Systematic errors and combination of individual CRF solutions in the framework of the international pilot project for the next ICRF

A new international Pilot Project for the re-determination of the ICRF was initiated by the International VLBI Service for Geodesy and Astrometry (IVS) in January 2005. The purpose of this project is to compare the individual CRF solutions and to analyze their systematic and random errors with focus on the selection of the optimal strategy for the next ICRF realization. Eight radio source catalogues provided by the IVS Analysis Centers GA, SHAO, DGFI, GIUB-BKG, JPL, MAO NANU, GSFC, USNO were analyzed. In present study, four analytical models were used to investigate the systematic differences between solutions: solid rotation, rotation and deformation (IERS method), and expansion in orthogonal functions: Legendre-Fourier polynomials and spherical functions. It was found that expansions by orthogonal function describe the differences between individual catalogues better than the two former models. Finally, the combined CRF was generated. Using the radio source positions from this combined catalogue for estimation of EOP has shown improvement of the uncertainty of the celestial pole offset time series.Comment: 9 pages, 8 figures. Presented at the XXVIth IAU General Assembly, JD16, Prague, Czech Republic, 14-25 August 200

Applying mesh conformation on shape analysis with missing data

A mesh conformation approach that makes use of deformable generic meshes has been applied to establishing correspondences between 3D shapes with missing data. Given a group of shapes with correspondences, we can build up a statistical shape model by applying principal component analysis (PCA). The conformation at first globally maps the generic mesh to the 3D shape based on manually located corresponding landmarks, and then locally deforms the generic mesh to clone the 3D shape. The local deformation is constrained by minimizing the energy of an elastic model. An algorithm was also embedded in the conformation process to fill missing surface data of the shapes. Using synthetic data, we demonstrate that the conformation preserves the configuration of the generic mesh and hence it helps to establish good correspondences for shape analysis. Case studies of the principal component analysis of shapes were presented to illustrate the successes and advantages of our approach

Structural adjustments and international trade: theory and evidence from China

This paper studies how changes in factor endowment, technology, and trade costs jointly determine the structural adjustments, which are defined as changes in distributions of production and exports. We document the structural adjustments in Chinese manufacturing firms from 1999 to 2007 and find that production became more capital-intensive while exports did not. We structurally estimate a Ricardian and Heckscher-Ohlin model with heterogeneous firms to explain this seemingly puzzling pattern. Counterfactual simulations show that capital deepening made Chinese production more capital-intensive, but technology changes that biased toward the labor-intensive sectors and trade liberalizations provided a counterbalancing forc

Possible approach to improve sensitivity of a Michelson interferometer

We propose a possible approach to achieve an 1/N sensitivity of Michelson interferometer by using a properly designed random phase modulation. Different from other approaches, the sensitivity improvement does not depend on increasing optical powers or utilizing the quantum properties of light. Moreover the requirements for optical losses and the quantum efficiencies of photodetection systems might be lower than the quantum approaches and the sensitivity improvement is frequency independent in all detection band.Comment: 8 pages, 3 figures, new versio

Dielectric properties of nanosilica/low-density polyethylene composites: The surface chemistry of nanoparticles and deep traps induced by nanoparticles

Four kinds of nanosilica particles with different surface modification were employed to fabricate low-density polyethylene (LDPE) composites using melt mixing and hot molding methods. The surface chemistry of modified nanosilica was analyzed by X-ray photoelectron spectroscopy. All silica nanoparticles were found to suppress the space charge injection and accumulation, increase the volume resistivity, decrease the permittivity and dielectric loss factor at low frequencies, and decrease the dielectric breakdown strength of the LDPE polymers. The modified nanoparticles, in general, showed better dielectric properties than the unmodified ones. It was found that the carrier mobility, calculated from J–V curves using the Mott-Gurney equation, was much lower for the nanocomposites than for the neat LDPE

Temperature sensitivity of a two-mode photonic crystal fiber interferometric sensor

Author name used in this publication: M. S. Demokan2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Transition of lithium growth mechanisms in liquid electrolytes

Next-generation high-energy batteries will require a rechargeable lithium metal anode, but lithium dendrites tend to form during recharging, causing short-circuit risk and capacity loss, by mechanisms that still remain elusive. Here, we visualize lithium growth in a glass capillary cell and demonstrate a change of mechanism from root-growing mossy lithium to tip-growing dendritic lithium at the onset of electrolyte diffusion limitation. In sandwich cells, we further demonstrate that mossy lithium can be blocked by nanoporous ceramic separators, while dendritic lithium can easily penetrate nanopores and short the cell. Our results imply a fundamental design constraint for metal batteries (“Sand's capacity”), which can be increased by using concentrated electrolytes with stiff, permeable, nanoporous separators for improved safety.MIT Energy Initiative (Robert Bosch GmbH)National Science Foundation (U.S.) (Grant DMR-1410636)Stanford University. Global Climate and Energy ProjectUnited States. Dept. of Energy. Office of Basic Energy Sciences (Stanford University. SUNCAT Center for Interface Science and Catalysis

Nonparallel support vector machines for pattern classification

We propose a novel nonparallel classifier, called nonparallel support vector machine (NPSVM), for binary classification. Our NPSVM that is fully different from the existing nonparallel classifiers, such as the generalized eigenvalue proximal support vector machine (GEPSVM) and the twin support vector machine (TWSVM), has several incomparable advantages: 1) two primal problems are constructed implementing the structural risk minimization principle; 2) the dual problems of these two primal problems have the same advantages as that of the standard SVMs, so that the kernel trick can be applied directly, while existing TWSVMs have to construct another two primal problems for nonlinear cases based on the approximate kernel-generated surfaces, furthermore, their nonlinear problems cannot degenerate to the linear case even the linear kernel is used; 3) the dual problems have the same elegant formulation with that of standard SVMs and can certainly be solved efficiently by sequential minimization optimization algorithm, while existing GEPSVM or TWSVMs are not suitable for large scale problems; 4) it has the inherent sparseness as standard SVMs; 5) existing TWSVMs are only the special cases of the NPSVM when the parameters of which are appropriately chosen. Experimental results on lots of datasets show the effectiveness of our method in both sparseness and classification accuracy, and therefore, confirm the above conclusion further. In some sense, our NPSVM is a new starting point of nonparallel classifiers