從中文作文看學生的情意表達能力: 個案研究

本文是一個追蹤研究，首先收集研究對象中一至中三的作文103篇，並採用現象學研究法（Phenomenological Research ）的意念進行研究。現象學研究法的重點在於深入了解人類自然的生活，把沒有虛飾的生活體驗和意義呈現出來。本文主要運用兩種分析工具：威堅遜模式（Wilkinson， 1980）及內容分析（text analysis）。論文研究的目的：分析受試者初中情意表達能力的層次。 This article is a longitudinal research which monitors 103 essays of a student from F.1 to F.3 by adopting 'phenomenological research'. Phenomenological research is based on the deep understanding of human life, presenting us with the truest life experiences without disguise. The ability to express emotion of a student as reflected from his Chinese composition. Two models are employed in this research: Wilkinson’s (1980) and text analysis. The objectives of this research is to analyse the abilities of junior secondary school students to express emotions.link_to_OA_fulltex

Decision theory applied to image quality control in radiology

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Theoretical vs. empirical discriminability:the application of ROC methods to eyewitness identification

Abstract ᅟ Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d’ or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability

Of monkeys and men:Impatience in perceptual decision-making

For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set decision standard throughout the decision process. Based on the theoretical argument of reward rate maximization, some authors have recently suggested that decision makers become increasingly impatient as time passes and therefore lower their decision standard. Indeed, a number of studies show that computational models with an impatience component provide a good fit to human and monkey decision behavior. However, many of these studies lack quantitative model comparisons and systematic manipulations of rewards. Moreover, the often-cited evidence from single-cell recordings is not unequivocal and complimentary data from human subjects is largely missing. We conclude that, despite some enthusiastic calls for the abandonment of the standard model, the idea of an impatience component has yet to be fully established; we suggest a number of recently developed tools that will help bring the debate to a conclusive settlement

Adaptation and visual search in mammographic images

Abstract Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether the salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. The observers were not radiologists, and thus had no diagnostic training with the im-ages. The stimuli were randomly selected sections from nor-mal mammograms previously classified with BIRADS Den-sity scores of Bfatty ^ versus Bdense, ^ corresponding to differ-ences in the relative quantities of fat versus fibroglandular tissue. These categories reflect conspicuous differences in vi-sual texture, with dense tissue being more likely to obscure lesion detection. The targets were simulated masses corre-sponding to bright Gaussian spots, superimposed by adding the luminance to the background. A single target was random-ly added to each image, with contrast varied over five levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location, before or after adapting to a gray field or to random sequences of a different set of dense or fatty images. Observers were faster at detecting the targets in either dense or fatty images after adapting to the specific background type (dense or fatty) that they were searching within. Thus, the adaptation led to a facilitation of search performance that was selective for the background tex-ture. Our results are consistent with the hypothesis that adap-tation allows observers to more effectively suppress the spe-cific structure of the background, thereby heightening visual salience and search efficiency

The human keratins: biology and pathology

The keratins are the typical intermediate filament proteins of epithelia, showing an outstanding degree of molecular diversity. Heteropolymeric filaments are formed by pairing of type I and type II molecules. In humans 54 functional keratin genes exist. They are expressed in highly specific patterns related to the epithelial type and stage of cellular differentiation. About half of all keratins—including numerous keratins characterized only recently—are restricted to the various compartments of hair follicles. As part of the epithelial cytoskeleton, keratins are important for the mechanical stability and integrity of epithelial cells and tissues. Moreover, some keratins also have regulatory functions and are involved in intracellular signaling pathways, e.g. protection from stress, wound healing, and apoptosis. Applying the new consensus nomenclature, this article summarizes, for all human keratins, their cell type and tissue distribution and their functional significance in relation to transgenic mouse models and human hereditary keratin diseases. Furthermore, since keratins also exhibit characteristic expression patterns in human tumors, several of them (notably K5, K7, K8/K18, K19, and K20) have great importance in immunohistochemical tumor diagnosis of carcinomas, in particular of unclear metastases and in precise classification and subtyping. Future research might open further fields of clinical application for this remarkable protein family