I predict VSP free-surface multiples and subtract them from VSP data, and then apply least squares migration (LSM) to the VSP data. The LSM image contains noticeably fewer artifacts associated with the aquisition footprints than the standard VSP image. The freesurface multiple artifact is considerably diminished in the demultipled data, and the migration image with demultiple VSP data has fewer...

We describe a method for measuring the lateral focal spot size of a multiphoton laser scanning microscope (LSM) with unprecedented accuracy. A specimen consisting of an aluminum film deposited on a glass coverslip was brought into focus in a LSM and the laser intensity was then increased enough to perform nanoablation of the metal film. This process leaves a permanent trace of the raster path u...

We study approaches to learning an exercise policy for American options directly from real data. We investigate an approximate policy iteration method, namely, least squares policy iteration (LSPI), for the problem of pricing American options. We also extend the standard least squares Monte Carlo (LSM) method of Longstaff and Schwartz, by composing sample paths from real data. We test the perfo...

In this paper, we present a novel weakly-supervised method for crosslingual sentiment analysis. In specific, we propose a latent sentiment model (LSM) based on latent Dirichlet allocation where sentiment labels are considered as topics. Prior information extracted from English sentiment lexicons through machine translation are incorporated into LSM model learning, where preferences on expectati...

Markov logic networks (MLNs) use first-order formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extreme computational costs, and thus are unable to represent complex regularities in data. To address this problem, we present LSM, the first MLN structure learner capable of efficiently and accurately learning long claus...

Evaluation of the extent and progression of liver fibrosis and cirrhosis is of critical importance in the management and prognosis of patients with chronic hepatitis B. Due to the limitation of liver biopsy, non-invasive methods, especially liver stiffness measurement (LSM) by vibration controlled transient elastography, have been developed and widely applied for liver fibrosis assessment. LSM ...

Background and Aims: Endothelial dysfunction is a hallmark of cardiovascular diseases. The straight region of an artery is protected from atherosclerosis via its laminar blood flow and high shear stress. This study investigated the cytoprotective effects of a new laminar shear medium (LSM) derived from a modified cone-and-plate shear device and identified basic fibroblast growth factor (bFGF) s...

The new myofilament Ca2+ sensitizer levosimendan (LSM) is a positive inotropic and vasodilatory agent. Its beneficial effects have been demonstrated at rest in congestive heart failure (CHF). However, its effect during exercise (Ex) in CHF is unknown. We assessed the effects of LSM on left ventricular (LV) dynamics at rest and during Ex in eight conscious, instrumented dogs with pacing-induced ...

A combined interpolation 3D Level Set Method (I+3DLSM) based segmentation process is presented. The performance in terms of accuracy of the 3-dimensional (3D) level set method (LSM) in the segmentation of throat regions from highly anisotropic magnetic resonance imaging (MRI) volumes, with and without an interpolation step is evaluated. Qualitative and quantitative results from real MRI data su...

We explore two different methods to predict the binding ability of nonapeptides at the class I major histocompatibility complex using a general linear scoring function that defines a separating hyperplane in the feature space of sequences. In absence of suitable data on non-binding nonapeptides we generated sequences randomly from a selected set of proteins from the protein data bank. The param...