3,447 research outputs found

    Dynamic Agent Compression

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    We introduce a new method for processing agents in agent-based models that significantly improves the efficiency of certain models. Dynamic Agent Compression allows agents to shift in and out of a compressed state based on their changing levels of heterogeneity. Sets of homogeneous agents are stored in compact bins, making the model more efficient in its use of memory and computational cycles. Modelers can use this increased efficiency to speed up the execution times, to conserve memory, or to scale up the complexity or number of agents in their simulations. We describe in detail an implementation of Dynamic Agent Compression that is lossless, i.e., no model detail is discarded during the compression process. We also contrast lossless compression to lossy compression, which promises greater efficiency gains yet may introduce artifacts in model behavior. The advantages outweigh the overhead of Dynamic Agent Compression in models where agents are unevenly heterogeneous — where a set of highly heterogeneous agents are intermixed with numerous other agents that fall into broad internally homogeneous categories. Dynamic Agent Compression is not appropriate in models with few, exclusively complex, agents.Agent-Based Modeling, Scaling, Homogeneity, Compression

    Experimental evaluation of Kuhn's geometric index of reduction and the flat-flake problem

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    This paper presents the results of an experiment designed to explore the performance of Kuhn's Geometric Index of Unifacial Reduction [S. Kuhn, A geometric index of reduction for unifacial stone tools, Journal of Archaeological Science 17 (1990) 585-593] in measuring the amount of material removed over a sequence of retouching events for a population of 30 flakes. The index provides a reliable absolute measure of reduction under experimental conditions, and does so irrespective of blank cross-section, suggesting that the "flat-flake" problem is not necessarily a serious difficulty for the index. Furthermore, Kuhn's Index provided a more sensitive and robust measurement of the extent of reduction than any of the alternative techniques proposed in recent years

    Study of space shuttle environmental control and life support problems

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    Four problem areas were treated: (1) cargo module environmental control and life support systems; (2) space shuttle/space station interfaces; (3) thermal control considerations for payloads; and (4) feasibility of improving system reusability

    Developing a novel organ-on-a-chip model to study ovarian cancer

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    PhD thesisFollowing the development of the lung-on-a-chip system there has been a rapid increase in interest in advanced tissue culture models embedded in microfluidic systems. Some models, and the focus of this thesis, utilise micro-structured compartments to control cell assembly and recapitulate tissue architecture. This thesis aims to develop a vascularised model of ovarian cancer within a microfluidic chip. Interactions between the vasculature and ovarian cancer have not been widely explored, though studies have demonstrated high micro-vessel density as an independent prognostic marker for worse progression-free survival in women with advanced epithelial ovarian cancer. In addition, the use of anti-angiogenics, such as bevacizumab, have been shown to be effective adjuvant and neoadjuvant therapies in high grade serous ovarian cancer (HGSOC) treatment. This thesis first examines the parameters enabling the formation of a reproducible stable microvascular system. Markers associated with the maturation of the microvasculture, including adheren and tight junction markers, are characterised, in addition to the quantification of the barrier properties of the endothelium. This system is then used to investigate the interactions between endothelial cells and various stromal cells potentially important for endothelium maturation. It is observed that pericytes inhibit vessel hyperplasia and reduce vessel permeability, in agreement with what is reported in literature, but also improve the stability of the vasculature in response to stress (low serum). The interaction between the vascular system and a HGSOC cell line (G33) is then presented. G33s are found to promote short-term vessel sprouting, whereas HUVECs were found to stimulate G33 proliferation and promote a change in morphology. Finally, our vascular model was used in developing a novel model for the assessment of efficacy of drug-therapy, via the embedding of G33 spheroids into a microvasculature

    Exploring the Potential of Environmental Impact Investing for Sustainable Development: The Cases of Dominion Energy and Tesla Motors

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    The health of our planet and the existence of our species faces an uncertain future. Climate change is the single largest issue facing society today, as carbon-based fuel and combustion engines have driven development in nearly every industry. Public investment through securities markets have enabled corporations to extract coal and oil, build combustion engines, and distribute fuel commercially for over one hundred and fifty years. However, it is now widely accepted that if business-as-usual continues, carbon emissions will cause irreversible and devastating effects to the environment and humankind. International, national, local governments, companies, and general populations have taken steps to combat the existential threat of climate change. Divestment in fossil fuel can come both from market mechanics encouraging investment in alternatives, as well as strategic decisions by corporations to make a change. Offering investors financial vehicles to promote sustainable development will improve the capacity of our world to have a more sustainable future, as well as offer investors competitive returns that are not subject to liabilities expected to continue in the fossil fuel industries. This research describes a quantitative additive preference model based on environmental criteria to analyze both Dominion Energy and Tesla Motors through the lens of environmental impact investing utility. The purpose of the model is to quantify the potential environmental impact of individual companies to inform institutional and retail investment decisions geared at environmentally conscious investing. Future work should focus on refining the criteria and weights, integrating the model into a fund-management toolkit, and providing greater transparency for all investors to make positive environmentally impactful investment decisions
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