Chimera or Jackalope? Department of Defense Efforts to Apply Civilian Sexual Harassment Criteria to the Military

Syftet med den här uppsatsen är att undersöka vilka ickepedagogiska texter som används i gymnasieskolans religionsundervisning samt i vilket syfte lärarna väljer att använda dem. Med begreppet ”ickepedagogiska texter” menas texter som inte, som läroböcker och skrivna i pedagogiskt syfte, utan mer autentiska texter som exempelvis artiklar, urkunder, prosa och lyrik. Uppsatsen består dels av en bakgrundsdel, där jag kort redogör för religionsämnet, dess utveckling samt de båda begreppen religionsdidaktik och textdidaktik, dels av en forskningsstudie. I den senare har jag intervjuat åtta gymnasielärare i religionskunskap om deras användning av och syn på ickepedagogiska texter. Resultatet visar att ickepedagogiska texter används av alla lärare i studien, men i betydligt varierande grad. Vanligast är användningen av religiösa urkunder, företrädelsevis Bibeln och Koranen, och olika artiklar. I någon mån används också skönlitteratur och vetenskapliga texter. Syftet med användningen är i första hand att utveckla kunskap om och förståelse för olika religioner. I viss mån används också texterna för att träna elevernas analytiska förmåga och för, via livsfrågepedagogik, främja elevernas personlighetsutveckling

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Object Histories as a Foundation for an Active OODB

Several links exist between active and temporal databases. These are summarised by the observation that rules are triggered by a specified evolution of the database. In this paper, we discuss the relation between active and temporal database using DEGAS, an object-based active database programming language. To achieve full active database functionality, a DEGAS object records its complete history. Hence, all data needed for a temporal database supporting a single temporal dimension is provided. Furthermore, the semantics of the active behaviour of DEGAS are defined straightforwardly in terms of the object history. Finally, we discuss the advantages and disadvantages of extending DEGAS with a second time dimension (to achieve full temporal functionality) from an active database perspective

A topological approach for protein classification

Protein function and dynamics are closely related to its sequence and structure. However prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity be- tween proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics. Persistent homology is a new branch of algebraic topology that has found its success in the topological data analysis in a variety of disciplines, including molecular biology. The present work explores the potential of using persistent homology as an indepen- dent tool for protein classification. To this end, we propose a molecular topological fingerprint based support vector machine (MTF-SVM) classifier. Specifically, we construct machine learning feature vectors solely from protein topological fingerprints, which are topological invariants generated during the filtration process. To validate the present MTF-SVM approach, we consider four types of problems. First, we study protein-drug binding by using the M2 channel protein of influenza A virus. We achieve 96% accuracy in discriminating drug bound and unbound M2 channels. Additionally, we examine the use of MTF-SVM for the classification of hemoglobin molecules in their relaxed and taut forms and obtain about 80% accuracy. The identification of all alpha, all beta, and alpha-beta protein domains is carried out in our next study using 900 proteins. We have found a 85% success in this identifica- tion. Finally, we apply the present technique to 55 classification tasks of protein superfamilies over 1357 samples. An average accuracy of 82% is attained. The present study establishes computational topology as an independent and effective alternative for protein classification

Reactivity on the Web

Reactivity, the ability to detect simple and composite events and respond in a timely manner, is an essential requirement in many present-day information systems. With the emergence of new, dynamic Web applications, reactivity on the Web is receiving increasing attention. Reactive Web-based systems need to detect and react not only to simple events but also to complex, real-life situations. This paper introduces XChange, a language for programming reactive behaviour on the Web, emphasising the querying of event data and detection of composite events