Cosmological and Astrophysical Tests of Constructive Gravity

In the last decade, the constructive gravity programme was developed to expand Einstein's derivation of general relativity to matter bearing a non-Lorentzian geometric structure. This thesis studies the phenomenology of general linear electrodynamics (GLED), the maximal linear generalisation of Maxwellian electrodynamics, and its corresponding gravitational dynamics. We derive quantum interaction rules for GLED Dirac quantum mechanics to determine the decay width of the Cherenkov decay of superluminar particles in vacuum. With this, we obtain two non- Lorentzian parameters of the GLED geometry. We employ a weak Field limit of GLED gravity in astrophysics, study the stability of symmetric gravitationally bound matter distributions and the internal structure of stars. Using galaxy rotation curves, we are able to estimate ranges for both additional gravitational constants arising from weak field GLED gravity. Finally, we derive and solve the linear growth equation which governs the structure formation in the early Universe, and calculate the bispectrum in tree-level perturbation theory

Greenview : the gorilla in the library smart sensing and behaviour change

This paper provides a description and analysis of the Greenview project, an experiment in smart sensing leading to energy consumption behaviour change in building users. Greenview was an innovative app built on the back of the successful DUALL project (funded by JISC). Where DUALL created a simple web-based information-feedback tool that could report electrical consumption in specific university buildings back to users via a simple dashboard using Yahoo widgets; Greenview refined the ICT tool further into a sophisticated smart phone application which could connect staff and students in De Montfort University (DMU) to monitor the relative energy consumptions of their buildings. The developed iPhone ‘app’ visualised comparative energy use on the DMU campus through a narrative of improving or declining habitats for endangered species, represented by animated cartoon characters living as virtual mascots in each university building. Based on the emotive nature of the ‘Tamagochi’ concept, the app tested an engaging way to encourage care for the environment. When consumption levels exceeded those on the same day of the previous year, the visible well being of species would change. The app also provided real-time data through meter readings provided on a half-hourly basis, allowing the inclusion of graphical data options, appealing both to emotional identification with the building mascot and to the range of preferences individuals have for viewing and interpreting data.Funded by the Horizon 2020 Framework Programme of the European Union.peer-reviewe

The Gorilla in the Library: lessons in using ICT to engage building users in energy reduction

This paper is concerned with the role of the digital economy as an enabler of behaviour change in the built environment. The Greenview research project at De Montfort University (DMU), funded by JISC’s Greening ICT fund , has undertaken innovative work to explore novel and interesting ways to engage building users in energy reduction. Findings are presented around both the methodological challenges of capturing and presenting live electrical data for iPhone applications and the wider opportunities and barriers to ICT enabled behaviour change. From a technical perspective Greenview has shown the need to conduct detailed and thorough technical work to ensure the visualisations correlate to actual building performance and from the behaviour change perspective both Greenview and its predecessor (DUALL ) have explored moving beyond quantitative approaches to presenting information on energy and sustainability that is fun, creative and [hopefully] engaging. Finally, it is clear that without senior commitment and sincere staff engagement and collaboration mere information provision in the form of dashboards are impotent

Tensor networks for quantum machine learning

Once developed for quantum theory, tensor networks have been established as a successful machine learning paradigm. Now, they have been ported back to the quantum realm in the emerging field of quantum machine learning to assess problems that classical computers are unable to solve efficiently. Their nature at the interface between physics and machine learning makes tensor networks easily deployable on quantum computers. In this review article, we shed light on one of the major architectures considered to be predestined for variational quantum machine learning. In particular, we discuss how layouts like MPS, PEPS, TTNs and MERA can be mapped to a quantum computer, how they can be used for machine learning and data encoding and which implementation techniques improve their performance

Visual histological grading system for the evaluation of in vitro-generated neocartilage

Here we present the development of a visual evaluation system for routine assessment of in vitro-engineered cartilaginous tissue. Neocartilage was produced by culturing human articular chondrocytes in pellet culture systems or in a scaffold-free bioreactor system. All engineered tissues were embedded in paraffin and were sectioned and stained with Safranin O-fast green. The evaluation of each sample was broken into 3 categories (uniformity and intensity of Safranin O stain, distance between cells/amount of matrix produced, and cell morphology), and each category had 4 components with a score ranging from 0 to 3. Three observers evaluated each sample, and the new system was independently tested against an objective computer-based histomorphometry system. Pellets were also assessed biochemically for glycosaminoglycan (GAG) content. Pellet histology scores correlated significantly with GAG contents and were in agreement with the computer-based histomorphometry system. This system allows a valid and rapid assessment of in vitro-generated cartilaginous tissue that has a relevant association with objective parameters indicative of cartilage quality

Potential analysis of a Quantum RL controller in the context of autonomous driving

The potential of quantum enhanced Q-learning with a focus on its applicability to a lane change manoeuvre is investigated. In this context we solve multiple simple reinforcement learning environments using variational quantum circuits. The achieved results were similar to or even better than those of a simple constrained classical agent. We could observe promising behaviour on the more complex lane change manoeuvre task, which has an environment with an observation vector size twice larger than commonly used ones. For the Frozen Lake environment we found indications of possible quantum advantages in convergence rate

PAR2 absence completely rescues inflammation and ichthyosis caused by altered CAP1/Prss8 expression in mouse skin

Altered serine protease activity is associated with skin disorders in humans and in mice. The serine protease channel-activating protease-1 (CAP1; also termed protease serine S1 family member 8 (Prss8)) is important for epidermal homeostasis and is thus indispensable for postnatal survival in mice, but its roles and effectors in skin pathology are poorly defined. In this paper, we report that transgenic expression in mouse skin of either CAP1/Prss8 (K14-CAP1/Prss8) or protease-activated receptor-2 (PAR2; Grhl3PAR2/+), one candidate downstream target, causes epidermal hyperplasia, ichthyosis and itching. K14-CAP1/Prss8 ectopic expression impairs epidermal barrier function and causes skin inflammation characterized by an increase in thymic stromal lymphopoietin levels and immune cell infiltrations. Strikingly, both gross and functional K14-CAP1/Prss8-induced phenotypes are completely negated when superimposed on a PAR2-null background, establishing PAR2 as a pivotal mediator of pathogenesis. Our data provide genetic evidence for PAR2 as a downstream effector of CAP1/Prss8 in a signalling cascade that may provide novel therapeutic targets for ichthyoses, pruritus and inflammatory skin diseases

The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

No transfer of calibration between action and perception in learning a golf putting task

We assessed calibration of perception and action in the context of a golf putting task. Previous research has shown that right-handed novice golfers make rightward errors both in the perception of the perfect aiming line from the ball to the hole and in the putting action. Right-handed experts, however, produce accurate putting actions but tend to make leftward errors in perception. In two experiments, we examined whether these skill-related differences in directional error reflect transfer of calibration from action to perception. In the main experiment, three groups of right-handed novice participants followed a pretest, practice, posttest, retention test design. During the tests, directional error for the putting action and the perception of the perfect aiming line were determined. During practice, participants were provided only with verbal outcome feedback about directional error; one group trained perception and the second trained action, whereas the third group did not practice. Practice led to a relatively permanent annihilation of directional error, but these improvements in accuracy were specific to the trained task. Hence, no transfer of calibration occurred between perception and action. The findings are discussed within the two-visual-system model for perception and action, and implications for perceptual learning in action are raised