cssi/SciSciGPT-SciSciNet huggingface dataset:
Transverse electric fields' effects in the Dark Energy Camera CCDs

Spurious electric fields transverse to the surface of thick CCDs displace the photo-generated charges, effectively modifying the pixel area and producing noticeable signals in astrometric and photometric measurements. We use data from the science verification period of the Dark Energy Survey (DES) to characterize these effects in the Dark Energy Camera (DECam) CCDs, where the transverse fields manifest as concentric rings (impurity gradients or ``tree rings'') and bright stripes near the boundaries of the detectors (``edge distortions'') with relative amplitudes of about 1% and 10%, respectively. Using flat-field images, we derive templates in the five DES photometric bands (grizY) for the tree rings and the edge distortions as a function of their position on each DECam detector. Comparison of the astrometric and photometric residuals confirms their nature as pixel-size variations. The templates are directly incorporated into the derivation of photometric and astrometric residuals. The results presented in these proceedings are a partial report of analysis performed before the workshop ``Precision Astronomy with Fully depleted CDDs'' at Brookhaven National Laboratory. Additional work is underway, and the final results and analysis will be published elsewhere (Plazas, Bernstein & Sheldon 2014, in prep.).
Possible Extension of the Chiral Perturbation Theory Program

After a brief discussion of how chiral dynamics has evolved from the “universal VA theory of weak interactions”, we present some evidence that symmetry breaking for the vector meson multiplet is not simpler than but rather analogous to that for the pseudoscalar multiplet. This provides a motivation for speculating on how to extend in a systematic way the chiral perturbation theory program to include vectors.
FAST RADIAL FLOWS IN TRANSITION DISK HOLES

Protoplanetary transition disks have large, mass-depleted central cavities, yet also deliver gas onto their host stars at rates comparable to disks without holes. The paradox of simultaneous transparency and accretion can be explained if gas flows inward at much higher radial speeds inside the cavity than outside the cavity, since surface density (and by extension optical depth) varies inversely with inflow velocity at fixed accretion rate. Radial speeds within the cavity might even have to approach free-fall values to explain the huge surface density contrasts inferred for transition disks. We identify observational diagnostics of fast radial inflow in channel maps made in optically thick spectral lines. Signatures include (1) twisted isophotes in maps made at low systemic velocities and (2) rotation of structures observed between maps made in high-velocity line wings. As a test case, we apply our new diagnostic tools to archival Atacama Large Millimeter Array data on the transition disk HD 142527 and uncover evidence for free-fall radial velocities inside its cavity. Although the observed kinematics are also consistent with a disk warp, the radial inflow scenario is preferred because it predicts low surface densities that appear consistent with recent observations of optically thin CO isotopologues in this disk. How material in the disk cavity sheds its angular momentum wholesale to fall freely onto the star is an unsolved problem; gravitational torques exerted by giant planets or brown dwarfs are briefly discussed as a candidate mechanism.
Bitwist 3–manifolds

Our earlier twisted-face-pairing construction showed how to modify an arbitrary orientation-reversing face-pairing on a faceted 3‐ball in a mechanical way so that the quotient is automatically a closed, orientable 3‐manifold. The modifications were, in fact, parametrized by a finite set of positive integers, arbitrarily chosen, one integer for each edge class of the original face-pairing. This allowed us to find very simple face-pairing descriptions of many, though presumably not all, 3‐manifolds. Here we show how to modify the construction to allow negative parameters, as well as positive parameters, in the twisted-face-pairing construction. We call the modified construction the bitwist construction. We prove that all closed connected orientable 3‐manifolds are bitwist manifolds. As with the twist construction, we analyze and describe the Heegaard splitting naturally associated with a bitwist description of a manifold. 57N10
Developing political-ecological theory: The need for many-task computing.

Models of political-ecological systems can inform policies for managing ecosystems that contain endangered species. To increase the credibility of these models, massive computation is needed to statistically estimate the model’s parameters, compute confidence intervals for these parameters, determine the model’s prediction error rate, and assess its sensitivity to parameter misspecification. To meet this statistical and computational challenge, this article delivers statistical algorithms and a method for constructing ecosystem management plans that are coded as distributed computing applications. These applications can run on cluster computers, the cloud, or a collection of in-house workstations. This downloadable code is used to address the challenge of conserving the East African cheetah (Acinonyx jubatus). This demonstration means that the new standard of credibility that any political-ecological model needs to meet is the one given herein.
Resolutions of standard modules over KLR algebras of type A

Khovanov-Lauda-Rouquier algebras $R_\theta$ of finite Lie type are affine quasihereditary with standard modules $\Delta(\pi)$ labeled by Kostant partitions $\pi$ of $\theta$. In type $A$, we construct explicit projective resolutions of standard modules $\Delta(\pi)$.
Assessment of Autism Zebrafish Mutant Models Using a High-Throughput Larval Phenotyping Platform.

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5, orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders.
Virtual Multi-view Fusion for 3D Semantic Segmentation

Semantic segmentation of 3D meshes is an important problem for 3D scene understanding. In this paper we revisit the classic multiview representation of 3D meshes and study several techniques that make them effective for 3D semantic segmentation of meshes. Given a 3D mesh reconstructed from RGBD sensors, our method effectively chooses different virtual views of the 3D mesh and renders multiple 2D channels for training an effective 2D semantic segmentation model. Features from multiple per view predictions are finally fused on 3D mesh vertices to predict mesh semantic segmentation labels. Using the large scale indoor 3D semantic segmentation benchmark of ScanNet, we show that our virtual views enable more effective training of 2D semantic segmentation networks than previous multiview approaches. When the 2D per pixel predictions are aggregated on 3D surfaces, our virtual multiview fusion method is able to achieve significantly better 3D semantic segmentation results compared to all prior multiview approaches and recent 3D convolution approaches.
Bayesian graph selection consistency under model misspecification.

Gaussian graphical models are a popular tool to learn the dependence structure in the form of a graph among variables of interest. Bayesian methods have gained in popularity in the last two decades due to their ability to simultaneously learn the covariance and the graph. There is a wide variety of model-based methods to learn the underlying graph assuming various forms of the graphical structure. Although for scalability of the Markov chain Monte Carlo algorithms, decomposability is commonly imposed on the graph space, its possible implication on the posterior distribution of the graph is not clear. An open problem in Bayesian decomposable structure learning is whether the posterior distribution is able to select a meaningful decomposable graph that is “close” to the true non-decomposable graph, when the dimension of the variables increases with the sample size. In this article, we explore specific conditions on the true precision matrix and the graph, which results in an affirmative answer to this question with a commonly used hyper-inverse Wishart prior on the covariance matrix and a suitable complexity prior on the graph space. In absence of structural sparsity assumptions, our strong selection consistency holds in a high-dimensional setting where $p=O(n^{\alpha })$ for $\alpha <1/3$. We show when the true graph is non-decomposable, the posterior distribution concentrates on a set of graphs that are minimal triangulations of the true graph.
Targeting transcriptional coregulator OCA-B/Pou2af1 blocks activated autoreactive T cells in the pancreas and type 1 diabetes

The transcriptional coregulator OCA-B promotes expression of T cell target genes in cases of repeated antigen exposure, a necessary feature of autoimmunity. We hypothesized that T cell-specific OCA-B deletion and pharmacologic OCA-B inhibition would protect mice from autoimmune diabetes. We developed an Ocab conditional allele and backcrossed it onto a diabetes-prone NOD/ShiLtJ strain background. T cell-specific OCA-B loss protected mice from spontaneous disease. Protection was associated with large reductions in islet CD8+ T cell receptor specificities associated with diabetes pathogenesis. CD4+ clones associated with diabetes were present but associated with anergic phenotypes. The protective effect of OCA-B loss was recapitulated using autoantigen-specific NY8.3 mice but diminished in monoclonal models specific to artificial or neoantigens. Rationally designed membrane-penetrating OCA-B peptide inhibitors normalized glucose levels and reduced T cell infiltration and proinflammatory cytokine expression in newly diabetic NOD mice. Together, the results indicate that OCA-B is a potent autoimmune regulator and a promising target for pharmacologic inhibition.
President’s Farewell Message: The Anthropocene, Earth Jurisprudence, and the Rights of Nature

A new paradigmatic shift in confronting the climactic endgame of the Anthropocene in Asia is in order. Scientific studies warned that Asia would become the epicentre of anthropogenic catastrophes and environmental disasters in the world. As the outgoing Asian Law and Society Association (ALSA) president, I wish to contribute to critical discussions on two issues: (1) Earth Jurisprudence and (2) the Rights of Nature. These legal concepts must be critically examined, discussed, and developed by socio-legal researchers and policy-makers in order to avert the impending crises of the Anthropocene in Asia. This report examines the recent development of a robust movement toward Earth Jurisprudence in multiple countries of Asia, the Americas, and the Pacific—that is, countries that have recently enshrined the concept of the Rights of Nature into their legal system through transforming nature into rights-bearing entities in order to protect them from harmful human activities. Failing any significant remedial measures, many Asian cities, shores, and coastlines, including the archipelagos of multiple island states in the Pacific Ocean and the Indian Ocean may soon disappear due to the many decades of egregious human activities of industrialized countries and the corporate world. A robust system of Earth Jurisprudence must be established, in which the Rights of Nature must be imbedded in the centre of legislative and constitutional discussions and deliberations.
TMEM41B Is a Pan-flavivirus Host Factor.

Flaviviruses pose a constant threat to human health. These RNA viruses are transmitted by the bite of infected mosquitoes and ticks and regularly cause outbreaks. To identify host factors required for flavivirus infection, we performed full-genome loss of function CRISPR-Cas9 screens. Based on these results, we focused our efforts on characterizing the roles that TMEM41B and VMP1 play in the virus replication cycle. Our mechanistic studies on TMEM41B revealed that all members of the Flaviviridae family that we tested require TMEM41B. We tested 12 additional virus families and found that SARS-CoV-2 of the Coronaviridae also required TMEM41B for infection. Remarkably, single nucleotide polymorphisms present at nearly 20% in East Asian populations reduce flavivirus infection. Based on our mechanistic studies, we propose that TMEM41B is recruited to flavivirus RNA replication complexes to facilitate membrane curvature, which creates a protected environment for viral genome replication.
Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning

This paper investigates the stochastic optimization problem focusing on developing scalable parallel algorithms for deep learning tasks. Our solution involves a reformation of the objective function for stochastic optimization in neural network models, along with a novel parallel computing strategy, coined the weighted aggregating stochastic gradient descent (WASGD). Following a theoretical analysis on the characteristics of the new objective function, WASGD introduces a decentralized weighted aggregating scheme based on the performance of local workers. Without any center variable, the new method automatically gauges the importance of local workers and accepts them by their contributions. Furthermore, we have developed an enhanced version of the method, WASGD+, by (1) implementing a designed sample order and (2) upgrading the weight evaluation function. To validate the new method, we benchmark our pipeline against several popular algorithms, including the state-of-the-art deep neural network classifier training techniques (e.g., elastic averaging SGD). Comprehensive validation studies have been conducted on four classic datasets: CIFAR-100, CIFAR-10, Fashion-MNIST, and MNIST. Subsequent results have firmly validated the superiority of the WASGD scheme in accelerating the training of deep architecture. Better still, the enhanced version, WASGD+, is shown to be a significant improvement over its prototype.
Mixed-norm $L_p$-estimates for non-stationary Stokes systems with singular VMO coefficients and applications

Abstract We prove the mixed-norm Sobolev estimates for solutions to both divergence and non-divergence form time-dependent Stokes systems with unbounded measurable coefficients having small mean oscillations with respect to the spatial variable in small cylinders. As a special case, our results imply Caccioppoli type inequalities for the Stokes systems with variable coefficients. A new ϵ-regularity criterion for Leray-Hopf weak solutions of Navier-Stokes equations is also obtained as a consequence of our regularity results, which in turn implies some borderline cases of the well-known Serrin's regularity criterion.
Behavioral response of insecticide-resistant mosquitoes against spatial repellent: A modified self-propelled particle model simulation.

Rapidly increasing pyrethroid insecticide resistance and changes in vector biting and resting behavior pose serious challenges in malaria control. Mosquito repellents, especially spatial repellents, have received much attention from industry. We attempted to simulate interactions between mosquitoes and repellents using a machine learning method, the Self-Propelled Particle (SPP) model, which we modified to include attractiveness/repellency effects. We simulated a random walk scenario and scenarios with insecticide susceptible/resistant mosquitoes against repellent alone and against repellent plus attractant (to mimic a human host). Simulation results indicated that without attractant/repellent, mosquitoes would fly anywhere in the cage at random. With attractant, all mosquitoes were attracted to the source of the odor by the end. With repellent, all insecticide-susceptible mosquitoes eventually moved to the corner of the cage farthest from the repellent release point, whereas, a high proportion of highly resistant mosquitoes might reach the attractant release point (the human) earlier in the simulation. At fixed concentration, a high proportion of mosquitoes could be able to reach the host when the relative repellency efficacy (compare to attractant efficacy) was 1. This result implies that repellent may not be sufficient against highly physiologically insecticide resistant mosquitoes, since very high concentrations of repellent are neither practically feasible nor cost-effective.
Determining the probability of hemiplasy in the presence of incomplete lineage sorting and introgression.

The incongruence of character states with phylogenetic relationships is often interpreted as evidence of convergent evolution. However, trait evolution along discordant gene trees can also generate these incongruences - a phenomenon known as hemiplasy. Classic comparative methods do not account for discordance, resulting in incorrect inferences about the number, timing, and direction of trait transitions. Biological sources of discordance include incomplete lineage sorting (ILS) and introgression, but only ILS has received theoretical consideration in the context of hemiplasy. Here, we present a model that shows introgression makes hemiplasy more likely, such that methods that account for ILS alone will be conservative. We also present a method and software (HeIST) for making statistical inferences about the probability of hemiplasy and homoplasy in large datasets that contain both ILS and introgression. We apply our methods to two empirical datasets, finding that hemiplasy is likely to contribute to the observed trait incongruences in both.
Processing of Crowdsourced Observations of Aircraft in a High Performance Computing Environment

As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards development. Both regulators and standards developing organizations have made extensive use of Monte Carlo collision risk analysis simulations using probabilistic models of aircraft flight. We've previously determined that the observations of manned aircraft by the OpenSkyNetwork, a community network of ground-based sensors, are appropriate to develop models of the low altitude environment. This works overviews the high performance computing workflow designed and deployed on the Lincoln Laboratory Supercomputing Center to process3.9 billion observations of aircraft. We then trained the aircraft models using more than 250,000 flighthours at 5,000 feet above ground level or below. A key feature of the workflow is that all the aircraft observations and supporting datasets are available as open source technologies or been released to the public domain.
Does the Disposition Effect Matter in Corporate Takeovers? Evidence from Institutional Investors of Target Companies

This paper examines whether one of the most important participants in the takeover market, the institutional investors of target companies, suffers from the disposition effect and, if so, how this selling bias influences the takeover outcomes. I report robust evidence that target institutional investors are reluctant to realize losses. This bias further allows their sunk cost to affect both the takeover price and the deal success. My results are explained by neither the undervalued targets nor the 52-week-high price effect. They are most pronounced among targets whose investors have a strong propensity to hold on to loser stocks.
The Effect of Fair Value versus Historical Cost Reporting Model on Analyst Forecast Accuracy

ABSTRACT: This paper examines how the reporting model for a firm's operating assets affects analyst forecast accuracy. We contrast U.K. and U.S. investment property firms having real estate as their primary operating asset, exploiting that U.K. (U.S.) firms report these assets at fair value (historical cost). We assess the accuracy of a balance-sheet-based forecast (net asset value, or NAV) and an income-statement-based forecast (earnings per share, or EPS). We predict and find higher NAV forecast accuracy for U.K. relative to U.S. firms, consistent with the fair value reporting model revealing private information that is incorporated into analysts' balance sheet forecasts. We find this difference is attenuated when the fair value and historical cost models are more likely to converge: during recessionary periods. Finally, we predict and find lower EPS forecast accuracy for U.K. firms when reporting under the full fair value model of IFRS, in which unrealized fair value gains and losses are included in ne...
Social protection in a crisis : Argentina's Plan Jefes y Jefas

This brief summarizes the results of a gender impact evaluation study, entitled Social protection in a crisis : Argentina's plan Jefes y Jefas, conducted between 2002 and 2003 in Argentina. The study observed the impact of Argentina's main social policy response to the severe economic crisis of 2002 on the individual level. It is clear that the eligibility criteria were not enforced. Large shares of the recipients were women. The program reduced unemployment by about 2.5 percentage points. The work requirement represented a positive opportunity cost for participants. The program had a small effect on the poverty rate and a somewhat larger effect on the incidence of extreme poverty. Funding for the study derived from the Government of Argentina.
Corporate uptake of the Sustainable Development Goals: Mere greenwashing or an advent of institutional change?

The United Nations’ Sustainable Development Goals (SDGs) are increasingly used by corporations for benchmarking and communicating their sustainability performance. The SDGs have several features that make them attractive for this purpose, including their universality, specificity and, in many cases, direct linkage with corporate outcomes. Corporations typically disclose their engagement strategies and outcomes voluntarily without the aid of standardized and externally verified reports. This creates a risk of corporations misusing the SDGs for “greenwashing” and “impact washing” their activities, for example through selective reporting of favorable information. Inaccurate and non-transparent disclosure can also introduce information asymmetries that distort decision-making by investors and other stakeholders. Increasing institutional change towards new measurement frameworks (such as GRI and SASB standards) and regulatory oversight to monitor disclosure (e.g., the EU’s Non-Financial Reporting Directive) is likely to improve transparency and reliability in sustainability reporting. This study critically examines the prospects of institutional changes that facilitate the integration, measurement, and reporting of corporate sustainability in general and the SDGs in particular. It also explores emerging innovations in corporate governance and regulation that seek to improve the integration of sustainability issues in corporations and financial markets.
Bagging Time Series Models

A common problem in out-of-sample prediction is that there are potentially many relevant predictors that individually have only weak explanatory power. We propose bootstrap aggregation of pre-test predictors (or bagging for short) as a means of constructing forecasts from multiple regression models with local-to-zero regression parameters and errors subject to possible serial correlation or conditional heteroskedasticity. Bagging is designed for situations in which the number of predictors (M) is moderately large relative to the sample size (T). We show how to implement bagging in the dynamic multiple regression model and provide asymptotic justification for the bagging predictor. A simulation study shows that bagging tends to produce large reductions in the out-of-sample prediction mean squared error and provides a useful alternative to forecasting from factor models when M is large, but much smaller than T. We also find that bagging indicators of real economic activity greatly redcues the prediction mean squared error of forecasts of U.S. CPI inflation at horizons of one month and one year.
Criminal Deterrence when There Are Offsetting Risks: Traffic Cameras. Vehicular Accidents. and Public Safety

Numerous cities have enacted electronic monitoring programs at traffic intersections in an effort to reduce the high number of vehicle accidents. The rationale is that the higher expected fines for running a red light will induce drivers to stop and lead to fewer cross-road collisions. However, the cameras also incentivize drivers to accept a greater accident risk from stopping. We evaluate the termination of a monitoring program via a voter referendum using 12 years of geocoded police accident data. We find that the cameras changed the composition of accidents but no evidence of a reduction in total accidents or injuries.
Behind the numbers: : Insights into large audit firm sampling policies

SYNOPSIS: Changes in the audit industry after the Sarbanes-Oxley Act, including mandatory audits of internal control over financial reporting and PCAOB oversight and inspection of audit work, have potentially changed the nature and extent of audit sampling in the largest accounting firms. However, little academic evidence exists on these firms' current audit sampling policies (Elder, Akresh, Glover, Higgs, and Liljegren 2013). As such, we administer an extensive, open-ended survey to the national office of the Big 4 and two other international accounting firms regarding their firm's audit sampling policies. We find variation among the largest auditing firms' policies in their use of statistical and nonstatistical sampling methods and in inputs used in the sampling applications that could result in different sample sizes. Sampling experts' internal reviews indicate that projecting and resolving identified misstatements is one of the biggest difficulties that audit engagement teams face when using sampling...
Murdering the Spirit: Racism, Rights, and Commerce

Patricia Williams' The Alchemy of Race and Rights: The Diary of a Law Professor, is an eloquent, profoundly original, and often brilliant collection of interdisciplinary essays and stories concerning the impact of racism and poverty on the human spirit; the historic and continuing role of law and legal institutions in defining, facilitating, and perpetuating those harms; and the possibilities and dangers imminent in the attempt to use law to effect a remedy for them. This is a book that we should celebrate: it reminds us that books are occasionally very, very important, that reading can be transformative, and that writing sometimes can be and should always strive to be a moral act of the highest order. In the first Part of this review, I will briefly discuss just three of the substantive and disciplinary accomplishments of this book, and then I will present two possible objections (and possible responses) to some of the implicit and explicit theses the book defends. It is my view, however, that the greatness of this book lies neither in its disciplinary breakthroughs nor in its explicit analysis of race and law. The book's importance and uniqueness is in what it shows about the nature of private racism, which Williams provocatively calls a form of "spirit-murder" – the generic "disregard for others whose lives qualitatively depend on our regard." Much of Williams' book is given over to rich personal depictions of both the nature of the act of spirit murder thus defined and, more importantly, perhaps, the nature of the injury its victims experience. Thus, in the second and major Part of this review, I will try to describe "spirit-murder," the depiction of which I take to be the heart of Williams' contribution to our modem understanding of race relations in this country. In the concluding Part, I will review the two possible legal paths toward compensating or correcting the multiple injuries of spirit-murder that Williams describes. The first, toward which Williams is deeply ambivalent, consists in the related worlds of commerce and contract. If spirit-murder is, in its legal sense, that injury that results from being the "object" rather than the subject of property, contract, and commerce – a legal "disregard" felt most dramatically by the slave – then inclusion as subjects rather than objects in the world of commerce might be thought an adequate remedy. The promise, however, that the injuries sustained from the legacy of slavery would be eradicated simply through the legally mandated inclusion of African Americans in this country's commerce has turned out to be at least somewhat illusory. Consequently, both commerce and the law of commercial relations play a pivotal but deeply ambiguous role in Williams' book. The second route of recovery, about which Williams is less equivocal and far more hopeful, is through an expansive and avowedly utopian conception of rights.
Erie’s Suppressed Premise

Some originalists believe that interpreting the Constitution with fidelity means following the Framers’ specific intent—that is, deciding constitutional questions as the Framers themselves would have if asked.1 For example, the death penalty cannot be judged to be cruel and unusual—and so contrary to the Eighth Amendment—unless the Framers would have said that the death penalty is cruel and unusual. But what if the Framers did not want judges to follow their specific intent?2 What if they wanted their intent to be followed only in the general sense that a judge interpreting the Eighth Amendment should do her best to identify what actually is cruel and unusual, whatever the Framers might have thought
Effective Hourly Rates of Contingency-Fee Lawyers: Competing Data and Non-Competitive Fees

One of the foremost civil justice issues commanding attention at both federal and state levels is reform of the tort system. Central to the ongoing tort reform debate is data cited by both proponents and opponents in support of their respective positions. No set of data more critically informs the debate than the yields realized by lawyers engaged in contingent-feefinanced tort claiming. Most cited as authoritative is a set of data indicating that the yields of contingent-fee claiming approximate the returns realized by hourly rate lawyers. This data—central to contentions that tort reform efforts are not only unnecessary but also counterproductive in that they would deny claimants access to justice—is unreliable and invalid. More reliable data, which I present, demonstrates that the yields from contingency-fee practice have become inordinately high; indeed, they have increased enormously in recent decades, often amounting today to thousands of dollars an hour. In theory, these yields implicate ethical rules purporting to limit fees to “reasonable” amounts. In fact, “reasonable fee” rules are
Quality heterogeneity and global economic growth

Abstract This paper develops a fully endogenous, variety-expansion growth model with firm-specific quality heterogeneity, limit pricing, and an endogenous distribution of markups. Firms with high-quality products engage in exporting, firms with intermediate-quality products serve the domestic market, and inefficient firms with low-quality products exit the market. Trade liberalization, measured by a reduction in trade costs or a decline in foreign market entry costs, generates a reallocation of resources from low-quality to high-quality products and exit of inefficient firms. However, it has ambiguous effects on the average global quality level, long-run growth, and welfare. An increase in the rate of population growth or in the intensity of trade-related knowledge spillovers accelerates economic growth. The laissez-faire equilibrium is inefficient, and this leaves room for welfare-improving government intervention.
Path dependence in aggregate output

This paper studies an economy in which incomplete markets and strong complementarities interact to generate path dependent aggregate output fluctuations. An economy is said to be path dependent when the effect of a shock on the level of aggregate output is permanent in the absence of future offsetting shocks. We analyze the evolution of an economy which consists of a countable infinity of industries. The production functions of individual firms in each industry are nonconvex and are linked through localized technological complementarities. The productivity of each firm at t is determined by the production decisions of technologically similar industries at t — 1. No markets exist which allow firms and industries to exploit complementarities by coordinating production decisions. This market incompleteness produces several interesting effects on aggregate output behavior. First, multiple stochastic equilibria exist in aggregate activity. These equilibria are distinguished by differences in both the mean and the variance of output. Second, output movements are path dependent as aggregate productivity shocks indefinitely affect real activity by shifting the economy across equilibria. Third, when aggregate shocks are recurrent, the economy cycles between periods of boom and depression. Simulations of example economies illustrate how v market incompleteness can produce rich aggregate dynamics.
Dynamic Factors and the Source of Momentum Profits

This article uses the dynamic principal component method to estimate a dynamic factor model for stock returns and identify the source of momentum profits. We find that momentum is a systematic-return phenomenon—momentum profits are due primarily to stock return response to a small number of dynamic systematic factors, and the contribution by the idiosyncratic component of stock return is statistically insignificant. We also find that the estimated dynamic factors can be partially related to observed economic factors.
Environmental Regulations and Corruption: Automobile Emissions in Mexico City

Emission regulations become more prevalent in developing countries, but they may be compromised by corruption. This paper documents the prevalence of corruption and the effectiveness of vehicle emission regulations in Mexico City. I develop a statistical test for identifying a specific type of cheating that involves bribing center technicians. I also estimate a structural model of car owner retesting and cheating decisions. Results suggest that 9.6 percent of car owners paid US$20 to circumvent the regulation. Eliminating cheating and increasing the cost of retests would reduce emissions by 3,708 tons at a high cost for vehicle owners.
The impact of network size on bank branch performance

Abstract Despite significant technological innovation in retail banking services delivery, the number of US bank branches has grown steadily over time. Further, more and more of these branches are held by banks with large branch networks. This paper assesses the implications of these developments by examining measures of branch performance and asking how these measure vary across institutions with different branch network sizes. Our findings suggest that banks with mid-sized branch networks may be at a competitive disadvantage in branching activities. We find no systematic relationship between branch network size and overall institutional profitability, perhaps because banking organizations optimize the size of their branch network operations as part of an overall strategy involving both branch-based and non-branch-based activities.
Stock options for undiversified executives

Abstract We employ a certainty-equivalence framework to analyze the cost, value and pay/performance sensitivity of non-tradable options held by undiversified, risk-averse executives. We derive “executive value” lines, the risk-adjusted analogues to Black–Scholes lines. We show that distinguishing between “executive value” and “company cost” provides insight into many issues regarding stock option practice including: executive views about Black–Scholes values; tradeoffs between options, restricted stock and cash; exercise price policies; option repricings; early exercise policies and decisions; and the length of vesting periods. It also leads to reinterpretations of both cross-sectional facts and longitudinal trends in the level of executive compensation.
Value versus Growth: Time-Varying Expected Stock Returns

Is the value premium predictable? We study time variations of the expected value premium using a two-state Markov switching model. We find that when conditional volatilities are high, the expected excess returns of value stocks are more sensitive to aggregate economic conditions than the expected excess returns of growth stocks. As a result, the expected value premium is time varying. It spikes upward in the high volatility state, only to decline more gradually in the subsequent periods. However, out-of-sample predictability of the value premium is close to nonexistent.
Do Endometrial Natural Killer and Regulatory T Cells Differ in Infertile and Clinical Pregnancy Patients? An Analysis in Patients Undergoing Frozen Embryo Transfer Cycles

Problem Clinical significance of endometrial and peripheral blood natural killer (NK) and regulatory T cells (Tregs) during frozen embryo transfer (FET) cycles has not been well characterized. Design Retrospective cohort study METHOD OF STUDY: Endometrial tissue was collected from infertility patients prior to a frozen embryo transfer cycle as part of an endometrial receptivity analysis (ERA® ) biopsy or endometrial scratch test. Uterine NK (uNK) and Treg cell density was compared based on pregnancy status in the subsequent frozen embryo transfer cycle. Peripheral blood was also collected from a separate cohort of patients undergoing frozen embryo transfer. Treg cell density was compared by the presence or the absence of a clinical pregnancy in each phase of the cycle. Results In the 33 luteal phase biopsies there were more endometrial Tregs, similar uNK and a trend toward lower CD16+ uNK cells in women with a future ongoing clinical pregnancy compared to non-pregnant women. There were no differences in uNK and Treg density in natural scratch cycles vs programmed cycles or in non-receptive vs receptive endometrium (ERA® cycles). In the peripheral blood analysis, the pregnant group had higher peripheral blood Tregs on the day of serum β-hCG time point when compared to the non-pregnant group. Conclusion Higher levels of endometrial Tregs and lower levels of CD16+ uNK cells are positive prognostic factors for infertile women prior to frozen embryo transfer. Our work on phenotypic and proportional analyses of endometrial immune cells may complement the ERA® in predicting improved pregnancy rates in patients with implantation failure.
Data Science as Political Action: Grounding Data Science in a Politics of Justice

In response to increasing public scrutiny and awareness of the social harms associated with data-driven algorithms, the field of data science has rushed to adopt ethics training and principles. Such efforts, however, are ill-equipped to address broad matters of social justice. Instead of a narrow vision of ethics grounded in vague principles and professional codes of conduct, I argue, the field must embrace politics (by which I mean not simply debates about specific political parties and candidates but more broadly the collective social processes that influence rights, status, and resources across society). Data scientists must recognize themselves as political actors engaged in normative constructions of society and, as befits political practice, evaluate their work according to its downstream impacts on people’s lives. I justify this notion in two parts: first, by articulating why data scientists must recognize themselves as political actors, and second, by describing how the field can evolve toward a deliberative and rigorous grounding in a politics of social justice. Part 1 responds to three arguments that are commonly invoked by data scientists when they are challenged to take political positions regarding their work: “I’m just an engineer,” “Our job isn’t to take political stances,” and “We should not let the perfect be the enemy of the good.” In confronting these arguments, I articulate how attempting to remain apolitical is itself a political stance — a fundamentally conservative one (in the sense of maintaining the status quo rather than in relation to any specific political party or movement) — and why the field’s current attempts to promote “social good” dangerously rely on vague and unarticulated political assumptions. Part 2 proposes a framework for what a politically engaged data science could look like and how to achieve it. Recognizing the challenge of reforming the field of data science in this manner, I conceptualize the process of incorporating politics into data science as following a sequence of four stages: becoming interested in directly addressing social issues, recognizing the politics underlying these issues, redirecting existing methods toward new applications that challenge oppression, and developing practices and methods for working with communities as productive partners in movements for social justice. The path ahead does not require data scientists to abandon their technical expertise, but does require them to expand their notions of what problems to work on and how to engage with social issues.
Why Has Regional Income Convergence in the U.S. Declined

The past thirty years have seen a dramatic decrease in the rate of income convergence across states and in population flows to wealthy places. These changes coincide with (1) an increase in housing prices in productive areas, (2) a divergence in the skill-specific real returns to living in productive places, (3) a redirection of low-skilled migration and (4) diminished human capital convergence due to migration. We develop a model where falling housing supply elasticity and endogenous labor mobility generates these patterns. Using a new panel measure of housing supply regulations, we demonstrate the importance of this channel. Income convergence continues in less-regulated places, while it has stopped in more-regulated places.
On Portraying Human Dignity

This article considers what, if anything, the use of Velazquez’s painting Las Meninas contributes to understanding of the conception of human dignity, drawing on several of Velazquez’s other paintings, including Juan de Pareja, The Buffoon Sebastian de Morra, El bufon Calabacillas, and Francisco Lezcano (El Nino de Vallecas). The work of Avishai Margalit, Emmanuel Levinas, and Hans Joas is drawn on to provide a theoretical structure for this endeavor. More broadly, I continue a conversation in the legal academy on how far resort to art forms such as literature and painting may help us understand problematic concepts in law and moral philosophy.
Living Wage Effects: New and Improved Evidence

This article explores the effects of living wages on low-wage workers and low-income families. First, earlier analyses are updated using data for 1996 through 2002, and a number of criticisms of those analyses are addressed. This article confirms earlier findings that business-assistance living wage laws boost wages of the lowest wage workers at the cost of some disemployment, ultimately reducing net urban poverty. Second, this article expands the analysis of distributional effects beyond the poverty threshold. It was not found that living wage laws increase the depth of poverty among families that remain poor; on the other hand, families somewhat below and somewhat above the poverty line are helped. Finally, this article suggests that the poverty reductions generated by living wages may stem from income gains for individuals with higher wages or skills who are nonetheless in poor families rather than for individuals with the lowest wages or skills.
Pricing American Options: A Duality Approach

We develop a new method for pricing American options. The main practical contribution of this paper is a general algorithm for constructing upper and lower bounds on the true price of the option using any approximation to the option price. We show that our bounds are tight, so that if the initial approximation is close to the true price of the option, the bounds are also guaranteed to be close. We also explicitly characterize the worst-case performance of the pricing bounds. The computation of the lower bound is straightforward and relies on simulating the suboptimal exercise strategy implied by the approximate option price. The upper bound is also computed using Monte Carlo simulation. This is made feasible by the representation of the American option price as a solution of a properly defined dual minimization problem, which is the main theoretical result of this paper. Our algorithm proves to be accurate on a set of sample problems where we price call options on the maximum and the geometric mean of a collection of stocks. These numerical results suggest that our pricing method can be successfully applied to problems of practical interest.
Abolish Anonymous Reporting to Child Abuse Hotlines

All states allow the public to anonymously report suspicions of child abuse or neglect to a toll free central phone number. An extensive examination of the policy and practices behind anonymous reporting hotlines indicates that they are widely unregulated and susceptible to abuse. The possible repercussions of an anonymous phone call create costs to the family and society which do not outweigh the potential benefit of allowing anonymous public reports. Under the guise of protecting children, the law has developed in such a way that it infringes on the fundamental rights of parents and children. At the same time, anonymous reporting overburdens the system, causing us to overlook some child maltreatment that can be, and is otherwise, addressed through confidential and mandatory reporting. Given the severity of the rights and lives at stake, it is time to abolish anonymous public reporting of suspected child maltreatment.
A Replication and Analysis of Tiebout Competition Using an Agent-Based Computational Model

Replication is a critical element of the scientific process. This article is an effort to contribute to the slowly growing literature concerning the replication of agent-based computational models. We present a replication of Kollman, Miller, and Page's model of Tiebout sorting. In that model, individual agents with heterogeneous preferences for government policies select among jurisdictions that offer the most satisfactory package of government services. This project makes three contributions to the literature. First, our successful replication provides the research community with a modernized version of that seminal model. Second, we confirm that earlier results with respect to the single jurisdiction setting are highly robust with respect to voter preferences, while the results for multiple jurisdiction settings are more sensitive. Finally, we demonstrate a technique for conducting sensitivity analyses that leverages a high-dimensional experimental design.