The Silurian Hypothesis: Would It Be Possible to Detect an Industrial Civilization in the Geological Record?

If an industrial civilization had existed on Earth many millions of years prior to ourown era, what traces would it have left and would they be detectable today? We summarize the likely geological fingerprint of the Anthropocene, and demonstrate that while clear, it will not differ greatly in many respects from other known events in the geological record. We then propose tests that could plausibly distinguish an industrial cause from an otherwise naturally occurring climate event

Call preparation documents: Guide for Applicants, Model Contract, Proposal Template, Call text, and publication plan for the call

Project HORSE, co-funded from the European Union’s Horizon 2020 research and innovation programme under agreement No 680734, foresees as an eligible activity the provision of financial support to third parties, as means to achieve its own objectives. The HORSE framework is driven by and validated with end-users - manufacturing companies- in two steps: in the first, the framework was jointly developed together with the selected end-users (Pilot Experiments); in the second, its suitability and transferability to further applications will be validated with new end-users recruited via this Open Call

Hygiene: new hopes, new horizons.

Although promotion of safe hygiene is the single most cost-effective means of preventing infectious disease, investment in hygiene is low both in the health and in the water and sanitation sectors. Evidence shows the benefit of improved hygiene, especially for improved handwashing and safe stool disposal. A growing understanding of what drives hygiene behaviour and creative partnerships are providing fresh approaches to change behaviour. However, some important gaps in our knowledge exist. For example, almost no trials of the effectiveness of interventions to improve food hygiene in developing countries are available. We also need to figure out how best to make safe hygiene practices matters of daily routine that are sustained by social norms on a mass scale. Full and active involvement of the health sector in getting safe hygiene to all homes, schools, and institutions will bring major gains to public health

A Biologically Motivated Software Retina for Robotic Sensors Based on Smartphone Technology

A key issue in designing robotics systems is the cost of an integrated camera sensor that meets the bandwidth/processing requirement for many advanced robotics applications, especially lightweight robotics applications, such as visual surveillance or SLAM in autonomous aerial vehicles. There is currently much work going on to adapt smartphones to provide complete robot vision systems, as the phone is so exquisitely integrated having camera(s), inertial sensing, sound I/O and excellent wireless connectivity. Mass market production makes this a very low-cost platform and manufacturers from quadrotor drone suppliers to children’s toys, such as the Meccanoid robot, employ a smartphone to provide a vision system/control system. Accordingly, many research groups are attempting to optimise image analysis, computer vision and machine learning libraries for the smartphone platform. However current approaches to robot vision remain highly demanding for mobile processors such as the ARM, and while a number of algorithms have been developed, these are very stripped down, i.e. highly compromised in function or performance For example, the semi-dense visual odometry implementation of [1] operates on images of only 320x240pixels. In our research we have been developing biologically motivated foveated vision algorithms, potentially some 100 times more efficient than their conventional counterparts, based on a model of the mammalian retina we have developed. Vision systems based on the foveated architectures found in mammals have the potential to reduce bandwidth and processing requirements by about x100 - it has been estimated that our brains would weigh ~60Kg if we were to process all our visual input at uniform high resolution. We have reported a foveated visual architecture that implements a functional model of the retina-visual cortex to produce feature vectors that can be matched/classified using conventional methods, or indeed could be adapted to employ Deep Convolutional Neural Nets for the classification/interpretation stage, [2,3,4]. We are now at the early stages of investigating how best to port our foveated architecture onto a smartphone platform. To achieve the required levels of performance we propose to optimise our retina model to the ARM processors utilised in smartphones, in conjunction with their integrated GPUs, to provide a foveated smart vision system on a smartphone. Our current goal is to have a foveated system running in real-time to serve as a front-end robot sensor for tasks such as general purpose object recognition and reliable dense SLAM using a commercial off-the-shelf smartphone which communicates with conventional hardware performing back-end visual classification/interpretation. We believe that, as in Nature, space-variance is the key to achieving the necessary data reduction to be able to implement the complete visual processing chain on the smartphone itself

Bimetric gravity is cosmologically viable

Bimetric theory describes gravitational interactions in the presence of an extra spin-2 field. Previous work has suggested that its cosmological solutions are generically plagued by instabilities. We show that by taking the Planck mass for the second metric, $M_f$, to be small, these instabilities can be pushed back to unobservably early times. In this limit, the theory approaches general relativity with an effective cosmological constant which is, remarkably, determined by the spin-2 interaction scale. This provides a late-time expansion history which is extremely close to $\Lambda$CDM, but with a technically-natural value for the cosmological constant. We find $M_f$ should be no larger than the electroweak scale in order for cosmological perturbations to be stable by big-bang nucleosynthesis. We further show that in this limit the helicity-0 mode is no longer strongly-coupled at low energy scales.Comment: 8+2 pages, 2 tables. Version published in PLB. Minor typo corrections from v

Accuracy of Patient-Specific Organ Dose Estimates Obtained Using an Automated Image Segmentation Algorithm

The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was -7%, with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors

Correction of Bathymetric Survey Artifacts Resulting from Apparent Wave-Induced Vertical Position of an AUV

Recent increases in the capability and reliability of autonomous underwater vehicles (AUVs) have provided the opportunity to conduct bathymetric seafloor surveys in shallow water (\u3c 50 m). Unfortunately, surveys of this water depth may contain artifacts induced by large amplitude wave motion at the surface. The artifacts occur when an onboard pressure sensor determines the depth of the AUV. Waves overhead induce small pressure fluctuations at depth, which modulate the AUV’s pressure sensor output without causing actual vertical movement of the AUV. Since bathymetric measurements are made with respect to the AUV’s depth, these pressure fluctuations, in turn, modulate the measurement of the seafloor. The result is a periodic across-track, vertical offset of the seafloor profile (similar to a heave artifact sometimes common in surface vessel surveys). In this paper we describe our experience with the “Gavia” model AUV (Hafmynd EHF, Iceland) in a recent bathymetric survey during which wave action overhead induced such an artifact with a peak-to-peak amplitude as large as 1 meter. A method for removing the artifact as well as recommendations for modifications to the sonar, INS and AUV to mitigate the effect in the future are provided