Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb

In this work we explore the use of reinforcement learning (RL) to help with human decision making, combining state-of-the-art RL algorithms with an application to prosthetics. Managing human-machine interaction is a problem of considerable scope, and the simplification of human-robot interfaces is especially important in the domains of biomedical technology and rehabilitation medicine. For example, amputees who control artificial limbs are often required to quickly switch between a number of control actions or modes of operation in order to operate their devices. We suggest that by learning to anticipate (predict) a user's behaviour, artificial limbs could take on an active role in a human's control decisions so as to reduce the burden on their users. Recently, we showed that RL in the form of general value functions (GVFs) could be used to accurately detect a user's control intent prior to their explicit control choices. In the present work, we explore the use of temporal-difference learning and GVFs to predict when users will switch their control influence between the different motor functions of a robot arm. Experiments were performed using a multi-function robot arm that was controlled by muscle signals from a user's body (similar to conventional artificial limb control). Our approach was able to acquire and maintain forecasts about a user's switching decisions in real time. It also provides an intuitive and reward-free way for users to correct or reinforce the decisions made by the machine learning system. We expect that when a system is certain enough about its predictions, it can begin to take over switching decisions from the user to streamline control and potentially decrease the time and effort needed to complete tasks. This preliminary study therefore suggests a way to naturally integrate human- and machine-based decision making systems.Comment: 5 pages, 4 figures, This version to appear at The 1st Multidisciplinary Conference on Reinforcement Learning and Decision Making, Princeton, NJ, USA, Oct. 25-27, 201

Evaluation of pyrolysis processes and biochar quality in the operation of flame curtain pyrolysis kiln for sustainable biochar production

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Joint genomic prediction of canine hip dysplasia in UK and US Labrador Retrievers

Canine hip dysplasia, a debilitating orthopedic disorder that leads to osteoarthritis and cartilage degeneration, is common in several large-sized dog breeds and shows moderate heritability suggesting that selection can reduce prevalence. Estimating genomic breeding values require large reference populations, which are expensive to genotype for development of genomic prediction tools. Combining datasets from different countries could be an option to help build larger reference datasets without incurring extra genotyping costs. Our objective was to evaluate genomic prediction based on a combination of UK and US datasets of genotyped dogs with records of Norberg angle scores, related to canine hip dysplasia. Prediction accuracies using a single population were 0.179 and 0.290 for 1,179 and 242 UK and US Labrador Retrievers, respectively. Prediction accuracies changed to 0.189 and 0.260, with an increased bias of genomic breeding values when using a joint training set (biased upwards for the US population and downwards for the UK population). Our results show that in this study of canine hip dysplasia, little or no benefit was gained from using a joint training set as compared to using a single population as training set. We attribute this to differences in the genetic background of the two populations as well as the small sample size of the US dataset

Marine substratum map of the Causeway Coast, Northern Ireland

A 1:30,000 substratum map for an area off the north coast of Ireland is presented. The study area is bounded in the south by the Causeway coastline and in the north by the following coordinates: top left corner (6°43′36″W, 55°17′N) and top right corner (6°27′W, 55°17′N). This mapping has been made possible through the availability of full seafloor coverage multibeam swath bathymetry and backscatter data (both gridded to 1 m), together with ground-truthing data collected over the past 40 years. Bathymetry data were used to generate terrain indices such as slope, rugosity, aspect, fine- and broad-scale Benthic Position Index, whilst the backscatter data were interpreted visually, subjected to an unsupervised classification process using QTC Multiview, and combined with the bathymetry-derived parameters into a clustermap in ArcGIS. The resulting maps allowed us to divide the seabed into 10 distinct acoustic classes, which, linked to sediment samples, diver surveys, underwater video-tows and remotely operated vehicle surveys, were converted into a substratum map. This is the most accurate seafloor substratum map to date for the north coast of Ireland and could form the basis for more in-depth geological, biological and hydrodynamic studies of this highly dynamic coastline

Marine substratum and biotope maps of the Maidens/Klondyke bedrock outcrops, Northern Ireland

The Maidens (including the North and Outer Klondyke) are a group of bedrock extrusions about 14 km northeast of Larne, off the coast of Northern Ireland (central point for Maidens Complex: 54°57′50.0, −5°42′20.0). Multibeam echosounder data have been combined with extensive ground-truthing to produce broad-scale substratum and biotope maps for the site. The bathymetry was used to derive rasters of slope gradient, rugosity, aspect, and fine- and broad-scale benthic position index which were used for further analyses with Principal Components Analysis. Ground-truthing data were used to create sample signatures and a Maximum Likelihood Analysis performed to classify the surfaces according to that signature. The supervised classifications generated distributions for three broad-scale substrata and habitat biotopes (six level three biotopes, four level four and one level five biotope). The maps provide critical information and distributions that greatly facilitate the conservation, management and monitoring of a proposed Special Area of Conservation

Microsecond dynamics control the HIV-1 Envelope conformation

The HIV-1 Envelope (Env) glycoprotein facilitates host cell fusion through a complex series of receptor-induced structural changes. Although remarkable progress has been made in understanding the structures of various Env conformations, microsecond timescale dynamics have not been studied experimentally. Here, we used time-resolved, temperature-jump small-angle x-ray scattering to monitor structural rearrangements in an HIV-1 Env SOSIP ectodomain construct with microsecond precision. In two distinct Env variants, we detected a transition that correlated with known Env structure rearrangements with a time constant in the hundreds of microseconds range. A previously unknown structural transition was also observed, which occurred with a time constant below 10 μs, and involved an order-to-disorder transition in the trimer apex. Using this information, we engineered an Env SOSIP construct that locks the trimer in the prefusion closed state by connecting adjacent protomers via disulfides. Our findings show that the microsecond timescale structural dynamics play an essential role in controlling the Env conformation with impacts on vaccine design

Implementation of Virtual Reality Motivated Physical Activity via Omnidirectional Treadmill in a Supported Living Facility for Older Adults: A Mixed-Methods Evaluation.: Virtual reality to motivate physical activity for older adults

Virtual reality (VR) can support healthy ageing, but few devices have been trialed with frail older adults to increase physical activity. We conducted a preliminary mixed-methods implementation evaluation of an omnidirectional VR treadmill and a static VR experience with seven older adults over a six-week period in a supported living facility. Frequency of use and pre-post physical functioning measures were collected, mainly to establish technology suitability based on person characteristics. Diary entries following technology use, resident focus group and staff interview revealed technology acceptance and perceived potential for increasing physical activity, health and wellbeing through accessing virtual environments, which motivated continued activity. Results demonstrated technology suitability for a range of older adults with various mobility and physical impairments. However, residents noted interest in a seated treadmill for physical activity without perceived risks of falls with standing treadmills. Staff raised considerations around care home implementations including usability, cost and space

Characterization of EMAT guided wave reflectivity on welded structures for use in ranging

Guided wave ranging measurements offers an elegant method to localize an inspection robot relative to the geometric features, such as welds, of a structure under test. This paper characterizes the suitability of various EMAT generated guided wave modes when reflecting from butt welds for the purpose of choosing a low frequency mode suitable for accurate ranging. Wave modes were tested in 10mm mild steel plate in experiment and simulation, the method of data extraction is discussed as well as the determination of the wave mode best suited for weld ranging by means of comparison of the reflection coefficients. The authors conclude SH1 at a frequency-thickness product of 2 MHz.mm, is shown to be a highly suitable wave mode for gaining a large reflection from a weld, with an average reflection co-efficient of approximately 0.45 across four different sized weld crowns. A ranging over 1 meter experimentally was demonstrated to have a 2.65% error using our method. This work will enable simultaneous detailed mapping through ranging and inspection of large welded structures by mobile robotic inspection systems using EMAT'