9,542 research outputs found

    Scaling up integrated photonic reservoirs towards low-power high-bandwidth computing

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    Full stack development toward a trapped ion logical qubit

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    Quantum error correction is a key step toward the construction of a large-scale quantum computer, by preventing small infidelities in quantum gates from accumulating over the course of an algorithm. Detecting and correcting errors is achieved by using multiple physical qubits to form a smaller number of robust logical qubits. The physical implementation of a logical qubit requires multiple qubits, on which high fidelity gates can be performed. The project aims to realize a logical qubit based on ions confined on a microfabricated surface trap. Each physical qubit will be a microwave dressed state qubit based on 171Yb+ ions. Gates are intended to be realized through RF and microwave radiation in combination with magnetic field gradients. The project vertically integrates software down to hardware compilation layers in order to deliver, in the near future, a fully functional small device demonstrator. This thesis presents novel results on multiple layers of a full stack quantum computer model. On the hardware level a robust quantum gate is studied and ion displacement over the X-junction geometry is demonstrated. The experimental organization is optimized through automation and compressed waveform data transmission. A new quantum assembly language purely dedicated to trapped ion quantum computers is introduced. The demonstrator is aimed at testing implementation of quantum error correction codes while preparing for larger scale iterations.Open Acces

    Industrial Robotics for Advanced Machining

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    This work presents a literature review of the current state of robotic machining with industrial machining robots, primarily those with 6-axis end effectors and serial link (anthropomorphic) construction. Various disadvantages of robotic machining in industry are presented, as well as the methods applied to mitigate them and discussions of their effects. From this review, the methods of dynamic modelling, stability prediction and configuration control are selected for application to the task of optimisation of a robotic machining cell for drilling operations. Matrix Structural Analysis (MSA) and methods developed by Klimchik et al. are used for compliance modelling, stability prediction methods developed by Altintas et al. and machining stability lobe prediction are then applied to a robotic drilling process, as explored by Mousavi et al. This optimisation method is applied using the measured and estimated properties of an ABB IRB 6640 robot and results are presented in comparison with previous experimentation with the physical robot, and analytical stability predictions from the same cutting parameters with Cutpro software. Results are discussed in the concluding chapters, as well as discontinued parts of the project and suggestions for future work

    Flexographic printed nanogranular LBZA derived ZnO gas sensors: Synthesis, printing and processing

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    Within this document, investigations of the processes towards the production of a flexographic printed ZnO gas sensor for breath H2 analysis are presented. Initially, a hexamethylenetetramine (HMTA) based, microwave assisted, synthesis method of layered basic zinc acetate (LBZA) nanomaterials was investigated. Using the synthesised LBZA, a dropcast nanogranular ZnO gas sensor was produced. The testing of the sensor showed high sensitivity towards hydrogen with response (Resistanceair/ Resistancegas) to 200 ppm H2 at 328 °C of 7.27. The sensor is highly competitive with non-catalyst surface decorated sensors and sensitive enough to measure current H2 guideline thresholds for carbohydrate malabsorption (Positive test threshold: 20 ppm H2, Predicted response: 1.34). Secondly, a novel LBZA synthesis method was developed, replacing the HMTA by NaOH. This resulted in a large yield improvement, from a [OH-] conversion of 4.08 at% to 71.2 at%. The effects of [OH-]/[Zn2+] ratio, microwave exposure and transport to nucleation rate ratio on purity, length, aspect ratio and polydispersity were investigated in detail. Using classical nucleation theory, analysis of the basal layer charge symmetries, and oriented attachment theory, a dipole-oriented attachment reaction mechanism is presented. The mechanism is the first theory in literature capable of describing all observed morphological features along length scales. The importance of transport to nucleation rate ratio as the defining property that controls purity and polydispersity is then shown. Using the NaOH derived LBZA, a flexographic printing ink was developed, and proof-of-concept sensors printed. Gas sensing results showed a high response to 200 ppm H2 at 300 °C of 60.2. Through IV measurements and SEM analysis this was shown to be a result of transfer of silver between the electrode and the sensing layer during the printing process. Finally, Investigations into the intense pulsed light treatment of LBZA were conducted. The results show that dehydration at 150 °C prior to exposure is a requirement for successful calcination, producing ZnO quantum dots (QDs) in the process. SEM measurements show mean radii of 1.77-2.02 nm. The QDs show size confinement effects with the exciton blue shifting by 0.105 eV, and exceptionally low defect emission in photoluminescence spectra, indicative of high crystalline quality, and high conductivity. Due to the high crystalline quality and amenity to printing, the IPL ZnO QDs have numerous potential uses ranging from sensing to opto-electronic devices

    Application of advanced surface patterning techniques to study cellular behavior

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    Surface manipulation for the fabrication of chemical or topographic micro- and nanopatterns, has been central to the evolution of in vitro biology research. A high variety of surface patterning methods have been implemented in a wide spectrum of applications, including fundamental cell biology studies, development of diagnostic tools, biosensors and drug delivery systems, as well as implant design. Surface engineering has increased our understanding of cell functions such as cell adhesion and cell-cell interaction mechanics, cell proliferation, cell spreading and migration. From a plethora of existing surface engineering techniques, we use standard microcontact printing methods followed by click chemistry to study the role of intercellular contacts in collective cancer cell migration. Cell dispersion from a confined area is fundamental in a number of biological processes, including cancer metastasis. To date, a quantitative understanding of the interplay of single cell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role of E- and N-Cadherin junctions, central components of intercellular contacts, is still controversial. Combining theoretical modeling with in vitro observations, we investigate the collective spreading behavior of colonies of human cancer cells (T24). The spreading of these colonies is driven by stochastic single-cell migration with frequent transient cell-cell contacts. We find that inhibition of E- and N-Cadherin junctions decreases colony spreading and average spreading velocities, without affecting the strength of correlations in spreading velocities of neighboring cells. Based on a biophysical simulation model for cell migration, we show that the behavioral changes upon disruption of these junctions can be explained by reduced repulsive excluded volume interactions between cells. This suggests that in cancer cell migration, cadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than cohesive interactions between cells, thereby promoting efficient cell spreading during collective migration. Despite the remarkable progress in surface engineering technology and its applications, a combination of pattern properties such as stability, precision, specificity, high-throughput outcome and spatiotemporal control is highly desirable but challenging to achieve. Here, we introduce a versatile and high-throughput covalent photo-immobilization technique, comprising a light-dose dependent patterning step and a subsequent functionalization of the pattern via click chemistry. This two-step process is feasible on arbitrary surfaces and allows for generation of sustainable patterns and gradients. The method is validated in different biological systems by patterning adhesive ligands on cell repellent surfaces, thereby constraining the growth and migration of cells to the designated areas. We then implement a sequential photopatterning approach by adding a second switchable pattering step, allowing for spatiotemporal control over two distinct surface patterns. As a proof of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis. Our results show that the spatiotemporal control provided by our “sequential photopatterning” system is essential for mimicking dynamic biological processes, and that our innovative approach has a great potential for further applications in cell science. In summary, this work introduces two novel and versatile paradigms of surface patterning for studying different aspects of cell behaviour in different cell types. The reliability of both setups is experimentally confirmed, providing new insight into the role of cell-cell contacts during collective cancer cell migration as well as the tip/stalk switch behaviour during angiogenesis

    Infrastructure for the Circular Economy: The Role of Policy in System Change

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    The concept of a Circular Economy has gained policy traction as a mainstream solution for preserving and renewing. This work sought to understand which policy instruments have been successful, might still be necessary, and are most likely in the future to deliver a high penetration Circular Economy for materials, wastes and associated energy. Waste related policy decisions in England over the past 20 years were reviewed, exploring the regulatory means that had achieved the current 44% diversion of municipal wastes from landfill. The hypothesis is that to achieve a far-reaching Circular Economy, at a greater scale, across different sectors and for a wider product range, suitable physical infrastructure (waste treatment assets) must be available to circulate those materials in the economy. Furthermore, the study set out to value financially and in terms of social and economic benefits that could be derived from a circular approach across the whole economy. We found the financial value to be significant at circa 1.5% of English GDP or  32bn and 72,000-175,000 jobs. It was demonstrated by calculation that DEFRA analysis (for England) underestimated the capacity gap for infrastructure by 11.3 million tonnes per annum in 2014. The policy findings were that the early implementation of blunt instruments such as a landfill tax and separate collection of recyclables did allow for diversion performance of approximately 45-50% recycling and composting, the remaining 50% of which was progressively treated by energy from waste rather than landfill. It is apparent that policies that drive system changes are effective in bringing about ecological transformations of how societies, economies, and governments operate at all levels. This ecological transformation is undoubtedly difficult to achieve since it will require consumers, manufacturers, regulators, policymakers, media, and business all to move differently and together, but nevertheless it is critical at a global scale.Open Acces

    A deep phenotyping approach to understand major depressive disorder and responses to antidepressant pharmacotherapy

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    Major depressive disorder (MDD) is a debilitating psychiatric disorder characterised by a complex underlying biology and poor response to pharmacological antidepressant strategies. Given the heterogeneity of MDD and the diverse range of available treatment options, there is an increasing desire to develop and implement precision medicine approaches to tailor existing treatment strategies to the biological system of the individual. In this thesis, high-resolution omics data (connectomics [fMRI], metabolomics [1H NMR] and immunomics [inflammatory cytokines]) collected from the Canadian Biomarker Integration Network in Depression (CAN-BIND) study has been integrated to facilitate the deep phenotyping of MDD. In addition, this approach has been used to predict the treatment response to two common antidepressant drugs, monotherapy with the selective serotonin reuptake inhibitor (SSRI) escitalopram (10-20 mg) or combination therapy with escitalopram and the dopaminergic antipsychotic aripiprazole (2-10 mg). This approach identified a multi-modal panel of sex-specific biomarkers of MDD and treatment response, highlighting a strong immunometabolic component in depressed males, but not females. Unsupervised clustering methods indicated the superiority of biological (neuroimaging) over symptom-based (clinical questionnaires) data for the stratification of patients into MDD subtypes with differential response to treatment. More importantly, a set of multi-modal, sex-specific biomarkers were identified that predicted treatment response with escitalopram monotherapy (84.7% accuracy) or aripiprazole augmentation (88.5% accuracy). In addition to highlighting potential new aspects of the biology of MDD (e.g. relevance of lipoprotein size and density for their relation to depression), this work is one of the first attempts to apply systems biology approaches to high-resolution biological data from a large clinical trial to predict later treatment outcome. With the validation of the findings presented in this thesis in independent cohorts, and with further development of omics technologies, leading to cheaper and high-throughput screening of the patient population, pre-dose biomarkers have the potential to achieve personalised treatment. Each year, escitalopram and aripiprazole are prescribed to an estimated 26 million and 7 million individuals respectively, and over one third of them do not respond. Thus, being able to predict response to antidepressant medication from baseline biomarkers has enormous clinical and socioeconomic benefits.Open Acces
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