解放思想观念,加强科技创新进一步深化农业科技体制改革

加强科技管理与创新 ,深化农业科技体制改革 ,施行研究主体和产业实体并存发展 ,大力培育农业科技企业 ,合理配置农业科技生产要素 ,完善以质效评价为核心的评价体系 ,建立面向社会、适应市场的农业科技管理新机制 ,对促进农业科技进步和生产力的发展具有决定性的作用     

培养高素质人才要坚持科技教育与人文教育相结合

结合 2 1世纪“知识经济”的特点及我国国情 ,分析指出我国必须重视科技教育 ,培养大批科技人才。并且通过论述人文素质对科技人才的重要性 ,阐明了培养高素质人才要坚持科技教育与人文教育相结合的观点     

深化电子系列课程教学改革

根椐指导学生参加全国大学生电子设计竞赛的体会,分析竞赛中所暴露出的有关教学方面的问题,从教学体系、教学内容、实践教学模式和教学手段方面,提出以电子竞赛为契机,深化教学改革的具体措施.     

教育技术的范式及其历史演变

教育技术的 4个范式包括媒体范式、传播与系统范式、行为科学范式、认知科学范式。许多教育技术学者开始探索并发展新的范式。库恩的科学范式的理论 ,讨论了教育技术领域的范式变迁 ,指出这实际上是一个范式持续在演变的过程。     

江苏高校科技服务的嬗变与反思

本文通过梳理江苏高校以科技服务社会的历史发展轨迹 ,总结了江苏高校科技服务社会四个发展特点与趋势 ,在此基础上 ,进一步思考如何提升江苏高校科技服务的质量 ,为江苏高校拓展科技服务的深度和广度提供有益的借鉴 ,推动江苏经济与社会的进步     

现代教育技术与高师教育改革进程

本文从信息时代对人才的需求及教育改革发展的趋势出发 ,论证了应用现代教育技术对培养创新型人才的必要性和迫切性 ,并提出了使现代教育技术在高师院校得到扎实、有效的推广和应用的若干可行性建议     

Olive Oil Consumption in Greece: A Microeconometric Analysis

In this paper, the factors affecting at-home demand for three types of oils and fats in Greece, with emphasis on olive oil, are investigated using the linear approximation of the Almost Ideal Demand System and family budget survey data. To overcome the econometric problem created with the existence of zero expenditure, a generalization of the two-stage Heckman procedure is employed. In order to investigate the role of self-consumption, two different samples were used. The first includes all households; the second excludes those that acquire olive oil only from own production. According to the results, there are important differences in the first stage of the decision process between the two samples. Unlike the first stage, the second stage of the decision process found no important differences between the results for the two samples.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

ASSESSING CONGRUENCEAMONG DISTANCE MATRICES: SINGLE-MALT SCOTCH WHISKIES REVISITED

A test of congruence among distance matrices is described. It tests the hypothesis that several matrices, containing different types of variables about the same objects, are congruent with one another, so they can be used jointly in statistical analysis. Raw data tables are turned into similarity or distance matrices prior to testing; they can then be compared to data that naturally come in the form of distance matrices. The proposed test can be seen as a generalization of the Mantel test of matrix correspondence to any number of distance matrices. This paper shows that the new test has the correct rate of Type I error and good power. Power increases as the number of objects and the number of congruent data matrices increase; power is higher when the total number of matrices in the study is smaller. To illustrate the method, the proposed test is used to test the hypothesis that matrices representing different types of organoleptic variables (colour, nose, body, palate and finish) in single‐malt Scotch whiskies are congruent.     

Estimation of Hazard, Density and Survivor Functions for Randomly Censored Data

Maximum likelihood estimation and goodness-of-fit techniques are used within a competing risks framework to obtain maximum likelihood estimates of hazard, density, and survivor functions for randomly right-censored variables. Goodness-of- fit techniques are used to fit distributions to the crude lifetimes, which are used to obtain an estimate of the hazard function, which, in turn, is used to construct the survivor and density functions of the net lifetime of the variable of interest. If only one of the crude lifetimes can be adequately characterized by a parametric model, then semi-parametric estimates may be obtained using a maximum likelihood estimate of one crude lifetime and the empirical distribution function of the other. Simulation studies show that the survivor function estimates from crude lifetimes compare favourably with those given by the product-limit estimator when crude lifetimes are chosen correctly. Other advantages are discussed.