Manipulating dc currents with bilayer bulk natural materials

The principle of transformation optics has been applied to various wave phenomena (e.g., optics, electromagnetics, acoustics and thermodynamics). Recently, metamaterial devices manipulating dc currents have received increasing attention which usually adopted the analogue of transformation optics using complicated resistor networks to mimic the inhomogeneous and anisotropic conductivities. We propose a distinct and general principle of manipulating dc currents by directly solving electric conduction equations, which only needs to utilize two layers of bulk natural materials. We experimentally demonstrate dc bilayer cloak and fan-shaped concentrator, derived from the generalized account for cloaking sensor. The proposed schemes have been validated as exact devices and this opens a facile way towards complete spatial control of dc currents. The proposed schemes may have vast potentials in various applications not only in dc, but also in other fields of manipulating magnetic field, thermal heat, elastic mechanics, and matter waves

Accurate Object Recognition with Assembling Appearance and Motion Information

How to effectively detect object and accurately give out its visible parts is a major challenge for object detection. In this paper we propose an explicit occlusion model through integrating appearance and motion information. The model combines together two parts: part-level object detection with single frame and object occlusion estimation with continuous frames. It breaks through the performance bottleneck caused by lack of information and effectively improves object detection rate under severe occlusion. Through reevaluating the semantic parts, the detecting performance of partial object detectors is largely enhanced. The explicit model enables the partial detectors to have the capability of occlusion estimation. By discarding the geometric representation in rigid single-angle perspective and applying effective pattern of objective shape, our proposed approaches greatly improve the performance and robustness of similarity measurement. For validating the performance of proposed methods, we designed a comparative experiment on challenging pedestrian frame sequences database. The experimental results on challenging pedestrian frame sequence demonstrate that, compared to the traditional algorithms, the methods proposed in this paper have significantly improved the detection rate for severe occlusion. Furthermore, it also can achieve better localization of semantic parts and estimation of occluding

Accurate Object Recognition with Assembling Appearance and Motion Information

How to effectively detect object and accurately give out its visible parts is a major challenge for object detection. In this paper we propose an explicit occlusion model through integrating appearance and motion information. The model combines together two parts: part-level object detection with single frame and object occlusion estimation with continuous frames. It breaks through the performance bottleneck caused by lack of information and effectively improves object detection rate under severe occlusion. Through reevaluating the semantic parts, the detecting performance of partial object detectors is largely enhanced. The explicit model enables the partial detectors to have the capability of occlusion estimation. By discarding the geometric representation in rigid single-angle perspective and applying effective pattern of objective shape, our proposed approaches greatly improve the performance and robustness of similarity measurement. For validating the performance of proposed methods, we designed a comparative experiment on challenging pedestrian frame sequences database. The experimental results on challenging pedestrian frame sequence demonstrate that, compared to the traditional algorithms, the methods proposed in this paper have significantly improved the detection rate for severe occlusion. Furthermore, it also can achieve better localization of semantic parts and estimation of occluding

Brain microvasculature defects and Glut1 deficiency syndrome averted by early repletion of the glucose transporter-1 protein

Haploinsufficiency of the SLC2A1 gene and paucity of its translated product, the glucose transporter-1 (Glut1) protein, disrupt brain function and cause the neurodevelopmental disorder, Glut1 deficiency syndrome (Glut1 DS). There is little to suggest how reduced Glut1 causes cognitive dysfunction and no optimal treatment for Glut1 DS. We used model mice to demonstrate that low Glut1 protein arrests cerebral angiogenesis, resulting in a profound diminution of the brain microvasculature without compromising the blood–brain barrier. Studies to define the temporal requirements for Glut1 reveal that pre-symptomatic, AAV9-mediated repletion of the protein averts brain microvasculature defects and prevents disease, whereas augmenting the protein late, during adulthood, is devoid of benefit. Still, treatment following symptom onset can be effective; Glut1 repletion in early-symptomatic mutants that have experienced sustained periods of low brain glucose nevertheless restores the cerebral microvasculature and ameliorates disease. Timely Glut1 repletion may thus constitute an effective treatment for Glut1 DS

ReCLIP (Reversible Cross-Link Immuno-Precipitation): An Efficient Method for Interrogation of Labile Protein Complexes

The difficulty of maintaining intact protein complexes while minimizing non-specific background remains a significant limitation in proteomic studies. Labile interactions, such as the interaction between p120-catenin and the E-cadherin complex, are particularly challenging. Using the cadherin complex as a model-system, we have developed a procedure for efficient recovery of otherwise labile protein-protein interactions. We have named the procedure “ReCLIP” (Reversible Cross-Link Immuno-Precipitation) to reflect the primary elements of the method. Using cell-permeable, thiol-cleavable crosslinkers, normally labile interactions (i.e. p120 and E-cadherin) are stabilized in situ prior to isolation. After immunoprecipitation, crosslinked binding partners are selectively released and all other components of the procedure (i.e. beads, antibody, and p120 itself) are discarded. The end result is extremely efficient recovery with exceptionally low background. ReCLIP therefore appears to provide an excellent alternative to currently available affinity-purification approaches, particularly for studies of labile complexes

Systematic Angle Random Walk Estimation of the Constant Rate Biased Ring Laser Gyro

An actual account of the angle random walk (ARW) coefficients of gyros in the constant rate biased rate ring laser gyro (RLG) inertial navigation system (INS) is very important in practical engineering applications. However, no reported experimental work has dealt with the issue of characterizing the ARW of the constant rate biased RLG in the INS. To avoid the need for high cost precise calibration tables and complex measuring set-ups, the objective of this study is to present a cost-effective experimental approach to characterize the ARW of the gyros in the constant rate biased RLG INS. In the system, turntable dynamics and other external noises would inevitably contaminate the measured RLG data, leading to the question of isolation of such disturbances. A practical observation model of the gyros in the constant rate biased RLG INS was discussed, and an experimental method based on the fast orthogonal search (FOS) for the practical observation model to separate ARW error from the RLG measured data was proposed. Validity of the FOS-based method was checked by estimating the ARW coefficients of the mechanically dithered RLG under stationary and turntable rotation conditions. By utilizing the FOS-based method, the average ARW coefficient of the constant rate biased RLG in the postulate system is estimated. The experimental results show that the FOS-based method can achieve high denoising ability. This method estimate the ARW coefficients of the constant rate biased RLG in the postulate system accurately. The FOS-based method does not need precise calibration table with high cost and complex measuring set-up, and Statistical results of the tests will provide us references in engineering application of the constant rate biased RLG INS

Observability Degree-Based AUV Single Beacon Navigation Trajectory Optimization with Range-Only Measurements

Aiming at the problem of autonomous underwater vehicle navigation trajectory optimization using single beacon location under direct route condition, a nonlinear system model for AUV single beacon navigation is established, and the linearized system model with error states is constructed by polar coordinate transformation and simplification. Then, current disturbance is considered. To find out the optimum path to utilize range-only measurements, a novel observability degree-based analysis method is proposed, which gives a quantitative insight into convergence characteristics of the error states by using the eigenvalues of the normalized error covariance matrix. Simulation experiments are done to test convergence characteristics of AUV integrated navigation error states with single beacon range-only measurements under direct route control conditions. The experimental results show that the proposed control method is effective, and it has an important engineering application value and provides us with an optimized path