Estimation of cancer cell migration in biomimetic random/oriented collagen fiber microenvironments

Increasing data indicate that cancer cell migration is regulated by extracellular matrixes and their surrounding biochemical microenvironment,playing a crucial role in pathological processes such as tumor invasion and metastasis.However,conventional two-dimensional cell culture and animal models have limitations in studying the influence of tumor microenvironment on cancer cell migration.Fortunately,the further development of microfluidic technology has provided solutions for the study of such questions.We utilize microfluidic chip to build a random collagen fiber microenvironment(RFM)model and an oriented collagen fiber microenvironment(OFM)model that resemble early stage and late stage breast cancer microenvironments,respectively.By combining cell culture,biochemical concentration gradient construction,and microscopic imaging techniques,we investigate the impact of different collagen fiber biochemical microenvironments on the migration of breast cancer MDA-MB-231-RFP cells.The results show that MDA-MB-231-RFP cells migrate further in the OFM model compared to the RFM model,with significant differences observed.Furthermore,we establish concentration gradients of the anticancer drug paclitaxel in both the RFM and OFM models and find that paclitaxel significantly inhibits the migration of MDA-MB-231-RFP cells in the RFM model,with stronger inhibition on the high concentration side compared to the low concentration side.However,the inhibitory effect of paclitaxel on the migration of MDA-MB-231-RFP cells in the OFM model is weak.These findings suggest that the oriented collagen fiber microenvironment resembling the late-stage tumor microenvironment is more favorable for cancer cell migration and that the effectiveness of anticancer drugs is diminished.The RFM and OFM models constructed in this study not only provide a platform for studying the mechanism of cancer development,but also serve as a tool for the initial measurement of drug screening.

Reliability Analysis of Correlated Competitive and Dependent Components Considering Random Isolation Times

In the Internet of Things(IoT)system,relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission efficiency.In Body Sensor Network(BSN)systems,biosensors communicate with receiving devices through relay nodes to improve their limited energy efficiency.When the relay node fails,the biosensor can communicate directly with the receiving device by releasing more transmitting power.However,if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device,the biosensor will be isolated by the system.Therefore,a new combinatorial analysis method is proposed to analyze the influence of random isolation time(RIT)on system reliability,and the competition relationship between biosensor isolation and propagation failure is considered.This approach inherits the advantages of common combinatorial algorithms and provides a new approach to effectively address the impact of RIT on system reliability in IoT systems,which are affected by competing failures.Finally,the method is applied to the BSN system,and the effect of RIT on the system reliability is analyzed in detail.

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering.The latter is particularly true for slope stability assessment,where the effects of uncertainty are synthesized in the so-called probability of failure.This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint.In view of this issue,this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments.The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion.Then,failure probabilities are estimated employing maximum entropy distribution with fractional moments.The application of the proposed approach is examined with two examples:a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope.The results show that the proposed approach has excellent accuracy and high efficiency,and it can be applied straightforwardly to similar geotechnical engineering problems.

Reliability Analysis on Repairable System with Dual Input Closed-Loop Feedback Link Considering Shutdown Correlation Based on Goal Oriented Methodology

Goal oriented( GO) methodology is a kind of success oriented system reliability analysis method and has been used widely.The repairable system with dual input closed-loop feedback link( DICLFL) considering shutdown correlation didn't make reliability analysis accurately based on existing GO methodology. So, a reliability analysis method used to deal with DICLFL considering shutdown correlation is provided based on GO methodology.Firstly, a new operator, which is used to describe DICLFL considering shutdown correlation,whose number is 1,is created and named as Type 9C operator. And then,the formulas of type 9C operator are derived based on Markov process theory. Finally,the new method presented in this paper is adopted to conduct the reliability analysis of an electro-hydraulic servo speed control system. The analysis result is compared with those of Monte Carlo simulation and fault tree analysis( FTA). The comparison results show that this new reliability analysis method based on GO methodology is feasible and meaningful for reliability analysis of repairable systems with DICLFL considering shutdown correlation.Meantime,it will be useful for more other applications.

Reliability analysis for aeroengine turbine disc fatigue life with multiple random variables based on distributed collaborative response surface method

The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.

STOCHASTIC OBJECT-ORIENTED PETRI NETS (SOPNS) AND ITS APPLICATION IN MODELING OF MANUFACTURING SYSTEM RELIABILITY

Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.

Fuzzy Random Reliability Analysis of Blocky Rock-Mass in Slopes

Slope stability assessment is a geotechnical problem characterized by many sources of uncertainty. In clas- sical reliability analysis, only the randomness of uncertainties is taken into account but the fuzziness of them is ignored. In this paper, a fuzzy probability approach and a fuzzy JC method are presented for the reliability analysis. The two methods have been applied to stability analysis of a certain slope of permanent ship lock in the Three-Gorges Project. The results obtained from these two methods are basically the same. However, compared with the fuzzy probability means, the fuzzy JC method can reflect the real situation better because it uses a fuzzy-based analysis applied to not only limit state equation but also mechanical parameters.

PROBABILITY OF RANDOM EVENTS OF INSPECTION AND REPAIR AND MAINTAINING RELIABILITY OF STRUCTURES

Reliability analysis of the inspected and repaired structure requires dealing with a large number of complex random events. Considering many kinds of random factors, a probability of these random events existing possibly in the inspection and repair process and reliability analysis methodologies are proposed. A systematic dynamic reliability model is given for structures in service under the scheduled inspection and repair.

Bias and Mean Square Error of Reliability Estimators under the One and Two Random Effects Models: The Effect of Non-Normality

The coefficient of reliability is often estimated from a sample that includes few subjects. It is therefore expected that the precision of this estimate would be low. Measures of precision such as bias and variance depend heavily on the assumption of normality, which may not be tenable in practice. Expressions for the bias and variance of the reliability coefficient in the one and two way random effects models using the multivariate Taylor’s expansion have been obtained under the assumption of normality of the score (Atenafu et al. [1]). In the present paper we derive analytic expressions for the bias and variance, hence the mean square error when the measured responses are not normal under the one-way data layout. Similar expressions are derived in the case of the two-way data layout. We assess the effect of departure from normality on the sample size requirements and on the power of Wald’s test on specified hypotheses. We analyze two data sets, and draw comparisons with results obtained via the Bootstrap methods. It was found that the estimated bias and variance based on the bootstrap method are quite close to those obtained by the first order approximation using the Taylor’s expansion. This is an indication that for the given data sets the approximations are quite adequate.

Reliability Modelling and Analysis of Satellite Propulsion System Based on Reliability Block Diagram and Extended Object-Oriented Petri Net

Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.

ON THE RANDOM-ORIENTED PERCOLATION

Let Ld=(Zd, Ed) be the d-dimensional lattice, suppose that each edge of Ld be oriented in a random direction, i.e., each edge being independently oriented positive direction along the coordinate axises with probability p and negative direction otherwise. Let Pp be the percolation measure, η(p) be the probability that there exists an infinite oriented path from the origin. This paper first proves η(p) θ(p) for d 2 and 1/2 p 1, where θ(p) is the percolation probability of bond model; then, as corollaries, the author gets η(1/2) = 0 for d = 2 and dc(1/2) = 2, where dc(1/2) = sup{d: η(1/2) = 0}. Next, based on BK Inequality for arbitrary events in percolation (see[2]), two inequalities are proved, which can be used as FKG Inequality in many cases (note that FKG Inequality is absent for Random-Oriented model). Finally, the author proves the uniqueness of infinite cluster and a theorem on geometry of the infinite cluster (similar to theorem (6.127) in [1] for bond percolation).

Reliability Simulation for a Missile Tank Under Random Loading

This paper presents a Monte-Carlo simulation method to calculate intensity reliability for a missile tank under random loading. The cumulative damage mathematical model is established , and it adopts a direct simulation method to present random loading and o-riginal intensity for a missile tank. It can effectively predict intensity reliability for a missile tank in the environment of transport and flight.

Study on the random simulation times of mining engineering reliability

The theory of Monte-Carlo simulation method is that the event happened probability was estimated by happened frequency in the experiments. So it is very im-portant to ascertain the times of simulation. The probability and statistic theory are used to determine the optimal simulation times through strict mathematic reasoning. The study of two cases is made to show the availability of the presented method, and some relative problems were discussed.

再生粗骨料混凝土应力-应变关系

再生粗骨料混凝土应力-应变关系是实现其材料到结构力学分析的桥梁纽带,成为再生粗骨料混凝土结构基础理论的基石。介绍了作者团队多年来在再生粗骨料混凝土应力-应变关系方面取得的研究进展:采用模型化再生粗骨料方法,研究了复杂界面过渡区对再生粗骨料混凝土破坏行为的影响,揭示了再生粗骨料混凝土细观损伤本质与演化机理;从静力作用到动力作用,系统地开展了不同工况下再生粗骨料混凝土应力-应变行为试验研究,探明了载荷条件对再生粗骨料混凝土应力与变形的影响规律并建立了相适应的力学与数学模型;进一步考虑再生粗骨料性能时空变异性,发现了再生粗骨料混凝土力学响应的概率分布特征,提出了再生粗骨料混凝土随机损伤本构关系;基于获得的本构模型,完成了再生粗骨料混凝土构件时变可靠度分析和结构动力非线性分析,为再生粗骨料混凝土在实际工程中的安全应用提供了理论支撑;提炼了相关研究结论并对未来研究工作进行了展望。

不平整跑道激励下飞机起落架随机响应及可靠性分析

采用非线性二自由度系统构建了飞机起落架模型,通过时域噪声刻画了不平整跑道对飞机起落架系统的随机激励,并引入路面不平度系数描述了跑道的不平整程度;基于飞机起落架模型响应的概率密度函数及其统计量,开展了不平整跑道对飞机起落架系统影响规律的研究。应用随机可靠性分析方法以及人体振动舒适性理论,通过建立安全域和舒适域与系统响应之间的关系,分析了起落架模型在不同路面不平度系数下的可靠性,并对乘客舒适性进行了评价。研究结果表明:路面不平度系数越大,系统状态变量的波动越剧烈,系统的可靠性和舒适性与路面不平度系数呈一定的负相关性;在路面不平度系数较小的情况下,系统平均首次穿越时间以及舒适性受随机扰动的影响更加显著。

车辆-轨道系统动力极值预测及可靠度计算

为从车辆-轨道系统的动力极值预测及其可靠度计算角度分析车辆系统行车安全、衡量系统可靠程度,基于车辆-轨道耦合动力学及概率理论,提出一种车轨系统动力极值预测及可靠度评估方法。首先,基于轨道不平顺概率模型,采用轨道不平顺累计概率谱确定具有不同激振能量的随机不平顺序列;依据离散Parseval定理,建立轨道不平顺时域序列和功率谱间的对应关系;将轨道不平顺概率模型与车辆-轨道耦合动力学模型相结合,从随机动力计算中提取车辆-轨道的动力极值及可靠度信息;随后利用车辆-轨道耦合动力模型及二维插值算子,根据谱线能量关系实现动力极值预测;此外,基于此系统激励输入与响应输出间的概率等效性,导出了动力极值的可靠度计算式。以实测的轨道不平顺和车体加速度数据及4种类型不平顺在不同累计概率下的谱组合计算得出的轮轨横向力和钢轨垂向位移的计算结果为样本,与预测结果进行对比。研究结果表明:计算时程的分布趋势基本与实测时程一致,动力极值预测结果与实际的动力计算结果较为接近。由于轨道不平顺随机性的存在使得车辆-轨道系统的动力响应存在随机离散及方差特征,但通过轨道不平顺的幅频及能量特性预测车辆-轨道系统的动力极值的方法是较为可行的。

温度循环和随机振动载荷下堆叠封装焊点可靠性模拟研究

采用有限元模拟研究了堆叠封装(Package on package, PoP)在温度循环和随机振动载荷下的焊点可靠性,包括封装内部的基板堆叠焊点和封装外部的板级互连焊点。通过应力分析定位危险焊点并计算焊点在温度循环下的疲劳寿命。模拟结果表明:在温度循环载荷下,应力主要集中于基板边角处焊点,基板堆叠焊点的疲劳寿命为3 002周次,板级互连焊点的疲劳寿命为1 552周次;在随机振动载荷下,两层焊点的应力值均较低,在50~2 000 Hz的随机振动频率范围内具有较高的可靠性。

钢梁腐蚀相关性对钢-混组合梁桥体系可靠度的影响

服役环境中钢主梁的腐蚀本质上是一个随机过程,腐蚀深度随机变量既有时变性亦有空间性。现有测量方法只能获得单根钢梁腐蚀深度数据,尚不能明确结构体系腐蚀深度变量的联合分布模式,可能导致腐蚀结构体系可靠度计算模型失真。以某钢-混凝土组合梁桥为研究对象,首先建立了钢主梁腐蚀深度增长Gamma随机过程模型,并利用钢梁腐蚀深度实测数据对模型进行了验证;然后采用Kendall秩相关系数量化表征主梁腐蚀深度相关性,推导了腐蚀钢梁的时变抗力计算公式;最后基于Copula函数提出了考虑主梁腐蚀相关性的梁桥体系失效概率计算方法,对比研究了钢梁腐蚀相关性对钢-混组合简支梁桥体系可靠度的影响。研究结果表明:桥梁运营前期腐蚀相关性对梁桥受力性能影响较小,在运营中后期,中高程度的腐蚀相关性将会对梁桥体系的可靠度影响较大。研究提出了钢梁腐蚀空间相关性量化方法,获得了更精确的钢-混组合梁桥体系可靠度计算方法,可为组合梁桥体系的时变可靠度评定提供参考。

基于CAN协议的服务化安全通信方案

针对CAN(controller area network)协议安全性及防护能力不足的问题,提出基于CAN总线的服务化安全通信方案,采用软件加强的方式满足车内通信的安全要求。通过对功能进行服务化定义、采用随机密钥与Seed-Key认证的方式,使CAN总线具有机密性、真实性和抗重放攻击的能力,同时不会增加网络负载。利用蓝牙模块和车身模块作为试验平台,针对蓝牙解锁功能,对所提出的CAN安全通信方案进行了验证,并采用不同的算法(AES128、、HMAC)满足信息安全防护要求和客户感知要求,同时该协议表现出良好的可靠性。

不确定采摘环境下改进RRT算法的机械臂路径规划研究

由于果蔬采摘环境的不确定性和复杂性,机械臂在复杂环境中完成采摘,其路径规划需考虑实时避障。为实现采摘机械臂在不确定环境下安全采摘,提出一种改进RRT的动态避障算法,以提升机械臂在不确定采摘环境的适应性。针对基本快速扩展随机树算法(Rapidly-exploring Random Trees,RRT)在动态环境下迭代时间长、路径长、适应性差等问题,在RRT算法的基础上,引入目标导向策略,把终点以一定概率作为随机采样点的采样方向,提高算法的迭代效率;引入动态检测机制,对已完成规划的初始路径进行实时检测,使算法适应动态变化的环境。通过仿真分析改进RRT算法,结果表明:改进RRT算法的路径减少16%,迭代时间缩短86.5%;同时,动态检测机制使算法适应动态环境。