cssi/SciSciGPT-SciSciNet huggingface dataset:
Visualization and analysis of the Kohn-Sham kinetic energy density and its orbital-free description in molecules.

We visualize the Kohn-Sham kinetic energy density (KED) and the ingredients — the electron density, its gradient, and Laplacian — used to construct orbital-free models of it, for the AE6 test set of molecules. These are compared to related quantities used in metaGGA’s, to characterize two important limits — the gradient expansion and the localized-electron limit typified by the covalent bond. We find the second-order gradient expansion of the KED to be a surprisingly successful predictor of the exact KED, particularly at low densities where this approximation fails for exchange. This contradicts the conjointness conjecture that the optimal enhancement factors for orbital-free kinetic and exchange energy functionals are closely similar in form. In addition we find significant problems with a recent metaGGA-level orbital-free KED, especially for regions of strong electron localization. We define an orbital-free description of electron localization and a revised metaGGA that improves upon atomization energies significantly.
Compressed air energy storage

Compressed air energy storage (CAES) systems are being developed for peak load leveling applications by electric utilities. Energy is stored by compressing air in an underground reservoir; when power is required, the air is heated and expanded through a turbine-generator system. Several CAES plants are being designed, and construction of the first large-scale plant will be completed late in 1977. From the specifications of these systems, it is concluded that CAES systems appear to be economically favored over gas turbines and other near-term utility storage systems for a substantial range of costs of fuel and off-peak charging power.
Restoration of Images Corrupted by Impulse Noise and Mixed Gaussian Impulse Noise Using Blind Inpainting

This article studies the problem of image restoration of observed images corrupted by impulse noise and mixed Gaussian impulse noise. Since the pixels damaged by impulse noise contain no information about the true image, how to find this set correctly is a very important problem. We propose two methods based on blind inpainting and $\ell_0$ minimization that can simultaneously find the damaged pixels and restore the image. By iteratively restoring the image and updating the set of damaged pixels, these methods have better performance than other methods, as shown in the experiments. In addition, we provide convergence analysis for these methods; these algorithms will converge to coordinatewise minimum points. In addition, they will converge to local minimum points (or with probability one) with some modifications in the algorithms.
Neutrino Masses and SO(10) SUSY GUTs

In this talk I discuss the qualitative features of an SO(10) SUSY GUT with an SU(2)×U(1)n family symmetry. I then describe the global fit of this theory to precision electroweak data [including charged fermion masses and mixing angles]. Finally, the predictions of the model for neutrino masses and mixing are discussed. The most predictive version of the model naturally fits atmospheric neutrino data with maximal νμ→ντ oscillations and solar neutrino data with small mixing angle MSW νe→νsterile oscillations.
Relativistic Diskoseismology. II. Analytical Results for c-modes

We first briefly review how we investigate the modes of oscillation trapped within the inner region of accretion disks by the strong-field gravitational properties of a black hole (or a compact, weakly magnetized neutron star). Then we focus on the "corrugation" (c-) modes, nearly incompressible perturbations of the inner disk. The fundamental c-modes have eigenfrequencies (ordered by radial mode number) which correspond to the Lense-Thirring frequency, evaluated at the outer trapping radius of the mode, in the slow rotation limit. This trapping radius is a decreasing function of the black hole angular momentum, so a significant portion of the disk is modulated only for slowly rotating black holes. The eigenfrequencies are thus strongly increasing functions of black hole angular momentum. The dependence of the eigenfrequencies on the speed of sound (or the luminosity) within the disk is very weak, except for slowly rotating black holes.
PREDICTION OF THE PROTON-TO-TOTAL TURBULENT HEATING IN THE SOLAR WIND

This paper employs a recent turbulent heating prescription to predict the ratio of proton-to-total heating due to the kinetic dissipation of Alfvenic turbulence as a function of heliocentric distance. Comparing to a recent empirical estimate for this turbulent heating ratio in the high-speed solar wind, the prediction shows good agreement with the empirical estimate for R 0.8 AU, but predicts less ion heating than the empirical estimate at smaller heliocentric radii. At these smaller radii, the turbulent heating prescription, calculated in the gyrokinetic limit, fails because the turbulent cascade is predicted to reach the proton cyclotron frequency before Landau damping terminates the cascade. These findings suggest that the turbulent cascade can reach the proton cyclotron frequency at R 0.8 AU, leading to a higher level of proton heating than predicted by the turbulent heating prescription in the gyrokinetic limit. At larger heliocentric radii, R 0.8 AU, this turbulent heating prescription contains all of the necessary physical mechanisms needed to reproduce the empirically estimated proton-to-total heating ratio.
Step growth and meandering in a precursor-mediated epitaxy with anisotropic attachment kinetics and terrace diffusion

Step meandering instability in a Burton-Cabrera-Frank (BCF)-type model for the growth of an isolated, atomically high step on a crystal surface is analyzed. It is assumed that the growth is sustained by the molecular precursors deposition on a terrace and their decomposition into atomic constituents; both processes are explicitly modeled. A strongly nonlinear evolution PDE for the shape of the step is derived in the long-wave limit and without assuming smallness of the amplitude; this equation may be transformed into a convective Cahn-Hilliard-type PDE for the step slope. Meandering is studied as a function of the precursors diffusivity and of the desorption rates of the precursors and adatoms. Several important features are identified, such as: the interrupted coarsening, “facet” bunching, and the lateral drift of the step perturbations (a traveling wave) when the terrace diffusion is anisotropic. The nonlinear drift introduces a disorder into the evolution of a step meander, which results in a pronounced oscillation of the step velocity, meander amplitude and lateral length scale in the steady-state that emerged after the coarsening was interrupted. The mean values of these characteristics are also strongly affected by the drift.
Eat4Thought: A Design of Food Journaling

Food journaling is an effective method to help people identify their eating patterns and encourage healthy eating habits as it requires self-reflection on eating behaviors. Current tools have predominately focused on tracking food intake, such as carbohydrates, proteins, fats, and calories. Other factors, such as contextual information and momentary thoughts and feelings that are internal to an individual, are also essential to help people reflect upon and change attitudes about eating behaviors. However, current dietary tracking tools rarely support capturing these elements as a way to foster deep reflection. In this work, we present Eat4Thought - a food journaling application that allows users to track their emotional, sensory, and spatio-temporal elements of meals as a means of supporting self-reflection. The application enables vivid documentation of experiences and self-reflection on the past through video recording. We describe our design process and an initial evaluation of the application. We also provide design recommendations for future work on food journaling.
Safety barrier certificates for heterogeneous multi-robot systems

This paper presents a formal framework for collision avoidance in multi-robot systems, wherein an existing controller is modified in a minimally invasive fashion to ensure safety. We build this framework through the use of control barrier functions (CBFs) which guarantee forward invariance of a safe set; these yield safety barrier certificates in the context of heterogeneous robot dynamics subject to acceleration bounds. Moreover, safety barrier certificates are extended to a distributed control framework, wherein neighboring agent dynamics are unknown, through local parameter identification. The end result is an optimization-based controller that formally guarantees collision free behavior in heterogeneous multi-agent systems by minimally modifying the desired controller via safety barrier constraints. This formal result is verified in simulation on a multi-robot system consisting of both “sluggish” and “agile” robots.
Mode I and II Interlaminar Fracture in Laminated Composites: A Size Effect Study

This work investigates the mode I and II interlaminar fracturing behavior of laminated composites and the related size effects. Fracture tests on geometrically scaled Double Cantilever Beam (DCB) and End Notch Flexure (ENF) specimens were conducted to understand the nonlinear effects of the cohesive stresses in the Fracture Process Zone (FPZ). The results show a significant difference between the mode I and mode II fracturing behaviors. It is shown that, while the strength of the DCB specimens scales according to the Linear Elastic Fracture Mechanics (LEFM), this is not the case for the ENF specimens. Small specimens exhibit a pronounced pseudo-ductility with limited size effect and a significant deviation from LEFM, whereas larger specimens behave in a more brittle way, with the size effect on nominal strength closer to that predicted by LEFM. This behavior, due to the significant size of the Fracture Process Zone (FPZ) compared to the specimen size, needs to be taken into serious consideration. It is shown that, for the specimen sizes investigated in this work, neglecting the non-linear effects of the FPZ can lead to an underestimation of the fracture energy by as much as 55%, with an error decreasing for increasing specimen sizes. Both the mode I and II test data can be captured very accurately by Bažant's type II Size Effect Law (SEL).
Quantum dynamics of a few-photon parametric oscillator

Experiments demonstrate a quantum parametric oscillator, a device with great potential in quantum error correction. Its minimal hardware design makes it a suitable building block for scalable quantum computing.
PageRank Pipeline Benchmark: Proposal for a Holistic System Benchmark for Big-Data Platforms

The rise of big data systems has created a need for benchmarks to measure and compare the capabilities of these systems. Big data benchmarks present unique scalability challenges. The supercomputing community has wrestled with these challenges for decades and developed methodologies for creating rigorous scalable benchmarks (e.g., HPC Challenge). The proposed PageRank pipeline benchmark employs supercomputing benchmarking methodologies to create a scalable benchmark that is reflective of many real-world big data processing systems. The PageRank pipeline benchmark builds on existing prior scalable benchmarks (Graph500, Sort, and PageRank) to create a holistic benchmark with multiple integrated kernels that can be run together or independently. Each kernel is well defined mathematically and can be implemented in any programming environment. The linear algebraic nature of PageRank makes it well suited to being implemented using the GraphBLAS standard. The computations are simple enough that performance predictions can be made based on simple computing hardware models. The surrounding kernels provide the context for each kernel that allows rigorous definition of both the input and the output for each kernel. Furthermore, since the proposed PageRank pipeline benchmark is scalable in both problem size and hardware, it can be used to measure and quantitatively compare a wide range of present day and future systems. Serial implementations in C++, Python, Python with Pandas, Matlab, Octave, and Julia have been implemented and their single threaded performance has been measured.
Numerical simulation of wave propagation in inhomogeneous media using Generalized Plane Waves

The Trefftz Discontinuous Galerkin (TDG) method is a technique for approximating the Helmholtz equation (or other linear wave equations) using piecewise defined local solutions of the equation to approximate the global solution. When coefficients in the equation (for example, the refractive index) are piecewise constant it is common to use plane waves on each element. However when the coefficients are smooth functions of position, plane waves are no longer directly applicable. In this paper we show how Generalized Plane Waves (GPWs) can be used in a modified TDG scheme to approximate the solution for piecewise smooth coefficients in two dimensions. GPWs are approximate solutions to the equation that reduce to plane waves when the medium through which the wave propagates is constant. We shall show how to modify the TDG sesquilinear form to allow us to prove convergence of the GPW based version. The new scheme retains the high order convergence of the original TDG scheme (when the solution is smooth) and also retains the same number of degrees of freedom per element (corresponding to the directions of the GPWs). Unfortunately it looses the advantage that only skeleton integrals need to be performed. Besides proving convergence, we provide numerical examples to test our theory.
To gauge or not to gauge

The D0 brane, or BFSS, matrix model is a quantum mechanical theory with an interesting gravity dual. We consider a variant of this model where we treat the SU(N) symmetry as a global symmetry, rather than as a gauge symmetry. This variant contains new non-singlet states. We consider the impact of these new states on its gravity dual. We argue that the gravity dual is essentially the same as the one for the original matrix model. The non-singlet states have higher energy at strong coupling and are therefore dynamically suppressed.
Robustness of interdependent networks: The case of communication networks and the power grid

We study the robustness of interdependent networks, in which the state of one network depends on the state of the other network and vice versa. In particular, we focus on the interdependency between the power grid and communication networks, where the grid depends on communications for its control, and the communication network depends on the grid for power. A real-world example is the Italian blackout of 2003, when a small failure in the power grid cascaded between the two networks and led to a massive blackout. In this paper, we study the minimum number of node failures needed to cause total blackout (i.e., all nodes in both networks to fail). In the case of unidirectional interdependency between the networks we show that the problem is NP-hard, and develop heuristics to find a near-optimal solution. On the other hand, we show that in the case of bidirectional interdependency this problem can be solved in polynomial time. We believe that this new interdependency model gives rise to important, yet unexplored, robust network design problems for interdependent networked infrastructures.
EPISODIC MASS LOSS FROM THE HYDROGEN-DEFICIENT CENTRAL STAR OF THE PLANETARY NEBULA LONGMORE 4*

A spectacular transient mass-loss episode from the extremely hot, hydrogen-deficient central star of the planetary nebula (PN) Longmore 4 (Lo 4) was discovered in 1992 by Werner et al. During that event, the star temporarily changed from its normal PG 1159 spectrum to that of an emission-line low-luminosity early-type Wolf-Rayet [WCE] star. After a few days, Lo 4 reverted to its normal, predominantly absorption-line PG 1159 type. To determine whether such events recur, and if so how often, I monitored the optical spectrum of Lo 4 from early 2003 to early 2012. Out of 81 spectra taken at random dates, 4 of them revealed mass-loss outbursts similar to that seen in 1992. This indicates that the episodes recur approximately every 100 days (if the recurrence rate has been approximately constant and the duration of a typical episode is ~5 days), and that the star is in a high-mass-loss state about 5% of the time. Since the enhanced stellar wind is hydrogen-deficient, it arises from the photosphere and is unlikely to be related to phenomena such as a binary or planetary companion or infalling dust. I speculate on plausible mechanisms for these unique outbursts, including the possibility that they are related to the non-radial GW Vir-type pulsations exhibited by Lo 4. The central star of the PN NGC 246 has stellar parameters similar to those of Lo 4, and it is also a GW Vir-type pulsator with similar pulsation periods. I obtained 167 spectra of NGC 246 between 2003 and 2011, but no mass ejections were found.
Asymptotically Optimal Exact Minibatch Metropolis-Hastings

Metropolis-Hastings (MH) is a commonly-used MCMC algorithm, but it can be intractable on large datasets due to requiring computations over the whole dataset. In this paper, we study minibatch MH methods, which instead use subsamples to enable scaling. We observe that most existing minibatch MH methods are inexact (i.e. they may change the target distribution), and show that this inexactness can cause arbitrarily large errors in inference. We propose a new exact minibatch MH method, TunaMH, which exposes a tunable trade-off between its batch size and its theoretically guaranteed convergence rate. We prove a lower bound on the batch size that any minibatch MH method must use to retain exactness while guaranteeing fast convergence-the first such bound for minibatch MH-and show TunaMH is asymptotically optimal in terms of the batch size. Empirically, we show TunaMH outperforms other exact minibatch MH methods on robust linear regression, truncated Gaussian mixtures, and logistic regression.
Higgs couplings and electroweak phase transition

We argue that extensions of the Standard Model (SM) with a strongly first-order electroweak phase transition generically predict significant deviations of the Higgs couplings to gluons, photons, and Z bosons from their SM values. Precise experimental measurements of the Higgs couplings at the LHC and at the proposed next-generation facilities will allow for a robust test of the phase transition dynamics. To illustrate this point, in this paper we focus on the scenario in which loops of a new scalar field are responsible for the first-order phase transition, and study a selection of benchmark models with various SM gauge quantum numbers of the new scalar. We find that the current LHC measurement of the Higgs coupling to gluons already excludes the possibility of a first-order phase transition induced by a scalar in a sextet, or larger, representation of the SU(3) c . Future LHC experiments (including HL-LHC) will be able to definitively probe the case when the new scalar is a color triplet. If the new scalar is not colored, an electron-positron Higgs factory, such as the proposed ILC or TLEP, would be required to test the nature of the phase transition. The extremely precise measurement of the Higgsstrahlung cross section possible at such machines will allow for a comprehensive and definitive probe of the possibility of a first-order electroweak phase transition in all models we considered, including the case when the new scalar is a pure gauge singlet.
Ferroelectricity in single crystal InMnO3

Single crystal synthesis, structure, electric polarization, and heat capacity measurements on hexagonal InMnO3 show that this small R ion in the RMnO3 series is ferroelectric (space group P63cm). Structural analysis of this system reveals a high degree of order within the MnO5 polyhedra but significant distortions in the R-O bond distributions compared to the previously studied materials. Point-charge estimates of the electric polarization yield an electrical polarization of ∼7.8 μC/cm2, 26% larger than the well-studied YMnO3 system. This system with enhanced room temperature polarization values may serve as a possible replacement for YMnO3 in device applications.
Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla.

Purpose Thalamic nuclei are largely invisible in conventional MRI due to poor contrast. Thalamus Optimized Multi-Atlas Segmentation (THOMAS) provides automatic segmentation of 12 thalamic nuclei using white-matter-nulled (WMn) Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequence at 7T, but increases overall scan duration. Routinely acquired, bias-corrected Magnetization Prepared 2 Rapid Gradient Echo (MP2RAGE) sequence yields superior tissue contrast and quantitative T1 maps. Application of THOMAS to MP2RAGE has been investigated in this study. Methods Eight healthy volunteers and five pediatric-onset multiple sclerosis patients were recruited at Children's Hospital of Philadelphia and scanned at Siemens 7T with WMn-MPRAGE and multi-echo-MP2RAGE (ME-MP2RAGE) sequences. White-matter-nulled contrast was synthesized (MP2-SYN) from T1 maps from ME-MP2RAGE sequence. Thalamic nuclei were segmented using THOMAS joint label fusion algorithm from WMn-MPRAGE and MP2-SYN datasets. THOMAS pipeline was modified to use majority voting to segment bias corrected T1-weighted uniform (MP2-UNI) images. Thalamic nuclei from MP2-SYN and MP2-UNI images were evaluated against corresponding nuclei obtained from WMn-MPRAGE images using dice coefficients, volume similarity indices (VSIs) and distance between centroids. Results For MP2-SYN, dice > 0.85 and VSI > 0.95 was achieved for five larger nuclei and dice > 0.6 and VSI > 0.7 was achieved for seven smaller nuclei. The dice and VSI were slightly higher, whereas the distance between centroids were smaller for MP2-SYN compared to MP2-UNI, indicating improved performance using the MP2-SYN image. Conclusions THOMAS algorithm can successfully segment thalamic nuclei in MP2RAGE images with essentially equivalent quality as WMn-MPRAGE, widening its applicability in studies focused on thalamic involvement in aging and disease.
A Spitzer IRAC Census of the Asymptotic Giant Branch Populations in Local Group Dwarfs. II. IC 1613

We present Spitzer IRAC photometry of the Local Group dwarf irregular galaxy IC 1613. We compare our 3.6, 4.5, 5.8, and 8.0 μm photometry with broadband optical photometry and find that from the optical data we cannot detect 43% and that an additional 11% of the total AGB population are misidentified, likely because of extinction caused by circumstellar material. Furthermore, we find that a narrowband optical carbon star study of IC 1613 detects 50% of the total AGB population and only considers 18% of this population in calculating the carbon to M-type AGB ratio. We derive an integrated mass-loss rate from the AGB stars of (0.2-1.0) × 10-3 M☉ yr-1 and find that the distribution of bolometric luminosities and mass-loss rates are consistent with those for other nearby metal-poor galaxies. Both the optical completeness fractions and mass-loss rates in IC 1613 are very similar to those in the Local Group dwarf irregular galaxy WLM, which is expected, given their similar characteristics and evolutionary histories.
DynamiTe: dynamic termination and non-termination proofs

There is growing interest in termination reasoning for nonlinear programs and, meanwhile, recent dynamic strategies have shown they are able to infer invariants for such challenging programs. These advances led us to hypothesize that perhaps such dynamic strategies for nonlinear invariants could be adapted to learn recurrent sets (for non-termination) and/or ranking functions (for termination). In this paper, we exploit dynamic analysis and draw termination and non-termination as well as static and dynamic strategies closer together in order to tackle nonlinear programs. For termination, our algorithm infers ranking functions from concrete transitive closures, and, for non-termination, the algorithm iteratively collects executions and dynamically learns conditions to refine recurrent sets. Finally, we describe an integrated algorithm that allows these algorithms to mutually inform each other, taking counterexamples from a failed validation in one endeavor and crossing both the static/dynamic and termination/non-termination lines, to create new execution samples for the other one. We have implemented these algorithms in a new tool called DynamiTe. For nonlinear programs, there are currently no SV-COMP termination benchmarks so we created new sets of 38 terminating and 39 non-terminating programs. Our empirical evaluation shows that we can effectively guess (and sometimes even validate) ranking functions and recurrent sets for programs with nonlinear behaviors. Furthermore, we show that counterexamples from one failed validation can be used to generate executions for a dynamic analysis of the opposite property. Although we are focused on nonlinear programs, as a point of comparison, we compare DynamiTe's performance on linear programs with that of the state-of-the-art tool, Ultimate. Although DynamiTe is an order of magnitude slower it is nonetheless somewhat competitive and sometimes finds ranking functions where Ultimate was unable to. Ultimate cannot, however, handle the nonlinear programs in our new benchmark suite.
Virtual mosaic knot theory

Mosaic diagrams for knots were first introduced in 2008 by Lomanoco and Kauffman for the purpose of building a quantum knot system. Since then, many others have explored the structure of these knot...
Geometry of AdS-Melvin Spacetimes

We study asymptotically AdS generalizations of Melvin spacetimes, describing gravitationally bound tubes of magnetic flux. We find that narrow fluxtubes, carrying strong magnetic fields but little total flux, are approximately unchanged from the Λ = 0 case at scales smaller than the AdS scale. However, fluxtubes with weak fields, which for Λ = 0 can grow arbitrarily large in radius and carry unbounded magnetic flux, are limited in radius by the AdS scale and like the narrow fluxtubes carry only small total flux. As a consequence, there is a maximum magnetic flux that can be carried by static fluxtubes in AdS. For flux Φtot < Φmax there are two branches of solutions, with one branch always narrower in radius than the other. We compute the ADM mass and tensions for AdS-Melvin fluxtube, finding that the wider radius branch of solutions always has lower mass. In the limit of vanishing flux, this branch reduces to the AdS soliton.
Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring

Abstract Extending from central California to Alaska, bull kelp (Nereocystis luetkeana) forms seasonal kelp forests that are iconic coastal ecosystems in much of the eastern Pacific. Historical and ongoing field surveys and aerial imagery are used to provide biological data on kelp canopy cover and health, but satellite remote sensing provides the opportunity to generate consistent, long-term datasets over a large spatial scale. Robust satellite-based timeseries measurements of giant kelp (Macrocystis pyrifera) are available for much of the California coastline (e.g., Santa Barbara to Santa Cruz), but there have been no equivalent publications for bull kelp. Recent loss of bull kelp in northern California emphasized the need for more expansive long-term monitoring of canopy trends. We tested various kelp classification approaches using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to Landsat imagery, which allowed sufficient temporal and spatial data collection during bull kelp's narrow seasonal maximum, and compare with the California Department of Fish and Wildlife (CDFW) aerial survey canopy area product. We addressed five main topics that have relevance to enabling Landsat in long-term monitoring of bull kelp canopy coverage in northern California: (1) the effect of MESMA configurations applied to Landsat imagery, including software dependencies and endmember configurations, (2) comparison of Landsat to traditional surveys, (3) differences across Landsat sensors, (4) tidal influence on canopy area, and (5) trends in the decadal timeseries. We found that there was no statistical difference (p = 0.53) between MESMA platforms (IDL-based and a Python-scripted method; RMSE 1.5 km2 or 17.6% when normalized by the range in CDFW), and that a 7-endmember MESMA model provided the lowest RMSE (1.4 km2 or 16.9%). Furthermore, while tidal phases can submerge or emerge kelp canopy and thus potentially affect kelp detection, we found a weak and statistically insignificant correlation between tides and performance of our remote estimate of kelp canopy area. Canopy estimations from Landsat-8 images yielded a higher NRMSE than Landsat-4 and -5 images, but the lack of matchup limits comparison. Imagery from early fall yielded the largest coverage estimates. Overall, our results show that Landsat enables broad remote measurement of bull kelp canopy coverage to supplement existing survey methods and increase continuity of timeseries for monitoring long-term trends.
Mixing and combustion in a laminar shear layer with imposed counterflow

Three-dimensional, steady laminar flow structures with mixing, chemical reaction, normal strain and shear strain representative of turbulent combustion are analysed. A mixing layer is subjected to counterflow in the transverse -directions providing the important practical interaction of shear-strain rate with normal-strain rate. Larger consequences for mixing rates and burning rates occur than would appear with shear strain or normal strain alone. The three characteristic times for chemical reaction, normal strain and shear strain are cast through two ratios: a Damkohler number based on rate of shear strain and a ratio of rate of normal strain to rate of shear strain. Reduction to a one-dimensional similar form is obtained with density and property variations. A generalization is found extending the Crocco integral for non-unitary Prandtl number and for imposed normal strain. A diffusion flamelet model with combined shear and normal strains is developed. Another similar solution is obtained for a configuration with a dominant diffusion flame and a weaker fuel-rich premixed flame. A conserved scalar is cast as the independent variable giving an alternative description. The imposed normal strain decreases mixing-layer thickness and increases scalar gradients and transport rates. Diffusion control is possible for partially premixed flames in the multi-branched flame situation. The imposition of shear strain and thereby vorticity on the counterflow can have a substantial consequence, indicating the need for flamelet models with both shear strain and normal strain.
Fundamental Thermal Noise Limits for Optical Microcavities

Noise from temperature fluctuations may limit the performance of small optical cavities in quantum computing applications.
Racial Disparities in COVID-19 and Excess Mortality in Minnesota

The coronavirus disease 2019 (COVID-19) pandemic has produced vastly disproportionate deaths for communities of color in the United States. Minnesota seemingly stands out as an exception to this national pattern, with white Minnesotans accounting for 80 percent of the population and 82 percent of COVID-19 deaths. The authors examine confirmed COVID-19 mortality alongside deaths indirectly attributable to the pandemic-"excess mortality"-in Minnesota. This analysis reveals profound racial disparities: age-adjusted excess mortality rates for whites are exceeded by a factor of 2.8 to 5.3 for all other racial groups, with the highest rates among Black, Latino, and Native Minnesotans. The seemingly small disparities in COVID-19 deaths in Minnesota reflect the interaction of three factors: the natural history of the disease, whose early toll was heavily concentrated in nursing homes; an exceptionally divergent age distribution in the state; and a greatly different proportion of excess mortality captured in confirmed COVID-19 rates for white Minnesotans compared with most other groups.
Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games

In this paper, zero-sum mean-field type games (ZSMFTG) with linear dynamics and quadratic utility are studied under infinite-horizon discounted utility function. ZSMFTG are a class of games in which two decision makers whose utilities sum to zero, compete to influence a large population of agents. In particular, the case in which the transition and utility functions depend on the state, the action of the controllers, and the mean of the state and the actions, is investigated. The game is analyzed and explicit expressions for the Nash equilibrium strategies are derived. Moreover, two policy optimization methods that rely on policy gradient are proposed for both model-based and sample-based frameworks. In the first case, the gradients are computed exactly using the model whereas they are estimated using Monte-Carlo simulations in the second case. Numerical experiments show the convergence of the two players’ controls as well as the utility function when the two algorithms are used in different scenarios.
On Boundedness and Growth of Unsteady Solutions Under the Double Porosity/Permeability Model

There is a recent surge in research activities on modeling the flow of fluids in porous media with complex pore-networks. A prominent mathematical model, which describes the flow of incompressible fluids in porous media with two dominant pore-networks allowing mass transfer across them, is the double porosity/permeability (DPP) model. However, we currently do not have a complete understanding of unsteady solutions under the DPP model. Also, because of the complex nature of the mathematical model, it is not possible to find analytical solutions, and one has to resort to numerical solutions. It is therefore desirable to have a procedure that can serve as a measure to assess the veracity of numerical solutions. In this paper, we establish that unsteady solutions under the transient DPP model are stable in the sense of Lyapunov. We also show that the unsteady solutions grow at most linear with time. These results not only have a theoretical value but also serve as valuable a posteriori measures to verify numerical solutions in the transient setting and under anisotropic medium properties, as analytical solutions are scarce for these scenarios under the DPP model.
Improving neural network predictions of material properties with limited data using transfer learning

We develop new transfer learning algorithms to accelerate prediction of material properties from ab initio simulations based on density functional theory (DFT). Transfer learning has been successfully utilized for data-efficient modeling in applications other than materials science, and it allows transferable representations learned from large datasets to be repurposed for learning new tasks even with small datasets. In the context of materials science, this opens the possibility to develop generalizable neural network models that can be repurposed on other materials, without the need of generating a large (computationally expensive) training set of materials properties. The proposed transfer learning algorithms are demonstrated on predicting the Gibbs free energy of light transition metal oxides.
Ensembling Low Precision Models for Binary Biomedical Image Segmentation

Segmentation of anatomical regions of interest such as vessels or small lesions in medical images is still a difficult problem that is often tackled with manual input by an ex-pert. One of the major challenges for this task is that the appearance of foreground (positive) regions can be similar to background (negative) regions. As a result, many automatic segmentation algorithms tend to exhibit asymmetric errors, typically producing more false positives than false negatives. In this paper, we aim to leverage this asymmetry and train a diverse ensemble of models with very high recall, while sacrificing their precision. Our core idea is straightforward: A diverse ensemble of low precision and high recall models are likely to make different false positive errors (classifying background as foreground in different parts of the image), but the true positives will tend to be consistent. Thus, in aggregate the false positive errors will cancel out, yielding high performance for the ensemble. Our strategy is general and can be applied with any segmentation model. In three different applications (carotid artery segmentation in a neck CT angiography, myocardium segmentation in a cardiovascular MRI and multiple sclerosis lesion segmentation in a brain MRI), we show how the proposed approach can significantly boost the performance of a baseline segmentation method.
Cryogenic microwave loss in epitaxial Al/GaAs/Al trilayers for superconducting circuits

Epitaxially grown superconductor/dielectric/superconductor trilayers have the potential to form high-performance superconducting quantum devices and may even allow scalable superconducting quantum computing with low-surface-area qubits such as the merged-element transmon. In this work, we measure the power-independent loss and two-level-state (TLS) loss of epitaxial, wafer-bonded, and substrate-removed Al/GaAs/Al trilayers by measuring lumped element superconducting microwave resonators at millikelvin temperatures and down to single-photon powers. The power-independent loss of the device is ( 4.8 ± 0.1 ) × 10 − 5, and the resonator-induced intrinsic TLS loss is ( 6.4 ± 0.2 ) × 10 − 5. Dielectric loss extraction is used to determine a lower bound of the intrinsic TLS loss of the trilayer of 7.2 × 10 − 5. The unusually high power-independent loss is attributed to GaAs’s intrinsic piezoelectricity.
Core‐collapse supernova enrichment in the core of the Virgo cluster

Using a deep (574 ks) Chandra observation of M87, the dominant galaxy of the nearby Virgo cluster, we present the best measurements to date of the radial distribution of metals in the central intracluster medium (ICM). Our measurements, made in 36 independent annuli with ∼250 000 counts each, extend out to a radius r∼ 40 kpc and show that the abundance profiles of Fe, Si, S, Ar, Ca, Ne, Mg and Ni are all centrally peaked. Interestingly, the abundance profiles of Si and S – which are measured robustly and to high precision – are even more centrally peaked than Fe, while the Si/S ratio is relatively flat. These measurements challenge the standard picture of chemical enrichment in galaxy clusters, wherein Type Ia supernovae (SN Ia) from an evolved stellar population are thought to dominate the central enrichment. The observed abundance patterns are most likely due to one or more of the following processes: continuing enrichment by winds of a stellar population pre-enriched by core-collapse supernova (SNCC) products; intermittent formation of massive stars in the central cooling core; early enrichment of the low-entropy gas. We also discuss other processes that might have contributed to the observed radial profiles, such as a stellar initial mass function that changes with radius; changes in the pre-enrichment of SNCC progenitors; and a diversity in the elemental yields of SN Ia. Although systematic uncertainties prevent us from measuring the O abundance robustly, indications are that it is about two times lower than predicted by the enrichment models.
BOARDS-R-US: RECONCEPTUALIZING CORPORATE BOARDS

State corporate law requires director services be provided by “natural persons.” This Article puts this obligation to scrutiny, and concludes that there are significant gains that could be realized by permitting firms (be they partnerships, corporations, or other business entities) to provide board services. We call these firms “board service providers” (BSPs). We argue that hiring a BSP to provide board services instead of a loose group of sole proprietorships will increase board accountability, both from markets and judicial supervision. The potential economies of scale and scope in the board services industry (including vertical integration of consultants and other board member support functions), as well as the benefits of risk pooling and talent allocation, mean that large professional director services firms may arise, and thereby create a market for corporate governance distinct from the market for corporate control. More transparency about board performance, including better pricing of governance by the market, as well as increased reputational assets at stake in board decisions, means improved corporate governance, all else being equal. But our goal in this Article is not necessarily to increase shareholder control over firms—we show how a firm providing board services could be used to increase managerial power as well. This shows the neutrality of our proposed reform, which can therefore be thought of as a reconceptualization of what a board is rather than a claim about the optimal locus of corporate power. * William D. Warren Distinguished Professor of Law, UCLA School of Law, and Professor of Law and Aaron Director Teaching Scholar, University of Chicago Law School, respectively. Thank you to workshop participants at the University of Chicago Law School and UCLA Law School for their helpful suggestions. Thank you to Jennifer Arlen, Peter Oh, Kelli Alces, . . . for their comments as
Sources of Real Exchange Rate Fluctuations: How Important are Nominal Shocks?

Abstract This paper investigates empirically and attempts to identify the sources of real exchange-rate fluctuations since the collapse of Bretton Woods. The paper's first two sections survey and extend earlier, nonstructural empirical work on this subject by Campbell and Clarida (1987), Meese and Rogoff (1988), and Cumby and Huizinga (1990). The paper's main contribution is to build and estimate a three-equation open macro model in the spirit of Dornbusch (1976) and Obstfeld (1985) and to identify the model's structural shocks to demand, supply, and money using the approach pioneered by Blanchard and Quah (1989). For two of the four countries we study, Germany and Japan, our structural estimates imply that monetary shocks to money supply as well as to the demand for real money balances explain a substantial amount of the variance of real exchange rates relative to the dollar. We find that demand shocks explain the majority of the variance in real exchange-rate fluctuations, while supply shocks explain very little. The model's estimated short-run dynamics are strikingly consistent with the predictions of the simple textbook Mundell-Fleming model.
Strict Liability for Individuals? The Impact of 3-D Printing on Products Liability Law

Although a relatively new technology, three-dimensional (“3-D”) printing has been pronounced an invention with “the potential to revolutionize the way we make almost everything.” As personal 3-D printing becomes more prevalent, the possibilities are truly endless, limited only by the users’ creativity. While this seemingly infinite potential is quite exciting, it also raises new legal questions: If individuals can 3-D print products, should they be held strictly liable for defective products that they manufacture and sell? And if not, what should be the scope of individual products liability? Drawing on the original rationale behind strict products liability, I explain that strict liability is not justified for individual sellers and manufacturers of defective 3-D printed products. Unlike commercial sellers, these individuals lack the expertise and resources to adequately inspect for and prevent defects in their products. Moreover, unlike their commercial counterparts, these individuals lack leverage over their buyers in price and warranty negotiations. Instead, I propose that these sellers should be afforded a “micro-seller” affirmative defense against a claim of strict products liability. Under this defense, the court will evaluate five factors to determine whether, in fairness, the seller should be subject to strict liability for the defective product. The micro-seller defense contemplates the modern marketplace of 3-D printed products and designs and addresses the policy inconsistencies resulting from personal 3-D printing. While it levels the legal landscape for sellers, the defense does not entirely eliminate recourse for consumers, who may still succeed on negligence or breach of warranty claims. 3-D printing offers immense opportunities for innovation and societal growth. In turn, the micro-seller affirmative defense strikes the balance between promoting such innovation and encouraging consumer safety.
The dark side of liquidity creation: Leverage and systemic risk

Abstract We consider a model in which the threat of bank liquidations by creditors as well as equity-based compensation incentives both discipline bankers, but with different consequences. Greater use of equity leads to lower ex-ante bank liquidity, whereas greater use of debt leads to a higher probability of inefficient bank liquidation. The bank's privately-optimal capital structure trades off these two costs. With uncertainty about aggregate risk, bank creditors learn from other banks’ liquidation decisions. Such inference can lead to contagious liquidations, some of which are inefficient; this is a negative externality that is ignored in privately-optimal bank capital structures. Thus, under plausible conditions, banks choose excessive leverage relative to the socially optimal level, providing a rationale for bank capital regulation. While a blanket regulatory forbearance policy can eliminate contagion, it also eliminates all market discipline. However, a regulator generating its own information about aggregate risk, rather than relying on market signals, can restore efficiency and market discipline by intervening selectively.
FURTHER EVIDENCE ON THE VALUE OF PROFESSIONAL INVESTMENT RESEARCH

This paper shall consider not only the potential for individual investors to exploit one of the major categories of professional investment advice to earn superior portfolio returns, but also will examine the actual return experiences of a representative sample of investors who were, in fact, observed to trade on such advice.
Market transparency, liquidity externalities, and institutional trading costs in corporate bonds

We develop a simple model of the effect of public transaction reporting on trade execution costs and test it using a sample of institutional trades in corporate bonds, before and after initiation of the TRACE reporting system. Trade execution costs fell approximately 50% for bonds eligible for TRACE transaction reporting, and 20% for bonds not eligible for TRACE reporting, suggesting the presence of a “liquidity externality.” The key results are robust to changes in variables, such as interest rate volatility and trading activity that might also affect execution costs. Market shares and the cost advantage to large dealers decreased post-TRACE. These results indicate that market design can have first-order effects, even for sophisticated institutional customers.
Can Civil Law Countries Get Good Institutions? Lessons from the History of Creditor Rights and Bond Markets in Brazil

Does a legal tradition adopted in the distant past constrain a country's ability to provide the protection that investors need for financial markets to develop? I look at the relationship between legal origin and the development of bond markets and find too much variation over time in bond market size, creditor protections, and court enforcement of bond contracts to assume that the adoption of a legal system constrains future financial development. I examine the evolution of bond markets in Brazil, a French civil law country, and provide preliminary results of similar variation for a small cross-section of countries.