Objective(s): Lipid-based nanoparticles (NLP) are PEGylated carriers composed of lipids and encapsulated nucleic acids with a diameter less than 100 nm. The presence of PEG in the NLP formulation improves the particle pharmacokinetic behavior. The purpose of this study was to prepare and characterize NLPs containing MDR1 siRNA and evaluate their cytotoxicity and cellular uptake. MDR1 siRNA coul...

OBJECTIVES This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large healthcare systems. Effectiveness is evaluated on how well NLP supports downstream influenza case-detection for disease surveillance. METHODS We independently developed two NLP parsers, one at Intermountain ...

The use of small aerial vehicles (SAVs) such as quadrotors for inspection and surveillance applications both indoors and out is well established, but motion planning techniques are needed which can be calculated in real-time and which result in provably safe vehicle motion in tightly constrained 3D environments. Applied to small quadrotor helicopters, our planning algorithm combines Probabilist...

In this paper, we discuss the solution of linear and quadratic eigenvalue complementarity problems (EiCPs) using an enumerative algorithm of the type introduced by Júdice et al. [1]. Procedures for computing the interval that contains all the eigenvalues of the linear EiCP are first presented. A nonlinear programming (NLP) model for the quadratic EiCP is formulated next, and a necessary and suf...

The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed point-to-point demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs at a specified arc dependent cost. The problem is to determine the number of facilities to be loa...

much attention has recently been paid to natural language processing in information storage and retrieval. this paper describes how the application of natural language processing ( nlp ) techniques can enhance cross-language information retrieval ( clir ). using a semi-experimental technique, we took farsi queries to retrieve relevant documents in english. for translating persian queries, we us...

This project aims at applying neural network-based deep learning to the problem of extractive text summarization. Our work is inspired by the work of Collobert and Weston [Collobert et al., 2011], who created a unified deep learning architecture to learn several common NLP tasks. In this report, we give the motivation behind our work, describe our problem formulation and present some results.

We present a discrete optimization model based on a linear programming formulation as an alternative to the cascade of classifiers implemented in many language processing systems. Since NLP tasks are correlated with one another, sequential processing does not guarantee optimal solutions. We apply our model in an NLG application and show that it performs better than a pipeline-based system.

We study the problem of packing equal circles in a square from the mathematical programming point of view. We discuss different formulations, we analyse formulation symmetries, we propose some symmetry breaking constraints and show that not only do they tighten the convex relaxation bound, but they also ease the task of local NLP solution algorithms in finding feasible solutions. We solve the p...