Perception-Aware Optimisation Methodologies for Quantum Dot Based Displays and Lighting

Human colour vision acuity is limited. This presents opportunities to leverage these perceptual limits to achieve engineering optimisations for devices and systems that interact with the human vision system. This dissertation presents the results of few investigations we carried out into quantifying these limits and several optimisation methodologies that we devised. The first step in this process is to quantify the acuity of human colour vision. We obtained a large corpus of colour matching data from a mobile video game called Specimen. We examine what questions about human vision this dataset allows us to answer and explore global statistics about colour vision based on this data on 41,000 players from 175 countries. We show that we can use the information in this dataset to infer potential candidate functions for the spectral sensitivities of each person in the dataset. The human eye acts like a many to one function; quantifiably different spectra can look like the same colour. This is referred to as metamerism. From a device perspective, different spectra consume different amounts of energy to generate. We show that we can use these two properties to elicit the same colour sensation using less energy. In the colour samples we evaluated, we show that we can achieve up to 10 times less power consumption while achieving a colour match. Given that one cannot change the emission spectrum of a display after fabrication, we propose the use of a multi-primary colour display to achieve this. We present two indices for quantifying the metameric capacity of such a display and its ability to save energy. The emission spectrum of a quantum dot (QD) based device is very narrow. Previous work in the literature suggested that narrow bandwidth spectra can lead to observer metameric breakdown; different observers disagreeing on the perceived ‘colour’ of a spectrum. We show that this might not be the case, using modern colour science tools, and show how metameric breakdown in a display could be minimised by carefully choosing the primary emission wavelengths. The limited colour acuity of human vision implies that people cannot notice small differences in colour. This fact has been used to create approximate colour transformation algorithms that subtly change colours in images such that they consume less energy when displayed on an emissive pixel display without causing unacceptable visual artefacts. We conducted a user study to gather information about the effect of one such colour transform called Crayon. We present a method for effectively picking the optimal transform parameters for Crayon, based on the user study results. The method presented calculates these parameters based on the properties of the image being transformed such that the power saving can be maximised while minimising the loss of image quality. The user study results show that we can achieve up to 50% power saving with a majority of the study participants reporting a negligible degradation in image quality in the transformed images. We additionally investigate a hypothesis that was presented stating that images with large amounts of highly luminous pixels cause increased power consumption in OLED displays due to localised display heating. We show that this hypothesis is wrong. We also investigate if sub-pixel rendering in Pentile displays can be used to reduce display power consumption by intentionally turning off random sub-pixels. However, we present a negative result showing that even single-pixel artefacts are observable on the test platform and thus, this cannot be used to improve display power efficiency. The narrow-band optical emissions of QD based devices mixed with their ability to be fabricated through solution processing can be used to mix multiple QDs together to build devices that generate arbitrary spectral shapes. We show how to use this property in an numerical optimisation based design framework to create lighting devices with a high colour rendering index (CRI). We evaluate the effects of different cost functions and initialisation strategies, and show that, we are able to design devices with a CRI > 96 using only four different QD primaries. We use a charge-transport based simulator to asses the electric properties of the designed devices. We also showcase initial work done on a modular software interface and a material library we developed for this simulator.EPSRC DTP studentship award RG84040:EP/N509620/

Investigating the role of Sarco-Endoplasmic Reticulum Ca2+-ATPase(SERCA)in airway development

Background: Disorders of lung development cause death and disability in the young and old: novel insights into developmental regulators can aid therapeutic strategies. The Ca2+ATPase SERCA, already implicated in asthma and cystic fibrosis, appears to play a key role in lung development. SERCA inhibition with cyclopiazonic acid (CPA) in vitro, reduces both airway branching and peristalsis reversibly and dose dependently, whilst also halting myogenesis. It is unclear however, whether changes in branching are mediated via SERCA dependent contractility, or whether SERCA is a direct regulator of airway branching. Aims: (i) to further explore the CPA-induced embryonic lung phenotype by assaying gene expression and cell proliferation; and (ii) to determine effects of genetic perturbation of SERCA function in vivo on airway branching morphogenesis, in the absence of contractility (using a Drosophila model). Methods: Embryonic mouse (E11.5) lung explants were cultured +/- CPA at an air/fluid interface. Standard techniques were used to rear Drosophila and SERCA expression manipulated using conditional, heat-sensitive mutants and RNAi targeted to the trachea. Positively labelled, loss-of-function ‘flip-out’ RNAi and mutant clones were produced using heat-shock induced FLP-recombinase. Gene expression was assayed using real-time RT-PCR and SERCA function assessed using calcium dyes and genetic indicators. Embryonic and larval fly airways were imaged using fluorescent proteins and immunostaining, with live or fixed-sample confocal microscopy. Immunofluorescent staining was used to assess protein expression and cell proliferation. Results: SERCA inhibition with CPA significantly up or down regulated mRNA levels of key genes involved in lung branching morphogenesis, myogenesis and angiogenesis in vitro. CPA treatment also reduced cell proliferation dose-dependently in the lung epithelium and mesenchyme. In the fly embryo, neither conditional SERCA mutants nor targeted RNAi significantly affected tracheal morphology. However, residual SERCA mRNA and protein function was evident at this stage of development. Tracheal maturation, in the form of gas filling was significantly impaired though, in embryos expressing a conditional SERCA mutation. In larvae, development of the dorsal air sac primordium (ASP) was severely disrupted by targeted SERCA RNAi and this phenotype could be reproduced when sufficient numbers of loss-of–function clones were present. SERCA inhibition reduced the number of mitotic cells in the ASP and correspondingly, SERCA deficient clones comprised fewer cells than control counterparts: SERCA regulation of airway cell proliferation was therefore evident across species. Fewer SERCA deficient cells reached the tip of the ASP during morphogenesis compared to controls, whereas a greater proportion remained in the stalk, findings that indicate a cell-autonomous defect in cell migration. Changes in morphology were independent of changes in expression of the key ASP signalling pathways MAP kinase and Notch. Expression of the ASP tip-cell marker escargot was expanded in SERCA deficient larvae, with a number of positive cells being abnormally present in the stalk. This finding could be explained by a failure of these cells to migrate to the tip, alternatively by changes in cell fate. Given key roles of tip cells in morphogenetic signalling, escargot may play a role in SERCA inhibition-induced dysmorphogenesis. Conclusions: SERCA has an essential, conserved role in airway branching morphogenesis across species: this role appears independent of contractility. SERCA regulates cell migration and proliferation processes in the airway, findings that may have wider relevance, e.g. in proliferative disease, metastasis and tissue regeneration. Given evidence in plants and fungi of Ca2+ cycling regulating budding, findings here may indicate a role for SERCA as a generic regulator of iterative branching across biology, with clear implications for further research

Visual Processing and Latent Representations in Biological and Artificial Neural Networks

The human visual system performs the impressive task of converting light arriving at the retina into a useful representation that allows us to make sense of the visual environment. We can navigate easily in the three-dimensional world and recognize objects and their properties, even if they appear from different angles and under different lighting conditions. Artificial systems can also perform well on a variety of complex visual tasks. While they may not be as robust and versatile as their biological counterpart, they have surprising capabilities that are rapidly improving. Studying the two types of systems can help us understand what computations enable the transformation of low-level sensory data into an abstract representation. To this end, this dissertation follows three different pathways. First, we analyze aspects of human perception. The focus is on the perception in the peripheral visual field and the relation to texture perception. Our work builds on a texture model that is based on the features of a deep neural network. We start by expanding the model to the temporal domain to capture dynamic textures such as flames or water. Next, we use psychophysical methods to investigate quantitatively whether humans can distinguish natural textures from samples that were generated by a texture model. Finally, we study images that cover the entire visual field and test whether matching the local summary statistics can produce metameric images independent of the image content. Second, we compare the visual perception of humans and machines. We conduct three case studies that focus on the capabilities of artificial neural networks and the potential occurrence of biological phenomena in machine vision. We find that comparative studies are not always straightforward and propose a checklist on how to improve the robustness of the conclusions that we draw from such studies. Third, we address a fundamental discrepancy between human and machine vision. One major strength of biological vision is its robustness to changes in the appearance of image content. For example, for unusual scenarios, such as a cow on a beach, the recognition performance of humans remains high. This ability is lacking in many artificial systems. We discuss on a conceptual level how to robustly disentangle attributes that are correlated during training, and test this on a number of datasets