Shade match of tooth-colored restorative materials hased on a commercial shade guide

Many restorative tnaterials are claimed by their manufacturers to match the Vita shade guide. To verifithis claim, 40 dental personnel were asked to color match five different restorative materials to their respective Vita shade tabs according to a 5-point scale (I = ver - poor color match; 5 = excellent color match). Three shades were chosen for each restorative material (a mid Value shade as well as the highest Value shade and the lowest Value shade present in each system). Pooled scores indicated that the resin composite materials had significantly better overall shade match than did the other tnaterials evaluated and that one resin-modified glass-ionomer cement had significantly better shade match than did the "compotner" and another resirt-tnodified glass-ionomer cement. Only 11% of the scores for all material and shade cotnbinations were given a good or excellent rating (score greater than 3). Shade match to the Vita shade guide was tiot materiai dependent but tended to differ among the different Value shades evaluated

Unpacking Big Systems -- Natural Language Processing Meets Network Analysis. A Study of Smart Grid Development in Denmark.

Studies within the detection of technological trajectories and technology forecasting tend traditionally to rely on patent or bibliometric data. The main drawback of these invention-focused approaches is their inability to account for many mainly non-technical factors related to the social and institutional framing of technology. Value driven policies, technological and institutional path dependencies or user expectations and routines have major impact on the technological outcomes in a particular context. This paper suggests a new method for the mapping and analysis of large (technical) systems and contained technological trajectories on a national level using a combination of methods from statistical natural language processing, vector space modelling and network analysis. The proposed approach does not aim at replacing the researcher or expert but rather offers the possibility to algorithmically structure and to some extent quantify unstructured text data. The utilized filtered corpora consist of two types of Danish text-documents: 99 R&DD project descriptions and 574 (initially before filtering 813) non-academic/industrial journal publications dealing with the development of the smart energy grid in Denmark. Results show that in the explored case it is not mainly new technologies and applications that are driving change but innovative re-combinations of old and new technologies

LAGOS-NE : A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. lakes

Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states. LAGOS-NE contains data for 51101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 datamodules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situmeasurements of lake water quality for a subset of the lakes fromthe past 3 decades for approximately 2600â\u80\u9312 000 lakes depending on the variable. The database contains approximately 150000 measures of total phosphorus, 200 000 measures of chlorophyll, and 900 000 measures of Secchi depth. The water quality data were compiled from87 lake water quality data sets fromfederal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest andmost comprehensive databases of its type because it includes both in situmeasurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scale