填料配比及环境因素对人工湿地去除氨氮效果的影响

选择火山灰、沸石和无烟煤作为人工湿地除氨氮填料,对不同比配的填料进行污水除氨氮吸附实验,筛选出最优填料配比。并对最优配比方案进行了p H值、有机质对去除氨氮的影响实验。实验结果证明火山灰、沸石和无烟煤的配比为1:1:2时处理污水中的氨氮效果最好。p H值在4~7范围内去除氨氮效果理想,有机质草酸对去除氨氮影响不大、但有葡萄糖存在时去除氨氮效果明显降低。     

细沟形成对坡面产流产沙过程的影响

为探明细沟形成条件下不同土壤坡面水沙变化特性,利用室内模拟降雨试验,分析了塿土和黄绵土在细沟发育及已有细沟条件下的水沙过程变化规律。结果表明,塿土产流快,易形成细沟,细沟发育有明显的规律性,在坡面上呈平行状分布,细沟密度与坡度密切相关,细沟存在会延长产流时间;黄绵土产流慢,较难形成细沟,细沟发育随机性大。细沟发育对产流过程没有明显影响,土壤入渗快慢是两种土壤产流过程存在差异的主要原因。细沟发育程度加剧,会使塿土含沙量的增加速度加快,达到稳定含沙量的时间提前,坡面已有细沟只对稳定含沙量有明显影响,细沟密度增加会使稳定含沙量提高;黄绵土含沙量的变化主要取决于细沟发育过程中的随机性,当细沟侵蚀以崩塌作用为主时,含沙量会出现急剧增加,即使雨强较小,也会产生严重的土壤侵蚀。     

人工挖孔扩底灌注CFG桩复合地基的设计与应用

在一些特殊的地层结构上建造建筑物,如何选择基础型式或地基处理方法,是工程顺利实施的关键.通过人工挖孔扩底灌注CFG桩复合地基在北京某地基处理的工程实践,介绍了人工挖孔扩底灌注CFG桩设计计算、施工工艺、加固机理及适用范围,为北京地区同类地基处理工程设计和施工提供了有益的借鉴.     

Height prediction of water flowing fractured zones based on BP artificial neural network

Factures caused by deformation and destruction of bedrocks over coal seams can easily lead to water flooding (inrush) in mines, a threat to safety production. Fractures with high hydraulic conductivity are good watercourses as well as passages for inrush in mines and tunnels. An accurate height prediction of water flowing fractured zones is a key issue in today's mine water prevention and control. The theory of leveraging BP artificial neural network in height prediction of water flowing fractured zones is analysed and app-lied in Qianjiaying Mine as an example in this paper. Per the comparison with traditional calculation results, the BP artificial neural network better reflects the geological condi-tions of the research mine areas and produces more objective, accurate and reasonable results, which can be applied to predict the height of water flowing fractured zones.     

基于核混合效应回归模型的地震数据预测

针对地震观测数据难以准确预测的难题,提出基于核混合效应回归模型。为验证该算法模型的可行性,结合湖北地震台站地球物理仪器产出数据开展仿真实验,并与传统的神经网络算法作对比。结果表明,该模型能准确预测地震地球物理观测数据且性能优于其他神经网络算法,对水温、水位数据的预测相对误差低于0.05%及0.48%。该研究为地震监测预报人员积累、分析地震基础数据提供了全新思路,同时也为较复杂的深度学习类算法框架模型的构建提供了实践基础。     

土壤水分微波反演方法进展和发展趋势

土壤水分是连接地表水循环和能量循环的关键参量,精确获取该参量对于理解气候变化、地表水文过程、地气间能量交换机理等具有重要意义。微波遥感由于其较为合适的探测深度和坚实的理论基础在观测地表浅层土壤水分上具有很大优势,结合反演方法可以获取空间连续的土壤水分含量,有助于更加客观认知土壤水分的时空演变机理。随着微波遥感数据的不断丰富,多种微波遥感土壤水分反演方法相继涌现,为了更好地了解其发展和趋势,本文总结了当前土壤水分微波反演常用的卫星遥感数据并分析其发展趋势,后从主动微波反演、被动微波反演和多源协同反演3个方面梳理了各类土壤水分微波反演方法的原理、发展和优缺点,最终总结出目前微波遥感土壤水分反演方法的发展趋势：即土壤水分微波反演方法的时空普适性逐渐增强、面向高时空分辨率的土壤水分微波协同反演方法快速发展以及土壤水分微波反演方法的智能化水平不断提高。     

Analysis of effects of operating parameters on rate of penetration in drilling process with air down-the-hole hammer

Air down-the-hole(DTH)hammer drilling has long been recognized to have the potential of drilling faster than conventional rotary drill,especially in some hard rocks such as granite,sandstone,limestone,dolomite,etc.with the same weight on bit(WOB)and rotations per minute(RPM).So,it has been widely used in many drilling fields including mineral resource exploration drilling,oil and gas drilling and geothermal drilling.In order to reduce drilling cost by selecting optimal drilling parameters,rate of penetration(ROP)should be estimated accurately and the effects of different factors on ROP should be analyzed.In this research,ANN model with several multi-layer perception back propagation(BP)networks for predicting ROP of air DTH hammer drilling was developed using controllable parameters such as impact energy,impact frequency,WOB,RPM and bit operating time for the formations with a certain drillability index of rock.Several BP neural networks with the different neurons in hidden layers were developed and compared for selecting optimal architecture of ANN.The effects of the drilling parameters such as impact energy,impacting frequency,WOB,RPM and bit operating time on the ROP of air DTH hammer drilling were investigated by trained ANN.From the analyses,the optimum range of drilling parameters for providing high ROP were determined and analyzed for a formation with a certain drillability index of rock.The methodology proposed in this study can be used in many mathematical problems for optimization of drilling process with air DTH hammer.     

Analytical theory of a lunar artificial satellite with third body perturbations

We present here the first numerical results of our analytical theory of an artificial satellite of the Moon. The perturbation method used is the Lie Transform for averaging the Hamiltonian of the problem, in canonical variables: short-period terms (linked to l, the mean anomaly) are eliminated first. We achieved a quite complete averaged model with the main four perturbations, which are: the synchronous rotation of the Moon (rate ), the oblateness J ₂ of the Moon, the triaxiality C ₂₂ of the Moon ( ) and the major third body effect of the Earth (ELP2000). The solution is developed in powers of small factors linked to these perturbations up to second-order; the initial perturbations being sorted ( is first-order while the others are second-order). The results are obtained in a closed form, without any series developments in eccentricity nor inclination, so the solution apply for a wide range of values. Numerical integrations are performed in order to validate our analytical theory. The effect of each perturbation is presented progressively and separately as far as possible, in order to achieve a better understanding of the underlying mechanisms. We also highlight the important fact that it is necessary to adapt the initial conditions from averaged to osculating values in order to validate our averaged model dedicated to mission analysis purposes.     

曼氏无针乌贼(Sepiella japonica)促性腺激素释放激素(GnRH)基因的鉴定、特征及成熟期的表达研究

促性腺激素释放激素（GnRH）在脊椎动物的繁殖过程中起着至关重要的作用,同时也存在于许多无脊椎动物中。利用cDNA末端快速扩增技术（RACE）克隆出曼氏无针乌贼（Sepiella japonica）促性腺激素释放激素（命名为SjGnRH,KP 982885.1）。SjGnRH基因的cDNA全长710 bp,开放阅读框（ORF）为273 bp,编码90个氨基酸,包括一条含有31个氨基酸的信号肽、12个氨基酸的GnRH多肽和44个氨基酸的GnRH相关肽（GAP）;SjGnRH与剑尖枪乌贼（Uroteuthis edulis）和真蛸（Octopus vulgaris）的同源性分别为86.7%和73.3%;SjGnRH高度保守的十二肽与剑尖枪乌贼和真蛸的octGnRH相似度达100%,其信号肽的相似性分别为66.7%和54.8%,GAP区的相似性分别为95.5%和77.3%;实时荧光定量PCR（qRT-PCR）结果显示,SjGnRH基因在成熟期的表达具有特异性,在脑中表达量最高,且与其他组织差异显著（P<0.05）;采用原位杂交技术检测SjGnRH mRNA在脑内的表达模式,结果表明：SjGnRH在食道上神经团、食道下神经团和视叶的不同部位均有表达,暗示SjGnRH可能参与曼氏无针乌贼的生殖调控作用。     

基于GIS的人工神经网络矿产预测系统设计及应用

利用地理信息系统(GIS)和人工神经网络(ANN)相结合，研究了基于GIS的人工神经网络矿产预测系统设计方案，实现了从地质变量优选到人工神经网络成矿预测结果图形显示的计算机自动化处理。在凤凰山矿田的应用显示，预测结果与现有矿床十分吻合，是矿产预测的有效方法。