Multiple mechanisms of spiral wave breakup in a model of cardiac electrical activity

It has become widely accepted that the most dangerous cardiac arrhythmias are due to re- entrant waves, i.e., electrical wave(s) that re-circulate repeatedly throughout the tissue at a higher frequency than the waves produced by the heart's natural pacemaker (sinoatrial node). However, the complicated structure of cardiac tissue, as well as the complex ionic currents in the cell, has made it extremely difficult to pinpoint the detailed mechanisms of these life-threatening reentrant arrhythmias. A simplified ionic model of the cardiac action potential (AP), which can be fitted to a wide variety of experimentally and numerically obtained mesoscopic characteristics of cardiac tissue such as AP shape and restitution of AP duration and conduction velocity, is used to explain many different mechanisms of spiral wave breakup which in principle can occur in cardiac tissue. Some, but not all, of these mechanisms have been observed before using other models; therefore, the purpose of this paper is to demonstrate them using just one framework model and to explain the different parameter regimes or physiological properties necessary for each mechanism (such as high or low excitability, corresponding to normal or ischemic tissue, spiral tip trajectory types, and tissue structures such as rotational anisotropy and periodic boundary conditions). Each mechanism is compared with data from other ionic models or experiments to illustrate that they are not model-specific phenomena. The fact that many different breakup mechanisms exist has important implications for antiarrhythmic drug design and for comparisons of fibrillation experiments using different species, electromechanical uncoupling drugs, and initiation protocols.Comment: 128 pages, 42 figures (29 color, 13 b&w

Selecting an Appropriate Damages Expert in a Patent Case; An Examination of the Current Status of Daubert

The determination of damages is a critical part of any patent case. As a plaintiff, maximizing awarded damages, whether financial or injunctive, is the ultimate objective of the patent case. As a defendant, minimizing or preventing any awarded damages is the ultimate objective. Multimillion dollar verdicts in patent cases are now the norm and hundred plus million dollar verdicts are becoming more frequent. A lawyer who fails to devote sufficient time to this critical component of a case does the client a disservice. There are generally two types of damages in patent cases: lost profits and a reasonable royalty. A patent owner may seek either lost profits or a reasonable royalty, or a combination of both, as long the recoveries do not overlap. The determination of patent damages awarded is a question of fact, and numerous damage theories exist within the broad categories of both lost profits and a reasonable royalty to help answer that question

Seismic Response to Injection Well Stimulation in a High-Temperature, High-Permeability Reservoir

Fluid injection into the Earth's crust can induce seismic events that cause damage to local infrastructure but also offer valuable insight into seismogenesis. The factors that influence the magnitude, location, and number of induced events remain poorly understood but include injection flow rate and pressure as well as reservoir temperature and permeability. The relationship between injection parameters and injection-induced seismicity in high-temperature, high-permeability reservoirs has not been extensively studied. Here we focus on the Ngatamariki geothermal field in the central Taupō Volcanic Zone, New Zealand, where three stimulation/injection tests have occurred since 2012. We present a catalog of seismicity from 2012 to 2015 created using a matched-filter detection technique. We analyze the stress state in the reservoir during the injection tests from first motion-derived focal mechanisms, yielding an average direction of maximum horizontal compressive stress (SHmax) consistent with the regional NE-SW trend. However, there is significant variation in the direction of maximum compressive stress (σ1), which may reflect geological differences between wells. We use the ratio of injection flow rate to overpressure, referred to as injectivity index, as a proxy for near-well permeability and compare changes in injectivity index to spatiotemporal characteristics of seismicity accompanying each test. Observed increases in injectivity index are generally poorly correlated with seismicity, suggesting that the locations of microearthquakes are not coincident with the zone of stimulation (i.e., increased permeability). Our findings augment a growing body of work suggesting that aseismic opening or slip, rather than seismic shear, is the active process driving well stimulation in many environments

The effect of variable labels on deep learning models trained to predict breast density

Purpose: High breast density is associated with reduced efficacy of mammographic screening and increased risk of developing breast cancer. Accurate and reliable automated density estimates can be used for direct risk prediction and passing density related information to further predictive models. Expert reader assessments of density show a strong relationship to cancer risk but also inter-reader variation. The effect of label variability on model performance is important when considering how to utilise automated methods for both research and clinical purposes. Methods: We utilise subsets of images with density labels to train a deep transfer learning model which is used to assess how label variability affects the mapping from representation to prediction. We then create two end-to-end deep learning models which allow us to investigate the effect of label variability on the model representation formed. Results: We show that the trained mappings from representations to labels are altered considerably by the variability of reader scores. Training on labels with distribution variation removed causes the Spearman rank correlation coefficients to rise from $0.751\pm0.002$ to either $0.815\pm0.006$ when averaging across readers or $0.844\pm0.002$ when averaging across images. However, when we train different models to investigate the representation effect we see little difference, with Spearman rank correlation coefficients of $0.846\pm0.006$ and $0.850\pm0.006$ showing no statistically significant difference in the quality of the model representation with regard to density prediction. Conclusions: We show that the mapping between representation and mammographic density prediction is significantly affected by label variability. However, the effect of the label variability on the model representation is limited

Variation in XANES in biotite as a function of orientation, crystal composition, and metamorphic history

Microscale analysis of ferrous:ferric iron ratios in silicate minerals has the potential to constrain geological processes but has proved challenging because textural information and spatial resolution are limited with bulk techniques, and in situ methods have limited spatial resolution. Synchrotron methods, such as XANES, have been hampered by the sensitivity of spectra to crystal orientation and matrix effects. In an attempt to break this nexus, biotites from Tanzania were characterized with a combination of optical microscopy, electron microprobe, Mössbauer analysis, electron backscatter diffraction (EBSD) and X-ray absorption near edge structure (XANES) spectroscopy. Pre-edge and edge characteristics of the FeKa absorption feature were compared to orientation information derived by EBSD and ferric iron content derived from Mössbauer analysis. Statistically significant correlations between measured spectral features and optic/crystallographic orientation were observed for individual samples. However, orientation corrections derived from these correlations did not reduce the uncertainty in Fe3+/Fetot. The observations are consistent with matrix- and ordering-dependency of the XANES features, and further work is necessary if a general formulation for orientation corrections is to be devised

Neutral B-meson mixing from three-flavor lattice QCD: Determination of the SU(3)-breaking ratio \xi

We study SU(3)-breaking effects in the neutral B_d-\bar B_d and B_s-\bar B_s systems with unquenched N_f=2+1 lattice QCD. We calculate the relevant matrix elements on the MILC collaboration's gauge configurations with asqtad-improved staggered sea quarks. For the valence light-quarks (u, d, and s) we use the asqtad action, while for b quarks we use the Fermilab action. We obtain \xi=f_{B_s}\sqrt{B_{B_s}}/f_{B_d}\sqrt{B_{B_d}}=1.268+-0.063. We also present results for the ratio of bag parameters B_{B_s}/B_{B_d} and the ratio of CKM matrix elements |V_{td}|/|V_{ts}|. Although we focus on the calculation of \xi, the strategy and techniques described here will be employed in future extended studies of the B mixing parameters \Delta M_{d,s} and \Delta\Gamma_{d,s} in the Standard Model and beyond.Comment: 36 pages, 7 figure

Quarkonium mass splittings in three-flavor lattice QCD

We report on calculations of the charmonium and bottomonium spectrum in lattice QCD. We use ensembles of gauge fields with three flavors of sea quarks, simulated with the asqtad improved action for staggered fermions. For the heavy quarks we employ the Fermilab interpretation of the clover action for Wilson fermions. These calculations provide a test of lattice QCD, including the theory of discretization errors for heavy quarks. We provide, therefore, a careful discussion of the results in light of the heavy-quark effective Lagrangian. By and large, we find that the computed results are in agreement with experiment, once parametric and discretization errors are taken into account.Comment: 21 pages, 17 figure

Shape-based peak identification for ChIP-Seq

We present a new algorithm for the identification of bound regions from ChIP-seq experiments. Our method for identifying statistically significant peaks from read coverage is inspired by the notion of persistence in topological data analysis and provides a non-parametric approach that is robust to noise in experiments. Specifically, our method reduces the peak calling problem to the study of tree-based statistics derived from the data. We demonstrate the accuracy of our method on existing datasets, and we show that it can discover previously missed regions and can more clearly discriminate between multiple binding events. The software T-PIC (Tree shape Peak Identification for ChIP-Seq) is available at http://math.berkeley.edu/~vhower/tpic.htmlComment: 12 pages, 6 figure