Structured Latent Curve Models for the Study of Change in Multivariate Repeated Measures.

This article considers a structured latent curve model for multiple repeated measures. In a structured latent curve model, a smooth nonlinear function characterizes the mean response. A first-order Taylor polynomial taken with regard to the mean function defines elements of a restricted factor matrix that may include parameters that enter nonlinearly. Similar to factor scores, random coefficients are combined with the factor matrix to produce individual latent curves that need not follow the same form as the mean curve. Here the associations between change characteristics in multiple repeated measures are studied. A factor analysis model for covariates is included as a means of relating latent covariates to the factors characterizing change in different repeated measures. An example is provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Phase I IASC-ASCE Structural Health Monitoring Benchmark Problem Using Simulated Data

Structural health monitoring (SHM) is a promising field with widespread application in civil engineering. Structural health monitoring has the potential to make structures safer by observing both long-term structural changes and immediate postdisaster damage. However, the many SHM studies in the literature apply different monitoring methods to different structures, making side-by-side comparison of the methods difficult. This paper details the first phase in a benchmark SHM problem organized under the auspices of the IASC–ASCE Structural Health Monitoring Task Group. The scale-model structure adopted for use in this benchmark problem is described. Then, two analytical models based on the structure—one a 12 degree of freedom (DOF) shear-building model, the other a 120-DOF model, both finite element based—are given. The damage patterns to be identified are listed as well as the types and number of sensors, magnitude of sensor noise, and so forth. MATLAB computer codes to generate the response data for the various cases are explained. The codes, as well as details of the ongoing Task Group activities, are available on the Task Group web site at 〈http://wusceel.cive.wustl.edu/asce.shm/〉.     

考虑风电接入和气电转换的综合能源系统日前区间优化

针对气电综合能源系统优化调度中未充分挖掘可调度因素、未充分考虑风电预测误差不确定性的现状,研究含风电的气电综合能源系统日前区间优化调度方法。首先,基于区间数学对风电出力的不确定性进行区间描述,综合考虑抽水蓄能、气电双向转换以及需求响应等资源和技术,并用区间数学表示优化目标和优化约束,构建含高比例风电的气电综合能源系统日前优化模型,综合优化系统的经济性、环保性。然后,基于区间序关系和可能度的方法将区间优化模型转化为确定性优化模型,继而采用Jaya算法进行求解,保证求解的高效性和解空间的可行性。最后,进行算例分析,仿真结果验证了综合利用抽水蓄能、气电双向转换以及需求响应等要素对系统进行区间优化,能取得优化效果上的优势,并能为系统调度人员提供风电不确定度对系统优化影响的信息。     

WEB应用系统性能测试的实现

对WEB应用系统进行合理的性能测试是保证系统质量的一个重要过程。以某远程教学系统为案例,借助于测试工具Load Runner,从负载反应层面对系统性能进行验证,并对测试结果进行分析,以保证系统的合理优化。     

异形截面钢筋砼双向压弯构件截面延性性能分析

根据异形截面(L、T、十、方形)钢筋砼双向压弯构件的工作机理,采用全过程非线性分析方法,编制了相应的电算程序,对异形截面钢筋砼双向压弯构件截面的延性性能进行了大量的理论研究分析,探讨了影响截面延性性能的各种因素,并对一些构造要求提出了设计建议。     

酶解法制备禾虫多肽液的工艺优化及其脱腥工艺探究

目的 应用单因素和响应面实验优化禾虫的酶解工艺,结合模糊数学法探究一种有效的脱腥方法。方法 以中性蛋白酶为酶解剂,禾虫为主要原料,研究液料比、酶用量、时间、温度、pH对酶解效果的影响。在单因素实验的基础上,以液料比、酶解温度、酶用量为自变量,禾虫多肽液的1,1-二苯基-2-三硝基苯肼（1,1-diphenyl-2-picrylhydrazyl,DPPH）自由基清除率为响应值,通过Box-Behnken响应面法分析不同因素对酶解效果的影响,确定酶解的最优组合,并应用美拉德反应、硅藻土和酵母粉对禾虫多肽液进行脱腥实验,模糊数学法评价3种脱腥处理的效果。结果 根据响应面实验得出禾虫的最佳酶解组合为：液料比1:1 (g/mL)、酶解温度60℃、中性蛋白酶用量2450 U/g,得到酶解液的DPPH自由基清除率47.25%±0.11%;禾虫多肽液脱腥的最佳处理为：酵母粉添加量0.7%,反应温度35℃,反应时间30 min。结论 中性蛋白酶酶解禾虫制备禾虫多肽液并采用酵母粉脱腥效果最佳,为禾虫的精深加工提供借鉴,促进禾虫产业的发展。     

土石坝动力反应分析

土石坝动力反应分析是土石坝力学计算中较为复杂和困难的课题。原因之一在于计算中选用的土石料和混凝土的动力本构模型与实际状态模拟有误 ;之二在于计算中动力平衡方程求解的复杂。本文试就动力反应的分析进行尝试 ,文中的计算方法在实际工程中得到验证 ,对于浙江溪口抽水蓄能电站上库面板堆石坝和四川清平水库面板堆石坝的计算分析得出合理有效的结果。1　动力本构模型1 .1　土石料动力本构模型土石料的动力性质较为复杂 ,它随振动频率而变化 ;剪切模量和阻尼比随动剪应变而变化。目前描述土石的动应力应变关系的模型有双线形模型、仑贝…     

压缩系统对温度突升响应的动态分析

基于时间滞后概念,建立了压缩系统动态响应分析的通用模型,并对温度突升条件下多级轴流压缩系统的动态响应及气动稳定性进行了详细的数值分析。对两个算例的分析,结果表明了本文新模型的可行性。     

响应面优化低糖滇红奶茶的配方

目的 通过响应面法优化低糖滇红奶茶的配方。方法 以滇红茶、全脂奶粉、零卡糖为主要原料,通过单因素分析结合响应面实验设计优化滇红奶茶配方,并分析产品的理化及卫生指标。结果 优化配方为：滇红茶汁50%、全脂奶粉15%、零卡糖10%、乳化剂0.22%、稳定剂0.2%,此时感官评分为87.83。滇红奶茶浅棕色稳定性好、质地均匀、浓稠恰当、细腻滑润无杂质,甜味适中茶香味与奶香香味协调无异味,经测定蛋白质含量(5.99±0.06)%、脂肪含量(3.38±0.02)%、茶多酚含量(320.6±2.25) mg/kg,微生物指标符合国家标准。结论 本研究开发了一种低糖健康的滇红奶茶,为滇红茶的深加工提供一定的实验依据。     

Environmental Stress and Plants

Land plants are constantly subjected to multiple unfavorable or even adverse environmental conditions. Among them, abiotic stresses (such as salt, drought, heat, cold, heavy metals, ozone, UV radiation, and nutrient deficiencies) have detrimental effects on plant growth and productivity and are increasingly important considering the direct or indirect effects of climate change. Plants respond in many ways to abiotic stresses, from gene expression to physiology, from plant architecture to primary, and secondary metabolism. These complex changes allow plants to tolerate and/or adapt to adverse conditions. The complexity of plant response can be further influenced by the duration and intensity of stress, the plant genotype, the combination of different stresses, the exposed tissue and cell type, and the developmental stage at which plants perceive the stress. It is therefore important to understand more about how plants perceive stress conditions and how they respond and adapt (both in natural and anthropogenic environments). These concepts were the basis of the Special Issue that International Journal of Molecular Sciences expressly addressed to the relationship between environmental stresses and plants and that resulted in the publication of 5 reviews and 38 original research articles. The large participation of several authors and the good number of contributions testifies to the considerable interest that the topic currently receives in the plant science community, especially in the light of the foreseeable climate changes. Here, we briefly summarize the contributions included in the Special Issue, both original articles categorized by stress type and reviews that discuss more comprehensive responses to various stresses.