CityPulse: Large Scale Data Analytics Framework for Smart Cities

Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains, such as healthcare, environmental monitoring, urban systems, and control and management applications, among several other areas. Cities currently face an increasing demand for providing services that can have an impact on people's everyday lives. The CityPulse framework supports smart city service creation by means of a distributed system for semantic discovery, data analytics, and interpretation of large-scale (near-)real-time Internet of Things data and social media data streams. To goal is to break away from silo applications and enable cross-domain data integration. The CityPulse framework integrates multimodal, mixed quality, uncertain and incomplete data to create reliable, dependable information and continuously adapts data processing techniques to meet the quality of information requirements from end users. Different than existing solutions that mainly offer unified views of the data, the CityPulse framework is also equipped with powerful data analytics modules that perform intelligent data aggregation, event detection, quality assessment, contextual filtering, and decision support. This paper presents the framework, describes its components, and demonstrates how they interact to support easy development of custom-made applications for citizens. The benefits and the effectiveness of the framework are demonstrated in a use-case scenario implementation presented in this paper

The locus for bovine dilated cardiomyopathy maps to chromosome 18

Bovine dilated cardiomyopathy (BDCMP) is a severe and terminal disease of the heart muscle observed in Holstein-Friesian cattle over the last 30 years. There is strong evidence for an autosomal recessive mode of inheritance for BDCMP. The objective of this study was to genetically map BDCMP, with the ultimate goal of identifying the causative mutation. A whole-genome scan using 199 microsatellite markers and one SNP revealed an assignment of BDCMP to BTA18. Fine-mapping on BTA18 refined the candidate region to the MSBDCMP06-BMS2785 interval. The interval containing the BDCMP locus was confirmed by multipoint linkage analysis using the software loki. The interval is about 6.7 Mb on the bovine genome sequence (Btau 3.1). The corresponding region of HSA19 is very gene-rich and contains roughly 200 genes. Although telomeric of the marker interval, TNNI3 is a possible positional and a functional candidate for BDCMP given its involvement in a human form of dilated cardiomyopathy. Sequence analysis of TNNI3 in cattle revealed no mutation in the coding sequence, but there was a G-to-A transition in intron 6 (AJ842179:c.378+315G>A). The analysis of this SNP using the study's BDCMP pedigree did not conclusively exclude TNNI3 as a candidate gene for BDCMP. Considering the high density of genes on the homologous region of HSA19, further refinement of the interval on BTA18 containing the BDCMP locus is needed