A functional role of the sky’s polarization pattern for orientation in the greater mouse-eared bat

Animals can call on a multitude of sensory information to orient and navigate. In some cases they may calibrate these cues against each other to establish the most accurate information available. One such cue is the pattern of polarized light in the sky, which may be used as a geographical reference to calibrate other cues in the compass mechanism. Mammals, however, have not been shown to use this cue, even though they do calibrate a magnetic compass with sunset. In this paper we demonstrate that bats use polarization cues at sunset to calibrate a magnetic compass, subsequently used for orientation during a homing experiment. It is thus the only mammal known so far to make use of the polarization pattern in the sky. This is an intriguing finding as currently there is no clear understanding of how this cue is perceived in this taxon and has general implications for the sensory biology of mammalian vision.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Large-scale association analysis identifies new risk loci for coronary artery disease

Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2)

Field Measurements of a Full Scale Tidal Device

Field testing studies are required for tidal turbine device developers to determine the performance of their turbines in tidal flows. Full-scale testing of the SCHOTTEL tidal turbine has been conducted at Queen’s University Belfast’s tidal site at Strangford Lough, NI. The device was mounted on a floating barge. Testing was conducted over 48 days, for 288 h, during flood tides in daylight hours. Several instruments were deployed, resulting in an expansive data set. The performance results from this data set are presented here. The device, rated to 50 kW at 2.75 m/s was tested in flows up to 2.5 m/s, producing up to 19 kW, when time-averaged. The thrust on the turbine reached 17 kN in the maximum flow. The maximum system efficiency of the turbine in these flows reached 35%. The test campaign was very successful and further tests may be conducted at higher flow speeds in a similar tidal environment.

Ferroelectricity in Si-doped HfO2 Revealed: A Binary Lead-free Ferroelectric

Static domain structures and polarization dynamics of silicon doped HfO2 are explored. The evolution of ferroelectricity as a function of Si-doping level driving the transition from paraelectricity via ferroelectricity to antiferroelectricity is investigated. Ferroelectric and antiferroelectric properties can be observed locally on the pristine, poled and electroded surfaces, providing conclusive evidence to intrinsic ferroic behavior.

Classifying pedestrian movement behaviour from GPS trajectories using visualization and clustering

The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted from these large movement data sets. Geovisual analytics offers powerful techniques to achieve this. This article describes a new geovisual analytics tool specifically designed for movement data. The tool features the classic space-time cube augmented with a novel clustering approach to identify common behaviour. These techniques were used to analyse pedestrian movement in a city environment which revealed the effectiveness of the tool for identifying spatiotemporal patterns. © 2014 Taylor & Francis.

Interpreting pedestrian behaviour by visualising and clustering movement data

Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube. Additionally, a new approach, using the mathematical description of motion within a space-time cube, is used to determine the similarity of trajectories and forms the basis for clustering them. These techniques were used to analyse pedestrian movement. The results reveal interesting and useful spatiotemporal patterns and clusters of pedestrians exhibiting similar behaviour.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

Gremlin1 preferentially binds to Bone Morphogenetic Protein-2 (BMP-2) and BMP-4 over BMP-7

Gremlin (Grem1) is a member of the DAN family of secreted bone morphogenetic protein (BMP) antagonists. Bone morphogenetic protein-7 (BMP-7) mediates protective effects during renal fibrosis-associated with diabetes and other renal diseases. The pathogenic mechanism of Grem1 during DN has been suggested to be binding and inhibition of BMP-7. However, the precise interactions between Grem1, BMP-7 and other BMPs have not been accurately defined. Here we show the affinity of Grem1 for BMP-7 is lower than that of BMP-2 and BMP-4, using a combination of surface plasmon resonance and cell culture techniques. Using kidney proximal tubule cells and HEK-293 cell Smad1/5/8 phosphorylation and BMP-dependent gene expression as readout, Grem1 consistently demonstrated a higher affinity for BMP-2>4>7. Cell-associated Grem1 did not inhibit BMP-2 or BMP-4 mediated signalling, suggesting that Grem1-BMP-2 binding occurred in solution, preventing BMP receptor activation. These data suggest that Grem1 preferentially binds to BMP-2 and this may be the dominant complex in a disease situation where levels of Grem1 and BMPs are elevated.

Determinants of root-associated fungal communities within Asteraceae in a semi-arid grassland

Summary

1.While plant–fungal interactions are important determinants of plant community assembly and ecosystem functioning, the processes underlying fungal community composition are poorly understood.
2.Here, we studied for the first time the root-associated eumycotan communities in a set of co-occurring plant species of varying relatedness in a species-rich, semi-arid grassland in Germany. The study system provides an opportunity to evaluate the importance of host plants and gradients in soil type and landscape structure as drivers of fungal community structure on a relevant spatial scale. We used 454 pyrosequencing of the fungal internal transcribed spacer region to analyse root-associated eumycotan communities of 25 species within the Asteraceae, which were sampled at different locations within a soil type gradient. We partitioned the variance accounted for by three predictors (host plant phylogeny, spatial distribution and soil type) to quantify their relative roles in determining fungal community composition and used null model analyses to determine whether community composition was influenced by biotic interactions among the fungi.
3.We found a high fungal diversity (156 816 sequences clustered in 1100 operational taxonomic units (OTUs)). Most OTUs belonged to the phylum Ascomycota (35.8%); the most abundant phylotype best-matched Phialophora mustea. Basidiomycota were represented by 18.3%, with Sebacina as most abundant genus. The three predictors explained 30% of variation in the community structure of root-associated fungi, with host plant phylogeny being the most important variance component. Null model analysis suggested that many fungal taxa co-occurred less often than expected by chance, which demonstrates spatial segregation and indicates that negative interactions may prevail in the assembly of fungal communities.
4.Synthesis. The results show that the phylogenetic relationship of host plants is the most important predictor of root-associated fungal community assembly, indicating that fungal colonization of host plants might be facilitated by certain plant traits that may be shared among closely related plant species.

Arbuscular mycorrhizal fungal communities are phylogenetically clustered at small scales

Next-generation sequencing technologies with markers covering the full Glomeromycota phylum were used to uncover phylogenetic community structure of arbuscular mycorrhizal fungi (AMF) associated with Festuca brevipila. The study system was a semi-arid grassland with high plant diversity and a steep environmental gradient in pH, C, N, P and soil water content. The AMF community in roots and rhizosphere soil were analyzed separately and consisted of 74 distinct operational taxonomic units (OTUs) in total. Community-level variance partitioning showed that the role of environmental factors in determining AM species composition was marginal when controlling for spatial autocorrelation at multiple scales. Instead, phylogenetic distance and spatial distance were major correlates of AMF communities: OTUs that were more closely related (and which therefore may have similar traits) were more likely to co-occur. This pattern was insensitive to phylogenetic sampling breadth. Given the minor effects of the environment, we propose that at small scales closely related AMF positively associate through biotic factors such as plant-AMF filtering and interactions within the soil biota.