cssi/SciSciGPT-SciSciNet huggingface dataset:
AN EXACT INTEGRATION SCHEME FOR RADIATIVE COOLING IN HYDRODYNAMICAL SIMULATIONS

A new scheme for incorporating radiative cooling in hydrodynamical codes is presented, centered around exact integration of the governing semidiscrete cooling equation. Using benchmark calculations based on the cooling downstream of a radiative shock, I demonstrate that the new scheme outperforms traditional explicit and implicit approaches in terms of accuracy, while remaining competitive in terms of execution speed.
Magnetic Catalysis: A Review

We give an overview of the magnetic catalysis phenomenon. In the framework of quantum field theory, magnetic catalysis is broadly defined as an enhancement of dynamical symmetry breaking by an external magnetic field. We start from a brief discussion of spontaneous symmetry breaking and the role of a magnetic field in its a dynamics. This is followed by a detailed presentation of the essential features of the phenomenon. In particular, we emphasize that the dimensional reduction plays a profound role in the pairing dynamics in a magnetic field. Using the general nature of underlying physics and its robustness with respect to interaction types and model content, we argue that magnetic catalysis is a universal and model-independent phenomenon. In support of this claim, we show how magnetic catalysis is realized in various models with short-range and long-range interactions. We argue that the general nature of the phenomenon implies a wide range of potential applications: from certain types of solid state systems to models in cosmology, particle and nuclear physics. We finish the review with general remarks about magnetic catalysis and an outlook for future research.
Effects of mathematical locality and number scaling on coordinate chart use

A stronger foundation for earlier work on the effects of number scaling, and local mathematics is described. Emphasis is placed on the effects of scaling on coordinate systems. Effects of scaling are represented by a scalar field, θ, that appears in gauge theories as a spin zero boson. Gauge theory considerations led to the concept of local mathematics, as expressed through the use of universes, ∪ x, as collections of local mathematical systems at each point, x, of a space time manifold, M. Both local and global coordinate charts are described. These map M into either local or global coordinate systems within a universe or between universes, respectively. The lifting of global expressions of nonlocal physical quantities, expressed by space and or time integrals or derivatives on M, to integrals or derivatives on coordinate systems, is described. The assumption of local mathematics and universes makes integrals and derivatives, on M or on global charts, meaningless. They acquire meaning only when mapped into a local universe. The effect of scaling, by including the effect of θ into the local maps, is described. The lack of experimental evidence for θ so far shows that the coupling constant of θ to matter fields must be very small compared to the fine structure constant. Also the gradient of θ must be very small in the local region of cosmological space and time occupied by us as observers. So far, there are no known restrictions on θ or its gradient in regions of space and/or time that are far away from our local region. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Minimal-Area Metrics on the Swiss Cross and Punctured Torus

The closed string theory minimal-area problem asks for the conformal metric of least area on a Riemann surface with the condition that all non-contractible closed curves have length greater than or equal to an arbitrary constant that can be set to one. Through every point in such a metric there is a geodesic that saturates the length condition, and the saturating geodesics in a given homotopy class form a band. The extremal metric is unknown when bands of geodesics cross, as it happens for surfaces of non-zero genus. We use recently proposed convex programs to numerically find the minimal-area metric on the square torus with a square boundary, for various sizes of the boundary. For large enough boundary the problem is equivalent to the “Swiss cross” challenge posed by Strebel. We find that the metric is positively curved in the two-band region and flat in the single-band regions. For small boundary the metric develops a third band of geodesics wrapping around it, and has both regions of positive and of negative curvature. This surface can be completed to provide the minimal-area metric on a once-punctured torus, representing a closed-string tadpole diagram.
Smooth hypersurface sections containing a given subscheme over a finite field

We use the "closed point sieve" to prove a variant of a Bertini theorem over finite fields. Specifically, given a smooth quasi-projective subscheme X of P^n of dimension m over F_q, and a closed subscheme Z in P^n such that Z intersect X is smooth of dimension l, we compute the fraction of homogeneous polynomials vanishing on Z that cut out a smooth subvariety of X. The fraction is positive if m>2l.
Synchronization of coupled optical microresonators

The phenomenon of synchronization occurs universally across the natural sciences and provides critical insight into the behaviour of coupled nonlinear dynamical systems. It also offers a powerful approach to robust frequency or temporal locking in diverse applications including communications, superconductors and photonics. Here, we report the experimental synchronization of two coupled soliton mode-locked chip-based frequency combs separated over distances of 20 m. We show that such a system obeys the universal Kuramoto model for synchronization and that the cavity solitons from the microresonators can be coherently combined, which overcomes the fundamental power limit of microresonator-based combs. This study could significantly expand the applications of microresonator combs, and with its capability for massive integration it offers a chip-based photonic platform for exploring complex nonlinear systems. Synchronization of two optical microresonator frequency combs coupled over distances larger than 20 metres is experimentally realized, opening up applications of microresonator combs and offering a chip-based photonic platform for exploring complex nonlinear systems.
A critical review of RHIC experimental results

The relativistic heavy-ion collider (RHIC) was constructed to achieve an asymptotic state of nuclear matter in heavy-ion collisions, a near-ideal gas of deconfined quarks and gluons denoted quark–gluon plasma or QGP. RHIC collisions are indeed very different from the hadronic processes observed at the Bevalac and AGS, but high-energy elementary-collision mechanisms are also non-hadronic. The two-component model (TCM) combines measured properties of elementary collisions with the Glauber eikonal model to provide an alternative asymptotic limit for A–A collisions. RHIC data have been interpreted to indicate formation of a strongly-coupled QGP (sQGP) or "perfect liquid". In this review, I consider the experimental evidence that seems to support such conclusions and alternative evidence that may conflict with those conclusions and suggest different interpretations.
Void growth in bcc metals simulated with molecular dynamics using the Finnis–Sinclair potential

The process of fracture in ductile metals involves the nucleation, growth, and linking of voids. This process takes place both at the low rates involved in typical engineering applications and at the high rates associated with dynamic fracture processes such as spallation. Here we study the growth of a void in a single crystal at high rates using molecular dynamics (MD) based on Finnis–Sinclair interatomic potentials for the body-centred cubic (bcc) metals V, Nb, Mo, Ta, and W. The use of the Finnis–Sinclair potential enables the study of plasticity associated with void growth at the atomic level at room temperature and strain rates from 109/s down to 106/s and systems as large as 128 million atoms. The atomistic systems are observed to undergo a transition from twinning at the higher end of this range to dislocation flow at the lower end. We analyse the simulations for the specific mechanisms of plasticity associated with void growth as dislocation loops are punched out to accommodate the growing void. W...
Semi-direct gauge mediation with the 4-1 model

We analyze a model of Semi-Direct Gauge Mediation in which the hidden sector is the 4-1 model and the messenger fields are charged under the U(1) gauge group. At tree level, the SUSY-breaking F-terms induce D-terms from which SUSY-split messenger masses arise. We calculate these masses by three complementary methods. Additionally, we compute the one-loop corrections to the masses. We consider this model both with and without a Fayet-Iliopoulos term for the hidden sector U(1). Finally, we write down a simple model of Minimal Gauge Mediation in which the only scale is dynamically generated.
The Exact Solution to Rank-1 L1-Norm TUCKER2 Decomposition

This letter studies the rank-1 L1-norm-based TUCKER2 (L1-TUCKER2) decomposition of 3-way tensors. First, we prove that the problem is formally NP-hard. Then, we derive the first two algorithms in the literature for its exact solution. Our algorithms are accompanied by formal complexity analysis. Finally, we conduct numerical studies to compare the performance of exact L1-TUCKER2 (proposed) with standard HOSVD, HOOI, GLRAM, PCA, L1-PCA, and TPCA-L1. In our numerical studies, L1-TUCKER2 outperforms (e.g., in tensor approximation) all the aforementioned counterparts when the processed data are outlier corrupted.
ON HYDRODYNAMIC MOTIONS IN DEAD ZONES

We investigate fluid motions near the midplane of vertically stratified accretion disks with highly resistive midplanes. In such disks, the magnetorotational instability drives turbulence in thin layers surrounding a resistive, stable dead zone. The turbulent layers in turn drive motions in the dead zone. We examine the properties of these motions using three-dimensional, stratified, local, shearing-box, non-ideal, magnetohydrodynamical simulations. Although the turbulence in the active zones provides a source of vorticity to the midplane, no evidence for coherent vortices is found in our simulations. It appears that this is because of strong vertical oscillations in the dead zone. By analyzing time series of azimuthally averaged flow quantities, we identify an axisymmetric wave mode particular to models with dead zones. This mode is reduced in amplitude, but not suppressed entirely, by changing the equation of state from isothermal to ideal. These waves are too low frequency to affect sedimentation of dust to the midplane, but may have significance for the gravitational stability of the resulting midplane dust layers.
Quantum speed limits under continuous quantum measurements

The pace of evolution of physical systems is fundamentally constrained by quantum speed limits (QSL), which have found broad applications in quantum science and technology. We consider the speed of evolution for quantum systems undergoing stochastic dynamics due to continuous measurements. It is shown that that there are trajectories for which standard QSL are violated, and we provide estimates for the range of velocities in an ensemble of realizations of continuous measurement records. We determine the dispersion of the speed of evolution and characterize the full statistics of single trajectories. By characterizing the dispersion of the Bures angle, we further show that continuous quantum measurements induce Brownian dynamics in Hilbert space.
THE INNER DYNAMICAL MASS ACROSS GALAXY MORPHOLOGY: A WEAK SCALING WITH TOTAL STELLAR MASS

We compile a sample of dispersion-supported and rotation-supported galaxies for which the dynamical mass enclosed at 500 pc can be measured. We find that this dynamical quantity increases only slowly with stellar mass () over ~9 decades in baryonic mass and ~3 in length scale, with a sudden upturn at the highest masses (M stars 1010 M ☉). This upturn occurs for the earliest types (S0 and Sa) of disk galaxies, and is consistent with the "extra" mass within 500 pc being predominantly stellar. This sudden change may be indicative of different bulge formation mechanisms between early- and late-type disks. We also compare the data to the results of recent galaxy formation simulations. These broadly track the observed trend, with some tendency to put too much mass in the inner 500 pc, depending on the details of each simulation.
Significance of Gravitational Nonlinearities on the Dynamics of Disk Galaxies

The discrepancy between the visible mass in galaxies or galaxy clusters, and that inferred from their dynamics is well known. The prevailing solution to this problem is dark matter. Here we show that a different approach, one that conforms to both the current Standard Model of Particle Physics and General Relativity, explains the recently observed tight correlation between the galactic baryonic mass and its observed acceleration. Using direct calculations based on General Relativity's Lagrangian, and parameter-free galactic models, we show that the nonlinear effects of General Relativity make baryonic matter alone sufficient to explain this observation.
Dot tracking methodology for background-oriented schlieren (BOS)

We propose a dot tracking methodology for processing background-oriented schlieren (BOS) images. The method improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32 × 32 pixels) and is robust to image noise. We also propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a “correlation correction”, whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy-driven turbulence rendered using ray-tracing simulations, and experimental images of flow in the exit plane of a converging–diverging nozzle. The results show that the improved spatial resolution results in a better accuracy of the tracking method compared to correlation-based methods in regions with sharp displacement gradients, and the correlation correction step reduces the noise floor of the measurement, resulting in a fourfold improvement in the dynamic range.
FORMING PLANETESIMALS BY GRAVITATIONAL INSTABILITY. I. THE ROLE OF THE RICHARDSON NUMBER IN TRIGGERING THE KELVIN-HELMHOLTZ INSTABILITY

Gravitational instability (GI) of a dust-rich layer at the midplane of a gaseous circumstellar disk is one proposed mechanism to form planetesimals, the building blocks of rocky planets and gas giant cores. Self-gravity competes against the Kelvin–Helmholtz instability (KHI): gradients in dust content drive a vertical shear which risks overturning the dusty subdisk and forestalling GI. To understand the conditions under which the disk can resist the KHI, we perform three-dimensional simulations of stratified subdisks in the limit that dust particles are small and aerodynamically well coupled to gas, thereby screening out the streaming instability and isolating the KHI. Each subdisk is assumed to have a vertical density profile given by a spatially constant Richardson number Ri. We vary Ri and the midplane dust-to-gas ratio μ0 and find that the critical Richardson number dividing KH-unstable from KH-stable flows is not unique; rather, Ricrit grows nearly linearly with μ0 for μ0 = 0.3–10. Plausibly, a linear dependence arises for μ0 � 1 because in this regime the radial Kepler shear replaces vertical buoyancy as the dominant stabilizing influence. Why this dependence should persist at μ0 > 1 is a new puzzle. The bulk (height-integrated) metallicity is uniquely determined by Ri and μ0. Only for disks of bulk solar metallicity is Ricrit ≈ 0.2, which is close to the classical value. Our empirical stability boundary is such that a dusty sublayer can gravitationally fragment and presumably spawn planetesimals if embedded within a solar metallicity gas disk ∼4× more massive than the minimum-mass solar nebula; or a minimum-mass disk having ∼3× solar metallicity; or some intermediate combination of these two possibilities. Gravitational instability seems possible without resorting to the streaming instability or to turbulent concentration of particles.
Environment-agnostic Multitask Learning for Natural Language Grounded Navigation

Recent research efforts enable study for natural language grounded navigation in photo-realistic environments, e.g., following natural language instructions or dialog . However, existing methods tend to overfit training data in seen environments and fail to generalize well in previously unseen environments. To close the gap between seen and unseen environments, we aim at learning a generalized navigation model from two novel perspectives: (1) we introduce a multitask navigation model that can be seamlessly trained on both Vision-Language Navigation (VLN) and Navigation from Dialog History (NDH) tasks, which benefits from richer natural language guidance and effectively transfers knowledge across tasks; (2) we propose to learn environment-agnostic representations for the navigation policy that are invariant among the environments seen during training, thus generalizing better on unseen environments. Extensive experiments show that environment-agnostic multitask learning significantly reduces the performance gap between seen and unseen environments, and the navigation agent trained so outperforms baselines on unseen environments by 16% (relative measure on success rate) on VLN and 120% (goal progress) on NDH. Our submission to the CVDN leaderboard establishes a new state-of-the-art for the NDH task on the holdout test set. Code is available at https://github.com/google-research/valan.
Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks

–We use a connection between compositional kernels and branching processes via Mehler’s formula to study deep neural networks. This new probabilistic insight provides us a novel perspective...
Prefusion spike protein stabilization through computational mutagenesis.

A novel severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2) has emerged as a human pathogen, causing global pandemic and resulting in over 400,000 deaths worldwide. The surface spike protein of SARS-CoV-2 mediates the process of coronavirus entry into human cells by binding angiotensin-converting enzyme 2 (ACE2). Due to the critical role in viral-host interaction and the exposure of spike protein, it has been a focus of most vaccines' developments. However, the structural and biochemical studies of the spike protein are challenging because it is thermodynamically metastable1 . Here, we develop a new pipeline that automatically identifies mutants that thermodynamically stabilize the spike protein. Our pipeline integrates bioinformatics analysis of conserved residues, motion dynamics from molecular dynamics simulations, and other structural analysis to identify residues that significantly contribute to the thermodynamic stability of the spike protein. We then utilize our previously developed protein design tool, Eris, to predict thermodynamically stabilizing mutations in proteins. We validate the ability of our pipeline to identify protein stabilization mutants through known prefusion spike protein mutants. We finally utilize the pipeline to identify new prefusion spike protein stabilization mutants. This article is protected by copyright. All rights reserved.
ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate

Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer variability across radiologists, thereby contributing to missed clinically significant cancers, overdiagnosed low-risk cancers, and frequent false positives. Interpretation of MRI could be greatly improved by providing radiologists with an answer key that clearly shows cancer locations on MRI. Registration of histopathology images from patients who had radical prostatectomy to pre-operative MRI allows such mapping of ground truth cancer labels onto MRI. However, traditional MRI-histopathology registration approaches are computationally expensive and require careful choices of the cost function and registration hyperparameters. This paper presents ProsRegNet, a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer. Our pipeline consists of image preprocessing, estimation of affine and deformable transformations by deep neural networks, and mapping cancer labels from histopathology images onto MRI using estimated transformations. We trained our neural network using MR and histopathology images of 99 patients from our internal cohort (Cohort 1) and evaluated its performance using 53 patients from three different cohorts (an additional 12 from Cohort 1 and 41 from two public cohorts). Results show that our deep learning pipeline has achieved more accurate registration results and is at least 20 times faster than a state-of-the-art registration algorithm. This important advance will provide radiologists with highly accurate prostate MRI answer keys, thereby facilitating improvements in the detection of prostate cancer on MRI. Our code is freely available at https://github.com/pimed//ProsRegNet.
Multi-Omics Characterization of Inflammatory Bowel Disease-Induced Hyperplasia/Dysplasia in the Rag2-/-/Il10-/- Mouse Model.

Epigenetic dysregulation is hypothesized to play a role in the observed association between inflammatory bowel disease (IBD) and colon tumor development. In the present work, DNA methylome, hydroxymethylome, and transcriptome analyses were conducted in proximal colon tissues harvested from the Helicobacter hepaticus (H. hepaticus)-infected murine model of IBD. Reduced representation bisulfite sequencing (RRBS) and oxidative RRBS (oxRRBS) analyses identified 1606 differentially methylated regions (DMR) and 3011 differentially hydroxymethylated regions (DhMR). These DMR/DhMR overlapped with genes that are associated with gastrointestinal disease, inflammatory disease, and cancer. RNA-seq revealed pronounced expression changes of a number of genes associated with inflammation and cancer. Several genes including Duox2, Tgm2, Cdhr5, and Hk2 exhibited changes in both DNA methylation/hydroxymethylation and gene expression levels. Overall, our results suggest that chronic inflammation triggers changes in methylation and hydroxymethylation patterns in the genome, altering the expression of key tumorigenesis genes and potentially contributing to the initiation of colorectal cancer.
SSUE: Simultaneous state and uncertainty estimation for dynamical systems

Parameters of the mathematical model describing many practical dynamical systems are prone to vary due to aging or renewal, wear and tear, as well as changes in environmental or service conditions. These variabilities will adversely affect the accuracy of state estimation. In this paper, we introduce SSUE: Simultaneous State and Uncertainty Estimation for quantifying parameter uncertainty while simultaneously estimating the internal state of a system. Our approach involves the development of a Bayesian framework that recursively updates the posterior joint density of the unknown state vector and parameter uncertainty. To execute the framework for practical implementation, we develop a computational algorithm based on maximum a posteriori estimation and the numerical Newton's method. Observability analysis is conducted for linear systems, and its relation with the consistency of the estimation of the uncertainty's location is unveiled. Additional simulation results are provided to demonstrate the effectiveness of the proposed SSUE approach.
On Weissler's conjecture on the Hamming cube I

Let $1\leq p \leq q <\infty$, and let $w \in \mathbb{C}$. Weissler conjectured that the Hermite operator $e^{w\Delta}$ is bounded as an operator from $L^{p}$ to $L^{q}$ on the Hamming cube $\{-1,1\}^{n}$ with the norm bound independent of $n$ if and only if \begin{align*} |p-2-e^{2w}(q-2)|\leq p-|e^{2w}|q. \end{align*} It was proved by Bonami (1970), Beckner (1975), and Weissler (1979) in all cases except $2<p\leq q <3$ and $3/2<p\leq q <2$, which stood open until now. The goal of this paper is to give a full proof of Weissler's conjecture in the case $p=q$. Several applications will be presented.
Exploring the potential of transfer learning for metamodels of heterogeneous material deformation.

Abstract From the nano-scale to the macro-scale, biological tissue is spatially heterogeneous. Even when tissue behavior is well understood, the exact subject specific spatial distribution of material properties is often unknown. And, when developing computational models of biological tissue, it is usually prohibitively computationally expensive to simulate every plausible spatial distribution of material properties for each problem of interest. Therefore, one of the major challenges in developing accurate computational models of biological tissue is capturing the potential effects of this spatial heterogeneity. Recently, machine learning based metamodels have gained popularity as a computationally tractable way to overcome this problem because they can make predictions based on a limited number of direct simulation runs. These metamodels are promising, but they often still require a high number of direct simulations to achieve an acceptable performance. Here we show that transfer learning, a strategy where knowledge gained while solving one problem is transferred to solving a different but related problem, can help overcome this limitation. Critically, transfer learning can be used to leverage both low-fidelity simulation data and simulation data that is the outcome of solving a different but related mechanical problem. In this paper, we extend Mechanical MNIST, our open source benchmark dataset of heterogeneous material undergoing large deformation, to include a selection of low-fidelity simulation results that require ≈ 2 − 4 orders of magnitude less CPU time to run. Then, we show that transferring the knowledge stored in metamodels trained on these low-fidelity simulation results can vastly improve the performance of metamodels used to predict the results of high-fidelity simulations. In the most dramatic examples, metamodels trained on 100 high fidelity simulations but pre-trained on 60,000 low-fidelity simulations achieves nearly the same test error as metamodels trained on 60,000 high-fidelity simulations (1 − 1.5% mean absolute percent error). In addition, we show that transfer learning is an effective method for leveraging data from different load cases, and for leveraging low-fidelity two-dimensional simulations to predict the outcomes of high-fidelity three-dimensional simulations. Looking forward, we anticipate that transfer learning will enable us to better capture the influence of tissue spatial heterogeneity on the mechanical behavior of biological materials across multiple different domains.
Making sense of algorithms: Relational perception of contact tracing and risk assessment during COVID-19

Governments and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment algorithms, whereby citize...
A transcriptomic taxonomy of Drosophila circadian neurons around the clock

Many different functions are regulated by circadian rhythms, including those orchestrated by discrete clock neurons within animal brains. To comprehensively characterize and assign cell identity to the 75 pairs of Drosophila circadian neurons, we optimized a single-cell RNA sequencing method and assayed clock neuron gene expression at different times of day. The data identify at least 17 clock neuron categories with striking spatial regulation of gene expression. Transcription factor regulation is prominent and likely contributes to the robust circadian oscillation of many transcripts, including those that encode cell-surface proteins previously shown to be important for cell recognition and synapse formation during development. The many other clock-regulated genes also constitute an important resource for future mechanistic and functional studies between clock neurons and/or for temporal signaling to circuits elsewhere in the fly brain.
A Fast Certificate for Power System Small-Signal Stability

Swing equations are an integral part of a large class of power system dynamical models used in rotor angle stability assessment. Despite intensive studies, some fundamental properties of lossy swing equations are still not fully understood. In this paper, we develop a sufficient condition for certifying the stability of equilibrium points (EPs) of these equations, and illustrate the effects of damping, inertia, and network topology on the stability properties of such EPs. The proposed certificate is suitable for real-time monitoring and fast stability assessment, as it is purely algebraic and can be evaluated in a parallel manner. Moreover, we provide a novel approach to quantitatively measure the degree of stability in power grids using the proposed certificate. Extensive computational experiments are conducted, demonstrating the practicality and effectiveness of the proposal.
Event-Triggered Distributed Inference

We study a setting where each agent in a network receives certain private signals generated by an unknown static state that belongs to a finite set of hypotheses. The agents are tasked with collectively identifying the true state. To solve this problem in a communication-efficient manner, we propose an event-triggered distributed learning algorithm that is based on the principle of diffusing low beliefs on each false hypothesis. Building on this principle, we design a trigger condition under which an agent broadcasts only those components of its belief vector that have adequate innovation, to only those neighbors that require such information. We establish that under standard assumptions, each agent learns the true state exponentially fast almost surely. We also identify sparse communication regimes where the inter-communication intervals grow unbounded, and yet, the asymptotic learning rate of our algorithm remains the same as when agents communicate at every time-step. We then establish, both in theory and via simulations, that our event-triggering strategy has the potential to significantly reduce information flow from uninformative agents to informative agents. Finally, we argue that, as far as only asymptotic learning is concerned, one can allow for arbitrarily sparse communication patterns.
The effect of competition on toxic pollution releases

We examine how competition affects toxic industrial releases, using five years of data from thousands of facilities across hundreds of industries. Our main result indicates that competition reduces toxic releases at the facility level. On average, each percentage-point reduction in the Herfindahl Index (HHI) results in a nearly two-percent reduction in a facility׳s toxic releases. At the same time, we find no evidence that competition increases aggregate pollution. Further analysis sheds some light on the mechanisms through which firms reduce pollution releases due to increased competition. In particular, we find suggestive evidence that this relationship is due to both reduced output and increases in abatement. We find no evidence that our result is driven by: consumer aversion to pollution, regulations changing with competition, or technologies introduced by new firms. Taken together, our results indicate that competition may be good, at least for public health in areas near polluting facilities, and fail to provide support for the hypothesis that competition leads to more socially undesirable behavior.
Tax uncertainty and retirement savings diversification

Abstract We investigate the optimal savings decisions for investors with access to pre-tax (traditional) and post-tax (Roth) versions of tax-advantaged retirement accounts. The model features a progressive tax schedule and uncertainty over future tax rates. Traditional accounts are valuable for hedging retirement account performance and managing current income near tax-bracket cutoffs, whereas Roth accounts allow investors to mitigate uncertainty over future tax schedules. The optimal asset location policy for most households involves diversifying between traditional and Roth vehicles. Contrary to conventional advice, the substantial economic benefits from Roth investments are not limited to investors with low current income.
Economic Policy Uncertainty in the United States and Europe: A Cointegration Test

Economic uncertainty is closely followed and analysed by businesses, policy makers and academic scholars because the world economies have now become very closely interconnected more than ever. This study is to examine a relationship between economic policy uncertainty between the United States and Europe. The results reveal a long-run equilibrium relationship (cointegration) in economic policy uncertainty between the United States and Europe. The findings provide evidence of the interconnectedness of economic conditions between the United State and Europe in line with the international transmission and spill-over literature.
The Origins of U.S. Total Factor Productivity Growth in the Golden Age

A consideration of TFP growth in the United States during the golden age (1948–1973) raises two related questions: on the one hand why was it so strong and on the other hand, why were TFP growth rates lower than they were during the Depression years (1929–1941)? A continuing downward trend in TFP growth within manufacturing, and its declining share after World War II, provide answers to the latter question. A persisting productivity windfall associated with the build out of the surface road infrastructure helps answer the former question. By adopting a longer historical perspective, we can move beyond understanding the golden age sui generis, and begin to see it instead as a period reflecting the persistence of trends and developments whose origins are to be found prior to the Second World War.
Revisiting Extraterritoriality after Al-Skeini: The ECHR and Its Lessons

Introduction 693 A. The Pertinence of Extraterritoriality 694 B. Context of the Judgments 695 C. Content of the Judgments 696 D. Issues Raised 699 E. Issues of Territoriality and Extraterritoriality 699 I. Relevant Convention Provisions 700 A. Article 56 ECHR 700 B. Article 1 ECHR 704 II. Historical Context of Territorial Provisions 706 A. Article 56: British Colonial Influence 706 B. Article 56 (Formerly 63) Drafting History 710 C. Article 1 Drafting History 717 D. Drafting History Summary 719 III. Jurisprudence 722 A. Early Case Law on Article 56 722 1. Article 56(1): “Territories for Whose International Relations . . . [the State Party] Is Responsible” 723 2. Articles 56(1) and 56(4): The Declaration Requirements ... 725 B. Early Case Law on Article 1 727 C. From Expansion to Bankovic: Two Steps Forward, One Step Back? 732 1. Retrenchment of Extraterritorial Application Under Drozd and Bankovic 733 D. Post-Bankovic Rebound in Extraterritorial Application ........ 736 E. Case Law Governing the Interaction Between Articles 1 and 56 739 1. Article 56 Attempts to Limit Article 1 739 2. Article 1 Attempts to Broaden Article 56: The Extraterritorial Absurdity Revealed 741 Conclusion 745
Social Comparisons in Ultimatum Bargaining

Experiments are used to examine the effects of social comparisons in ultimatum bargaining. We inform responders about the average offer before they decide whether to accept or reject their specific offer. This significantly increases offers and offer-specific rejection probabilities. For comparison, we consider another change in informational conditions: telling responders the total pie is $30—ex ante it was either $15 or $30—affects offers and rejection probabilities roughly as much. Our results are consistent with people’s dislike for deviations from the norm of equity but inconsistent with fairness theories, where people dislike income disparity between themselves and their referents.
All of This Has Happened before and All of This Will Happen Again: Innovation in Copyright Licensing

Claims that copyright licensing can substitute for fair use have a long history. This Article focuses on a new cycle of the copyright licensing debate, which has brought revised arguments in favor of universal copyright licensing. First, the new arrangements offered by large copyright owners often purport to sanction the large-scale creation of derivative works, rather than mere reproductions, which were the focus of earlier blanket licensing efforts. Second, the new licenses are often free. Rather than demanding royalties as in the past, copyright owners just want a piece of the action—along with the right to claim that unlicensed uses are infringing. In a world where licenses are readily and cheaply available, the argument will go, it is unfair not to get one. This development, copyright owners hope, will combat increasingly fair use–favorable case law. This Article describes three key examples of recent innovations in licensing-like arrangements in the noncommercial or formerly noncommercial spheres—Getty Images’ new free embedding of millions of its photos, YouTube’s Content ID, and Amazon’s Kindle Worlds—and discusses how uses of works under these arrangements differ from their unlicensed alternatives in ways both subtle and profound. These differences change the nature of the communications and communities at issue, illustrating why licensing can never substitute for transformative fair use even when licenses are routinely available. Ultimately, as courts have already recognized, the mere desire of copyright owners to extract value from a market—especially when they desire to extract it from third parties rather than licensees— should not affect the scope of fair use. 1. See Battlestar Galactica (NBC Universal Television 2004–2007; Universal Media Studios 2007–2009). © 2014 Rebecca Tushnet. † Professor of Law, Georgetown University. Thanks to Julie Cohen for helpful comments. 1447-1488_TUSHNET_FINAL.DOCX (DO NOT DELETE) 2/12/15 5:42 PM 1448 BERKELEY TECHNOLOGY LAW JOURNAL [Vol. 29:1447
When hubs forget, lie, and play favorites: Interpersonal network structure, information distortion, and organizational learning

The interpersonal network structure of an organization directly influences the diffusion and recombination of ideas and can thus facilitate or impede organizational learning. Most interpersonal networks have �hubs��individuals who have significantly more connections than does the average member. This raises important questions about how hubs influence organizational learning outcomes. Does the presence of hubs improve or impair performance? What happens if hubs forget or misrepresent information that is transmitted through the network? Using simulation models, we find that moderately hubby networks outperform both very hubby and democratic networks.? We also find that moderate amounts of information omission or misrepresentation can be surprisingly beneficial to performance, though the patterns of their effects are strikingly different.
Executive Opportunism, Presidential Signing Statements, and the Separation of Powers

Executive discretion over policy outcomes is an inevitable feature of our political system. However, in recent years, the President has sought to expand his discretion using a variety of controversial and legally questionable tactics. Through a series of simple separation of powers models, we study one such tactic, employed by both Democratic and Republicanpresidents: theuseof signing statements,whichpurport tohave status in the interpretation of statutory meaning. Our models also show that signing statements upset the constitutional vision of lawmaking and, in a wide range of cases, exacerbate legislative gridlock. We argue that courts should not legally credit signing statements; we conclude by discussing executive opportunism broadly.
Affine General Equilibrium Models

No-arbitrage models are extremely flexible modelling tools but often lack economic motivation. This paper describes an equilibrium consumption-based CAPM framework based on Epstein-Zin preferences, which produces analytic pricing formulas for stocks and bonds under the assumption that macro growth rates follow affine processes. This allows the construction of equilibrium pricing formulas while maintaining the same flexibility of state dynamics as in no-arbitrage models. In demonstrating the approach, the paper presents a model that incorporates inflation such that asset prices are nominal. The model takes advantage of the possibility of non-Gaussian shocks and model macroeconomic uncertainty as a jump-diffusion process. This leads to endogenous stock market crashes as stock prices drop to reflect a higher expected rate of return in response to sudden increases in risk. The nominal yield curve in this model has a positive slope if expected inflation growth negatively impacts real growth. This model also pr...
Accountability of Transnational NGOs: Aspirations vs. Practice

Nongovernmental organizations (NGOs) working across borders face increased accountability demands. Although many have proposed ways of changing accountability practices, the debate is rarely informed by leaders’ perspectives of how accountability is perceived and practiced across different organizational settings. In interviews with NGO leaders we find aspirations to make accountability more meaningful and integrated, in particular by listening more to stakeholders other than donors. However, these aspirations are rarely put in practice and leaders continue to highlight traditional means such as financial accounting. This gap is particularly pronounced for smaller organizations and reflects an increasingly competitive environment shaped by rating agencies and a focus on financial metrics. To move from aspirations to practice, NGOs have to be willing to share more meaningful information about their work and outcomes with stakeholders. Practicing transparency that empowers beneficiaries is central to effect...
The Aggression Amendments: Points of Consensus and Dissension

This paper encapsulates remarks made at the Annual Meeting of the American Society of International Law on a panel devoted to considering the new amendments to the ICC Statute adding the crime of aggression to the Court's subject matter jurisdiction. It addresses the interpretive understandings adopted at the Review Conference in Kampala Uganda vis-a-vis the definition of the crime, the negotiations surrounding the crime's jurisdictional regime, and lingering confusion over the way in which the ICC Statute's amendment provisions should apply to the codification of the crime of aggression. The paper argues that the plain language reading of Article 121(5) should govern the question of when states parties are "bound" by the amendments such that the Court can prosecute the crime when committed by their nationals or on their territories.
The Uncertain Value of Uncertainty: When Consumers Are Unwilling to Pay for What They Like

Do people have an irrational dislike for risk? People pay less for uncertain prospects than their worst possible outcomes, and researchers have proposed that this effect occurs because people stron...
The Marginal Product of Capital

Whether or not the marginal product of capital (MPK) differs across countries is a question that keeps coming up in discussions of comparative economic development and patterns of capital flows. Using easily accessible macroeconomic data we find that MPKs are remarkably similar across countries. Hence, there is no prima facie support for the view that international credit frictions play a major role in preventing capital flows from rich to poor countries. Lower capital ratios in these countries are instead attributable to lower endowments of complementary factors and lower efficiency, as well as to lower prices of output goods relative to capital. We also show that properly accounting for the share of income accruing to reproducible capital is critical to reach these conclusions. One implication of our findings is that increased aid flows to developing countries will not significantly increase these countries’ capital stocks and incomes. I. INTRODUCTION Is the world’s capital stock efficiently allocated across countries? If so, then all countries have roughly the same aggregate marginal product of capital (MPK). If not, the MPK will vary substantially from country to country. In the latter case, the world foregoes an opportunity to increase global GDP by reallocating capital from low to high MPK countries. The policy implications are far reaching. Given the enormous cross-country differences in observed capital-labor ratios (they vary by a factor of 100 in the data used in this paper) it may seem obvious that the MPK must vary dramatically as well. In this case we would have to conclude that there are important frictions in international capital markets that prevent an efficient cross-country allocation of capital. 1 However, as Lucas [1990] pointed out in his celebrated article, poor countries also have lower endowments of factors complementary with physical capital, such as human capital, and lower total
Federal Water Law and the 'Double Whammy': How the Bureau of Reclamation can Help the West Adapt to Drought and Climate Change

The water resources of the American West — especially the Southwest — are at risk from climate change, as an already arid region grows even drier, warmer, and prone to drought. The dual threat of drought and climate change is a particular challenge for the U.S. Bureau of Reclamation (USBR), which operates hundreds of federal water projects throughout the region. USBR has some authority to deal with these problems under the 2009 SECURE Water Act (for climate change) and the 1992 Drought Relief Act (for drought). This article considers USBR’s climate change and drought programs, examining both the authorities and the implementation. It concludes with recommendations on how USBR could better use the Drought Relief Act to help reduce the impacts of future water shortages.
Complexities of Hedging Mortgages

This article shows the challenges and complexities of hedging fixed rate mortgages. A survey of forecasts of brokers about the risks of mortgages shows many significant disagreements, especially for mortgage derivatives such as interest only strip securities.