The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Probability Distribution Characteristics of Strong Nonlinear Waves Under Typhoon Conditions in the Northern South China Sea

The generation and propagation mechanism of strong nonlinear waves in the South China Sea is an essential research area. In this study, the third-generation wave model WAVEWATCH Ⅲ is employed to simulate wave fields under extreme sea states. The model, integrating the ST6 source term, is validated against observed data, demonstrating its credibility. The spatial distribution of the occurrence probability of strong nonlinear waves during typhoons is shown, and the waves in the straits and the northeastern part of the South China Sea show strong nonlinear characteristics. The high-order spectral model HOS-ocean is employed to simulate the random wave surface series beneath five different platform areas. The waves during the typhoon exhibit strong nonlinear characteristics, and freak waves exist. The space-varying probability model is established to describe the short-term probability distribution of nonlinear wave series. The exceedance probability distributions of the wave surface beneath different platform areas are compared and analyzed. The results show that with an increase in the platform area, the probability of a strong nonlinear wave beneath the platform increases.

Probability Laws Derived from the Gamma Function

Several densities or probability laws of continuous random variables derive from the Euler Gamma function. These laws form the basis of sampling theory, namely hypothesis testing and estimation. Namely the gamma, beta, and Student law, through the chi-square law and the normal law are all distributions resulting from applications of Euleur functions.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Stochastic Model of Dengue: Analysing the Probability of Extinction and LLN

In this article, we develop and analyze a continuous-time Markov chain (CTMC) model to study the resurgence of dengue. We also explore the large population asymptotic behavior of probabilistic model of dengue using the law of large numbers (LLN). Initially, we calculate and estimate the probabilities of dengue extinction and major outbreak occurrence using multi-type Galton-Watson branching processes. Subsequently, we apply the LLN to examine the convergence of the stochastic model towards the deterministic model. Finally, theoretical numerical simulations are conducted exploration to validate our findings. Under identical conditions, our numerical results demonstrate that dengue could vanish in the stochastic model while persisting in the deterministic model. The highlighting of the law of large numbers through numerical simulations indicates from what population size a deterministic model should be considered preferable.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Integrating host biological and ecological variables to predict probability of haemosporidian infection in raptors

Variations in host traits that influence their exposure and susceptibility may impact probability of vector-transmitted diseases.Therefore,identifying the predictors of infection probability is necessary to understand the risk of disease outbreaks during expanding environmental perturbation.Here,we conducted a large survey based on microscopic examination and molecular analysis of haemosporidian parasite infection in raptors rescued at the Beijing Raptor Rescue Centre.Combining these data with biological and ecological variables of the raptors,we determined predictors that affect the probability of haemosporidian infection using generalized linear mixed models and multimodel inference.Our results showed that infection probability exhibited considerable variation across host species in raptors,and body mass,sex,and evolutionary history played relatively weaker roles in driving infection probability.Instead,activity pattern,age,geographic range size,migration distance,and nest type were important predictors of the probability of haemosporidian infection,and the role of each predictor differed in the three main haemosporidian genera(Plasmodium,Haemoproteus,and Leucocytozoon).This macro-ecological analysis will add to our understanding of host traits that influence the probability of avian haemosporidian infection and will help inform risk of emerging diseases.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

SEPS联合激光闭合术治疗老年大隐静脉曲张的临床疗效

目的分析SEPS联合激光闭合术治疗老年大隐静脉曲张的临床疗效。方法选取2021年1月—2023年1月在本院治疗的大隐静脉曲张老年患者78例进行研究,将其随机分为对照组与观察组,每组39例。其中,对照组采用传统交通支静脉结扎术联合激光闭合术,观察组采用交通支静脉离断术(SEPS)联合激光闭合术进行治疗,对两组患者术前、术后各时间段创伤定量指标及手术指标进行对比。结果观察组手术指标、创伤定量指标均明显优于对照组(P<0.05)。结论SEPS与激光闭合术联合治疗大隐静脉曲张能够有效减少患者下肢瘀斑面积,提升生活质量。

Variations in Probability Assessment With Atypical Scenarios

Probability assessment in some scenarios may involve unusual aspects such as requiring certain values for some events and extremely high or low probabilities in other cases.

Calculation of Two-Tailed Exact Probability in the Wald-Wolfowitz One-Sample Runs Test

The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n0 (number of zeros) and n1 (number of ones), as well as the number of runs. Fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using Friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.

基于SEP法的火力发电厂作业安全风险管控

随着我国经济社会的不断发展,能源问题日渐突出。如何提升生产效率、降低作业安全风险是火力发电厂面临的重要问题之一。本文采用SEP法探讨了发电厂作业风险控制方法的制订,并在宁夏某火力发电厂作业燃煤运输系统中进行应用,在一定程度上降低了危险隐患有害因素,变被动为主动,更有利于了解电厂作业安全事件的成因原理,对实现电厂安全作业具有一定的借鉴意义。

Flashover Probability of Wind Turbine Blade and Impact of Strong Electromagnetic Pulse from Lightning Strikes on Wind Turbine Safety

This paper systematically studies the flashover probability of wind turbine blade lightning arrester and the impact of strong electromagnetic pulses on the local and surrounding wind turbines during lightning strikes.The research results indicate that the flashover probability of direct lightning strikes by the wind turbine blade lightning arrester is almost negligible,and the strong electromagnetic pulse of wind turbine blade during lightning strikes has a serious impact on the electronic equipment of the machine,while the impact on the surrounding wind turbine is relatively small.At the same time,the calculation formula for the reflection of lightning current on the carbon brush between the wind turbine hub and the engine compartment during the flashing of the wind turbine blades is provided,and the calculation method for calculating the spatial gradient distribution of electromagnetic field intensity using Biot-Savart Law theorem is applied.The limitations of using wind turbine blades for lightning protection are pointed out,and a technical route for achieving wind turbine lightning safety is proposed,which can be used as a reference for wind turbine lightning protection technicians.

Probability Distribution of Ratio of China Aviation Network Edge Vertices Degree and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the ratio of edge vertices degree in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the ratio of edge vertices degree had linear probability distribution and the two parameters of the probability distribution had linear evolution trace.

榛子全基因组ChSEP基因鉴定、多克隆抗体制备及其在胚珠中的表达研究

【目的】正常的胚珠充实是榛子种仁形成的前提与基础,胚珠充实不足可频繁导致瘪仁、空壳果实的形成,SEP基因被认为是可以影响胚珠发育的E类MADS-box基因。为研究SEP在榛子种仁充实过程中的重要调节作用,拟鉴定参与榛子胚珠发育的重要作用基因ChSEP,并制备ChSEP的多克隆抗体,开展正常发育与败育胚珠中ChSEP的免疫组织化学分析,以期为深入解析SEP基因调控榛子胚珠发育机制提供科学依据。【方法】用榛子基因组与转录组数据鉴定基因组中所有的SEP基因家族成员,并进行重要SEP基因的原核表达载体构建、基因表达及多克隆抗体制备,最后对参与胚珠发育调控的重要SEP蛋白进行免疫组织化学检测。【结果】(1)榛子基因组中鉴定到3条ChSEP蛋白序列(Cor0054610.1、Cor0008190.1、Cor0119400.1),所有ChSEP蛋白均包含SRF-TF与K-box结构域。制备了Cor0054610.1的多克隆抗血清E18305和E18306,它们的抗体抗原条带分子量在45 kDa左右,1∶1000稀释后可检测到1~2 ng抗原。(2)免疫组织化学分析结果表明:ChSEP在发育胚珠与败育胚珠的珠被中均有表达,珠被中的ChSEP表达量高于子叶,正常发育胚珠与败育胚珠ChSEP分布特征差异不明显。【结论】本研究在转录与蛋白水平上提供了ChSEP(Cor0054610.1)参与榛子胚珠发育调控的证据,为深入解析榛子胚珠发育机理提供了科学依据。

SEP矩阵的性质

为刻画群可逆条件下SEP矩阵的性质,通过替换SEP矩阵刻画式中某些矩阵为未知量的方法构造了新的方程,并利用新方程的可解性给出SEP矩阵的存在性准则.运用单变量矩阵方程和双变量矩阵方程在给定集合中的有解性方法,讨论了SEP矩阵的相关性质.结果表明:若A∈C^(n×n)是一个群可逆矩阵,则A是SEP矩阵当且仅当AXA^(#)=(A^(#))^(H)XA^(+),AXA^(#)AY=(A^(#))^(H)XY在ρ^(2)_(A)={(α,β)|α,β∈ρ_(A)}中可解,其中ρ_(A)={A,A^(#),A^(+),A^(H),(A^(#))^(H),(A^(+))^(H),(A^(+))^(#),(A^(#))^(+)}.

再论SEP许可谈判良性生态系统改进和完善——兼评美英欧日SEP最新政策动向

当前全球SEP许可引发的纠纷不断,SEP许可市场正处于对抗的动荡期,伴随诉讼或诉讼威胁的商业许可谈判能否体现自愿及公平需打上问号。5G的商业格局已发生变化,其在许可等方面更加复杂。主要包括:一是有更多的5G专利权人;二是主要许可人已经宣布了更高的5G专利费率;三是5G的SEP持有人对专利费叠加上限没有明确声明;四是SEP实施者的规模和范围超出了移动终端制造商。移动通信领域SEP许可谈判模式需要革新,各国纷纷出台政策意见增强各自SEP规则主导权,我国在SEP全球许可谈判和诉讼的国际趋势中应尽快明确规则,以更好地维护本国优势产业的发展利益。

竞争法视角下SEP善意许可谈判框架之构建

欧盟法院通过“华为诉中兴案”构建了一个颇具影响力的FRAND许可费善意谈判框架,但仍存在一些问题有待进一步澄清,如SEP持有人提起侵权诉讼的条件,SEP持有人发出的要约是否须在实体上符合FRAND原则,法院审查要约合理性的义务及审查方法等。对华为—中兴善意谈判机制进行合理解读,需认识到欧盟竞争法干预SEP许可行为具有双重目标——提高SEP许可效率,维护下游市场的竞争效率。SEP持有人在未履行发出侵权通知与要约的程序性义务之前,不得申请禁令救济,同时,SEP持有人应承担对其要约符合FRAND原则的举证责任。法院对这一问题的审查主要考虑两个方面:一是SEP持有人差别对待被许可方是否有合理理由,二是差异性的对待是否会影响下游市场的竞争。