cssi/SciSciGPT-SciSciNet huggingface dataset:
Bank Runs and Banking Policies: Lessons for African Policymakers

Although banking crises in Asia and Latin America have grabbed the headlines, the banking systems of many African countries have been under stress for years. Table 1 documents and Figures 1A and 1B map problems observed during 1980-1996 across the continent as a whole. The sources from which the table was compiled report that banking problems were experienced in 50 of the continent’s 56 countries. Many of these problems proved long-lasting and 10 countries experienced additional rounds of banking weakness. Figure 2 shows that the number of countries experiencing banking distress has trended upward over time. Figure 3 plots a frequency distribution for the duration of banking distress in individual countries. Table 2 partly updates Table 1. It summarizes information gleaned from interviews with informed sources and information on major banking failures reported since 1995 on the Lexis-Nexis database for five selected sub-Saharan countries: Kenya, Nigeria, Uganda, Zambia, and Zimbabwe. Lexis-Nexis descriptions of when and why a bank fails focus on directly
Hope a Better Rate for Me

Ratemaking, the dreariest legal expression of the dismal science, is sexy again. Once upon a time, judicially enforced constitutional restraints on the setting of public utility rates strengthened the intellectual backbone of the Lochner era. Contemporary interest in this doctrine stems from the imposition of "the duty to interconnect, to lease unbundled network elements, and to sell services for resale" on incumbent firms in the few remaining "market segments that have natural monopoly characteristics." The Federal Communications Commission's contribution to this great legal transformation, its embattled total element long-run incremental cost rule (TELRIC), will in all likelihood be reviewed under some variant of the confiscatory ratemaking doctrine. So controversial is TELRIC that it has inspired a literature on "deregulatory takings" and a counter-literature denying the entire phenomenon.On this occasion, I do not wish so much to re-engage this debate as to entertain the combatants. I therefore offer the following anthem for our deregulatory age, a ballad "dedicated to the [law] I love." Sing along, all you who debate the notion of deregulatory takings, "And we'll have memories for company / Long after the songs are sung."
Diffusion of online reverse auctions for B2B procurement: an exploratory study

Purpose – To investigate the diffusion of online reverse auctions by exploring differences between their early, late and lagging adopters. More specifically, adopter categories are compared against organizational characteristics and auction behavior as a result of learning. Organizational characteristics include number of employees and purchasing authority structure (PAS). Differences in learning are investigated by behavioral manifestations, consisting of the savings achieved, as well as the use of bundles in reverse auctions.Design/methodology/approach – Four hypotheses were developed based on academic and trade literature. Data were collected with a large‐scale online survey among members of the Institute for Supply Management, receiving 363 complete and useable responses. Records were split into three adopter categories based on whether the respondent's firm adopted reverse auctions early (before April 2002) or late (after April 2002), or whether the adoption was merely planned. Differences related to...
The Decline of Investment Banking: Preliminary Thoughts on the Evolution of the Industry 1996-2008

In this paper, I provide a basic, preliminary financial analysis of several prominent, independent investment banks: Goldman Sachs, Morgan Stanley, Merrill Lynch, Lehman Brothers, and Bear Stearns. I provide the following data: (1) segmentation of net revenue by products and services, (2) return on average equity, (3) leverage ratio, and (4) debt to equity ratio. Although the data analysis here is very basic, it still tells an interesting narrative of the evolution of the investment banking industry. The investment banking industry has undergone significant change in the twelve-year period 1996 to 2008. In the mid-1990s, banks had a balance mix of the three major product lines: trading, asset management, and investment banking. In the past few years, trading has become the primary business activity of major investment banks. It has overshadowed the other two major products and services of full service firms, investment banking and asset management. In essence, the executives at these firms made “bet the company” type decisions through heavy reliance on trading and increased leverage to boost profitability. This is a new phenomenon. In fact investment banks had changed their business models. In hindsight, with a collapse of the housing and credit bubbles, pure investment banks were especially vulnerable in a way that they were not only a few years ago.
Sheaves of categories and the notion of 1-affineness

We define the notion of 1-affineness for a prestack, and prove an array of results that establish 1-affineness of certain types of prestacks.
Judicial capacity and the conditional spending paradox

This Article examines the spending power and anti-commandeering principle through the lens of the author's judicial capacity model of Supreme Court decision-making. Taking the Court's recent decision in NFIB v. Sebelius as a jumping off point, this examination yields three important payoffs: First, it helps to explain the Court's historically broad interpretation of the spending power. Second, it refutes the conventional wisdom that this broad interpretation cannot be reconciled with the anti-commandeering principle -- a view the Article dubs the "conditional spending paradox." Third, it offers a rigorous theoretical basis for predicting that NFIB's spending power holding will be short-lived. This account obviously has significant implications for the spending power and anti-commandeering doctrine. It also contributes to a broader understanding of the influence of judicial capacity on the substance of constitutional law.
Theft, Gift-Giving, and Trustworthiness: Honesty Is Its Own Reward in Rural Paraguay

In developing countries lacking legal enforcement, villagers may use implicit contracts to minimize crime. I construct a dynamic limited-commitment model, in which a thief cannot commit to forego stealing, but is induced to steal less by the promise of future gifts. Combining survey data on production, theft, gifts, and trust with experiments measuring trustworthiness, I provide supporting evidence. Farmers living near more relatives or with plots that are difficult to steal from give fewer gifts and trust more, and those living near more relatives also experience less theft. Giving increases when trust is lower and the threat of theft is greater.
Labor Market Uncertainty and Private Sector Labor Supply in Russia

Abstract : The development of a vibrant private sector has been one of the key failures of the transitional period in Russia. This paper develops a theoretical and empirical model of individual labor supply behavior under uncertainty, and estimates this model using data from the Russian Longitudinal Monitoring Survey for the years 1994 - 1996 & 1998. As hypothesized, a decrease in private sector earnings variability is estimated to increase the likelihood of private sector employment for individuals with constrained consumption smoothing ability. Evidence of ex-ante intra-household risk sharing is also found with individuals reducing their exposure to uncertainty by diversifying the portfolio of jobs held by their household.
Choice Inconsistencies Among the Elderly: Evidence from Plan Choice in the Medicare Part D Program.

We explore the in- and out-of-sample robustness of tests for choice inconsistencies based on parameter restrictions in parametric models, focusing on tests proposed by Ketcham, Kuminoff, and Powers (2016). We argue that their nonparametric alternatives are inherently conservative with respect to detecting mistakes. We then show that our parametric model is robust to KKP's suggested specification checks, and that comprehensive goodness of fit measures perform better with our model than the expected utility model.Finally, we explore the robustness of our 2011 results to alternative normative assumptions highlighting the role of brand fixed effects and unobservable characteristics.
Exponential stabilization of a smart piezoelectric composite beam with only one boundary controller

Abstract Layered smart composite beams involving a piezoelectric layer are traditionally actuated by a voltage source by the extension mechanism. In this paper, we consider only the bending and shear of a cantilevered piezoelectric smart composite beam modeled by the Mead-Marcus sandwich beam assumptions. Uniform exponential stabilitization with only one boundary state feedback controller, simultaneously controlling both bending moment and shear, is proved by using a spectral multiplier approach. The state feedback controller slightly differs from the classical counterparts by a non-trivial compact and nonnegative integral operator. This is due to the strong coupling of the charge equation with the stretching and bending equations. For simulations, the so-called filtered semi-discrete finite difference method is adopted.
BCL::MP‐fold: Membrane protein structure prediction guided by EPR restraints

For many membrane proteins, the determination of their topology remains a challenge for methods like X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. Electron paramagnetic resonance (EPR) spectroscopy has evolved as an alternative technique to study structure and dynamics of membrane proteins. The present study demonstrates the feasibility of membrane protein topology determination using limited EPR distance and accessibility measurements. The BCL::MP-Fold (BioChemical Library membrane protein fold) algorithm assembles secondary structure elements (SSEs) in the membrane using a Monte Carlo Metropolis (MCM) approach. Sampled models are evaluated using knowledge-based potential functions and agreement with the EPR data and a knowledge-based energy function. Twenty-nine membrane proteins of up to 696 residues are used to test the algorithm. The RMSD100 value of the most accurate model is better than 8 A for 27, better than 6 A for 22, and better than 4 A for 15 of the 29 proteins, demonstrating the algorithms' ability to sample the native topology. The average enrichment could be improved from 1.3 to 2.5, showing the improved discrimination power by using EPR data.
The international rule of law and the domestic analogy

A surge in academic interest in the interaction of international law with international politics has recently raised the profile of the rule of law in global politics. The idea of an ‘international rule of law’ is central to many accounts of international order, and to both political science and legal scholarship. Despite its popularity, the concept is rarely defined or examined. This article considers the theory and practice of the international rule of law. It shows first that the international rule of law cannot be deduced from the conventional Anglo-American version of the rule of law in domestic legal theory, as sketched by Joseph Raz and others. It then considers two competing versions of a distinctly international concept of the rule of law, one based on a positivist theory of compliance and the other on a structurationist theory of practice. The former is more common in legal and political scholarship but the latter accounts better for the political power of international law in relation to states.
High dimensional dynamic stochastic copula models

Abstract We build a class of copula models that captures time-varying dependence across large panels of financial assets. Our models nest Gaussian, Student’s t , grouped Student’s t , and generalized hyperbolic copulas with time-varying correlations matrices, as special cases. We introduce time-variation into the densities by writing them as factor models with stochastic loadings. The proposed copula models have flexible dynamics and heavy tails yet remain tractable in high dimensions due to their factor structure. Our Bayesian estimation approach leverages a recent advance in sequential Monte Carlo methods known as particle Gibbs sampling which can draw large blocks of latent variables efficiently and in parallel. We use this framework to model an unbalanced, 200-dimensional panel consisting of credit default swaps and equities for 100 US corporations. Our analysis shows that the grouped Student’s t stochastic copula is preferred over seven competing models.
High short interest effect and aggregate volatility risk

Abstract We propose a risk-based firm-type explanation on why stocks of firms with high relative short interest (RSI) have lower future returns. We argue that these firms have negative alphas because they are a hedge against expected aggregate volatility risk. Consistent with this argument, we show that these firms have high firm-specific uncertainty and option-like equity, and the aggregate volatility risk factor can largely explain the high RSI effect. The key mechanism is that high RSI firms have abundant growth options and, all else equal, growth options become less sensitive to the underlying asset value and more valuable as idiosyncratic volatility goes up. Idiosyncratic volatility usually increases with aggregate volatility (i.e., in recessions).
Rough Waters For The Ratings Companies: Should The Securities Ratings Companies Be Held Liable For Investor Reliance In The Wake Of The Real Estate Meltdown Of 2007-2008?

In the wake of the Real Estate market meltdown and the "Great Recession" that followed, this note focuses on whether securities ratings companies, such as Standard & Poor’s, Fitch, and Moody’s, should be held liable to the investors of residential mortgage backed securities (also referred to as “RMBS”). These investors relied on the ratings only to have the value of those securities decrease significantly due to real estate market downturn and subsequent re-rating of those securities by the ratings companies. The focus of this analysis will be on the liability of the securities ratings companies under both contract and tort theories. Specifically, the potential liability will be analyzed under the doctrine of promissory estoppel in contracts and under an extension of negligence and products liability theories in torts.
The effect of supplier industry competition on pay-for-performance incentive intensity

Abstract We examine how supplier industry competition affects CEO incentive intensity in procuring firms. Using Bureau of Economic Analysis data to compute a weighted supplier industry competition measure, we predict and find that higher supplier competition is associated with stronger CEO pay-for-performance incentive intensity. This effect is incremental to that of the firm's own industry competition previously documented and is robust to alternative measures of supplier competition and to exogenous shocks to competition. Importantly, we show that performance risk and product margin act as mediating variables in the relation between supplier competition and CEO incentive intensity providing support for the theory underpinning our finding. We document that CEO compensation contracts are used as a mechanism to exploit the market dynamics of upstream industries to a firm's benefit. Our findings are economically important as suppliers provide, on average, 45 percent of the value delivered by procuring firms to the market (BEA, 2016).
Nonstationary Gauss-Markov Processes: Parameter Estimation and Dispersion

This paper provides a precise error analysis for the maximum likelihood estimate $\hat {\textit a}_{\text {ML}}({\textit u}_{1}^{\textit n})$ of the parameter ${\textit a}$ given samples ${\textit u}_{1}^{\textit n} = ({\textit u}_{1}, \ldots, {\textit u}_{\textit n})'$ drawn from a nonstationary Gauss-Markov process ${\textit U}_{\textit i} = {\textit a} {\textit U}_{\textit i-1} + {\textit Z}_{\textit i},\,\,{\textit i}\geq 1$ , where ${\textit U}_{0} = 0$ , ${\textit a}> 1$ , and ${\textit Z}_{\textit i}$ ’s are independent Gaussian random variables with zero mean and variance $\sigma ^{2}$ . We show a tight nonasymptotic exponentially decaying bound on the tail probability of the estimation error. Unlike previous works, our bound is tight already for a sample size of the order of hundreds. We apply the new estimation bound to find the dispersion for lossy compression of nonstationary Gauss-Markov sources. We show that the dispersion is given by the same integral formula that we derived previously for the asymptotically stationary Gauss-Markov sources, i.e., $|{\textit a}| . New ideas in the nonstationary case include separately bounding the maximum eigenvalue (which scales exponentially) and the other eigenvalues (which are bounded by constants that depend only on a) of the covariance matrix of the source sequence, and new techniques in the derivation of our estimation error bound.
Generalized Pose-and-Scale Estimation using 4-Point Congruence Constraints

We present gP4Pc, a new method for computing the absolute pose of a generalized camera with unknown internal scale from four corresponding 3D point-and-ray pairs. Unlike most pose-and-scale methods, gP4Pc is based on constraints arising from the congruence of shapes defined by two sets of four points related by an unknown similarity transformation. By choosing a novel parametrization for the problem, we derive a system of four quadratic equations in four scalar variables. The variables represent the distances of 3D points along the rays from the camera centers. After solving this system via Grobner basis-based automatic polynomial solvers, we compute the similarity transformation using an efficient 3D point-point alignment method. We also propose a specialized variant of our solver for the case of coplanar points, which is computationally very efficient and about $ 3\times$ faster than the fastest existing solver. Our experiments on real and synthetic datasets, demonstrate that gP4Pc is among the fastest methods in terms of total running time when used within a RANSAC framework, while achieving competitive numerical stability, accuracy, and robustness to noise.
A Theory of Assurance: Balancing Costly Formal Control with Tone at the Top

Informal tone at the top (TATT) is widely regarded as a fundamental ingredient of organizational control, yet because of its soft nature, the scholarship on TATT has not emphasized mathematical mod...
Visual Navigation Among Humans With Optimal Control as a Supervisor

Real world visual navigation requires robots to operate in unfamiliar, human-occupied dynamic environments. Navigation around humans is especially difficult because it requires anticipating their future motion, which can be quite challenging. We propose an approach that combines learning-based perception with model-based optimal control to navigate among humans based only on monocular, first-person RGB images. Our approach is enabled by our novel data-generation tool, HumANav, that allows for photorealistic renderings of indoor environment scenes with humans in them, which are then used to train the perception module entirely in simulation. Through simulations and experiments on a mobile robot, we demonstrate that the learned navigation policies can anticipate and react to humans without explicitly predicting future human motion, generalize to previously unseen environments and human behaviors, and transfer directly from simulation to reality. Videos describing our approach and experiments, as well as a demo of HumANav are available on the project website. 1
Optimal Taxation of Families: Mirrlees Meets Becker

This paper studies the optimal taxation of families in an environment in which (i) potential parents differ by their labor productivity and child-bearing preference, which are only observable by the family, and (ii) child-rearing requires both goods and parental time. Potential parents simultaneously decide how much labor to exert and how many children to have. The government uses information on family income and size to construct an optimal tax system through the combination of an income tax schedule and child tax credits. I observe that parental time and the cost of goods involved in child-rearing have distinct impacts on the shape of optimal child tax credits. As a quantitative analysis, I calibrate my model to US data and show that childrearing costs translate into a pattern of optimal credits that is U-shaped in income. In particular, tax credits decrease along the first nine deciles of the income distribution and increase thereafter. In addition, tax credits decrease according to family size because of the economies of scale in child-rearing. For median-income families, the credit for the second child equals 71% of the credit for the first child. I also find that implementing the optimum yields large welfare gains.
Coarse Grained Parallel Selection

Several efficient, but non-optimal, solutions to the Selection Problem on coarse grained parallel computers have appeared in the literature. We consider the example of the Saukas-Song algorithm; we...
Magnetic charge's relaxation propelled electricity in two-dimensional magnetic honeycomb lattice

Summary Emerging new concepts, such as magnetic charge dynamics in two-dimensional magnetic material, can provide novel mechanism for spin based electrical transport at macroscopic length. In artificial spin ice of single domain elements, magnetic charge's relaxation can create an efficient electrical pathway for conduction by generating fluctuations in local magnetic field that couple with conduction electrons spins. In a first demonstration, we show that the electrical conductivity is propelled by more than an order of magnitude at room temperature due to magnetic charge defects sub-picosecond relaxation in artificial magnetic honeycomb lattice. The direct evidence to the proposed electrical conduction mechanism in two-dimensional frustrated magnet points to the untapped potential for spintronic applications in this system.
Representativeness in Statistics, Politics, and Machine Learning

Representativeness is a foundational yet slippery concept. Though familiar at first blush, it lacks a single precise meaning. Instead, meanings range from typical or characteristic, to a proportionate match between sample and population, to a more general sense of accuracy, generalizability, coverage, or inclusiveness. Moreover, the concept has long been contested. In statistics, debates about the merits and methods of selecting a representative sample date back to the late 19th century; in politics, debates about the value of likeness as a logic of political representation are older still. Today, as the concept crops up in the study of fairness and accountability in machine learning, we need to carefully consider the term's meanings in order to communicate clearly and account for their normative implications. In this paper, we ask what representativeness means, how it is mobilized socially, and what values and ideals it communicates or confronts. We trace the concept's history in statistics and discuss normative tensions concerning its relationship to likeness, exclusion, authority, and aspiration. We draw on these analyses to think through how representativeness is used in FAccT debates, with emphasis on data, shift, participation, and power.
Methodological Variation in Empirical Corporate Finance

I document large variation in empirical methodology in corporate finance regressions in top finance journals. Although methodological variation allows for customization of empirical tests to fit specific theories, it can also enable excessive reporting of statistically significant results. For example, given discretion over ten routine methodological decisions, a researcher could report that over 70% of randomly generated variables are statistically significant determinants of leverage at the 5% level. The methodological decisions that impact statistical significance the most are dependent variable selection, variable transformation, and outlier treatment. I discuss remedies that can mitigate the negative effects of methodological variation.
The X-ray spectrum of 3C 273

An X-ray spectral measurement of the quasar 3C 273 with the HEAO-A2 experiment in June/July 1978 is reported. The best power law fit to the photon flux over the range 2-60 keV gives a slope of 1.41 + or - 0.02. However, structure is observed, indicating a slope of 1.52 between 2 keV and 9 keV and a slight flattening between 9 keV and 30 keV. Observations with the same experiment in December 1977 and OSO-8 in June 1976 allows confirmation of 40% intensity variability on the time scale of months, although within limits provided by the poorer statistical quality of the additional data no spectral change is discerned. Absorption from the source is found to be low, with the 1978 data yielding a 90% confidence upper limit to the hydrogen column density of 4.5 x 10 to the 21st power atoms/sq cm.
First Exit-Time Analysis for an Approximate Barndorff-Nielsen and Shephard Model with Stationary Self-Decomposable Variance Process

In this paper, an approximate version of the Barndorff-Nielsen and Shephard model, driven by a Brownian motion and a L\'evy subordinator, is formulated. The first-exit time of the log-return process for this model is analyzed. It is shown that with certain probability, the first-exit time process of the log-return is decomposable into the sum of the first exit time of the Brownian motion with drift, and the first exit time of a L\'evy subordinator with drift. Subsequently, the probability density functions of the first exit time of some specific L\'evy subordinators, connected to stationary, self-decomposable variance processes, are studied. Analytical expressions of the probability density function of the first-exit time of three such L\'evy subordinators are obtained in terms of various special functions. The results are implemented to empirical S&P 500 dataset.
GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural Networks.

Machine Learning as a Service (MLaaS) is enabling a wide range of smart applications on end devices. However, privacy-preserved computation is still expensive. Our investigation has found that the most time-consuming component of the HE-based linear computation is a series of Permutation (Perm) operations that are imperative for dot product and convolution in privacy-preserved MLaaS. To this end, we propose GALA: Greedy computAtion for Linear Algebra in privacy-preserved neural networks, which views the HE-based linear computation as a series of Homomorphic Add, Mult and Perm operations and chooses the least expensive operation in each linear computation step to reduce the overall cost. GALA makes the following contributions: (1) It introduces a row-wise weight matrix encoding and combines the share generation that is needed for the GC-based nonlinear computation, to reduce the Perm operations for the dot product; (2) It designs a first-Add-second-Perm approach (named kernel grouping) to reduce Perm operations for convolution. As such, GALA efficiently reduces the cost for the HE-based linear computation, which is a critical building block in almost all of the recent frameworks for privacy-preserved neural networks, including GAZELLE (Usenix Security'18), DELPHI (Usenix Security'20), and CrypTFlow2 (CCS'20). With its deep optimization of the HE-based linear computation, GALA can be a plug-and-play module integrated into these systems to further boost their efficiency. Our experiments show that it achieves a significant speedup up to 700x for the dot product and 14x for the convolution computation under different data dimensions. Meanwhile, GALA demonstrates an encouraging runtime boost by 2.5x, 2.7x, 3.2x, 8.3x, 7.7x, and 7.5x over GAZELLE and 6.5x, 6x, 5.7x, 4.5x, 4.2x, and 4.1x over CrypTFlow2, on AlexNet, VGG, ResNet-18, ResNet-50, ResNet-101, and ResNet-152, respectively.
Short Simplex Paths in Lattice Polytopes

The goal of this paper is to design a simplex algorithm for linear programs on lattice polytopes that traces “short” simplex paths from any given vertex to an optimal one. We consider a lattice polytope P contained in $$[0,k]^n$$ and defined via m linear inequalities. Our first contribution is a simplex algorithm that reaches an optimal vertex by tracing a path along the edges of P of length in $$O(n^{4} k\, \hbox {log}\, k).$$ The length of this path is independent from m and it is the best possible up to a polynomial function. In fact, it is only polynomially far from the worst-case diameter, which roughly grows as nk. Motivated by the fact that most known lattice polytopes are defined via $$0,\pm 1$$ constraint matrices, our second contribution is a more sophisticated simplex algorithm which exploits the largest absolute value $$\alpha $$ of the entries in the constraint matrix. We show that the length of the simplex path generated by this algorithm is in $$O(n^2k\, \hbox {log}\, ({nk} \alpha ))$$ . In particular, if $$\alpha $$ is bounded by a polynomial in n, k, then the length of the simplex path is in $$O(n^2k\, \hbox {log}\, (nk))$$ . For both algorithms, if P is “well described”, then the number of arithmetic operations needed to compute the next vertex in the path is polynomial in n, m, and $$\hbox {log}\, k$$ . If k is polynomially bounded in n and m, the algorithm runs in strongly polynomial time.
Online Allocation and Pricing: Constant Regret via Bellman Inequalities

We develop a framework for designing simple and efficient policies for a family of online allocation and pricing problems that includes online packing, budget-constrained probing, dynamic pricing, ...
Medical Malpractice and Vestibular Schwannomas: A Nationwide Review.

Objective Most surgeons face litigation related to the care of their patients, with specialties including neurosurgery facing a particularly high risk. Diagnosis and management of vestibular schwannomas can be challenging, potentially giving rise to medicolegal proceedings. Accordingly, a full appreciation of the medicolegal implications of treating these challenging tumors is warranted. Methods A systematic search of the Westlaw Edge legal database was conducted to identify all cases of medicolegal proceedings related to the management of vestibular schwannomas. All cases identified by the search were screened in full, and relevant cases included for analysis. Variables pertaining to the nature of the case and legal outcomes were extracted. Results A total of 38 cases were included in this analysis from 11 U.S. states. Failure to diagnose and negligent surgery were the most common allegations. Neurosurgeons were the most frequently implicated specialists followed by otolaryngologists and radiologists. A verdict was reached in 30 cases, with the jury finding in favor of the defendant(s) in most cases (n = 26, 87.0%), a proportion that increased across each decade of the study period. Damages were paid out in 11 cases, with a mean value of $1,534,446. Mean value of damages paid in verdicts in favor of the plaintiff were larger than those in settlements ($2,116,543 and $1,385,457, respectively). Conclusions The data presented provide a comprehensive overview of medicolegal proceedings related to the management of vestibular schwannomas. This study provides clinicians with a greater appreciation of the medicolegal implications of treating vestibular schwannomas.
Valley relaxation of resident electrons and holes in a monolayer semiconductor: Dependence on carrier density and the role of substrate-induced disorder

Analogous to the keen interest in electron, hole, and exciton spin relaxation during the early days of semiconductor spintronics, measurements of valley relaxation in monolayer transition-metal dichalcogenide (TMD) semiconductors such as WSe2 are currently a focus of attention for potential applications in valleytronics. For many notional valleytronic devices, the important parameter is the intrinsic valley relaxation time of the resident electrons and holes that exist in n-type and p-type TMD monolayers. Using optical methods, the authors determine these timescales as a systematic function of carrier density, and study the (important) role of the underlying substrate. Microsecond-long valley relaxation of carriers is revealed at low densities.
Empirical Policy Evaluation With Supergraphs

We devise algorithms for the policy evaluation problem in reinforcement learning, assuming access to a simulator and certain side information called the supergraph . Our algorithms explore backward from high-cost states to find high-value ones, in contrast to approaches that work forward from all states. While several papers have demonstrated the utility of backward exploration empirically, we conduct rigorous analyses which show that our algorithms can reduce average-case sample complexity from $O(S \log S)$ to as low as $O(\log S)$ . Analytically, we adapt tools from the network science literature to provide a new methodology for reinforcement learning problems.
Compensation disclosures and strategic commitment: Evidence from revenue-based pay

Abstract A 2006 rule change in the United States mandated that publicly traded firms provide more detailed disclosures about executives’ compensation plans. In response to the new disclosure requirements, Cournot firms with large market shares add revenue-based pay to their CEOs’ pay packages. This change in pay practices coincides with a shift towards more aggressive product market equilibria, characterized by greater production expenditures and lower margins. Jointly, these patterns are consistent with predictions from the theory of “strategic delegation,” and suggest that the new disclosure requirements enhanced the viability of committing through executive incentives. After adopting the new disclosure requirements, many firms appear to restructure their executives’ pay packages as strategic devices designed to make rivals curtail their competitive actions.
Post-Acquisition Harassment and the Scope of the Fair Housing Act

Because Halprin v. Prairie Single Family Homes of Dearborn Park Ass’n creates a split of circuit authority and threatens established civil rights protections, the Seventh Circuit’s decision provides a useful opportunity to reconsider the proper scope of the FHA. The subject of housing harassment, in general, has received significant scholarly attention in the recent past; however, no commentator has focused on the concept of post-acquisition harassment or evaluated the validity of the underlying assumption that the FHA does, in fact, protect against harassment occurring after housing has been secured. With the current schism in federal case law as a backdrop, and with incidents of violence, intimidation, and harassment targeting minorities in housing continuing today, this Article reconsiders the concept of housing discrimination and inquires whether there are solid legal and policy justifications to continue protecting post-acquisition harassment under the FHA.Part II briefly reviews several restrictive judicial interpretations of the FHA’s scope, putting the Seventh Circuit’s Halprin decision in context. Part III then analyzes various arguments set forth by the Halprin court to limit the scope of the FHA. This analysis also tracks the basic framework used by the Supreme Court in its analysis of the FHA in Trafficante v. Metropolitan Life Insurance Co., focusing on the text of the FHA, underlying congressional intent, and the applicability of Title VII to an interpretation of the FHA. Finally, Part IV considers two policy-based arguments bearing on whether the FHA should be read expansively to include a post-transaction dimension. Included in this discussion is a brief treatment of the role that post-acquisition harassment has played in the creation and maintenance of residential segregation. Ultimately, I reject the limiting arguments of the Seventh Circuit and conclude that the FHA is properly interpreted as encompassing claims not only of pre-access discrimination but also of harassment occurring after occupation begins.
A Receding Horizon Scheduling Approach for Search & Rescue Scenarios

Abstract Many applications involving complex multi-task problems such as disaster relief, logistics and manufacturing necessitate the deployment and coordination of heterogeneous multi-agent systems due to the sheer number of tasks that must be executed simultaneously. A fundamental requirement for the successful coordination of such systems is leveraging the specialization of each agent within the team. This work presents a Receding Horizon Planning (RHP) framework aimed at scheduling tasks for heterogeneous multi-agent teams in a robust manner. In order to allow for the modular addition and removal of different types of agents to the team, the proposed framework accounts for the capabilities that each agent exhibits (e.g. quadrotors are agile and agnostic to rough terrain but are not suited to transport heavy payloads). An instantiation of the proposed RHP is developed and tested for a search and rescue scenario. Moreover, we present an abstracted search and rescue simulation environment, where a heterogeneous team of agents is deployed to simultaneously explore the environment, find and rescue trapped victims, and extinguish spreading fires as quickly as possible. We validate the effectiveness of our approach through extensive simulations comparing the presented framework with various planning horizons to a greedy task allocation scheme.
Additive conjugacy and the Bohr compactification of orthogonal representations

We say that two unitary or orthogonal representations of a finitely generated group G are additive conjugates if they are intertwined by an additive map, which need not be continuous. We associate to each representation of G a topological action that is a complete additive conjugacy invariant: the action of G by group automorphisms on the Bohr compactification of the underlying Hilbert space. Using this construction we show that the property of having almost invariant vectors is an additive conjugacy invariant. As an application we show that G is amenable if and only if there is a nonzero homomorphism from $$L^2(G)$$ into $$\mathbb {R}/\mathbb {Z}$$ that is invariant to the G-action.
Beyond 4D Tracking: Using Cluster Shapes for Track Seeding

Tracking is one of the most time consuming aspects of event reconstruction at the Large Hadron Collider (LHC) and its high-luminosity upgrade (HL-LHC). Innovative detector technologies extend tracking to four-dimensions by including timing in the pattern recognition and parameter estimation. However, present and future hardware already have additional information that is largely unused by existing track seeding algorithms. The shape of pixel-clusters provides an additional dimension for track seeding that can significantly reduce the combinatorial challenge of track finding. We use neural networks to show that cluster shapes can reduce significantly the rate of fake combinatorical backgrounds while preserving a high efficiency. We demonstrate this using the information in cluster singlets, doublets and triplets. Numerical results are presented with simulations from the TrackML challenge.
Rapid ordering of barcoded transposon insertion libraries of anaerobic bacteria

Commensal bacteria from the human intestinal microbiota play important roles in health and disease. Research into the mechanisms by which these bacteria exert their effects is hampered by the complexity of the microbiota, the strict growth requirements of the individual species and a lack of genetic tools and resources. The assembly of ordered transposon insertion libraries, in which nearly all nonessential genes have been disrupted and the strains stored as independent monocultures, would be a transformative resource for research into many microbiota members. However, assembly of these libraries must be fast and inexpensive in order to empower investigation of the large number of species that typically compose gut communities. The methods used to generate ordered libraries must also be adapted to the anaerobic growth requirements of most intestinal bacteria. We have developed a protocol to assemble ordered libraries of transposon insertion mutants that is fast, cheap and effective for even strict anaerobes. The protocol differs from currently available methods by making use of cell sorting to order the library and barcoded transposons to facilitate the localization of ordered mutations in the library. By tracking transposon insertions using barcode sequencing, our approach increases the accuracy and reduces the time and effort required to locate mutants in the library. Ordered libraries can be sorted and characterized over the course of 2 weeks using this approach. We expect this protocol will lower the barrier to generating comprehensive, ordered mutant libraries for many species in the human microbiota, allowing for new investigations into genotype–phenotype relationships within this important microbial ecosystem. This protocol assembles ordered libraries of transposon insertion mutants, even for strict anaerobes. It uses cell sorting to order the library and tracks transposon insertions using barcode sequencing to locate individual mutant strains in the ordered library.
Single-objective selective-volume illumination microscopy enables high-contrast light-field imaging.

The performance of light-field microscopy is improved by selectively illuminating the relevant subvolume of the specimen with a second objective lens. Here we advance this approach to a single-objective geometry, using an oblique one-photon illumination path or two-photon illumination to accomplish selective-volume excitation. The elimination of the second orthogonally oriented objective to selectively excite the volume of interest simplifies specimen mounting; yet, this single-objective approach still reduces the out-of-volume background, resulting in improvements in image contrast, effective resolution, and volume reconstruction quality. We validate our new, to the best of our knowledge, approach through imaging live developing zebrafish, demonstrating the technology’s ability to capture imaging data from large volumes synchronously with high contrast while remaining compatible with standard microscope sample mounting.
The effects of free surfaces on deformation twinning in HCP metals

Abstract Deformation twinning is a predominant mode of plastic deformation for hexagonal close packed metals, like Mg and Ti. The heterogenous microstructure and the local stresses associated with twinning play a key role in their mechanical response and fracture. Surface analyses, like electron microscopy, are frequently employed to spatially map microstructure and micromechanical fields in order to study twinning behavior. However, these measurements are inherently influenced by the vicinity of the free surface. Here, an elasto-visco-plastic fast-Fourier-transform (EVP-FFT) polycrystal modeling approach is employed to investigate the effects of free surfaces on twin development before and after loading. We compare calculated micromechanical fields on free surfaces with those calculated inside the bulk and, in some cases, experimental surface measurements. The results indicate that the creation of free surfaces can promote twin propagation and growth and can influence twin morphology by causing a twin lamella to become larger, more blunted and irregular. The structure along the twin boundaries are also affected, due to the higher driving stresses that extend prismatic-basal and basal-prismatic facets. Furthermore, free surfaces invoke different slip activities in the twin and the surrounding parent crystal by enhancing basal, prismatic and pyramidal slip in some localized regions, while reducing slip in others. We demonstrate that the simulated free-surface effects lead to better qualitative and quantitative agreement with experimental measurements from scanning electron microscopy and digital image correlation.
Risk-averse multi-stage stochastic programming to optimizing vaccine allocation and treatment logistics for effective epidemic response

Existing compartmental-logistics models in epidemics control are limited in terms of optimizing the allocation of vaccines and treatment resources under a risk-averse objective. In this paper, we present a data-driven, mean-risk, multi-stage, stochastic epidemics-vaccination-logistics model that evaluates various disease growth scenarios under the Conditional Value-at-Risk (CVaR) risk measure to optimize the distribution of treatment centers, resources, and vaccines, while minimizing the total expected number of infections, deaths, and close contacts of infected people under a limited budget. We integrate a new ring vaccination compartment into a Susceptible-Infected-Treated-Recovered-Funeral-Burial epidemics-logistics model. Our formulation involves uncertainty both in the vaccine supply and the disease transmission rate. Here, we also consider the risk of experiencing scenarios that lead to adverse outcomes in terms of the number of infected and dead people due to the epidemic. Combining the risk-neutral objective with a risk measure allows for a tradeoff between the weighted expected impact of the outbreak and the expected risks associated with experiencing extremely disastrous scenarios. We incorporate human mobility into the model and develop a new method to estimate the migration rate between each region when data on migration rates is not available. We apply our multi-stage stochastic mixed-integer programming model to the case of controlling the 2018–2020 Ebola Virus Disease (EVD) in the Democratic Republic of the Congo (DRC) using real data. Our results show that increasing the risk-aversion by emphasizing potentially disastrous outbreak scenarios reduces the expected risk related to adverse scenarios at the price of the increased expected number of infections and deaths over all possible scenarios. We also find that isolating and treating infected individuals are the most efficient ways to slow the transmission of the disease, while vaccination is supplementary to primary interventions on reducing the number of infections. Furthermore, our analysis indicates that vaccine acceptance rates affect the optimal vaccine allocation only at the initial stages of the vaccine rollout under a tight vaccine supply.
Microporous Scaffolds Drive Assembly and Maturation of Progenitors into β-Cell Clusters

Human pluripotent stem cells (hPSCs) represent a promising cell source for the development of β-cells for use in therapies for type 1 diabetes. Current culture approaches provide the signals to drive differentiation towards β-cells, with the cells spontaneously assembling into clusters. Herein, we adapted the current culture systems to cells seeded on microporous biomaterials, with the hypothesis that the pores can guide the assembly into β-cell clusters of defined size that can enhance maturation. The microporous scaffold culture allows hPSC-derived pancreatic progenitors to form clusters at a consistent size as cells undergo differentiation to immature β-cells. By modulating the scaffold pore sizes, we observed 250-425 µm pore size scaffolds significantly enhance insulin expression and key β-cell maturation markers compared to suspension cultures. Furthermore, when compared to suspension cultures, the scaffold culture showed increased insulin secretion in response to glucose stimulus indicating the development of functional β-cells. In addition, scaffolds facilitated cell-cell interactions enabled by the scaffold design and cell-mediated matrix deposition of extracellular matrix (ECM) proteins associated with the basement membrane of islet cells. We further investigated the influence of ECM on cell development by incorporating an ECM matrix on the scaffold prior to cell seeding; however, their presence did not further enhance maturation. These results suggest the microporous scaffold culture facilitates 3D cluster formation, supports cell-cell interactions, and provides a matrix similar to a basement membrane to drive in vitro hPSC-derived β-cell maturation and demonstrates the feasibility of these scaffolds as a biomanufacturing platform.