Substituent-mediated quantum interference toward a giant single-molecule conductance variation.

Quantum interference (QI) in single molecular junctions shows a promising perspective for realizing conceptual nanoelectronics. However, controlling and modulating the QI remains a big challenge. Herein, two-type substituents at different positions ofmeta-linked benzene, namely electron-donating methoxy (-OMe) and electron-withdrawing nitryl (-NO2), are designed and synthesized to investigate the substituent effects on QI. The calculated transmission coefficientsT(E) indicates that -OMe and -NO2could remove the antiresonance and destructive quantum interference (DQI)-induced transmission dips at position 2. -OMe could raise the antiresonance energy at position 4 while -NO2groups removes the DQI features. For substituents at position 5, both of them are nonactive for tuning QI. The conductance measurements by scanning tunneling microscopy break junction show a good agreement with the theoretical prediction. More than two order of magnitude single-molecule conductance on/off ratio could be achieved at the different positions of -NO2substituent groups at room temperature. The present work proves chemical substituents can be used for tuning QI features in single molecular junctions, which provides a feasible way toward realization of high-performance molecular devices.

Tracking by parts: a bayesian approach with component collaboration.

Instead of using global-appearance information for visual tracking, as adopted by many methods, we propose a tracking-by-parts (TBP) approach that uses partial appearance information for the task. The proposed method considers the collaborations between parts and derives a probability propagation framework by encoding the spatial coherence in a Bayesian formulation. To resolve this formulation, a TBP particle-filtering method is introduced. Unlike existing methods that only use the spatial-coherence relationship for particle-weight estimation, our method further applies this relationship for state prediction based on system dynamics. Thus, the part-based information can be utilized efficiently, and the tracking performance can be improved. Experimental results show that our approach outperforms the factored-likelihood and particle reweight methods, which only use spatial coherence for weight estimation.

Visual tracking in high-dimensional state space by appearance-guided particle filtering.

In this paper, we propose a new approach, appearance-guided particle filtering (AGPF), for high degree-of-freedom visual tracking from an image sequence. This method adopts some known attractors in the state space and integrates both appearance and motion-transition information for visual tracking. A probability propagation model based on these two types of information is derived from a Bayesian formulation, and a particle filtering framework is developed to realize it. Experimental results demonstrate that the proposed method is effective for high degree-of-freedom visual tracking problems, such as articulated hand tracking and lip-contour tracking.

On pose recovery for generalized visual sensors.

With the advances in imaging technologies for robot or machine vision, new imaging devices are being developed for robot navigation or image-based rendering. However, to satisfy some design criterion, such as image resolution or viewing ranges, these devices are not necessarily being designed to follow the perspective rule and, thus, the imaging rays may not pass through a common point. Such generalized imaging devices may not be perspective and, therefore, their poses cannot be estimated with traditional techniques. In this paper, we propose a systematic method for pose estimation of such a generalized imaging device. We formulate it as a nonperspective n point (NPnP) problem. The case with exact solutions, n=3, is investigated comprehensively. Approximate solutions can be found for n>3 in a least-squared-error manner by combining an initial-pose-estimation procedure and an orthogonally iterative procedure. This proposed method can be applied not only to nonperspective imaging devices but also perspective ones. Results from experiments show that our approach can solve the NPnP problem accurately.

Effect and mechanism of bishudiwan(BSDW) against allergy / 中国中药杂志

<p><b>OBJECTIVE</b>To investigate the effect and mechanism of BSDW on the model of allergic rhinitis and the model of guinea pigs by histamine shocking in guinea pigs.</p><p><b>METHOD</b>Using the model of allergic rhinitis in guinea pigs caused by 10% TDI, we observed the effect of BSDW on physiological and pathological symptoms of allergic rhinitis in guinea pigs, the effect of the levels of serum IgE and serum and nasal histamine. Using the model of guinea pigs by histamine shocking, we observed the effect of BSDW on physiological symptoms in guinea pigs.</p><p><b>RESULT</b>BSDW significantly relieved the pathological symptoms of allergic rhinitis in guinea pigs, alleviated the hyperplasia of columnar epithelium, decreased the number of monocyte and eosinocyte compared with the model group. It also reduced the levels of serum IgE, and decreased the release of serum and nasal histamine. BSDW significantly prolonged the occurent time of gasping, eclampsia and death caused by shock, reduced the times of gasping in the model of guinea pigs by histamine shocking.</p><p><b>CONCLUSION</b>BSDW has significant effect against allergy. The mechanism relates to its effects of decreasing the levels of serum IgE and inhibiting the release of serum and nasal histamine.</p>