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Additional file 1: Supplementary Fig. 1. Notch3 expression was significantly positively correlated with macrophages infiltration. a. Representative correlation results analyzed using CIBERSORT-ABS. b. Survival curves of patients with colorectal carcinoma from the TCGA database stratified according to expression levels of Notch1,2,4. Supplementary Fig. 2. Notch3 expression was positively correlated with the degree of macrophage infiltration in colorectal carcinoma tissue. a. Immunohistochemical staining of HCT116 with or without Notch3 knockdown derived tumor tissues using Notch3 antibody. b. IHC score standard of Notch3 in colon cancer. c. Notch3 and CD68 staining of the colon cancer tissue continuous section from patient #2. Supplementary Fig. 3. Notch3 expression was positively correlated with the macrophage recruitment-related cytokines expression. a. The relation between Notch3 and macrophage recruitment-related genes analyzed using LinkedOmics database ( http://www.linkedomics.org/login.php ). b. The relationship between Notch3 and macrophage recruitment-related genes analyzed using GEPIA2 database ( http://gepia2.cancer-pku.cn/#index ). Supplementary Fig. 4. Interference Notch3 attenuated the colon tumor growth and decreased macrophage infiltration in vivo. a. Notch3 staining of NCT and Notch3-shRNA in mice tumor tissues. b. Gating strategy for flow cytometry. c. Flow cytometry analysis of blood from MC38 tumors carrying mice. d. The quantification of the results in b.

This paper examines the direction of arrival (DOA) estimation for polarized signals impinging on a sparse vector sensor array which is based on the maximum interelement spacing constraint (MISC). The vector array effectively utilizes the polarization domain information of incident signals, and the quaternion model is adopted for signals polarization characteristic maintenance and computational burden reduction. The features of MISC arrays are crucial to the mutual coupling effects reduction and higher degrees of freedom (DOFs). The quaternion data model based on vector MISC arrays is established, which extends the scalar MISC array into the vector MISC array. Based on the model, a quaternion multiple signal classification (MUSIC) algorithm based on vector MISC arrays is proposed for DOA estimation. The algorithm combines the advantages of the quaternion model and the vector MISC array to enhance the DOA estimation performance. Analytical simulations are performed to certify the capability of the algorithm.

In this paper, we consider a special class of nonlinear optimal control problems, where the control variables are box-constrained and the objective functional is strongly convex corresponding to control variables and separable with respect to the state variables and control variables. We convert solving the original nonlinear problem into solving a sequence of constrained linear-quadratic optimal control problems by quasilinearization method. In order to solve each linear-quadratic problem efficiently we turn to study its dual problem. We formulate dual problem by the scheme of Fenchel duality, the strong duality property and the saddle point property corresponding to primal and dual problem are also proved, which together ensure that solving dual problem is effective. Thus solving the sequence of control constrained linear-quadratic optimal control problems obtained by quasilinearization technique is substituted by solving the sequence of their dual problem. We solve the sequence of dual problem and obtain the solution to primal control constrained linear-quadratic problem by the saddle point property. Furthermore, the fact that solution to each subproblem finally converges to the solution to the optimality conditions of original nonlinear problem is also proved. After that we carry out numerical experiments using present approach, for each subproblem we formulate the discretized primal and dual problem by Euler discretization scheme in our experiments. Efficiency of the present method is validated by numerical results., Comment: 25 pages, 5 figures

In addition to target echoes, high frequency surface wave radar (HFSWR) receives sea and ionospheric clutter. Among these clutters, the ionospheric clutter is dominant and significantly affects the detection performance of HFSWR, particularly when the targets are located 100 kilometers away from the radar, rendering it an unsolved problem for HFSWR. Existing studies concerning HFSWR ionospheric clutter lack empirical research on the nonlinear dynamical characteristics of the ionosphere of HFSWR as existing ionospheric suppression methods are still insufficient to adapt the project application. Therefore, the present study utilized the threshold segmentation method to eliminate the sea clutter in HFSWR Range-Doppler spectrum and extracted ionospheric signals from this spectrum by edge feature extraction. Subsequently, the chaotic invariants, such as correlation dimension and the largest Lyapunov exponent of HFSWR ionospheric clutter, were calculated by phase space reconstruction, whilst the chaotic dynamical characteristics of HFSWR ionospheric clutter were determined by the 0-1 test for chaos and other algorithms. Furthermore, the present study demonstrated, for the first time, the chaotic dynamics of the ionospheric clutter of HFSWR with a low-dimensional attractor by processing and analyzing the experimental data from the Weihai High Frequency Radar Station. The conclusion redefines HFSWR ionospheric clutter based on chaotic dynamics rather than regarding it as a stochastic process, which is conducive to efforts to explore the formation mechanism of ionospheric clutter in essence, which can ultimately improve the detection capability of HFSWR, particularly for long-distance targets.

The detection performance of high-frequency surface wave radar (HFSWR) is significantly impacted by ionospheric clutter and sea clutter. In order to suppress the ionospheric clutter, a new method based on the largest Lyapunov exponent prediction algorithm is proposed in this Letter. Firstly, it is demonstrated, for the first time, that the ionospheric clutter from HFSWR is a chaotic dynamical process, and then the largest Lyapunov exponent is estimated using the Wolf algorithm. After verifying the actual data, this suppression algorithm can decrease the amplitude of the ionospheric clutter by at least 30 dB.

High Frequency Surface Wave Radar (HFSWR) has been shown to provide enhanced performance in over the horizon detection of targets and sea states remote sensing by the returns of targets and ocean surface. Meanwhile, HFSWR can also receive ionospheric echoes reflected by the ionosphere, which severely affect the radar detection performance. In this paper, the radar cross section (RCS) of ionosphere for HFSWR is estimated, which would help quantify the impact of the ionosphere to radar system and the performance of clutter mitigation techniques. Simulations are provided to illustrate the effect of parameters including radar operating frequency, scale size of irregularities, aspect angle and detection range on the RCS of ionosphere.

High frequency surface wave radar (HFSWR) is traditionally unable to detect target altitude information. To simultaneously estimate the target altitude and radar cross-sections (RCS) with bistatic HFSWR, a novel estimation model is proposed with the variation of the propagation attenuation, and the target echoes are utilized to construct the measurement equation. The presented model is completely observable to the target state, which can contribute to preferable estimation results. In order to improve the estimation accuracy, a centralized fusion model is adopted to fuse four measurement vectors. Simulations and practical examples demonstrate the effectiveness of the proposed estimation model.

This paper introduces the theoretical basis of spatial time-frequency distributions in direction-of-arrival (DOA) estimation, and then proposes a new method through analysis to non-stationary signals' time-frequency distributions and extraction of their cross terms. The work done by the previous researchers almost based on paying attention to the auto terms information and suppressing of cross terms, and this paper examines the signal cross terms from a new perspective. Study found that cross terms between signals do contain rich information, and using cross terms information alone can calculate out the direction of the source signals. In particular, when the strength between the signals is different, the auto terms information of the weak signal have a certain possibility can not be detected. Therefore, extraction of cross terms information to estimate the DOA of signals is much easier. Simulation experiments verified these characteristics.

We consider questions related to the well-known conjecture due to Embrechts and Goldie on the closedness of different classes of heavy- and light-tailed distributions with respect to convolution roots. We show that the class L(��)\cap OS is not closed under convolution roots related to an infinitely divisible distribution for any ��\ge0, i.e. we provide examples of infinitely divisible distributions belonging to this class such that the corresponding Levy spectral distribution does not. We also prove a similar statement for the class (L(��)\cap OS)\ S(��). In order to facilitate our analysis, we explore the structural properties of some of the classes of distributions, and study some properties of the well-known transformation from a heavy-tailed distribution to a light-tailed one., 28 pages

Recently, the quaternion-valued feedforward neural network (QFNN) has been developed to process three dimensional (3-D) and 4-D signals in quaternion domain, and the weight matrices and bias vectors of the QFNN were obtained based on the quaternion backward propagation (QBP) method. However, it should be noted that the QBP is a first-order quaternion gradient descent algorithm. The convergence speed of the QBP is usually slow and may not be very suitable to process nonstationary quaternion-valued signals. To address this problem, a widely linear quaternion unscented Kalman filter (WLQUKF) algorithm is proposed to train the QFNN. This is derived by utilizing some recent studies in the augmented quaternion statistics and the $\mathbb {HR}$ -calculus. With the augmented quaternion statistics, the WLQUKF is able to process general quaternion-valued noncircular, nonlinear, and nonstationary signals, effectively. Simulations on both benchmark circular and noncircular quaternion-valued signals, and on real-world quaternion-valued signals support the analysis.

In this paper, the local asymptotic estimation for the supremum of a random walk and its applications are presented. The summands of the random walk have common long-tailed and generalized strong subexponential distribution. This distribution class and the corresponding generalized local subexponential distribution class are two new distribution classes with some good properties. Further, some long-tailed distributions with intuitive and concrete forms are found, which show that the intersection of the two above-mentioned distribution classes with long-tailed distribution class properly contain the strong subexponential distribution class and the locally subexponential distribution class, respectively., Comment: 26 pages

Double-frequency phase difference method is a simple and effective means for measuring the group delay of Frequency-Translating Devices (FTD). Especially for measuring the group delay of FTD which cannot accept the other local oscillator, the method shows the irreplaceable advantage. In order to obtain an accurate description of the group delay characteristics in the pass band of FTD, two improved methods are put forward in this paper which are variable aperture measurement method and multiple-frequency phase difference(MFPD) method on the basis of the measuring group delay by using double-frequency phase difference(DFPD) method. The variable aperture measurement method uses genetic algorithm (GA) to optimize the measurement aperture and the measurement interval on the basis of the rate of the group delay, and the measured data is handled with the cubic spline interpolation and Taylor series expansion method. Finally, an accurate group delay characteristics curve of the system is fitted. The MFPD method turns the double-frequency into the multiple-frequency on the basis of the DFPD method, which improves the testing efficiency and the measurement accuracy in a great extent. However, the premise is that the measured output spectrum should have enough signal-to-noise ratio. The simulation results show that these two improved methods are equally effective in reducing the measurement error and improving the measurement accuracy greatly.

This system centers on high-performance microcontroller AT89S52. Through the motor control on ASSP chip MMC-1 which controlling two DC motors, it can achieve accuracy position control of the moving acoustic. The buzzer can make an aural signal on a certain frequency using the microcontroller AT89S52. Because the distances between the three audio receivers and the moving acoustic are different, the signal they receive has a certain time difference. Then the control system makes a control signal according to the time difference. This signal is transmitted to the moving sound source through a wireless transceiver module and guides its motion.

Group delay is a key parameter describing the phase characteristic of the signal transmission system, which can also measure the phase linearity of the continuous signal passing through transmission system. The group delay of Frequency-Translating Devices (FTD) is measured by the double-frequency phase difference method in this paper. But the measurement error will increase in the FTD whose group delay changes greatly. In view of this problem, an optimization method is put forward. Combined with polynomial fitting of high order, this proposed method, which uses the reasonable selection of the parameters such as measuring aperture and measurement interval, can improve the measurement precision and the test efficiency.

Azimuthal measurements of the high frequency ground wave over-the-horizon (OTH) radar are either coarse or unavailable in an actual environment. It is very hard for a single station OTH radar to performance effective tracking under that condition. A bi-station OTH radar system is proposed to triangulate target tracks using range and Doppler measurements only. Multi-sensor data association and combining positioning are key issues of this system. This paper focuses on positioning and tracking filter algorithm. The locating and tracking model is established and the extended Kalman filter (EKF) is used to solve the bi-station nonlinear tracking problem. Simulation result shows that EKF can handle this well, and the bi-station OTH radar system can meet or slightly better than the accuracy of the conventional single station OTH radar tracking system with poor bearing resolution.

In a complex environment radar plot is often changing dramatically, non-uniform, discontinuous, uncertain and containing lots of false alarms. It is difficult for tracking system to form tracks in such complex environment. Traditional track formation methods can not accurately determine the size of track initiation gate and select specific initiation criteria. In this paper, an intelligent information processing method is proposed to solve track initiation in complex environments. The track initiation is considered as a progress of plot identification, classification and fuzzy information processing. According to the integration and fusion of neural network (NN), fuzzy reasoning (FR) and expert system (ES) technology, an intellectualized track initiation knowledge reasoning system is constructed which can realize structural, functional, algorithmic and hierarchical complementation. Further more the adaptive robust learning algorithm and the weighted synthesis reasoning algorithm are used in this system. Real data experiment shows that the proposed knowledge engineering method can effectively solve track initiation problem in complex conditions.

Though a Monostatic-Bistatic Composite High Frequency Surface Wave Radar Network (MBC-HFSWR Network) is established to cover the shortage of the monostatic radar, how to judge the real target update from the plausible measurements to initiate tracks quickly and accurately still remains a challenging problem. A novel method utilizing unconventional characteristics for track initiation is proposed in this paper, which uses more accurate information and avoids the problem of low detection precision of high frequency radar. A highly intelligent information fusion model which is a combination of Neural network, Fuzzy reasoning and Expert system (NFE model) is presented to solve the problem above and the validity of the provided method is demonstrated by Monte Carlo simulations.

Based on a dual-polarisation high-frequency surface wave radar system, main characteristics and performance of sky wave interference are described, and a new polarisation filter, adaptive null phase-shift polarisation filtering, is applied. Suppressing the interference in each pulse and keeping the original phases of the targets, about 20 dB signal-to-interference ratio is expected with experimentally derived data.

Microtubule inhibitors, as chemotherapeutic drugs, are widely used for cancer treatment in clinic. However, the development of multidrug resistance (MDR) in cancer is a major challenge for microtubule inhibitors in its clinical implementation. From a high throughput drug screening using cells transformed by oncogenic RAS, we identified a small molecule AR8-1006 that blocks cell proliferation. The analysis of structure-activity relationship indicated that this serial of scaffold represents a potent inhibitor of tumor cell growth. AR8-1006 shows activities against a larger panel of more than 1000 human cancer cell lines with a wide variety of tissue origins. Further analysis showed that this compound depolymerizes microtubules and affects formation of the spindle. Interestingly, it induces the spike-like conformation of microtubules in vitro and in vivo, which is different from typical microtubule modulators. Structural analysis revealed that this serial of compounds binds to the colchicine pocket at the intra-dimer interface, though mostly not overlapping with colchicine binding. More importantly, AR8-1006 displays favorable pharmacological properties on overcoming tumor MDR both in vitro and in vivo. Taken together, our data reveal a novel scaffold represented by AR8-1006 that could be developed as cancer therapeutics, especially for tumor multidrug resistance. Citation Format: Nannan Ning, Chengyong Wu, Min Wu, Yamei Yu, Changjun Zhu, Cyril Benes, Jianming Zhang, Xianming Deng, Qiang Chen, Ruibao Ren. Discovering a novel microtubule inhibitor overcoming tumor multidrug resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3926.