cssi/SciSciGPT-SciSciNet huggingface dataset:
Cryptic and extensive hybridization between ancient lineages of American crows

Most species and therefore most hybrid zones have historically been defined using phenotypic characters. However, both speciation and hybridization can occur with negligible morphological differentiation. Recently developed genomic tools provide the means to better understand cryptic speciation and hybridization. The Northwestern Crow (Corvus caurinus) and American Crow (Corvus brachyrhynchos) are continuously distributed sister taxa that lack reliable traditional characters for identification. In this first population genomic study of Northwestern and American crows, we use genomic SNPs (nuDNA) and mtDNA to investigate the degree of genetic differentiation between these crows and the extent to which they may hybridize. Our results indicate that American and Northwestern crows have distinct evolutionary histories, supported by two nuDNA ancestry clusters and two 1.1%-divergent mtDNA clades dating to the late Pleistocene, when glacial advances may have isolated crow populations in separate refugia. We document extensive hybridization, with geographic overlap of mtDNA clades and admixture of nuDNA across >900 km of western Washington and western British Columbia. This broad hybrid zone consists of late-generation hybrids and backcrosses, but not recent (e.g., F1) hybrids. Nuclear DNA and mtDNA clines had concordant widths and were both centred in southwestern British Columbia, farther north than previously postulated. Overall, our results suggest a history of reticulate evolution in American and Northwestern crows, perhaps due to recurring neutral expansion(s) from Pleistocene glacial refugia followed by lineage fusion(s). However, we do not rule out a contributing role for more recent potential drivers of hybridization, such as expansion into human-modified habitats.
The Kindness of Commenters: An Empirical Study of the Effectiveness of Perceived and Received Support for Weight‐Loss Outcomes

Social media‐based online communities are becoming increasingly popular for various social interactions, including those for healthcare and health‐related activities. The benefits from these activities, however, are constrained by how a platform is designed, as a platform's design defines what activities can be done and how individuals can engage and interact on the platform. In this study, we focus on weight‐loss communities and social tools that facilitate social communication and establish a variety of relationships between users. In particular, we examine the effectiveness of one‐way and two‐way social relationships on individuals’ weight‐loss management. Drawing from theories of social support, social reciprocity, and social indebtedness, we use two‐way friendship relationships to proxy perceived support and one‐way commenting relationships to proxy received support and conjecture that they work through different pathways. We find, through empirical analyses, that both types of social relationships as well as self‐monitoring are effective in promoting weight loss, but perceived and received support have different impacts. Whereas both perceived and received support are positively related to weight‐loss outcomes, the effect of received support is found to be higher than that of perceived support and the difference is statistically significant. Moreover, we find that received support is positively associated with self‐monitoring behaviors, whereas perceived support is not. These findings provide insights for platform providers to improve the social design aspect of online services and for healthcare practitioners in their efforts to advise individuals on weight self‐management. Our results also can be used to design and implement more effective online interventions.
Kawaguchi-Silverman conjecture for endomorphisms on several classes of varieties

Abstract We prove Kawaguchi-Silverman conjecture (KSC) and Shibata's conjecture on ample canonical heights for endomorphisms on several classes of algebraic varieties including varieties of Fano type and projective toric varieties. We also prove KSC for group endomorphisms of linear algebraic groups. We also propose a possible approach to the conjecture using equivariant MMP.
WOTBoost: Weighted Oversampling Technique in Boosting for imbalanced learning

Machine learning classifiers often stumble over imbalanced datasets where classes are not equally represented. This inherent bias towards the majority class may result in low accuracy in labeling minority class. Imbalanced learning is prevalent in many real-world applications, such as medical research, network intrusion detection, and fraud detection in credit card transactions, etc. A good number of research works have been reported to tackle this challenging problem. For example, Synthetic Minority Over-sampling TEchnique (SMOTE) and ADAptive SYNthetic sampling approach (ADASYN) use oversampling techniques to balance the skewed datasets. In this paper, we propose a novel method that combines a Weighted Oversampling Technique and ensemble Boosting method (WOT-Boost) to improve the classification accuracy of minority data without sacrificing the accuracy of the majority class. WOTBoost adjusts its oversampling strategy at each round of boosting to synthesize more targeted minority data samples. The adjustment is enforced using a weighted distribution. We compare WOTBoost with other four classification models (i.e., decision tree, SMOTE + decision tree, ADASYN + decision tree, SMOTEBoost) extensively on 18 public accessible imbalanced datasets. WOTBoost achieves the best G mean on 6 datasets and highest AUC score on 7 datasets.
Does a big bazooka matter? Quantitative easing policies and exchange rates

Abstract We estimate the effects of quantitative easing (QE) measures by the ECB and the Federal Reserve on the US dollar-euro exchange rate at frequencies and horizons relevant for policymakers. To do so, we derive a theoretically-consistent local projection regression equation from the standard asset pricing formulation of exchange rate determination. We then proxy unobserved QE shocks by future changes in the relative size of central banks’ balance sheets, which we instrument with QE announcements in two-stage least squares regressions in order to account for their endogeneity. We find that QE measures have large and persistent effects on the exchange rate: The typical ECB or Federal Reserve expansionary QE announcement in our sample resulted in an increase in the relative balance sheet of about 20% and, in turn, in a persistent exchange rate depreciation of around 7%. Regarding transmission channels, we find that a relative QE shock that expands the ECB’s balance sheet relative to that of the Federal Reserve depreciates the euro against the US dollar by reducing euro-dollar short-term money market rate differentials, by widening the cross-currency basis and by eliciting adjustments in “residual” deviations from interest parity. Changes in the expectations about the future monetary policy stance, reflecting the “signalling” channel of QE, also contribute to the exchange rate response to QE shocks.
Dissecting the economic impact of soybean diseases in the United States over two decades.

Soybean (Glycine max L. Merrill) is an economically important commodity for United States agriculture. Nonetheless, the profitability of soybean production has been negatively impacted by soybean diseases. The economic impacts of 23 common soybean diseases were estimated in 28 soybean-producing states in the U.S., from 1996 to 2016 (the entire data set consisted of 13,524 data points). Estimated losses were investigated using a variety of statistical approaches. The main effects of state, year, pre- and post-discovery of soybean rust, region, and zones based on yield, harvest area, and production, were significant on “total economic loss” as a function of diseases. Across states and years, the soybean cyst nematode, charcoal rot, and seedling diseases were the most economically damaging diseases while soybean rust, bacterial blight, and southern blight were the least economically damaging. A significantly greater mean loss (51%) was observed in states/years after the discovery of soybean rust (2004 to 2016) compared to the pre-discovery (1996 to 2003). From 1996 to 2016, the total estimated economic loss due to soybean diseases in the U.S. was $95.48 billion, with $80.89 billion and $14.59 billion accounting for the northern and southern U.S. losses, respectively. Over the entire time period, the average annual economic loss due to soybean diseases in the U.S. reached nearly $4.55 billion, with approximately 85% of the losses occurring in the northern U.S. Low yield/harvest/production zones had significantly lower mean economic losses due to diseases in comparison to high yield/harvest/production zones. This observation was further bolstered by the observed positive linear correlation of mean soybean yield loss (in each state, due to all diseases considered in this study, across 21 years) with the mean state wide soybean production (MT), mean soybean yield (kg ha-1), and mean soybean harvest area (ha). Results of this investigation provide useful insights into how research, policy, and educational efforts should be prioritized in soybean disease management
The equivariant Ehrhart theory of the permutahedron

Equivariant Ehrhart theory enumerates the lattice points in a polytope with respect to a group action. Answering a question of Stapledon, we describe the equivariant Ehrhart theory of the permutahedron, and we prove his Effectiveness Conjecture in this special case.
Simultaneous current graph constructions for minimum triangulations and complete graph embeddings

The problems of calculating the genus of the complete graphs and of finding a minimum triangulation for each surface were both solved using the theory of current graphs, and each of them divided into twelve different cases, depending on the residue modulo 12 of the number of vertices. Cases 8 and 11 were of particular difficulty for both problems, with multiple families of current graphs developed to solve these cases. We solve these cases, in addition to Cases 6 and 9 , in a unified manner, greatly simplifying previous constructions by Ringel, Youngs, Guy, and Jungerman. All these new constructions are index 3 current graphs sharing nearly all of the structure of the simple solution for Case 5 of the Map Color Theorem.
Low-Rank MMWAVE MIMO Channel Estimation in One-Bit Receivers

Receivers with one-bit analog-to-digital converters (ADCs) are promising for high bandwidth millimeter wave (mmWave) systems as they consume less power than their full resolution counterparts. The extreme quantization in one-bit receivers and the use of large antenna arrays at mmWave make channel estimation challenging. In this paper, we develop channel estimation algorithms that exploit the low-rank property of mmWave channels. We also propose a novel training solution that results in a low complexity implementation of our algorithms. Simulation results indicate that the proposed methods achieve better channel reconstruction than compressed sensing-based techniques that exploit sparsity of mmWave channels.
Retrograde-rotating Exoplanets Experience Obliquity Excitations in an Eccentricity-enabled Resonance

Previous studies have shown that planets that rotate retrograde (backwards with respect to their orbital motion) generally experience less severe obliquity variations than those that rotate prograde (the same direction as their orbital motion). Here we examine retrograde-rotating planets on eccentric orbits and find a previously unknown secular spin-orbit resonance that can drive significant obliquity variations. This resonance occurs when the frequency of the planet's rotation axis precession becomes commensurate with an orbital eigenfrequency of the planetary system. The planet's eccentricity enables a participating orbital frequency through an interaction in which the apsidal precession of the planet's orbit causes a cyclic nutation of the planet's orbital angular momentum vector. The resulting orbital frequency follows the relationship $f = 2 \dot{\varpi} - \dot{\Omega}$, where $\dot{\varpi}$ and $\dot{\Omega}$ are the rates of the planet's changing longitude of periapsis and ascending node, respectively. We test this mechanism by simulating cases of a simple Earth-Jupiter system, and confirm the predicted resonance. Over the course of 100 Myr, the test Earths with rotation axis precession rates near the predicted resonant frequency experienced pronounced obliquity variations of order $10^\circ$-$30^\circ$. These variations can be significant, and suggest that while retrograde rotation is a stabilizing influence most of the time, retrograde rotators can experience large obliquity variations if they are on eccentric orbits and enter this spin-orbit resonance.
Why is Fertility on the Rise in Egypt? The Role of Women’s Employment Opportunities

Can declining employment opportunities for women reverse the fertility transition? This paper presents evidence that the demographic transition has not just stalled but in fact reversed in Egypt. After falling for decades, fertility rates increased. The paper examines the drivers of rising fertility rates, with a particular focus on the role of declining public sector employment opportunities for women. Estimates show the effect of public sector employment on the spacing and occurrence of births using discrete-time hazard models. The paper then uses the results to simulate total fertility rates. The models address the potential endogeneity of employment by incorporating woman-specific fixed effects, incorporating local employment opportunities rather than women’s own employment, and using local employment opportunities as an instrument. Results indicate that the decrease in public sector employment, which is particularly appealing to women, may have contributed to the rise in fertility but is unlikely to be its main cause.
Positive-Definite Functions, Exponential Sums and the Greedy Algorithm: a Curious Phenomenon

Abstract We describe a curious dynamical system that results in sequences of real numbers in [ 0 , 1 ] with seemingly remarkable properties. Let the even function f : T → R satisfy f ( k ) ≥ c | k | − 2 and define a sequence via x n = arg min x ∑ k = 1 n − 1 f ( x − x k ) . Such sequences ( x n ) n = 1 ∞ seem to be astonishingly regularly distributed in various ways (satisfying favorable exponential sum estimates; every interval J ⊂ [ 0 , 1 ] contains ∼ | J | n elements). We prove W 2 μ , ν ≤ c n , where μ = 1 n ∑ k = 1 n δ x k is the empirical distribution, ν = d x is the Lebesgue measure and W 2 ( μ , ν ) is the 2-Wasserstein distance between these two. Much stronger results seem to be true and it is an interesting problem to understand this dynamical system better. We obtain optimal results in dimension d ≥ 3 : using G ( x , y ) to denote the Green’s function of the Laplacian on a compact manifold, we show that x n = arg min x ∈ M ∑ k = 1 n − 1 G ( x , x k ) satisfies W 2 1 n ∑ k = 1 n δ x k , d x ≲ 1 n 1 ∕ d .
Functionality-Oriented Convolutional Filter Pruning

The sophisticated structure of Convolutional Neural Network (CNN) allows for outstanding performance, but at the cost of intensive computation. As significant redundancies inevitably present in such a structure, many works have been proposed to prune the convolutional filters for computation cost reduction. Although extremely effective, most works are based only on quantitative characteristics of the convolutional filters, and highly overlook the qualitative interpretation of individual filter's specific functionality. In this work, we interpreted the functionality and redundancy of the convolutional filters from different perspectives, and proposed a functionality-oriented filter pruning method. With extensive experiment results, we proved the convolutional filters' qualitative significance regardless of magnitude, demonstrated significant neural network redundancy due to repetitive filter functions, and analyzed the filter functionality defection under inappropriate retraining process. Such an interpretable pruning approach not only offers outstanding computation cost optimization over previous filter pruning methods, but also interprets filter pruning process.
A Microeconomic Framework for Evaluating Energy Efficiency Rebound And Some Implications

Improving energy efficiency can lower the cost of using energy-intensive goods and may create wealth from the energy savings, both of which lead to increased energy use, a "rebound" effect. I present a theoretical framework that parses rebound into economic income and substitution effects. The framework leads to new insights about the magnitude of rebound when goods are not priced at marginal cost and when consumers are imperfect optimizers, as well as the role of technological progress in rebound. I then explore the implications of this framework with illustrative calculations for improved auto fuel economy and lighting efficiency. These suggest that rebound is unlikely to more than offset the savings from energy efficiency investments (known as "backfire"), but rebound likely reduces the net savings by roughly 10% to 40% from these energy efficiency improvements.
Process Modeling and Integration of the Salicide Process Module for Sub-Half Micron Technology

Metal silicides have been used extensively in CMOS technology for reducing electrical resistance. As wafer-scale features have shrunk to the sub-half micron domain, obtaining a self-aligned silicide - or salicide - process that satisfies all requirements has become a significant challenge. One part of this challenge lies in developing the necessary scientific insights and technological innovations for the actual salicide process, while the other part lies in building a complete salicide process module which meets requirements of performance, reliability, ease of integration, control, etc. at the least possible cost and cycle-time for technology development. This second part is seldom addressed by researchers, and yet, is fundamentally important for successful application of any salicide technology to actual integrated circuit products. This paper presents a complete picture of the salicide module in the context of all the aforesaid components; and describes the use of abstraction and hierarchical models to capture process information and to facilitate process design. Prototype compact models for key wafer-state and performance outputs such as TiSi2 thickness and resistance are presented to demonstrate implementation of this process module.
Misconceptions and Political Outcomes

A large literature shows that strategic interactions among actors with conflicting objectives can cause the political process to produce outcomes that lower welfare. This paper investigates an alternative explanation of such outcomes: if individuals’ errors in assessing the likely effects of proposed policies are correlated, democratic decisionmaking can produce welfare-reducing outcomes even in the absence of conflicting objectives. Under plausible assumptions, choosing candidates from among the best informed individuals does not remedy the problems created by such errors, but subsidising information and exposing representatives to information after their election do. Concentration of power has ambiguous effects.
Cases Relating to Chapter 11 – Opinions and Expert Testimony

Publisher Summary This chapter presents several case studies related to opinions and expert testimony. These cases include the case of Bowling versus State, Osbourn versus State, and United States versus Delatorre. In the first case, jury found Daniel Bowling guilty of operating a boat while under the influence of alcohol to the extent it was less safe for him to do so. He appeals from his conviction, claiming the evidence was insufficient to show that he was a less safe driver, or that he was less safe as a result of being under the influence of alcohol. In the second case the appellant was convicted in a bench trial of possession of marihuana, a usable amount of less than two ounces. Punishment was assessed at twenty days' confinement in the county jail. The Court of Appeals affirmed the trial court's conviction. In the third case, Alberto Naranjo Delatorre appeals his convictions for conspiracy to possess with intent to distribute at least five kilograms of cocaine and aiding and abetting possession with intent to distribute at least five kilograms of cocaine. He asserts that there was insufficient evidence for the jury to convict him on either count and that the district court abused its discretion by permitting an expert witness to testify to matters outside the scope of her expertise.
8 – More Quadratic Equations

Publisher Summary This chapter discusses the solving of quadratic equations that cannot be factored. It presents a method of solving quadratic equations that is used on all quadratic equations, regardless of whether they are factorable. This method is applied to the general quadratic equation ax2 +bx + c = 0 and arrive at what is known as the quadratic formula. Any equation that is in the form ax2 +bx + c = 0, where a is not equal to 0, has as its solutions .The expression under the square root sign, b2 - 4ac, is known as the discriminant. When the discriminant is negative, the solutions are complex numbers.
Multi-state pair-density functional theory

Multi-configuration pair-density functional theory (MC-PDFT) has previously been applied successfully to carry out ground-state and excited-state calculations. However, because they include no interaction between electronic states, MC-PDFT calculations in which each state's PDFT energy is calculated separately can give an unphysical double crossing of potential energy surfaces (PESs) in a region near a conical intersection. We have recently proposed state-interaction pair-density functional theory (SI-PDFT) to treat nearly degenerate states by creating a set of intermediate states with state interaction; although this method is successful, it is inconvenient because two SCF calculations and two sets of orbitals are required and because it puts the ground state on an unequal footing with the excited states. Here we propose two new methods, called extended-multi-state-PDFT (XMS-PDFT) and variational-multi-state-PDFT (VMS-PDFT), that generate the intermediate states in a balanced way with a single set of orbitals. The former uses the intermediate states proposed by Granovsky for extended multi-configuration quasi-degenerate perturbation theory (XMC-QDPT); the latter obtains the intermediate states by maximizing the sum of the MC-PDFT energies for the intermediate states. We also propose a Fourier series expansion to make the variational optimizations of the VMS-PDFT method convenient, and we implement this method (FMS-PDFT) both for conventional configuration-interaction solvers and for density-matrix-renormalization-group solvers. The new methods are tested for eight systems, exhibiting avoided crossings among two to six states. The FMS-PDFT method is successful for all cases for which it has been tested (all cases in this paper except O3 for which it was not tested), and XMS-PDFT is successful for all eight cases except the mixed-valence case. Since both XMS-PDFT and VMS-PDFT are less expensive than XMS-CASPT2, they will allow well-correlated calculations on much larger systems for which perturbation theory is unaffordable.
A “Primarily Property” Presumption Is—Still —Really Needed for the IP/Antitrust Interface

Antitrust discussions in the U.S. have a long tradition of describing intellectual property (IP)—primarily patents and copyrights—in unqualified terms of “monopoly”. Although there have been substantial efforts over the past two decades to pull back from this automatic association, the presumption of unqualified monopoly continues to appear in important legal decisions—as well as in legal and social sciences academic discussions—that involve IP. There is another place where these decisions and discussions might start: with a presumption that any IP is “primarily property”—albeit with some important distinctions that separate IP from “garden variety” tangible property and that raise the possibility of market power in some instances. This paper explores the important similarities—and differences—between “garden variety” property, such as real estate, and IP; it concludes that the similarities are substantial, so that the presumption that IP is “primarily property” is a reasonable alternative starting point for antitrust/IP discussions. It then discusses some beneficial differences that this alternative starting point could have made and/or could still make.
Why Compatibilists Cannot Resist Prepunishment: A Defense of Smilansky

Prepunishment is to hold a person morally responsible for a crime she has yet to commit. Punishing a person prior to committing a crime is considered wrong due to the fact that the crime has not yet in fact been committed; it is punishing the innocent. Prepunishment, therefore, is morally abhorrent. In a series of recent papers, Saul Smilansky (2007, 2008a, 2008b) argues that compatibilists cannot, in any principled way, reject the temptation to prepunish, which shows compatibilism to be a much more radical view, since it runs counter to our ordinary moral intuitions. Further, Smilansky argues that the common-sense objection – namely, that prepunishment is morally abhorrent – is unavailable to compatibilists because of the fact that one who has not yet committed a crime is a mere temporal matter bearing no moral significance (Robinson 2010, 590). Smilansky’s argument has met several objections, one of which, from Michael Robinson (2010), objects that compatibilists are not committed to prepunish in virtue of two pairs of principles that are available to compatibilists, and yet necessarily entail that prepunishment is inappropriate and unjustified. I argue that these two pairs of principles, which Robinson appeals to, are not as obvious as they seem, and their truth is open to dispute.
Paired Observations, Distribution Free Methods

Data are said to be paired if the ith observation on the first sample is naturally paired with the ith observation on the second sample. The objective in paired observations is to eliminate, to the extent possible, sources of extraneous variation. In behavioral studies, for example, paired observations may be employed to assess the effectiveness of a treatment or experimental procedure. Techniques often used to analyze paired observations include the McNemar Chi-square test, the paired t Test, the sign test, and the Wilcoxon Signed-Rank test. Keywords: Mc Nemar Chi-square test; paired observations; paired t Test; sign test; Wilcoxon Signed-Rank test
Genetic Signatures of Evolutionary Rescue by a Selective Sweep

One of the most useful models in population genetics is that of a selective sweep and the consequent hitch-hiking of linked neutral alleles. While variations on this model typically assume constant population size, many instances of strong selection and rapid adaptation in nature may co-occur with complex demography. Here, we extend the hitch-hiking model to evolutionary rescue, where adaptation and demography not only co-occur but are intimately entwined. Our results show how this feedback between demography and evolution determines-and restricts-the genetic signatures of evolutionary rescue, and how these differ from the signatures of sweeps in populations of constant size. In particular, we find rescue to harden sweeps from standing variance or new mutation (but not from migration), reduce genetic diversity both at the selected site and genome-wide, and increase the range of observed Tajima's D values. For a given initial rate of population decline, the feedback between demography and evolution makes all of these differences more dramatic under weaker selection, where bottlenecks are prolonged. Nevertheless, it is likely difficult to infer the co-incident timing of the sweep and bottleneck from these simple signatures, never mind a feedback between them. Temporal samples spanning contemporary rescue events may offer one way forward.
Leading-Edge Flutter of Supercavitating Hydrofoils

This paper presents the results of experiments and analysis of the phenomenon of leading-edge flutter which has been observed to occur for supercavitating hydrofoils. The experiments confirmed the existence of such a single-degree-of-freedom flutter involving chordwise bending and indicated that for long, natural (or vapor-filled) cavities the reduced flutter speed, [formula], was in the range 0.15 to 0.23. Secondary effects observed were the variation with the angle of attack (a minimum flutter speed occurred at 10 deg) and with foil mass ratio. Shorter cavities typically yielded lower flutter speeds due to a complex interaction between the bubble collapse process occurring in the cavity closure region and the unsteady hydrodynamic load on the foil. Finally, a relatively simple theoretical analysis for supercavitating hydrofoils with elastic axes aft of midchord is presented. This linear analysis yields reduced flutter velocities somewhat lower than those observed.
Biocompatible Direct Deposition of Functionalized Nanoparticles Using Shrinking Surface Plasmonic Bubble

Functionalized nanoparticles (NPs) are the foundation of diverse applications, such as photonics, composites, energy conversion, and especially biosensors. In many biosensing applications, concentrating the higher density of NPs in the smaller spot without deteriorating biofunctions is usually an inevitable step to improve the detection limit, which remains to be a challenge. In this work, we demonstrate biocompatible deposition of functionalized NPs to an optically transparent surface using shrinking surface plasmonic bubbles. Leveraging the shrinking bubble can enable to mitigate any potential biomolecules degradation by strong photothermal effect, which has been a big obstacle of bridging plasmonic bubbles with biomolecules. The deposited NPs are closely packed in a micro-sized spot (as small as 3 μm), and the functional molecules are able to survive the process as verified by their strong fluorescence signals. We elucidate that the contracting contact line of the shrinking bubble forces the NPs captured by the contact line to a highly concentrated island. Such a shrinking surface bubble deposition (SSBD) is low temperature in nature as no heat is added during the process. Using a hairpin DNA-functionalized gold NP suspension as a model system, SSBD is shown to enable much stronger fluorescence signal compared to the optical pressure deposition and the conventional steady thermal bubble contact line deposition. The demonstrated SSBD technique capable of directly depositing functionalized NPs may benefit a wide range of applications, such as the manufacturing of multiplex biosensors.
Civic capital and social distancing during the Covid-19 pandemic

Using mobile phone and survey data, we show that during the early phases of COVID-19, voluntary social distancing was greater in areas with higher civic capital and amongst individuals exhibiting a higher sense of civic duty. This effect is robust to including controls for political ideology, income, age, education, and other local-level characteristics. This result is present for U.S. individuals and U.S. counties as well as European regions. Moreover, we show that after U.S. states began re-opening, high civic capital counties maintained a more sustained level of social distancing, while low civic capital counties did not. Finally, we show that U.S. individuals report a higher tendency to use protective face masks in high civic capital counties. Our evidence points to the importance of considering the level of civic capital in designing public policies not only in response to pandemics, but also more generally.
The Sexual Misconduct of Donald J. Trump: Toward a Misogyny Report

The numerous allegations of sexual misconduct — unwanted, unwelcome, and often aggressive sexual behavior — levied against Donald Trump merit attention and redress. Despite obstacles to civil remedies, there has been some litigation, but it has mostly been unsatisfactory. The many allegations reported in the media have not been amenable to judicial, legislative, executive, or political resolution. Women, including women who allege Trump committed sexual misconduct against them when they were minors, have generally not been afforded the remedies to which they are entitled. Because litigation and media accounts have proven inadequate to the task of addressing Trump’s sexual misconduct, there should be a government inquiry and resulting report. Such a report — a misogyny report focused on Donald Trump — would assist the nation in assessing and contextualizing the troubling and persistent allegations of his sexual misconduct. An inquiry and report could provide a forum for considering each individual woman affected and as part of a pattern of Trump’s conduct. Further, an inquiry and report could ameliorate the silencing of women — through isolation, threats, and nondisclosure agreements — and propose remedies to empower these women as well as other women. A misogyny report could also suggest specific correctives to obstacles in the path of bringing and completing litigation that could address the alleged sexual misconduct of Trump and ultimately of others. A government misogyny report initiated by Congress or some other governmental body, could provide a much-needed reckoning.
Reciprocal Learning Networks for Human Trajectory Prediction

We observe that the human trajectory is not only forward predictable, but also backward predictable. Both forward and backward trajectories follow the same social norms and obey the same physical constraints with the only difference in their time directions. Based on this unique property, we develop a new approach, called reciprocal learning, for human trajectory prediction. Two networks, forward and backward prediction networks, are tightly coupled, satisfying the reciprocal constraint, which allows them to be jointly learned. Based on this constraint, we borrow the concept of adversarial attacks of deep neural networks, which iteratively modifies the input of the network to match the given or forced network output, and develop a new method for network prediction, called reciprocal attack for matched prediction. It further improves the prediction accuracy. Our experimental results on benchmark datasets demonstrate that our new method outperforms the state-of-the-art methods for human trajectory prediction.
A FAST SIMPLE ALGORITHM FOR COMPUTING THE POTENTIAL OF CHARGES ON A LINE

Abstract We present a fast method for evaluating expressions of the form u j = ∑ i = 1 , i ≠ j n α i x i − x j , for j = 1 , … , n , where α i are real numbers, and x i are points in a compact interval of R . This expression can be viewed as representing the electrostatic potential generated by charges on a line in R 3 . While fast algorithms for computing the electrostatic potential of general distributions of charges in R 3 exist, in a number of situations in computational physics it is useful to have a simple and extremely fast method for evaluating the potential of charges on a line; we present such a method in this paper, and report numerical results for several examples.
Unpacking the Black Box of Translation: A framework for infusing spatial thinking into curricula

Spatial thinking skills are strongly correlated with achievement in Science, Technology, Engineering, and Mathematics (STEM) fields and emerging research suggests that interventions aimed at building students’ skills will likely yield measurable impacts on learning across K-12 settings. The importance of spatial thinking in science has received increased attention in academic discussions; however, the intentional practice of teaching spatial thinking skills is still largely absent from K-12 education. The translation of science into educational practice is challenging for a variety of reasons, including the difficulty “translating” research findings into practical applications and limited resources to support its development, implementation, and evaluation. Given these obstacles, one may ask “can spatial thinking be brought to the classroom?” In this paper, we argue that in order to effectively move research into the classroom, we must first systematically explore how spatial thinking can be translated into practice. We present a use-inspired, integrative framework that draws upon planned action and translation science theories, as well as research from cognitive, developmental, educational, and implementation sciences, to guide the infusion of spatial thinking into science curricula. In the Knowledge Translation Framework (KTF), translation is conceived as a multistage process, proceeding through seven stages: (1) the identification of relevant disciplinary and contextual knowledge, (2) the synthesis and translation of knowledge into guidelines to support the infusion of knowledge into the curriculum, (3) the development of tools to support curriculum development, implementation, and track the translation process, (4) the iterative development and refinement of the spatially-enhanced curriculum, (5) the creation of an analysis plan to evaluate the impact of the spatial enhancements and other contextual features on learning, (6) the development and implementation of an intervention plan, and (7) the evaluation of the intervention. The KTF is a use-inspired, integrative framework that unpacks the translation process and offers practical guidance on how a team may synthesize scientific and contextual knowledge, infuse it into a curriculum, and evaluate its impact in ways that will yield scientific understanding and practical knowledge. We also provide illustrative examples of how this approach was used to spatially enhance an elementary science curriculum.
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot Parallel Play.

We consider shared workspace scenarios with humans and robots acting to achieve independent goals, termed as parallel play. We model these as general-sum games and construct a framework that utilizes the Nash equilibrium solution concept to consider the interactive effect of both agents while planning. We find multiple Pareto-optimal equilibria in these tasks. We hypothesize that people act by choosing an equilibrium based on social norms and their personalities. To enable coordination, we infer the equilibrium online using a probabilistic model that includes these two factors and use it to select the robot's action. We apply our approach to a close-proximity pick-and-place task involving a robot and a simulated human with three potential behaviors - defensive, selfish, and norm-following. We showed that using a Bayesian approach to infer the equilibrium enables the robot to complete the task with less than half the number of collisions while also reducing the task execution time as compared to the best baseline. We also performed a study with human participants interacting either with other humans or with different robot agents and observed that our proposed approach performs similar to human-human parallel play interactions. The code is available at this https URL
Near-Optimal Algorithms for Shortest Paths in Weighted Unit-Disk Graphs

We revisit a classical graph-theoretic problem, the single-source shortest-path (SSSP) problem, in weighted unit-disk graphs. We first propose an exact (and deterministic) algorithm which solves the problem in $$O(n\log ^2\!n)$$ time using linear space, where n is the number of the vertices of the graph. This significantly improves the previous deterministic algorithm by Cabello and Jejcic [CGTA’15] which uses $$O(n^{1+\delta })$$ time and $$O(n^{1+\delta })$$ space (for any constant $$\delta >0$$ ) and the previous randomized algorithm by Kaplan et al. [SODA’17] which uses $$O(n\log ^{12+o(1)}\!n)$$ expected time and $$O(n\log ^3\!n)$$ space. More specifically, we show that if the 2D offline insertion-only (additively) weighted nearest-neighbor problem with k operations (i.e., insertions and queries) can be solved in f(k) time, then the SSSP problem in weighted unit-disk graphs can be solved in $$O(n\log n+f(n))$$ time. Using the same framework with some new ideas, we also obtain a $$(1+\varepsilon )$$ -approximate algorithm for the problem, using $$O(n\log n+n\log ^2(1/\varepsilon ))$$ time and linear space. This improves the previous $$(1+\varepsilon )$$ -approximate algorithm by Chan and Skrepetos [SoCG’18] which uses $$O((1/\varepsilon )^2n\log n)$$ time and $$O((1/\varepsilon )^2 n)$$ space. More specifically, we show that if the 2D offline insertion-only weighted nearest-neighbor problem with $$k_1$$ operations in which at most $$k_2$$ operations are insertions can be solved in $$f(k_1,k_2)$$ time, then the $$(1+\varepsilon )$$ -approximate SSSP problem in weighted unit-disk graphs can be solved in $$O(n\log n+f(n,O(\varepsilon ^{-2})))$$ time. Because of the $$\Omega (n\log n)$$ -time lower bound of the problem (even when approximation is allowed), both of our algorithms are almost optimal.
Direct materials deposition: Designed macro and microstructure

Solid freeform fabrication of engineering materials is now possible using the Direct Metal Deposition (DMD) technique. Closed loop optical feedback system for DMD makes realistic components with dimensional accuracy of 0.01 inch. On the other hand, close control of the process parameter can provide microstructure of choice. Such continued capability to control macro and microstructure is creating considerable interest. H13 tool steel is one of the difficult alloys for deposition due to residual stress accumulation from martensitic transformation. However, it is the material of choice for the die and tool industry. DMD offers Copper chill blocks and water cooling channels as the integral part of the tool. On the other hand ZrO2 was co-deposited with nickel superalloys using DMD. This process thus is amenable to produce both macro and microstructure to a designed specification. This paper briefly reviews the state of the art of DMD and describes the microstructure and mechanical properties of selected engineering alloy systems deposited by DMD.
Shared Autonomy with Learned Latent Actions.

Assistive robots enable people with disabilities to conduct everyday tasks on their own. However, these tasks can be complex, containing both coarse reaching motions and fine-grained manipulation. For example, when eating, not only does one need to move to the correct food item, but they must also precisely manipulate the food in different ways (e.g., cutting, stabbing, scooping). Shared autonomy methods make robot teleoperation safer and more precise by arbitrating user inputs with robot controls. However, these works have focused mainly on the high-level task of reaching a goal from a discrete set, while largely ignoring manipulation of objects at that goal. Meanwhile, dimensionality reduction techniques for teleoperation map useful high-dimensional robot actions into an intuitive low-dimensional controller, but it is unclear if these methods can achieve the requisite precision for tasks like eating. Our insight is that---by combining intuitive embeddings from learned latent actions with robotic assistance from shared autonomy---we can enable precise assistive manipulation. In this work, we adopt learned latent actions for shared autonomy by proposing a new model structure that changes the meaning of the human's input based on the robot's confidence of the goal. We show convergence bounds on the robot's distance to the most likely goal, and develop a training procedure to learn a controller that is able to move between goals even in the presence of shared autonomy. We evaluate our method in simulations and an eating user study. See videos of our experiments here: this https URL
Cutting in-line with iron: ribosomal function and non-oxidative RNA cleavage

Divalent metal cations are essential to the structure and function of the ribosome. Previous characterizations of the ribosome performed under standard laboratory conditions have implicated Mg2+ as a primary mediator of ribosomal structure and function. Possible contributions of Fe2+ as a ribosomal cofactor have been largely overlooked, despite the ribosome's early evolution in a high Fe2+ environment, and the continued use of Fe2+ by obligate anaerobes inhabiting high Fe2+ niches. Here, we show that (i) Fe2+ cleaves RNA by in-line cleavage, a non-oxidative mechanism that has not previously been shown experimentally for this metal, (ii) the first-order in-line rate constant with respect to divalent cations is >200 times greater with Fe2+ than with Mg2+, (iii) functional ribosomes are associated with Fe2+ after purification from cells grown under low O2 and high Fe2+ and (iv) a small fraction of Fe2+ that is associated with the ribosome is not exchangeable with surrounding divalent cations, presumably because those ions are tightly coordinated by rRNA and deeply buried in the ribosome. In total, these results expand the ancient role of iron in biochemistry and highlight a possible new mechanism of iron toxicity.
Joint Employment in the United States

The joint-employer doctrine in the United States is as fissured as the economy itself. As this paper’s brief survey of the different joint-employer standards used in the U.S. shows, the diverse set of work laws and governing authorities involved in workplace disputes have led to an unpredictable and confusing set of joint-employer standards.Although most of these standards share similarities, there are numerous differences based on the statute involved, whether the dispute is brought under federal or state law, which federal court is hearing the case, and which political party controls a relevant agency. Moreover, thanks in large part to a labor law action against McDonald’s, the joint-employer doctrine has become a politically charged issue, leading several federal agencies recently to change their approach to the question. As a result, businesses and workers cannot be certain that the relevant joint employer standard that exists today will be the same one that applies later. In short, joint employment in the U.S. consists of a complex set of standards that lack clarity and predictability, imposing costs on businesses and workers alike.
Neurokinin 1 receptor activation in the rat spinal cord maintains latent sensitization, a model of inflammatory and neuropathic chronic pain

Abstract Latent sensitization is a model of chronic pain in which a persistent state of pain hypersensitivity is suppressed by opioid receptors, as evidenced by the ability of opioid antagonists to induce a period of mechanical allodynia. Our objective was to determine if substance P and its neurokinin 1 receptor (NK1R) mediate the maintenance of latent sensitization. Latent sensitization was induced by injecting rats in the hindpaw with complete Freund's adjuvant (CFA), or by tibial spared nerve injury (SNI). When responses to von Frey filaments returned to baseline (day 28), the rats were injected intrathecally with saline or the NK1R antagonist RP67580, followed 15 min later by intrathecal naltrexone. In both pain models, the saline-injected rats developed allodynia for 2 h after naltrexone, but not the RP67580-injected rats. Saline or RP67580 were injected daily for two more days. Five days later (day 35), naltrexone was injected intrathecally. Again, the saline-injected rats, but not the RP67580-injected rats, developed allodynia in response to naltrexone. To determine if there is sustained activation of NK1Rs during latent sensitization, NK1R internalization was measured in lamina I neurons in rats injected in the paw with saline or CFA, and then injected intrathecally with saline or naltrexone on day 28. The rats injected with CFA had a small amount of NK1R internalization that was significantly higher than in the saline-injected rats. Naltrexone increased NK1R internalization in the CFA-injected rats but nor in the saline-injected rats. Therefore, sustained activation of NK1Rs maintains pain hypersensitivity during latent sensitization.