SPARCNN: SPAtially Related Convolutional Neural Networks

The ability to accurately detect and classify objects at varying pixel sizes in cluttered scenes is crucial to many Navy applications. However, detection performance of existing state-of the-art approaches such as convolutional neural networks (CNNs) degrade and suffer when applied to such cluttered and multi-object detection tasks. We conjecture that spatial relationships between objects in an image could be exploited to significantly improve detection accuracy, an approach that had not yet been considered by any existing techniques (to the best of our knowledge) at the time the research was conducted. We introduce a detection and classification technique called Spatially Related Detection with Convolutional Neural Networks (SPARCNN) that learns and exploits a probabilistic representation of inter-object spatial configurations within images from training sets for more effective region proposals to use with state-of-the-art CNNs. Our empirical evaluation of SPARCNN on the VOC 2007 dataset shows that it increases classification accuracy by 8% when compared to a region proposal technique that does not exploit spatial relations. More importantly, we obtained a higher performance boost of 18.8% when task difficulty in the test set is increased by including highly obscured objects and increased image clutter.Comment: 6 pages, AIPR 2016 submissio

The Dark Matter Telescope

Weak gravitational lensing enables direct reconstruction of dark matter maps over cosmologically significant volumes. This research is currently telescope-limited. The Dark Matter Telescope (DMT) is a proposed 8.4 m telescope with a 3 degree field of view, with an etendue of 260 $(m. degree)^2$, ten times greater than any other current or planned telescope. With its large etendue and dedicated observational mode, the DMT fills a nearly unexplored region of parameter space and enables projects that would take decades on current facilities. The DMT will be able to reach 10-sigma limiting magnitudes of 27-28 magnitude in the wavelength range .3 - 1 um over a 7 square degree field in 3 nights of dark time. Here we review its unique weak lensing cosmology capabilities and the design that enables those capabilities.Comment: in-press version with additions; to appear in proceedings of the Dark Matter 2000 conference (Santa Monica, February 2000) to be published by Springe

The changing nature of risk and risk management: the challenge of borders, uncertainty and resilience

No abstract available

Estimating the number needed to treat from continuous outcomes in randomised controlled trials: methodological challenges and worked example using data from the UK Back Pain Exercise and Manipulation (BEAM) trial

Background Reporting numbers needed to treat (NNT) improves interpretability of trial results. It is unusual that continuous outcomes are converted to numbers of individual responders to treatment (i.e., those who reach a particular threshold of change); and deteriorations prevented are only rarely considered. We consider how numbers needed to treat can be derived from continuous outcomes; illustrated with a worked example showing the methods and challenges. Methods We used data from the UK BEAM trial (n = 1, 334) of physical treatments for back pain; originally reported as showing, at best, small to moderate benefits. Participants were randomised to receive 'best care' in general practice, the comparator treatment, or one of three manual and/or exercise treatments: 'best care' plus manipulation, exercise, or manipulation followed by exercise. We used established consensus thresholds for improvement in Roland-Morris disability questionnaire scores at three and twelve months to derive NNTs for improvements and for benefits (improvements gained+deteriorations prevented). Results At three months, NNT estimates ranged from 5.1 (95% CI 3.4 to 10.7) to 9.0 (5.0 to 45.5) for exercise, 5.0 (3.4 to 9.8) to 5.4 (3.8 to 9.9) for manipulation, and 3.3 (2.5 to 4.9) to 4.8 (3.5 to 7.8) for manipulation followed by exercise. Corresponding between-group mean differences in the Roland-Morris disability questionnaire were 1.6 (0.8 to 2.3), 1.4 (0.6 to 2.1), and 1.9 (1.2 to 2.6) points. Conclusion In contrast to small mean differences originally reported, NNTs were small and could be attractive to clinicians, patients, and purchasers. NNTs can aid the interpretation of results of trials using continuous outcomes. Where possible, these should be reported alongside mean differences. Challenges remain in calculating NNTs for some continuous outcomes

Spinal plasticity in robot-mediated therapy for the lower limbs

Robot-mediated therapy can help improve walking ability in patients following injuries to the central nervous system. However, the efficacy of this treatment varies between patients, and evidence for the mechanisms underlying functional improvements in humans is poor, particularly in terms of neural changes in the spinal cord. Here, we review the recent literature on spinal plasticity induced by robotic-based training in humans and propose recommendations for the measurement of spinal plasticity using robotic devices. Evidence for spinal plasticity in humans following robotic training is limited to the lower limbs. Body weight-supported (BWS) robotic-assisted step training of patients with spinal cord injury (SCI) or stroke patients has been shown to lead to changes in the amplitude and phase modulation of spinal reflex pathways elicited by electrical stimulation or joint rotations. Of particular importance is the finding that, among other changes to the spinal reflex circuitries, BWS robotic-assisted step training in SCI patients resulted in the re-emergence of a physiological phase modulation of the soleus H-reflex during walking. Stretch reflexes elicited by joint rotations constitute a tool of interest to probe spinal circuitry since the technology necessary to produce these perturbations could be integrated as a natural part of robotic devices. Presently, ad-hoc devices with an actuator capable of producing perturbations powerful enough to elicit the reflex are available but are not part of robotic devices used for training purposes. A further development of robotic devices that include the technology to elicit stretch reflexes would allow for the spinal circuitry to be routinely tested as a part of the training and evaluation protocols

Target product profiles for protecting against outdoor malaria transmission.

BACKGROUND\ud \ud Long-lasting insecticidal nets (LLINs) and indoor residual sprays (IRS) have decimated malaria transmission by killing indoor-feeding mosquitoes. However, complete elimination of malaria transmission with these proven methods is confounded by vectors that evade pesticide contact by feeding outdoors.\ud \ud METHODS\ud \ud For any assumed level of indoor coverage and personal protective efficacy with insecticidal products, process-explicit malaria transmission models suggest that insecticides that repel mosquitoes will achieve less impact upon transmission than those that kill them outright. Here such models are extended to explore how outdoor use of products containing either contact toxins or spatial repellents might augment or attenuate impact of high indoor coverage of LLINs relying primarily upon contact toxicity.\ud \ud RESULTS\ud \ud LLIN impact could be dramatically enhanced by high coverage with spatial repellents conferring near-complete personal protection, but only if combined indoor use of both measures can be avoided where vectors persist that prefer feeding indoors upon humans. While very high levels of coverage and efficacy will be required for spatial repellents to substantially augment the impact of LLINs or IRS, these ambitious targets may well be at least as practically achievable as the lower requirements for equivalent impact using contact insecticides.\ud \ud CONCLUSIONS\ud \ud Vapour-phase repellents may be more acceptable, practical and effective than contact insecticides for preventing outdoor malaria transmission because they need not be applied to skin or clothing and may protect multiple occupants of spaces outside of treatable structures such as nets or houses

Models of Star-Planet Magnetic Interaction

Magnetic interactions between a planet and its environment are known to lead to phenomena such as aurorae and shocks in the solar system. The large number of close-in exoplanets that were discovered triggered a renewed interest in magnetic interactions in star-planet systems. Multiple other magnetic effects were then unveiled, such as planet inflation or heating, planet migration, planetary material escape, and even modification of the host star properties. We review here the recent efforts in modelling and understanding magnetic interactions between stars and planets in the context of compact systems. We first provide simple estimates of the effects of magnetic interactions and then detail analytical and numerical models for different representative scenarii. We finally lay out a series of future developments that are needed today to better understand and constrain these fascinating interactions.Comment: 23 pages, 10 figures, accepted as a chapter in the Handbook of Exoplanet