水文序列相依变异识别的RIC定阶准则——以自回归模型为例

水文过程相依性是水文变异的主要表现形式之一,应用自回归模型对其进行拟合时合理确定模型阶数是一个难点问题。本文在分析AIC和BIC准则的基础上,提出了一种以原序列与其相依成分的相关系数作为拟合度指标,同时借用信息熵形式的函数式,作为模型不确定性度量指标的自回归模型定阶准则(简称RIC准则)。以AR(1)、AR(2)、AR(3)和AR(4)模型为例进行统计试验,将不同序列长度下该准则的定阶准确率与其他定阶准则进行比较,试验结果表明,RIC准则对于上述模型均具有较好的适应性,且定阶准确率远高于AIC准则,其中对于前三阶模型RIC准则优于BIC准则,但四阶模型略低于BIC准则。RIC准则的优势是可以同时满足模型定阶、相依程度分级与模型检验的需求,将其应用于实测水文序列分析,结果显示,该准则能较准确地识别自回归模型的阶数,且符合提出的"相依有变异而残差无变异的最小阶数"的检验标准。     

Simultaneous accommodation of Dy3+ at the lattice site of β-Ca3(PO4)2 and t-ZrO2 mixtures: Structural stability,mechanical, optical,and magnetic features

Structurally stable β-Ca₃(PO₄)₂/t-ZrO₂ composite mixtures with the aid of Dy³⁺ stabilizer were accomplished at 1500°C. The precursors comprising Ca²⁺, P⁵⁺, Zr⁴⁺, and Dy³⁺ have been varied to obtain five different combinations. The results revealed the fact that complete phase transformation of calcium-deficient apatite to β-Ca₃(PO₄)₂ occurred only at 1300°C, whereas the evidence of t-ZrO₂ crystallization is obvious at 900°C. The dual occupancy of Dy³⁺ at β-Ca₃(PO₄)₂ and t-ZrO₂ structures was evident; however, Dy³⁺ initially prefers to occupy β-Ca₃(PO₄)₂ lattice until its saturation limit and thereafter accommodates at the lattice site of ZrO₂. The typical absorption and emission behavior of Dy³⁺ were noticed in all the systems and, moreover, the surrounding symmetry of Dy³⁺ domains has been determined from the luminescence study. All the systems ensured paramagnetic response that is generally contributed by the presence of Dy³⁺. A gradual increment in the phase content of t-ZrO₂ in the composite mixtures ensured a significant improvement in the hardness and Young's modulus of the investigated compositions.     

某油田油井采出水腐蚀因素研究

我国油田油井生产中采油井管柱腐蚀现象十分普遍,所以在注CO_2驱进行开采过程中要进行采出水的质量分析。对现阶段的油田生产腐蚀及防腐技术进行论述,提出相对应的防腐措施,进一步为油田生产作业提高产量。     

Modelling consumer choice through the random regret minimization model: An application in the food domain

In line with findings on post-purchase food-choice regret, one can expect that pre-purchase anticipated regret with respect to forgone (non-chosen) alternatives has an impact on consumer food choices, especially when the choice is considered to be important. The traditional Random Utility Maximization (RUM) models for discrete choices may not fully capture this impact. This study investigates the usefulness and potential in the food domain of a discrete choice model that follows the regret minimization principle, the Random Regret Minimization (RRM) model, as an alternative and complement to existing RUM models. The two models are applied to consumer stated choices of cheese in a choice experiment. The study also investigates whether and to what extent a number of personality traits determine whether particular consumers rather choose according to utility-maximization, or regret-minimization principles. Results show that at the aggregate level the two models have a similar goodness of fit to the data and prediction ability. Still, each of them shows better fit for particular subgroups of consumers, based on personality traits. Hence, the present study reveals a potential for the RRM model applications in the food domain, and adds to the empirical literature supporting previous findings on the RRM model found in other contexts. Further research is needed to explore in which situations and for which consumer segments the RRM model is the most useful model.     

Modified embedded-atom method interatomic potential for the Mg–Zn–Ca ternary system

Mg–Zn–Ca alloys are representative Mg alloys with high formability at room temperature. Their high formability is thought to be related to slip, twinning, and recrystallization of the alloys, but the detailed mechanisms have not yet been clarified. To enable atomistic simulations for investigating those behaviors, an interatomic potential for the Mg–Zn–Ca ternary system was developed. The development was based on the second nearest-neighbor modified embedded-atom method formalism, combining previously developed Mg–Zn and Mg–Ca potentials with the newly developed Zn–Ca binary potential. The Zn–Ca and Mg–Zn–Ca potentials reproduce structural, elastic, and thermodynamic properties of compounds and solution phases of relevant alloy systems in reasonable agreement with experimental data, first-principles and CALPHAD calculations. The applicability of the developed potentials is demonstrated through calculations of the effects of Zn and Ca solutes on the generalized stacking fault energy for various slip systems, segregation energy on twin boundaries, and volumetric misfit strain.     

Combination of vegetable soup and glucan demonstrates synergistic effects on macrophage-mediated immune responses

Vegetable soup (VS), a plant-based functional food, has been used as a traditional folk medicine and is attracting attention for its ability to enhance the immune response. β-Glucan, a well-established and effective immunomodulator, has synergistic effects when used in combination with some bioactive compounds. In the present study, we aimed to evaluate the synergistic immunomodulatory effects of the combination of VS and β-glucan on macrophage-mediated immune responses. β-Glucan was demonstrated to synergistically enhance the VS-stimulated immune response, including the production of interleukin-6, tumor necrosis factor-α, and nitric oxide, mainly through the mitogen-activated protein kinase pathway in macrophages. In addition, this combination has the potential for further development in functional foods with immune-enhancing activity.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10068-021-00888-x.     

海上稠油油田蒸汽吞吐产量确定新方法

针对目前蒸汽吞吐产量预测模型假设条件简单、普适性差等问题,一般采用测试法和类比法综合确定海上稠油油田蒸汽吞吐初期产量。由于目前海上油田通常只开展常规测试,无法直接获得热采开发初期产量。笔者提出海上稠油油田蒸汽吞吐初期产量确定新方法,建立蒸汽吞吐相对于常规开发的初期产量倍数预测模型,通过蒸汽吞吐产量倍数,将常规测试确定的产量转化为蒸汽吞吐产量。研究表明,蒸汽吞吐初期产量倍数主要受储集层渗透率、原油黏度、注入强度、蒸汽干度等因素影响,利用正交试验设计和多元回归等方法,建立海上稠油油田蒸汽吞吐初期产量倍数与油藏地质参数及注入参数之间的非线性预测模型,该模型经实际生产数据验证,预测误差小于5%,可靠性高,能够为海上稠油油田蒸汽吞吐初期产量的确定提供依据。     

张峰水库溢洪道体型优化设计

本文对已设计的张峰水库溢洪道进行了模型试验,根据对试验结果分析,认为原方案设计存在一些问题,并针对问题进行了优化设计。通过对修改方案模型试验结果分析,得出修改方案改进了原方案中存在的不足,优化合理,是可以采用的。     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

电路电磁兼容建模与仿真

提出了对暴露在任意外场中的传输线进行时频分析的新方法，这种方法非常稳定，它能够与任意的传输线模型和电路仿真方法兼容，并且使用这种方法得到的仿真值和实际值之间的差别小于1％。