7,585 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Studies on genetic and epigenetic regulation of gene expression dynamics

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    The information required to build an organism is contained in its genome and the first biochemical process that activates the genetic information stored in DNA is transcription. Cell type specific gene expression shapes cellular functional diversity and dysregulation of transcription is a central tenet of human disease. Therefore, understanding transcriptional regulation is central to understanding biology in health and disease. Transcription is a dynamic process, occurring in discrete bursts of activity that can be characterized by two kinetic parameters; burst frequency describing how often genes burst and burst size describing how many transcripts are generated in each burst. Genes are under strict regulatory control by distinct sequences in the genome as well as epigenetic modifications. To properly study how genetic and epigenetic factors affect transcription, it needs to be treated as the dynamic cellular process it is. In this thesis, I present the development of methods that allow identification of newly induced gene expression over short timescales, as well as inference of kinetic parameters describing how frequently genes burst and how many transcripts each burst give rise to. The work is presented through four papers: In paper I, I describe the development of a novel method for profiling newly transcribed RNA molecules. We use this method to show that therapeutic compounds affecting different epigenetic enzymes elicit distinct, compound specific responses mediated by different sets of transcription factors already after one hour of treatment that can only be detected when measuring newly transcribed RNA. The goal of paper II is to determine how genetic variation shapes transcriptional bursting. To this end, we infer transcriptome-wide burst kinetics parameters from genetically distinct donors and find variation that selectively affects burst sizes and frequencies. Paper III describes a method for inferring transcriptional kinetics transcriptome-wide using single-cell RNA-sequencing. We use this method to describe how the regulation of transcriptional bursting is encoded in the genome. Our findings show that gene specific burst sizes are dependent on core promoter architecture and that enhancers affect burst frequencies. Furthermore, cell type specific differential gene expression is regulated by cell type specific burst frequencies. Lastly, Paper IV shows how transcription shapes cell types. We collect data on cellular morphologies, electrophysiological characteristics, and measure gene expression in the same neurons collected from the mouse motor cortex. Our findings show that cells belonging to the same, distinct transcriptomic families have distinct and non-overlapping morpho-electric characteristics. Within families, there is continuous and correlated variation in all modalities, challenging the notion of cell types as discrete entities

    Optimising water quality outcomes for complex water resource systems and water grids

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    As the world progresses, water resources are likely to be subjected to much greater pressures than in the past. Even though the principal water problem revolves around inadequate and uncertain water supplies, water quality management plays an equally important role. Availability of good quality water is paramount to sustainability of human population as well as the environment. Achieving water quality and quantity objectives can be conflicting and becomes more complicated with challenges like, climate change, growing populations and changed land uses. Managing adequate water quality in a reservoir gets complicated by multiple inflows with different water quality levels often resulting in poor water quality. Hence, it is fundamental to approach this issue in a more systematic, comprehensive, and coordinated fashion. Most previous studies related to water resources management focused on water quantity and considered water quality separately. However, this research study focused on considering water quantity and quality objectives simultaneously in a single model to explore and understand the relationship between them in a reservoir system. A case study area was identified in Western Victoria, Australia with water quantity and quality challenges. Taylors Lake of Grampians System in Victoria, Australia receives water from multiple sources of differing quality and quantity and has the abovesaid problems. A combined simulation and optimisation approach was adopted to carry out the analysis. A multi-objective optimisation approach was applied to achieve optimal water availability and quality in the storage. The multi-objective optimisation model included three objective functions which were: water volume and two water quality parameters: salinity and turbidity. Results showed competing nature of water quantity and quality objectives and established the trade-offs. It further showed that it was possible to generate a range of optimal solutions to effectively manage those trade-offs. The trade-off analysis explored and informed that selective harvesting of inflows is effective to improve water quality in storage. However, with strict water quality restriction there is a considerable loss in water volume. The robustness of the optimisation approach used in this study was confirmed through sensitivity and uncertainty analysis. The research work also incorporated various spatio-temporal scenario analyses to systematically articulate long-term and short-term operational planning strategies. Operational decisions around possible harvesting regimes while achieving optimal water quantity and quality and meeting all water demands were established. The climate change analysis revealed that optimal management of water quantity and quality in storage became extremely challenging under future climate projections. The high reduction in storage volume in the future will lead to several challenges such as water supply shortfall and inability to undertake selective harvesting due to reduced water quality levels. In this context, selective harvesting of inflows based on water quality will no longer be an option to manage water quantity and quality optimally in storage. Some significant conclusions of this research work included the establishment of trade-offs between water quality and quantity objectives particular to this configuration of water supply system. The work demonstrated that selective harvesting of inflows will improve the stored water quality, and this finding along with the approach used is a significant contribution to decision makers working within the water sector. The simulation-optimisation approach is very effective in providing a range of optimal solutions, which can be used to make more informed decisions around achieving optimal water quality and quantity in storage. It was further demonstrated that there are range of planning periods, both long-term (>10 years) and short-term (<1 year), all of which offer distinct advantages and provides useful insights, making this an additional key contribution of the work. Importantly, climate change was also considered where it was found that diminishing water resources, particularly to this geographic location, makes it increasingly difficult to optimise both quality and quantity in storage providing further useful insights from this work.Doctor of Philosoph

    Social plasticity and limited resilience of coral-dwelling gobies (genus Gobiodon) to climate change: outlook for coral-fish mutualisms in a changing world

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    Climate change is rapidly altering ecosystems on a global scale, and coral reefs are particularly vulnerable to climate-induced disturbances. Coral reefs depend on mutualisms with their foundation species, i.e. corals, and yet most of the literature has focused on their mutualisms with only one type of symbiont (algae). Little is known about how coral-fish mutualisms respond to climatic disturbances, and yet cyclones and heatwaves are increasingly devastating coral reefs. We urgently need to assess how coral-fish mutualisms respond to disturbances as changes in mutualisms have the potential for causing ecosystem-level changes. Yet fish in coral-fish mutualisms have often been overlooked in studies regarding environmental disturbances. There are multiple aspects of the life history, behaviour, and movement of fish that may impact their mutualisms with corals. Here, I investigated (1) whether both symbionts in coral-fish mutualisms respond similarly to climatic disturbances, and (2) what mechanisms from the fish perspective are likely responsible for how coral-fish mutualisms respond to climatic disturbances. I used a model coral-fish mutualism between coral hosts from the genus Acropora and coral-dwelling gobies from the genus Gobiodon in which both organisms provide important benefits for the resilience of each partner. I implemented a comparative approach by investigating multiple goby and coral species encountered in study locations to provide genus-wide understandings of how their coral-goby mutualisms are impacted by climatic disturbances. Particularly important is that gobies can live in social groups and living in groups can improve coral maintenance. Accordingly, first I provided a comprehensive review on how climate change is impacting the sociality of coral reef fish as the sociality of these taxa have only recently been investigated. Studies have shown that climate change affected the habitat and physiology of fishes, and each of these effects impacted their sociality. The review highlighted key changes to the sociality of these fish depending on how corals respond to disturbances, like reduction in coral size, shifts in coral communities, and health of corals. Secondly, I set the scene by monitoring coral-goby mutualisms throughout four extreme disturbances in the northern Great Barrier Reef (GBR): two cyclones and two heatwaves that caused mass bleaching events. In the aftermath and after a few years of recovery, there were more coral species, but corals were almost three times smaller. For gobies though, there were two times fewer coral species, there were fewer gobies, and most corals became absent of gobies when previously most were occupied. Alarmingly, this study highlighted that gobies declined far more than corals and were far slower to recover than their hosts. Finally, I used a combination of observational and manipulative studies to investigate the potential for coral gobies to exhibit plasticity in their host use, sociality, and movement in relation to disturbances. Following the same four extreme disturbances, I found that gobies shifted hosts to the newly abundant coral species. Although exhibiting host plasticity may be an advantage in the short-term, using alternative coral hosts may reduce the fitness of gobies, i.e. their growth rates. I then investigated whether gobies shifted their social tendencies to live in groups or in pairs following these four extreme disturbances in the northern GBR and following a single extreme disturbance in the southern GBR. Gobies no longer lived in groups, rarely in pairs, and primarily lived as solitary individuals after the four disturbances, whereas there was relatively little change in their social tendencies after the single disturbance. This study suggests that if consecutive disturbances become the norm, gobies may continue to decline if they primarily stay solitary as they need to live in pairs to breed. I then completed another study to investigate how predation risk, coral size and health, and number of group members affected the movement of gobies. I translocated gobies in situ into corals with varying sizes, number of individuals, and health. I replicated the study in a relatively undisturbed environment in Papua New Guinea, and in the highly disturbed environment following the four extreme disturbances in northern GBR. Regardless of the disturbance state, gobies preferred to face high costs of predation and did alter their movement based on coral size, health, or number of group members, even when predation risk was higher in disturbed environments. This suggests that gobies do not alter their movement plasticity based on environmental disturbances even though predation risk is heightened. This means that gobies exhibited host and social plasticity, but they did not exhibit movement plasticity to disturbances. I found that each mechanism of plasticity was likely responsible for a reduced recovery potential of gobies compared to their coral hosts. By combining the findings from each chapter of the thesis, I suggest that coral-fish mutualisms are highly vulnerable to climate change as fish experience barriers to recovery via host, social, and movement plasticity. Future conservation strategies should address declines in fish in order to maintain coral-fish mutualisms important for coral health

    A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling

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    The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    Information limits of imaging through highly diffusive materials using spatiotemporal measurements of diffuse photons

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    Conventional medical imaging instruments are bulky, expensive, and use harmful ionising radiation. Combining ultrafast single-photon detectors and pulsed laser sources at optical wavelengths has the potential to offer inexpensive, safe, and potentially wearable alternatives. However, photons at optical wavelengths are strongly scattered by biological tissue, which corrupts direct imaging information about regions of absorbing interactions below the tissue surface. The work in this thesis studies the potential of measuring indirect imaging information by resolving diffuse photon measurements in space and time. The practical limits of imaging through highly diffusive material, e.g., biological tissue, is explored and validated with experimental measurements. The ill-posed problem of using the information in diffuse photon measurements to reconstruct images at the limits of the highly diffusive regime is tackled using probabilistic machine learning, demonstrating the potential of migrating diffuse optical imaging techniques beyond the currently accepted limits and underlining the importance of uncertainty quantification in reconstructions. The thesis is concluded with a challenging biomedical optics experiment to transmit photons diametrically through an adult human head. This problem was tackled experimentally and numerically using an anatomically accurate Monte Carlo simulation which uncovered key practical considerations when detecting photons at the extreme limits of the highly diffusive regime. Although the experimental measurements were inconclusive, comparisons with the numerical results were promising. More in-depth numerical simulations indicated that light could be guided in regions of low scattering and absorption to reach deep areas inside the head, and photons can, in principle, be transmitted through the entire diameter of the head. The collective evidence presented in this thesis reveals the potential of diffuse optical imaging to extend beyond the currently accepted limits to non-invasively image deep regions of the human body and brain using optical wavelengths

    Modeling and data analysis of biochemical oscillators using Chemical Master Equation and AI: applications to the NF-kB activity in patient derived xenografts

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    There are two stages from DNA sequence of a gene to protein: transcription, i.e. the process of making a strand of RNA molecule, and translation, that is the process by which a protein is synthesized from the information contained in a molecule of RNA. In the process of transcription, proteins called “transcription factors” play a central role because they bind to a DNA sequence and help the transcription initiation complex. In this work of thesis, we are particularly interested in modeling the nuclear factor-kappa B (NF-kB) activity which is ubiquitous within cells and its dysfunction leads to chronic diseases, cancers, neurodegenerative diseases and much other. However, we do not start immediately modeling its behavior. In this stochastic context, firstly we aim to deepen into algorithms to solve the Chemical Master Equation (CME) giving an our alternative algorithm called “hybrid” because it combines the Gillespie’s Stochastic Simulation Algorithm (SSA) with the tauleaping algorithm with the aim to improve the algorithm’s speed; secondly we analyse the stochastic simulation results of three basics genetic circuits (the simplest model of gene expression, the autorepressor and the toggle switch); third, we faced the problem of parameters estimation of these simple models using artificial neural networks; finally, aware of what we have learned after all such steps, we provide a very little NF-kB model using the CME. The relevant results are the following: the hybrid algorithm applied to the first genetic model is faster than the SSA in configurations where the number of molecules produced tends to be high; periodicity arises from what we defined as unpredictable (being stochastic processes); neural networks learn to predict the model parameters given the autocorrelation as input but the choice of chemical specie makes the difference; finally, our little NF-kB model shows an oscillating behavior that is similar to the one found by experiments

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

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