Forward Vehicle Collision Warning Based on Quick Camera Calibration

Forward Vehicle Collision Warning (FCW) is one of the most important functions for autonomous vehicles. In this procedure, vehicle detection and distance measurement are core components, requiring accurate localization and estimation. In this paper, we propose a simple but efficient forward vehicle collision warning framework by aggregating monocular distance measurement and precise vehicle detection. In order to obtain forward vehicle distance, a quick camera calibration method which only needs three physical points to calibrate related camera parameters is utilized. As for the forward vehicle detection, a multi-scale detection algorithm that regards the result of calibration as distance priori is proposed to improve the precision. Intensive experiments are conducted in our established real scene dataset and the results have demonstrated the effectiveness of the proposed framework

Channel Reconstruction for SVD-ZF Precoding in Massive 3D-MIMO Systems Low-Complexity Algorithm

In this paper, we study the low-complexity channel reconstruction methods for downlink precoding in massive MIMO systems. When the user is allocated less streams than the number of its antennas, the BS or user usually utilizes the singular value decomposition (SVD) factorizations to get the effective channels, whose dimension is equal to the num of streams. This process is called channel reconstruction in BS for TDD mode. However, with the increasing of antennas in BS, the computation burden of SVD is becoming incredibly high. As a countermeasure, we propose a series of novel low-complexity channel reconstruction methods for downlink zero-forcing precoding (ZF). We adopt randomized algorithms to construct an approximate SVD, which could reduce the dimensions of the matrix, especially when approximating an input matrix with a low-rank element. Besides, this method could automatically modify the parameters to adapt arbitrary number demand of streams from users. The simulation results show that the proposed methods only cost less than 30% float computation than the traditional SVD-ZF method, while keeping nearly the same performance of 1Gbps with 128 BS antennas.Comment: 7 pages, 6 figures, received by 2016 IEEE 83rd Vehicular Technology Conference. arXiv admin note: substantial text overlap with arXiv:1510.0850

Genistein increases epidermal growth factor receptor signaling and promotes tumor progression in advanced human prostate cancer.

Genistein is an isoflavone found in soy, and its chemo-preventive and -therapeutic effects have been well established from in vitro studies. Recently, however, its therapeutic actions in vivo have been questioned due to contradictory reports from animal studies, which rely on rodent models or implantation of cell lines into animals. To clarify in vivo effects of genistein in advanced prostate cancer patients, we developed a patient-derived prostate cancer xenograft model, in which a clinical prostatectomy sample was grafted into immune deficient mice. Our results showed an increased lymph node (LN) and secondary organ metastases in genistein-treated mice compared to untreated controls. Interestingly, invasive malignant cells aggregated to form islands/micrometastasis only in the secondary organs of the genistein-treated groups, not in the untreated control group. To understand the underlying mechanism for metastatic progression, we examined cell proliferation and apoptosis on paraffin-sections. Immunohistological data show that tumors of genistein-treated groups have more proliferating and fewer apoptotic cancer cells than those of the untreated group. Our immunoblotting data suggest that increased proliferation and metastasis are linked to enhanced activities of tyrosine kinases, EGFR and its downstream Src, in genistein-treated groups. Despite the chemopreventive effects proposed by earlier in vitro studies, the cancer promoting effect of genistein observed here suggests the need for careful selection of patients and safer planning of clinical trials

Stacking-symmetry governed second harmonic generation in graphene trilayers

Crystal symmetry plays a central role in governing a wide range of fundamental physical phenomena. One example is the nonlinear optical second harmonic generation (SHG), which requires inversion symmetry breaking. Here we report a unique stacking-induced SHG in trilayer graphene, whose individual monolayer sheet is centrosymmetric. Depending on layer stacking sequence, we observe a strong optical SHG in Bernal (ABA) stacked non-centrosymmetric trilayer, while it vanishes in rhombohedral (ABC) stacked one which preserves inversion symmetry. This highly contrasting SHG due to the distinct stacking symmetry enables us to map out the ABA and ABC crystal domains in otherwise homogeneous graphene trilayer. The extracted second order nonlinear susceptibility of the ABA trilayer is surprisingly large, comparable to the best known 2D semiconductors enhanced by excitonic resonance. Our results reveal a novel stacking order induced nonlinear optical effect, as well as unleash the opportunity for studying intriguing physical phenomena predicted for stacking-dependent ABA and ABC graphene trilayers.Comment: To appear in Science Advance