EPSRC : Mr Joshua Brown : EP/S515188/1 Teleoperation is a field in robotics concerned with the real-time control of remotely acting robots. Such systems may be mobile or fixed-base, aerial, terrestrial or marine, and sometimes incorporate some autonomous functionality to take over either mundane or highly complex tasks from the human operator. Teleoperated robots offer users the maximum possible degree of control and oversight over pre-programmed and fully-autonomous robots, but their overall effectiveness is limited by the attentiveness and capability of the operator. This negates one of the most significant benefits of modern robotics - the elimination of human error. This project aims to evaluate a novel device of my own design and making which is able to communicate information about the robot's state to a human operator via haptic feedback, specifically vibration. For example, hazards such as loose terrain or a steep incline may not be well reported to the operator via a camera feed, and blind spots are inevitable in real world systems. The focus of my PhD is the design of this novel control device and its application in making robot teleoperation safer for the robotic vehicle and less prone to errors. Existing research in this area remains limited and the apporoach my work takes to report hazards via carefully controlled vibrations that mimic the movement and forces experienced by a robot has not been done before. The first two years of my PhD have been concerned with the design, construction and lab-based evaluation of this novel haptic device. My third year, in which I hope to undertake this project, aims to evaluate this device's utility in mobile robot teleoperation tasks in the ground (off-road, rough terrain) and aquatic domains. This project will give me access to large-scale off-road and underwater robots and the facilities to operate and test them. There is no existing research that considers applying haptic feedback to underwater robot control. These do not exist in the UK, meaning my original research proposal relied on very small model robots and computer simulations. Whilst these are useful tools, being able to access the real world systems available in Canada via my proposed supervisor would add a great deal of value to my PhD research and the results I am able to obtain from it. My proposed project in Canada will progress in two phases. The first phase will take advantage of my proposed supervisor's unique combination of expertise in mobile robotics and human perception, to conduct experiments to determine how vibrating haptic feedback can best be used to represent or recreate hazardous situations a mobile robot might encounter in real world use. These results will then very quickly inform the parameters for a second study, using the large scale off-road and aquatic robots to complete tasks that, by design, will involve navigating certain environmental hazards such as loose terrain, obstacles, very uneven ground, strong water currents, etc. The value of haptic feedback in helping the human operators to navigate these hazards will be assessed.

Our project will deliver a step-change for terrestrial biodiversity monitoring by developing new sampling arrays and capabilities to monitor species with airborne environmental DNA (eDNA). Environmental DNA takes the form of small fragments of DNA-bearing particles shed from animals and plants as fur, skin cells, pollen, faeces, and exhaled in breath. Recently, our team has discovered that this material is present in air and can potentially reflect local biodiversity, representing a transfer of this technology from aquatic to terrestrial ecosystems. eDNA-based methods are important because they allow scientists to target a broad range of taxonomic groups at fine temporal scales, which is not usually achievable with other methods of biodiversity monitoring. We will develop and optimise a sampling array composed of air samplers to measure change in biodiversity over time and to evaluate how animals use habitat to move around the landscape (functional connectivity). We propose to evaluate existing commercial options because many air samplers have already been developed for air quality and microbial monitoring applications, but the use of these instruments to capture airborne eDNA from animals and plants represents a novel use case which must be validated and optimised. We will test a variety of active (a power source is used to draw air through a filter onto which particles are captured) and passive (particles are deposited onto a surface and no power source is used) units using a combination of qPCR and metabarcoding techniques to evaluate the amount of eDNA, taxonomic richness and composition detected by the samplers. Sampling media and preservation techniques will be tested in combination with the different units to optimise their effectiveness. We will use approaches from atmospheric science to understand the efficiency of the samplers at capturing eDNA particulates. We will compare the quantities of eDNA captured by samplers to predictions made by a forward dispersion model - an approach that uses wind strength and direction to model how particles move away from a source. We will optimise how samplers need to be positioned in the landscape in order to capture eDNA. Finally we will perform real-world testing of the optimised sampling arrays within two National Nature Reserves and compare our results to species records captured with conventional monitoring. We will use our array to evaluate whether animals are using areas as dispersal corridors between habitats. We envisage that potential applications will include 1) detection of taxa at scales for national reporting and targets (e.g., Environment Act targets, Environmental Improvement Plan Outcome Indicator Framework and Global Biodiversity Framework targets) and 2) monitoring species at local scales (e.g. for species recovery programme, Biodiversity Net Gain, and to inform sustainable development). Potential end-users include wildlife NGOs, government, and commercial organisations providing a monitoring service using eDNA technology. Co-creation of our asset with end-users is embedded throughout our work programme. We are working with Natural England - who deliver a large part of the terrestrial components of the Natural Capital and Ecosystem Assessment Programme - as a co-investigator. We have embedded a survey of the needs of end-users into WP1 and a second survey in which end-users will evaluate our optimised sampling asset. The final work package is dedicated to dissemination and two-way engagement with end-users.

Protein motion enables function, with celebrated examples being the oar-like stroke of myosin during muscle contraction, ATP synthase rotation and the valving of ligand-gated ion channels. However, we know almost nothing about how the majority of proteins move and how this contributes to function. This knowledge gap represents an enormous arena for discovery and opportunity to advance biotechnology and develop new drugs. Examples include the development of new gene editing tools and drugs able to bias protein dynamics toward health. Protein structural dynamics can be investigated using Hydrogen/Deuterium eXchange (HDX), a technique which is rapidly gaining popularity in UK and global bioscience. HDX involves mixing protein with deuterium for defined periods of seconds to hours, then mixing to preserve incorporated deuterium into the protein backbone, followed by analysis using mass spectrometry (MS) or nuclear magnetic resonance (NMR). Incorporation rates are used to determine protein structure and dynamics. Currently, however, exchange technology is too slow to observe highly dynamic regions, regions thought to play pivotal roles governing shape-mediated protein function. To observe these behaviours we need methods providing single millisecond or even microsecond incubations, 10,000-fold faster than conventional methods (10 seconds minimum). To achieve fast HDX, processing in wells is replaced with flow in capillaries or microchannels. Methods using turbulent flow require large protein quantities and cannot achieve single millisecond incubations. Microfluidics in various guises has been explored with each having different failings; uncontrolled incubation times, slow mixing, inability to quench, complex, costly and unreliable fabrication. To address these shortcomings, we propose a new concept based on advanced flow structuring principles to achieve ultrafast microfluidic HDX. Simulations predict precision time control with microsecond resolution. A device cloning strategy will be used for technology sharing with Jonathan Phillips (Exeter) and Derek Wilson (Toronto), the world-leaders in fast HDX-MS. An open hardware approach will enable adoption in other labs, expanding the market in readiness for commercialisation. As proof of concept, the technology will be validated using calmodulin, a protein with well-characterised dynamics and Ca2+-triggered shape-change. The discovery potential will then be test-driven using S100A9, a protein involved in fibril formation leading to neurodegeneration. Millisecond-scale structural transitions are as yet uncharted, but are thought to initiate a fibril competent state. In summary, we propose to develop, validate, explore and share an ultrafast microfluidic HDX prototype to transform the scale and reach of discovery in the science of protein structural dynamics.

The human brain uses small differences between the images reaching our two eyes to perceive the three-dimensional shape of the world around us. In order to detect these differences, known as binocular disparities, the brain must find points in one eye's image that match to points in the other eye's image. However, for any single point in an image, the brain is often forced to choose between multiple matches. The problem of finding the correct match from amongst these alternatives is known as the correspondence problem. This problem can be simplified by making assumptions about the typical shape of objects in the world, and by finding matches between different kinds of basic tokens. For example, the number of alternative solutions to the correspondence problem will be far greater if the brain uses single points of light as a basic token for matching, compared to a case where a more complex token, such as a shape or texture, is used. Furthermore, these complex tokens can be based on different kinds of information. The research proposed here examines how matching tokens based on different forms of information can be used by the brain to solve the correspondence problem. Specifically, we shall examine how the brain may solve the correspondence problem using tokens derived from mechanisms sensitive to changes in light and dark (i.e. changes in luminance), and mechanisms sensitive to changes in texture. We shall develop computer simulations of the processes used by the brain to solve the correspondence problem and measure disparity. These simulations will show how the use of different basic information for matching (i.e. changes in luminance and changes in texture) can change the nature of the correspondence problem. We shall discover whether the combined use of texture- and luminance-based matching tokens can help to reduce noise in disparity measurement and whether the use of texture-based matching can reduce the number of available solutions to the correspondence problem. Following this, we shall examine whether the brain actually makes use of the combined information available from texture and luminance. By presenting human participants with images containing disparities defined by both texture and luminance, we shall establish whether the human brain actually uses these different types of information to reduce noise, or improve its ability to solve the correspondence problem. In addition to examining whether using luminance and texture information to measure disparity helps the brain to reduce noise and simplify the correspondence problem, we shall also examine whether sensitivity to these different types of image information can help the brain to detect discontinuities in depth. Depth discontinuities arise when depth changes sharply across a small area, such as when an observer's view of one object is partially obscured by another object in front of it. The processing of texture-based disparities may help in the detection of depth discontinuities since different objects often differ in texture. We shall establish whether information of this kind may actually be useful in the detection of depth discontinuities, and whether human observers actually use this information.

EPSRC : Jordan Stewart : EP/R513386/1 Atmospheric oxidants are responsible for the degradation and ultimate removal of the vast majority of emissions into our atmosphere. A complete understanding of this chemistry is therefore essential if we are to develop effective and timely policies that address the pressing societal problems of air quality and climate change. Chlorine atoms are the least understood of these oxidants, and are currently not included in models that routinely forecast air quality and climate. However, work over the last decade suggests chlorine could be more important than previously thought. A major unanswered question is the source of chlorine in mid-continental regions, where models predict there to be very little. By contributing to an existing international measurement program looking at air quality in global megacities, this project will make measurements of key chlorine compounds in a mid-continental megacity (Toronto). This will provide vital data on the sources of chlorine in this important environment.