Nonparametric control charts based on runs and Wilcoxon-type rank-sum statistics

In this article, we introduce three new distribution-free Shewhart-type control charts that exploit run and Wilcoxon-type rank-sum statistics to detect possible shifts of a monitored process. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of these charts is that, due to their nonparametric nature, the false alarm rate (FAR) and in-control run length distribution is the same for all continuous process distributions. Tables are provided for the implementation of the charts for some typical FAR values. Furthermore, a numerical study carried out reveals that the new charts are quite flexible and efficient in detecting shifts to Lehmann-type out-of-control situations.     

打破传统模式 培养创新人才--"高师美术教育专业水彩画符号、图式建构教学的研究与实践"总结

高师美术教育专业培养模式与培养具有创新性的新型城乡中学美术教师的宗旨相背已久.从基础水彩画课入手进行符号、图式建构教学的研究与实践,有利于该专业课程体系改革的全面实施,进而打破传统培养模式,为城乡中学输送具有审美能力、创新能力的新型人才.     

The impact of water supply and sanitation on infant mortality: Individual-level evidence from Tartu,Estonia, 1897–1900

Evidence from a number of historical studies has demonstrated a strong impact of the provision of clean water on mortality risks, while no clear effect has been reported in others. We investigated the relationship between water supply, sanitation, and infant survival in Tartu, a university town in Estonia, 1897–1900. Based on data from parish registers, which were linked to the first census of the Russian Empire, the analysis reveals a clear disadvantage for infants in households using surface water, compared with families that acquired water from groundwater or artesian wells. The impact is stronger in the later stages of infancy. Competing-risk analysis shows that the effect is more pronounced for deaths caused by diseases of the digestive system. Our findings suggest that it may have been possible to improve the water supply, and consequently reduce infant mortality, before the introduction of piped water and sewage systems.     

水质预报系统的MPI+OpenMP并行优化研究

OpenMP(Open Multi-Processing)能够在共享存储环境中获得理想的并行性能,MPI＋OpenMP混合并行编程模型更贴近于多核心集群的体系结构。在多核心集群上进行实验,混合模型相对串行程序可缩短95%的运算时间,加速比超过20。实验结果表明,该混合模型比纯MPI并行的系统具有更优的加速比和扩展性,是对纯MPI并行系统的一种改进。     

包头师范学院有机化学实验教学改革探索

本文介绍了有机化学实验课程教学中存在的问题,初步探讨了包头师范学院化学、应用化学专业在有机化学实验教学过程中对实验教学内容、实验教学方式、实验室三废处理、学生成绩评定等方面进行的改革以及取得的成果。     

‘Warren Buffet is my cousin’: shaping public understanding of big data biotechnology,direct-to-consumer genomics,and 23andMe on Twitter

Scholars, educators, regulators, pundits, and other observers are advocating for regulation and oversight of direct-to-consumer (DTC) genomic testing. As a result, the technology has been subject of highly visible public and regulatory controversy. In this article, we explore the nature and the shape of the sentiment of public discourse about the DTC company, 23andMe. We conduct a quantitative content analysis and qualitative framing analysis on Tweets. We find that the discourse surrounding DTC genomics and 23andMe is largely positive. We also identify a number of frames users deploy to debate, discuss, and share their experiences with DTC genomics and 23andMe. We argue that these frames create meaning around this emerging technology for its users.     

Do Mission Statements Matter for Nonprofit Performance?

In this exploratory study, we examine whether organizational mission statement attributes make a difference to the performance of nonprofit performing arts organizations. We use text analysis to measure two semantic attributes—activity and commonality—of mission statements. We examine whether these attributes are associated with improved performance for the instrumental and expressive functions of nonprofit performing arts organizations. Our findings indicate that the mission statement attribute activity is associated with improved performance for both instrumental and expressive functions. Our analysis of nonfindings for the mission statement attribute commonality suggests that there is a need to develop and use content analysis tools tailored to nonprofit contexts.     

Birds of a feather petition together? Characterizing e-petitioning through the lens of platform data

E-petitioning platforms are increasingly popular in Western democracies and considered by some lawmakers and scholars to enhance citizen participation in political decision-making. In addition to social media and other channels for informal political communication, online petitioning is regarded as both a useful instrument to afford citizens a more important role in the political process and allow them to express support for issues which they find relevant. Building on existing pre-internet systems, e-petitioning websites are increasingly implemented to make it easier and faster to set up and sign petitions. However, little attention has so far been given to the relationship between different styles of usage and the causes supported by different groups of users. The functional difference between signing paper-based petitions vs. doing so online is especially notable with regard to users who sign large numbers of petitions. To characterize this relationship, we examine the intensity of user participation in the German Bundestag’s online petitioning platform through the lens of platform data collected over a period of five years, and conduct an analysis of highly active users and their political preferences. We find that users who sign just a single petition favor different policy areas than those who sign many petitions on a variety of issues. We conclude our analysis with observations on the potential of behavioral data for assessing the dynamics of online participation, and suggest that quantity (the number of signed petitions) and quality (favored policy areas) need more systematic joint assessment.     

What is gained and what is left to be done when content analysis is added to network analysis in the study of a social movement: Twitter use during Gezi Park

As social movements relying on the weak ties found in social networks have spread around the world, researchers have taken several approaches to understanding how networks function in such instances as the Arab Spring. While social scientists have primarily relied on survey or content analysis methodology, network scientists have used social network analysis. This research combines content analysis with the automated techniques of network analysis to determine the roles played by those using Twitter to communicate during the Turkish Gezi Park uprising. Based on a network analysis of nearly 2.4 million tweets and a content analysis of a subset of 5126 of those tweets, we found that information sharing was by far the most common use of the tweets and retweets, while tweets that indicated leadership of the movement constituted a small percentage of the overall number of tweets. Using automated techniques, we experimented with coded variables from content analysis to compute the most discriminative tokens and to predict values for each variable using only textual information. We achieved 0.61 precision on identifying types of shared information. Our results on detecting the position of user in the protest and purpose of the tweets achieved 0.42 and 0.33 precision, respectively, illustrating the necessity of user cooperation and the shortcomings of automated techniques. Based on annotated values of user tweets, we computed similarities between users considering their information production and consumption. User similarities are used to compute clusters of individuals with similar behaviors, and we interpreted average activities for those groups.