Curvature matching and strain relief in bucky-tori: usage of sp3-hybridization and nonhexagonal rings

The relief of different types of curvature strain in bucky-tori of elemental carbon is considered in a general formal framework. This theory then is used to aid in the design of several structures, which are treated via molecular mechanics. Novel illustrations of the remnant strain are made, and some modest conclusions as to the nature of the structure of the experimentally observed bucky-tori are suggested.     

Packed capillary reversed-phase liquid chromatography with high-performance electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry for proteomics

In this study, high-efficiency packed capillary reversed-phase liquid chromatography (RPLC) coupled on-line with high-performance Fourier transform ion cyclotron resonance (FTICR) mass spectrometry has been investigated for the characterization of complex cellular proteolytic digests. Long capillary columns (80-cm) packed with small (3-micron) C18 bonded particles provided a total peak capacity of approximately 1000 for cellular proteolytic polypeptides when interfaced with an ESI-FTICR mass spectrometer under composition gradient conditions at a pressure of 10,000 psi. Large quantities of cellular proteolytic digests (e.g., 500 micrograms) could be loaded onto packed capillaries of 150-micron inner diameter without a significant loss of separation efficiency. Precolumns with suitable inner diameters were found useful for improving the elution reproducibility without a significant loss of separation quality. Porous particle packed capillaries were found to provide better results than those containing nonporous particles because of their higher sample capacity. Two-dimensional analyses from the combination of packed capillary RPLC with high-resolution FTICR yield a combined capacity for separations of > 1 million polypeptide components and simultaneously provided information for the identification of the separated components based upon the accurate mass tag concept previously described.     

Statistical two-dimensional correlation spectroscopy: its theory and applications to sets of vibrational spectra

The present study aims at developing a new form of two-dimensional (2D) correlation spectroscopy, statistical 2D correlation spectroscopy. Statistical 2D spectroscopy differs from the widely used generalized 2D correlation spectroscopy in that the former abstracts spectral features by pretreatment and by 2D maps that are limited by the correlation coefficients in the range from 1 to -1. In this paper, the theory of the new 2D method is briefly described, and then its applications are discussed to reveal spectral and concentration features of artificial model spectra, infrared spectra of polycondensation of bis(hydroxyethyl terephthalate) measured on-line, and short-wave near-infrared spectra of raw milk. The results are analyzed thoroughly and compared with those from generalized 2D correlation spectroscopy and partial least-squares loadings and scores. The most significant advantage of statistical 2D correlation spectroscopy is that the 2D correlation spectra are easy to calculate and are purely mathematical in nature, thereby eliminating any subjective involvement of an experimenter, while the inherent weakness of the method lies in its sensitivity to the noise.     

北京奥运安全倒计时

奥运会网络会运行三大系统：计时计分系统（Timing＆Scoring）、信息发布系统（IDS）以及运动会管理系统（GMS）。     

High Definition Digital Fabrication of Active Organic Devices by Molecular Jet Printing

We introduce a high resolution molecular jet (MoJet) printing technique for vacuum deposition of evaporated thin films and apply it to fabrication of 30 μm pixelated (800 ppi) molecular organic light emitting devices (OLEDs) based on aluminum tris(8‐hydroxyquinoline) (Alq₃) and fabrication of narrow channel (15 μm) organic field effect transistors (OFETs) with pentacene channel and silver contacts. Patterned printing of both organic and metal films is demonstrated, with the operating properties of MoJet‐printed OLEDs and OFETs shown to be comparable to the performance of devices fabricated by conventional evaporative deposition through a metal stencil. We show that the MoJet printing technique is reconfigurable for digital fabrication of arbitrary patterns with multiple material sets and high print accuracy (of better than 5 μm), and scalable to fabrication on large area substrates. Analogous to the concept of “drop‐on‐demand” in Inkjet printing technology, MoJet printing is a “flux‐on‐demand” process and we show it capable of fabricating multi‐layer stacked film structures, as needed for engineered organic devices.     

A multimodal hand-based verification system with an aliveness-detection module

This paper presents a multimodal biometrie verification system based on the following hand features: palmprint, four digitprints and four fingerprints. The features are obtained using the Karhunen-Loève transform based approach, and information fusion at the matching-score level was applied. We experimented with different resolutions of the regions of interest, different numbers of features and several normalization and fusion techniques at the matching-score level. To increase the reliability of the system to spoof attacks we included an aliveness-detection module based on thermal images of the hand dor sa. The verification performance when using a system configuration with optimum parameters, i.e., resolution, number of features, normalization and fusion technique, showed an equal error rate (EER) of 0.0020%, which makes the system appropriate for the implementation of high-security biometric systems.     

Discriminative functional analysis of human movements

This paper investigates the use of statistical dimensionality reduction (DR) techniques for discriminative low dimensional embedding to enable affective movement recognition. Human movements are defined by a collection of sequential observations (time-series features) representing body joint angle or joint Cartesian trajectories. In this work, these sequential observations are modelled as temporal functions using B-spline basis function expansion, and dimensionality reduction techniques are adapted to enable application to the functional observations. The DR techniques adapted here are: Fischer discriminant analysis (FDA), supervised principal component analysis (PCA), and Isomap. These functional DR techniques along with functional PCA are applied on affective human movement datasets and their performance is evaluated using leave-one-out cross validation with a one-nearest neighbour classifier in the corresponding low-dimensional subspaces. The results show that functional supervised PCA outperforms the other DR techniques examined in terms of classification accuracy and time resource requirements.     

INFERENCE PROCEDURES FOR FUZZY KNOWLEDGE REPRESENTATION SCHEME

This article presents a formal model of the knowledge representation scheme based on the fuzzy Petri net (FPN) theory. The model is represented as a 13-tuple consisting of the components of the FPN, two functions that give semantic meanings to the scheme and a set of contradictions. For the scheme, called the knowledge representation scheme based on the fuzzy Petri nets theory (KRFPN) the fuzzy inheritance and fuzzy recognition-inference procedures based on the dynamical properties of the FPN, are described in detail. The upper-time complexity of both the proposed inference algorithms is O(nm), where n is the number of places (concepts) and m is the number of transitions (relations) in the scheme. Illustrative examples of the fuzzy inheritance and the fuzzy recognition algorithms for the knowledge base, designed by the KRFPN, are given.