Quantum nonlocality test for continuous-variable states with dichotomic observables

There have been theoretical and experimental studies on quantum nonlocality for continuous variables, based on dichotomic observables. In particular, we are interested in two cases of dichotomic observables for the light field of continuous variables: One case is even and odd numbers of photons and the other case is no photon and the presence of photons. We analyze various observables to give the maximum violation of Bell's inequalities for continuous-variable states. We discuss an observable which gives the violation of Bell's inequality for any entangled pure continuous-variable state. However, it does not have to be a maximally entangled state to give the maximal violation of Bell's inequality. This is attributed to a generic problem of testing the quantum nonlocality of an infinite- dimensional state using a dichotomic observable.

Experimentally realizable characterizations of continuous- variable Gaussian states

Measures of entanglement, fidelity, and purity are basic yardsticks in quantum-information processing. We propose how to implement these measures using linear devices and homodyne detectors for continuous-variable Gaussian states. In particular, the test of entanglement becomes simple with some prior knowledge that is relevant to current experiments.

Simple models of complex aggregation: Vesicle formation by soft repulsive spheres with dipolelike interactions

Structural and thermodynamic properties of spherical particles carrying classical spins are investigated by Monte Carlo simulations. The potential energy is the sum of short range, purely repulsive pair contributions, and spin-spin interactions. These last are of the dipole-dipole form, with however, a crucial change of sign. At low density and high temperature the system is a homogeneous fluid of weakly interacting particles and short range spin correlations. With decreasing temperature particles condense into an equilibrium population of free floating vesicles. The comparison with the electrostatic case, giving rise to predominantly one-dimensional aggregates under similar conditions, is discussed. In both cases condensation is a continuous transformation, provided the isotropic part of the interatomic potential is purely repulsive. At low temperature the model allows us to investigate thermal and mechanical properties of membranes. At intermediate temperatures it provides a simple model to investigate equilibrium polymerization in a system giving rise to predominantly two-dimensional aggregates.

Accumulation of entanglement in a continuous variable memory

We study entanglement accumulation in a memory built out of two continuous variable systems interacting with a qubit that mediates their indirect coupling. We show that, in contrast with the case of bidimensional Hilbert spaces, entanglement superior to one ebit can be accumulated in the memory, even though no entangled resource is used. The protocol is immediately implementable and we assess the role of the main imperfections.

Enhanced surface attachment of protein-type targeting ligands to poly(lactide-co-glycolide) nanoparticles using variable expression of polymeric acid functionality

The density of reactive carboxyl groups on the surface of poly(lactide-co-glycolide) (PLGA) nanoparticles (NP) was modulated using a combination of high-molecular weight (MW) encapped and low MW non-encapped PLGA. Carboxyl groups were activated using carbodiimide chemistry and conjugated to bovine serum albumin and a model polyclonal antibody. Activation of carboxyl,groups in solution-phase PLGA prior to NP formation was compared with a postformation activation of peripheral carboxyl groups on intact NP. Activation before or after NP formation did not influence conjugation efficiency to NP prepared using 100% of the low-MW PLGA. The effect of steric stabilization using poly(vinyl alcohol) reduced conjugation of a polyclonal antibody from 62 mu g/(mg NP) to 32 mu g/(mg NP), but enhanced particulate stability. Increasing the amount of a high-MW PLGA also reduced Conjugation, with the activation post-formation still superior to the preformation approach. Drug release studies showed that high proportions of high-MW PLGA in the NP produced a longer sustained release profile of a model drug (celecoxib). It can be concluded that activating intact PLGA NP is superior to activating component parts prior to NP formation. Also, high MW PLGA could be used to prolong drug release, but at the expense of conjugation efficiency on to the NP surface. (C) 2008 Wiley Periodicals, Inc. J Biomed Mater Res 87A: 873-884, 2008

Protein aggregation in the brain: the molecular basis for Alzheimer's and Parkinson's diseases.

Developing effective treatments for neurodegenerative diseases is one of the greatest medical challenges of the 21st century. Although many of these clinical entities have been recognized for more than a hundred years, it is only during the past twenty years that the molecular events that precipitate disease have begun to be understood. Protein aggregation is a common feature of many neurodegenerative diseases, and it is assumed that the aggregation process plays a central role in pathogenesis. In this process, one molecule (monomer) of a soluble protein interacts with other monomers of the same protein to form dimers, oligomers, and polymers. Conformation changes in three-dimensional structure of the protein, especially the formation of beta-strands, often accompany the process. Eventually, as the size of the aggregates increases, they may precipitate as insoluble amyloid fibrils, in which the structure is stabilized by the beta-strands interacting within a beta-sheet. In this review, we discuss this theme as it relates to the two most common neurodegenerative conditions-Alzheimer's and Parkinson's diseases.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.