cssi/SciSciGPT-SciSciNet huggingface dataset:
Subalgebras of simple AF-algebras

It is shown that if A is a separable, exact C*-algebra which satisfies the Universal Coefficient Theorem (UCT) and has a faithful, amenable trace, then A admits a trace-preserving embedding into a simple, unital AF-algebra with unique trace. Modulo the UCT, this provides an abstract characterization of C*-subalgebras of simple, unital AF-algebras. As a consequence, for a countable, discrete, amenable group G acting on a second countable, locally compact, Hausdorff space X, C_0(X) \rtimes_r G embeds into a simple, unital AF-algebra if, and only if, X admits a faithful, invariant, Borel, probability measure. Also, for any countable, discrete, amenable group G, the reduced group C*-algebra C*_r(G) admits a trace-preserving embedding into the universal UHF-algebra.
Comparison of Semi-Lagrangian Discontinuous Galerkin Schemes for Linear and Nonlinear Transport Simulations

Transport problems arise across diverse fields of science and engineering. Semi-Lagrangian (SL) discontinuous Galerkin (DG) methods are a class of high-order deterministic transport solvers that enjoy advantages of both the SL approach and the DG spatial discretization. In this paper, we review existing SLDG methods to date and compare numerically their performance. In particular, we make a comparison between the splitting and non-splitting SLDG methods for multi-dimensional transport simulations. Through extensive numerical results, we offer a practical guide for choosing optimal SLDG solvers for linear and nonlinear transport simulations.
Extending the Agent in QBism

According to the subjective Bayesian interpretation of quantum mechanics (QBism), the instruments used to measure quantum systems are to be regarded as an extension of the senses of the agent who is using them, and quantum states describe the agent’s expectations for what they will experience through these extended senses. How can QBism then account for the fact that (i) instruments must be calibrated before they can be used to ‘sense’ anything; (ii) some instruments are more precise than others; (iii) more precise instruments can lead to discovery of new systems? Furthermore, is the agent ‘incoherent’ if they prefer to use a less precise instrument? Here we provide answers to these questions.
Paradoxical Role of AT-rich Interactive Domain 1A in Restraining Pancreatic Carcinogenesis

Background & Aims: ARID1A is postulated to be a tumor suppressor gene owing to loss-of-function mutations in human pancreatic ductal adenocarcinomas (PDAC). However, its role in pancreatic pathogenesis is not clear despite recent studies using genetically engineered mouse (GEM) models. We aimed at further understanding of its direct functional role in PDAC, using a combination of GEM model and PDAC cell lines. Methods: Pancreas-specific mutant Arid1a-driven GEM model (Ptf1a-Cre; KrasG12D; Arid1af/f or “KAC”) was generated by crossing Ptf1a-Cre; KrasG12D (“KC”) mice with Arid1af/f mice and characterized histologically with timed necropsies. Arid1a was also deleted using CRISPR-Cas9 system in established human and murine PDAC cell lines to study the immediate effects of Arid1a loss in isogenic models. Cell lines with or without Arid1a expression were developed from respective autochthonous PDAC GEM models, compared functionally using various culture assays, and subjected to RNA-sequencing for comparative gene expression analysis. DNA damage repair was analyzed in cultured cells using immunofluorescence and COMET assay. Results: Retention of Arid1a is critical for early progression of mutant Kras-driven pre-malignant lesions into PDAC, as evident by lower Ki-67 and higher apoptosis staining in “KAC” as compared to “KC” mice. Enforced deletion of Arid1a in established PDAC cell lines caused suppression of cellular growth and migration, accompanied by compromised DNA damage repair. Despite early development of relatively indolent cystic precursor lesions called intraductal papillary mucinous neoplasms (IPMNs), a subset of “KAC” mice developed aggressive PDAC in later ages. PDAC cells obtained from older autochthonous “KAC” mice revealed various compensatory (“escaper”) mechanisms to overcome the growth suppressive effects of Arid1a loss. Conclusions: Arid1a is an essential survival gene whose loss impairs cellular growth, and thus, its expression is critical during early stages of pancreatic tumorigenesis in mouse models. In tumors that arise in the setting of ARID1A loss, a multitude of “escaper” mechanisms drive progression.
Dimension reduction in vertex-weighted exponential random graphs

Abstract We investigate the behavior of vertex-weighted exponential random graphs. We show that vertex-weighted exponential random graphs with edge weights induced by products of independent vertex weights are approximate mixtures of graphs whose vertex weight vector is a near fixed point of a certain vector equation. For graphs with Hamiltonians counting cliques, it is demonstrated that, under appropriate conditions, every solution to this equation is close to a block vector with a small number of communities. We prove that for the cases of positive weights and small weights in the Hamiltonian in particular, the vector equation has a unique solution. Lastly, the behavior of vertex-weighted exponential random graphs counting triangles is studied in detail and the solution to the vector equation is shown to approach the zero vector as the weight diverges to negative infinity for sufficiently large networks.
Minors of a skew symmetric matrix: a combinatorial approach

Knuth's combinatorial approach to Pfaffians is used to reprove and clarify a century-old formula, due to Brill. It expresses arbitrary minors of a skew symmetric matrix in terms of Pfaffians.
Enhancement of trans-cleavage activity of Cas12a with engineered crRNA enables amplified nucleic acid detection

The CRISPR-Cas12a RNA-guided complexes have tremendous potential for nucleic acid detection but are limited to the picomolar detection limit without an amplification step. Here, we develop a platform with engineered crRNAs and optimized conditions that enabled us to detect various clinically relevant nucleic acid targets with higher sensitivity, achieving a limit of detection in the femtomolar range without any target pre-amplification step. By extending the 3′- or 5′-ends of the crRNA with different lengths of ssDNA, ssRNA, and phosphorothioate ssDNA, we discover a self-catalytic behavior and an augmented rate of LbCas12a-mediated collateral cleavage activity as high as 3.5-fold compared to the wild-type crRNA and with significant improvement in specificity for target recognition. Particularly, the 7-mer DNA extension to crRNA is determined to be universal and spacer-independent for enhancing the sensitivity and specificity of LbCas12a-mediated nucleic acid detection. We perform a detailed characterization of our engineered ENHANCE system with various crRNA modifications, target types, reporters, and divalent cations. With isothermal amplification of SARS-CoV-2 RNA using RT-LAMP, the modified crRNAs are incorporated in a paper-based lateral flow assay that can detect the target with up to 23-fold higher sensitivity within 40–60 min. CRISPR-Cas12a based detection systems can be sensitive down to the picomolar range. Here the authors modify the 3′- and 5′-ends of the crRNA and show this enhances trans-cleavage for improved sensitivity.
Bilevel Optimization for On-Demand Multimodal Transit Systems

This study explores the design of an On-Demand Multimodal Transit System (ODMTS) that includes segmented mode switching models that decide whether potential riders adopt the new ODMTS or stay with their personal vehicles. It is motivated by the desire of transit agencies to design their network by taking into account both existing and latent demand, as quality of service improves. The paper presents a bilevel optimization where the leader problem designs the network and each rider has a follower problem to decide her best route through the ODMTS. The bilevel model is solved by a decomposition algorithm that combines traditional Benders cuts with combinatorial cuts to ensure the consistency of mode choices by the leader and follower problems. The approach is evaluated on a case study using historical data from Ann Arbor, Michigan, and a user choice model based on the income levels of the potential transit riders.
Robotic Sacral Colpopexy Using Autologous Fascia Lata Compared with Mesh

Objective: The objective is to compare robotic sacral colpopexy (RSC) utilizing autologous fascia lata with RSC with synthetic mesh in the treatment of pelvic organ prolapse (POP). Methods: We perf...
Broadly Reactive Influenza Antibodies Are Not Limited by Germinal Center Competition with High-Affinity Antibodies.

ABSTRACT Enhancing the generation of broadly reactive antibodies against influenza A virus (IAV) is a pertinent goal toward developing a universal IAV vaccine. While antibodies that bind conserved IAV epitopes have been identified in humans, antibodies specific for the variable epitopes are much more prevalent than antibodies recognizing conserved epitopes. It is important to define the factors that limit the generation of broadly reactive IAV antibodies in order to develop an effective universal IAV vaccine. The predominant theory is that competition within germinal centers favors the synthesis of high-affinity antibodies specific for the variable region of the virus, and limits antibodies specific for conserved IAV epitopes. Here, we show that reducing germinal center formation and removing competition with high-affinity antibodies was not sufficient to increase broadly reactive IAV antibodies or enhance protection against distinct IAV subtypes. These data disprove the prevailing hypothesis that broadly reactive IAV antibodies are rare due to competition within germinal centers, and reveal the critical need to further investigate factors that limit broadly reactive IAV antibodies. Additionally, our data show that IAV-specific IgM antibodies persist in mice in the absence of germinal centers, highlighting the protective capacity of germinal center-independent IgM antibodies, which are not typically considered when testing correlates of protection, and offer an alternate target for delivering a universal IAV vaccine. IMPORTANCE It is estimated that 250,000 to 650,000 individuals worldwide die each year from seasonal influenza A virus (IAV) infections. Current vaccines provide little protection against newly emerging strains. Thus, considerable effort is focused on enhancing the generation of broadly reactive IAV antibodies in order to develop a universal IAV vaccine. However, broadly reactive IAV antibodies are rare and the factors that limit their generation are not completely understood. Our data disprove the prevailing hypothesis that broadly reactive IAV antibodies are uncommon due to competition in the germinal centers with antibodies specific for the variable, hemagglutinin (HA) head. Understanding the factors that constrain development of antibodies specific for conserved regions of IAV is imperative for developing an effective universal IAV vaccine, which could potentially circumvent a catastrophic pandemic. These findings are significant as they highlight the importance of investigating other mechanisms that contribute to the paucity of broadly reactive IAV antibodies.
A note on mediated simplices

Abstract Many homogeneous polynomials that arise in the study of sums of squares and Hilbert's 17th problem are those formed by monomial substitutions into the arithmetic-geometric inequality. In 1989, Reznick [14] gave a necessary and sufficient condition for such a form to have a representation as a sum of squares of forms, involving the arrangement of lattice points in the simplex whose vertices were the n-tuples of the exponents used in the substitution. Further, a claim was made, and not proven, that sufficiently large dilations of any such simplex will also satisfy this condition. The aim of this short note is to prove the claim, and provide further context for the result, both in the study of Hilbert's 17th Problem and the study of lattice point simplices.
Creative Careers: The Life Cycles of Nobel Laureates in Economics

We identify two polar life cycles of scholarly creativity among Nobel laureate economists with Tinbergen falling broadly in the middle. Experimental innovators work inductively, accumulating knowledge from experience. Conceptual innovators work deductively, applying abstract principles. Innovators whose work is more conceptual do their most important work earlier in their careers than those whose work is more experimental. Our estimates imply that the probability that the most conceptual laureate publishes his single best work peaks at age 25 compared to the mid-50 s for the most experimental laureate. Thus, while experience benefits experimental innovators, newness to a field benefits conceptual innovators.
Heme oxygenase-1 affects cytochrome P450 function through the formation of heteromeric complexes: Interactions between CYP1A2 and heme oxygenase-1.

Heme oxygenase 1 (HO-1) and the cytochromes P450 (P450s) are endoplasmic reticulum–bound enzymes that rely on the same protein, NADPH-cytochrome P450 reductase (POR), to provide the electrons necessary for substrate metabolism. Although the HO-1 and P450 systems are interconnected owing to their common electron donor, they generally have been studied separately. As the expressions of both HO-1 and P450s are affected by xenobiotic exposure, changes in HO-1 expression can potentially affect P450 function and, conversely, changes in P450 expression can influence HO-1. The goal of this study was to examine interactions between the P450 and HO-1 systems. Using bioluminescence resonance energy transfer (BRET), HO-1 formed HO-1•P450 complexes with CYP1A2, CYP1A1, and CYP2D6, but not all P450s. Studies then focused on the HO-1–CYP1A2 interaction. CYP1A2 formed a physical complex with HO-1 that was stable in the presence of POR. As expected, both HO-1 and CYP1A2 formed BRET-detectable complexes with POR. The POR•CYP1A2 complex was readily disrupted by the addition of HO-1, whereas the POR•HO-1 complex was not significantly affected by the addition of CYP1A2. Interestingly, enzyme activities did not follow this pattern. BRET data suggested substantial inhibition of CYP1A2-mediated 7-ethoxyresorufin de-ethylation in the presence of HO-1, whereas its activity was actually stimulated at subsaturating POR. In contrast, HO-1–mediated heme metabolism was inhibited at subsaturating POR. These results indicate that HO-1 and CYP1A2 form a stable complex and have mutual effects on the catalytic behavior of both proteins that cannot be explained by a simple competition for POR.
View-Invariant Probabilistic Embedding for Human Pose

Depictions of similar human body configurations can vary with changing viewpoints. Using only 2D information, we would like to enable vision algorithms to recognize similarity in human body poses across multiple views. This ability is useful for analyzing body movements and human behaviors in images and videos. In this paper, we propose an approach for learning a compact view-invariant embedding space from 2D joint keypoints alone, without explicitly predicting 3D poses. Since 2D poses are projected from 3D space, they have an inherent ambiguity, which is difficult to represent through a deterministic mapping. Hence, we use probabilistic embeddings to model this input uncertainty. Experimental results show that our embedding model achieves higher accuracy when retrieving similar poses across different camera views, in comparison with 2D-to-3D pose lifting models. We also demonstrate the effectiveness of applying our embeddings to view-invariant action recognition and video alignment. Our code is available at https://github.com/google-research/google-research/tree/master/poem.
A very light dilaton

We present a completely perturbative model that displays behavior similar to that of walking technicolor. In one phase of the model RG-trajectories run towards an IR-fixed point but approximate scale invariance is spontaneously broken before reaching the fixed point. The trajectories then run away from it and a light dilaton appears in the spectrum. The mass of the dilaton is controlled by the “distance” of the theory to the critical surface, and can be adjusted to be arbitrarily small without turning off the interactions. There is a second phase with no spontaneous symmetry breaking and hence no dilaton, and in which RG trajectories do terminate at the IR-fixed point.
Solving Constrained Horn Clauses Using Dependence-Disjoint Expansions

Recursion-free Constrained Horn Clauses (CHCs) are logic-programming problems that can model safety properties of programs with bounded iteration and recursion. In addition, many CHC solvers reduce recursive systems to a series of recursion-free CHC systems that can each be solved efficiently. In this paper, we define a novel class of recursion-free systems, named Clause-Dependence Disjoint (CDD), that generalizes classes defined in previous work. The advantage of this class is that many CDD systems are smaller than systems which express the same constraints but are part of a different class. This advantage in size allows CDD systems to be solved more efficiently than their counterparts in other classes. We implemented a CHC solver named Shara. Shara solves arbitrary CHC systems by reducing the input to a series of CDD systems. Our evaluation indicates that Shara outperforms state-of-the-art implementations in many practical cases.
Nuclear Lattice Simulations with EFT

This proceedings article is a summary of results from work done in collaboration with Buḡra Borasoy and Thomas Schaefer. We study nuclear and neutron matter by combining chiral effective field theory with non-perturbative lattice methods. We present results for hot neutron matter at temperatures 20 to 40 MeV and densities below twice nuclear matter density.
Solution of Nonlinear Stokes Equations Discretized By High-Order Finite Elements on Nonconforming and Anisotropic Meshes, with Application to Ice Sheet Dynamics

Motivated by the need for efficient and accurate simulation of the dynamics of the polar ice sheets, we design high-order finite element discretizations and scalable solvers for the solution of nonlinear incompressible Stokes equations. In particular, we focus on power-law, shear thinning rheologies commonly used in modeling ice dynamics and other geophysical flows. We use nonconforming hexahedral meshes and the conforming inf-sup stable finite element velocity-pressure pairings $\mathbb{Q}_k \times \mathbb{Q}^{disc}_{k-2}$ or $\mathbb{Q}_k \times \mathbb{P}^{disc}_{k-1}$, where $k\ge 2$ is the polynomial order of the velocity space. To solve the nonlinear equations, we propose a Newton--Krylov method with a block upper triangular preconditioner for the linearized Stokes systems. The diagonal blocks of this preconditioner are sparse approximations of the (1,1)-block and of its Schur complement. The (1,1)-block is approximated using linear finite elements based on the nodes of the high-order discretization...
Compressive strain-induced metal–insulator transition in orthorhombic SrIrO3 thin films

Orthorhombic SrIrO3 is a correlated metal whose electronic properties are highly susceptible to external perturbations due to the comparable interactions of spin–orbit interaction and electronic correlation. We have investigated the electronic properties of epitaxial orthorhombic SrIrO3 thin-films under compressive strain using transport measurements, optical absorption spectra, and magnetoresistance. The metastable, orthorhombic SrIrO3 thin-films are synthesized on various substrates using an epi-stabilization technique. We have observed that as in-plane lattice compression is increased, the dc-resistivity (ρ) of the thin films increases by a few orders of magnitude, and the dρ/d T changes from positive to negative values. However, optical absorption spectra show Drude-like, metallic responses without an optical gap opening for all compressively strained thin films. Transport measurements under magnetic fields show negative magnetoresistance at low temperature for compressively strained thin-films. Our results suggest that weak localization is responsible for the strain-induced metal–insulator transition for the orthorhombic SrIrO3 thin-films.
A Study of Neural Matching Models for Cross-lingual IR

In this study, we investigate interaction-based neural matching models for ad-hoc cross-lingual information retrieval (CLIR) using cross-lingual word embeddings (CLWEs). With experiments conducted on the CLEF collection over four language pairs, we evaluate and provide insight into different neural model architectures, different ways to represent query-document interactions and word-pair similarity distributions in CLIR. This study paves the way for learning an end-to-end CLIR system using CLWEs.
Gamma-Ray Burst Pulse Shapes: Evidence for Embedded Shock Signatures?

A study of a set of well-isolated pulses in long and intermediate gamma-ray burst (GRB) light curves indicates that simple pulse models having smooth and monotonic pulse rise and decay regions are inadequate. Examining the residuals of fits of pulses to such models suggests the following patterns of departure from smooth pulses: three separate wavelike peaks found in the residuals of each pulse (the precursor peak, the central peak, and the decay peak) combine with the underlying Norris et al. pulse model to produce five distinct regions in the temporal evolution of each pulse. The Precursor Shelf occurs prior to or concurrent with the exponential Rapid Rise. The pulse reaches maximum intensity at the Peak Plateau, then undergoes a Rapid Decay. The decay gradually slows into an Extended Tail. Despite these distinct temporal segments, the pulses studied are almost universally characterized by hard-to-soft spectral evolution, arguing that the new pulse features reflect a single evolution, rather than being artifacts of pulse overlap. The fluctuations can give a single pulse the appearance of having up to three distinct localized peaks, leading to ambiguities in pulse-fitting if an incorrect pulse model is used. The approach demonstrates that complex GRBs may be composed of fewer pulses than indicated by the number of peaks. The large degree of similar spectro-temporal behavior within GRB pulses indicates that a single process is responsible for producing pulses spanning a tremendous range of durations, luminosities, and spectral hardnesses, and the correlated characteristics of the wavelike peaks are related to the pulse asymmetry, suggesting kinematic origins that seem supportive of relativistic shocks.
Refined class number formulas and Kolyvagin systems

We use the theory of Kolyvagin systems to prove (most of) a refined class number formula conjectured by Darmon. We show that, for every odd prime p, each side of Darmon’s conjectured formula (indexed by positive integers n) is ‘almost’ a p-adic Kolyvagin system as n varies. Using the fact that the space of Kolyvagin systems is free of rank one over ℤp, we show that Darmon’s formula for arbitrary n follows from the case n=1, which in turn follows from classical formulas.
Physics at a Higgs factory

I give an overview of the physics potential at possible future e+e− colliders, including the ILC, FCC-ee, and CEPC. The goal is to explain some of the measurements that can be done in the context of electroweak precision tests and Higgs couplings, to compare some of the options under consideration, and to put the measurements in context by summarizing their implications for some new physics scenarios. This is a writeup of a plenary talk at the Hong Kong University of Science and Technology Jockey Club Institute for Advanced Study Program on High Energy Physics Conference, 18–21 January 2016. Some previously unpublished electroweak precision results for FCC-ee and CEPC are included.
Predicting Role Relevance with Minimal Domain Expertise in a Financial Domain

Word embeddings have made enormous inroads in recent years in a wide variety of text mining applications. In this paper, we explore a word embedding-based architecture for predicting the relevance of a role between two financial entities within the context of natural language sentences. In this extended abstract, we propose a pooled approach that uses a collection of sentences to train word embeddings using the skip-gram word2vec architecture. We use the word embeddings to obtain context vectors that are assigned one or more labels based on manual annotations. We train a machine learning classifier using the labeled context vectors, and use the trained classifier to predict contextual role relevance on test data. Our approach serves as a good minimal-expertise baseline for the task as it is simple and intuitive, uses open-source modules, requires little feature crafting effort and performs well across roles.
The Intermediate-mass Black Hole Candidate in the Center of NGC 404: New Evidence from Radio Continuum Observations

We present the results of deep, high-resolution, 5 GHz Expanded Very Large Array (EVLA) observations of the nearby, dwarf lenticular galaxy and intermediate-mass black hole candidate (M{sub BH} {approx} 4.5 Multiplication-Sign 10{sup 5} M{sub Sun }), NGC 404. For the first time, radio emission at frequencies above 1.4 GHz has been detected in this galaxy. We found a modestly resolved source in the NGC 404 nucleus with a total radio luminosity of 7.6 {+-} 0.7 Multiplication-Sign 10{sup 17} W Hz{sup -1} at 5 GHz and a spectral index from 5 to 7.45 GHz of {alpha} = -0.88 {+-} 0.30. NGC 404 is only the third central intermediate-mass black hole candidate detected in the radio regime with subarcsecond resolution. The position of the radio source is consistent with the optical center of the galaxy and the location of a known, hard X-ray point source (L{sub X} {approx} 1.2 Multiplication-Sign 10{sup 37} erg s{sup -1}). The faint radio and X-ray emission could conceivably be produced by an X-ray binary, star formation, a supernova remnant, or a low-luminosity active galactic nucleus powered by an intermediate-mass black hole. In light of our new EVLA observations, we find that the most likely scenario is anmore » accreting intermediate-mass black hole, with other explanations being either incompatible with the observed X-ray and/or radio luminosities or statistically unlikely.« less
Scalar gravitational waves in the effective theory of gravity

As a low energy effective field theory, classical General Relativity receives an infrared relevant modification from the conformal trace anomaly of the energy-momentum tensor of massless, or nearly massless, quantum fields. The local form of the effective action associated with the trace anomaly is expressed in terms of a dynamical scalar field that couples to the conformal factor of the spacetime metric, allowing it to propagate over macroscopic distances. Linearized around flat spacetime, this semi-classical EFT admits scalar gravitational wave solutions in addition to the transversely polarized tensor waves of the classical Einstein theory. The amplitude of the scalar wave modes, as well as their energy and energy flux which are positive and contain a monopole moment, are computed. Astrophysical sources for scalar gravitational waves are considered, with the excited gluonic condensates in the interiors of neutron stars in merger events with other compact objects likely to provide the strongest burst signals.
Magnetic properties of single crystalline itinerant ferromagnet AlFe2B2

Single crystals of ${\mathrm{AlFe}}_{2}{\mathrm{B}}_{2}$ have been grown using the self-flux growth method, and then we measured the structural properties, temperature- and field-dependent magnetization, and temperature-dependent electrical resistivity at ambient as well as high pressure. The Curie temperature of ${\mathrm{AlFe}}_{2}{\mathrm{B}}_{2}$ is determined to be 274 K. The measured saturation magnetization and the effective moment for the paramagnetic Fe ion indicate the itinerant nature of the magnetism with a Rhode-Wohlfarth ratio $\frac{{M}_{C}}{{M}_{\text{sat}}}\ensuremath{\approx}1.14$. Temperature-dependent resistivity measurements under hydrostatic pressure show that transition temperature ${T}_{C}$ is suppressed down to 255 K for $p=2.24$ GPa pressure with a suppression rate of $\ensuremath{\sim}\ensuremath{-}8.9$ K/GPa. The anisotropy fields and magnetocrystalline anisotropy constants are in reasonable agreement with density functional theory calculations.
On the construction of functorial factorizations for model categories

We present general techniques for constructing functorial factorizations appropriate for model structures that are not known to be cofibrantly generated. Our methods use “algebraic” characterizations of fibrations to produce factorizations that have the desired lifting properties in a completely categorical fashion. We illustrate these methods in the case of categories enriched, tensored and cotensored in spaces, proving the existence of Hurewicz-type model structures, thereby correcting an error in earlier attempts by others. Examples include the categories of (based) spaces, (based) G ‐spaces and diagram spectra among others. 55U35, 55U40; 18A32, 18G55
Studying uniform thickness I: Legendrian simple iterated torus knots

We prove that the class of topological knot types that are both Legendrian simple and satisfy the uniform thickness property (UTP) is closed under cabling. An immediate application is that all iterated cabling knot types that begin with negative torus knots are Legendrian simple. We also examine, for arbitrary numbers of iterations, iterated cablings that begin with positive torus knots, and establish the Legendrian simplicity of large classes of these knot types, many of which also satisfy the UTP. In so doing we obtain new necessary conditions for both the failure of the UTP and Legendrian nonsimplicity in the class of iterated torus knots, including specific conditions on knot types.
Polarization of the microwave background due to primordial gravitational waves

The contribution of gravitational wave (tensor metric) and energy density (scalar metric) fluctuations to the cosmic microwave background polarization is computed. We find that the tensor contribution is significant only at large angular scales (multipoles l≤40). For standard recombination, the tensor contribution can dominate at l≤40; however, the effect would be difficult to detect since the total (scalar plus tensor) polarization is less than 1%. For models with late reionization, the total large angular scale polarization is large (∼7%-9%), but the tensor fraction is negligibly small. Hence, polarization may be useful for discriminating ionization history, but it is less promising as a means for detecting tensor fluctuations
On the dynamics of a free surface of an ideal fluid in a bounded domain in the presence of surface tension

We derive a set of equations in conformal variables that describe a potential flow of an ideal two-dimensional inviscid fluid with free surface in a bounded domain. This formulation is free of numerical instabilities present in the equations for the surface elevation and potential derived in Dyachenko et al. (Plasma Phys. Rep. vol. 22 (10), 1996, pp. 829–840) with some restrictions on analyticity relieved, which allows to treat a finite volume of fluid enclosed by a free-moving boundary. We illustrate with a comparison of numerical simulations of the Dirichlet ellipse, an exact solution for a zero surface tension fluid. We demonstrate how the oscillations of the free surface of a unit disc droplet may lead to breaking of one droplet into two when surface tension is present.
The Charge-Magnet Paradoxes of Classical Electrodynamics

(Published in Proc. of SPIE, Spintronics VII, H-J. Drouhin, J-E. Wegrowe, M. Razeghi, eds., Vol. 9167, 91670J (2014).) Abstract. A number of charge-magnet paradoxes have been discussed in the literature, beginning with Shockley's famous 1967 paper, where he introduced the notion of hidden momentum in electromagnetic systems. We discuss all these paradoxes in a single, general context, showing that the conservation laws of linear and angular momenta can be satisfied without the need for hidden entities, provided that the Einstein-Laub laws of force and torque are used in place of the standard Lorentz law. Einstein and Laub published their paper in 1908, but the simplicity of the conventional Lorentz law overshadowed the subtle features of their formulation which, at first sight, appears somewhat complicated. However, that slight complication turns out to lead to subsequent advantages in light of Shockley's discovery of hidden momentum, which occurred more than a decade after Einstein had passed away. In this paper, we show how the Einstein-Laub formalism handles the underlying problems associated with certain paradoxes of classical electrodynamics involving a static distribution of electric charges and a magnet whose magnetization slowly fades away in time. The Einstein-Laub laws of electromagnetic force and torque treat these paradoxes with elegance and without contradicting the existing body of knowledge, which has been confirmed by more than one and a half century of theoretical and experimental investigations. 1. Introduction. In classical electrodynamics, it is generally accepted that neither the mechanical nor the electromagnetic (EM) momentum are conserved by themselves; it is the total momentum (i.e., EM plus mechanical) that must be conserved. The continuity equation for momentum involves the EM stress-tensor ���, the EM momentum-density ��, and the EM force-density ��, as follows:
A Linear Algorithm for Optimization Over Directed Graphs With Geometric Convergence

In this letter, we study distributed optimization, where a network of agents, abstracted as a directed graph, collaborates to minimize the average of locally known convex functions. Most of the existing approaches over directed graphs are based on push-sum (type) techniques, which use an independent algorithm to asymptotically learn either the left or right eigenvector of the underlying weight matrices. This strategy causes additional computation, communication, and nonlinearity in the algorithm. In contrast, we propose a linear algorithm based on an inexact gradient method and a gradient estimation technique. Under the assumptions that each local function is strongly convex with Lipschitz-continuous gradients, we show that the proposed algorithm geometrically converges to the global minimizer with a sufficiently small step-size. We present simulations to illustrate the theoretical findings.
Charged grain boundaries reduce the open-circuit voltage of polycrystalline solar cells—An analytical description

Analytic expressions are presented for the dark current-voltage relation J(V ) of a pn+ junction with positively charged columnar grain boundaries with high defect density. These expressions apply to non-depleted grains with sufficiently high bulk hole mobilities. The accuracy of the formulas is verified by direct comparison to numerical simulations. Numerical simulations further show that the dark J(V ) can be used to determine the open-circuit potential Voc of an illuminated junction for a given short-circuit current density Jsc. A precise relation between the grain boundary properties and Voc is provided, advancing the understanding of the influence of grain boundaries on the efficiency of thin film polycrystalline photovoltaics like CdTe and Cu(In, Ga)Se2.
DeepLocNet: Deep Observation Classification and Ranging Bias Regression for Radio Positioning Systems

WiFi technology has been used pervasively in fine-grained indoor localization, gesture recognition, and adaptive communication. Achieving better performance in these tasks generally boils down to differentiating Line-Of-Sight (LOS) from Non-Line-Of-Sight (NLOS) signal propagation reliably which generally requires expensive/specialized hardware due to the complex nature of indoor environments. Hence, the development of low-cost accurate positioning systems that exploit available infrastructure is not entirely solved. In this paper, we develop a framework for indoor localization and tracking of ubiquitous mobile devices such as smartphones using on-board sensors. We present a novel deep LOS/NLOS classifier which uses the Received Signal Strength Indicator (RSSI), and can classify the input signal with an accuracy of 85%. The proposed algorithm can globally localize and track a smartphone (or robot) with a priori unknown location, and with a semi-accurate prior map (error within 0.8m) of the WiFi Access Points (AP). Through simultaneously solving for the trajectory and the map of access points, we recover a trajectory of the device and corrected locations for the access points. Experimental evaluations of the framework show that localization accuracy is increased by using the trained deep network; furthermore, the system becomes robust to any error in the map of APs.
WEIGHING GALAXY CLUSTERS WITH GAS. I. ON THE METHODS OF COMPUTING HYDROSTATIC MASS BIAS

Mass estimates of galaxy clusters from X-ray and Sunyeav-Zel'dovich observations assume the intracluster gas is in hydrostatic equilibrium with their gravitational potential. However, since galaxy clusters are dynamically active objects whose dynamical states can deviate significantly from the equilibrium configuration, the departure from the hydrostatic equilibrium assumption is one of the largest sources of systematic uncertainties in cluster cosmology. In the literature there have been two methods for computing the hydrostatic mass bias based on the Euler and the modified Jeans equations, respectively, and there has been some confusion about the validity of these two methods. The word 'Jeans' was a misnomer, which incorrectly implies that the gas is collisionless. To avoid further confusion, we instead refer these methods as 'summation' and 'averaging' methods respectively. In this work, we show that these two methods for computing the hydrostatic mass bias are equivalent by demonstrating that the equation used in the second method can be derived from taking spatial averages of the Euler equation. Specifically, we identify the correspondences of individual terms in these two methods mathematically and show that these correspondences are valid to within a few percent level using hydrodynamical simulations of galaxy cluster formation. In addition, we computemore » the mass bias associated with the acceleration of gas and show that its contribution is small in the virialized regions in the interior of galaxy clusters, but becomes non-negligible in the outskirts of massive galaxy clusters. We discuss future prospects of understanding and characterizing biases in the mass estimate of galaxy clusters using both hydrodynamical simulations and observations and their implications for cluster cosmology.« less
Evidence against star-forming galaxies as the dominant source of IceCube neutrinos

Keith Bechtol, 2, ∗ Markus Ahlers, 2, † Mattia Di Mauro, 4, 5 Marco Ajello, and Justin Vandenbroucke 2 Wisconsin IceCube Particle Astrophysics Center (WIPAC), Madison, WI 53703, USA Department of Physics, University of Wisconsin–Madison, Madison, WI 53706, USA W. W. Hansen Experimental Physics Laboratory, Stanford University, Stanford, CA 94305, USA Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, CA 94305, USA Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305, USA Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA
Assessing Phrasal Representation and Composition in Transformers

Deep transformer models have pushed performance on NLP tasks to new limits, suggesting sophisticated treatment of complex linguistic inputs, such as phrases. However, we have limited understanding of how these models handle representation of phrases, and whether this reflects sophisticated composition of phrase meaning like that done by humans. In this paper, we present systematic analysis of phrasal representations in state-of-the-art pre-trained transformers. We use tests leveraging human judgments of phrase similarity and meaning shift, and compare results before and after control of word overlap, to tease apart lexical effects versus composition effects. We find that phrase representation in these models relies heavily on word content, with little evidence of nuanced composition. We also identify variations in phrase representation quality across models, layers, and representation types, and make corresponding recommendations for usage of representations from these models.
THE STAR FORMATION HISTORIES OF LOCAL GROUP DWARF GALAXIES. III. CHARACTERIZING QUENCHING IN LOW-MASS GALAXIES*

We explore the quenching of low-mass galaxies (10 108 ) as a function of lookback time using the star formation histories (SFHs) of 38 Local Group dwarf galaxies. The SFHs were derived by analyzing color–magnitude diagrams of resolved stellar populations in archival Hubble Space Telescope/Wide Field Planetary Camera 2 imaging. We find: (1) lower-mass galaxies quench earlier than higher-mass galaxies; (2) inside of R there is no correlation between a satellite's current proximity to a massive host and its quenching epoch; and (3) there are hints of systematic differences in the quenching times of M31 and Milky Way (MW) satellites, although the sample size and uncertainties in the SFHs of M31 dwarfs prohibit definitive conclusions. Combined with results from the literature, we qualitatively consider the redshift evolution (z = 0–1) of the quenched galaxy fraction over ~7 dex in stellar mass (10 10 ). The quenched fraction of all galaxies generally increases toward the present, with both the lowest and highest-mass systems exhibiting the largest quenched fractions at all redshifts. In contrast, galaxies between 108–1010 have the lowest quenched fractions. We suggest that such intermediate-mass galaxies are the least efficient at quenching. Finally, we compare our quenching times with predictions for infall times for low-mass galaxies associated with the MW. We find that some of the lowest-mass satellites (e.g., CVn II, Leo IV) may have been quenched before infall, while higher-mass satellites (e.g., Leo I, Fornax) typically quench ~1–4 Gyr after infall.
Shades of dark uncertainty and consensus value for the Newtonian constant of gravitation

The Newtonian constant of gravitation, G, stands out in the landscape of the most common fundamental constants owing to its surprisingly large relative uncertainty, which is attributable mostly to the dispersion of the values measured for it by different methods and in different experiments, each of which may have rather small relative uncertainty. This study focuses on a set of measurements of G comprising results published very recently as well as older results, some of which have been corrected since the original publication. This set is inconsistent, in the sense that the dispersion of the measured values is significantly larger than what their reported uncertainties suggest that it should be. Furthermore, there is a loosely defined group of measured values that lie fairly close to a consensus value that may reasonably be derived from all the measurement results, and then there are one or more groups with measured values farther away from the consensus value, some appreciably higher, others lower. This same general pattern is often observed in many other interlaboratory studies and meta-analyses. In the conventional treatments of such data, the mutual inconsistency is addressed by inflating the reported uncertainties, either multiplicatively, or by the addition of ‘random effects’, both reflecting the presence of dark uncertainty. The former approach is often used by CODATA and by the Particle Data Group, and the latter is common in medical meta-analysis and in metrology. However, both achieve consistency ignoring how the measured values are arranged relative to the consensus value, and measured values close to the consensus value often tend to be penalized excessively, by such ‘extra’ uncertainty. We propose a new procedure for consensus building that models the results using latent clusters with different shades of dark uncertainty, which assigns a customized amount of dark uncertainty to each measured value, as a mixture of those shades, and does so taking into account both the placement of the measured values relative to the consensus value, and the reported uncertainties. We demonstrate this procedure by deriving a new estimate for G, as a consensus value m3 kg−1 s−2, with m3 kg−1 s−2.
POWER-ENHANCED MULTIPLE DECISION FUNCTIONS CONTROLLING FAMILY-WISE ERROR AND FALSE DISCOVERY RATES.

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Sidak procedure for FWER control and the Benjamini–Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p-values, as is the case, for example, with the Sidak, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p-value based procedures whose theoretical validity is contingent on each of these p-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional “large M, small n” data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.
Big Self-Supervised Models are Strong Semi-Supervised Learners

One paradigm for learning from few labeled examples while making best use of a large amount of unlabeled data is unsupervised pretraining followed by supervised fine-tuning. Although this paradigm uses unlabeled data in a task-agnostic way, in contrast to common approaches to semi-supervised learning for computer vision, we show that it is surprisingly effective for semi-supervised learning on ImageNet. A key ingredient of our approach is the use of big (deep and wide) networks during pretraining and fine-tuning. We find that, the fewer the labels, the more this approach (task-agnostic use of unlabeled data) benefits from a bigger network. After fine-tuning, the big network can be further improved and distilled into a much smaller one with little loss in classification accuracy by using the unlabeled examples for a second time, but in a task-specific way. The proposed semi-supervised learning algorithm can be summarized in three steps: unsupervised pretraining of a big ResNet model using SimCLRv2, supervised fine-tuning on a few labeled examples, and distillation with unlabeled examples for refining and transferring the task-specific knowledge. This procedure achieves 73.9% ImageNet top-1 accuracy with just 1% of the labels ($\le$13 labeled images per class) using ResNet-50, a $10\times$ improvement in label efficiency over the previous state-of-the-art. With 10% of labels, ResNet-50 trained with our method achieves 77.5% top-1 accuracy, outperforming standard supervised training with all of the labels.