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In this paper, we address the fixed-time consensus tracking problem of second-order leader-follower multi-agent systems with nonlinear dynamics under directed topology. The consensus tracking algorithm consists of distributed observer and observer-based decentralized controller. The fixed-time distributed observer guarantees that each follower estimates the leader’s state under directed topology within a fixed time, where the upper bound of convergence time is independent on the initial conditions. The fixed-time decentralized controller makes each follower converge to the leader’s state in fixed time via tracking the distributed observer’s state and overcome the nonlinear dynamics without adding linear control terms. Finally, the numerical example is provided to illustrate the effectiveness of the results.

We propose multilayer information spillover networks, including return spillover layer, volatility spillover layer, and extreme risk spillover layer in the variance decomposition framework for comprehensively investigating the information spillovers and connectedness among 30 Chinese financial institutions (i.e., banks, securities, and insurers) during the period 2011–2018. We analyze the topological characteristics of static and dynamic multilayer networks at the system and institution levels. We find that (i) at a system level, each layer exhibits a unique network structure and spillover evolution behavior, and multilayer information spillover networks provide synthetic information on the connectedness among financial institutions, and (ii) at an individual level, institutions from different financial sectors play different roles in receiving or sending shocks based on different information spillover or contagion channels. Our findings supply valuable knowledge for investors when they assess risk and optimize asset allocation, and for regulators when they measure connectedness and prevent system risk.

This paper deals with the coordinated welding problem of multi-robot systems by applying a deep reinforcement learning algorithm which is called multi-agent deep deterministic policy gradient (MADDPG). It is assumed that the states and actions of robots are continuous and each robot can only get local information of its neighbors. A novel reward composed of trajectory optimization, coordinated welding and collision avoidance is designed, which yield multi-robot systems to arrive the welding targets quickly, achieve the simultaneous welding for a weld line and avoid collision among robots. Simulation results are provided to demonstrate the effectiveness of the proposed control algorithm.

This paper considers the coordinated welding control based on deep multi-agent reinforcement learning. The discrete-time states and actions with local observation for the welding robots and the characteristics of the weld lines (e.g., the starting points of the weld lines and the ending points of the weld lines) are defined, which is suitable to use the monotonic value function factorisation for deep multi-agent reinforcement learning (QMIX) algorithm. A novel reward composed of trajectory optimization, collision avoidance and the task done is designed, which is proved by the simulation in the grid-world environment.

The distributed estimation problem for wireless sensor networks with limited communication/sensing ranges and observability is studied. A novel sensor measuring activation scheme based on a fully distributed event-triggered strategy is proposed to make each node achieve a better trade-off between estimation error and energy saving. The strategy depends on both the predicted synthetic performance index and the predicted position of the target. A distributed Kalman filtering algorithm based on the minimum trace fusion principle is proposed. It is proved that comparing with the time-triggered strategy, the proposed event-triggered measuring strategy has better performance. Although the event-triggered measuring topology is time-varying and each sensor is not observable, it is proved that as long as there exists at least one collaboratively observable sensor in the available distance-based sensing network at each time instant, the estimation errors are bounded in mean square sense. Simulation examples are given to illustrate the validity of the algorithm.

Nonlinear energy sink (NES) has proven to be very effective in reducing the vibration response of structures. In this paper, a magnetic bistable nonlinear energy sink (BNES) that composed of a guided moving mass attached with linear springs and permanent magnets is proposed. To assess the seismic control performance of the proposed BNES, a shear frame model equipped with the proposed BNES is compared with the same shear frame model equipped with an optimized cubic NES and with a linear tuned mass damper (TMD) system. The results show that, in the idealized situation, where the mass and stiffness is clearly defined (no uncertainty), the BNES can achieve similar performance as a thoroughly in-tuned TMD system. Moreover, in the detuned condition, due to broadband high internal resonance capability, the proposed BNES can outperform the linear TMD and the cubic NES. The study demonstrates that the proposed BNES can be used as an efficient passive vibration absorber for structural seismic control.

This paper takes the planar formation tracking control problem of second-order agents with model uncertainties into consideration. A novel adaptive neural network (ANN) estimation method based on neighborhood information is designed to estimate model uncertainties. By using the tools of the back-stepping method and ANN, a robust formation tracking control law is given. The law can guarantee this formation tracking errors uniformly bounded under connected topologies. Numerical simulation results verify the validity of the analysis results.

This paper addresses the formation tracking control problem for spacecrafts flying spherically with certain formation. Compared to existing works that deal with bidirectional communication topology and disturbance-free scenarios, this paper proposes a brand-new formation tracking control protocol with directed network and unknown external disturbance with a known upperbound. Moreover, spacecraft flying model is introduced to the system dynamics. The formation tracking law of spacecraft is designed, and the uniform ultimate boundedness is proven through Lyapunov functions as well. To avoid the "explosion of terms" caused by time derivative, the dynamic surface control (DSC) technology is employed to the designing procedure of control input. Numerical simulation results are presented to demonstrate the effectiveness of the proposed scheme.

In this paper, a novel method named spatial pooling is proposed for visual lane line segmentation. Occlusion is one of the most common and difficult scenes among various and complex road environments. In most existing references, the structure of lane line is still not considered for the occlusion problem. To better solve this case and enhance the long-distance information fusion for lane lines, a spatial pooling module is proposed firstly by using a combination of horizontal and vertical pooling to achieve pooling in the direction across the lane line. This method can enhance the information fusion ability in oblique directions and improve the lane line detection performance. Then, for further study, we propose an end-to-end network for lane line segmentation based on the spatial pooling module. Finally, the experimental results on tuSimple lane line dataset verify the effectiveness of our method.

This cross-sectional study aimed to investigate cancer patients’ cognitive level of pain control and to evaluate the patient-related factors or barriers to effective cancer pain management in China. In seven tertiary hospitals across China, 372 patients experiencing cancer pain were surveyed through a self-designed questionnaire to assess the factors associated with effective pain control. Patients’ demographic data and pain control-related factors were recorded. Cluster sampling and binary logistic regression models were used to investigate the association between predictive factors and effective pain control. The survey showed that the majority of the patients were more than 45 years old (76.3%), and 64.4% had an average annual income of more than 20 000 RMB. One-third of the patients suffered from cancer pain for more than 3 months, and 75.1% received professional guidance during medication. The barriers to pain control for patients included preference to enduring pain and refusing analgesics (62.9%), negligence towards drug usage (28.5%), concerns about the addiction (48.2%) and adverse reaction (56.4%). The average annual family income, professional guidance, knowledge of pain medication, adherence to analgesics, and concerns about addiction to analgesics were significantly correlated to the effect of patients’ pain control. The study presents major barriers to optimal pain control among patients with cancer in China. Our findings suggest that educational programs and medical insurance reimbursement support from the government are urgently needed to overcome the cognitive barriers toward effective pain management and to relieve the economic burden among patients with cancer pain in China.

We propose Granger causality networks in the time domain and frequency domain to investigate the interconnectedness of Chinese financial institutions based on the daily returns of banks, securities, and insurers during 2011–2018. We find that the system-level interconnectedness mainly concentrates on the medium-high frequency, but individual-level interconnectedness varies across different frequencies. Dynamically, the system-level interconnectedness is consistent in the time domain and frequency domain, while this consistency in the individual-level interconnectedness does not hold, but both of them are affected by macroeconomic situations and financial events. During 2015–2016 and 2018, the system-level interconnectedness increased significantly and was at a high level.

Enhanced recovery after surgery (ERAS) programs are a series of measures being taken during the perioperation to alleviate surgical stress and accelerate the recovery rate of patients. Although several studies reported the efficacy of ERAS in liver surgery, the role of ERAS in laparoscopic hepatectomy is still unclear. This meta-analysis is aimed to evaluate the efficacy and safety of ERAS programs versus traditional care in laparoscopic hepatectomy.We searched PubMed, EMBASE, the Cochrane Library, CNKI, Wang Fang Database and VIP Database for randomized controlled trials (RCTs) or clinical controlled trials (CCTs) concerning using ERAS in laparoscopic hepatectomy. Data collection ended in June 1st, 2016. The main end points were intraoperative blood loss, intraoperative blood transfusion, operative time, the cost of hospitalization, time to first flatus, the time to first diet after surgery, duration of postoperative hospital stay, total postoperative complication rate, gradeⅠcomplication rate, grade Ⅱ-Ⅴcomplication rate.8 studies with 580 patients were eligible for analysis. There were 292 cases in ERAS group and 288 cases in traditional perioperative care (CTL) group. Compared with CTL group, ERAS group was associated with significantly accelerated of time to first diet after surgery (SMD = -1.79, 95%CI: -3.19 ∼ -0.38, P = 0.01), time to first flatus (MD = -0.51, 95%CI: -0.91 ∼ -0.12, P = 0.01). Meanwhile, it was associated with significantly decreased of duration of the postoperative hospital stay (MD = -3.31, 95%CI: -3.95 ∼ -2.67, P 0.00001), cost of hospitalization (MD = -1.0, 95%CI: -1.49 ∼ -0.51, P 0.0001), total postoperative complication rate (OR = 0.34, 95%CI: 0.15-0.75, P = 0.008), gradeⅠcomplication rate (OR = 0.37, 95%CI: 0.22-0.64, P = 0.0003) and gradeⅡ-Ⅴcomplication rate (OR = 0.49, 95%CI: 0.32-0.77, P = 0.002). Whereas there was no significantly difference in intraoperative blood loss (P 0.05), intraoperative blood transfusion (P 0.05), operative time (P 0.05) between ERAS group and CTL group.Application of ERAS in laparoscopic hepatectomy is safe and effective, and it could accelerate the postoperative recovery and lighten the financial burden of patients.

A response surface method (RSM) for composite laminate structures is proposed in this paper, which is based on the moving Kriging interpolation. The substitute limit state function for failure criteria is discussed and constructed on series of deterministic finite element analysis. Combined with first order reliability method, reliabilities of composite laminate structures are subsequently obtained. Reliability analysis of a composite laminate plate, as a numerical example, is illustrated by the proposed method. The results demonstrate the practicability of the method.

This paper addresses a local formation tracking control for multiple first-order agents in 3D space, where each agent's trajectory converges to the given super-ellipsoid and the tracking target is movement with an unknown speed. Differing from the using of GPS in the literature, a new distributed solution is given based on local measurements of relative position. To develop the spherical formation tracking motion into the superellipsoidal case, a general desired distance function of the relative position is introduced to describe the super-ellipsoidal following error and each agent's control input projected onto the superellipsoidal normal vector service to super-ellipsoidal following. At the same time, each agent's control input projected onto the the direction of meridian and parallel are used to accomplish the solid formation along meridian and parallel. Λ consensus-based estimator is given to estimate the moving target's speed according to adaptive design. The validity of the proposed control law is proved through numerical simulations.

This article considers the problem of directing a family of fully actuated surface vessels to cooperatively follow a set of convex and closed orbits with a time-invariant reference orbital velocity and maintain attitude synchronization. A consensus-based adaptive control law under a bidirectional communication topology is proposed to estimate the reference orbital velocity so that the restriction that every vessel in the family must have access to the reference in the previous literature can be removed. The assumption of nonzero total linear speed of each vessel is removed by the use of potential function. Simulation results demonstrate the effectiveness of the proposed approach.

Extreme Learning Machine (ELM) as an emergent technology has shown its promising performance in many applications. This paper proposes a parallelized ELM ensemble based on the Min-Max Modular network (M^3-network) to meet the challenge of the so-called big data. The proposed M^3-ELM first decomposes classification problems into smaller subproblems, then trains an ELM for each subproblem, and in the end ensembles these ELMs with the M^3-network. Twelve data sets including both benchmarks and real-world applications are employed to test the proposed method. The experimental results show that M^3-ELM not only speeds up the training phrases by 1.6-4.6 times but also reduces the test errors by 0.37-19.51% compared with the normal ELM. The results also indicate that M^3-ELM possesses scalability on large-scale tasks and accuracy improvement on imbalanced tasks.

Recently, the market share of die making in our country is increasing day by day, which can be attributed to the development of processing and manufacturing industry as well as the deepening of reform and opening-up. At current, die making has been applied in these practices such as manufacturing of electronic connector and producing of workpieces of dashboard. With the arrival of computer age, the die making technology based on Pro/E is becoming increasingly common. With specific cases, this text carry out discussions on the die making which is based on Pro/E.

Die design and manufacturing are organic unity, primarily owning to its own characteristics. On account of the fact that curves and surfaces constitute the main inner part of die, CAD software can be applied in die designing, plotting and three-dimensional modeling. Additionally, CAPP software could be applied in the scheming of die processing while CAM software in the imitation of die manufacturing. As the intensive research and development of CAD/CAPP/CAM, computers not only offer spacious room for die design, modeling and application but also bring about great prospects for research and development of computer software.

Reverse engineering, as the advanced absorption technique, playing a vital role in shortening the design time of products and providing technological guarantee for modeling design of products, is the latest hotspot in the present technological field. The application principle of this technology is to turn the primary physical modeling into design modeling through the transformative platform. It serves as both the technological foundation in intensifying the engineering quality and the information for accurate analysis of modeling design data and processing of modeling profile. Coupled with modernized design concept and improved creativity , reverse engineering capitalize fully on CAE/CAM/CAD technology to integrate the current resources for information supply of manufacturing accurate modeling. The practice of reverse engineering could be conducive to bring the preference of measuring equipment into full play so as to improve the data processing ratio in CAD/CAM system and advance the level of industrial design for the purpose of manufacturing automation.

This paper deals with a rigid formation control problem of n agents moving in the plane, where each agent is required to maintain a nominated distance from its neighbors, and each agent is described by a double integrator. A globally stable formation control strategy is designed to drive the multi-agent systems to a desired rigid formation using the integrator backstepping technique and the adaptive perturbation method. Therefore, the proposed control law can guarantee that the equilibrium set of the overall system is unique, and all agents' velocity converge to a common value without collision between each communicating agents. Simulation results are provided to illustrate the effectiveness of the control algorithm.

In this paper, some factors effect on the maximum stress of inner rubber of some elastomer isolators with big diameter of 1500mm are analyzed by FEA. These factors include size of hole, ratio of , shear modulus of inner rubber , the first shape factor , thickness of cover rubber. The isolators include those used in building or bridge, loading condition is single compress . Research results show that size of hole, ratio of and have a little effect on the maximum stress of inner rubber, but shear modulus of inner rubber, and thickness of cover rubber hardly effect.

LNR and LRB in which the value of shear modulus of inner rubber is 0.392MPa have been widely used in the practical isolation projects, although there are some test researches about dependency of shear property of them, but there is little complete study under high design compressive stress, such as 15MPa, and equations of dependency of shear property of them have seldom been found. In this paper, completely experiments about dependency of shear property of them have been done, and the fitted equations about various dependencies for LNR and LRB are given. Effect of size of rubber bearing on various dependencies is also studied. Formulas of determination of parameters in bilinear model of LRB are proposed, and have been testified well with FEA program.

Using the effective-mass Hamiltonian for an arbitrary direction wurtzite semiconductor on the basis of k⋅p theory, we investigate the strain effects on the optical anisotropy in semi-polar and nonpolar GaN planes. The optical matrix elements are formulated for an arbitrary direction and calculated for the A- and R-planes. It is found that giant optical anisotropy appears in the A- and R-planes and the biaxial strain significantly changes the polarization properties.

This paper deals with a directed formation control problem of three agents moving in the plane, where the agents have a cyclic ordering with each one required to maintain a nominated distance from its neighbor, and each agent is described by a double integrator. Firstly, a directed formation control law based on the knowledge only of the neighbor's direction is designed by using the integrator backstepping technique, which can not only accomplish the desired triangle formation but also ensure that speeds of all agents converge to a common value without collision between each other during the motion. Then, with the purpose of relaxing and even overcoming the restriction of initial conditions of the agents owing to collision avoidance, we introduce the inter-agent potential functions into the design. The convergence of the proposed control algorithms is proved by using tools from LaSalle's invariance principle. Simulation results are provided to illustrate the effectiveness of the control laws. Copyright © 2008 John Wiley & Sons, Ltd.

Circulating tumor cells (CTCs) are valuable for diagnosis, monitoring therapy and prognosis in primary lung cancer. Herein, we evaluated the clinical significance of lung cancer CTCs in this study. Detection of CTCs was performed using epithelial cell adhesion molecule-independent enrichment and CD45 fluorescence in situ hybridization detection. CTCs ≥ 2/3.2 mL were considered as positive. The positive rates in primary lung cancer, benign lung disease and healthy control groups were 84, 0 and 4.2 %. CTCs count was significantly higher in lung cancer patients than healthy controls and benign lung disease, with an area under ROC curve of 0.917 (95 % confidence interval 0.855-0.979; p = 0.000) between lung cancer and nonmalignant diseases. CTCs count significantly increased with an increase in pathological stage with mean count of 2.3 ± 2.6 (stage I-II), 3.5 ± 3.3 (stage III) and 4.5 ± 4.3 (stage IV), respectively. The positive detection rate of CTCs for primary lung cancer diagnosis was higher than serum tumor markers. In total, 25 metastasis lung cancer patients participated in the follow-up. Changes in CTCs count after two cycles of chemotherapy were consistent with radiographic appearance. Moreover, CTCs count was better than serum tumor markers for monitoring chemotherapy response. Median progression-free survival (PFS) was 2.05, 3.25 and 8.348 months (p < 0.05) in group in which post-treatment CTCs count was increased, unchanged and decreased, respectively. Furthermore, PFS in patients whose post-treatment CTCs count increased or were unchanged accompanied by a baseline CTCs count ≥3 was significantly shorter than those whose post-treatment CTCs count decreased or was unchanged accompanied with baseline value C < 3 (1.85 vs. 8.22 months, p = 0.000) [Corrected]. Therefore, CTCs are a reproducible indicator of disease status that may be superior to imaging.

This article considers the problem of directing a family of nonholonomic vehicles to formation flying a set of closed convex planar orbits and approach a time-varying reference orbital velocity in a three-dimensional (3D) space. A novel coordinated adaptive control law based on local neighbor-to-neighbor information is proposed to estimate the desired orbital velocity so that the assumption that every vehicle in the family has access to the reference in the literature is removed. We show how the geometric extension design, projection tracking method and consensus-based technique can be combined together to construct the formation flying controller under the bidirectional commutation topology. Simulation results demonstrate the effectiveness of the proposed approach.

The study on pattern classification trends to be towards large-scale, multi-label, and imbalanced problems. The amount of the data which need to be classified is typically dozens of millions and it keeps rapid increasing in recent years. Traditional pattern classification approaches are inefficient and even ineffective in this situation. In our previous work, we proposed a min-max modular (M3) network for dealing with large-scale and imbalanced problems. M3-network is a generalized modular learning framework and includes three main steps: decomposing a large-scale problem into several smaller independent sub-problems, learning these sub-problems in parallel, and combining the results of the sub-problems to generate a solution to the original problem. In this paper, we embed LIBLINEAR into M3-network (M3-liblnear) to deal with large-scale, multi-label, and imbanlanced pattern classification problems. LIBLINEAR is a fast implementation of a linear classifier. M3-Liblinear uses LIBLINEAR as a base classifier to learn each of the sub-problems. We compare M3-Liblinear with Liblinear-cdblock on a large-scale Japanese patent classification problem. Experimental results demonstrate that M3-Liblinear is superior to Liblinear-cdblock in both training time and generalization performance.

Inter carrier interference (ICI) are widespread in the orthogonal frequency division multiplexing (OFDM) communication systems. This paper mainly discusses two ICI self-cancellation algorithms, the data-conversion based ICI self-cancellation algorithm and the data-conjugate based ICI self-cancellation algorithm. The properties and the application environments are also given. Simulation results show that the performance of the data-conversion based ICI self-cancellation algorithm is superior to the data-conjugate based ICI self-cancellation algorithm in mobile environment, while the data-conjugate based ICI self-cancellation algorithm self-cancellation algorithm has better bit error rate perfomence than the data-conversion based ICI self-cancellation algorithm in small phase noise circumstance.