969 resultados para Geometrical transforms
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ACKNOWLEDGEMENTS The authors are grateful to the following bodies that provided financial support for the project: (i) China Scholarship Council, (ii) National Natural Science Foundation of China (Grant No. U1334201 and (iii) UK Engineering and Physical Sciences Research Council (Grant No. EP/G069441/1).
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Acknowledgements This study was funded by Sarcoma UK, Friends of Anchor and the Medical Research Council grant number 99477 awarded to HW and PSZ. This work was also supported, in part, by NHS funding to the NIHR Biomedical Research Centre at The Royal Marsden and the Institute of Cancer Research, and the Chris Lucas Trust, UK. We also thank the CCLG Tissue Bank for access to samples, and contributing CCLG centres, including members of the ECMC paediatric network. The CCLG Tissue Bank is funded by Cancer Research UK and CCLG. In addition we would like to thank Prof KunLiang Guan and Prof Malcolm Logan for kindly providing constructs
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Acknowledgements This study was funded by Sarcoma UK, Friends of Anchor and the Medical Research Council grant number 99477 awarded to HW and PSZ. This work was also supported, in part, by NHS funding to the NIHR Biomedical Research Centre at The Royal Marsden and the Institute of Cancer Research, and the Chris Lucas Trust, UK. We also thank the CCLG Tissue Bank for access to samples, and contributing CCLG centres, including members of the ECMC paediatric network. The CCLG Tissue Bank is funded by Cancer Research UK and CCLG. In addition we would like to thank Prof KunLiang Guan and Prof Malcolm Logan for kindly providing constructs
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.
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Understanding the microscopic mechanisms of electronic excitation in organic photovoltaic cells is a challenging problem in the design of efficient devices capable of performing sunlight harvesting. Here we develop and apply an ab initio approach based on time-dependent density functional theory and Ehrenfest dynamics to investigate photoinduced charge transfer in small organic molecules. Our calculations include mixed quantum–classical dynamics with ions moving classically and electrons quantum mechanically, where no experimental external parameter other than the material geometry is required. We show that the behavior of photocarriers in zinc phthalocyanine (ZnPc) and C60 systems, an effective prototype system for organic solar cells, is sensitive to the atomic orientation of the donor and the acceptor units as well as the functionalization of covalent molecules at the interface. In particular, configurations with the ZnPc molecules facing on C60 facilitate charge transfer between substrate and molecules that occurs within 200 fs. In contrast, configurations where ZnPc is tilted above C60 present extremely low carrier injection efficiency even at longer times as an effect of the larger interfacial potential level offset and higher energetic barrier between the donor and acceptor molecules. An enhancement of charge injection into C60 at shorter times is observed as binding groups connect ZnPc and C60 in a dyad system. Our results demonstrate a promising way of designing and controlling photoinduced charge transfer on the atomic level in organic devices that would lead to efficient carrier separation and maximize device performance.
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This thesis discusses memory effects in open quantum systems with an emphasis on the Breuer, Laine, Piilo (BLP) measure of non-Markovianity. It is shown how the calculation of the measure can be simplifed and how quantum information protocols can bene t from memory e ects. The superdense coding protocol is used as an example of this. The quantum Zeno effect will also be studied from the point of view of memory e ects. Finally the geometric ideas used in simplifying the calculation of the BLP measure are applied in studying the amount of resources needed for detecting bipartite quantum correlations. It is shown that to decide without prior information if an unknown quantum state is entangled or not, an informationally complete measurement is required. The first part of the thesis contains an introduction to the theoretical ideas such as quantum states, closed and open quantum systems and necessary mathematical tools. The theory is then applied in the second part of the thesis as the results obtained in the original publications I-VI are presented and discussed.
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A set of observables is described for the topological quantum field theory which describes quantum gravity in three space-time dimensions with positive signature and positive cosmological constant. The simplest examples measure the distances between points, giving spectra and probabilities which have a geometrical interpretation. The observables are related to the evaluation of relativistic spin networks by a Fourier transform.
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One of the simplest models of adaptation to a new environment is Fisher's Geometric Model (FGM), in which populations move on a multidimensional landscape defined by the traits under selection. The predictions of this model have been found to be consistent with current observations of patterns of fitness increase in experimentally evolved populations. Recent studies investigated the dynamics of allele frequency change along adaptation of microbes to simple laboratory conditions and unveiled a dramatic pattern of competition between cohorts of mutations, i.e., multiple mutations simultaneously segregating and ultimately reaching fixation. Here, using simulations, we study the dynamics of phenotypic and genetic change as asexual populations under clonal interference climb a Fisherian landscape, and ask about the conditions under which FGM can display the simultaneous increase and fixation of multiple mutations-mutation cohorts-along the adaptive walk. We find that FGM under clonal interference, and with varying levels of pleiotropy, can reproduce the experimentally observed competition between different cohorts of mutations, some of which have a high probability of fixation along the adaptive walk. Overall, our results show that the surprising dynamics of mutation cohorts recently observed during experimental adaptation of microbial populations can be expected under one of the oldest and simplest theoretical models of adaptation-FGM.
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This study highlights the importance of cognition-affect interaction pathways in the construction of mathematical knowledge. Scientific output demands further research on the conceptual structure underlying such interaction aimed at coping with the high complexity of its interpretation. The paper discusses the effectiveness of using a dynamic model such as that outlined in the Mathematical Working Spaces (MWS) framework, in order to describe the interplay between cognition and affect in the transitions from instrumental to discursive geneses in geometrical reasoning. The results based on empirical data from a teaching experiment at a middle school show that the use of dynamic geometry software favours students’ attitudinal and volitional dimensions and helps them to maintain productive affective pathways, affording greater intellectual independence in mathematical work and interaction with the context that impact learning opportunities in geometric proofs. The reflective and heuristic dimensions of teacher mediation in students’ learning is crucial in the transition from instrumental to discursive genesis and working stability in the Instrumental-Discursive plane of MWS.
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This thesis builds a framework for evaluating downside risk from multivariate data via a special class of risk measures (RM). The peculiarity of the analysis lies in getting rid of strong data distributional assumptions and in orientation towards the most critical data in risk management: those with asymmetries and heavy tails. At the same time, under typical assumptions, such as the ellipticity of the data probability distribution, the conformity with classical methods is shown. The constructed class of RM is a multivariate generalization of the coherent distortion RM, which possess valuable properties for a risk manager. The design of the framework is twofold. The first part contains new computational geometry methods for the high-dimensional data. The developed algorithms demonstrate computability of geometrical concepts used for constructing the RM. These concepts bring visuality and simplify interpretation of the RM. The second part develops models for applying the framework to actual problems. The spectrum of applications varies from robust portfolio selection up to broader spheres, such as stochastic conic optimization with risk constraints or supervised machine learning.