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.

STFC: William Parrott: ST/S505390/1 The Large Hadron Collider (LHC) at CERN, possibly the most famous physics experiment ever, and certainly one of the most exciting, continues to push the boundaries of our knowledge, and questions our perceived notions of the workings of the universe. But how well do we understand the particles that are detected there? Most particles made of quarks that are seen at the LHC have a well-understood theoretical explanation, being simple mesons and baryons with a standard quark and/or antiquark content. These confirm what we think we know about the universe, but there also seem to be particles that do not fit into this box. Recent hints of exciting new particles have prompted questions about what kinds of particles can exist within our theoretical framework, and for those that can, what masses we would expect them to have. For some non-standard particles, called tetraquarks, there is some emerging evidence that their existnce may be consistent with our current theories, and also some evidence of their possible detection at the LHC. In order to confirm the possibility of these new particles, a much clearer theoretical picture is needed and that means more precise determination of their mass. This is what we intend to calculate, using improved methods to obtain a better picture of how the binding of a particular set of possible tetraquarks depends on the masses of the quarks they contain. The unambiguous discovery of such a particle would be extremely exciting for the world of particle physics, and improved theory calculations will help the experimentalists searching for them. Another exciting frontier of physics is the development of new and better computers. Computers have become a huge part of everyday life and computing power has increased vastly since their inception, but we want to carry out ever more complicated tasks and do so ever more quickly. There is a limit to how powerful we can make a classical computer, so we must look for other options. The most exciting option, which is in the early stages of development, is the so-called quantum computer. It is looking increasingly likely that quantum computers will one day be a reality, and so it is important that we have thought through how to use them. They could be a real game-changer for computationally very challenging fields such as that of quark physics. Because quantum computers work in a very different way to existing computers, we need to develop the tools to make use of them. This project will equip me to work in this area by setting up a prototype of a possible calculation in quark physics. My project will combine these two cutting-edge areas of physics, calculating the masses of tetraquarks, as well as working towards the use of quantum computers to carry out similar calculations in future. As well as pushing the boundaries of physics, the project will help the development of my own personal skills. I will be able to bring my knowledge of computational techniques to a new challenge in the tetraquark calculation, as well as learn from my Canadian hosts about a whole new area of research in the quantum computing work.

AHRC : Marcus Jack : AH/L503915 This project will examine the work of Scottish-Canadian experimental animator Norman McLaren through close analysis of the film production infrastructures and cultural programme of nation-building in Canada in the mid-twentieth century. Understanding McLaren as a complex figure caught between contradictory political, aesthetic and social conditions, this project will look at the strategies of complicity and subterfuge which enabled McLaren and his contemporaries to produce a remarkable body of film work against the odds. This research will draw upon new archival research undertaken in Toronto and Montreal to form a live, event-based output delivered in Canada. On return to the UK, this will be followed by a period of research in Scottish archives with a view to the later development of a journal article.

"ESRC : Louise Couceiro : ES/P000681/1" In recent years, there has been a surge in non-profit organisations providing free online resources aiming to inspire girls to 'get into STEM' in Canada. Resources include instructional videos, blog posts and 'role model' biographies of women working in STEM. To maximise the potential of these online educational resources, research is urgently needed to better understand the content, the objectives behind their development, and how they are being used. This project aims to do this by focusing on the work of three non-profit organisations: Science World, the Canadian Association for Girls in Science and STEMforGIRLS. Following analysis of the organisations' online resources, I will conduct interviews with developers and a group of girls who are engaging/have engaged with the resources. The findings will be invaluable for the development of future resources and the evaluation of similar initiatives.

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.