The production of glow precursors by oxidative erosion of spacecraft surfaces

Erosion rates of organic materials are measured during a recent flight of the shuttle (STS-8). Several forms of carbon and a variety of thermosetting and thermoplastic polymers are exposed to the ram beam of atomic oxygen. Arrhenius energies of about 1000 to 2000 cal/mole were measured from the rate dependencies on temperature. If some simple assumptions are made about the chemical nature of the desorbed species, the data can be used to estimate production rates at surfaces in orbit under different conditions of temperature, oxygen atom flux, and material surface conditions

Why will rat's go where rats will not

Experimental evidence indicates that regular plurals are nearly always omitted from English compounds (e.g., rats-eater) while irregular plurals may be included within these structures (e.g., mice-chaser). This phenomenon is considered to be good evidence to support the dual mechanism model of morphological processing (Pinker & Prince, 1992). However, evidence from neural net modelling has shown that a single route associative memory based account might provide an equally, if not more, valid explanation of the compounding phenomenon

Plural morphology in compounding is not good evidence to support the dual mechanism model

The compounding phenomena is considered to be good evidence to support the dual mechanism model of morphological processing (Pinker & Prince, 1992). However evidence from initial neural net modeling has shown that a single route associative memory based account might provide an equally, if not more valid explanation of the treatment of plurals in compounds. Further neural net modeling and empirical work is proposed to test this single route accoun

Bayesian Gait Optimization for Bipedal Locomotion

One of the key challenges in robotic bipedal locomotion is finding gait parameters that optimize a desired performance criterion, such as speed, robustness or energy efficiency. Typically, gait optimization requires extensive robot experiments and specific expert knowledge. We propose to apply data-driven machine learning to automate and speed up the process of gait optimization. In particular, we use Bayesian optimization to efficiently find gait parameters that optimize the desired performance metric. As a proof of concept we demonstrate that Bayesian optimization is near-optimal in a classical stochastic optimal control framework. Moreover, we validate our approach to Bayesian gait optimization on a low-cost and fragile real bipedal walker and show that good walking gaits can be efficiently found by Bayesian optimization. © 2014 Springer International Publishing

Smoking, dementia and cognitive decline in the elderly, a systematic review.

Background. Nicotine may aid reaction time, learning and memory, but smoking increases cardiovascular risk. Cardiovascular risk factors have been linked to increased risk of dementia. A previous meta-analysis found that current smokers were at higher risk of subsequent dementia, Alzheimers disease, vascular dementia and cognitive decline. Methods. In order to update and examine this further a systematic review and meta-analysis was carried out using different search and inclusion criteria, database selection and more recent publications. Both reviews were restricted to those aged 65 and over. Results. The review reported here found a significantly increased risk of Alzheimers disease with current smoking and a likely but not significantly increased risk of vascular dementia, dementia unspecified and cognitive decline. Neither review found clear relationships with former smoking. Conclusion. Current smoking increases risk of Alzheimers disease and may increase risk of other dementias. This reinforces need for smoking cessation, particularly aged 65 and over. Nicotine alone needs further investigation. © 2008 Peters et al; licensee BioMed Central Ltd

Maximally entangled mixed states: Creation and concentration

Using correlated photons from parametric downconversion, we extend the boundaries of experimentally accessible two-qubit Hilbert space. Specifically, we have created and characterized maximally entangled mixed states (MEMS) that lie above the Werner boundary in the linear entropy-tangle plane. In addition, we demonstrate that such states can be efficiently concentrated, simultaneously increasing both the purity and the degree of entanglement. We investigate a previously unsuspected sensitivity imbalance in common state measures, i.e., the tangle, linear entropy, and fidelity.Comment: 4 pages, 3 figures, 1 table; accepted versio

Feedback Error Learning for Rhythmic Motor Primitives

Abstract — Rhythmic motor primitives can be used to learn a variety of oscillatory behaviors from demonstrations or reward signals, e.g., hopping, walking, running and ball-bouncing. However, frequently, such rhythmic motor primitives lead to failures unless a stabilizing controller ensures their functionality, e.g., a balance controller for a walking gait. As an ideal oscillatory behavior requires the stabilizing controller only for exceptions, e.g., to prevent failures, we devise an online learning approach that reduces the dependence on the stabilizing controller. Inspired by related approaches in model learning, we employ the stabilizing controller’s output as a feedback error learning signal for adapting the gait. We demonstrate the resulting approach in two scenarios: a rhythmic arm’s movements and gait adaptation of an underactuated biped. I