cssi/SciSciGPT-SciSciNet huggingface dataset:
Comprehensive Synthetic Genetic Array Analysis of Alleles That Interact with Mutation of the Saccharomyces cerevisiae RecQ Helicases Hrq1 and Sgs1.

Most eukaryotic genomes encode multiple RecQ family helicases, including five such enzymes in humans. For many years, the yeast Saccharomyces cerevisiae was considered unusual in that it only contained a single RecQ helicase, named Sgs1. However, it has recently been discovered that a second RecQ helicase, called Hrq1, resides in yeast. Both Hrq1 and Sgs1 are involved in genome integrity, functioning in processes such as DNA inter-strand crosslink repair, double-strand break repair, and telomere maintenance. However, it is unknown if these enzymes interact at a genetic, physical, or functional level as demonstrated for their human homologs. Thus, we performed synthetic genetic array (SGA) analyses of hrq1Δ and sgs1Δ mutants. As inactive alleles of helicases can demonstrate dominant phenotypes, we also performed SGA analyses on the hrq1-K318A and sgs1-K706A ATPase/helicase-null mutants, as well as all combinations of deletion and inactive double mutants. We crossed these eight query strains (hrq1Δ, sgs1Δ, hrq1-K318A, sgs1-K706A, hrq1Δ sgs1Δ, hrq1Δ sgs1-K706A, hrq1-K318A sgs1Δ, and hrq1-K318A sgs1-K706A) to the S. cerevisiae single gene deletion and temperature-sensitive allele collections to generate double and triple mutants and scored them for synthetic positive and negative genetic effects based on colony growth. These screens identified hundreds of synthetic interactions, supporting the known roles of Hrq1 and Sgs1 in DNA repair, as well as suggesting novel connections to rRNA processing, mitochondrial DNA maintenance, transcription, and lagging strand synthesis during DNA replication.
Stock-market disruptions and corporate disclosure policies

Abstract We examine managers’' disclosure decisions in response to non-fundamental price shocks. Using mutual fund fire sales as a source of market disruption, we show some firms respond by issuing earnings guidance. Others, especially firms with weaker performance and more short-term-oriented investors, engage in accrual-based earnings management. To identify the efficacy of firm disclosure choices, we examine passage of Sarbanes-Oxley and Regulation Fair Disclosure and show that they increased reliance on guidance rather than earnings management. The shift is associated with faster post-fire-sales price recovery, suggesting enhancing information disclosure rather than manipulation is effective in mitigating the effect of market disruptions.
Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models

Advances in deep neural networks (DNNs) have shown tremendous promise in the medical domain. However, the deep learning tools that are helping the domain, can also be used against it. Given the prevalence of fraud in the healthcare domain, it is important to consider the adversarial use of DNNs in manipulating sensitive data that is crucial to patient healthcare. In this work, we present the design and implementation of a DNN-based image translation attack on biomedical imagery. More specifically, we propose Jekyll, a neural style transfer framework that takes as input a biomedical image of a patient and translates it to a new image that indicates an attacker-chosen disease condition. The potential for fraudulent claims based on such generated ‘fake’ medical images is significant, and we demonstrate successful attacks on both X-rays and retinal fundus image modalities. We show that these attacks manage to mislead both medical professionals and algorithmic detection schemes. Lastly, we also investigate defensive measures based on machine learning to detect images generated by Jekyll.
STRONG [O III] OBJECTS AMONG SDSS BROAD-LINE ACTIVE GALAXIES

We present the results of a spectral principal component analysis on 9046 broad-line active galactic nuclei from the Sloan Digital Sky Survey. We examine correlations between spectral regions within various eigenspectra (e.g., between Fe II strength and Hβ width) and confirm that the same trends are apparent in spectral measurements, as validation of our technique. Because we found that our sample had a large range in the equivalent width of [O III] λ5007, we divided the data into three subsets based on [O III] strength. Of these, only in the sample with the weakest equivalent width of [O III] were we able to recover the known correlation between [O III] strength and full width at half maximum of Hβ and their anticorrelation with Fe II strength. At the low luminosities considered here (L 5100 A of 1042-1046 erg s–1), interpretation of the principal components is considerably complicated particularly because of the wide range in [O III] equivalent width. We speculate that variations in the covering factor are responsible for this wide range in [O III] strength.
Magellan/PFS Radial Velocities of GJ 9827, a Late K dwarf at 30 pc with Three Transiting Super-Earths

The Kepler mission showed us that planets with sizes between that of Earth and Neptune appear to be the most common type in our Galaxy. These "super-Earths" continue to be of great interest for exoplanet formation, evolution, and composition studies. However, the number of super-Earths with well-constrained mass and radius measurements remains small (40 planets with $\sigma_{\rm{mass}}<$ 25\%), due in part to the faintness of their host stars causing ground-based mass measurements to be challenging. Recently, three transiting super-Earth planets were detected by the K2 mission around the nearby star GJ 9827/HIP 115752, at only 30 pc away. The radii of the planets span the "radius gap"' detected by Fulton et al. (2017), and all orbit within ~6.5 days, easing follow-up observations. Here we report radial velocity (RV) observations of GJ 9827, taken between 2010 and 2016 with the Planet Finder Spectrograph on the Magellan II Telescope. We employ two different RV analysis packages, SYSTEMIC and RadVel, to derive masses and thus densities of the GJ 9827 planets. We also test a Gaussian Process regression analysis, but find the correlated stellar noise is not well constrained by the PFS data, and that the GP tends to over fit the RV semi-amplitudes resulting in a lower K value. Our RV observations are not able to place strong mass constraints on the two outer planets (c & d) but do indicate that planet b, at 1.64 R$_{\oplus}$ and ~8 M$_{\oplus}$, is one of the most massive (and dense) super-Earth planets detected to date.
De-biased populations of Kuiper belt objects from the deep ecliptic survey

The Deep Ecliptic Survey (DES) was a survey project that discovered hundreds of Kuiper Belt objects from 1998 to 2005. Extensive follow-up observations of these bodies has yielded 304 objects with well-determined orbits and dynamical classifications into one of several categories: Classical, Scattered, Centaur, or 16 mean-motion resonances with Neptune. The DES search fields are well documented, enabling us to calculate the probability on each frame of detecting an object with its particular orbital parameters and absolute magnitude at a randomized point in its orbit. The detection probabilities range from a maximum of 0.32 for the 3:2 resonant object 2002 GF {sub 32} to a minimum of 1.5 × 10{sup –7} for the faint Scattered object 2001 FU {sub 185}. By grouping individual objects together by dynamical classes, we can estimate the distributions of four parameters that define each class: semimajor axis, eccentricity, inclination, and object size. The orbital element distributions (a, e, and i) were fit to the largest three classes (Classical, 3:2, and Scattered) using a maximum likelihood fit. Using the absolute magnitude (H magnitude) as a proxy for the object size, we fit a power law to the number of objects versus H magnitude for eight classesmore » with at least five detected members (246 objects). The Classical objects are best fit with a power-law slope of α = 1.02 ± 0.01 (observed from 5 ≤ H ≤ 7.2). Six other dynamical classes (Scattered plus five resonances) have consistent magnitude distribution slopes with the Classicals, provided that the absolute number of objects is scaled. Scattered objects are somewhat more numerous than Classical objects, while there are only a quarter as many 3:2 objects as Classicals. The exception to the power law relation is the Centaurs, which are non-resonant objects with perihelia closer than Neptune and therefore brighter and detectable at smaller sizes. Centaurs were observed from 7.5 < H < 11, and that population is best fit by a power law with α = 0.42 ± 0.02. This is consistent with a knee in the H-distribution around H = 7.2 as reported elsewhere. Based on the Classical-derived magnitude distribution, the total number of objects (H ≤ 7) in each class is: Classical (2100 ± 300 objects), Scattered (2800 ± 400), 3:2 (570 ± 80), 2:1 (400 ± 50), 5:2 (270 ± 40), 7:4 (69 ± 9), 5:3 (60 ± 8). The independent estimate for the number of Centaurs in the same H range is 13 ± 5. If instead all objects are divided by inclination into 'Hot' and 'Cold' populations, following Fraser et al., we find that α{sub Hot} = 0.90 ± 0.02, while α{sub Cold} = 1.32 ± 0.02, in good agreement with that work.« less
A core-shell-surface layer model to explain the size dependence of effective magnetic anisotropy in magnetic nanoparticles

The particle size (D) dependence of the effective magnetic anisotropy K eff of magnetic nanoparticles (NPs) usually shows K eff increasing with decreasing D. This dependence is often interpreted using the Eq.: K eff = K b + (6K S /D) where K b and K s are the anisotropy constants of the spins in the bulk-like core and surface layer, respectively. Here, we show that this model is inadequate to explain the observed size-dependency of K eff for smaller nanoparticles with D 2 O 3 ), NiO and Ni are best described by an extension of the above model leading to the variation given by K eff = K b + (6K S /D) +K Sh {[1-(2rf/D)]−3 −1}, where the last term is due to the spins in a shell of thickness d with anisotropy K sh . The validation of this core-shell-surface layer (CSSL) model for three different magnetic NPs systems viz. ferrimagnetic γ-Fe 2 O 3 , ferromagnetic Ni and antiferromagnetic NiO suggests its possible applicability for all magnetic nanoparticles.
Finite-time degeneration of hyperbolicity without blowup for quasilinear wave equations

In three spatial dimensions, we study the Cauchy problem for the wave equation − ∂t2Ψ + (1 + Ψ)PΔΨ = 0 for P ∈{1,2}. We exhibit a form of stable Tricomi-type degeneracy formation that has not previously been studied in more than one spatial dimension. Specifically, using only energy methods and ODE techniques, we exhibit an open set of data such that Ψ is initially near 0, while 1 + Ψ vanishes in finite time. In fact, generic data, when appropriately rescaled, lead to this phenomenon. The solution remains regular in the following sense: there is a high-order L2-type energy, featuring degenerate weights only at the top-order, that remains bounded. When P = 1, we show that any C1 extension of Ψ to the future of a point where 1 + Ψ = 0 must exit the regime of hyperbolicity. Moreover, the Kretschmann scalar of the Lorentzian metric corresponding to the wave equation blows up at those points. Thus, our results show that curvature blowup does not always coincide with singularity formation in the solution variable. Similar phenomena occur when P = 2, where the vanishing of 1 + Ψ corresponds to the failure of strict hyperbolicity, although the equation is hyperbolic at all values of Ψ. The data are compactly supported and are allowed to be large or small as measured by an unweighted Sobolev norm. However, we assume that initially the spatial derivatives of Ψ are nonlinearly small relative to |∂tΨ|, which allows us to treat the equation as a perturbation of the ODE (d2∕dt2)Ψ = 0. We show that for appropriate data, ∂tΨ remains quantitatively negative, which simultaneously drives the degeneracy formation and yields a favorable spacetime integral in the energy estimates that is crucial for controlling some top-order error terms. Our result complements those of Alinhac and Lindblad, who showed that if the data are small as measured by a Sobolev norm with radial weights, then the solution is global.
Orderability and Dehn filling

Motivated by conjectures relating group orderability, Floer homology and taut foliations, we discuss a systematic and broadly applicable technique for constructing left-orders on the fundamental groups of rational homology 3 –spheres. Specifically, for a compact 3 –manifold M with torus boundary, we give several criteria which imply that whole intervals of Dehn fillings of M have left-orderable fundamental groups. Our technique uses certain representations from π 1 ( M ) into PSL 2 ℝ ˜ , which we organize into an infinite graph in H 1 ( ∂ M ; ℝ ) called the translation extension locus. We include many plots of such loci which inform the proofs of our main results and suggest interesting avenues for future research.
Universal correlations in percolation

We discuss correlations in percolation and recent contributions of Xiaojun Tan, Youjin Deng and Jesper Lykke Jacobsen in their paper "N-cluster correlations in four- and five-dimensional percolation," Frontiers of Physics 15, 41501 (July, 2020). This is a View and Perspective in Frontiers of Physics.
GENERALIZATIONS OF IWASAWA'S "RIEMANN–HURWITZ" FORMULA FOR CYCLIC p-EXTENSIONS OF NUMBER FIELDS

We produce generalizations of Iwasawa's "Riemann–Hurwitz" formula for number fields. These generalizations apply to cyclic extensions of number fields of degree pn for any positive integer n. We first deduce some congruences and inequalities and then use these formulas to establish a vanishing criterion for Iwasawa λ-invariants which generalizes a result of Fukuda et al. for totally real number fields.
Upper-division student difficulties with the Dirac delta function

Understanding how upper-division physics students struggle to manipulate and interpret Dirac delta functions.
Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems

With unprecedented increases in traffic load in today's wireless networks, design challenges shift from the wireless network itself to the computational support behind the wireless network. In this vein, there is new interest in quantum-compute approaches because of their potential to substantially speed up processing, and so improve network throughput. However, quantum hardware that actually exists today is much more susceptible to computational errors than silicon-based hardware, due to the physical phenomena of decoherence and noise. This paper explores the boundary between the two types of computation---classical-quantum hybrid processing for optimization problems in wireless systems---envisioning how wireless can simultaneously leverage the benefit of both approaches. We explore the feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing. Preliminary results on a low-latency, large MIMO system envisioned in the 5G New Radio roadmap are encouraging, showing approximately 2-10x better performance in terms of processing time than prior published results.
Pulsar Wind Bubble Blowout from a Supernova

For pulsars born in supernovae, the expansion of the shocked pulsar wind nebula is initially in the freely expanding ejecta of the supernova. While the nebula is in the inner flat part of the ejecta density profile, the swept-up, accelerating shell is subject to the Rayleigh-Taylor instability. We carried out 2 and 3-dimensional simulations showing that the instability gives rise to filamentary structure during this initial phase but does not greatly change the dynamics of the expanding shell. The flow is effectively self-similar. If the shell is powered into the outer steep part of the density profile, the shell is subject to a robust Rayleigh-Taylor instability in which the shell is fragmented and the shocked pulsar wind breaks out through the shell. The flow is not self-similar in this phase. For a wind nebula to reach this phase requires that the deposited pulsar energy be greater than the supernova energy, or that the initial pulsar period be in the ms range for a typical $10^{51}$ erg supernova. These conditions are satisfied by some magnetar models for Type I superluminous supernovae. We also consider the Crab Nebula, which may be associated with a low energy supernova for which this scenario applies.
Multi de Bruijn sequences

We generalize the notion of a de Bruijn sequence to a "multi de Bruijn sequence": a cyclic or linear sequence that contains every k-mer over an alphabet of size q exactly m times. For example, over the binary alphabet {0,1}, the cyclic sequence (00010111) and the linear sequence 000101110 each contain two instances of each 2-mer 00,01,10,11. We derive formulas for the number of such sequences. The formulas and derivation generalize classical de Bruijn sequences (the case m=1). We also determine the number of multisets of aperiodic cyclic sequences containing every k-mer exactly m times; for example, the pair of cyclic sequences (00011)(011) contains two instances of each 2-mer listed above. This uses an extension of the Burrows-Wheeler Transform due to Mantaci et al, and generalizes a result by Higgins for the case m=1.
Central exclusive production at the Tevatron

The Collider Detector at Fermilab, CDF, observed for the first time in hadron–hadron collisions photon–photon (γ + γ → e+e-, μ+μ-) and photon–pomeron (γ + ℙ → J/ψ, ψ(2S)) interactions, as well as by double pomeron exchange, ℙ + ℙ or DPE. Exclusive π+π- production was also measured at and 1960 GeV; resonance structures are discussed.
Substrate effects on charged defects in two-dimensional materials

Two-dimensional (2D) materials are strongly affected by the dielectric environment, including substrates, making it an important factor in designing materials for quantum and electronic technologies. Yet, first-principles evaluations of charged defect energetics in 2D materials typically do not include substrates due to the high computational cost. We present a general continuum model approach to incorporate substrate effects directly in density-functional theory calculations of charged defects in the 2D material alone. We show that this technique accurately predicts charge defect energies compared to much more expensive explicit substrate calculations, but with the computational expediency of calculating defects in freestanding 2D materials. Using this technique, we rapidly predict the substantial modification of charge transition levels of two defects in ${\mathrm{MoS}}_{2}$ and ten defects promising for quantum technologies in hBN, due to ${\mathrm{SiO}}_{2}$ and diamond substrates. This establishes a foundation for high-throughput computational screening of new quantum defects in 2D materials that critically accounts for substrate effects.
Early Results from APOKASC

Asteroseismology and spectroscopy provide complementary constraints on the fundamental and chemical properties of stars. I describe the first results from APOKASC, a collaboration between the Kepler asteroseismic science consortium (KASC) and the SDSS-III APOGEE survey. These include (1) the first test of asteroseismic scaling relationships in the metal-poor regime using halo and thick disk stars identified in the APOKASC sample; and (2) the calibration of spectroscopic parameters using precise asteroseismic measurements of surface gravity. I also highlight future research avenues that are made possible by this unique sample of thousands of well-characterized red giant stars.
Main-belt Asteroids with WISE/NEOWISE: Near-infrared Albedos

We present revised near-infrared albedo fits of 2835 main-belt asteroids observed by WISE/NEOWISE over the course of its fully cryogenic survey in 2010. These fits are derived from reflected-light near-infrared images taken simultaneously with thermal emission measurements, allowing for more accurate measurements of the near-infrared albedos than is possible for visible albedo measurements. Because our sample requires reflected light measurements, it undersamples small, low-albedo asteroids, as well as those with blue spectral slopes across the wavelengths investigated. We find that the main belt separates into three distinct groups of 6%, 16%, and 40% reflectance at 3.4 μm. Conversely, the 4.6 μm albedo distribution spans the full range of possible values with no clear grouping. Asteroid families show a narrow distribution of 3.4 μm albedos within each family that map to one of the three observed groupings, with the (221) Eos family being the sole family associated with the 16% reflectance 3.4 μm albedo group. We show that near-infrared albedos derived from simultaneous thermal emission and reflected light measurements are important indicators of asteroid taxonomy and can identify interesting targets for spectroscopic follow-up.
What is information

Information is a precise concept that can be defined mathematically, but its relationship to what we call ‘knowledge’ is not always made clear. Furthermore, the concepts ‘entropy’ and ‘information’, while deeply related, are distinct and must be used with care, something that is not always achieved in the literature. In this elementary introduction, the concepts of entropy and information are laid out one by one, explained intuitively, but defined rigorously. I argue that a proper understanding of information in terms of prediction is key to a number of disciplines beyond engineering, such as physics and biology.
Recognizing Handwritten Source Code

Supporting programming on touchscreen devices requires effective text input and editing methods. Unfortunately, the virtual keyboard can be inefficient and uses valuable screen space on already small devices. Recent advances in stylus input make handwriting a potentially viable text input solution for programming on touchscreen devices. The primary barrier, however, is that handwriting recognition systems are built to take advantage of the rules of natural language, not those of a programming language. In this paper, we explore this particular problem of handwriting recognition for source code. We collect and make publicly available a dataset of handwritten Python code samples from 15 participants and we characterize the typical recognition errors for this handwritten Python source code when using a state-of-the-art handwriting recognition tool. We present an approach to improve the recognition accuracy by augmenting a handwriting recognizer with the programming language grammar rules. Our experiment on the collected dataset shows an 8.6% word error rate and a 3.6% character error rate which outperforms standard handwriting recognition systems and compares favorably to typing source code on virtual keyboards.
Complex and Quaternionic Principal Component Pursuit and Its Application to Audio Separation

Recently, the principal component pursuit has received increasing attention in signal processing research ranging from source separation to video surveillance. So far, all existing formulations are real-valued and lack the concept of phase, which is inherent in inputs such as complex spectrograms or color images. Thus, in this letter, we extend principal component pursuit to the complex and quaternionic cases to account for the missing phase information. Specifically, we present both complex and quaternionic proximity operators for the ${\ell _1}$ - and trace-norm regularizers. These operators can be used in conjunction with proximal minimization methods such as the inexact augmented Lagrange multiplier algorithm. The new algorithms are then applied to the singing voice separation problem, which aims to separate the singing voice from the instrumental accompaniment. Results on the iKala and MSD100 datasets confirmed the usefulness of phase information in principal component pursuit.
Finite Time Extinction for Stochastic Sign Fast Diffusion and Self-Organized Criticality

We prove finite time extinction for stochastic sign fast diffusion equations driven by linear multiplicative space-time noise, corresponding to the Bak–Tang–Wiesenfeld model for self-organized criticality. This solves a problem posed and left open in several works: (Barbu, Methods Appl Sci 36:1726–1733, 2013; Rockner and Wang, J Lond Math Soc (2) 87:545–560, 2013; Barbu et al. J Math Anal Appl 389:147–164, 2012; Barbu and Rockner, Comm Math Phys 311:539–555, 2012; Barbu et al., Comm Math Phys 285:901–923, 2009, C R Math Acad Sci Paris 347(1–2):81–84, 2009). The highly singular-degenerate nature of the drift in interplay with the stochastic perturbation causes the need for new methods in the analysis of mass diffusion, and several new estimates and techniques are introduced.
Non-linear Stability of the Kerr–Newman–de Sitter Family of Charged Black Holes

We prove the global non-linear stability, without symmetry assumptions, of slowly rotating charged black holes in de Sitter spacetimes in the context of the initial value problem for the Einstein–Maxwell equations: if one perturbs the initial data of a slowly rotating Kerr–Newman–de Sitter (KNdS) black hole, then in a neighborhood of the exterior region of the black hole, the metric and the electromagnetic field decay exponentially fast to their values for a possibly different member of the KNdS family. This is a continuation of recent work of the author with Vasy on the stability of the Kerr–de Sitter family for the Einstein vacuum equations. Our non-linear iteration scheme automatically finds the final black hole parameters as well as the gauge in which the global solution exists; we work in a generalized wave coordinate/Lorenz gauge, with gauge source functions lying in a suitable finite-dimensional space. We include a self-contained proof of the linear mode stability of Reissner–Nordstrom–de Sitter black holes, building on work by Kodama–Ishibashi. In the course of our non-linear stability argument, we also obtain the first proof of the linear (mode) stability of slowly rotating KNdS black holes using robust perturbative techniques.
The Ground State Energy of the Massless Spin-Boson Model

We provide an explicit combinatorial expansion for the ground state energy of the massless spin-Boson model as a power series in the coupling parameter. Our method uses the technique of cluster expansion in constructive quantum field theory and takes as a starting point the functional integral representation and its reduction to an Ising model on the real line with long range interactions. We prove the analyticity of our expansion and provide an explicit lower bound on the radius of convergence. We do not need multiscale nor renormalization group analysis. A connection to the loop-erased random walk is indicated.
Magnetism in Dense Quark Matter

We review the mechanisms via which an external magnetic field can affect the ground state of cold and dense quark matter. In the absence of a magnetic field, at asymptotically high densities, cold quark matter is in the Color-Flavor-Locked (CFL) phase of color superconductivity characterized by three scales: the superconducting gap, the gluon Meissner mass, and the baryonic chemical potential. When an applied magnetic field becomes comparable with each of these scales, new phases and/or condensates may emerge. They include the magnetic CFL (MCFL) phase that becomes relevant for fields of the order of the gap scale; the paramagnetic CFL, important when the field is of the order of the Meissner mass, and a spin-one condensate associated to the magnetic moment of the Cooper pairs, significant at fields of the order of the chemical potential. We discuss the equation of state (EoS) of MCFL matter for a large range of field values and consider possible applications of the magnetic effects on dense quark matter to the astrophysics of compact stars.
Bounds on sup-norms of half-integral weight modular forms

Bounding sup-norms of modular forms in terms of the level has been the focus of much recent study. In this work the sup norm of a half integral weight cusp form is bounded in terms of the level.
The Neutral Gas Dynamics of the Nearby Magellanic Irregular Galaxy UGCA 105

We present new low-resolution H I spectral line imaging, obtained with the Karl G. Jansky Very Large Array, of the star-forming Magellanic irregular galaxy UGCA 105. This nearby (D = 3.39 ± 0.25 Mpc), low-mass ( 4.3 ± 0.5 × 108 M ☉) system harbors a large neutral gas disk (H I radius ~7.2 kpc at the = 1020 cm–2 level) that is roughly twice as large as the stellar disk at the B-band R 25 isophote. We explore the neutral gas dynamics of this system, fitting tilted ring models in order to extract a well-sampled rotation curve. The rotation velocity rises in the inner disk, flattens at 72 ± 3 km s–1, and remains flat to the last measured point of the disk (~7.5 kpc). The dynamical mass of UGCA 105 at this outermost point, (9 ± 2) × 109 M ☉, is ~10 times as large as the luminous baryonic components (neutral atomic gas and stars). The proximity and favorable inclination (55°) of UGCA 105 make it a promising target for high-resolution studies of both star formation and rotational dynamics in a nearby low-mass galaxy.
With Little Power Comes Great Responsibility

Despite its importance to experimental design, statistical power (the probability that, given a real effect, an experiment will reject the null hypothesis) has largely been ignored by the NLP community. Underpowered experiments make it more difficult to discern the difference between statistical noise and meaningful model improvements, and increase the chances of exaggerated findings. By meta-analyzing a set of existing NLP papers and datasets, we characterize typical power for a variety of settings and conclude that underpowered experiments are common in the NLP literature. In particular, for several tasks in the popular GLUE benchmark, small test sets mean that most attempted comparisons to state of the art models will not be adequately powered. Similarly, based on reasonable assumptions, we find that the most typical experimental design for human rating studies will be underpowered to detect small model differences, of the sort that are frequently studied. For machine translation, we find that typical test sets of 2000 sentences have approximately 75% power to detect differences of 1 BLEU point. To improve the situation going forward, we give an overview of best practices for power analysis in NLP and release a series of notebooks to assist with future power analyses.
AN OPERATOR ANALYSIS OF A SUPERSYMMETRIC EFFECTIVE THEORY

An analysis of a SU(2)L×SU(2)R invariant, supersymmetric effective theory is given. The resulting leading and next-to-leading independent invariants are stated in terms of the underlying Killing vectors and Kahler potential. The appendices are devoted to the relationship between this geometrical point of view and the standard unitary matrix formulation.
UNUSUAL POLAR CONDITIONS IN SOLAR CYCLE 24 AND THEIR IMPLICATIONS FOR CYCLE 25

We report on the prolonged solar-maximum conditions until late 2015 at the north-polar region of the Sun indicated by the occurrence of high-latitude prominence eruptions (PEs) and microwave brightness temperature close to the quiet-Sun level. These two aspects of solar activity indicate that the polarity reversal was completed by mid-2014 in the south and late 2015 in the north. The microwave brightness in the south-polar region has increased to a level exceeding the level of the Cycle 23/24 minimum, but just started to increase in the north. The northsouth asymmetry in the polarity reversal has switched from that in Cycle 23. These observations lead us to the hypothesis that the onset of Cycle 25 in the northern hemisphere is likely to be delayed with respect to that in the southern hemisphere. We find that the unusual condition in the north is a direct consequence of the arrival of poleward surges of opposite polarity from the active region belt. We also find that multiple rush-to-the-pole episodes were indicated by the PE locations that lined up at the boundary between opposite-polarity surges. The high-latitude PEs occurred in the boundary between the incumbent polar flux and the insurgent flux of opposite polarity.
MagNet: Discovering Multi-agent Interaction Dynamics using Neural Network

We present the MagNet, a neural network-based multi-agent interaction model to discover the governing dynamics and predict evolution of a complex multi-agent system from observations. We formulate a multi-agent system as a coupled non-linear network with a generic ordinary differential equation (ODE) based state evolution, and develop a neural network-based realization of its time-discretized model. MagNet is trained to discover the core dynamics of a multi-agent system from observations, and tuned on-line to learn agent-specific parameters of the dynamics to ensure accurate prediction even when physical or relational attributes of agents, or number of agents change. We evaluate MagNet on a point-mass system in two-dimensional space, Kuramoto phase synchronization dynamics and predator-swarm interaction dynamics demonstrating orders of magnitude improvement in prediction accuracy over traditional deep learning models.
A Model Connecting Galaxy Masses, Star Formation Rates, and Dust Temperatures across Cosmic Time

We investigate the evolution of dust content in galaxies from redshifts z=0 to z=9.5. Using empirically motivated prescriptions, we model galactic-scale properties -- including halo mass, stellar mass, star formation rate, gas mass, and metallicity -- to make predictions for the galactic evolution of dust mass and dust temperature in main sequence galaxies. Our simple analytic model, which predicts that galaxies in the early Universe had greater quantities of dust than their low-redshift counterparts, does a good job at reproducing observed trends between galaxy dust and stellar mass out to z~6. We find that for fixed galaxy stellar mass, the dust temperature increases from z=0 to z=6. Our model forecasts a population of low-mass, high-redshift galaxies with interstellar dust as hot as, or hotter than, their more massive counterparts; but this prediction needs to be constrained by observations. Finally, we make predictions for observing 1.1-mm flux density arising from interstellar dust emission with the Atacama Large Millimeter Array.
Systemic: A Testbed for Characterizing the Detection of Extrasolar Planets. I. The Systemic Console Package

We present the Systemic Console, a new all-in-one, general-purpose software package for the analysis and combined multiparameter fitting of Doppler radial velocity (RV) and transit timing observations. We give an overview of the computational algorithms implemented in the console, and describe the tools offered for streamlining the characterization of planetary systems. We illustrate the capabilities of the package by analyzing an updated radial velocity data set for the HD 128311 planetary system. HD 128311 harbors a pair of planets that appear to be participating in a 2:1 mean motion resonance. We show that the dynamical configuration cannot be fully determined from the current data. We find that if a planetary system like HD 128311 is found to undergo transits, then self-consistent Newtonian fits to combined radial velocity data and a small number of timing measurements of transit midpoints can provide an immediate and vastly improved characterization of the planet’s dynamical state.
Learning Global Transparent Models consistent with Local Contrastive Explanations

There is a rich and growing literature on producing local contrastive/counterfactual explanations for black-box models (e.g. neural networks). In these methods, for an input, an explanation is in the form of a contrast point differing in very few features from the original input and lying in a different class. Other works try to build globally interpretable models like decision trees and rule lists based on the data using actual labels or based on the black-box models predictions. Although these interpretable global models can be useful, they may not be consistent with local explanations from a specific black-box of choice. In this work, we explore the question: Can we produce a transparent global model that is simultaneously accurate and consistent with the local (contrastive) explanations of the black-box model? We introduce a natural local consistency metric that quantifies if the local explanations and predictions of the black-box model are also consistent with the proxy global transparent model. Based on a key insight we propose a novel method where we create custom boolean features from sparse local contrastive explanations of the black-box model and then train a globally transparent model on just these, and showcase empirically that such models have higher local consistency compared with other known strategies, while still being close in performance to models that are trained with access to the original data.
Barn and pole paradox: revisited

We present two different paradoxes related to the length contraction in special relativity and explain their resolution.
Geometric Renormalization Below the Ground State

The caloric gauge was introduced by Tao with studying large data energy critical wave maps mapping from $\mathbf{R}^{2+1}$ to hyperbolic space $\mathbf{H}^m$ in view. In \cite{BIKT} Bejenaru, Ionescu, Kenig, and Tataru adapted the caloric gauge to the setting of Schrodinger maps from $\mathbf{R}^{d + 1}$ to the standard sphere $S^2 \hookrightarrow \mathbf{R}^3$ with initial data small in the critical Sobolev norm. Here we develop the caloric gauge in a bounded geometry setting with a construction valid up to the ground state energy.
Pair-Density-Wave Order and Paired Fractional Quantum Hall Fluids

A theoretical analysis provides new insight into how Majorana fermions behave in fractional quantum Hall systems, which, in turn, could lead to a better understanding of the interplay between topology and symmetry breaking in quantum matter.
ON THE OXYGEN ISOTOPIC COMPOSITION OF THE SOLAR SYSTEM

The 18O/17O ratio of the solar system is 5.2 while that of the interstellar medium (ISM) and young stellar objects is ~4. This difference cannot be explained by pollution of the Sun's natal molecular cloud by 18O-rich supernova ejecta because (1) the necessary B-star progenitors live longer than the duration of star formation in molecular clouds, (2) the delivery of ejecta gas is too inefficient and the amount of dust in supernova ejecta is too small compared to the required pollution (2% of total mass or ~20% of oxygen), and (3) the predicted amounts of concomitant short-lived radionuclides (SLRs) conflicts with the abundances of 26Al and 41Ca in the early solar system. Proposals for the introduction of 18O-rich material must also be consistent with any explanation for the origin of the observed slope-one relationship between 17O/16O and 18O/16O in the high-temperature components of primitive meteorites. The difference in 18O/17O ratios can be explained by enrichment of the ISM by the 17O-rich winds of asymptotic giant branch (AGB) stars, the sequestration of comparatively 18O-rich gas from star-forming regions into long-lived, low-mass stars, and a monotonic decrease in the 18O/17O ratio of interstellar gas. At plausible rates of star formation and gas infall, Galactic chemical evolution does not follow a slope-one line in a three-isotope plot, but instead moves along a steeper trajectory toward an 17O-rich state. Evolution of the ISM and star-forming gas by AGB winds also explains the difference in the carbon isotope ratios of the solar system and ISM.
Stochastic magnetoelectric neuron for temporal information encoding

Emulating various facets of computing principles of the brain can potentially lead to the development of neuro-computers that are able to exhibit brain-like cognitive capabilities. In this Letter, we propose a magnetoelectronic neuron that utilizes noise as a computing resource and is able to encode information over time through the independent control of external voltage signals. We extensively characterize the device operation using simulations and demonstrate its suitability for neuromorphic computing platforms performing temporal information encoding.
SUPERSYMMETRIC HIGGS TRIPLETS AND BILINEAR R-PARITY NONCONSERVATION

The supersymmetric standard model of particle interactions is extended to include two Higgs triplet superfields at the TeV scale, carrying two units of lepton number. Realistic tree-level Majorana neutrino masses are obtained in the presence of soft, i.e. bilinear, R-parity nonconservation.
CONCENTRIC MACLAURIN SPHEROID MODELS OF ROTATING LIQUID PLANETS

I present exact expressions for the interior gravitational potential V of a system of N concentric constant-density (Maclaurin) spheroids. I demonstrate an iteration procedure to find a self-consistent solution for the shapes of the interfaces between spheroids, and for the interior gravitational potential. The external free-space potential, expressed as a multipole expansion, emerges as part of the self-consistent solution. The procedure is both simpler and more precise than perturbation methods. One can choose the distribution and mass densities of the concentric spheroids so as to reproduce a prescribed barotrope to a specified accuracy. I demonstrate the method's efficacy by comparing its results with several published test cases.
Irreducible Ginzburg–Landau Fields in Dimension 2

Ginzburg–Landau fields are the solutions of the Ginzburg–Landau equations which depend on two positive parameters, $$\alpha $$ and $$\beta $$ . We give conditions on $$\alpha $$ and $$\beta $$ for the existence of irreducible solutions of these equations. Our results hold for arbitrary compact, oriented, Riemannian 2-manifolds (for example, bounded domains in $$\mathbb {R}^2$$ , spheres, tori, etc.) with de Gennes–Neumann boundary conditions. We also prove that, for each such manifold and all positive $$\alpha $$ and $$\beta $$ , the Ginzburg–Landau free energy is a Palais–Smale function on the space of gauge equivalence classes; Ginzburg–Landau fields exist for only a finite set of energy values, and the moduli space of Ginzburg–Landau fields is compact.
Partition functions and elliptic genera from supergravity

We develop the spacetime aspects of the computation of partition functions for string/M-theory on AdS3 × M. Subleading corrections to the semi-classical result are included systematically, laying the groundwork for comparison with CFT partition functions via the AdS3/CFT2 correspondence. This leads to a better understanding of the "Farey tail" expansion of Dijkgraaf et. al. from the point of view of bulk physics. Besides clarifying various issues, we also extend the analysis to the N = 2 setting with higher derivative effects included.
Measurement of 139 La(p,x) cross sections from 35–60 MeV by stacked-target activation

A stacked-target of natural lanthanum foils (99.9119% 139La) was irradiated using a 60 MeV proton beam at the LBNL 88-Inch Cyclotron. 139La(p,x) cross sections are reported between 35–60 MeV for nine product radionuclides. The primary motivation for this measurement was the need to quantify the production of 134Ce. As a positron-emitting analogue of the promising medical radionuclide 225Ac, 134Ce is desirable for in vivo applications of bio-distribution assays for this emerging radio-pharmaceutical. The results of this measurement were compared to the nuclear model codes TALYS, EMPIRE and ALICE (using default parameters), which showed significant deviation from the measured values.
Remote Measurement of Sea Ice Dynamics With Regularized Optimal Transport

As Arctic conditions rapidly change, human activity in the Arctic will continue to increase and so will the need for high-resolution observations of sea ice. While satellite imagery can provide high spatial resolution, it is temporally sparse and significant ice deformation can occur between observations. This makes it difficult to apply feature tracking or image correlation techniques that require persistent features to exist between images. With this in mind, we propose a technique based on optimal transport, which is commonly used to measure differences between probability distributions. When little ice enters or leaves the image scene, we show that regularized optimal transport can be used to quantitatively estimate ice deformation. We discuss the motivation for our approach and describe efficient computational implementations. Results are provided on a combination of synthetic and MODIS imagery to demonstrate the ability of our approach to estimate dynamics properties at the original image resolution.
Naturality of the contact invariant in monopole Floer homology under strong symplectic cobordisms

The contact invariant is an element in the monopole Floer homology groups of an oriented closed three-manifold canonically associated to a given contact structure. A nonvanishing contact invariant implies that the original contact structure is tight, so understanding its behavior under symplectic cobordisms is of interest if one wants to further exploit this property. By extending the gluing argument of Mrowka and Rollin to the case of a manifold with a cylindrical end, we will show that the contact invariant behaves naturally under a strong symplectic cobordism. As quick applications of the naturality property, we give alternative proofs for the vanishing of the contact invariant in the case of an overtwisted contact structure, its nonvanishing in the case of strongly fillable contact structures and its vanishing in the reduced part of the monopole Floer homology group in the case of a planar contact structure. We also prove that a strong filling of a contact manifold which is an L–space must be negative definite.
Entities as Experts: Sparse Memory Access with Entity Supervision

We focus on the problem of capturing declarative knowledge about entities in the learned parameters of a language model. We introduce a new model---Entities as Experts (EaE)---that can access distinct memories of the entities mentioned in a piece of text. Unlike previous efforts to integrate entity knowledge into sequence models, EaE's entity representations are learned directly from text. We show that EaE's learned representations capture sufficient knowledge to answer TriviaQA questions such as "Which Dr. Who villain has been played by Roger Delgado, Anthony Ainley, Eric Roberts?'', outperforming an encoder-generator Transformer model with 10x the parameters on this task. According to the Lama knowledge probes, EaE contains more factual knowledge than a similar sized Bert, as well as previous approaches that integrate external sources of entity knowledge.Because EaE associates parameters with specific entities, it only needs to access a fraction of its parameters at inference time, and we show that the correct identification and representation of entities is essential to EaE's performance.