Effects of Mass and Interpersonal Communication on Breast Cancer Screening: Advancing Agenda-Setting Theory in Health Contexts

Drawing on components of agenda-setting theory and the two-step flow of information from mass media to news audiences, this study examines the effects of mass and interpersonal communication on breast cancer screening practices among college- and middle-aged women (n = 284). We theorized that screening behaviors among younger women would be influenced more by interpersonal sources of information while screening among middle-aged women would be more influenced by exposure to mass-mediated information. Findings supported anticipated patterns, revealing important and varying roles for both mass and interpersonal communication in the health behaviors of women. Implications for health practitioners and campaign planners, as well as recommendations for future research, are discussed.     

Multilingual modeling of cross-lingual spelling variants

Technical term translations are important for cross-lingual information retrieval. In many languages, new technical terms have a common origin rendered with different spelling of the underlying sounds, also known as cross-lingual spelling variants (CLSV). To find the best CLSV in a text database index, we contribute a formulation of the problem in a probabilistic framework, and implement this with an instance of the general edit distance using weighted finite-state transducers. Some training data is required when estimating the costs for the general edit distance. We demonstrate that after some basic training our new multilingual model is robust and requires little or no adaptation for covering additional languages, as the model takes advantage of language independent transliteration patterns. We train the model with medical terms in seven languages and test it with terms from varied domains in six languages. Two test languages are not in the training data. Against a large text database index, we achieve 64–78 % precision at the point of 100% recall. This is a relative improvement of 22% on the simple edit distance.     

Forschungs- und Entwicklungsprojekte Virtuelle Maschinen: zSeries- und S/390-Partitionierung

Der gleichzeitige Betrieb mehrerer Gast-Betriebssysteme auf einem einzigen physischen Rechner unter einem Host-Betriebssystem ist eine leistungsfähige moderne Entwicklung. Bekannte Beispiele sind VMware für die IA32-Architektur sowie das Betriebssystem z/VM und die PR/SM-LPAR Einrichtungen der zSeries-Architektur. Die Nutzung eines Betriebssystems als Gast bedingt einen Leistungsverlust. Die als Partitionierung bezeichnete Zuordnung von Systemressourcen zu den einzelnen Gast-Betriebssysteme ist schwierig, wenn eine dynamische Anpassung an sich ändernde Lastprofile erforderlich ist. Diese Probleme lassen sich mittels Erweiterungen der Hardwarearchitektur adressieren, sowie durch Softwarestrukturen, welche diese Erweiterungen nutzen. Die Erweiterungen der Hardwarearchitektur gehen über das hinaus, was auf heutigen Rechnerarchitekturen wie IA32 oder Mips verfügbar ist. Der vorliegende Beitrag erläutert den optimalen Betrieb von Gast-Betriebssystemen und die begleitenden Partitionierungsmöglichkeiten auf der zSeries-Plattform und beschreibt die zusätzlichen Hardware- und Software-Einrichtungen, welche dies ermöglichen.     

Buddhist Wall Paintings at Nako Monastery,North India: Changing of the Technology Throughout Centuries

The technical study of wall paintings from the Buddhist temple complex at Nako, Western Himalayas, was one of the basic preconditions required for designing an appropriate conservation strategy. The complex, composed of four temples from the eleventh–twelfth century, offered a unique possibility to carry out a comprehensive research of technology and painting materials used in early and later western Tibetan Buddhist wall paintings as well as a comparative assessment with murals from other sites in the Western Himalayas. The study was based on extensive fieldwork and an integrated analytical approach comprising a wide range of non-destructive and micro-destructive methods. Answering the question of the coevality of paintings in the smaller temples with other original murals, the precise characterisation of binding media, the detection of the yellow dye gamboge and natural minerals posnjakite and brochantite identified for the first time in Himalayan murals, the clarification of technology of metal decoration, and the making of raised elements are some of the most exciting results which emerged from the research.     

Relational turbulence and perceptions of partner support during reintegration after military deployment

The transition from deployment to reintegration can be stressful for returning military personnel and at-home partners, and support plays a key role in their ability to transition effectively. We draw on relational turbulence theory to advance predictions about how parameters of the relationship between returning service members and at-home partners predict their perceptions of their partner’s support during the post-deployment transition. We surveyed 235 individuals (117 returning service members, 118 at-home partners) who had experienced the transition within the past 6 months. Findings consistent with the theory indicated that relational turbulence partially mediated the negative associations that relational uncertainty and interference from a partner shared with partner support. Partner uncertainty was a direct negative predictor of partner support as well. We consider how these results extend theory, research, and practice.     

Why Users Share the News: A Theory of Reasoned Action-Based Study on the Antecedents of News-Sharing Behavior

Social media have become an integral part of online news use, affecting how individuals find, consume, and share news. By applying the Theory of Reasoned Action (TRA), this study investigates the effects of motives, attitude, and intention on news-sharing behavior among German social media users (n = 333). Findings show that news-sharing attitude and subjective norms have a positive effect on news-sharing intention, which in turn has a positive effect on actual news-sharing behavior. Taken together, we see that a new media behavior in the early phases of its societal diffusion—like social media news sharing in Germany in 2015—can mainly be explained by a rational choice logic and is rooted in the motives of socializing and information seeking. This finding thus reflects the double nature of social media as a means for both information retrieval and social grooming.     

The Effects of Darkness and Lightness Cues in the Visual Depiction of Political Actors Involved in Scandals: An Experimental Study

Reports about political scandals have increased lately. Yet the general impact of news visuals and the specific role of lightness and darkness cues in images of scandalized politicians remain unclear. With the help of an experiment, the present pilot study examined the influence of candidate images and the effects of particular image backgrounds (light versus dark). While the foreground of the image depicting a politician involved in a scandal remained unchanged, the background was systematically altered. The results revealed that a light background had a positive effect on recipients’ attitudes toward the politician. In contrast, participants exposed to a dark image background demanded a more severe punishment for the politician.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.