The politics of descriptive inference: contested concepts in conflict data

Descriptive research is sometimes understood as simply compiling and presenting objective facts, or ‘telling it like it is.’ We challenge this understanding, arguing that description involves a series of subjective, value-laden decisions that may reflect, reinforce, or alternatively undermine, existing narratives and power structures; accordingly, description is fundamentally, and unavoidably, political. We illustrate this argument with respect to descriptive research on violence against civilians by comparing how three descriptive research outputs—the Uppsala Conflict Data Program’s One-Sided Violence, the Political Instability Task Force’s Genocide and Politicide, and the Targeted Mass Killings datasets—define contested concepts relating to the distinction between combatants and civilians, identification of state actors, and intent. We demonstrate how differences in these definitions manifest in different descriptive inferences about violence in Burundi in 1993, and we discuss how an understanding of description as political relates to researchers’ responsibilities as compilers and users of descriptive data

A novel algorithm for color quantization by 3D diffusion

Author name used in this publication: Y. H. ChanRefereed conference paper2002-2003 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Combined state and parameter estimation in level-set methods

Reduced-order models based on level-set methods are widely used tools to qualitatively capture and track the nonlinear dynamics of an interface. The aim of this paper is to develop a physics-informed, data-driven, statistically rigorous learning algorithm for state and parameter estimation with level-set methods. A Bayesian approach based on data assimilation is introduced. Data assimilation is enabled by the ensemble Kalman filter and smoother, which are used in their probabilistic formulations. The level-set data assimilation framework is verified in onedimensional and two-dimensional test cases, where state estimation, parameter estimation and uncertainty quantification are performed. The statistical performance of the proposed ensemble Kalman filter and smoother is quantified by twin experiments. In the twin experiments, the combined state and parameter estimation fully recovers the reference solution, which validates the proposed algorithm. The level-set data assimilation framework is then applied to the prediction of the nonlinear dynamics of a forced premixed flame, which exhibits the formation of sharp cusps and intricate topological changes, such as pinch-off events. The proposed physics-informed statistical learning algorithm opens up new possibilities for making reduced-order models of interfaces quantitatively predictive, any time that reference data is available

A data-driven kinematic model of a ducted premixed flame

Reduced-order models of flame dynamics can be used to predict and mitigate the emergence of thermoacoustic oscillations in the design of gas turbine and rocket engines. This process is hindered by the fact that these models, although often qualitatively correct, are not usually quantitatively accurate. As automated experiments and numerical simulations produce ever-increasing quantities of data, the question arises as to how this data can be assimilated into physics-informed reduced-order models in order to render these models quantitatively accurate. In this study, we develop and test a physics-based reduced-order model of a ducted premixed flame in which the model parameters are learned from high speed videos of the flame. The experimental data is assimilated into a level-set solver using an ensemble Kalman filter. This leads to an optimally calibrated reduced-order model with quantified uncertainties, which accurately reproduces elaborate nonlinear features such as cusp formation and pinch-off. The reduced-order model continues to match the experiments after assimilation has been switched off. Further, the parameters of the model, which are extracted automatically, are shown to match the first order behavior expected on physical grounds. This study shows how reduced-order models can be updated rapidly whenever new experimental or numerical data becomes available, without the data itself having to be stored

Assimilation of Experimental Data to Create a Quantitatively Accurate Reduced-Order Thermoacoustic Model

Abstract We combine a thermoacoustic experiment with a thermoacoustic reduced order model using Bayesian inference to accurately learn the parameters of the model, rendering it predictive. The experiment is a vertical Rijke tube containing an electric heater. The heater drives a base flow via natural convection, and thermoacoustic oscillations via velocity-driven heat release fluctuations. The decay rates and frequencies of these oscillations are measured every few seconds by acoustically forcing the system via a loudspeaker placed at the bottom of the tube. More than 320,000 temperature measurements are used to compute state and parameters of the base flow model using the Ensemble Kalman Filter. A wave-based network model is then used to describe the acoustics inside the tube. We balance momentum and energy at the boundary between two adjacent elements, and model the viscous and thermal dissipation mechanisms in the boundary layer and at the heater and thermocouple locations. Finally, we tune the parameters of two different thermoacoustic models on an experimental dataset that comprises more than 40,000 experiments. This study shows that, with thorough Bayesian inference, a qualitative model can become quantitatively accurate, without overfitting, as long as it contains the most influential physical phenomena.European Unio

Metabolic Phenotype of Stage IV Lung Adenocarcinoma: relationship with epidermal growth factor receptor mutation

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Contextual algorithm for color quantization

2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Mitochondrial respiration is reduced in atherosclerosis, promoting necrotic core formation and reducing relative fibrous cap thickness

Objective: Mitochondrial DNA (mtDNA) damage is present in murine and human atherosclerotic plaques. However, whether endogenous levels of mtDNA damage are sufficient to cause mitochondrial dysfunction, and whether decreasing mtDNA damage and improving mitochondrial respiration affects plaque burden or composition are unclear. We examined mitochondrial respiration in human atherosclerotic plaques, and whether augmenting mitochondrial respiration affects atherogenesis. Approach and Results: Human atherosclerotic plaques showed marked mitochondrial dysfunction, manifested as reduced mtDNA copy number and oxygen consumption rate in fibrous cap and core regions. Vascular smooth muscle cells (VSMCs) derived from plaques showed impaired mitochondrial respiration, reduced complex I expression and increased mitophagy, which was induced by oxidized low-density lipoprotein. Apolipoprotein E-deficient (ApoE-/-) mice showed decreased mtDNA integrity and mitochondrial respiration, associated with increased mitochondrial reactive oxygen species (ROS). To determine whether alleviating mtDNA damage and increasing mitochondrial respiration affects atherogenesis, we studied ApoE-/- mice overexpressing the mitochondrial helicase Twinkle (Tw+/ApoE-/-). Tw+/ApoE-/- mice showed increased mtDNA integrity, copy number, respiratory complex abundance and respiration. Tw+/ApoE-/- mice had decreased necrotic core and increased fibrous cap areas, and Tw+/ApoE-/- bone marrow transplantation also reduced core areas. Twinkle increased VSMC mtDNA integrity and respiration. Twinkle also promoted VSMC proliferation and protected both VSMCs and macrophages from oxidative stress-induced apoptosis. Conclusions: Endogenous mtDNA damage in mouse and human atherosclerosis is associated with significantly reduced mitochondrial respiration. Reducing mtDNA damage and increasing mitochondrial respiration decreases necrotic core and increases fibrous cap areas independently of changes in ROS, and may be a promising therapeutic strategy in atherosclerosis.This work was supported by British Heart Foundation (BHF) grants PG/14/69/31032 and RG/13/14/30314, a Wellcome Trust PhD Fellowship to J. Reinhold, the National Institute for Health Research Cambridge Biomedical Research Centre, the BHF Centre for Research Excellence, the Academy of Medical Sciences and by grants to M.P. Murphy from the Medical Research Council UK (MC_U105663142), and by a Wellcome Trust Investigator award (110159/Z/15/Z)

Wigner Crystallization in a Quasi-3D Electronic System

When a strong magnetic field is applied perpendicularly (along z) to a sheet confining electrons to two dimensions (x-y), highly correlated states emerge as a result of the interplay between electron-electron interactions, confinement and disorder. These so-called fractional quantum Hall (FQH) liquids form a series of states which ultimately give way to a periodic electron solid that crystallizes at high magnetic fields. This quantum phase of electrons has been identified previously as a disorder-pinned two-dimensional Wigner crystal with broken translational symmetry in the x-y plane. Here, we report our discovery of a new insulating quantum phase of electrons when a very high magnetic field, up to 45T, is applied in a geometry parallel (y-direction) to the two-dimensional electron sheet. Our data point towards this new quantum phase being an electron solid in a "quasi-3D" configuration induced by orbital coupling with the parallel field

Field-induced polarisation of Dirac valleys in bismuth

Electrons are offered a valley degree of freedom in presence of particular lattice structures. Manipulating valley degeneracy is the subject matter of an emerging field of investigation, mostly focused on charge transport in graphene. In bulk bismuth, electrons are known to present a threefold valley degeneracy and a Dirac dispersion in each valley. Here we show that because of their huge in-plane mass anisotropy, a flow of Dirac electrons along the trigonal axis is extremely sensitive to the orientation of in-plane magnetic field. Thus, a rotatable magnetic field can be used as a valley valve to tune the contribution of each valley to the total conductivity. According to our measurements, charge conductivity by carriers of a single valley can exceed four-fifth of the total conductivity in a wide range of temperature and magnetic field. At high temperature and low magnetic field, the three valleys are interchangeable and the three-fold symmetry of the underlying lattice is respected. As the temperature lowers and/or the magnetic field increases, this symmetry is spontaneously lost. The latter may be an experimental manifestation of the recently proposed valley-nematic Fermi liquid state.Comment: 14 pages + 5 pages of supplementary information; a slightly modified version will appear as an article in Nature physic