Surface morphology and phase transformations of femtosecond laser-processed saphire

The morphological and structural modifications induced in sapphire by surface treatment with femtosecond laser radiation were studied. Single-crystal sapphire wafers cut parallel to the (0 1 2) planes were treated with 560 fs, 1030 nm wavelength laser radiation using wide ranges of pulse energy and repetition rate. Self-ordered periodic structures with an average spatial periodicity of similar to 300 nm were observed for fluences slightly higher than the ablation threshold. For higher fluences the interaction was more disruptive and extensive fracture, exfoliation, and ejection of ablation debris occurred. Four types of particles were found in the ablation debris: (a) spherical nanoparticles about 50 nm in diameter; (b) composite particles between 150 and 400 nm in size; (c) rounded resolidified particles about 100-500 nm in size; and (d) angular particles presenting a lamellar structure and deformation twins. The study of those particles by selected area electron diffraction showed that the spherical nanoparticles and the composite particles are amorphous, while the resolidified droplets and the angular particles, present a crystalline a-alumina structure, the same of the original material. Taking into consideration the existing ablation theories, it is proposed that the spherical nanoparticles are directly emitted from the surface in the ablation plume, while resolidified droplets are emitted as a result of the ablation process, in the liquid phase, in the low intensity regime, and by exfoliation, in the high intensity regime. Nanoparticle clusters are formed by nanoparticle coalescence in the cooling ablation plume. (C) 2013 Elsevier B.V. All rights reserved.

Quantitative description of the self-assembly of patchy particles into chains and rings

We numerically study a simple fluid composed of particles having a hard-core repulsion complemented by two patchy attractive sites on the particle poles. An appropriate choice of the patch angular width allows for the formation of ring structures which, at low temperatures and low densities, compete with the growth of linear aggregates. The simplicity of the model makes it possible to compare simulation results and theoretical predictions based on the Wertheim perturbation theory, specialized to the case in which ring formation is allowed. Such a comparison offers a unique framework for establishing the quality of the analytic predictions. We find that the Wertheim theory describes remarkably well the simulation results.

Probabilistic consensus clustering using evidence accumulation

Clustering ensemble methods produce a consensus partition of a set of data points by combining the results of a collection of base clustering algorithms. In the evidence accumulation clustering (EAC) paradigm, the clustering ensemble is transformed into a pairwise co-association matrix, thus avoiding the label correspondence problem, which is intrinsic to other clustering ensemble schemes. In this paper, we propose a consensus clustering approach based on the EAC paradigm, which is not limited to crisp partitions and fully exploits the nature of the co-association matrix. Our solution determines probabilistic assignments of data points to clusters by minimizing a Bregman divergence between the observed co-association frequencies and the corresponding co-occurrence probabilities expressed as functions of the unknown assignments. We additionally propose an optimization algorithm to find a solution under any double-convex Bregman divergence. Experiments on both synthetic and real benchmark data show the effectiveness of the proposed approach.

Rheology of the cytoskeleton as a fractal network

We model the cytoskeleton as a fractal network by identifying each segment with a simple Kelvin-Voigt element with a well defined equilibrium length. The final structure retains the elastic characteristics of a solid or a gel, which may support stress, without relaxing. By considering a very simple regular self-similar structure of segments in series and in parallel, in one, two, or three dimensions, we are able to express the viscoelasticity of the network as an effective generalized Kelvin-Voigt model with a power law spectrum of retardation times L similar to tau(alpha). We relate the parameter alpha with the fractal dimension of the gel. In some regimes ( 0 < alpha < 1), we recover the weak power law behaviors of the elastic and viscous moduli with the angular frequencies G' similar to G" similar to w(alpha) that occur in a variety of soft materials, including living cells. In other regimes, we find different power laws for G' and G".

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.