cssi/SciSciGPT-SciSciNet huggingface dataset:
Appropriations for the Abolitionists: Undermining Effects of the U.S. Mandatory Anti-Prostitution Pledge in the Fight against Human Trafficking and HIV/AIDS

"Appropriations for the Abolitionists" examines the global impact of U.S. policies requiring organizations to endorse a pledge “explicitly opposing prostitution and sex trafficking” as a condition of funding for programs to combat human trafficking and address HIV/AIDS. The article begins by exploring legal challenges to the policy by U.S.-based non-profit organizations on First Amendment and due process grounds. Utilizing doctrinal analysis and reports from advocates in the field, the paper exposes the undermining effects of the U.S. anti-prostitution pledge in HIV/AIDS and anti-trafficking interventions abroad. Based on a year of field research in Thailand and interviews with front-line activists and state agents involved in counter-trafficking networks, the article illustrates the practical effects of prostitution-abolitionist funding and programming policies as they are implemented on the ground. Fractured alliances, abandoned interventions, and the failure to engage targeted communities in a non-discriminatory manner hinder initiatives to address HIV/AIDS and human trafficking, particularly among migrants in the commercial sex industry. Without consulting a broad coalition of groups, encouraging rigorous development of best practices in the field, and taking seriously the demands of trafficked and exploited migrants themselves, even the best-intentioned policies will ultimately backfire.
Damped Seasonality Factors: Introduction

Previous research has shown that seasonal factors provide one of the most important ways to improve forecast accuracy. For example, in forecasts over an 18-month horizon for 68 monthly economic series from the M-Competition, Makridakis et al. (1984, Table 14) found that seasonal adjustments reduced the MAPE from 23.0 to 17.7 percent, an error reduction of 23%. On the other hand, research has also shown that seasonal factors sometimes increase forecast errors (e.g., Nelson, 1972). So, when forecasting with a data series measured in intervals that represent part of a year, should one use seasonal factors or not? Statistical tests have been devised to answer this question, and they have been quite useful. However, some people might say that the question is not fair. Why does it have to be either/or? Shouldn^Rt the question be ^Sto what extent should seasonal factors be used for a given series?^T
Less is better: when low‐value options are valued more highly than high‐value options

This research demonstrates a less-is-better eAect in three contexts: (1) a person giving a $45 scarf as a gift was perceived to be more generous than one giving a $55 coat; (2) an overfilled ice cream serving with 7 oz of ice cream was valued more than an underfilled serving with 8 oz of ice cream; (3) a dinnerware set with 24 intact pieces was judged more favourably than one with 31 intact pieces (including the same 24) plus a few broken ones. This less-is-better eAect occurred only when the options were evaluated separately, and reversed itself when the options were juxtaposed. These results are explained in terms of the evaluability hypothesis, which states that separate evaluations of objects are often influenced by attributes which are easy to evaluate rather than by those which are important. #1998 John Wiley & Sons, Ltd.
Differences in Trading Behavior across NYSE Specialist Firms

Using a sample of NYSE-listed equities from 1992, this study examines whether market maker performance differs across specialist firms. We find that spreads and depth differ across specialist firms, but the competitiveness of NYSE quotes relative to other exchanges does not appear to be affected by these differences. Differences are also evident in measures of transitory volatility and in the frequency and duration of order-imbalance trading halts. The results suggest that specialists have a significant effect on execution costs, liquidity, and noise in security prices and that these effects are not completely eliminated by competition or the NYSE's monitoring mechanisms.
In-depth and 3-dimensional exploration of the budding yeast phosphoproteome

Phosphorylation is one of the most dynamic and widespread post-translational modifications regulating virtually every aspect of eukaryotic cell biology. Here, we assemble a dataset from 75 independent phosphoproteomic experiments performed in our laboratory using Saccharomyces cerevisiae. We report 30,902 phosphosites identified from cells cultured in a range of DNA damage conditions and/or arrested in distinct cell cycle stages. To generate a comprehensive resource for the budding yeast community, we aggregate our dataset with the Saccharomyces Genome Database and another recently published study, resulting in over 46,000 budding yeast phosphosites. With the goal of enhancing the identification of functional phosphorylation events, we perform computational positioning of phosphorylation sites on available 3D protein structures and systematically identify events predicted to regulate protein complex architecture. Results reveal hundreds of phosphorylation sites mapping to or near protein interaction interfaces, many of which result in steric or electrostatic "clashes" predicted to disrupt the interaction. With the advancement of Cryo-EM and the increasing number of available structures, our approach should help drive the functional and spatial exploration of the phosphoproteome.
A Revolution at War with Itself? Preserving Employment Preferences from Weber to Ricci

Two aspects of the constitutional transformation Bruce Ackerman describes in The Civil Rights Revolution were on a collision course, one whose trajectory has implications for Ackerman’s account and for his broader theory of constitutional change. Ackerman makes a compelling case that what he terms “reverse state action” (the targeting of private actors) and “government by numbers” (the use of statistics to identify and remedy violations of civil rights laws) defined the civil rights revolution. Together they “requir[ed] private actors, as well as state officials, to . . . realize the principles of constitutional equality” and allowed the federal government to “actually achieve egalitarian advances in the real world.” Within the frame of Ackerman’s study, these features of the civil rights revolution worked in tandem, perhaps even synergistically, helping to generate the period’s remarkable changes in voting, employment, and education. But as this essay shows, at least in the case of employment discrimination, reverse state action quickly became a threat to government by numbers. In the 1970s, no sooner did numerical measures take hold in preventing, settling, and remedying employment discrimination than courts faced claims that these measures violated the very laws pursuant to which they had been adopted. Exactly when and where state action adhered ultimately helped decide the viability of the numerical approach in the new employment discrimination regime. The eventual tensions between the “government by numbers” and “reverse state action” strands of Ackerman’s account raise questions about the content and viability of the civil rights revolution he documents. They also underscore the importance of refining his theory’s account of what he terms consolidation, synthesis, and judicial betrayal. author. Assistant Professor of Law and History, University of Pennsylvania. I would like to thank Maria da Silva for outstanding research assistance; Christine Jolls and Reva Siegel for helpful comments; and the Journal’s editors for their help polishing the piece. I am deeply indebted to Bruce Ackerman for inviting me to participate in this symposium and for being such an inspirational teacher and scholar. a revolution at war with itself?
A Search for OH Megamasers at z > 0.1. I. Preliminary Results

We present the preliminary results of a survey for OH megamasers underway at the Arecibo Observatory1. The goals of the survey are to calibrate the luminosity function of OH megamasers to the low-redshift galaxy merger rate (0.1 0.1. The new megamasers show a wide range of spectral properties but are consistent with the extant set of 55 previously reported objects, only eight of which have z > 0.1.
Non-Bayesian updating: a theoretical framework

This paper models an agent in a multi-period setting who does not update according to Bayes' Rule, and who is self-aware and anticipates her updating behavior when formulating plans. Choice-theoretic axiomatic foundations are provided to capture updating biases that reflect excessive weight given to either prior beliefs, or alternatively, to observed data. A counterpart of the exchangeable Bayesian learning model is also described.
Regulating Online Buzz Marketing: Untangling a Web of Deceit

During the past fifteen years, the Internet has swelled into its own virtual world of commentary, opinion, criticism, news, music, videos, gaming, role playing, shopping, banking, finance, and digital commerce. Coupled with the growth of blogs and social networking sites, millions of Americans appear willing to share online their own thoughts and experiences regarding products, services and companies. In response to the public’s interest, companies have begun to rely more heavily in recent years on word of mouth marketing, often referred to as “buzz marketing,” a technique that attempts to generate conversations among and with current and potential customers. Marketers have discovered that the Internet is an excellent interactive medium to promote goods and services. Some marketers have begun to engage in the flourishing business of “stealth marketing,” a method of communicating with potential customers in a way that disguises the originator of the communication. The increase in use of the Internet as a marketing medium gives rise to a conundrum: consumers are bombarded by, skeptical of, and generally ignore overt commercial messages, but consumers are more likely to pay attention to—even seek out—and regard as credible, reviews and opinions by fellow consumers. Marketers therefore hope to convey their advertising messages through consumer comments (endorsements/testimonials). However, if consumers know a marketer sponsors the comments, the comments are less likely to be viewed as credible, and if the marketers do not disclose the sponsorship, they are potentially deceiving the public.
A Social IoT-Driven Pedestrian Routing Approach During Epidemic Time

The unprecedented worldwide spread of coronavirus disease has significantly sped up the development of technology-based solutions to prevent, combat, monitor, or predict pandemics and/or its evolution. The omnipresence of smart Internet-of-things (IoT) devices can play a predominant role in designing advanced techniques helping in minimizing the risk of contamination. In this paper, we propose a practical framework that uses the Social IoT (SIoT) concept to improve pedestrians safely navigate through a real-wold map of a smart city. The objective is to mitigate the risks of exposure to the virus in high-dense areas where social distancing might not be well-practiced. The proposed routing approach recommends pedestrians' route in a real-time manner while considering other devices' mobility. First, the IoT devices are clustered into communities according to two SIoT relations that consider the devices' locations and the friendship levels among their owners. Accordingly, the city map roads are assigned weights representing their safety levels. Afterward, a navigation algorithm, namely the Dijkstra algorithm, is applied to recommend the safest route to follow. Simulation results applied on a real-world IoT data set have shown the ability of the proposed approach in achieving trade-offs between both safest and shortest paths according to the pedestrian preference.
A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes.

Motivation Transcriptome-wide association studies (TWAS) have successfully facilitated the discovery of novel genetic risk loci for many complex traits, including late-onset Alzheimer's disease (AD). However, most existing TWAS methods rely only on gene expression and ignore epigenetic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer-promoter interactions), both of which contribute significantly to the genetic basis of AD. Results We develop a novel gene-level association testing method that integrates genetically regulated DNA methylation and enhancer-target gene pairs with genome-wide association study (GWAS) summary results. Through simulations, we show that our approach, referred to as the CMO (cross methylome omnibus) test, yielded well controlled type I error rates and achieved much higher statistical power than competing methods under a wide range of scenarios. Furthermore, compared with TWAS, CMO identified an average of 124% more associations when analyzing several brain imaging-related GWAS results. By analyzing to date the largest AD GWAS of 71,880 cases and 383,378 controls, CMO identified six novel loci for AD, which have been ignored by competing methods. Availability Software: https://github.com/ChongWuLab/CMO. Supplementary information Supplementary data are available at Bioinformatics online.
Topology optimization of nonlinear periodically microstructured materials for tailored homogenized constitutive properties

Abstract A topology optimization method is presented for the design of periodic microstructured materials with prescribed homogenized nonlinear constitutive properties over finite strain ranges. Building upon an existing computational homogenization method for periodic materials undergoing finite strain, generalized sensitivity equations are derived for the gradient-based topology optimization of periodic unit cells that account for the nonlinear homogenized response of the unit cell. The mechanical model assumes linear elastic isotropic materials , geometric nonlinearity at finite strain, and a quasi-static response. The optimization problem is solved by a nonlinear programming method and the sensitivities computed via the adjoint method. Several topology optimization examples are presented to evaluate the performance of the developed method. Furthermore, two-dimensional structures identified using this optimization method are additively manufactured and their uniaxial tensile strain response compared with the numerically predicted behavior. The optimization approach herein enables the design and development of lattice-like materials with prescribed nonlinear effective properties, for use in myriad potential applications, ranging from stress wave and vibration mitigation to soft robotics.
Adapting in Difficult Circumstances: Protestant Pastors and the Xi Jinping Effect

To understand the consequences of Xi Jinping’s rise, one must look down as well as up. Even in the face of increased repression, people have a say over how it unfolds and the shape it takes. Many C...
Explainable AI for Robot Failures: Generating Explanations that Improve User Assistance in Fault Recovery

With the growing capabilities of intelligent systems, the integration of robots in our everyday life is increasing. However, when interacting in such complex human environments, the occasional failure of robotic systems is inevitable. The field of explainable AI has sought to make complex-decision making systems more interpretable but most existing techniques target domain experts. On the contrary, in many failure cases, robots will require recovery assistance from non-expert users. In this work, we introduce a new type of explanation, eerr, that explains the cause of an unexpected failure during an agent's plan execution to non-experts. In order for error explanations to be meaningful, we investigate what types of information within a set of hand-scripted explanations are most helpful to non-experts for failure and solution identification. Additionally, we investigate how such explanations can be autonomously generated, extending an existing encoder-decoder model, and generalized across environments. We investigate such questions in the context of a robot performing a pick-and-place manipulation task in the home environment. Our results show that explanations capturing the context of a failure and history of past actions, are the most effective for failure and solution identification among non-experts. Furthermore, through a second user evaluation, we verify that our model-generated explanations can generalize to an unseen office environment, and are just as effective as the hand-scripted explanations.
Extent-compatible control barrier functions

Abstract Safety requirements in dynamical systems are commonly enforced with set invariance constraints over a safe region of the state space. Control barrier functions, which are Lyapunov-like functions for guaranteeing set invariance, are an effective tool to enforce such constraints and guarantee safety when the system is represented as a point in the state space. In this paper, we introduce extent-compatible control barrier functions as a tool to enforce safety for the system explicitly accounting for its volume (extent) within an ambient workspace. In order to implement the extent-compatible control barrier functions framework, we first propose a sum-of-squares optimization program that is solved pointwise in time to ensure safety. Since sum-of-squares programs can be computationally prohibitive, we next propose an approach that instead considers a finite number of points sampled on the extent boundary. The result is a quadratic program for guaranteed safety that retains the computational advantage of traditional barrier functions. While this alternative is generally more conservative than the sum-of-squares approach, we show that conservatism is reduced by increasing the number of sampled points. Simulation and robotic implementation results are provided.
The ultrafast Kerr effect in anisotropic and dispersive media

The ultrafast optical Kerr effect (OKE) is widely used to investigate the structural dynamics and interactions of liquids, solutions, and solids by observing their intrinsic nonlinear temporal responses through nearly collinear four-wave mixing. Non-degenerate mixing schemes allow for background free detection and can provide information on the interplay between a material's internal degrees of freedom. Here, we show a source of temporal dynamics in the OKE signal that is not reflective of the internal degrees of freedom but arises from a group index and momentum mismatch. It is observed in two-color experiments on condensed media with sizable spectral dispersion, a common property near an optical resonance. In particular, birefringence in crystalline solids is able to entirely change the character of the OKE signal via the off-diagonal tensor elements of the nonlinear susceptibility. We develop a detailed description of the phase-mismatched ultrafast OKE and show how to extract quantitative information on the spectrally resolved birefringence and group index from time-resolved experiments in one and two dimensions.
SMAC: Symbiotic Multi-Agent Construction

We present a novel concept of a heterogeneous, distributed platform for autonomous 3D construction. The platform is composed of two types of robots acting in a coordinated and complementary fashion: (i) A collection of communicating smart construction blocks behaving as a form of growable smart matter, and capable of planning and monitoring their own state and the construction progress; and (ii) A team of inchworm-inspired builder robots designed to navigate and modify the 3D structure, following the guidance of the smart blocks. We describe the design of the hardware and introduce algorithms for navigation and construction that support a wide class of 3D structures. We demonstrate the capabilities of our concept and characterize its performance through simulations and real-robot experiments.
Gaussian Function On Response Surface Estimation

We propose a new framework for 2-D interpreting (features and samples) black-box machine learning models via a metamodeling technique, by which we study the output and input relationships of the underlying machine learning model. The metamodel can be estimated from data generated via a trained complex model by running the computer experiment on samples of data in the region of interest. We utilize a Gaussian process as a surrogate to capture the response surface of a complex model, in which we incorporate two parts in the process: interpolated values that are modeled by a stationary Gaussian process Z governed by a prior covariance function, and a mean function µ that captures the known trends in the underlying model. The optimization procedure for the variable importance parameter θ is to maximize the likelihood function. This θ corresponds to the correlation of individual variables with the target response. There is no need for any pre-assumed models since it depends on empirical observations. Experiments demonstrate the potential of the interpretable model through quantitative assessment of the predicted samples.
Pin assignment and routing on a single-layer pin grid array

PGA routing has the freedom of routing any pin to any pad. We propose an algorithm (EVENPGA) that generates a monotonic topological routing. The routing has no detours and is uniformly distributed optimally. The wire length is also the shortest possible under the taxicab wiring metric. If the topological routing is routable, the maximum density of critical cuts along a ring is the minimum possible. Once the topological routing is done, physical layout can easily be obtained using Surf, a rubberband-based routing system.
Tort Law's Deterrent Effect and Procedural Due Process

The defendants in Philip Morris USA v. Williams and Wal-Mart Stores, Inc. v. Dukes claimed a right to present defenses. The defendants also both claimed that the mechanisms in place in those cases—the consideration of nonparties in imposing punitive damages and the use of sampling to litigate a large class action—violated that right. The Supreme Court agreed, a death knell for the advocated use of both mechanisms to counteract tort law’s under-litigation problem: the fact that not all injured persons sue, precluding tort law’s ability to achieve effective deterrence. This Article argues that procedural due process theories do not support such a right. The process-based theory provides only a flexible level of participation and the defendants in both Philip Morris and Dukes had a meaningful opportunity to participate. The outcome-based theory also does not support such a right because the total damage obligations produced by the mechanisms are actually accurate. Even though no procedural due process right precludes the consideration of nonparties and sampling, the mechanisms are still problematic because of how they shift the burden of proof. The burden, however, is based in substantive law; substantive law can be changed to help alleviate the harmful effects of tort law’s under-litigation problem.
Diffeomorphism Stability and Codimension Three

Given $$k\in \mathbb {R}$$ , v, $$D>0$$ , and $$n\in \mathbb {N}$$ , let $$\left\{ M_{\alpha }\right\} _{\alpha =1}^{\infty }$$ be a Gromov–Hausdorff convergent sequence of Riemannian n–manifolds with sectional curvature $$\ge k$$ , volume $$>v$$ , and diameter $$\le D$$ . Perelman’s Stability Theorem implies that all but finitely many of the $$M_{\alpha }$$ s are homeomorphic. The Diffeomorphism Stability Question asks whether all but finitely many of the $$ M_{\alpha }$$ s are diffeomorphic. We answer this question affirmatively in the special case when all of the singularities of the limit space occur along Riemannian manifolds of codimension $$\le 3$$ . We then describe several applications. For instance, if the limit space is an orbit space whose singular strata are of codimension $$\le 3$$ , then all but finitely many of the $$M_{\alpha }$$ s are diffeomorphic.
Forecasting e-scooter substitution of direct and access trips by mode and distance

Abstract An e-scooter trip model is estimated from four U.S. cities: Portland, Austin, Chicago and New York City. A log–log regression model is estimated for e-scooter trips based on user age, population, land area, and the number of scooters. The model predicts 75 K daily e-scooter trips in Manhattan for a deployment of 2000 scooters, which translates to 77 million USD in annual revenue. We propose a novel nonlinear, multifactor model to break down the number of daily trips by the alternative modes of transportation that they would likely substitute based on statistical similarity. The model parameters reveal a relationship with direct trips of bike, walk, carpool, automobile and taxi as well as access/egress trips with public transit in Manhattan. Our model estimates that e-scooters could replace 32% of carpool; 13% of bike; and 7.2% of taxi trips. The distance structure of revenue from access/egress trips is found to differ from that of other substituted trips.
Injective stabilization of additive functors, III. Asymptotic stabilization of the tensor product

The injective stabilization of the tensor product is subjected to an iterative procedure that utilizes its bifunctor property. The limit of this procedure, called the asymptotic stabilization of the tensor product, provides a homological counterpart of Buchweitz's asymptotic construction of stable cohomology. The resulting connected sequence of functors is isomorphic to Triulzi's \(J\)-completion of the Tor functor. A comparison map from Vogel homology to the asymptotic stabilization of the tensor product is constructed and shown to be always epic. The category of finitely presented functors is shown to be complete and cocomplete. As a consequence, the inert injective stabilization of the tensor product with fixed variable a finitely generated module over an artin algebra is shown to be finitely presented. Its defect and consequently all right-derived functors are determined. New notions of asymptotic torsion and cotorsion are introduced and are related to each other.
ALOGTIME and a conjecture of S.A. Cook

Usingsequential, machine-independent characterization of theparallel complexity classesAC k andNC k , we establish the following conjecture of S.A. Cook. There is a free variable equational logicALV with the property thatif f, g are function symbols forALOGTIME computable functions for which “f=g” is provable inALV, then there are polynomial size Frege proofs for the infinite family {|f=g| n :n, m∈ℕ} of propositional tautologies. Here, the propositional formula |f=g| expresses the equality off andg on inputs of length at mostn, provided that the function values are of length at mostm. We establish a related result with constant formula-depth polynomial size Frege proofs for a systemAV related to uniformAC 0 functions.
Embryo CHH hypermethylation is mediated by RdDM and is autonomously directed in Brassica rapa

RNA-directed DNA methylation (RdDM) initiates cytosine methylation in all contexts and maintains asymmetric CHH methylation. Mature plant embryos show one of the highest levels of CHH methylation, and it has been suggested that RdDM is responsible for this hypermethylation. Because loss of RdDM in Brassica rapa causes seed abortion, embryo methylation might play a role in seed development. RdDM is required in the maternal sporophyte, suggesting that small RNAs from the maternal sporophyte might translocate to the developing embryo, triggering DNA methylation that prevents seed abortion. This raises the question of whether embryo hypermethylation is autonomously regulated by the embryo itself or influenced by the maternal sporophyte. Here, we demonstrate that B. rapa embryos are hypermethylated in both euchromatin and heterochromatin and that this process requires RdDM. Contrary to the current models, B. rapa embryo hypermethylation is not correlated with demethylation of the endosperm. We also show that maternal somatic RdDM is not sufficient for global embryo hypermethylation, and we find no compelling evidence for maternal somatic influence over embryo methylation at any locus. Decoupling of maternal and zygotic RdDM leads to successful seed development despite the loss of embryo CHH hypermethylation. We conclude that embryo CHH hypermethylation is conserved, autonomously controlled, and not required for embryo development. Furthermore, maternal somatic RdDM, while required for seed development, does not directly influence embryo methylation patterns.
Optimizing Demand-Responsive Paratransit Operations: A Mixed Integer Programming Approach

The traditional demand-responsive paratransit system plays an important role in connecting people to health care, particularly those who are carless, low-income, over age 65, underinsured/uninsured, or who have a disability. However, the existing paratransit system usually has low service quality due to long waiting times, low operation frequencies, and high costs. In order to improve the service quality, we propose to design a new demand-responsive paratransit system that offers public, Uber-like options for non-emergency medical transportation. We developed mixed integer programming models to optimize the system operations with the objectives of minimizing waiting times for riders as well as operating costs for operators. The results produced in this paper will assist local departments of transportation and transit agencies as they consider operational strategies to meet non-emergency medical transport needs.
Macroscopic forcing method: A tool for turbulence modeling and analysis of closures

We present a numerical procedure, which we call the macroscopic forcing method (MFM), which reveals the differential operators acting upon the mean fields of quantities transported by underlying fluctuating flows. More broadly, MFM can reveal differential operators associated with turbulence closure for scalar and momentum transport. We present MFM using canonical problems with increasing complexity, from a simple parallel flow to a complex nonhomogeneous flow, and show its efficacy, which can be utilized for quantitative understanding of non-Boussinesq effects and assessment of model forms in turbulence closures.
Labor Regulation as Family Regulation: Decent Work and Decent Families

It is due time that we understood that regulating the family has been a longstanding goal of labor regulation. This article presents the trajectory of labor regulation as family regulation. It provides a history of the “decent standards” discourse pertaining to wage and hour regulation, and reveals its double meanings: to provide “decent work” and to promote “decent families.” It terms the goal of providing decent standards of work and wages as “productive decency” and the goals pertaining to family decency, proper gender norms, and sexual purity as “repressive decency.” It shows how labor regulation surprisingly began in the Progressive Era as a means to lower divorce rates by fighting prostitution and address concerns over maternal functions and domestic roles in the family at the beginning of the 20th century, and how it culminated in the New Deal as reproducing the husband-asbreadwinner family model in the Fair Labor Standards Act of 1938. Despite the notion that federal law does not interfere in the personal relationship between husband and wife in such mundane and private issues as “who does the dishes,” regulating the family has, in fact, been a longstanding goal of labor regulation. Understanding labor regulation as regulating the family
The Price Effects of Event Risk Protection: The Results from a Natural Experiment

Prior studies conclude that bond prices reflect both an issuer's event risk and a bond's contractual protections from event risk. Therefore, it is assumed that the market requires a higher return for unprotected bonds than for comparable protected bonds. These prior studies, however, struggle with the problem of isolating the pricing effect by controlling for comparability. Issuers will differ from each other on a number of other attributes that could affect their bond prices. The issue of comparability eludes a simple modeling solution given the indefiniteness and multiplicity of variables that could cause the market to distinguish one issuer from another. Recent court decisions regarding the buyout of Bell Canada Enterprises provide a natural experiment for evaluating the pricing effect of event-risk protection that mitigates this comparability problem. Based on this experiment, we find support for the prior conclusions that an exogenous shift in event-risk protection is priced by the market.
HELIOS, A VTOL FLYING CAR

HELIos is a single seat, three wheel, vertical take-off and landing (VTOL) flying car concept. It uses duct enclosed counter-rotating propellers. This technology eliminates the need for a tail rotor and makes the vehicle more compact. It needs no modification to switch between drive mode and flight mode. It uses a modified motorcycle or snowmobile engine for road travel and a two-stroke, aircraft, diesel engine for air propulsion. It is flown by wire for directional control, and a helicopter pitch control is used for vertical motion. HELIos is equipped with a guidance control system for safe and precise flying. In emergency cases, the driver/pilot can employ a ballistic parachute, which allows the vehicle to float safely down to earth. It will be street legal under the rules of the Department of Transportation (DOT); its three-wheel design categorizes it in the motorcycle and scooter category. Table 1: Preliminary Design Data engine power cruise speed (air) range (air) cruise altitude cruise speed (road) range (road) 300 160 48
How inhibitory neurons increase information transmission under threshold modulation

Modulation of neuronal thresholds is ubiquitous in the brain. Phenomena such as figure-ground segmentation, motion detection, stimulus anticipation, and shifts in attention all involve changes in a neuron's threshold based on signals from larger scales than its primary inputs. However, this modulation reduces the accuracy with which neurons can represent their primary inputs, creating a mystery as to why threshold modulation is so widespread in the brain. We find that modulation is less detrimental than other forms of neuronal variability and that its negative effects can be nearly completely eliminated if modulation is applied selectively to sparsely responding neurons in a circuit by inhibitory neurons. We verify these predictions in the retina where we find that inhibitory amacrine cells selectively deliver modulation signals to sparsely responding ganglion cell types. Our findings elucidate the central role that inhibitory neurons play in maximizing information transmission under modulation.
Organizations as Artificial Intelligences: The Use of Artificial Intelligence Analogies in Organization Theory

A rarely acknowledged fact about organization theory (OT) is that many of its ideas stem from the field of artificial intelligence (AI). For example, key OT concepts such as problemistic search, he...
Designing non-segregating granular mixtures

In dense flowing bidisperse particle mixtures varying in size or density alone, large particles rise (driven by percolation) and heavy particles sink (driven by buoyancy). When the two particle species differ from each other in both size and density, the two segregation mechanisms either enhance (large/light and small/heavy) or oppose (large/heavy and small/light) each other. In the latter case, an equilibrium condition exists in which the two mechanisms balance and the particles no longer segregate. This leads to a methodology to design non-segregating particle mixtures by specifying particle size ratio, density ratio, and mixture concentration to achieve the equilibrium condition. Using DEM simulations of quasi-2D bounded heap flow, we show that segregation is significantly reduced for particle mixtures near the equilibrium condition. In addition, the rise-sink transition for a range of particle size and density ratios matches the predictions of the combined size and density segregation model.
The kernel trick for nonlinear factor modeling

Abstract Factor modeling is a powerful statistical technique that permits common dynamics to be captured in a large panel of data with a few latent variables, or factors, thus alleviating the curse of dimensionality. Despite its popularity and widespread use for various applications ranging from genomics to finance, this methodology has predominantly remained linear. This study estimates factors nonlinearly through the kernel method, which allows for flexible nonlinearities while still avoiding the curse of dimensionality. We focus on factor-augmented forecasting of a single time series in a high-dimensional setting, known as diffusion index forecasting in macroeconomics literature. Our main contribution is twofold. First, we show that the proposed estimator is consistent and it nests the linear principal component analysis estimator as well as some nonlinear estimators introduced in the literature as specific examples. Second, our empirical application to a classical macroeconomic dataset demonstrates that this approach can offer substantial advantages over mainstream methods.
Higher-order corrections for tW production at high-energy hadron colliders

We discuss cross sections for tW production in proton-proton collisions at the LHC and at higher-energy colliders with energies of up to 100 TeV. We find that, remarkably, the soft-gluon corrections are numerically dominant even at very high collider energies. We present results with soft-gluon corrections at approximate NNLO and approximate N3LO matched to complete NLO results. These higher-order corrections are large and need to be included for better theoretical accuracy and smaller scale dependence. Total cross sections as well as top-quark and W-boson transverse-momentum and rapidity distributions are presented using various recent sets of parton distribution functions.
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset

We present a new dataset of Wikipedia articles each paired with a knowledge graph, to facilitate the research in conditional text generation, graph generation and graph representation learning. Existing graph-text paired datasets typically contain small graphs and short text (1 or few sentences), thus limiting the capabilities of the models that can be learned on the data. Our new dataset WikiGraphs is collected by pairing each Wikipedia article from the established WikiText-103 benchmark (Merity et al., 2016) with a subgraph from the Freebase knowledge graph (Bollacker et al., 2008). This makes it easy to benchmark against other state-of-the-art text generative models that are capable of generating long paragraphs of coherent text. Both the graphs and the text data are of significantly larger scale compared to prior graph-text paired datasets. We present baseline graph neural network and transformer model results on our dataset for 3 tasks: graph -> text generation, graph -> text retrieval and text -> graph retrieval. We show that better conditioning on the graph provides gains in generation and retrieval quality but there is still large room for improvement.
PigPaxos: Devouring the Communication Bottlenecks in Distributed Consensus

Strongly consistent replication helps keep application logic simple and provides significant benefits for correctness and manageability. Unfortunately, the adoption of strongly-consistent replication protocols has been curbed due to their limited scalability and performance. To alleviate the leader bottleneck in strongly-consistent replication protocols, we introduce Pig, an in-protocol communication aggregation and piggybacking technique. Pig employs randomly selected nodes from follower subgroups to relay the leader's message to the rest of the followers in the subgroup, and to perform in-network aggregation of acknowledgments back from these followers. By randomly alternating the relay nodes across replication operations, Pig shields the relay nodes as well as the leader from becoming hotspots and improves throughput scalability. We showcase Pig in the context of classical Paxos protocols employed for strongly consistent replication by many cloud computing services and databases. We implement and evaluate PigPaxos, in comparison to Paxos and EPaxos protocols under various workloads over clusters of size 5 to 25 nodes. We show that the aggregation at the relay has little latency overhead, and PigPaxos can provide more than 3 folds improved throughput over Paxos and EPaxos with little latency deterioration. We support our experimental observations with the analytical modeling of the bottlenecks and show that the communication bottlenecks are minimized when employing only one randomly rotating relay node.
The Limit Shape of the Leaky Abelian Sandpile Model

The leaky abelian sandpile model (Leaky-ASM) is a growth model in which $n$ grains of sand start at the origin in $\mathbb{Z}^2$ and diffuse along the vertices according to a toppling rule. A site can topple if its amount of sand is above a threshold. In each topple a site sends some sand to each neighbor and leaks a portion $1-1/d$ of its sand. We compute the limit shape as a function of $d$ in the symmetric case where each topple sends an equal amount of sand to each neighbor. The limit shape converges to a circle as $d\to 1$ and a diamond as $d\to\infty$. We compute the limit shape by comparing the odometer function at a site to the probability that a killed random walk dies at that site. When $d\to 1$ the Leaky-ASM converges to the abelian sandpile model (ASM) with a modified initial configuration. We also prove the limit shape is a circle when simultaneously with $n\to\infty$ we have that $d=d_n$ converges to $1$ slower than any power of $n$. To gain information about the ASM faster convergence is necessary.
Towards a quantization of the double via the enhanced symplectic “category”

This paper considers the enhanced symplectic “category” for purposes of quantizing quasi-Hamiltonian (G)-spaces, where (G) is a compact simple Lie group. Our starting point is the well-acknowledged analogy between the cotangent bundle $$T^*G$$ in Hamiltonian geometry and the internally fused double $$D(G)=G\times G$$ in quasi-Hamiltonian geometry. Guillemin and Sternberg consider the former, studying half-densities and phase functions on its so-called character Lagrangians $$\Lambda _{{\mathcal {O}}}\subseteq T^*G$$ . Our quasi-Hamiltonian counterpart replaces these character Lagrangians with the universal centralizers $$\Lambda _{{\mathcal {C}}}\longrightarrow {\mathcal {C}}$$ of regular, $$\frac{1}{k}$$ -integral conjugacy classes $${\mathcal {C}}\subseteq G$$ . We show each universal centralizer to be a “quasi-Hamiltonian Lagrangian” in D(G) and to come equipped with a half-density and phase function. At the same time, we consider a Dehn twist-induced automorphism $$R:D(G)\longrightarrow D(G)$$ that lacks a natural Hamiltonian analogue. Each quasi-Hamiltonian Lagrangian $$R(\Lambda _{{\mathcal {C}}})$$ is shown to have a clean intersection with every $$\Lambda _{{\mathcal {C}}'}$$ , and to come equipped with a half-density and phase function of its own. This leads us to consider the possibility of a well-behaved, quasi-Hamiltonian notion of the BKS pairing between $$R(\Lambda _{{\mathcal {C}}})$$ and $$\Lambda _{{\mathcal {C}}'}$$ . We construct such a pairing and study its properties. This is facilitated by the nice geometric features of $$R(\Lambda _{{\mathcal {C}}})\cap \Lambda _{{\mathcal {C}}'}$$ and a reformulation of the classical BKS pairing. Our work is perhaps the first step towards a level-k quantization of D(G) via the enhanced symplectic “category”.
Capacity and Flexibility in Community College CTE Programs: Program Offerings and Student Success

This article asks whether small changes to community college courses and programs can help improve student outcomes. We use administrative data from the California Community College system, including millions of student records and detailed course-level information for most career-technical education programs in the state. We construct a summary measure of each program’s flexibility, incorporating many components of the availability and scheduling of its courses. We show considerable variation in this flexibility measure across programs and over time. An increase in a program’s flexibility is associated with increases in enrollment and completions, but not with changes in its completion rate.
Fast Sketching of Polynomial Kernels of Polynomial Degree

Kernel methods are fundamental in machine learning, and faster algorithms for kernel approximation provide direct speedups for many core tasks in machine learning. The polynomial kernel is especially important as other kernels can often be approximated by the polynomial kernel via a Taylor series expansion. Recent techniques in oblivious sketching reduce the dependence in the running time on the degree $q$ of the polynomial kernel from exponential to polynomial, which is useful for the Gaussian kernel, for which $q$ can be chosen to be polylogarithmic. However, for more slowly growing kernels, such as the neural tangent and arc-cosine kernels, $q$ needs to be polynomial, and previous work incurs a polynomial factor slowdown in the running time. We give a new oblivious sketch which greatly improves upon this running time, by removing the dependence on $q$ in the leading order term. Combined with a novel sampling scheme, we give the fastest algorithms for approximating a large family of slow-growing kernels.
Polyfold regularization of constrained moduli spaces

We introduce tame sc-Fredholm sections and slices of sc-Fredholm sections. A slice is a notion of subpolyfold that is compatible with the sc-Fredholm section and has finite locally constant codimension. We prove that the subspace of a tame polyfold that satisfies a transverse sc-smooth constraint in a finite dimensional smooth manifold is a slice of any tame sc-Fredholm section compatible with the constraint. Moreover, we prove that a sc-Fredholm section restricted to a slice is a tame sc-Fredholm section with a drop in Fredholm index given by the codimension of the slice. As a corollary, we obtain fiber products of tame sc-Fredholm sections. We describe applications to Gromov-Witten invariants, constructing the Piunikhin-Salamon-Schwarz maps for general closed symplectic manifolds, and avoiding sphere bubbles in moduli spaces of expected dimension $0$ and $1$.
Worldwide variations in the lifetime probability of reproductive cancer in women: Implications of best-case, worst-case, and likely-case assumptions about the effect of oral contraceptive use

Abstract Cancer incidence in countries representative of three patterns of reproductive cancer and age-specific mortality was used to estimate the effect of oral contraceptive use on the lifetime probability of reproductive cancer under three sets of assumptions about the effects of oral contraceptives. Under the set of assumptions considered likely, oral contraceptives were estimated to reduce or increase only slightly the lifetime probability of any reproductive cancer in each setting. Under worst-case assumptions, oral contraceptives were estimated to increase the lifetime probability of reproductive cancer only modestly in settings with low cancer rates and in settings with high rates of breast, ovarian, and endometrial cancer, but it might have a large impact on lifetime probability of reproductive cancer in settings with high cervical cancer rates. Under best-case assumptions, oral contraceptives were estimated to decrease the lifetime probability of reproductive cancer in each setting; this reduction was estimated to be greatest in settings where endometrial and ovarian cancer incidence are high.