), =1.10(2), m=1.1758(24). For D=0.1: PC=0.9172(1), β/v=0.252(9), z=1.579(11), =1.11(4), m=1.173(4)
Resumo:
Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
Resumo:
Digital Elevation Models (DEM) are numerical representations of a portion of the earth surface. Among several factors which affect the quality of a DEM, it should be emphasized the attention on the input data and the choice of the interpolating algorithm. On the other hand, several numerical models are used nowadays to characterize nearshore hydrodynamics and morphological changes in coastal areas, whose validation is based on field data collection. Independent on the complexity of the physical processes which are modeled, little attention has been given to the intrinsic bathymetric interpolation built within the numerical models of the specific application. Therefore, this study aims to investigate and to quantify the influence of the bathymetry, as obtained by a DEM, on the hydrodynamic circulation model at a coastal stretch, off the coast of the State of Rio Grande do Norte, Northeast Brazil. This coastal region is characterized by strong hydrodynamic and littoral processes, resulting in a very dynamic morphology with shallow coastal bathymetry. Important economic activities, such as oil exploitation and production, fisheries, salt ponds, shrimp farms and tourism, also bring impacts upon the local ecosystems and influence themselves the local hydrodynamics. This fact makes the region one of the most important for the development of the State, but also enhances the possibility of serious environmental accidents. As a hydrodynamic model, SisBaHiA® - Environmental Hydrodynamics System ( Sistema Básico de Hidrodinâmica Ambiental ) was chosen, for it has been successfully employed at several locations along the Brazilian coast. This model was developed at the Coastal and Oceanographical Engineering Group of the Ocean Engineering Program at the Federal University of Rio de Janeiro. Several interpolating methods were tested for the construction of the DEM, namely Natural Neighbor, Kriging, Triangulation with Linear Interpolation, Inverse Distance to a Power, Nearest Neighbor, and Minimum Curvature, all implemented within the software Surfer®. The bathymetry which was used as reference for the DEM was obtained from nautical charts provided by the Brazilian Hydrographic Service of the Brazilian Navy and from a field survey conducted in 2005. Changes in flow velocity and free surface elevation were evaluated under three aspects: a spatial vision along three profiles perpendicular to the coast and one profile longitudinal to the coast as shown; a temporal vision from three central nodes of the grid during 30 days; a hodograph analysis of components of speed in U and V, by different tidal cycles. Small, but negligible, variations in sea surface elevation were identified. However, the differences in flow and direction of velocities were significant, depending on the DEM