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Optical spin, optical helicity, and light-matter interactions
Get PDFOver the past three decades, a tremendous amount of research has been dedicated to the theoretical analysis and experimental realization of structured forms of light—optical fields with complex structures in their phase, polarization, or other degrees of freedom. Beyond their inherent optical properties, which are often interesting and unexpected compared to simpler, unstructured fields, structured light fields also give rise to novel effects when interacting with matter. In this Thesis, I examine some fundamental and practical aspects of the angular momentum and chirality of light, two key topics in modern structured light research. My focus is on the optical spin angular momentum and the optical helicity in monochromatic fields. Regarding the former, I examine the local spin in non-interfering superpositions of plane waves. Amongst other intriguing features, the electric and magnetic spins—which are distinct physical contributions to the total optical spin—show striking differences in these fields, and I discuss the implications of these spin structures on light-matter interactions. In connection with the optical helicity, I develop a theoretical model for the transfer of helicity from a monochromatic optical field to a single atom, shedding greater light on the fundamental role of helicity in light-matter interactions. I also present two derivations—one of the Faraday effect in a gas, the other of the helicity-dependent chiroptical force—within the framework of molecular quantum electrodynamics, opening the door to future explorations of structured light-matter interactions from the fundamental photonic perspective
Hardware-software co-design of FPGA-based neural network accelerators for edge inference
Get PDFThe demand for efficient Deep Neural Network (DNN) accelerators has increased due to the growing popularity of DNNs in various applications, including image classification, speech recognition, and natural language processing. However, designing flexible, reconfigurable, and efficient DNN accelerators is challenging due to the computational intensity and memory requirements of DNN models. As such, Field-Programmable Gate Arrays (FPGAs) have become a popular choice for implementing DNN accelerators due to their ability to be reconfigured to suit the requirements of the workload and their energy efficiency compared to traditional general-purpose CPUs and GPUs. However, designing efficient accelerators for resource-constrained edge devices with FPGAs is challenging. As such, this thesis focuses on solving the difficulties of designing new efficient DNN accelerators for resource-constrained edge FPGAs.
First, this thesis presents the SECDA methodology (SystemC Enabled Co design of DNN Accelerator), which enables hardware-software co-design of resource-constrained hardware accelerators for DNN inference on edge FPGAs. To expand upon the SECDA methodology, SECDA-TFLite and SECDA-LLM were developed to quickly adopt the design methodology within TensorFlow Lite and llama.cpp, two popular frameworks for DNN inference on edge devices.
Second, this thesis presents the design of the MM2IM architecture for accelerating Transposed Convolution (TCONV) operations within Generative Adversarial Networks (GANs) for resource-constrained edge devices. This architecture was developed utilising the SECDA methodology and the SECDA-TFLite toolkit. The MM2IM accelerator achieved an average speedup of 84× across 261 TFLite TCONV problem configurations compared to an ARM Neon-optimised CPU baseline.
Finally, this thesis presents AXI4MLIR, an extension to the MLIR compiler framework that enables efficient host-accelerator communication by automatically generating host driver code that is aware of the accelerator architecture and capable of performing efficient data transfers. Our experiments using specialised FPGA accelerators demonstrate AXI4MLIR’s versatility across different types of accelerators and problems, showcasing significant CPU cache reference reductions (up to 56%) and up to a 1.65× speedup compared to manually optimised driver code implementations
Group psychological interventions for individuals with eating disorders and their carers
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The impact of inflammatory context on the metabolic profile of T follicular helper cells
Get PDFT follicular helper (Tfh) cells are a subset of CD4⁺ T cells that are key in driving the Germinal Centre response, assisting B cells to produce high-affinity antibodies during the adaptive response. Tfh cell differentiation/function is metabolically regulated; however, characterisation of Tfh cell metabolism during a type 2 helminth infection (e.g. H. polygyrus ), and its relationship to Tfh cells derived from type 1 inflammation, remains poorly understood. To date, Tfh cell metabolism in comparison to other T effector cells (Th1/Th2) remains understudied. This thesis aims to define the key metabolic pathways utilised by murine Tfh cells compared to other CD4⁺ T cell subsets, in Th1 (IAV Infection) and Th2-mediated inflammation (H. polygyrus ). Both infections induce strong Tfh and T effector cell responses. Using metabolic profiling techniques (METFLOW, PHOSFLOW, lipid assays, bulk RNA sequencing), I demonstrated that Tfh cells are metabolically active, capable of lipid accumulation and show lipid-dependent gene expression profiles, albeit less so than Th2 cells in H. polygyrus infection. Thus, Tfh cells favoured increased glycolytic gene expression over Th2 cells; however, Th2 cells have increased expression of genes associated with lipid and cholesterol pathways. To assess variation in Tfh metabolism across inflammatory contexts, I used bulk RNAseq to compare metabolic gene expression in Tfh cells from both Th1- and Th2-driven infections. My analysis revealed that Tfh2 cells (type 2) consistently display increased gene expression for lipid metabolism compared to Tfh1 (type 1), regardless of anatomical location or infection. Further to this, I found that in human in vitro-derived Tfh cells, acute inhibition of SCD-1, a key enzyme in lipid biosynthesis, facilitated a reduction in CXCR5 (and possibly CCR7) expression on the surface of Tfh cells. This indicates that manipulation of lipid metabolism directly influences Tfh cell biology and could possibly prevent their migratory capacity. Overall, my data shows that Tfh cell metabolism does not exhibit a fixed phenotype and that it can alter depending on the immune environment. Furthermore, this increases understanding of key metabolic nodes of Tfh cells, like lipid biosynthesis and the role of SCD-1, suggesting that metabolic manipulation may be a viable strategy for the selective modulation of Tfh cells. This is crucial as, to date, no therapies specifically target Tfh cells; however, with further research, we may be able to target Tfh immunometabolism effectively to enhance vaccine efficacy or, in cases of aberrant Tfh cell responses, modulate these responses in favour of the patient's needs
Propagation of type III solar radio burst exciters and plasma density fluctuations
Get PDFSolar flare accelerated electron beams travel along open magnetic field lines in the solar corona and interplanetary (IP) medium and can interact with the local plasma to produce Langmuir waves and subsequently trigger intense radio emissions known as type III solar radio bursts. These bursts serve as a crucial diagnostic tool for advancing our understanding of electron transport in the inner heliosphere and as potential early indicators of hazardous space weather events. Despite the rapid quasilinear relaxation of electron beams towards a plateau in velocity space, observations suggest significant propagation distances, a challenge referred to as Sturrock’s dilemma. Here, we develop a novel electron transport model by introducing a self-consistently evolving quasilinear time/distance. The resulting nonlinear advection-diffusion equation predicts super-diffusive, ballistic-like expansion of the beam; analytical predictions are consistent with the results of numerical simulations using kinetic equations and can account for some observed characteristics of type III solar radio bursts. A complementary analysis using spacecraft data from SolO/RPW, PSP/RFS, and STEREO A/WAVES enables us to derive the speeds and accelerations of type III exciters from isolated bursts associated with flares of well-characterized angular positions. For the first time, this analysis allows the correction of velocities and accelerations for the angular separation between the spacecraft and the apparent source. The observed rate of change of velocity with heliocentric distance is then compared to theoretical predictions for a beam-plasma structure propagating through a background plasma of decreasing density, with energy loss attributed to the negative shift in velocity space of Langmuir waves and their subsequent absorption by the Maxwellian component of the plasma, shedding light on the mechanisms driving energy dissipation in beam-plasma structures. Additionally, we investigate the impact of compressive waves in the turbulent solar atmosphere on radio wave propagation through the solar corona and solar wind. Using a new anisotropic density fluctuation model from the kinetic scattering theory for type III radio bursts, we infer the plasma velocities needed to explain observed spacecraft signal frequency broadening. At heliocentric distances beyond 10 R⊙, the velocities align with solar wind flows, while closer to the Sun (≲ 10 R⊙), the broadening implies additional radial and transverse speeds consistent, respectively, with sound or proton thermal speeds and non-thermal motions measured via coronal Doppler-line broadening, interpreted as Alfvénic fluctuations. The energy deposition rates due to ion-sound wave damping peak at a heliocentric distance of ∼(1 − 3) R⊙ and are comparable to the rates available from a turbulent cascade of Alfvénic waves at large scales, suggesting a coherent picture of energy transfer, via the cascade or/and parametric decay of Alfvén waves to the small scales where heating takes place
New York’s 79th Highlanders: the evolution of Scottish martial and civic identity in Antebellum and Civil War era America
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Characterisation of therapeutic approaches for Alzheimer's dementia in the APP mouse model - neurotrophic factors and sensory stimulation
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Investigating the role of gap junction protein and novel genes in renal function
Get PDFThis thesis investigates the roles of genes with enriched expression in particular cells or regions of the Drosophila melanogaster Malpighian tubules in renal function and cellular homeostasis. Using reverse genetic, transcriptomic and metabolomic techniques, this study characterises the physiological role of Innexin 2, Innexin 7, the octopamine receptor Octα2R and the novel gene
CG6602. These findings highlight the power of the Malpighian tubules as a model system for studying gene function in relation to osmoregulation, ion transport, and responses to stress.
Initial studies characterised the gap junction proteins Innexin 2 and Innexin 7 to the principal cells of the tubules but found no strong impact of fluid secretion after RNAi knockdown. By contrast, Octα2R analysis revealed a specific role in secretion: reductions of Octα2R in stellate cells decreased the rate of secretion, and tubule secretion was found to be especially sensitive to octopamine compared with other biogenic amines.
Further studies focused on CG6602, which is tubule-specific and might contribute to stress response pathways. Collectively, the knockdown of CG6602 resulted in altered expression of stress response genes, which implies possible involvement of CG6602 in pathways related to the maintenance of homeostasis of the cell. Metabolomic profiling confirmed this view, detecting changes in metabolites including those associated with oxidative stress defence, suggesting that CG6602's regulatory role in managing metabolic and environmental stress in the tubule cells.
This study highlights the power of performing renal physiology studies in the fruit fly and begin to shed light on the molecular players responsible for maintaining tubule homeostasis. Due to the limitations of the analytical methods applied in this study, a more detailed exploration of the metabolomic data was not possible but the study provides a framework to connect state-of-the-art metabolomics with multi-omics approaches in future. It also adds to knowledge about the roles of gap junction proteins and the unique gene CG6602 in the renal system, and the genetic and metabolic networks involved in supporting renal function and stress responses
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