Distribution and Migration of Heavy Metals in Undisturbed Forest Soils:A High Resolution Sampling Method

The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.

Robust Variance Components Estimation in the PERG Mixed Distributions of Empirical Variances—PEROBVC Method

A mixed distribution of empirical variances, composed of two distributions the basic and contaminating ones, and referred to as PERG mixed distribution of empirical variances, is considered. In the paper a robust inverse problem solution is given, namely a (new) robust method for estimation of variances of both distributions—PEROBVC Method, as well as the estimates for the numbers of observations for both distributions and, in this way also the estimate of contamination degree.

Strong Convergence of Empirical Distribution for a Class of Random Matrices

Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai×si and si=1/√N（v1i,…, vN,i）^T. The spectral distribution of SN is proven to converge, with probability one, to a nonrandom distribution function under mild conditions.

EEMD and bidimensional RLS to suppress physiological interference for heterogeneous distribution in fNIRS study

Near-infrared spectroscopy(NIRS)can provide the hemodynamics information based on the hemoglobin concentration representing the blood oxygen metabolism of the cerebral cortical,which can be deployed for the cerebral function study.However,NIRS-based cerebral function detection accuracy can be signi¯cantly in°uenced by the physiological activities such as cardic cycle,respiration,spontaneous low-frequency oscillation and ultra-low frequency oscillation.The distribution difference of the capillary,artery and vein leads to the heterogeneity feature of the cerebral tissues.In the case that the heterogeneity is not serious,good detection accuracy and stable performance can be achieved through the regression analysis as the reference signal can well represent the interference in the measurement signal when conducting the multi-distance measurement approach.The direct use of the reference signal to estimate the interference is not able to achieve good performance in the case that the heterogeneity is serious.In this study,the cerebral function activity signal is extracted using recursive least square(RLS)method based on the multi-distance measurement method in which the reference signal is processed by ensemble empirical mode decomposition(EEMD)algorithm.The temporal and dimensional correlation of the neighboring sampling values are applied to estimate the interference in the measurement signal.Monte Carlo simulation based on a heterogeneous model is adopted here to investigate the effectiveness of this methodology.The results show that this methodology can effectively suppress the physiological interference and improve the detection accuracy of cerebral activity signal.

Reliability Assessment for the Solenoid Valve of a High-Speed Train Braking System under Small Sample Size

Reliability assessment of the braking system in a high?speed train under small sample size and zero?failure data is veryimportant for safe operation. Traditional reliability assessment methods are only performed well under conditions of large sample size and complete failure data,which lead to large deviation under conditions of small sample size and zero?failure data. To improve this problem,a new Bayesian method is proposed. Based on the characteristics of the solenoid valve in the braking system of a high?speed train,the modified Weibull distribution is selected to describe the failure rate over the entire lifetime. Based on the assumption of a binomial distribution for the failure probability at censored time,a concave method is employed to obtain the relationships between accumulation failure prob?abilities. A numerical simulation is performed to compare the results of the proposed method with those obtained from maximum likelihood estimation,and to illustrate that the proposed Bayesian model exhibits a better accuracy for the expectation value when the sample size is less than 12. Finally,the robustness of the model is demonstrated by obtaining the reliability indicators for a numerical case involving the solenoid valve of the braking system,which shows that the change in the reliability and failure rate among the di erent hyperparameters is small. The method is provided to avoid misleading of subjective information and improve accuracy of reliability assessment under condi?tions of small sample size and zero?failure data.

Empirical Likelihood Inference Under Stratified Random Sampling in the Presence of Measurement Error

Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper the empirical likelihood method is put forward for making inferences on parameters of interest under stratified random sampling in the presence of measurement error, Our results show that it can lead to estimators which are asymptotically normal and utilize all the available sample information. We also obtain the asymptotic distribution of empirical likelihood testing statistics. In particular, we apply the method to obtain estimator and confidence interval of population mean.

STUDY ON THE SEQUENCE STRUCTURE OF SBR BY ^(13)C-NMR METHOD Ⅱ. PEAK ASSIGNMENT FOR ALIPHATIC CARBONS SPECTRA

The study on ^(13)C-NMR spectra of aliphatic carbon region of emuision-processed and solution-processed (by lithium catalyst) SBR was carried out. The assignments for more than thirty odd peaks observed experimentally were made by using 'corresponding analysis' method, combined with the empirical parameters reported in literature. The peak intensifies were calculated based on BemouUian statistic assumption.

基于新课标的中小学生计算思维量表构建研究

对学生计算思维的培养已成为数字时代的核心议题,科学、精准的评价则是培养学生计算思维能力的基础。然而,针对义务教育阶段学生的计算思维测评,目前国内尚无依托相关课程标准制定的本土化的、权威的量表。为此,研究首次依托《义务教育信息科技课程标准(2022年版)》(以下简称“新课标”)中的计算思维定义及培养要求,共以12920名(N1=1029,N2=1458,N3=10433)小学生和初中生为研究样本,运用收敛混合方法构建一个面向我国教育实际的、经严格论证的中小学生计算思维量表。结果显示:经过两轮的收敛混合分析,修改后的计算思维量表共包含5个因子及15个题项,具有良好的内容效度;经过大样本实证检验分析,量表具有良好的信效度,且具有跨性别、年级和地区测量等值性,可以用来测量中小学生的计算思维水平。

无人机高光谱岩性和矿物识别技术研究

无人机高光谱遥感技术以其高空间分辨率和高光谱分辨率的技术优势,在大比例尺区域地质填图领域可以发挥重要作用。利用无人机搭载全谱段高光谱成像仪(HD_SAVI)获取0.2 m高空间分辨率影像数据,采用经验线性法对所获取数据进行光谱重建,重建后无人机高光谱影像光谱曲线与地面实测光谱曲线谱形基本一致,典型特征吸收峰位置偏差均在1个像元以内。采集岩性样本构建岩性知识库,利用深度学习算法基于无人机高光谱影像数据开展岩性识别;岩性识别结果与大比例尺地质图对比,岩性空间分布基本一致,地质体边界准确且较清晰。参考典型矿物光谱库进行矿物识别。与同一地区CASI/SASI航空高光谱数据地质填图结果进行对比分析,结果表明:两者提取的矿物在空间分布上具有较高的一致性,但无人机低空高光谱影像空间分辨率较高,识别出的矿物种类更加丰富。无人机高光谱遥感技术可以满足无人区、交通不便地区地质勘查,以及重点区或矿区外围等地区大比例尺地质填图的需要。

水体微塑料的垂向分布及采样方法比较研究——以九龙江河口为例

由于受到潮汐过程的影响,河口区微塑料的调查和研究存在着方法不统一、数据误差较大的问题.2019年夏季使用泵采法在九龙江河口开展原位全水层微塑料采样,对不同水层、不同站位间的微塑料丰度及其赋存特征进行分析,并与其他在该河口的相关调查研究结果进行对比.结果表明:九龙江河口表、中、底层水体中的微塑料赋存量存在明显差异,河流入海口及靠近污染源处表层水中微塑料丰度明显高于中、底层中,在潮汐作用剧烈的河口区,中、底层中微塑料丰度高于表层水中,存在明显分层现象;使用不同采样方法获取的微塑料数量浓度值存在较大差异,泵采法相比拖网法能更有效地截留塑料纤维;使用泵采法过滤水样体积、滤经筛网孔径大小都对收集到的微塑料丰度、尺寸有显著影响.采样方法的不同将导致微塑料丰度结果的显著差异,在潮汐河口进行微塑料监测有必要将潮汐作用考虑在内.因此,建议建立潮汐河口的微塑料业务化监测和通量观测,并采用洪、枯季,大、小潮的全潮时段的观测采样方法.

基于频次与极值外推综合的载荷外推总体方法

载荷外推作为载荷谱编制的重要技术手段,当前研究缺乏对于载荷外推总体方法的全面梳理、马尔可夫稳态分布的求解方法适应性不够、缺乏不同非参频次外推方法的比较与选用原则,导致不便生成高精度载荷谱以支撑装备性能设计。围绕坦克在高机动和极限工况下的载荷谱编制问题,基于某坦克行进间身管位移数据样本,分别使用基于雨流矩阵及核密度估计的非参数外推法、基于马尔可夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)的信号重构法以及Metropolis-Hastings(简称MH)直接采样法进行了载荷频次外推,并针对MCMC的信号重构法提出了一种改良马尔可夫稳态分布的求解方法。应用所提出的频次-极值相结合的载荷外推总体方法对坦克身管位移进行了频次扩充与极值预测,并结合实车试验结果验证了方法的准确性。研究结果表明:改良的马尔可夫稳态分布求解方法是有效的;在样本长度足够、外推精度要求不甚高的情况下,MH直接采样法可作为一种新的频次外推方法;运用频次-极值相结合的载荷外推总体方法所得结果精度较高;形成的频次外推法选用原则对于载荷谱编制过程中的方法选择具有一定的指导意义。研究工作为装备载荷谱的高质量编制提供了成熟的技术路线和参考。

Method of sequential mesh on Koopman-Darmois distributions

For costly and/or destructive tests,the sequential method with a proper maximum sample size is needed.Based on Koopman-Darmois distributions,this paper proposes the method of sequential mesh,which has an acceptable maximum sample size.In comparison with the popular truncated sequential probability ratio test,our method has the advantage of a smaller maximum sample size and is especially applicable for costly and/or destructive tests.

污染地块土壤调查布点及采样方法探讨

自中华人民共和国土壤污染防治法实施以来,全国各地对污染地块开展了土壤污染状况调查,在调查过程中也存在着诸多的问题,点位布设不充分、钻探深度不够、污染因子识别不全、地勘资料不齐全等现象,任一影响因素调查不充分或识别不到位均可能会对土壤调查结果产生影响。本文主要综述了污染地块土壤采样的布点与采样方法作了探讨。

基于多源信息融合的引信可靠性评估方法研究

针对高价值弹药引信利用全弹飞行试验验证其可靠性弹药价格昂贵,全弹的靶试试验量很小,且引信的可靠性指标高于全弹的可靠性指标的问题,充分地利用模拟试验数据对小子样进行重要数据补充;采用继承因子、环境因子折算数据,将不同类型的数据折合为成败型试验数据,再用CMSR方法根据系统串并联关系将多源数据融合,并将所得的数据与靶试数据结合,减少靶试试验样本量;以混合Beta分布为先验分布,得到了评估引信可靠性的Bayes方法,该法解决了模拟试验数据与靶试数据融合的问题;以某引信为应用背景进行了可靠性评估,证明该方法比经典方法减少了一定的靶场试验量。

拉普拉斯分布参数的近似贝叶斯估计

拉普拉斯分布是刻画尖峰厚尾数据的重要分布之一.本文提出拉普拉斯分布两参数具有显式解的线性近似贝叶斯估计,通过理论证明和数值模拟验证了线性近似贝叶斯估计相比其他估计的优越性,并考察了线性近似贝叶斯估计随着样本量增加的渐近性质.

基于产状Fisher分布的岩石节理最小样本容量确定方法

节理产状是影响岩体结构及其工程性质的关键参数之一,因此准确计算节理的平均产状是岩体工程性质研究的基础。由于节理产状的离散性,合理确定节理的最小样本容量对于计算节理组的平均产状具有重要意义。基于Fisher分布,阐释了节理产状随机数的生成方法,提出一种考虑“超越上半球投影产状”(OEBEUHP)的平均产状计算方法。随机生成不同数量、不同κ值的Fisher分布产状来研究节理样本容量对平均产状准确性的影响,在保证准确率不低于0.95的情况下,建立了最小样本容量与Fisher分布常数κ值的经验关系。研究结果表明:节理样本容量对平均产状的统计准确性影响显著,样本容量越大,平均产状的统计准确率越高;最小样本容量与κ值呈明显的反比例关系,反比例系数为1 007.23。通过对三峡地下厂房上游边墙和乌东德水电站平洞PD5-2节理的统计分析,验证了该经验关系的适用性,能够有效指导节理产状的采样工作。

分布式光伏接入电网净负荷不确定性潮流计算研究

在分布式光伏接入电网的情况下,由于数据量波动较大以及电网净负荷存在不确定性,可能会导致潮流计算中电压幅值、相角、有功、无功潮流期望值和标准差的平均相对误差较大。为此,提出分布式光伏接入电网净负荷不确定性潮流计算方法。计算分布式光伏接入电网后的潮流参数后,建立光伏和净负荷不确定性概率模型。引入Beta分布,以近似描述光照强度变化情况。采用中值拉丁超立方采样法采集样本,将串行计算替换为并行计算。通过改进的牛顿-拉夫逊法,执行多次潮流计算,并绘制相关指标概率密度曲线,以实现分布式光伏接入电网净负荷不确定性潮流计算。试验结果表明,所提方法电压幅值、相角、有功、无功潮流期望值和标准差平均相对误差较小,计算所用时间较短。该方法能够快速、高效地进行收敛,具有较强的鲁棒性。

黄褐天幕毛虫幼虫在山杏天然林中的空间分布格局

本研究通过调查内蒙古兴安盟地区6块山杏天然林标准地黄褐天幕毛虫虫口密度,采用6种判断空间分布格局的聚集度指标和Iwao、Talor等回归分析法对黄褐天幕毛虫幼虫的空间分布型进行了研究。结果表明:黄褐天幕毛虫幼虫的空间分布型为聚集分布,聚集的原因是由害虫本身的生物学特性和环境因子共同作用所导致。在此基础上计算出幼虫最适理论抽样数公式为N=t 2(1.0734/m+0.0041)/D 2,为黄褐天幕毛虫的调查与防治提供了科学依据。

沙棘木蠹蛾的幼虫空间分布与抽样技术

利用常用的聚集度指标 ,对沙棘木蠹蛾HolcocerushippophaecolusHua ,Chou ,FangetChen幼虫的分布进行了分析。结果显示 ,该幼虫的空间分布格局为聚集型分布。通过Iwao的m - x回归检验方程 ,确定了其最适抽样数和最佳样方大小。采用对角线、之字型、五点式、棋盘式和平行线等 5种抽样方法对沙棘木蠹蛾幼虫的抽样技术分别进行了研究 ,结果表明 :最佳的抽样方法为棋盘式。

考虑基坑开挖空间效应的邻近建筑物沉降预测方法

通过工程监测数据统计,分析了基坑开挖引起的墙后土体变形特性,再结合建筑物变形响应研究提出了一种考虑空间效应的紧邻基坑建筑物沉降简化算法.重点研究了土体变形空间分布规律,发现可以采用高斯函数对墙后土体变形空间效应进行定量描述,结果表明,基坑短边处变形空间效应不明显,长边上拐角处变形明显小于中部变形.坑后土体可划分为3个区域,不同区域空间效应分布不同,而且建筑物短边刚度对土体变形空间分布影响不大.建筑物沉降简化算法以监测数据统计规律为基础,结合变形空间分布规律可以预测邻近基坑建筑物沉降,通过经验系数γ可将土层性质、周边施工情况等纳入考量,使建筑物沉降预测更为准确.算例分析表明,本文方法计算值与实测值有较好的一致性,可为预测、分析紧邻基坑施工的建筑物沉降提供参考.