Selection of prior distributions and multiscale analysis in Bayesian temperature reconstructions based on fossil assemblages

It is possible to reconstruct the past variation of an environmental variable from measured historical indicators when the modern values of the variable and the indicators are known. In a Bayesian statistical approach, the selection of a prior probability distribution for the past values of the environmental variable can then be crucial and the selection therefore should be made carefully. This is particularly the case when the data are noisy and the statistical model used is complex since the influence of the prior on the results can then be especially strong. It can be difficult to elicit the prior probability distribution from the available information, since usually there are no measured data on the past values of the variable one wants to reconstruct and different reconstructions are typically consistent with each other only at a coarse level. To overcome these difficulties we propose to use a non-informative smoothing prior, possibly in combination with an informative prior, that simply penalizes for roughness of the reconstruction as measured by the variability of its values. We believe that it can sometimes be easier to set an overall prior distribution on the roughness than to agree on a prior for the actual values of the reconstructed variable. Note that by using a smoothing prior one incorporates into the model itself the smoothing step usually done before or after the actual numerical reconstruction. Another idea proposed in this paper is to integrate the reconstruction model with a multiscale feature analysis technique known as SiZer. Multiscale analysis of the posterior distribution of the reconstructed variable makes it possible to infer its statistically significant features such as trends, maxima and minima at several different time scales. While only temperature is considered in this paper, the technique can be applied to other environmental variables.     

“刚柔”钻具组合在新疆油田八区的应用

在易斜地层钻进时，带稳定器的钟摆防斜钻具组合的防斜效果往往不甚理想。通过计算和实践，发现“刚柔”钻具组合钟摆力强、防斜降斜效果好，而且可在常压下钻进，既保证了井身质量又提高了机械钻速。为大倾角硬地层易斜区防斜打快提供了一种新型的钻具组合类型。     

Fast ensemble smoothing

Smoothing is essential to many oceanographic, meteorological, and hydrological applications. There are two predominant classes of smoothing problems. The first is fixed-interval smoothing, where the objective is to estimate model states within a time interval using all available observations in the interval. The second is fixed-lag smoothing, where the objective is to sequentially estimate model states over a fixed or indefinitely growing interval by restricting the influence of observations within a fixed window of time ahead of the evolving estimation time. In this paper, we use an ensemble-based approach to fixed-interval and fixed-lag smoothing, and synthesize two algorithms. The first algorithm is a fixed-interval smoother whose computation time is linear in the interval. The second algorithm is a fixed-lag smoother whose computation time is independent of the lag length. The complexity of these algorithms is presented, shown to improve upon existing implementations and verified with identical-twin experiments conducted with the Lorenz-95 system. Results suggest that ensemble methods yield efficient fixed-interval and fixed-lag smoothing solutions in the sense that the additional increment for smoothing is a small fraction of either filtering or model propagation costs in a practical ensemble application. We also show that fixed-interval smoothing can perform as fast as fixed-lag smoothing, and it may not be necessary to use a fixed-lag approximation for computational savings alone.     

On unbiased backtransform of lognormal kriging estimates

Lognormal kriging is an estimation technique that was devised for handling highly skewed data distributions. This technique takes advantage of a logarithmic transformation that reduces the data variance. However, backtransformed lognormal kriging estimates are biased because the nonbias term is totally dependent on a semivariogram model. This paper proposes a new approach for backtransforming lognormal kriging estimates that not only presents none of the problems reported in the literature but also reproduces the sample histogram and, consequently, the sample mean.     

基于黄土物理化学性质变化的固化土强度影响因素分析

基于黄河中游地区黄土自西北向东南分布变化的规律,研究黄土的物理化学性质和矿物成分对水泥基土壤固化剂固化土无侧限抗压强度的影响。试验结果表明：随着黏粒含量的增加,固化土的强度先降低后增加,其中黏粒含量17.0%是分界点;随着碱度的增加,固化土的强度增加;蒙脱石的加固效果好于伊利石,在以伊利石为主的土中,随着伊利石含量的增加,固化土的强度升高;随着阳离子交换总量的增加和交换性钠离子百分比的降低,固化土的强度增加。研究表明,黄土的物理化学性质不同是水泥基土壤固化剂土质适宜性产生的主要原因;黄河中游地区自西北向东南加固土的强度具有增大的规律性     

粘土矿物改性在岩土工程中的应用

１　问题的提出粘土矿物广泛存在于各种地质体中。特殊的晶体结构赋予粘土矿物许多特性。例如吸水性、膨胀性、可塑性、离子交换性和吸附性能等等。粘土的高比表面积使其具有较强的活性。目前矿物学家和材料学家的兴趣主要集中在研究粘土矿物的表面物理化学性质,采用各种方法改变和提高其活性,扩展它的应用范围,提高粘土的附加值。但是,在岩土力学工程中,却要抑制和降低粘土矿物的活性,特别是与水的结合能力。在工程界,凡涉及岩土工程的领域,都有一个灾害防治（包括地质灾害和工程灾害）和软基处理问题,其中重点处理和防治的对象就…     

新型固化材料在软土地区的应用探索

土加固技术经过近100年的发展,应用范围广泛,近20年来也出现了许多新型的加固材料。针对上海软土地基特点,通过对室内试验进行分析、室外原位搅拌桩施工、钻探取芯及芯样试验,分析了软土固化专用水泥这一新型固化材料的适用性,并提出一些相应的应用建议,以促进上海这类软土地基加固土技术的进一步应用发展。     

Image Stabilization System for Hinode (Solar-B) Solar Optical Telescope

The Hinode Solar Optical Telescope (SOT) is the first space-borne visible-light telescope that enables us to observe magnetic-field dynamics in the solar lower atmosphere with 0.2 – 0.3 arcsec spatial resolution under extremely stable (seeing-free) conditions. To achieve precise measurements of the polarization with diffraction-limited images, stable pointing of the telescope (<0.09 arcsec, 3σ) is required for solar images exposed on the focal plane CCD detectors. SOT has an image stabilization system that uses image displacements calculated from correlation tracking of solar granules to control a piezo-driven tip-tilt mirror. The system minimizes the motions of images for frequencies lower than 14 Hz while the satellite and telescope structural design damps microvibration in higher frequency ranges. It has been confirmed from the data taken on orbit that the remaining jitter is less than 0.03 arcsec (3σ) on the Sun. This excellent performance makes a major contribution to successful precise polarimetric measurements with 0.2 – 0.3 arcsec resolution. K. Kobayashi now at NASA/Marshall Space Flight Center, Huntsville, AL 35812, USA.     

元坝地区珍珠冲地层新型三牙轮钻头的研制与应用

砂砾岩地层是钻井工程中的难钻地层,如何提高砂砾岩地层的钻进效率和钻头寿命一直是工程实践中的重要问题。针对在元坝地区珍珠冲石英砂砾岩地层钻进过程中,使用普通型牙轮钻头外排齿易早期断齿、综合使用指标低的问题,开展了地层岩性、钻头使用与失效分析。针对性地开展了钻头的切削结构、齿材优化以及加强保径等方面的研究,优化设计、研制出HJT547GKL型新型三牙轮钻头。现场试用结果表明,这种新型牙轮钻头在元坝地区珍珠冲组石英砂砾岩地层钻进中有较高的行程进尺。该钻头是一种结构简单、扶正保径好、可靠实用,适用于较硬、有硬夹地层的新型实用三牙轮钻头。     

DATA ANALYSIS IN THE SHOT NOISE LIMIT.PART Ⅲ:ADAPTIVE DATA SMOOTHING FILTERS

Digital filter smoothing methods for shot-noise-limited data are addressed in this study.The preferredmethod is based on a Gaussian filter in which the width of the Gaussian filter function is varied dependingon the estimate of the second derivative of the raw data.This filter is developed from the standpoint ofmaximum likelihood parameter estimation of the probability density function which describes shot-noise-limited data.The smoothing filter is tested and compared with the conventional sequential regressionfilter.This adaptive Gaussian smoothing filter works better than both the sequential regression and theadaptive Gaussian filter derived for normal noise.For data containing both high-and low-frequencycomponents,the limiting step in the adaptive filter is an estimation of the smoothing interval.Methodsfor determining an optimum smoothing interval are discussed.With the optimized smoothing interval,the adaptive Gaussian filter works well for data sets with a wide range of varying frequency components.In particular,synthetic data typical of atomic emission spectra are used to test this smoothing filter.