基于OpenSSH实现Windows与Linux平台间的安全文件传输

OpenSSH是一种典型的C/S构架,是一种很实用的网络安全解决方案.这里分析讨论OpenSSH的原理、认证方法及无人值守系统的实现,通过实例说明OpenSSH如何实现Windows与Linux平台间的安全文件传输.     

A New Solution Assessment Approach and Its Application to Space Geodesy Data Analysis

The statistics of the residuals are used in this paper to perform a quality assessment of the solutions from space geodesy data analysis. With the stochastic estimation and the relatively arbitrary empirical parameters being employed to absorb unmodelled errors, it has long been noticed that different estimate combinations or analysis strategies may achieve the same level of fitting yet result in significantly different solutions. Based on the postulate that no conceivable signals should remain in the residuals, solutions of the same level of root mean square error (RMS) and variance–covariance may be differentiated in the sense that for reasonable solutions, the residuals are virtually identical with noise. While it is possible to develop complex noise models, the Gaussian white noise model simplifies the solution interpretation and implies the unmodelled errors have been smoothed out. Statistical moments of the residuals as well as the Pearson chi-square are computed in this paper to measure the discrepancies between the residuals and Gaussian white noise. Applying to both satellite laser ranging (SLR) and global positioning system (GPS) data analysis, we evaluate different parameter estimate combinations and/or different strategies that would be hardly discriminated by the level of fitting. Unlike most solution assessment methods broadly termed as external comparison, no information independent of the data analyzed is required. This makes the immediate solution assessment possible and easy to carry out. While the external comparison is the best and most convincing quality assessment of the solution, the statistics of the residuals provide important information on the solutions and, in some cases as discussed in this paper, can be supported with external comparison.     

关于数值求解天体运动方程的几个问题

本文讨论三个问题：1.在采用各种非辛（Symplectic）的数值积分器积分天体运动方程时，截断误差将引起人为的能量耗散，这一问题是不能用简单地在相应的力模型中加进一个人为的阻力因子而得以解决的，被歪曲的能量（或数值轨道）必须在积分过程的每一步用能量关系来进行校正，此即能量控制方法．2.当摄动加速度涉及到坐标轴的旋转时，如何在各种积分器中采用能量控制方法．3.对于大偏心率轨道，用数值方法求解相应运动方程时，积分步长必须随运动天体与中心天体之间的距离变化而改变，显然，这对所有积分器都是不方便的，特别是多步积分器．本义给出了一种步长均匀化的处理，可以使上述大偏心率轨道积分问题按定步长计算．     

考虑后牛顿效应的二体问题的解和星历计算

本文给出考虑后牛顿(PN)效应的二体问题解所对应的基本关系式,并仿照开普勒(Kepler)运动,给出星历表计算方法和相应的计算公式以及适用于数值研究中的简单形式。     

GPS应用于地球动力学研究的进展

介绍了GPS卫星系统的现代化以及IGS(International GPS Service)的最新研究成果；重点介绍了GPS技术在地球动力学研究中，包括国际地球参考架的建立与维护，固体地球形变和海平面变化的监测，科学卫星轨道的确定以及全球和中国地壳运动、地球定向参数的监测，GPS在大气研究和气象预报中的最新进展；评述了GPS技术目前存在的问题，包括与SLR测量之间存在的系统偏差、GPS技术本身可能存在的周年变化和GPS卫星天线相位中心的变化。     

钢筋混凝土预制拼装柱扭转力学性能数值模拟与参数分析

采用ABAQUS大型有限元分析软件开展预制拼装柱扭转力学性能数值模拟及参数分析,研究了轴压比、灌浆套筒位置及长度、预制构件拼接缝界面黏结强度对灌浆套筒连接中柱抗扭性能的影响。研究结果表明:轴压比会显著影响预制拼装柱抗扭承载力和变形,而灌浆套筒位置和长度对预制拼装柱抗扭力学性能的影响不明显;预制构件拼接缝界面黏结强度显著影响预制拼装柱抗扭性能。基于预制拼装构件和现浇构件力学性能的对比分析,提出了轴向荷载和扭矩共同作用下灌浆套筒连接预制拼装柱抗扭承载力设计方法。     

安徽长江经济带地热资源赋存特征及潜力评价

【研究目的】安徽长江经济带地热资源储量丰富,未来开发利用前景好,对该区域进行地热资源评价可为安徽省能源结构优化及地热资源可持续开发利用提供科学依据。【研究方法】在分析研究区地质构造、地层岩性、地热流体水化学类型等地质与水文地质条件的基础上,揭示了安徽长江经济带地热资源概况及分布特征,探讨了隆起山地对流型和沉积盆地传导型地热资源的赋存特征,并对其储量及开发利用潜力进行评价。【研究结果】安徽长江经济带地热资源热储主要赋存在巢湖—和县基岩隆起区、大别山隆起区、沿江基岩隆起区、江南隆起等隆起山地及定远断陷盆地、肥东断陷盆地、霍山—九井盆地、庐枞断陷盆地、安庆断陷盆地、宣城断陷盆地等沉积盆地。前者隆起区热储类型为带状,岩性以断裂破碎带中花岗岩为主,后者断陷盆地热储类型为层状及层状兼带状,岩性以砂岩和碳酸盐岩为主。带内热储主要为偏硅酸·氟热矿水,隆起山地型地热流体水化学类型主要为SO₄、HCO₃型水,沉积盆地型地热流体水化学类型主要为HCO₃型水。通过潜力评价可知,隆起山地型地热资源潜力较小,且处于开发利用状态的地热田基本处于超采状态;沉积盆地型地热资源潜力相对较大,其中潜力大、中和小的盆地分别有4处、6处和10处。【结论】安徽长江经济带区域内地热资源潜力分布不均,地热资源需要分区规划利用,并且需要考虑高氟、高矿化度热矿水利用造成的地表水环境污染。     

A large-scale obliquely inclined bedding rockslide triggered by heavy rainstorm on the 8th of July 2020 in Shiban Village,Guizhou, China

A large-scale obliquely inclined bedding rockslide, activated by a heavy rainstorm, occurred on July 8, 2020, at 7:05 (UTC?+?8) in Shiban Village, Songtao Miao Autonomous County, Guizhou Province, China. The loss of life in this event was greatly reduced owing to the local warning system for rainstorm-induced geohazards. To understand the failure characteristics, triggering factors, the genetic mechanism of the landslide, the geomorphological features, geological characteristics, hydrological conditions, and rainfall characteristics were systematically studied by a synthetic approach including field investigations, satellite imagery, unmanned aerial vehicle (UAV) photography, laboratory tests, and rainfall data statistics. The results indicated that the interface between the soft and hard rock, the well-developed joints, and the free face in front of the slope constituted the boundaries of this landslide. The concave topography at the back and southern edge of the landslide, the bare ground, and the cataclastic structure of the rock mass provided favorable conditions for the collection or infiltration of rainwater. The concentrated rainstorm was the direct trigger for the landslide, which led to a rapid inflow and retention of rainfall in the landslide through favorable landform and geological conditions. The groundwater recharge that cannot be drained in time caused the mechanical deterioration of rock mass and induced a rapid increase in pore water pressure in the landslide. Moreover, the water level of the Ganlong River at the toe of the slope also rose rapidly, and the uplift pressure in front of the slope increased accordingly. Under the combined action of these adverse factors, the overall anti-sliding force of the slope was less than the sliding force, finally resulting in the landslide. Remarkably, the local warning system for rainstorm-induced geohazards successfully forecasted the landslide, but the shortcoming is that the forecast time in advance is short. Nevertheless, the prediction has significantly reduced human casualties and provided valuable experience for the prediction of this type of landslide.

     

Comparison of interpolation models for estimating heavy metals in soils under various spatial characteristics and sampling methods

Heavy metal pollution in soils has become increasingly challenging, especially in developing countries. Estimating the spatial distribution of heavy metals in soils is essential to preventing their build‐up. This article aims to identify the effects of spatial scales, spatial autocorrelation, sampling methods, and proportion on interpolation models in estimating the distribution of heavy metals in soils. Six interpolation models (area‐and‐point kriging, AAPK; inverse distance weighting, IDW; local polynomial interpolation, LP; ordinary kriging, OK; simple kriging, SK; and thin plate spline, TPS), three sampling methods (random, stratified, and systematic sampling), and five sampling proportions (1, 5, 10, 15, and 20%) are considered in this study using sets of simulated data, and the real situation was tested for verification. The results show that, in general, with the increase of spatial autocorrelation or the sampling percentage, the accuracy and stability of different interpolation models gradually increase; however, the various interpolation models have their own specific characteristics and application conditions. The best application conditions of the interpolation models compared with other models under the same situation are summarized and explained in theory. These conclusions have implications for future work.