Effect of weighting materials on carbonation of oil well cement-based composites under high temperature and CO2-rich environment

As an indispensable part of cement slurry for high temperature and high pressure oil and gas wells, weighting materials have a significant impact on the carbon dioxide corrosion of oil well cement-based composites.This paper studied the carbonation process of cement with three weighting agents, and evaluated the compressive strength and carbonation depth of cement at 150 ℃. XRD, SEM and MIP were used to study the carbonation mechanism of cement. When 21 days of carbonation, the carbonation depth growth rate of hausmannite cement was 0.21 mm/d, hematite cement was 0.24 mm/d, and barite cement was 0.31 mm/d. The compressive strength of cement decreased after carbonation,and the carbonation had a minor influence on the compressive strength of hausmannite cement and the most significant impact on barite cement. The carbonation product of oil well cement was mainly calcite. Unstable vaterite mainly existed in the barite cement sample, indicating that the barite cement sample was the most serious corrosion. In the carbonation zone, the number of pores smaller than 10 nm increased the most in the hausmannite cement sample. Pores with a diameter greater than 100 nm accounted for 1.9 % in the hausmannite cement, 3.0 % in hematite cement, and 4.8 % in barite cement. The result shows that hausmannite is the most conducive to the corrosion resistance of oil well cement.     

Analysis and use of fragment-occurrence data in similarity-based virtual screening

Current systems for similarity-based virtual screening use similarity measures in which all the fragments in a fingerprint contribute equally to the calculation of structural similarity. This paper discusses the weighting of fragments on the basis of their frequencies of occurrence in molecules. Extensive experiments with sets of active molecules from the MDL Drug Data Report and the World of Molecular Bioactivity databases, using fingerprints encoding Tripos holograms, Pipeline Pilot ECFC_4 circular substructures and Sunset Molecular keys, demonstrate clearly that frequency-based screening is generally more effective than conventional, unweighted screening. The results suggest that standardising the raw occurrence frequencies by taking the square root of the frequencies will maximise the effectiveness of virtual screening. An upper-bound analysis shows the complex interactions that can take place between representations, weighting schemes and similarity coefficients when similarity measures are computed, and provides a rationalisation of the relative performance of the various weighting schemes.     

基于多孔径闪烁的湍流强度廓线反演方法研究

以多孔径闪烁方法的理论为基础,分别讨论了孔径滤波函数和光谱响应函数对权重函数的影响.根据包括边界层项的Hufnagel-Valley 5/7模型得到的闪烁指数,采用奇异值分解法反演了垂直方向的湍流强度廓线,结果的量级介于10~(-15)~10~(-17)之间,并随高度的增加不断减小,在量级和趋势上与理论模型基本一致;同时结合Shack-Hartman的实际测量结果,反演了水平方向1 km传输路径上的湍流强度分布状况.水平方向反演结果的量级在10~(-14)~10~(-15)之间,随传播距离的变化趋势与实验场地的实际情况较为符合,随时间的变化趋势与合肥地区同期的统计结果基本一致.     

On the choice of parameters for the weighting method in vector optimization

We present a geometrical interpretation of the weighting method for constrained (finite dimensional) vector optimization. This approach is based on rigid movements which separate the image set from the negative of the ordering cone. We study conditions on the existence of such translations in terms of the boundedness of the scalar problems produced by the weighting method. Finally, using recession cones, we obtain the main result of our work: a sufficient condition under which weighting vectors yield solvable scalar problems. An erratum to this article can be found at     

Image segmentation based on hierarchical belief propagation with variable weighting parameters

The belief propagation (BP) algorithm is an efficient way to minimize the MRF energy for image segmentation. This paper proposes a hierarchical BP algorithm with variable weighting parameters (HBP-VW) to improve the segmentation accuracy of the BP-based algorithms. In the HBP-VW, two variable weighting parameters are introduced, the global parameter and the local parameter. The global parameter is used to overall adjust the influence of each part in the message update rule. The local parameter is designed to describe the local texture pattern for each site. Texture, remote sensing, and nature images are employed to test the proposed algorithm. Experimental results illustrate a better segmentation accuracy compared with other BP-based algorithms.     

m相依样本均值的Bootstrap及其随机加权逼近的收敛速度

本文研究了ｍ相依样本均值的Ｂｏｏｔｓｔｒａｐ及随机加权逼近问题，讨论了有关收敛速度。     

Analytic evaluation of the weighting functions for remote sensing of blackbody planetary atmospheres: a general linearization approach

An analytic approach is proposed for the evaluation of weighting functions for remote sensing of a blackbody planetary atmosphere based on straightforward, general linearization. In the present paper, this approach is applied to the case of remote sensing with the nadir (down-looking) geometry. Expressions for weighting functions for various atmospheric parameters are derived. It is demonstrated that in a realistic case of temperature-dependent atmospheric absorption, an additional term appears in the expression for the temperature weighting function which contains the temperature derivative of the atmospheric absorption coefficient. The approach is applied to the case of a semi-infinite atmosphere and then, to the atmosphere of a finite optical depth with the underlying surface. In this, latter case, the expressions are also obtained for partial derivatives of observed radiances with respect to surface parameters: surface pressure, temperature and emissivity.     

Estimation of the uncertainty of mass measurements from in-house calibrated analytical balances

The uncertainty evaluation of mass measurements when using “in-house” calibrated analytical balances is revisited according to the Guide to the expression of Uncertainty Measurement (GUM). The calibration of analytical balances is discussed according to the guidelines of several bodies such as ASTM, UKAS and DKD/PTB. The remainder components of uncertainty can be estimated from the balance data sheet specifications.     

A comparison of location estimators for interlaboratory data contaminated with value and uncertainty outliers

While estimation of measurement uncertainty (MU) is increasingly acknowledged as an essential component of the chemical measurement process, there is little agreement on how best to use even nominally well-estimated MU. There are philosophical and practical issues involved in defining what is “best” for a given data set; however, there is remarkably little guidance on how well different MU-using estimators perform with imperfect data. This report characterizes the bias, efficiency, and robustness properties for several commonly used or recently proposed estimators of true location, μ, using “Monte Carlo” (MC) evaluation of “measurement” data sets drawn from well-defined distributions. These synthetic models address a number of issues pertinent to interlaboratory comparisons studies. While the MC results do not provide specific guidance on “which estimator is best” for any given set of real data, they do provide broad insight into the expected relative performance within broadly defined scenarios. Perhaps the broadest and most emphatic guidance from the present study is that (1) well-estimated measurement uncertainties can be used to improve the reliability of location determination and (2) some approaches to using measurement uncertainties are better than others. The traditional inverse squared uncertainty-weighted estimators perform well only in the absence of unrepresentative values (value outliers) or underestimated uncertainties (uncertainty outliers); even modest contamination by such outliers may result in relatively inaccurate estimates. In contrast, some inverse total variance-weighted-estimators and probability density function area-based estimators perform well for all scenarios evaluated, including underestimated uncertainties, extreme value outliers, and asymmetric contamination.     

Relationship between different approaches to derive weighting functions related to atmospheric remote sensing problems

The paper is devoted to the investigation of the relationship between different methods used to derive weighting functions required to solve numerous inverse problems related to the remote sensing of the Earth's atmosphere by means of scattered solar light observations. The first method commonly referred to as the forward-adjoint approach is based on a joint solution of the forward and adjoint radiative transfer equations and the second one requires the linearized forward radiative transfer equation to be solved. In the framework of the forward-adjoint method we consider two approaches commonly used to derive the weighting functions. These approaches are referenced as the “response function” and the “formal solution” techniques, respectively. We demonstrate here that the weighting functions derived employing the formal solution technique can also be obtained substituting the analytical representations for the direct forward and direct adjoint intensities into corresponding expressions obtained in the framework of the response function technique. The advantages and disadvantages of different techniques are discussed.