7,977 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2023-2024

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    Tensor product approach to modelling epidemics on networks

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    To improve mathematical models of epidemics it is essential to move beyond the traditional assumption of homogeneous well--mixed population and involve more precise information on the network of contacts and transport links by which a stochastic process of the epidemics spreads. In general, the number of states of the network grows exponentially with its size, and a master equation description suffers from the curse of dimensionality. Almost all methods widely used in practice are versions of the stochastic simulation algorithm (SSA), which is notoriously known for its slow convergence. In this paper we numerically solve the chemical master equation for an SIR model on a general network using recently proposed tensor product algorithms. In numerical experiments we show that tensor product algorithms converge much faster than SSA and deliver more accurate results, which becomes particularly important for uncovering the probabilities of rare events, e.g. for number of infected people to exceed a (high) threshold

    Explaining the flaws in human random generation as local sampling with momentum

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    In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regarding random sequence generation, not predicted by previous accounts—which suggests that randomness is produced by inhibition of habitual behavior, striving for unpredictability. We verify these predictions in two experiments: people show the same deviations from randomness when randomly generating from non-uniform or recently-learned distributions. In addition, our data show a novel signature behavior, that people’s sequences have too few changes of trajectory, which argues against the specific local sampling algorithms that have been proposed in past work with other tasks. Using computational modeling, we show that local sampling where direction is maintained across trials best explains our data, which suggests it may be used in other tasks too. While local sampling has previously explained why people are unpredictable in standard cognitive tasks, here it also explains why human random sequences are not unpredictable enough

    Displacement and the Humanities: Manifestos from the Ancient to the Present

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    This is the final version. Available on open access from MDPI via the DOI in this recordThis is a reprint of articles from the Special Issue published online in the open access journal Humanities (ISSN 2076-0787) (available at: https://www.mdpi.com/journal/humanities/special_issues/Manifestos Ancient Present)This volume brings together the work of practitioners, communities, artists and other researchers from multiple disciplines. Seeking to provoke a discourse around displacement within and beyond the field of Humanities, it positions historical cases and debates, some reaching into the ancient past, within diverse geo-chronological contexts and current world urgencies. In adopting an innovative dialogic structure, between practitioners on the ground - from architects and urban planners to artists - and academics working across subject areas, the volume is a proposition to: remap priorities for current research agendas; open up disciplines, critically analysing their approaches; address the socio-political responsibilities that we have as scholars and practitioners; and provide an alternative site of discourse for contemporary concerns about displacement. Ultimately, this volume aims to provoke future work and collaborations - hence, manifestos - not only in the historical and literary fields, but wider research concerned with human mobility and the challenges confronting people who are out of place of rights, protection and belonging

    Facing the storm:Assessing global storm tide hazards in a changing climate

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    Coastal flooding is one of the most frequent natural hazards around the globe and can have devastating societal impacts. It is caused by extreme storm tides, which are composed of storm surges and tides, on top of mean sea levels. Due to socio-economic developments in the world’s coastal zones, the impacts of coastal floods have increased in recent decades. In addition, projected changes in the frequency and intensity of storms, as well as sea level rise due to climate change are expected to increase the coastal flood hazard. These trends show that it is crucial to further improve coastal flood hazard assessments to support coastal flood management. A lack of understanding of the influence of tropical cyclones (TCs) on storm tide level return periods (RPs) currently prevails. Available meteorological data does not adequately capture the structure of TCs, and the temporal length of this data is too short to accurately compute RPs because TCs are low-probability events. Existing large scale coastal flood hazard assessments assume an infinite flood duration and do not capture the physical hydrodynamic processes that drive coastal flooding. Furthermore, future changes in the frequency and intensity of TCs and extratropical cyclones (ETCs) are often neglected in coastal flood hazard assessments. As such, the goal of this thesis is to improve global storm tide modelling through the better representation of TC-related extremes and enable dynamic flood mapping in both current and future climates. The research in this thesis contributes to ongoing efforts in the coastal risk community to better understand coastal flood hazards and risks on a global scale. The COAST-RP dataset can help identify hotspot regions most prone to coastal flooding. Such information can then be used to determine where more detailed local-scale coastal flood hazard assessments are most needed. Combining data from COAST-RP with the HGRAPHER method allows us to move away from planar towards more advanced dynamic inundation methods. This will improve the accuracy of the coastal flood hazard maps. Lastly, the developed TC intensity Δ method that is applicable to different kinds of future climate TC datasets opens the door to studying the future intensity of TCs and corresponding storm surges by placing them in a future climate

    Graduate Catalog of Studies, 2023-2024

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    Classical and quantum algorithms for scaling problems

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    This thesis is concerned with scaling problems, which have a plethora of connections to different areas of mathematics, physics and computer science. Although many structural aspects of these problems are understood by now, we only know how to solve them efficiently in special cases.We give new algorithms for non-commutative scaling problems with complexity guarantees that match the prior state of the art. To this end, we extend the well-known (self-concordance based) interior-point method (IPM) framework to Riemannian manifolds, motivated by its success in the commutative setting. Moreover, the IPM framework does not obviously suffer from the same obstructions to efficiency as previous methods. It also yields the first high-precision algorithms for other natural geometric problems in non-positive curvature.For the (commutative) problems of matrix scaling and balancing, we show that quantum algorithms can outperform the (already very efficient) state-of-the-art classical algorithms. Their time complexity can be sublinear in the input size; in certain parameter regimes they are also optimal, whereas in others we show no quantum speedup over the classical methods is possible. Along the way, we provide improvements over the long-standing state of the art for searching for all marked elements in a list, and computing the sum of a list of numbers.We identify a new application in the context of tensor networks for quantum many-body physics. We define a computable canonical form for uniform projected entangled pair states (as the solution to a scaling problem), circumventing previously known undecidability results. We also show, by characterizing the invariant polynomials, that the canonical form is determined by evaluating the tensor network contractions on networks of bounded size

    Development of variable and robust brain wiring patterns in the fly visual system

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    Precise generation of synapse-specific neuronal connections are crucial for establishing a robust and functional brain. Neuronal wiring patterns emerge from proper spatiotemporal regulation of axon branching and synapse formation during development. Several neuropsychiatric and neurodevelopmental disorders exhibit defects in neuronal wiring owing to synapse loss and/or dys-regulated axon branching. Despite decades of research, how the two inter-dependent cellular processes: axon branching and synaptogenesis are coupled locally in the presynaptic arborizations is still unclear. In my doctoral work, I investigated the possible role of EGF receptor (EGFR) activity in coregulating axon branching and synapse formation in a spatiotemporally restricted fashion, locally in the medulla innervating Dorsal Cluster Neuron (M- DCN)/LC14 axon terminals. In this work I have explored how genetically encoded EGFR randomly recycles in the axon branch terminals, thus creating an asymmetric, non-deterministic distribution pattern. Asymmetric EGFR activity in the branches acts as a permissive signal for axon branch pruning. I observed that the M-DCN branches which stochastically becomes EGFR ‘+’ during development are synaptogenic, which means they can recruit synaptic machineries like Syd1 and Bruchpilot (Brp). My work showed that EGFR activity has a dual role in establishing proper M-DCN wiring; first in regulating primary branch consolidation possibly via actin regulation prior to synaptogenesis. Later in maintaining/protecting the levels of late Active Zone (AZ) protein Brp in the presynaptic branches by suppressing basal autophagy level during synaptogenesis. When M-DCNs lack optimal EGFR activity, the basal autophagy level increases resulting in loss of Brp marked synapses which is causal to increased exploratory branches and post-synaptic target loss. Lack of EGFR activity affects the M-DCN wiring pattern that makes adult flies more active and behave like obsessive compulsive in object fixation assay. In the second part of my doctoral work, I have asked how non-genetic factors like developmental temperature affects adult brain wiring. To test that, I increased or decreased rearing temperature which is known to inversely affect pupal developmental rate. We asked if all the noisy cellular processes of neuronal assembly: filopodial dynamics, axon branching, synapse formation and postsynaptic connections scale up or down accordingly. I observed that indeed all the cellular processes slow down at lower developmental temperature and vice versa, which changes the DCN wiring pattern accordingly. Interestingly, behavior of flies adapts to their developmental temperature, performing best at the temperature they have been raised at. This shows that optimal brain function is an adaptation of robust brain wiring patterns which are specified by noisy developmental processes. In conclusion, my doctoral work helps us better understand the developmental regulation of axon branching and synapse formation for establishing precise brain wiring pattern. We need all the cell intrinsic developmental processes to be highly regulated in space and time. It is infact a combinatorial effect of such stochastic processes and external factors that contribute to the final outcome, a functional and robust adult brain
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