高一学生化学学科自我概念与学业成绩的关系

运用化学自我概念问卷,对高一学生化学学科自我概念和化学学业成绩之间的关系进行探讨,结果表明:学生化学学科自我概念达到中等水平,化学学业自信较高,化学学业自我调控较弱;学生化学学科自我概念水平在性别上无显著差异;父母职业背景对学生化学自我概念有较大的影响;学生化学成绩与化学学科自我概念得分之间具有一致性,学生化学成绩对化学学科概念的形成有显著的影响.     

中学生化学学业成败归因与自我效能感研究

运用中学生化学学业成败归因量表和学业自我效能感量表,抽取653名城乡中学生进行测查,对测查数据进行分析得出以下结论：中学生化学学业成败倾向于外部归因;城乡之间中学生化学学业成败归因、学业自我效能感存在显著差异;学业成败归因和学习行为自我效能感通过学习能力自我效能感这一中介变量影响学生的化学学业成绩。     

大学生的化学自我效能感对自我调节学习策略及学业成就的影响研究*

大学生的学业成就是衡量高等教育质量的重要因素之一。由社会认知理论、建构主义学习和人本主义学习理论可知,高校大学生的化学自我效能感应能促进自我调节学习策略的运用,对学业成就与综合素质提升具有积极效应,但仍需要进行验证。故本研究目的:探讨高校大学生的化学自我效能感对学业成就的影响性,并考察自我调节学习策略的中介作用。研究方法:采用大学生的化学自我效能感量表、自我调节学习策略量表、化学专业学业成就量表等工具,通过整群抽样的方式,对国内某高校的536名化学化工专业大学生进行问卷调查。研究结果显示:大学生的化学自我效能感与化学专业学业成就显著正相关;大学生的化学自我效能感与自我调节学习策略显著正相关;自我调节学习策略与化学专业学业成就显著正相关;自我调节学习策略在化学自我效能感与化学专业学业成就之间起部分中介效应。     

高中生化学学业求助行为、学业自我效能感与化学学习焦虑的关系：个体中心的视角

采用潜在剖面分析和多项Logistic回归分析方法,探索1 092名高中生化学学习焦虑的潜在类别,以及学业求助行为和学业自我效能感对不同类别化学学习焦虑的影响。结果表明：高中生化学学习焦虑存在3个类别,分别是C1组(低化学学习焦虑)(23.81%)、C2组(中等化学学习焦虑)(57.60%)和C3组(高化学学习焦虑)(18.59%);高中生的执行性求助和回避求助得分越高、工具性求助和学业自我效能感得分越低,越容易被分到C2或C3组,而不易被分到C1组。     

中学生化学学习归因结构调查研究

以中学生化学学习归因结构三维模型为理论框架,编制《中学生化学学习归因能力测量问卷》。该问卷由5个因子维度构成,分别是化学学习特定自我概念、化学学习情境认知、化学学习策略认知、化学学习人际认知、化学学习使能认知维度。经过理论预设、内容及项目分析、探索性因素分析、信度分析、专家效度和维度分析、验证性因素分析等过程最终形成正式问卷。问卷整体信度、效度较高,结构效度良好,可以作为中学生化学学习归因能力测量工具。     

高中生化学学习情况自评量表的编制研究

本文介绍了“高中生化学学习情况自评量表”的编制及修订过程,并对其信度与效度进行了检验。结果表明,该量表具有较好的信度与效度,可以用于对高中学生的化学学习状况进行分析与判断。     

高中学业水平考试试题难度模型建构*

利用主成分分析方法厘清试题难度影响因素之间的关系,进而从问题表征、问题解决和结果输出等3个维度上建立了影响高中学业水平考试试题难度的主要因素。通过编写高中学业水平考试测试题进行实证研究,建立影响因素常见呈现类型的难易赋值规则。选用机器学习的线性回归方法建构试题难度分析模型,并使用高考化学江苏卷部分试题的实测难度数据进行校验,模型难度预测值和高考难度实测值具有较好的拟合度,表明模型具有较好的应用价值和推广意义。     

化学类硕士研究生学业拖延影响因素的质性研究

学业拖延是当前化学类硕士研究生在科研活动中普遍存在的问题,成为阻碍学业进步的重要因素。研究选取16名化学类硕士研究生作为访谈对象,对访谈资料进行编码,通过分析发现,化学类硕士研究生学业拖延行为源自个体压力与动力的交互、个性与环境的对抗作用。基于此,研究构建了关于化学类硕士研究生学业拖延影响因素的模型,并对改善学业拖延行为提出了对策建议。     

中学生化学学习动机的调查分析

为了了解当代中学生化学学习动机的特点,便于化学教师科学有效地培养、激发和强化中学生的化学学习动机,我们根据美国教育心理学家奥苏伯尔(D ·P ·Ausubel )的学业成就动机理论,结合中学化学教学实际,将化学学习动机分为三大类14项制成调查表,在我市6所中学(含省重点、市重点、普通中学、职业中学)的初三到高三四个年级的八百余名学生中进行了间卷调查。     

证据呈现方式对中学生书面化学论证能力的影响研究

在界定了相关概念后,设计了3个以中学化学核心课程内容为背景的书面化学论证任务,并形成了证据呈现方式分别为文字、表格和曲线图的3份"同内容、异形式"的测试卷。通过对135名中学生进行不同证据呈现方式下书面化学论证能力的测试,并依据Toulmin论证型式对测试结果进行分析,发现在不同的证据呈现方式下,中学生的书面化学论证能力存在差异,学生的学业水平也会影响其在书面化学论证中的得分。     

Automatic window factor analysis—A more efficient method for determining concentration profiles from evolutionary spectra

An algorithm called automatic window factor analysis (AUTOWFA) is developed for the purpose of determining, efficiently and automatically, the concentration profiles of the spectroscopically active components present in evolutionary processes, such as chemical titration, chromatography and kinetics. The method not only yields windows and profiles in agreement with those reported in the literature, but also reveals components not detected by precursor techniques. The method, however, has not been optimized and may require user interaction to fine-tune the windows.     

Chemometric and trend analysis of water quality of the South Chennai lakes: an integrated environmental study

In order to bring out the nature of the factors influencing lake water composition, multivariate statistical analysis and trend analysis were performed based on the hydrochemical data of the study area, namely, South Chennai. Change in land use pattern and settlements along the banks of the lakes alters the quality and quantity of the surface water. In the present study, the R‐mode factor analysis and cluster analysis were applied to the geochemical parameters of the water to identify the factors affecting the chemical composition of the lake water. Dendograms of both the seasons give three major clusters, reflecting the groups of unpolluted to moderately polluted, polluted, and heavily polluted stations. The movement of stations from one cluster to another clearly brings out the seasonal variation in the chemical composition of the lake water. The complex hydrochemical data of the surface water were interpreted by condensing them into three major factors. Factor score analysis was used successfully to delineate the stations under study and the role of the contributing factors, and the nature of factors responsible for the variation in chemical composition of the water has been clearly brought out. Results of trend analysis using ArcGIS clearly indicate that the trend in water quality is deteriorating at a faster rate in the eastern part of the study area. It is understood that although natural shifts probably can account for some of the variation, it is most likely that human activities play a major role in affecting the water quality on a regional scale. Copyright © 2014 John Wiley & Sons, Ltd.     

不同产地黄芪的聚类分析

用ＩＣＰ－ＡＥＳ测定１５个不同产地的黄芪中的１４种微量元素,以其含量为指标,进行因子分析,提取７个特征元素,并以特征指标进行样品的谱系聚类分析,把不同产地的黄芪分类,为地道性中药材的鉴别提供可靠方法。     

In-situ characterization of MgLi composite materials by means of AES and factor analysis

During manufacture of -Al₂O₃ fibre reinforced MgLi alloys the high mobility and reacitivity especially of the Li metal can cause damage of the fibres and loss of the good mechanical behaviour. Because of the low fibre diameter (2 to 5 m), and the necessity to detect Li, laterally highly resolved Auger electron spectroscopy was used to study the fibre-matrix-interaction. The measurements were performed at sample surfaces, which had been uncovered by in-situ fracture in the UHV apparatus. Due to the bad signal/noise ratio (which was tolerated to achieve high lateral resolution) and the overlapping spectral features, and in order to make an attempt to classify the large amount of spectra obtained, factor analysis in conjuction with cluster analysis was used in the interpretation of AES data. So it was possible to detect the chemical species which are responsible for the apperance of the experimental spectra and to draw conclusions concerning the fracture morphology (inter granular, trans granular).Dedicated to Professor Dr. rer. nat. Dr. h.c. Hubertus Nickel on the occasion of his 65th birthday     

Estimating Pesticide Field Half-lives from a Backpropagation Neural Network

Abstract

The field half-lives of 110 pesticides were modelled using a backpropagation neural network (NN). The molecules were described by means of the frequency of 17 structural fragments. Before training the NN, different scaling transformations were assayed. Best results were obtained with correspondence factor analysis which also allowed a reduction of dimensionality. The training and testing sets of the NN analysis gave 95.5% and 84.6% of good classifications, respectively. Comparison with discriminant factor analysis showed that a backpropagation NN was more appropriate to model the field half-lives of pesticides.     

Factor analysis of spectroelectrochemical reduction of FAD reveals the pKa of the reduced state and the reduction pathway

The free flavin adenine dinucleotide (FAD) cofactor is known to exhibit a pH‐dependent midpoint potential involving a simultaneous two‐electron transfer step (n = 2). Uv‐vis spectroelectrochemical reductions of FAD at constant pH, ranging from 5 to 9, were recorded and analyzed by factor analysis. Principal factor analysis was used to determine the number of species present at each pH. The results indicate that only two composite forms of FAD are present: the oxidized and the reduced forms. Window factor analysis was used to extract the concentration profiles of the controlling species. The oxidized form was found to be a single pH‐independent species, whereas the reduced form consists of two species. The pH‐dependent spectroscopic changes of reduced FAD were best modeled by a single proton transfer step involving two different ionization states with an apparent pK_a = 6.3. This value compares favorably with those obtained from NMR and from midpoint potential measurements. At pH 6, the reduction of FAD was found to be first order, whereas at pH 9 the reduction is zero order; these observations are explained in terms of the reaction pathway involving xanthine oxidase, its substrate, and the pH. Copyright © 2007 John Wiley & Sons, Ltd.     

Determination of rank by augmentation (DRAUG)

Determining the rank of a chemical matrix is the first step in many multivariate, chemometric studies. Rank is defined as the minimum number of linearly independent factors after deletion of factors that contribute to random, nonlinear, uncorrelated errors. Adding a matrix of rank 1 to a data matrix not only increases the rank by one unit but also perturbs the primary factor axes, having little effect on the secondary axes associated with the random errors in the measurements. The primary rank of a data matrix can be determined by comparing the residual variances obtained from principal component analysis (PCA) of the original data matrix to those obtained from an augmented matrix. The ratio of the residual variances between adjacent factor levels represents a Fisher ratio that can be used to distinguish the primary factors (chemical as well as instrumental factors) from the secondary factors (experimental errors). The results gleaned from model studies as well as those from experimental studies are used to illustrate the efficacy of the proposed methodology. The method is independent of the nature of the error distribution. Limitations and precautions are discussed. An algorithm, written in MATLAB format, is included. Copyright © 2011 John Wiley & Sons, Ltd.     

Proteomic characterization of plasma‐derived clotting factor VIII–von Willebrand factor concentrates

Proteomic methods were used to identify the levels of impurities in three commercial plasma‐derived clotting factor VIII‐von Willebrand factor (FVIII/VWF) concentrates. In all three concentrates, significant amounts of other plasma proteins were found. In Octanate and Haemoctin, two concentrates developed in the 1990s, the major impurities identified were inter‐α inhibitor proteins, fibrinogen and fibronectin. These two concentrates were also found to contain additional components such as clotting factor II (prothrombin) that are known activators of FVIII. In Wilate, a recently developed FVIII/VWF concentrate, the amount of these impurities was significantly reduced. Batch‐to‐batch variations and differences between three investigated products were detected using iTRAQ, an isotope labeling technique for comparative MS, demonstrating the potential value of this technique for quality control analysis. The importance of thorough proteomic investigations of therapeutic FVIII/VWF preparations from human plasma is also discussed.     

保存、分析方法等因素对土壤中硝态氮测定的影响

为探明土壤中硝态氮测定的影响因素,采用黑土、潮土、红壤为材料,研究样品的保存方法、浸提剂种类、分析方法、实验用水及试剂纯度对土壤中硝态氮测定的影响。结果表明,测定土壤硝态氮时,土样在冷冻条件下保存优于冷藏条件。冷冻条件下保存可在45 d内完成测试,而冷藏保存则需在7 d内完成测试。采用0.01 mol/L CaCl2和2 mol/L KCl为浸提剂时,对土壤中硝态氮的测定结果无显著差异。紫外比色法的测定结果与林业标准法(LY/T1230-1999)相比无显著差异,但显著高于流动注射法,且紫外比色法与流动注射法之间有显著相关性。流动注射法的测定结果与林业标准法相比也无显著差异。实验用水的杂质可使土壤中硝态氮的测定结果显著偏高,对其进行加热煮沸、蒸馏及无氨化蒸馏后可显著降低水中杂质的含量。