GENESI: Wireless sensor networks for structural monitoring

The GENESI project has the ambitious goal of bringing WSN technology to the level where it can provide the core of the next generation of systems for structural health monitoring that are long lasting, pervasive and totally distributed and autonomous. This goal requires embracing engineering and scientific challenges never successfully tackled before. Sensor nodes will be redesigned to overcome their current limitations, especially concerning energy storage and provisioning (we need devices with virtually infinite lifetime) and resilience to faults and interferences (for reliability and robustness). New software and protocols will be defined to fully take advantage of the new hardware, providing new paradigms for cross-layer interaction at all layers of the protocol stack and satisfying the requirements of a new concept of Quality of Service (QoS) that is application-driven, truly reflecting the end user perspective and expectations. The GENESI project will develop long lasting sensor nodes by combining cutting edge technologies for energy generation from the environment (energy harvesting) and green energy supply (small form factor fuel cells); GENESI will define models for energy harvesting, energy conservation in super-capacitors and supplemental energy availability through fuel cells, in addition to the design of new algorithms and protocols for dynamic allocation of sensing and communication tasks to the sensors. The project team will design communication protocols for large scale heterogeneous wireless sensor/actuator networks with energy-harvesting capabilities and define distributed mechanisms for context assessment and situation awareness. This paper presents an analysis of the GENESI system requirements in order to achieve the ambitious goals of the project. Extending from the requirements presented, the emergent system specification is discussed with respect to the selection and integration of relevant system components.The resulting integrated system will be evaluated and characterised to ensure that it is capable of satisfying the functional requirements of the projec

Vector-Based Integration of Local and Long-Range Information in Visual Cortex

Integration of inputs by cortical neurons provides the basis for the complex information processing performed in the cerebral cortex. Here, we propose a new analytic framework for understanding integration within cortical neuronal receptive fields. Based on the synaptic organization of cortex, we argue that neuronal integration is a systems--level process better studied in terms of local cortical circuitry than at the level of single neurons, and we present a method for constructing self-contained modules which capture (nonlinear) local circuit interactions. In this framework, receptive field elements naturally have dual (rather than the traditional unitary influence since they drive both excitatory and inhibitory cortical neurons. This vector-based analysis, in contrast to scalarsapproaches, greatly simplifies integration by permitting linear summation of inputs from both "classical" and "extraclassical" receptive field regions. We illustrate this by explaining two complex visual cortical phenomena, which are incompatible with scalar notions of neuronal integration

Optimized broad-histogram simulations for strong first-order phase transitions: Droplet transitions in the large-Q Potts model

The numerical simulation of strongly first-order phase transitions has remained a notoriously difficult problem even for classical systems due to the exponentially suppressed (thermal) equilibration in the vicinity of such a transition. In the absence of efficient update techniques, a common approach to improve equilibration in Monte Carlo simulations is to broaden the sampled statistical ensemble beyond the bimodal distribution of the canonical ensemble. Here we show how a recently developed feedback algorithm can systematically optimize such broad-histogram ensembles and significantly speed up equilibration in comparison with other extended ensemble techniques such as flat-histogram, multicanonical or Wang-Landau sampling. As a prototypical example of a strong first-order transition we simulate the two-dimensional Potts model with up to Q=250 different states on large systems. The optimized histogram develops a distinct multipeak structure, thereby resolving entropic barriers and their associated phase transitions in the phase coexistence region such as droplet nucleation and annihilation or droplet-strip transitions for systems with periodic boundary conditions. We characterize the efficiency of the optimized histogram sampling by measuring round-trip times tau(N,Q) across the phase transition for samples of size N spins. While we find power-law scaling of tau vs. N for small Q \lesssim 50 and N \lesssim 40^2, we observe a crossover to exponential scaling for larger Q. These results demonstrate that despite the ensemble optimization broad-histogram simulations cannot fully eliminate the supercritical slowing down at strongly first-order transitions.Comment: 11 pages, 12 figure

Shear-Velocity Structure and Dynamics Beneath the Sicily Channel and Surrounding Regions of the Central Mediterranean Inferred From Seismic Surface Waves

The evolution of the Sicily Channel Rift Zone (SCRZ) is thought to accommodate the regional tectonic stresses of the Calabrian subduction system. Much of the observations we have today are either limited to the surface or to the upper crust or deeper from regional seismic tomography, missing important details about the lithospheric structure and dynamics. It is unclear whether the rifting is passive from far-field extensional stresses or active from mantle upwelling beneath. We measure Rayleigh-and Love-wave phase velocities from ambient seismic noise and invert for 3-D shear-velocity and radial anisotropic models. Variations in crustal S-velocities coincide with topographic and tectonic features. The Tyrrhenian Sea has a ∼10 km thin crust, followed by the SCRZ (∼20 km). The thickest crust is beneath the Apennine-Maghrebian Mountains (∼55 km). Areas experiencing extension and intraplate volcanism have positive crustal radial anisotropy (VSH > VSV); areas experiencing compression and subduction-related volcanism have negative anisotropy. The crustal anisotropy across the Channel shows the extent of the extension. Beneath the Tyrrhenian Sea, we find very low sub-Moho S-velocities. In contrast, the SCRZ has a thin mantle lithosphere underlain by a low-velocity zone. The lithosphere-asthenosphere boundary rises from 60 km depth beneath Tunisia to ∼33 km beneath the SCRZ. Negative radial anisotropy in the upper mantle beneath the SCRZ is consistent with vertical mantle flow. We hypothesize a more active mantle upwelling beneath the rift than previously thought from an interplay between poloidal and toroidal fluxes related to the Calabrian slab, which in turn produces uplift at the surface and induces volcanism

Pervasive Rise of Small-scale Deforestation in Amazonia

Understanding forest loss patterns in Amazonia, the Earth’s largest rainforest region, is critical for effective forest conservation and management. Following the most detailed analysis to date, spanning the entire Amazon and extending over a 14-year period (2001–2014), we reveal significant shifts in deforestation dynamics of Amazonian forests. Firstly, hotspots of Amazonian forest loss are moving away from the southern Brazilian Amazon to Peru and Bolivia. Secondly, while the number of new large forest clearings (>50 ha) has declined significantly over time (46%), the number of new small clearings (<1 ha) increased by 34% between 2001–2007 and 2008–2014. Thirdly, we find that small-scale low-density forest loss expanded markedly in geographical extent during 2008–2014. This shift presents an important and alarming new challenge for forest conservation, despite reductions in overall deforestation rates