The Crustal Thickness and Poissons Ratio Distribution in Guangdong and Its Adjacent Areas

Based on the teleseismic waveform data recorded by 82 permanent broadband stations in Guangdong Province and its adjacent areas including Fujian, Jiangxi, Hunan, Guangxi, Hainan and Taiwan, we calculate body wave receiver functions under all stations, and obtain the crustal thickness and average Poisson＇s ratio beneath all stations by the H-K stacking-search method of receiver function. The results show that the crustal thickness with an average thickness of 29. 5km in Guangdong Province and its adjacent areas ranges between 26. 8km and 33. 6kin and gradually thins from northwest to southeast. The crustal thickness in the Zhujiang Delta, western Guangdong, Nanning and Nan＇ao areas is relatively thinner and ranges between 25. 0km and 28. 0km. The minimum crustal thickness is about 26km beneath Wengtian, Hainan and the Zhanjiang zone and Shangchuan Island in Guangdong. The crustal thickness in the zones of Mingxi, Fujian and Yongzhou, Hunan is thicker and varies between 31.0km and 34.0km. The distribution of Poisson＇s ratio in our study region ranges between 0.20 and 0. 29. Poisson＇s ratios in Southeast Hainan, the coastal areas of East Guangdong and West Fujian and the South Jiangxi have distinctly higher values than in others. It suggests that the various geothermal fields located in these areas have high heat flow values. The distribution of crustal thickness and Poisson＇s ratio has an obvious block feature and may be related to the distribution of faults and historical earthquakes.

核酸单反应性质量控制多规则的建立

目的探讨建立1个基于Poisson分布的监控核酸筛查实验室污染情况的质控机制。方法收集2022—2023年基立福Panther核酸检测系统的核酸单反应性率和鉴别试验反应性率相关数据,采用Poisson分布概率法计算每日核酸检测单反应性的概率,利用单反应性率和鉴别反应性率及ROC曲线分析法进一步验证该质控模型的灵敏度和特异性,并提出相应的多规则化的质控策略。结果仅以P=0.05为失控限,Poisson分布概率质控模型判定P<0.05的失控点为40个,结合鉴别反应性率进行人工验证后发现失控点为20个,其判定失控的灵敏度为60.0%,特异性为95.6%,失控点较多,结合鉴别反应性率和运用多规则化质控方法进行质量监控后,2022—2023年核酸检测单反应性警告点为18个,失控点为2个。结论基于Poisson分布概率的多规则核酸单反应性监控机制,更适用于核酸实验室监测预警实验室污染,有利于提升核酸实验室管理能力和检测质量。

通过嵌合管来增强负Poisson比结构的耐撞性能

为了提高结构耐撞性,从而实现车辆轻量化,提出了一种嵌合管(由薄壁方形管嵌入双箭头格子而组成的)具有负Poisson比的增强型结构。通过负Poisson比的收缩效应,来增强负Poisson比结构和嵌合管的耦合作用。建立了增强型结构的有限元模型,并通过压缩试验,来验证其准确性;通过数值方法,在轴向载荷下,比较双箭头点阵结构、结构填充管和嵌合管负Poisson比增强型结构的耐撞性能,并进行了参数分析。结果表明:与双箭头点阵结构和填充管结构相比,增强型结构的总吸收能量为1.12 MJ,提升了约40%;比吸能13.2 kJ/kg,提升了约30%;短梁的夹角70°、长梁的夹角40°、长梁厚度1.4~1.6 mm、短梁厚度1.2 mm的结构填充管结构,具有较大的比吸能和较小的碰撞峰值力;增加嵌管厚度显著提升耐撞性能,但结构质量急剧增加,嵌管厚度达到1.2 mm左右时,兼顾耐撞性和轻量化的需求。

开挖补偿法防控深部地下岩爆灾害——引汉济渭工程秦岭输水隧洞案例分析

Rockburst disasters occur frequently during deep underground excavation,yet traditional concepts and methods can hardly meet the requirements for support under high geo-stress conditions.Consequently,rockburst control remains challenging in the engineering field.In this study,the mechanism of excavation-induced rockburst was briefly described,and it was proposed to apply the excavation compensation method(ECM)to rockburst control.Moreover,a field test was carried out on the Qinling Water Conveyance Tunnel.The following beneficial findings were obtained:Excavation leads to changes in the engineering stress state of surrounding rock and results in the generation of excess energy DE,which is the fundamental cause of rockburst.The ECM,which aims to offset the deep excavation effect and lower the risk of rockburst,is an active support strategy based on high pre-stress compensation.The new negative Poisson’s ratio(NPR)bolt developed has the mechanical characteristics of high strength,high toughness,and impact resistance,serving as the material basis for the ECM.The field test results reveal that the ECM and the NPR bolt succeed in controlling rockburst disasters effectively.The research results are expected to provide guidance for rockburst support in deep underground projects such as Sichuan-Xizang Railway.

基于地理加权回归模型的凉水自然保护区红松空间分布分析

依据凉水国家级自然保护区的671块随机样地的标准地调查数据及landsat9遥感影像,分别建立以最小二乘为基础的泊松回归(Poisson)模型、逻辑斯蒂回归(Logistic)模型和高斯回归(Gaussian)模型3种全局模型,以及以地理加权回归模型(GWR)为基础的地理加权泊松(GWPR)模型、地理加权逻辑斯蒂(GWLR)模型和地理加权高斯(GWGR)模型3种局部模型来预测凉水国家级自然保护区的天然红松分布情况。结果显示,对该地区天然红松分布影响最为显著的因子为坡度和海拔;通过对比全局模型和GWR模型的残差空间相关性发现,GWR模型能够产生更为理想的模型残差,模型残差的空间相关性明显小于全局模型,因此,可以使用GWR模型来解决样地间存在的空间异质性问题,有利于提高红松分布的预测精度;全局模型和GWR模型均有不错的拟合效果,但GWR模型的各个评价指标要优于全局模型,拟合结果更好;天然红松在凉水国家级自然保护区的北部分布最多,在中间条状带区域分布最少。研究结果可为大区域森林经营中的天然红松分布估测提供理论依据。

不放回样本追加下基于永久随机数抽样技术的多层次推断方法及应用研究

抽样调查如何满足多层次推断的需要是我国政府统计调查在实践应用过程中面临的主要难题之一。本文根据我国现阶段抽样调查工作的实际情况,提出一套完整的适用于多层次推断的抽样调查方法。首先,使用永久随机数对现有抽样框进行更新维护,打破现有方法假设抽样框不变的局限性;其次,采用基于列表–序贯算法的条件Poisson抽样实现多层次推断,消除了固定样本量抽样技术仅适用于一次性抽样调查的限制,同时解决了随机样本量抽样技术样本量不固定的问题;此外,分别使用Sen-Yates-Grundy方法和Deville方法进行方差估计,以提高估计精度;最后,通过数值模拟和应用研究验证所提出方法的有效性。该方法在不显著增加调查经费的情况下,可广泛适用于不同数据类型的目标总体,在企业、住户等经济领域调查中具有可推广性的同时,也可为大数据背景下各级政府在实际解决多层次推断问题方面提供有价值的参考。

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

基于DP算法的Poisson回归模型的变量选择

利用已有的DP算法,对Poisson回归模型的似然函数进行优化估计出模型的参数,分别写出Lasso、Adaptive Lasso、SCAD、MCP 4种惩罚似然函数,用DP算法进行求解,实现变量选择.为了实现算法的自动变量选择,在对惩罚参数的选择上,使用了AIC、BIC信息准则.为了验证DP算法的可行性,通过随机模拟的方式生成数据进行求解.在各项指标下,将DP算法与已有的相关算法进行对比.

一类二阶非标准广义力学的正则变换和第一积分

研究带有指数Lagrange函数的二阶非标准广义力学的正则变换以及关于第一积分的Poisson理论.首先,建立二阶非标准广义力学的Hamilton原理,导出Euler-Lagrange方程,并由Legendre变换定义Hamilton函数,建立正则方程;其次,建立二阶非标准广义力学的正则变换的判别条件,并通过母函数的不同选择给出四种基本形式的正则变换;最后,验证二阶非标准广义力学具有Lie代数结构,建立关于第一积分的Poisson理论.文中通过算例演示结果之应用.

广义结构Poisson括号与Casimir函数

证明了广义结构Poisson括号恒等于零的相关结果并得到验证,改进了广义Poisson括号的Casimir函数的结果,并得到了一个推论。

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.

Helmholtz decomposition with a scalar Poisson equation in elastic anisotropic media

P-and S-wave separation plays an important role in elastic reverse-time migration.It can reduce the artifacts caused by crosstalk between different modes and improve image quality.In addition,P-and Swave separation can also be used to better understand and distinguish wave types in complex media.At present,the methods for separating wave modes in anisotropic media mainly include spatial nonstationary filtering,low-rank approximation,and vector Poisson equation.Most of these methods require multiple Fourier transforms or the calculation of large matrices,which require high computational costs for problems with large scale.In this paper,an efficient method is proposed to separate the wave mode for anisotropic media by using a scalar anisotropic Poisson operator in the spatial domain.For 2D problems,the computational complexity required by this method is 1/2 of the methods based on solving a vector Poisson equation.Therefore,compared with existing methods based on pseudoHelmholtz decomposition operators,this method can significantly reduce the computational cost.Numerical examples also show that the P and S waves decomposed by this method not only have the correct amplitude and phase relative to the input wavefield but also can reduce the computational complexity significantly.

Sustainable land management in Mali

This study uses logistic and Poisson regression models to examine the factors influencing the adoption of sustain-able land management(SLM)practices in Mali using two rounds of the nationally representative survey Enquête Agricole de Conjoncture Intégrée aux Conditions de Vie des Ménages.The SLMs considered include the applica-tion of organic fertilizers,the application of inorganic fertilizers,the use of improved seeds,and the practice of intercropping.On average the application of organic fertilizers(39.2%),and inorganic fertilizers(28.7%)are the most frequent SLM practices among Malian farmers,and between 2014 and 2017,we observe a decline in the practice of intercropping.The regression results show that farmers’adoption of different SLMs is significantly associated with biophysical factors(average temperature,climate type,plot size,plot shape,and location),de-mographic factors(age,gender,education,household size),and socioeconomic factors(number of cultivated plots,livelihood diversification,type of crop grown,market access,credit access,economic shocks,and social capital).Our findings suggest that policymakers and agricultural development agencies in Mali need to adopt a multidimensional policy framework to unlock the untapped potential of SLM practices in promoting sustainable agriculture and food security.

Topology Optimization of Metamaterial Microstructures for Negative Poisson’s Ratio under Large Deformation Using a Gradient-Free Method

Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance.To address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free method.The unit cell microstructural topologies are described with the material-field series-expansion(MFSE)method.The MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design variables.To conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique.Initially,we use homogenization to find a preliminary NPR design under a small deformation assumption.In the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation.Using this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% strain.Furthermore,typical microstructure designs are fabricated and tested through experiments.The experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.

负Poisson比热电器件的热-电-力耦合弯曲特征及强度分析

随着智能可穿戴设备的快速发展,对供电元件的续航时间、便捷性以及轻量化等提出了更高要求.热电器件可以直接将人体新陈代谢释放的热能转换为电能,为可穿戴设备持续供电.利用整体-局部、细观-宏观相结合的分析方法,该文研究了负Poisson比热电器件的热-电-力耦合弯曲行为及其强度失效问题.首先,通过建立负Poisson比热电器件的均质化分析模型,获取了器件的宏观弯曲特征,并给出了应力最大的截面.然后,建立热电蜂窝的受力分析模型,利用热力学强度理论导出了胞壁的细观强度失效临界荷载.研究发现:热电蜂窝的应力水平随着内凹角增大呈现先减小后增加的趋势;对于负Poisson比热电蜂窝,强度失效首先发生在中间部位;对于传统的六边形热电蜂窝,端部比中间部位先发生强度破坏;热电器件发生断裂破坏时,中间和端部的临界裂纹长度近似相等,可以拟合为内凹角的指数函数.

任意特征域上sl(2)的Poisson结构

利用李代数上Poisson代数的定义与双线性决定了任意特征域上李代数sl(2)的所有Poisson结构,得到结论:特征不为2的域上,sl(2)的Poisson结构由一个参数完全决定,都是非交换且非结合的;特征为2的域上,sl(2)的Poisson结构由8个参数完全决定,而且既有结合的Poisson结构、交换的Poisson结构,也有非交换且非结合的Poisson结构.

一类随机泊松系统的保结构数值方法

考虑一类随机泊松系统,称为随机Lotka-Volterra系统的保结构数值模拟。为该类系统提出一种随机泊松积分子,并证明了该积分子具有一阶均方收敛阶。数值实验对理论结果进行了验证。

Hybrid millimeter wave heterogeneous networks with spatially correlated user equipment

In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate.We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations(SBSs)are deployed in the areas with high User Equipment(UE)density.Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs.For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication.By using tools from stochastic geometry,we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association.For UE clustering we considered Thomas cluster process and derive expressions for the association probability,coverage probability,area spectral efficiency,and energy efficiency.We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions.Furthermore,we analyze the impact of mmWave operating frequency,antenna gain,small cell biasing,and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets.Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.

山西省运城市居民年住院次数影响因素分析——基于零膨胀及其相关回归模型

[目的]通过拟合居民年住院次数的最优模型,筛选出影响山西省运城市居民年住院次数的主要影响因素。[方法]分别构建负二项回归、Poisson回归、零膨胀负二项回归和零膨胀Poisson回归4种模型,经比较得出最优模型,并据此开展居民年住院次数的影响因素分析。[结果]近一年内0次住院共计4870例(88.18%)。模型分析显示:性别、年龄、文化程度、居住区域、患有慢性病者、家庭年人均收入及常住人口数是居民年住院次数的影响因素(P<0.05);年龄、职业、家庭常住人口数、患有慢性病情况、吸烟、居住区域及健康知识获取途径是居民住院次数出现零膨胀现象的影响因素(P<0.05)。[结论]山西省运城市居民的年住院次数零膨胀负二项回归模型拟合效果最优。家庭年人均收入处于中等水平、患有慢性病人群就医行为较多;年龄偏大、家庭常住人口数为4~6人、城区居住、患有慢性病及经常吸烟的人群的住院潜在需求更大。

稀疏过程在常利率环境下的广义Poisson风险模型中的应用

风险理论是连接数学与金融问题的一座桥梁,它是保险精算学(即实际寿险精算)的重要组成部分,是保险精算人员对保险业务进行风险管理的重要理论工具,同时也是保险公司发展业务进行有效营运的理论保证。破产概率是风险理论研究的核心问题,而利息是影响破产概率的重要因素。本文讨论了常利率环境下离散时间风险模型的破产概率,给出了模型的破产概率的上界。首先构造了风险模型,通过鞅方法得到模型的破产概率满足的Lundberg不等式和相关公式;然后给出了离散时间情形下的双险种风险模型,得到了与破产相关的一些变量的表达式和性质。