盐酸克伦特罗残留检测研究进展

介绍了盐酸克伦特罗残留检测的样品前处理技术、分析测试方法,并绘制了样品前处理技术路线图.其样品前处理技术主要有沉淀、离心、液-液萃取、固相萃取、基体分散固相萃取、中空纤维液相微萃取、分散液相微萃取、固相微萃取、免疫亲和色谱、分子印迹、超临界萃取等.分析测试方法主要有化学分析法、色谱法、毛细管电泳法、电化学分析法、免疫学分析法、生物传感器法等.相对于色谱-质谱联用等仪器分析技术的高速发展,盐酸克伦特罗残留检测样品前处理技术发展较为缓慢.因此,发展快速、高效、高选择性、环境友好、易于标准化且与分析测试方法衔接配套的样品前处理技术非常重要.     

固相萃取技术及其应用

评述了近年来固相萃取的新进展，涉及固相萃取的优点、作用机理和过程，固相萃取在多方面的应用及发展趋势。引用文献99篇。     

酞酸酯及其降解产物的前处理技术研究综述

酞酸酯是一类普遍使用的有机化合物,主要用作塑料的增塑剂,目前在环境中已经大量存在,由于其具有致癌、致畸和致突变性,引起广泛的关注。综述了近年来环境中酞酸酯类及其降解产物前处理技术的研究进展,指出现阶段主要有液-液萃取（LLE）、固相萃取（SPE）、固相微萃取（SPME）、固相膜萃取（SME）、液相微萃取技术（LPME）、超临界萃取（SFE）和衍生化技术等7种酞酸酯前处理方法;介绍了酞酸酯及降解产物衍生化技术的应用研究,并提出了前处理技术应用的研究前景。     

固相微萃取及其在生物样品分析中的应用

固相微萃取技术是近年来发展起来的一种样品分析预处理的新方法;与传统的溶剂萃取技术相比,它具有快速、高效、简便、无需溶剂、易于自动化操作等优点,目前已被广泛应用于生物样品和环境样品等领域的检测分析。本文重点介绍了固相微萃取及其在生物样品分析中的应用。     

环境中邻苯二甲酸酯样品前处理研究进展

回顾近十年来环境中邻苯二甲酸酯类化合物分析方法的研究进展，比较环境中大气、水及土壤等不同样品的前处理技术和检测方法，介绍固相萃取和固相微萃取等新型样品前处理技术在水样分析中的应用研究。     

样品制备技术在农药多残留分析中的应用

样品制备技术是农药多残留分析的关键．本文回顾了农药多残留分析样品制备技术的研究现状,着重介绍了固相萃取、固相微萃取、基质固相分散萃取、分散固相萃取、凝胶渗透色谱、超临界流体萃取、加速溶剂萃取的基本原理及在农药多残留分析中的应用情况,并对这些技术在农药多残留分析中的应用情况进行比较,展望了农药多残留分析样品制备技术的发展趋势。     

固相萃取技术分析环境水样中痕量铬的研究

固相萃取技术在环境样品痕量元素的分析中表现出了突出优点,重点研究了无机纳米氧化物颗粒,离子交换树脂、C18键合硅胶、分子印迹聚合物和活性炭等作为固相萃取吸附剂分析环境水样中铬形态的最新研究进展.     

水中有机污染物的前处理技术及其进展

水中有机污染物的前处理技术主要有固相萃取、固相微萃取、吹扫捕集法、浊点萃取法、液相微萃取、分散液液微萃取等.     

固相萃取原理及其从生物样品中提取滥用药物时常用的分离模式

文章评述了固相萃取技术的原理、方法、特点以及从生物样品中提取滥用药物时常用的分离模式、吸附剂和洗脱剂．     

固相萃取技术及其在氟喹诺酮类兽药残留分析中的应用

氟喹诺酮类兽药残留分析中的样品处理问题一直是分析检测人员关注的热点。固相萃取技术作为一种高效的样品处理技术,近年来得到越来越广泛的重视和应用。本文阐述了固相萃取技术的基本原理及方法,并对这一技术在氟喹诺酮类兽药残留分析中的应用进行了综述。     

高校阳光体育运动现状调查与对策

根据国家教育部、国家体育总局关于开展全国亿万学生阳光体育运动的要求,采用文献资料和调查等研究方法,分析高校阳光体育运动的现状,探讨阳光体育运动发展对策,以促使阳光体育运动有效、广泛、持久、深入地开展。     

抛物线方程算法在不规则地形电波传播中的应用

文章对标准抛物线方程（SPE）的分裂步傅里叶变换（SSFT）方法进行了详细的分析,引入一种适合SPE的不规则地形建模方式,利用SSFT算法计算自由空间与不规则地形的电波传播问题,与经典理论计算所得的结果相当吻合。     

非线性音系学：学术渊源及研究视野的多元化

20世纪60年代《英语语音模式》(SPE)的问世标志着生成音系学终于冲破结构主义的羁绊成为了一门崭新的学科。在随后的几十年中,生成音系学的标准理论在实践中不断经受检验并得到更新,各种以非线性音系为核心的理论学派推陈出新,它们采用独特新颖的多元研究视野,在SPE的基础上实现了质的飞跃。     

软件性能工程在采用UML再工程中的应用

本文首先论述了软件性能工程(SPE)方法，包括SPE概念、SPE过程、SPE与其它软件开发模型的集成、SPE策略及SPE工具，然后讨论了如何在从基于数据流模型(包括分析模型和设计模型)再工程为UML模型过程使用SPE的方法。     

邻苯二甲酸丁基苄基酯C18萃取条件的优化

一种环境友好样品处理技术———固相萃取技术被用于环境激素类物质邻苯二甲酸丁基苄基酯(BBP)痕量检测研究中。利用GC-ECD进行检测,借助于均匀设计法合理安排试验,通过计算机回归技术对C18固相萃取柱的萃取条件进行设计和优化,建立了相关的数学模型,找出了各因素对峰面积的影响规律。成功地确定优化的BBP固相萃取条件为:正己烷与丙酮配比30∶1、洗脱体积2.0ml、洗脱速率4.0ml/min、上样速率8.0ml/min。     

Revisiting the Stanford Prison Experiment: A Case Study in Organized Skepticism

Growing evidence exists that the findings of individual studies—including classic experiments—often fail to replicate. Such published results, however, are considered by scholars, and taught to students, as established scientific truth. In this context, citations to Zimbardo and colleagues’ classic Stanford Prison Experiment (SPE) in criminology/criminal justice journals (1975–2014) were content analyzed to assess whether the study’s conclusions have been embraced or treated with skepticism. The data revealed that scholars were widely accepting of the SPE and, even when voicing concerns, supportive of its message. These results suggest the need to give replications higher priority and for scholars to adhere more closely to the scientific norm of organized skepticism. In the classroom, the continued, uncritical acceptance of the SPE—now more than 40 years old—can serve as an opportunity to teach students about the production and assessment of knowledge within criminology.     

A Developmental Study of the Self-Prioritization Effect in Children Between 6 and 10 Years of Age

Self-biases are well described in adults but remain poorly understood in children. Here, we investigated in 6–10 year-old children (N = 132) the self-prioritization effect (SPE), a self-bias which reflects, in adults, the perceptual advantage for stimuli arbitrarily associated with the self as compared to those associated with other persons. We designed a child-friendly adaptation of a paradigm originally introduced in adults by Sui, He, and Humphreys (2012) in order to test whether the SPE also occurs in children and if so, to determine its evolution with age. A robust SPE was obtained from the age of 6, and this effect was similar-sized in our four age groups. These findings are discussed with reference to the development of the self during childhood.     

Section Preequating Under the Equivalent Groups Design Without IRT

In this article, we introduce a section preequating (SPE) method (linear and nonlinear) under the randomly equivalent groups design. In this equating design, sections of Test X (a future new form) and another existing Test Y (an old form already on scale) are administered. The sections of Test X are equated to Test Y, after adjusting for the imperfect correlation between sections of Test X, to obtain the equated score on the complete form of X. Simulations and a real‐data application show that the proposed SPE method is fairly simple and accurate.     

Teachers’ beliefs systems about improving transfer of algebraic skills from mathematics into physics in senior pre-university education

Senior pre-university education (SPE) students experience difficulties applying mathematics to physics. This paper reports the outcome of an online explorative quantitative study of teachers' belief systems about improving transfer of algebraic skills from mathematics into physics, conducted among 503 mathematics and physics teachers working in SPE. We used a questionnaire with 16 beliefs about improving transfer, and asked teachers to select a top 5 and distribute 50 points among them. We used agglomerative hierarchical clustering to cluster qualified SPE teachers with more than 10 years of teaching experience. We found 3 large clusters, each containing naïve and desirable beliefs about transfer. These clusters turned out to be rather coherent sets of beliefs. Hence, these clusters can be interpreted as belief systems, to a certain extent justifying Ernest's [(1991). The philosophy of mathematics education. London: Falmer.] idea to cluster teachers based on their belief systems. We found relations between our groups and those of Ernest. Since naïve beliefs turn out to be weak in each cluster, science teacher educators can help science teachers to change their harmful naïve beliefs, into desirable transfer enhancing beliefs. Furthermore, we discuss some implications of our results for science teacher educators, curricula, teachers and textbooks.     

New Confidence Intervals and Bias Comparisons Show That Maximum Likelihood Can Beat Multiple Imputation in Small Samples

When analyzing incomplete data, is it better to use multiple imputation (MI) or full information maximum likelihood (ML)? In large samples ML is clearly better, but in small samples ML’s usefulness has been limited because ML commonly uses normal test statistics and confidence intervals that require large samples. We propose small-sample t-based ML confidence intervals that have good coverage and are shorter than t-based confidence intervals under MI. We also show that ML point estimates are less biased and more efficient than MI point estimates in small samples of bivariate normal data. With our new confidence intervals, ML should be preferred over MI, even in small samples, whenever both options are available.