Towards efficient modelling of optical micromanipulation of complex structures

Computational methods for electromagnetic and light scattering can be used for the calculation of optical forces and torques. Since typical particles that are optically trapped or manipulated are on the order of the wavelength in size, approximate methods such as geometric optics or Rayleigh scattering are inapplicable, and solution or either the Maxwell equations or the vector Helmholtz equation must be resorted to. Traditionally, such solutions were only feasible for the simplest geometries; modern computational power enable the rapid solution of more general--but still simple--geometries such as axisymmetric, homogeneous, and isotropic scatterers. However, optically-driven micromachines necessarily require more complex geometries, and their computational modelling thus remains in the realm of challenging computational problems. We review our progress towards efficient computational modelling of optical tweezers and micromanipulation, including the trapping and manipulation of complex structures such as optical micromachines. In particular, we consider the exploitation of symmetry in the modelling of such devices.Comment: 5 pages, 4 figure

Modelling optical micro-machines

A strongly focused laser beam can be used to trap, manipulate and exert torque on a microparticle. The torque is the result of transfer of angular momentum by scattering of the laser beam. The laser could be used to drive a rotor, impeller, cog wheel or some other microdevice of a few microns in size, perhaps fabricated from a birefringent material. We review our methods of computationally simulating the torque and force imparted by a laser beam. We introduce a method of hybridizing the T-matrix with the Finite Difference Frequency Domain (FDFD) method to allow the modelling of materials that are anisotropic and inhomogeneous, and structures that have complex shapes. The high degree of symmetry of a microrotor, such as discrete or continuous rotational symmetry, can be exploited to reduce computational time and memory requirements by orders of magnitude. This is achieved by performing calculations for only a given segment or plane that is repeated across the whole structure. This can be demonstrated by modelling the optical trapping and rotation of a cube.Comment: 4 pages, 3 figure

Efficacy of antiplatelet therapy in secondary prevention following lacunar stroke:Pooled analysis of randomized trials

Background and Purpose: Lacunar stroke accounts for ≈25% of ischemic stroke, but optimal antiplatelet regimen to prevent stroke recurrence remains unclear. We aimed to evaluate the efficacy of antiplatelet agents in secondary stroke prevention after a lacunar stroke. Methods: We searched MEDLINE, Embase, and the Cochrane library for randomized controlled trials that reported risk of recurrent stroke or death with antiplatelet therapy in patients with lacunar stroke. We used random effects meta-analysis and evaluated heterogeneity with I2. Results: We included 17 trials with 42 234 participants (mean age 64.4 years, 65% male) and follow up ranging from 4 weeks to 3.5 years. Compared with placebo, any single antiplatelet agent was associated with a significant reduction in recurrence of any stroke (risk ratio [RR] 0.77, 0.62–0.97, 2 studies) and ischemic stroke (RR 0.48, 0.30–0.78, 2 studies), but not for the composite outcome of any stroke, myocardial infarction, or death (RR 0.89, 0.75–1.05, 2 studies). When other antiplatelet agents (ticlodipine, cilostazol, and dipyridamole) were compared with aspirin, there was no consistent reduction in stroke recurrence (RR 0.91, 0.75–1.10, 3 studies). Dual antiplatelet therapy did not confer clear benefit over monotherapy (any stroke RR 0.83, 0.68–1.00, 3 studies; ischemic stroke RR 0.80, 0.62–1.02, 3 studies; composite outcome RR 0.90, 0.80–1.02, 3 studies). Conclusions: Our results suggest that any of the single antiplatelet agents compared with placebo in the included trials is adequate for secondary stroke prevention after lacunar stroke. Dual antiplatelet therapy should not be used for long-term stroke prevention in this stroke subtype

Transfer of K-types on local theta lifts of characters and unitary lowest weight modules

In this paper we study representations of the indefinite orthogonal group O(n,m) which are local theta lifts of one dimensional characters or unitary lowest weight modules of the double covers of the symplectic groups. We apply the transfer of K-types on these representations of O(n,m), and we study their effects on the dual pair correspondences. These results provide examples that the theta lifting is compatible with the transfer of K-types. Finally we will use these results to study subquotients of some cohomologically induced modules

A background-priority discrete boundary triangulation method

Discrete boundary triangulation methods generate triangular meshes through the centers of the boundary voxels of a volumetric object. At some voxel configurations it may be arbitrary whether a part of the volume should be included in the object or could be classified as background. Consequently, important details such as concave and convex edges and corners are not consistently preserved in the describing geometry. We present a "background priority" version of an existing "object priority" algorithm [6]. We show that the ad hoc configurations of the well-known Discretized Marching Cubes algorithm [13] can be derived from our method and that a combined triangulation with "object priority" and "background priority" better would preserve object details

Segmentação de dados 3D

Este artigo apresenta um algoritmo para efectuar uma segmentação não supervisionada em 3D, mostrando a sua aplicação a diferentes volumes, tais como: volumes artificiais, acústica submarina e de ressonância magnética (NMR- Nuclear Magnetic Resonance). O trabalho tem por base o efectuado em 2D e já apresentado numa anterior Tecnovisão [I]

Fast segmentation of 3D data using an octree

The algorithm developed uses an octree pyramid in which noise is reduced at the expense of the spatial resolution. At a certain level an unsupervised clustering without spatial connectivity constraints is applied. After the classification, isolated voxels and insignificant regions are removed by assigning them to their neighbours. The spatial resolution is then increased by the downprojection of the regions, level by level. At each level the uncertainty of the boundary voxels is minimised by a dynamic selection and classification of these, using an adaptive 3D filtering. The algorithm is tested using different data sets, including NMR data