cssi/SciSciGPT-SciSciNet huggingface dataset:
THE OPTICAL, ULTRAVIOLET, AND X-RAY STRUCTURE OF THE QUASAR HE 0435−1223 ∗

Microlensing has proved an effective probe of the structure of the innermost regions of quasars and an important test of accretion disk models. We present light curves of the lensed quasar HE 0435–1223 in the R band and in the ultraviolet (UV), and consider them together with X-ray light curves in two energy bands that are presented in a companion paper. Using a Bayesian Monte Carlo method, we constrain the size of the accretion disk in the rest-frame near- and far-UV, and constrain for the first time the size of the X-ray emission regions in two X-ray energy bands. The R-band scale size of the accretion disk is about 1015.23 cm (~23rg ), slightly smaller than previous estimates, but larger than would be predicted from the quasar flux. In the UV, the source size is weakly constrained, with a strong prior dependence. The UV to R-band size ratio is consistent with the thin disk model prediction, with large error bars. In soft and hard X-rays, the source size is smaller than ~1014.8 cm (~10rg ) at 95% confidence. We do not find evidence of structure in the X-ray emission region, as the most likely value for the ratio of the hard X-ray size to the soft X-ray size is unity. Finally, we find that the most likely value for the mean mass of stars in the lens galaxy is ~0.3 M ☉, consistent with other studies.
The World Monetary System and External Relations of the EMU: Fasten your safety belts!

Traditionally clustered around one leading "hegemonic" world currency, with the introduction of the euro the international monetary regime might become a "symmetric" dipolar system. This fundamental change would come at a time of already considerable uncertainty when, after the Asian, Russian and Latin American financial crises caused general dismay, the major institutional framework is in a constant reform process as the G7 are considering a "new financial architecture" and the IMF is facing fundamental critique. At the same time, the legal position of the ECOFIN and the ECB in the international field in the international monetary organizations is not yet clear. This article tries to point out some concrete areas of diversity of interest in the international consequences of the introduction of the Euro and analyzes the costs and gains from cooperation in different ways of dealing with these conflicts. From the structure of the issues some conclusions on the challenges facing the institutions can be drawn and some speculation as to the appropriate distribution of competences may be possible. Thus, I try to give an overview of the legal issues surrounding the representation of the EMU in the international monetary institutions in the light of a functional analysis of the challenges created by a transformation of a "hegemonic" monetary system to a "symmetric dipolar system".
Expanding Stare Decisis: The Role of Precedent in the Unfolding Dialectic of Brady v. Maryland

Does stare decisis constrain the expansion of constitutional doctrine? Does existing precedent preclude the Supreme Court from expanding a criminal defendant’s right to exculpatory evidence? While commentators frequently clash on when stare decisis should prevent the Court from overruling its own precedents, the question of when fidelity to precedent should inhibit doctrinal expansion is surprisingly under-theorized. This Article begins to fill this gap through an in-depth case study of stare decisis and the expansion of criminal due process doctrine.This Article analyzes the longstanding constitutional dialectic between procedural and substantive schools of criminal due process. Focus is on Brady v. Maryland – the Court’s landmark 1963 decision that requires prosecutors to disclose favorable evidence to criminal defendants. Last Term, Justice Scalia argued in his Connick v. Thompson concurrence that Brady’s scope does not extend to prosecutorial disclosure of untested evidence that could prove innocence. Though coherent, Scalia’s argument depends on a particularly formal approach to stare decisis and a procedural view of due process. His argument against expanding Brady can be contested by what I term a “justificatory” approach to stare decisis and a competing substantive view of due process. This recent conflict between formal and justificatory stare decisis approaches and competing due process schools reflects a deeper metadoctrinal pattern.Based on a close reading of over a century of case law, this Article demonstrates how successful justificatory stare decisis arguments have facilitated expansion of criminal due process while formal stare decisis arguments have constrained doctrinal growth. Building on prior work, I illustrate the Brady dialectic and its relationship to stare decisis through graphical “opinion maps” that chart rival lines of majority, concurring, and dissenting opinions. Mapping this key due process territory offers insight on the deeper conflict between substance and procedure in due process jurisprudence as well as a generalizable method for studying the impact of stare decisis on constitutional adjudication.
Why I Write (and Why I Think Law Professors Generally Should Write)

Looking back on forty-five years of law review writing, Professor Kamisar concludes that, to use George Orwell's words, he has been moved to write by "a sense of injustice" and the need to "expose" "some lie," e.g., the lie that the trial judge or the prosecuting attorney can be counted on to protect the rights of unrepresented defendants. He maintains further that law professors generally should feel an obligation to write because they can think through and research exhaustively any and every problem they meet along the way without worrying about billable hours and they can do so "under working conditions that thousands of busy, hurried practitioners would envy."
Other People's Money

Legal principles that are almost right are often more mischievous than those that are completely wrong. What is transparently wrong is interpreted narrowly (or ignored altogether) and is likely to be repealed. An almost-right principle invites sloppy thinking, vague generalities, and a general distortion of the otherwise sound ideas that lie close by. An example of an almost-right principle that has distorted much of the thinking about corporate law in recent decades is the oft-repeated maxim that directors of a corporation owe a fiduciary duty to the shareholders.
VAT, tariffs, and withholding: Border taxes and informality in developing countries

Abstract This paper explores the implications of a distinctive feature of the value added tax (VAT) that is stressed by practitioners but has been largely overlooked by theorists: that it functions, in part, as a tax on the purchases of informal operators from formal sector businesses and, not least, on their imports. It also stresses the potential importance of the withholding taxes that are levied by many developing countries — which have also been ignored. It is shown, in a simple model of informality, that if both of these instruments are optimally deployed then the usual prescription that a small economy should not deploy tariffs remains valid even in the presence of an informal sector; and a simple strategy is established — generalizing the standard prescription developed in models without informality — for deploying these instruments so as to preserve government revenue and increase welfare in the face of efficiency-improving tariff cuts. Conditions are established under which a VAT alone is fully optimal, precisely because it is in part a tax on informal sector production. But they are restrictive: in general, an efficient tax structure requires deploying both a VAT and withholding taxes.
The role of financial analysts in stock market efficiency with respect to annual earnings and its cash and accrual components

This study examines biases in stock prices and financial analysts' earnings forecasts. These biases take the form of systematic overweighting or underweighting of the persistence characteristics of cash versus accrual earnings components. Our evidence suggests that stock prices tend to overweight and financial analysts tend to underweight these persistence characteristics. Furthermore, we find that analysts' underweighting attenuates stock price overweighting. However, we find little evidence that the overweighting in stock prices attenuates analyst underweighting. This study brings a new perspective to the literature regarding the disciplining role of financial analysts in capital markets.
Black-and-White Judging in a World of Grays

This essay was solicited for a symposium on "The Roberts Court." Though other cases have drawn more political attention, I discuss the most important "Erie decision" in fifty years: Shady Grove Orthopedic Associates v. Allstate.Insurance. After discussing the Court's result and opinions, this essay considers what Shady Grove means for other cases about Erie and the Rules Enabling Act. Most important, I consider what the case means for the future of precedent and the rule of law as the "Early Roberts Court" gains matures over time, and with new judicial appointments.
Mining Public Opinion about Economic Issues: Twitter and the U.S. Presidential Election

Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding elections. Social media has provided a platform for collecting a large amount of social media data. This article proposes a computational public opinion mining approach to explore the discussion of economic issues in social media during an election. Current related studies use text mining methods independently for election analysis and election prediction; this research combines two text mining methods: sentiment analysis and topic modeling. The proposed approach has effectively been deployed on millions of tweets to analyze economic concerns of people during the 2012 US presidential election.
Budget System Reform in Transitional Economies : The Experience of Russia

This paper stresses the role of budget system reform in economies in transition as an essential basis for the implementation of effective fiscal policies. However, introducing such structural reforms in often unstable economic environments has not proved easy. Using Russia as a case study, the magnitude of the problems faced is documented and the strategy of reform eventually adopted is critically reviewed. In conclusion, some lessons are drawn for other transitional countries undertaking similar reforms and the future agenda for completing these reforms in Russia is indicated.
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation

In this work we consider data-driven optimization problems where one must maximize a function given only queries at a fixed set of points. This problem setting emerges in many domains where function evaluation is a complex and expensive process, such as in the design of materials, vehicles, or neural network architectures. Because the available data typically only covers a small manifold of the possible space of inputs, a principal challenge is to be able to construct algorithms that can reason about uncertainty and out-of-distribution values, since a naive optimizer can easily exploit an estimated model to return adversarial inputs. We propose to tackle the MBO problem by leveraging the normalized maximum-likelihood (NML) estimator, which provides a principled approach to handling uncertainty and out-of-distribution inputs. While in the standard formulation NML is intractable, we propose a tractable approximation that allows us to scale our method to high-capacity neural network models. We demonstrate that our method can effectively optimize high-dimensional design problems in a variety of disciplines such as chemistry, biology, and materials engineering.
Social Media as Social Lubricant: How Ambient Awareness Eases Knowledge Transfer

Knowledge stickiness often impedes knowledge transfer. When knowledge is complex and the knowledge seeker lacks intimacy with the knowledge source, knowledge sticks in its point of origin because t...
The Cost of Friendship

We investigate how personal characteristics affect people's desire to collaborate and whether this attraction enhances or detracts from performance in venture capital. We find that venture capitalists who share the same ethnic, educational, or career background are more likely to syndicate with each other. This homophily reduces the probability of investment success, and the detrimental effect is most prominent for early-stage investments. A variety of tests show that the cost of affinity is most likely attributable to poor decision-making by high-affinity syndicates after the investment is made. These results suggest that “birds-of-a-feather-flock-together” effects in collaboration can be costly.
The Commerce Clause Meets the Delhi Sands Flower-Loving Fly

Is the Endangered Species Act constitutional? The D.C. Circuit considered that question in National Association of Home Builders v. Babbitt in 1997. More specifically, the case considered whether the congressional power to regulate interstate commerce authorized the ESA's prohibition upon building a large regional hospital in the habitat of an endangered fly that lives only in a small area of southern California. The three judges on the D.C. Circuit approached the question from three different perspectives: the relationship between biodiversity as a whole and interstate commerce, the relationship between the fly and interstate commerce, and the relationship between the hospital and interstate commerce. In this article, I argue that the constitutionality of such an application of the ESA depends upon three unanswered questions. First, I consider which effects can be aggregated for purposes of determining their effect upon interstate commerce, concluding that there must be some limit upon such aggregations. Second, I examine the potential effects that an activity may have upon interstate commerce, suggesting that Congress must provide a reasonable basis for believing that a particular resource will contribute to interstate commerce one day. And third, I consider which activities must be related to interstate commerce, arguing that the requisite effect can be judged based upon the activity that impacts an endangered species.
Censored Regression Models with Unobserved Stochastic Censoring Thresholds

Abstract The ‘Tobit’ model is a useful tool for estimation of regression models with truncated or limited dependent variables, but it requires a threshold which is either a known constant or an observable and independent variable. The model presented here extends the Tobit model to the censored case where the threshold is an unobserved and not necessarily independent random variable. Maximum likelihood procedures can be employed for joint estimation of both the primary regression equation and the parameters of the distribution of that random threshold.
Does drinking impair college performance? Evidence from a regression discontinuity approach

article i nfo This paper examines the effect of alcohol consumption on student achievement. To do so, we exploit the discontinuity in drinking at age 21 at a college in which the minimum legal drinking age is strictly enforced. We find that drinking causes significant reductions in academic performance, particularly for the highest- performing students. This suggests that the negative consequences of alcohol consumption extend beyond the narrow segment of the population at risk of more severe, low-frequency, outcomes.
Uranium and Nuclear Power: The Role of Exploration Information in Framing Public Policy

Abstract As the importance of addressing climate change increases the future global role for nuclear power, the demand for uranium will increase. Expanded uranium reserves will be needed to meet this increased demand, highlighting the importance of future exploratory efforts. To shed light on the social desirability of future exploration levels I analyze a past expansionary period in the U.S. uranium industry. I find exploration levels were smaller than socially efficient during this period, resulting from a deviation between the private and social values of information. Looking forward, public policies can encourage optimal exploration levels by addressing this deviation.
Valuation of tax expense

As tax expense reflects value lost to taxes paid, it should be negatively associated with value, provided nontax, value-relevant information is controlled for. However, valuation regressions estimated in prior research—using contemporaneous tax expense and nontax variables—document substantial variation in the coefficients on tax expense, ranging from significant negative to significant positive values. We show this variation is (a) caused by the omission of expected future profitability, and (b) explained by many factors that cause variation in the correlations among included variables and omitted future profitability. Unfortunately, difficulties associated with separating the impact of individual factors hampers tax research investigating determinants of the value relevance of tax expense.
Synchronization Strings and Codes for Insertions and Deletions—A Survey

Already in the 1960s, Levenshtein and others studied error-correcting codes that protect against synchronization errors, such as symbol insertions and deletions. However, despite significant efforts, progress on designing such codes has been lagging until recently, particularly compared to the detailed understanding of error-correcting codes for symbol substitution or erasure errors. This paper surveys the recent progress in designing efficient error-correcting codes over finite alphabets that can correct a constant fraction of worst-case insertions and deletions. Most state-of-the-art results for such codes rely on synchronization strings, simple yet powerful pseudo-random objects that have proven to be very effective solutions for coping with synchronization errors in various settings. This survey also includes an overview of what is known about synchronization strings and discusses communication settings related to error-correcting codes in which synchronization strings have been applied.
Noncommutative-Geometry Wormholes with Isotropic Pressure

The strategy adopted in the original Morris-Thorne wormhole was to retain complete control over the geometry at the expense of certain engineering considerations. The purpose of this paper is to obtain several complete wormhole solutions by assuming a noncommutative-geometry background with a concomitant isotropic pressure condition. This condition allows us to consider a cosmological setting with a perfect-fluid equation of state. An extended form of the equation generalizes the first solution and subsequently leads to the generalized Chaplygin gas model and hence to a third solution. The solutions obtained extend several previous results. This paper also reiterates the need for a noncommutative-geometry background to account for the enormous radial tension that is a characteristic of Morris-Thorne wormholes.
Association of metformin and development of dry age-related macular degeneration in a U.S. insurance claims database.

Purpose:To assess whether metformin is associated with dry age-related macular degeneration (dAMD) development.Methods:In this retrospective cohort study, patients enrolled in a nationwide U.S. med...
Relational Structures of Fundamental Theories

General relativity and quantum mechanics have both revealed the relativity of certain notions that were previously thought to be absolute. I clarify the precise sense in which these theories are relational, and I argue that the various aspects of relationality pertain to the same movement in the progress of physical theories.
Medical knowledge-guided deep curriculum learning for elbow fracture diagnosis from x-ray images

Elbow fractures are one of the most common fracture types. Diagnoses on elbow fractures often need the help of radiographic imaging to be read and analyzed by a specialized radiologist with years of training. Thanks to the recent advances of deep learning, a model that can classify and detect different types of bone fractures needs only hours of training and has shown promising results. However, most existing deep learning models are purely data-driven, lacking incorporation of known domain knowledge from human experts. In this work, we propose a novel deep learning method to diagnose elbow fracture from elbow X-ray images by integrating domain-specific medical knowledge into a curriculum learning framework. In our method, the training data are permutated by sampling without replacement at the beginning of each training epoch. The sampling probability of each training sample is guided by a scoring criterion constructed based on clinically known knowledge from human experts, where the scoring indicates the diagnosis difficultness of different elbow fracture subtypes. We also propose an algorithm that updates the sampling probabilities at each epoch, which is applicable to other sampling-based curriculum learning frameworks. We design an experiment with 1865 elbow X-ray images for a fracture/normal binary classification task and compare our proposed method to a baseline method and a previous method using multiple metrics. Our results show that the proposed method achieves the highest classification performance. Also, our proposed probability update algorithm boosts the performance of the previous method.
Management of Multiple Sources of Risk in Livestock Production

Firm operators continually manage multiple sources of risk. In an application to cattle feedlot operations, our objective is to determine if producers view output price and animal health risks separately or jointly. We conduct a survey with a choice experiment placing operators in forward looking, decision-making scenarios, and capture information on past risk management approaches. Evidence regarding a relationship between animal health and output price risk mitigation is mixed and depends on the decision being made. Combined, these results provide new insight into how managers approach multiple risks when facing resource constraints.
Heisenberg spin chain as a worldsheet coordinate for lightcone quantized string

Although the energy spectrum of the Heisenberg spin chain on a circle defined by $$ H=\frac{1}{4}\sum \limits_{k=1}^M\left({\sigma}_k^x{\sigma}_{k+1}^x+{\sigma}_k^y{\sigma}_{k+1}^y+\Delta {\sigma}_k^z{\sigma}_{k+1}^z\right) $$ is well known for any fixed M, the boundary conditions vary according to whether M ∈ 4ℕ + r, where r = −1, 0, 1, 2, and also according to the parity of the number of overturned spins in the state, In string theory all these cases must be allowed because interactions involve a string with M spins breaking into strings with M1 < M and M − M1 spins (or vice versa). We organize the energy spectrum and degeneracies of H in the case ∆ = 0 where the system is equivalent to a system of free fermions. In spite of the multiplicity of special cases, in the limit M → ∞ the spectrum is that of a free compactified worldsheet field. Such a field can be interpreted as a compact transverse string coordinate x(σ) ≡ x(σ) + R0. We construct the bosonization formulas explicitly in all separate cases, and for each sector give the Virasoro conformal generators in both fermionic and bosonic formulations. Furthermore from calculations in the literature for selected classes of excited states, there is strong evidence that the only change for ∆ ≠ 0 is a change in the compactification radius R0 → R∆. As ∆ → −1 this radius goes to infinity, giving a concrete example of noncompact space emerging from a discrete dynamical system. Finally we apply our work to construct the three string vertex implied by a string whose bosonic coordinates emerge from this mechanism.
Can You Trust Your Trust Measure

Trust in human-robot interactions (HRI) is measured in two main ways: through subjective questionnaires and through behavioral tasks. To optimize measurements of trust through questionnaires, the field of HRI faces two challenges: the development of standardized measures that apply to a variety of robots with different capabilities, and the exploration of social and relational dimensions of trust in robots (e.g., benevolence). In this paper we look at how different trust questionnaires (Lyons & Guznov, 2019; Schaefer, 2016; Ullman & Malle, 2018) fare given these challenges that pull in different directions (being general vs. being exploratory) by studying whether people think the items in these questionnaires are applicable to different kinds of robots and interactions. In Study 1 we show that after being presented with a robot (non-humanoid) and an interaction scenario (fire evacuation), participants rated multiple questionnaire items such as "This robot is principled" as "Non-applicable to robots in general" or "Non-applicable to this robot." In Study 2 we show that the frequency of these ratings change (indeed, even for items rated as N/A to robots in general) when a new scenario is presented (game playing with a humanoid robot). Finally, while overall trust scores remained robust to N/A ratings, our results revealed potential fallacies in the way these scores are commonly interpreted. We conclude with recommendations for the development, use and results-reporting of trust questionnaires for future studies, as well as theoretical implications for the field of HRI.
Polynomial invariants of singular knots and links

We generalize the notion of the quandle polynomial to the case of singquandles. We show that the singquandle polynomial is an invariant of finite singquandles. We also construct a singular link inv...
The effects of engineered nanoparticles on nitrification during biological wastewater treatment.

Technological advancements in the past few decades have made it possible to manufacture nanomaterials at large scale and engineered nanoparticles (ENPs) are increasingly found in consumer products such as cosmetics, sports products and LED displays. A large amount of these ENPs end up in wastewater and potentially impact the performance of wastewater treatment plants (WWTPs). One important function of the WWTP is nitrification, which is carried out by the actions of two groups of bacteria, ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). Since most ENPs are found to have or are designed to have antimicrobial activities, it is a legitimate concern that ENPs entering WWTPs may have negative impacts on nitrification. In this paper, the effects of ENPs on nitrification is discussed, focusing mainly on autotrophic nitrification by AOBs and NOBs. This review also covers ENPs effects on anaerobic ammonium oxidation (ANAMMOX). Generally, nitrifiers in pure and mixed culture can be inhibited by a variety of ENPs, but stress response mechanisms may attenuate toxicity. Long-term studies demonstrated that a wide range of NPs can cause severe deterioration of AOBs and/or NOBs when the influent concentration exceeded an inhibition threshold. Proposed mechanisms include the generation of reactive oxygen species, dissolved metals, physical disruption of cell membranes, bacterial engulfment, and intracellular accumulation of ENPs. Future research needs are also discussed. This article is protected by copyright. All rights reserved.
Helly-gap of a graph and vertex eccentricities

Abstract A new metric parameter for a graph, Helly-gap, is introduced. A graph G is called α-weakly-Helly if any system of pairwise intersecting disks in G has a nonempty common intersection when the radius of each disk is increased by an additive value α. The minimum α for which a graph G is α-weakly-Helly is called the Helly-gap of G and denoted by α ( G ) . The Helly-gap of a graph G is characterized by distances in the injective hull H ( G ) , which is a (unique) minimal Helly graph which contains G as an isometric subgraph. This characterization is used as a tool to generalize many eccentricity related results known for Helly graphs ( α ( G ) = 0 ), as well as for chordal graphs ( α ( G ) ≤ 1 ), distance-hereditary graphs ( α ( G ) ≤ 1 ) and δ-hyperbolic graphs ( α ( G ) ≤ 2 δ ), to all graphs, parameterized by their Helly-gap α ( G ) . Several additional graph classes are shown to have a bounded Helly-gap, including AT-free graphs and graphs with bounded tree-length, bounded chordality or bounded α i -metric.
Switchable X-Ray Orbital Angular Momentum from an Artificial Spin Ice

Artificial spin ices (ASI) have been widely investigated as magnetic metamaterials with exotic properties governed by their geometries. In parallel, interest in x-ray photon orbital angular momentum (OAM) has been rapidly growing. Here we show that a square ASI with a patterned topological defect, a double edge dislocation, imparts OAM to scattered x rays. Unlike single dislocations, a double dislocation does not introduce magnetic frustration, and the ASI equilibrates to its antiferromagnetic (AFM) ground state. The topological charge of the defect differs with respect to the structural and magnetic order; thus, x-ray diffraction from the ASI produces photons with even and odd OAM quantum numbers at the structural and AFM Bragg conditions, respectively. The magnetic transitions of the ASI allow the AFM OAM beams to be switched on and off by modest variations of temperature and applied magnetic field. These results demonstrate ASIs can serve as metasurfaces for reconfigurable x-ray optics that could enable selective probes of electronic and magnetic properties.
Brucella ovis Cysteine Biosynthesis Contributes to Peroxide Stress Survival and Fitness in the Intracellular Niche.

Brucella ovis is an ovine intracellular pathogen with tropism for the male genital tract. To establish and maintain infection, B. ovis must survive stressful conditions inside host cells, including low pH, nutrient limitation, and reactive oxygen species. These same conditions are often encountered in axenic cultures during stationary phase. Studies of stationary phase may thus inform understanding of Brucella infection biology, yet the genes and pathways that are important in Brucella stationary phase physiology remain poorly defined. We measured fitness of a barcoded pool of B. ovis Tn-himar mutants as a function of growth phase and identified cysE as a determinant of fitness in stationary phase. CysE catalyzes the first step in cysteine biosynthesis from serine, and we provide genetic evidence that two related enzymes, CysK1 and CysK2, function redundantly to catalyze cysteine synthesis at steps downstream of CysE. Deleting either cysE (ΔcysE) or both cysK1 and cysK2 (ΔcysK1 ΔcysK2) results in premature entry into stationary phase, reduced culture yield and sensitivity to exogenous hydrogen peroxide. These phenotypes can be chemically complemented by cysteine or glutathione. ΔcysE and ΔcysK1 ΔcysK2 strains have no defect in host cell entry in vitro but have significantly diminished intracellular fitness between 2 and 24 hours post infection. Our study has uncovered unexpected redundancy at the CysK step of cysteine biosynthesis in B. ovis, and demonstrates that cysteine anabolism is a determinant of peroxide stress survival and fitness in the intracellular niche.
POLYNOMIALS WITH ZEROS ON THE UNIT CIRCLE: REGULARITY OF LEJA SEQUENCES

Let $z_1, \dots, z_m$ be $m$ distinct complex numbers, normalized to $|z_k| = 1$, and consider the polynomial $$ p_{m}(z) = \prod_{k=1}^{m}{(z-z_k)}.$$ We define a sequence of polynomials in a greedy fashion, $$ p_{N+1}(z) = p_{N}(z) \left(z - z^*\right)\qquad \mbox{where}~z^* = \arg\max_{|z|=1} |p_{N}(z)|,$$ and prove that, independently of the initial polynomial $p_m$, the roots of $p_{N}$ equidistribute in angle at rate at most $(\log{N})^2/N$. This even persists when sometimes adding `adversarial' points by hand. We rephrase the main result in terms of a dynamical system involving the inverse fractional Laplacian $(-\Delta)^{-1/2}$ and conjecture that, when phrased in this language, the underlying regularity phenomenon might appear in a very general setting.
A NORMATIVE THEORY OF THE CLEAN HANDS DEFENSE

What is the clean hands defense (CHD) normatively about? Courts designate court integrity as the CHD's primary norm. Yet, while the CHD may at times further court integrity, it is not fully aligned with court integrity. In addition to occasionally instrumentally furthering certain goods (e.g., court legitimacy, judge integrity, deterrence), the CHD embodies two judicially undetected norms: retribution and tu quoque (“you too!”). Tu quoque captures the moral intuition that wrongdoers are in no position to blame, condemn, or make claims on others who are guilty of similar or related wrongdoing. The CHD shares the structure of the tu quoque: both are doctrines of standing that deflate the illocutionary force (and not the truth-value) of normative speech acts directed against wrongdoers by those guilty of similar or connected wrongdoing. The CHD also exhibits retributive logic: it sanctions plaintiffs by reason of their wrongdoing and manifests the retributive principle that “punishment must fit the crime.”
Decay of Information for the Kac Evolution

We consider a system of M particles in contact with a heat reservoir of $$N\gg M$$ particles. The evolution in the system and the reservoir, together with their interaction, is modeled via the Kac’s master equation. We chose the initial distribution with total energy $$N+M$$ and show that if the reservoir is initially in equilibrium, that is, if the initial distribution depends only on the energy of the particle in the reservoir, then the entropy of the system decays exponentially to a very small value. We base our proof on a similar property for the Information. A similar argument allows us to greatly simplify the proof of the main result in Bonetto et al. (Commun Math Phys 363(3):847–875, 2018).
An Online Evolving Framework for Advancing Reinforcement-Learning based Automated Vehicle Control

Abstract In this paper, an online evolving framework is proposed to detect and revise a controller’s imperfect decision-making in advance. The framework consists of three modules: the evolving Finite State Machine (e-FSM), action-reviser, and controller modules. The e-FSM module evolves a stochastic model (e.g., Discrete-Time Markov Chain) from scratch by determining new states and identifying transition probabilities repeatedly. With the latest stochastic model and given criteria, the action-reviser module checks validity of the controller’s chosen action by predicting future states. Then, if the chosen action is not appropriate, another action is inspected and selected. In order to show the advantage of the proposed framework, the Deep Deterministic Policy Gradient (DDPG) w/ and w/o the online evolving framework are applied to control an ego-vehicle in the car-following scenario where control criteria are set by speed and safety. Experimental results show that inappropriate actions chosen by the DDPG controller are detected and revised appropriately through our proposed framework, resulting in no control failures after a few iterations.
Multitask Bandit Learning Through Heterogeneous Feedback Aggregation

In many real-world applications, multiple agents seek to learn how to perform highly related yet slightly different tasks in an online bandit learning protocol. We formulate this problem as the $\epsilon$-multi-player multi-armed bandit problem, in which a set of players concurrently interact with a set of arms, and for each arm, the reward distributions for all players are similar but not necessarily identical. We develop an upper confidence bound-based algorithm, RobustAgg$(\epsilon)$, that adaptively aggregates rewards collected by different players. In the setting where an upper bound on the pairwise similarities of reward distributions between players is known, we achieve instance-dependent regret guarantees that depend on the amenability of information sharing across players. We complement these upper bounds with nearly matching lower bounds. In the setting where pairwise similarities are unknown, we provide a lower bound, as well as an algorithm that trades off minimax regret guarantees for adaptivity to unknown similarity structure.
Quantum Circuit Cutting with Maximum Likelihood Tomography

We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.
Consistent k-Median: Simpler, Better and Robust

In this paper we introduce and study the online consistent $k$-clustering with outliers problem, generalizing the non-outlier version of the problem studied in [Lattanzi-Vassilvitskii, ICML17]. We show that a simple local-search based online algorithm can give a bicriteria constant approximation for the problem with $O(k^2 \log^2 (nD))$ swaps of medians (recourse) in total, where $D$ is the diameter of the metric. When restricted to the problem without outliers, our algorithm is simpler, deterministic and gives better approximation ratio and recourse, compared to that of [Lattanzi-Vassilvitskii, ICML17].
SPlit: An Optimal Method for Data Splitting

In this article, we propose an optimal method referred to as SPlit for splitting a dataset into training and testing sets. SPlit is based on the method of support points (SP), which was initially d...
Thermal Transport in Polymers: A Review

In this article, we review thermal transport in polymers with different morphologies from aligned fibers to bulk amorphous states. We survey early and recent efforts in engineering polymers with high thermal conductivity by fabricating polymers with large-scale molecular alignments. The experimentally realized extremely high thermal conductivity of polymer nanofibers are highlighted, and understanding of thermal transport physics from molecular simulations are discussed. We then transition to the discussion of bulk amorphous polymers with an emphasize on the physics of thermal transport and its relation with the conformation of molecular chains in polymers. We also discuss the current understanding of how the chemistry of polymers would influence thermal transport in amorphous polymers and some limited, but important chemistry-structural-property relationships. Lastly, challenges, perspectives and outlook of this field are presented. We hope this review will inspire more fundamental and applied research in the polymer thermal transport field to advance scientific understanding and engineering applications.
Distinct expression of select and transcriptome-wide isolated 3'UTRs suggests critical roles in development and transition states

Mature mRNA molecules are expected to be comprised of a 5'UTR, a 3'UTR and a coding region (CDS). Unexpectedly, however, there have been multiple recent reports of widespread differential expression of mRNA 3'UTRs and their cognate coding regions (CDS), reflecting the expression of isolated 3'UTRs (i3'UTRs); these i3'UTRs can be highly expressed, often in reciprocal patterns to their cognate CDS. As with other long non-coding (lncRNAs), isolated 3'UTRs are likely to play an important role in gene regulation, but little is known about the contexts in which they are deployed. To illuminate the functions of i3'UTRs, here we carry out in vitro, in vivo and in silico analyses of differential 3'UTR/CDS mRNA ratio usage across tissues, development and cell state changes both for a select list of developmentally important genes as well as by unbiased transcriptome-wide analyses. Across two developmental paradigms we find a distinct switch from high i3'UTR expression for stem cell related genes in proliferating cells to high CDS for these genes in newly differentiated cells. Unbiased transcriptome analysis across multiple gene sets shows that regardless of tissue, genes with high 3'UTR to CDS ratios belong predominantly to gene ontology categories related to cell-type specific functions. In contrast, the gene ontology categories of genes with low 3'UTR to CDS ratios are similar across tissues and relate to common cellular functions. We further show that, at least for some genes, traditional transcriptional start site genomic elements correspond to identified RNAseq 3'UTR peak regions, suggesting that some i3'UTRs may be generated by de novo transcription. Our results provide critical information from which detailed hypotheses for individual i3'UTRs can be tested, with a common theme that i3'UTRs appear poised to regulate cell-specific gene expression and state.
The Speed of Traveling Waves in a FKPP-Burgers System

We consider a coupled reaction–advection–diffusion system based on the Fisher-KPP and Burgers equations. These equations serve as a one-dimensional version of a model for a reacting fluid in which the arising density differences induce a buoyancy force advecting the fluid. We study front propagation in this system through the lens of traveling waves solutions. We are able to show two quite different behaviors depending on whether the coupling constant $$\rho $$ is large or small. First, it is proved that there is a threshold $$\rho _0$$ under which the advection has no effect on the speed of traveling waves (although the advection is nonzero). Second, when $$\rho $$ is large, wave speeds must be at least $$\mathcal {O}(\rho ^{1/3})$$ . These results together give that there is a transition from pulled to pushed waves as $$\rho $$ increases. Because of the complex dynamics involved in this and similar models, this is one of the first precise results in the literature on the effect of the coupling on the traveling wave solution. We use a mix of ordinary and partial differential equation methods in our analytical treatment, and we supplement this with a numerical treatment featuring newly created methods to understand the behavior of the wave speeds. Finally, various conjectures and open problems are formulated.
An observational program to search for radio signals from extraterrestrial intelligence through the use of existing facilities

Abstract Approaches to the detection of radio signals from extraterrestrial intelligence (ETI) have, of necessity, circumscribed the vast parameter space which might be searched. Uncertainties in location, frequency, modulation, and reasonable power flux density have drawn arguments for huge antennas and philosophical approaches to frequency selection. Yet the observational limits within which ETI signals might await detection are largely undefined. The state of the art has advanced so that observations with existing antennas, equipped with modern data processors, can define limits over very broad frequency ranges in reasonable observational times. A modest program has been initiated to search for ETI signals from 1 to 25 GHz over 80% of the sky to flux levels from 10 −19 to 10 −23 W/m 2 .
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities

Machine learning (ML) is now commonplace, powering data-driven applications in various organizations. Unlike the traditional perception of ML in research, ML production pipelines are complex, with many interlocking analytical components beyond training, whose sub-parts are often run multiple times on overlapping subsets of data. However, there is a lack of quantitative evidence regarding the lifespan, architecture, frequency, and complexity of these pipelines to understand how data management research can be used to make them more efficient, effective, robust, and reproducible. To that end, we analyze the provenance graphs of 3000 production ML pipelines at Google, comprising over 450,000 models trained, spanning a period of over four months, in an effort to understand the complexity and challenges underlying production ML. Our analysis reveals the characteristics, components, and topologies of typical industry-strength ML pipelines at various granularities. Along the way, we introduce a specialized data model for representing and reasoning about repeatedly run components in these ML pipelines, which we call model graphlets. We identify several rich opportunities for optimization, leveraging traditional data management ideas. We show how targeting even one of these opportunities, i.e., identifying and pruning wasted computation that does not translate to model deployment, can reduce wasted computation cost by 50% without compromising the model deployment cadence.
Callable barrier reverse convertible securities

We study the valuation of callable barrier reverse convertible contracts written on one or two underlying asset prices. We assume the issuer of the contract can call early redemption at any time du...
Single-Qubit Fidelity Assessment of Quantum Annealing Hardware

As a wide variety of quantum computing platforms become available, methods for assessing and comparing the performance of these devices are of increasing interest and importance. Inspired by the success of single-qubit error rate computations for tracking the progress of gate-based quantum computers, this work proposes a quantum annealing single-qubit assessment (QASA) protocol for quantifying the performance of individual qubits in quantum annealing computers. The proposed protocol scales to large quantum annealers with thousands of qubits and provides unique insights into the distribution of qubit properties within a particular hardware device. The efficacy of the QASA protocol is demonstrated by analyzing the properties of a D-Wave 2000Q system, revealing unanticipated correlations in the qubit performance of that device. A study repeating the QASA protocol at different annealing times highlights how the method can be utilized to understand the impact of annealing parameters on qubit performance. Overall, the proposed QASA protocol provides a useful tool for assessing the performance of current and emerging quantum annealing devices.
Shape Matters: Understanding the Implicit Bias of the Noise Covariance

The noise in stochastic gradient descent (SGD) provides a crucial implicit regularization effect for training overparameterized models. Prior theoretical work largely focuses on spherical Gaussian noise, whereas empirical studies demonstrate the phenomenon that parameter-dependent noise --- induced by mini-batches or label perturbation --- is far more effective than Gaussian noise. This paper theoretically characterizes this phenomenon on a quadratically-parameterized model introduced by Vaskevicius et al. and Woodworth et al. We show that in an over-parameterized setting, SGD with label noise recovers the sparse ground-truth with an arbitrary initialization, whereas SGD with Gaussian noise or gradient descent overfits to dense solutions with large norms. Our analysis reveals that parameter-dependent noise introduces a bias towards local minima with smaller noise variance, whereas spherical Gaussian noise does not.