cssi/SciSciGPT-SciSciNet huggingface dataset:
QCD corrections to flavor-changing neutral currents in the supersymmetric standard model

Abstract We compute the leading QCD corrections to K- K mixing in the supersymmetric standard model with general soft supersymmetry-breaking parameters. We construct the ΔS = 2 effective Lagrangian for three hierarchies of supersymmetric particle masses, namely, when the gluino mass is comparable to, much greater than, or much less than the masses of the first two generation squarks. We find that the QCD corrections tighten the limits on squark mass splittings by more than a factor of two.
unWISE: Unblurred Coadds of the WISE Imaging

The Wide-field Infrared Survey Explorer (WISE) satellite observed the full sky in four mid-infrared bands in the 2.8-28 μm range. The primary mission was completed in 2010. The WISE team has done a superb job of producing a series of high-quality, well-documented, complete data releases in a timely manner. However, the "Atlas Image" coadds that are part of the recent AllWISE and previous data releases were intentionally blurred. Convolving the images by the point-spread function while coadding results in "matched-filtered" images that are close to optimal for detecting isolated point sources. But these matched-filtered images are sub-optimal or inappropriate for other purposes. For example, we are photometering the WISE images at the locations of sources detected in the Sloan Digital Sky Survey through forward modeling, and this blurring decreases the available signal-to-noise by effectively broadening the point-spread function. This paper presents a new set of coadds of the WISE images that have not been blurred. These images retain the intrinsic resolution of the data and are appropriate for photometry preserving the available signal-to-noise. Users should be cautioned, however, that the W3- and W4-band coadds contain artifacts around large, bright structures (large galaxies, dusty nebulae, etc.); eliminating these artifacts is the subject of ongoing work. These new coadds, and the code used to produce them, are publicly available at http://unwise.me.
Packing squares in a torus

The densest packings of N unit squares in a torus are studied using analytical methods as well as simulated annealing. A rich array of dense packing solutions are found: density-one packings when N is the sum of two square integers; a family of 'gapped bricklayer' Bravais lattice solutions with density N/(N + 1); and some surprising non-Bravais lattice configurations, including lattices of holes as well as a configuration for N = 23 in which not all squares share the same orientation. The entropy of some of these configurations and the frequency and orientation of density-one solutions as are discussed.
Star-cluster Mass and Age Distributions of Two Fields in M83 Based on HST/WFC3 Observations

We study star clusters in two fields in the nearby spiral galaxy M83 using broadband and narrowband optical imaging taken with the Wide Field Camera 3 onboard the Hubble Space Telescope. We present results on the basis of several different catalogs of star clusters in inner and outer fields, and we conclude that different methods of selection do not strongly affect the results, particularly for clusters older than ≈10 Myr. The age distributions can be described by a power law, dN/dτ∝τγ, with γ ≈ –0.84 ± 0.12 in the inner field, and γ ≈ –0.48 ± 0.12 in the outer field for τ 10 Myr. We bracket the difference, Δγ, between the two fields to be in the 0.18 to 0.36 range, based on estimates of the relative star-formation histories. The mass functions can also be described by a power law, dN/dM∝M β, with β ≈ –1.98 ± 0.14 and β ≈ –2.34 ± 0.26 in the inner and outer fields, respectively. We conclude that the shapes of the mass and age distributions of the clusters in the two fields are similar, as predicted by the quasi-universal model. Any differences between the two fields are at the ≈2σ-3σ (≈1σ-2σ) level for the age (mass) distributions. Therefore, any dependence of these distributions on the local environment is probably weak. We compare the shapes of the distributions with those predicted by two popular cluster disruption models. We find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass. We compare the shapes of the distributions with those predicted by two popular cluster disruption models, and find that both show evidence that the clusters are disrupted at a rate that is approximately independent of their mass, and that observational results do not support the earlier disruption of lower-mass clusters relative to their higher-mass counterparts.
Galois level and congruence ideal for $p$-adic families of finite slope Siegel modular forms

We consider families of Siegel eigenforms of genus , while the remainder appear as isolated points on the eigenvariety.
Spectral Gap Estimates in Mean Field Spin Glasses

We show that mixing for local, reversible dynamics of mean field spin glasses is exponentially slow in the low temperature regime. We introduce a notion of free energy barriers for the overlap, and prove that their existence imply that the spectral gap is exponentially small, and thus that mixing is exponentially slow. We then exhibit sufficient conditions on the equilibrium Gibbs measure which guarantee the existence of these barriers, using the notion of replicon eigenvalue and 2D Guerra Talagrand bounds. We show how these sufficient conditions cover large classes of Ising spin models for reversible nearest-neighbor dynamics and spherical models for Langevin dynamics. Finally, in the case of Ising spins, Panchenko’s recent rigorous calculation (Panchenko in Ann Probab 46(2):865–896, 2018) of the free energy for a system of “two real replica” enables us to prove a quenched LDP for the overlap distribution, which gives us a wider criterion for slow mixing directly related to the Franz–Parisi–Virasoro approach (Franz et al. in J Phys I 2(10):1869–1880, 1992; Kurchan et al. J Phys I 3(8):1819–1838, 1993). This condition holds in a wider range of temperatures.
CONSTRAINTS ON DARK ENERGY FROM THE OBSERVED EXPANSION OF OUR COSMIC HORIZON

Within the context of standard cosmology, an accelerating universe requires the presence of a third "dark" component of energy, beyond matter and radiation. The available data, however, are still deemed insufficient to distinguish between an evolving dark energy component and the simplest model of a time-independent cosmological constant. In this paper, we examine the cosmological expansion in terms of observer-dependent coordinates, in addition to the more conventional comoving coordinates. This procedure explicitly reveals the role played by the radius Rh of our cosmic horizon in the interrogation of the data. (In Rindler's notation, Rh coincides with the "event horizon" in the case of de Sitter, but changes in time for other cosmologies that also contain matter and/or radiation.) With this approach, we show that the interpretation of dark energy as a cosmological constant is clearly disfavored by the observations. Within the framework of standard Friedmann–Robertson–Walker cosmology, we derive an equation describing the evolution of Rh, and solve it using the WMAP and Type Ia supernova data. In particular, we consider the meaning of the observed equality (or near-equality) Rh(t0) ≅ ct0, where t0 is the age of the universe. This empirical result is far from trivial, for a cosmological constant would drive Rh(t) toward ct (t is the cosmic time) only once — and that would have to occur right now. Though we are not here espousing any particular alternative model of dark energy, for comparison we also consider scenarios in which dark energy is given by scaling solutions, which simultaneously eliminate several conundrums in the standard model, including the "coincidence" and "flatness" problems, and account very well for the fact that Rh(t0) ≈ ct0.
Analysis and Entropy Stability of the Line-Based Discontinuous Galerkin Method

We develop a discretely entropy-stable line-based discontinuous Galerkin method for hyperbolic conservation laws based on a flux differencing technique. By using standard entropy-stable and entropy-conservative numerical flux functions, this method guarantees that the discrete integral of the entropy is non-increasing. This nonlinear entropy stability property is important for the robustness of the method, in particular when applied to problems with discontinuous solutions or when the mesh is under-resolved. This line-based method is significantly less computationally expensive than a standard DG method. Numerical results are shown demonstrating the effectiveness of the method on a variety of test cases, including Burgers’ equation and the Euler equations, in one, two, and three spatial dimensions.
Polar Alignment of a Protoplanetary Disk around an Eccentric Binary

We use three-dimensional hydrodynamical simulations to show that an initially mildly misaligned circumbinary accretion disk around an eccentric binary can evolve to an orientation that is perpendicular to the orbital plane of the binary (polar alignment). As the disk evolves to the perpendicular state, it undergoes nodal libration oscillations of the tilt angle and the longitude of the ascending node. Dissipation within the disk causes the oscillations to damp. The process operates above a critical initial misalignment angle that depends upon the eccentricity of the binary and the mass of the disk. For binary eccentricity of 0.5, the process operates typically for disk masses smaller than a few percent of the binary mass and initial tilt angle of more than 40°. This evolution has important implications for planet formation around eccentric binary star systems.
Finding Your Literature Match – A Recommender System

The universe of potentially interesting, searchable literature is expanding continuously. Besides the normal expansion, there is an additional influx of literature because of interdisciplinary boundaries becoming more and more diffuse. Hence, the need for accurate, efficient and intelligent search tools is bigger than ever. Even with a sophisticated search engine, looking for information can still result in overwhelming results. An overload of information has the intrinsic danger of scaring visitors away, and any organization, for-profit or not-for-profit, in the business of providing scholarly information wants to capture and keep the attention of its target audience. Publishers and search engine engineers alike will benefit from a service that is able to provide visitors with recommendations that closely meet their interests. Providing visitors with special deals, new options and highlights may be interesting to a certain degree, but what makes more sense (especially from a commercial point of view) than to let visitors do most of the work by the mere action of making choices? Hiring psychics is not an option, so a technological solution is needed to recommend items that a visitor is likely to be looking for. In this presentation we will introduce such a solution and argue that it is practically feasible to incorporate this approach into a useful addition to any information retrieval system with enough usage.
Casimir effect of a Lorentz-violating scalar in magnetic field

In this paper, I study the Casimir effect caused by a charged and massive scalar field that breaks Lorentz invariance in a CPT-even, aether-like manner. I investigate the case of a scalar field tha...
Statistical Description of a Magnetized Corona above a Turbulent Accretion Disk

We present a physics-based statistical theory of a force-free magnetic field in the corona above a turbulent accretion disk. The field is represented by a statistical ensemble of loops tied to the disk. Each loop evolves under several physical processes: Keplerian shear, turbulent random walk of the disk footpoints, and reconnection with other loops. To build a statistical description, we introduce the distribution function of loops over their sizes and construct a kinetic equation that governs its evolution. This loop kinetic equation is formally analogous to Boltzmann's kinetic equation, with loop-loop reconnection described by a binary collision integral. A dimensionless parameter is introduced to scale the (unknown) overall rate of reconnection relative to Keplerian shear. After solving for the loop distribution function numerically, we calculate self-consistently the distribution of the mean magnetic pressure and dissipation rate with height, and the equilibrium shapes of loops of different sizes. We also compute the energy and torque associated with a given loop, as well as the total magnetic energy and torque in the corona. We explore the dependence of these quantities on the reconnection parameter and find that they can be greatly enhanced if reconnection between loops is suppressed.
SCAD-penalized regression in high-dimensional partially linear models

We consider the problem of simultaneous variable selection and estimation in partially linear models with a divergent number of covariates in the linear part, under the assumption that the vector of regression coefficients is sparse. We apply the SCAD penalty to achieve sparsity in the linear part and use polynomial splines to estimate the nonparametric component. Under reasonable conditions, it is shown that consistency in terms of variable selection and estimation can be achieved simultaneously for the linear and nonparametric components. Furthermore, the SCAD-penalized estimators of the nonzero coefficients are shown to have the asymptotic oracle property, in the sense that it is asymptotically normal with the same means and covariances that they would have if the zero coefficients were known in advance. The finite sample behavior of the SCAD-penalized estimators is evaluated with simulation and illustrated with a data set.
General Relativistic Binary Merger Simulations and Short Gamma-Ray Bursts

The recent localization of some short-hard gamma-ray bursts (GRBs) in galaxies with low star formation rates has lent support to the suggestion that these events result from compact object binary mergers. We discuss how new simulations in general relativity are helping to identify the central engine of short-hard GRBs. Motivated by our latest relativistic black hole-neutron star merger calculations, we discuss a scenario in which these events may trigger short-hard GRBs and compare this model to competing relativistic models involving binary neutron star mergers and the delayed collapse of hypermassive neutron stars. Distinguishing features of these models may help guide future GRB and gravitational wave observations to identify the nature of the sources.
THE CALIFORNIA PLANET SURVEY IV: A PLANET ORBITING THE GIANT STAR HD 145934 AND UPDATES TO SEVEN SYSTEMS WITH LONG-PERIOD PLANETS*

We present an update to seven stars with long-period planets or planetary candidates using new and archival radial velocities from Keck-HIRES and literature velocities from other telescopes. Our updated analysis better constrains orbital parameters for these planets, four of which are known multi-planet systems. HD 24040 b and HD 183263 c are super-Jupiters with circular orbits and periods longer than 8 yr. We present a previously unseen linear trend in the residuals of HD 66428 indicative of an additional planetary companion. We confirm that GJ 849 is a multi-planet system and find a good orbital solution for the c component: it is a 1 M_(Jup) planet in a 15 yr orbit (the longest known for a planet orbiting an M dwarf). We update the HD 74156 double-planet system. We also announce the detection of HD 145934 b, a 2 M_(Jup) planet in a 7.5 yr orbit around a giant star. Two of our stars, HD 187123 and HD 217107, at present host the only known examples of systems comprising a hot Jupiter and a planet with a well constrained period greater than 5 yr, and with no evidence of giant planets in between. Our enlargement and improvement of long-period planet parameters will aid future analysis of origins, diversity, and evolution of planetary systems.
Amortized entanglement of a quantum channel and approximately teleportation-simulable channels

This paper defines the amortized entanglement of a quantum channel as the largest difference in entanglement between the output and the input of the channel, where entanglement is quantified by an arbitrary entanglement measure. We prove that the amortized entanglement of a channel obeys several desirable properties, and we also consider special cases such as the amortized relative entropy of entanglement and the amortized Rains relative entropy. These latter quantities are shown to be single-letter upper bounds on the secret-key-agreement and PPT-assisted quantum capacities of a quantum channel, respectively. Of especial interest is a uniform continuity bound for these latter two special cases of amortized entanglement, in which the deviation between the amortized entanglement of two channels is bounded from above by a simple function of the diamond norm of their difference and the output dimension of the channels. We then define approximately teleportation- and positive-partial-transpose-simulable (PPT-simulable) channels as those that are close in diamond norm to a channel which is either exactly teleportation- or PPT-simulable, respectively. These results then lead to single-letter upper bounds on the secret-key-agreement and PPT-assisted quantum capacities of channels that are approximately teleportation- or PPT-simulable, respectively. Finally, we generalize many of the concepts in the paper to the setting of general resource theories, defining the amortized resourcefulness of a channel and the notion of $\nu$-freely-simulable channels, connecting these concepts in an operational way as well.
Gravity Multiplet on KS and BB Backgrounds

In this paper we study the spectra of glueballs on the Klebanov-Strassler background and its extension to the baryonic branch. We numerically calculate the mass spectrum of glueballs from the spin 2 ``gravity'' multiplet, which contains the traceless part of the stress-energy tensor and the transverse part of the U(1) -current. The mass spectra of the corresponding fluctuations in supergravity coincide due to supersymmetry, which is manifest in the effective five-dimensional theory through a Supersymmetric Quantum Mechanics transformation. We show that the glueball spectra grow as mn2 ∝ Un2 for large values of the baryonic branch parameter U.
NEW PERSPECTIVES FOR QCD FROM AdS/CFT ⁄

The AdS/CFT correspondence between conformal field theory and string states in an extended space-time has provided new insights into not only hadron spectra, but also their light-front wavefunctions. We show that there is an exact correspondence between the fifth-dimensional coordinate of anti-de Sitter space z and a specific impact variable {zeta} which measures the separation of the constituents within the hadron in ordinary space-time. This connection allows one to predict the form of the light-front wavefunctions of mesons and baryons, the fundamental entities which encode hadron properties and scattering amplitudes. A new relativistic Schroedinger light-cone equation is found which reproduces the results obtained using the fifth-dimensional theory.
Modularity Component Analysis versus Principal Component Analysis

In this paper the exact linear relation between the leading eigenvectors of the modularity matrix and the singular vectors of an uncentered data matrix is developed. Based on this analysis the concept of a modularity component is defined, and its properties are developed. It is shown that modularity component analysis can be used to cluster data similar to how traditional principal component analysis is used except that modularity component analysis does not require data centering.
An ALMA and MagAO Study of the Substellar Companion GQ Lup B

National Science Foundation [1506818]; NSF AAG [1615408]; NASA Origins of Solar Systems award; TRIF fellowship; California Institute of Technology (Caltech) - NASA through the Sagan Fellowship Program; NASA Exoplanets Research Program (XRP) [NNX16AD44G]; National Science Foundation
Rate-distortion bounds on Bayes risk in supervised learning

An information-theoretic framework is presented for estimating the number of labeled samples needed to train a classifier in a parametric Bayesian setting. Ideas from rate-distortion theory are used to derive bounds for the average L 1 or L ∞ distance between the learned classifier and the true maximum a posteriori classifier in terms of familiar information-theoretic quantities and the number of training samples available. The maximum a posteriori classifier is viewed as a random source, labeled training data are viewed as a finite-rate encoding of the source, and the L 1 or L ∞ Bayes risk is viewed as the average distortion. The result is a framework dual to the well-known probably approximately correct (PAC) framework. PAC bounds characterize worst-case learning performance of a family of classifiers whose complexity is captured by the Vapnik-Chervonenkis (VC) dimension. The rate-distortion framework, on the other hand, characterizes the average-case performance of a family of data distributions in terms of a quantity called the interpolation dimension, which represents the complexity of the family of data distributions. The resulting bounds do not suffer from the pessimism typical of the PAC framework, particularly when the training set is small.
Upgrading from Gaussian Processes to Student’s-T Processes

Gaussian process priors are commonly used in aerospace design for performing Bayesian optimization. Nonetheless, Gaussian processes suffer two significant drawbacks: outliers are a priori assumed unlikely, and the posterior variance conditioned on observed data depends only on the locations of those data, not the associated sample values. Student's-T processes are a generalization of Gaussian processes, founded on the Student's-T distribution instead of the Gaussian distribution. Student's-T processes maintain the primary advantages of Gaussian processes (kernel function, analytic update rule) with additional benefits beyond Gaussian processes. The Student's-T distribution has higher Kurtosis than a Gaussian distribution and so outliers are much more likely, and the posterior variance increases or decreases depending on the variance of observed data sample values. Here, we describe Student's-T processes, and discuss their advantages in the context of aerospace optimization. We show how to construct a Student's-T process using a kernel function and how to update the process given new samples. We provide a clear derivation of optimization-relevant quantities such as expected improvement, and contrast with the related computations for Gaussian processes. Finally, we compare the performance of Student's-T processes against Gaussian process on canonical test problems in Bayesian optimization, and apply the Student's-T process to the optimization of an aerostructural design problem.
Exact analytic solutions for the rotation of an axially symmetric rigid body subjected to a constant torque

New exact analytic solutions are introduced for the rotational motion of a rigid body having two equal principal moments of inertia and subjected to an external torque which is constant in magnitude. In particular, the solutions are obtained for the following cases: (1) Torque parallel to the symmetry axis and arbitrary initial angular velocity; (2) Torque perpendicular to the symmetry axis and such that the torque is rotating at a constant rate about the symmetry axis, and arbitrary initial angular velocity; (3) Torque and initial angular velocity perpendicular to the symmetry axis, with the torque being fixed with the body. In addition to the solutions for these three forced cases, an original solution is introduced for the case of torque-free motion, which is simpler than the classical solution as regards its derivation and uses the rotation matrix in order to describe the body orientation. This paper builds upon the recently discovered exact solution for the motion of a rigid body with a spherical ellipsoid of inertia. In particular, by following Hestenes’ theory, the rotational motion of an axially symmetric rigid body is seen at any instant in time as the combination of the motion of a “virtual” spherical body with respect to the inertial frame and the motion of the axially symmetric body with respect to this “virtual” body. The kinematic solutions are presented in terms of the rotation matrix. The newly found exact analytic solutions are valid for any motion time length and rotation amplitude. The present paper adds further elements to the small set of special cases for which an exact solution of the rotational motion of a rigid body exists.
Characterizing local noise in QAOA circuits

Recently Xue et al. [arXiv:1909.02196] demonstrated numerically that QAOA performance varies as a power law in the amount of noise under certain physical noise models. In this short note, we provide a deeper analysis of the origin of this behavior. In particular, we provide an approximate closed form equation for the fidelity and cost in terms of the noise rate, system size, and circuit depth. As an application, we show these equations accurately model the trade off between larger circuits which attain better cost values, at the expense of greater degradation due to noise.
Adversarial Generative Grammars for Human Activity Prediction.

In this paper we propose an adversarial generative grammar model for future prediction. The objective is to learn a model that explicitly captures temporal dependencies, providing a capability to forecast multiple, distinct future activities. Our adversarial grammar is designed so that it can learn stochastic production rules from the data distribution, jointly with its latent non-terminal representations. Being able to select multiple production rules during inference leads to different predicted outcomes, thus efficiently modeling many plausible futures. The adversarial generative grammar is evaluated on the Charades, MultiTHUMOS, Human3.6M, and 50 Salads datasets and on two activity prediction tasks: future 3D human pose prediction and future activity prediction. The proposed adversarial grammar outperforms the state-of-the-art approaches, being able to predict much more accurately and further in the future, than prior work. Code will be open sourced.
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search

Efficient search is a core issue in Neural Architecture Search (NAS). It is difficult for conventional NAS algorithms to directly search the architectures on large-scale tasks like ImageNet. In general, the cost of GPU hours for NAS grows with regard to training dataset size and candidate set size. One common way is searching on a smaller proxy dataset (e.g., CIFAR-10) and then transferring to the target task (e.g., ImageNet). These architectures optimized on proxy data are not guaranteed to be optimal on the target task. Another common way is learning with a smaller candidate set, which may require expert knowledge and indeed betrays the essence of NAS. In this paper, we present DA-NAS that can directly search the architecture for large-scale target tasks while allowing a large candidate set in a more efficient manner. Our method is based on an interesting observation that the learning speed for blocks in deep neural networks is related to the difficulty of recognizing distinct categories. We carefully design a progressive data adapted pruning strategy for efficient architecture search. It will quickly trim low performed blocks on a subset of target dataset (e.g., easy classes), and then gradually find the best blocks on the whole target dataset. At this time, the original candidate set becomes as compact as possible, providing a faster search in the target task. Experiments on ImageNet verify the effectiveness of our approach. It is \(\mathbf{2} \varvec{\times }\) faster than previous methods while the accuracy is currently state-of-the-art, at 76.2% under small FLOPs constraint. It supports an argument search space (i.e., more candidate blocks) to efficiently search the best-performing architecture.
Viral-induced alternative splicing of host genes promotes influenza replication

Viral infection induces the expression of numerous host genes that impact the outcome of infection. Here, we show that infection of human lung epithelial cells with influenza A virus (IAV) also induces a broad program of alternative splicing of host genes. Although these splicing-regulated genes are not enriched for canonical regulators of viral infection, we find that many of these genes do impact replication of IAV. Moreover, in several cases, specific inhibition of the IAV-induced splicing pattern also attenuates viral infection. We further show that approximately a quarter of the IAV-induced splicing events are regulated by hnRNP K, a host protein required for efficient splicing of the IAV M transcript in nuclear speckles. Finally, we find an increase in hnRNP K in nuclear speckles upon IAV infection, which may alter accessibility of hnRNP K for host transcripts thereby leading to a program of host splicing changes that promote IAV replication.
Thermomagnetic instability of plasma composition gradients

We show that, under Braginskii magneto-hydrodynamics, anti-parallel gradients in an average ion charge state and electron temperature can be unstable to the growth of self-generated magnetic fields. The instability is analogous to the field-generating thermomagnetic instability, although it is driven by the collisional thermal force magnetic source term rather than the Biermann battery term. The gradient in ion charge state causes a gradient in collisionality, which couples with temperature perturbations to create a self-generated magnetic field. This magnetic field deflects the electron heat flux in a way that reinforces the temperature perturbation. The derived linearized growth rate, typically on hydrodynamic timescales, includes resistive and thermal smoothing. It increases with large ion composition gradients and electron heat flux, conditions typical of the hohlraum walls or contaminant mix jets in inertial confinement fusion implosions. However, extended magneto-hydrodynamic simulations indicate that the instability is usually dominated and stabilized by nonlinear Nernst advection, in a similar manner to the standard thermomagnetic instability.
Messenger RNA 5′ NAD+ Capping Is a Dynamic Regulatory Epitranscriptome Mark That Is Required for Proper Response to Abscisic Acid in Arabidopsis

Although eukaryotic messenger RNAs (mRNAs) normally possess a 5' end N7-methyl guanosine (m7G) cap, a non-canonical 5' nicotinamide adenine dinucleotide (NAD+) cap can tag certain transcripts for degradation mediated by the NAD+ decapping enzyme DXO1. Despite this importance, whether NAD+ capping dynamically responds to specific stimuli to regulate eukaryotic transcriptomes remains unknown. Here, we reveal a link between NAD+ capping and tissue- and hormone response-specific mRNA stability. In the absence of DXO1 function, transcripts displaying a high proportion of NAD+ capping are instead processed into RNA-dependent RNA polymerase 6-dependent small RNAs, resulting in their continued turnover likely to free the NAD+ molecules. Additionally, the NAD+-capped transcriptome is significantly remodeled in response to the essential plant hormone abscisic acid in a mechanism that is primarily independent of DXO1. Overall, our findings reveal a previously uncharacterized and essential role of NAD+ capping in dynamically regulating transcript stability during specific physiological responses.
Entire functions, PT-symmetry and Voros's quantization scheme

In this paper, A. Avila's theoremon convergence of the exact quantization scheme of A.~Vo\-rosis related to the reality proofs of eigenvalues of certain $PT$-symmetricboundary value problems.As a result, a special caseof a conjecture of C. Bender, S. Boettcherand P. Meisinger on reality of eigenvalues is proved.In particular the following Theorem~2 is proved:{\sl Consider the eigenvalue problem$$-w''+(-1)^\ell(iz)^mw=\lambda w,$$where $m\geq 2$ is real, and $(iz)^m$ is the principal branch,$(iz)^m>0$ when $z$ is on the negative imaginary ray,with boundary conditions $w(te^{i\beta})\to 0,\ t\to\infty,$where$ \beta=\pi/2\pm\frac{\ell+1}{m+2}\pi.$If $\ell=2$, and $m\geq 4$, then all eigenvalues are positive.}\
Active World Model Learning with Progress Curiosity

World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal horizons, and an understanding of the behavioral patterns of other agents. In this work, we study how to design such a curiosity-driven Active World Model Learning (AWML) system. To do so, we construct a curious agent building world models while visually exploring a 3D physical environment rich with distillations of representative real-world agents. We propose an AWML system driven by $\gamma$-Progress: a scalable and effective learning progress-based curiosity signal. We show that $\gamma$-Progress naturally gives rise to an exploration policy that directs attention to complex but learnable dynamics in a balanced manner, thus overcoming the "white noise problem". As a result, our $\gamma$-Progress-driven controller achieves significantly higher AWML performance than baseline controllers equipped with state-of-the-art exploration strategies such as Random Network Distillation and Model Disagreement.
On Information Transfer-Based Characterization of Power System Stability

In this paper, we present a novel approach to identify the generators and states responsible for the small-signal stability of power networks. To this end, the newly developed notion of information transfer between the states of a dynamical system is used. In particular, using the concept of information transfer, which characterizes influence between the various states of a dynamical system, we identify the generators and states which are responsible for causing instability of the power network. While characterizing influence from state to state, information transfer can also describe influence from state to modes thereby generalizing the well known notion of participation factor while at the same time overcoming some of the limitations of the participation factor. The developed framework is applied to reproduce known results for the three bus system, identifying the various causes of instabilities, and is extended to IEEE 39 bus system.
Radiation damage and thermal annealing in tunnel structured hollandite materials

Abstract Three tunnel structured hollandite samples (Cs1.33Ga1.33Ti6.67O16, Cs1.33Fe1.33Ti6.67O16, and Cs1.33Zn0.67Ti7.33O16) with demonstrated thermodynamic stability and chemical durability were synthesized and irradiated by a 1.1 GeV Au ion beam in order to study effects of B-site dopants on radiation stability. A crystalline-to-amorphous transformation induced by the high-energy ion irradiation was confirmed by complementary characterization techniques sensitive to different length-scales, such as powder X-ray diffraction, Raman spectroscopy and neutron total scattering. High-temperature oxide melt solution calorimetry was performed to determine the energy landscape before and after ion irradiation. Together, structural and thermodynamic analyses demonstrated distinctly different radiation responses of the hollandite with different B-site dopants; the Ga-substituted hollandite exhibited the smallest enthalpy of damage indicating the best radiation stability among the three samples. The hypothesized origin of the different radiation responses is the structural feature in the binary oxide form of the respective B-site dopants (e.g., Ga2O3 versus Fe2O3/ZnO for Ga and Fe/Zn dopants, respectively). Moreover, thermal analysis (i.e., differential scanning calorimetry) was conducted to investigate structural changes from the irradiation induced damaged states after thermal annealing. Results of thermal analysis revealed that the annealing-induced structural evolution of the radiation damaged hollandite structure is complex and decoupled at different length-scales. The long-range periodic structure (nanometers) was not recovered after thermal annealing and structural changes over a shorter range (≤ ∼3 A) occurred in multiple steps during the annealing process.
A combined BSA-Seq and linkage mapping approach identifies genomic regions associated with Phytophthora root and crown rot resistance in squash.

Two QTL mapping approaches were used to identify a total of six QTL associated with Phytophthora root and crown rot resistance in a biparental squash population. Phytophthora root and crown rot, caused by the soilborne oomycete pathogen Phytophthora capsici, leads to severe yield losses in squash (Cucurbita pepo). To identify quantitative trait loci (QTL) involved in resistance to this disease, we crossed a partially resistant squash breeding line with a susceptible zucchini cultivar and evaluated over 13,000 F2 seedlings in a greenhouse screen. Bulked segregant analysis with whole genome resequencing (BSA-Seq) resulted in the identification of five genomic regions—on chromosomes 4, 5, 8, 12, and 16—featuring significant allele frequency differentiation between susceptible and resistant bulks in each of two independent replicates. In addition, we conducted linkage mapping using a population of 176 F3 families derived from individually genotyped F2 individuals. Variation in disease severity among these families was best explained by a four-QTL model, comprising the same loci identified via BSA-Seq on chromosomes 4, 5, and 8 as well as an additional locus on chromosome 19, for a combined total of six QTL identified between both methods. Loci, whether those identified by BSA-Seq or linkage mapping, were of small-to-moderate effect, collectively accounting for 28–35% and individually for 2–10% of the phenotypic variance explained. However, a multiple linear regression model using one marker in each BSA-Seq QTL could predict F2:3 disease severity with only a slight drop in cross-validation accuracy compared to genomic prediction models using genome-wide markers. These results suggest that marker-assisted selection could be a suitable approach for improving Phytophthora crown and root rot resistance in squash.
A septin GTPase scaffold of dynein–dynactin motors triggers retrograde lysosome transport

The metabolic and signaling functions of lysosomes depend on their intracellular positioning and trafficking, but the underlying mechanisms are little understood. Here, we have discovered a novel septin GTPase-based mechanism for retrograde lysosome transport. We found that septin 9 (SEPT9) associates with lysosomes, promoting the perinuclear localization of lysosomes in a Rab7-independent manner. SEPT9 targeting to mitochondria and peroxisomes is sufficient to recruit dynein and cause perinuclear clustering. We show that SEPT9 interacts with both dynein and dynactin through its GTPase domain and N-terminal extension, respectively. Strikingly, SEPT9 associates preferentially with the dynein intermediate chain (DIC) in its GDP-bound state, which favors dimerization and assembly into septin multimers. In response to oxidative cell stress induced by arsenite, SEPT9 localization to lysosomes is enhanced, promoting the perinuclear clustering of lysosomes. We posit that septins function as GDP-activated scaffolds for the cooperative assembly of dynein-dynactin, providing an alternative mechanism of retrograde lysosome transport at steady state and during cellular adaptation to stress.
Which criteria should be used to select patients for the Fontan operation

The Fontan operation has improved the survival of children born with single ventricle physiology. Selecting candidates for the Fontan operation may be difficult on borderline cases. No clear criterion has been established on the risk for staged Fontan palliation. Another aspect that remains controversial is the indications for fenestration. Intraoperative pulmonary flow study may identify high-risk patients for the procedure. In this report, the authors describe their results with Fontan procedures in children with pulmonary pressure >15 mmHg.
Generalizing HMMs to Continuous Time for Fast Kinetics: Hidden Markov Jump Processes.

Abstract The hidden Markov model (HMM) is a framework for time series analysis widely applied to single-molecule experiments. Although initially developed for applications outside the natural sciences, the HMM has traditionally been used to interpret signals generated by physical systems, such as single molecules, evolving in a discrete state space observed at discrete time levels dictated by the data acquisition rate. Within the HMM framework, transitions between states are modeled as occurring at the end of each data acquisition period and are described using transition probabilities. Yet, whereas measurements are often performed at discrete time levels in the natural sciences, physical systems evolve in continuous time according to transition rates. It then follows that the modeling assumptions underlying the HMM are justified if the transition rates of a physical process from state to state are small as compared to the data acquisition rate. In other words, HMMs apply to slow kinetics. The problem is, because the transition rates are unknown in principle, it is unclear, a priori, whether the HMM applies to a particular system. For this reason, we must generalize HMMs for physical systems, such as single molecules, because these switch between discrete states in “continuous time”. We do so by exploiting recent mathematical tools developed in the context of inferring Markov jump processes and propose the hidden Markov jump process. We explicitly show in what limit the hidden Markov jump process reduces to the HMM. Resolving the discrete time discrepancy of the HMM has clear implications: we no longer need to assume that processes, such as molecular events, must occur on timescales slower than data acquisition and can learn transition rates even if these are on the same timescale or otherwise exceed data acquisition rates.
Pollution Haven or Hythe? New Evidence from Mexico

Foreign direct investment (FDI) flows into developing countries have been increasing dramatically over the past decade. At the same time, there has been widespread concern that lax environmental standards are in part responsible for this surge. This paper revisits the pollution haven hypothesis by examining to what extent the pollution intensity of production helps explain FDI in Mexico. By focusing on pollution intensities, which are directly related to emission regulations, we avoid the problem of unobservable pollution taxes and allow for substitution between capital and pollution. Examining several different pollutants, we find a positive correlation between FDI and pollution that is both statistically and economically significant in the case of the highly regulated sulfur dioxide emissions. Industries for which the estimated relationship between FDI and pollution is positive receive as much as 40 percent of total FDI and account for as much as 30 percent of manufacturing output. Although our results suggest that environmental considerations matter for firms' location decisions, FDI locates in Mexico also in accordance with its comparative advantage in labor- intensive production processes, consistent with the previous literature.
Two Concepts of Religious Liberty: The Natural Rights and Moral Autonomy Approaches to the Free Exercise of Religion

Due in part to the influence of Michael McConnell, free exercise exemptionism is generally thought to be compatible with, if not dictated by, the founders’ church-state political philosophy. This article rejects that position, arguing instead that America's constitutional tradition offers two distinct conceptions of religious liberty: the founders’ natural rights free exercise and modern moral autonomy exemptionism. The article aims to distinguish these two approaches by clarifying how they are grounded upon divergent philosophical understandings of human freedom and by explaining how they advance different views of what religious liberty is, how it is threatened, and, accordingly, how it is best protected. The article also attempts to demonstrate how our modern approach expands the protection for religious liberty in some ways but limits it in others.
The AFL-CIO — NDLON Agreement:Five Proposals for Advancing the Partnership

This article explores possibilities for collaboration between organized labor and worker centers in the United States. As a point of departure, the article describes a formal partnership created in 2006 between the AFL-CIO and the National Day Laborer Organizing Network (NDLON). Areas for collaboration that are discussed include occupational safety and health, enforcement of the Davis-Bacon Act, educational campaigns, local partnerships, and job training & apprenticeship programs.
Making Sense of Citizenship

Response to Commentators. Symposium: Denaturalizing Citizenship: A Symposium on Linda Bosniak’s The Citizen and the Alien and Ayelet Shachar’s The Birthright Lottery.
The use of advertising activities to meet earnings benchmarks: evidence from monthly data

Using a unique database of monthly media advertising spending, we examine whether managers engage in real earnings management to meet quarterly financial reporting benchmarks. We extend prior literature by (1) separately analyzing advertising activities, allowing us to explore the possibility that managers could reduce or boost advertising to meet benchmarks; (2) analyzing actual activities as opposed to inferring them from reported expenses, which are also subject to accrual choices; (3) investigating the timing, within a quarter, of altered advertising spending; and (4) examining quarterly earnings benchmarks. We find that managers, on average, reduce advertising spending to avoid losses and earnings decreases. However, we also report that firms in the late stages of their life cycle increase advertising to meet earnings benchmarks. Finally, we find some evidence that firms increase advertising in the third month of a fiscal quarter and in the fourth quarter to beat prior year’s earnings.
Momentum and overreaction in experimental asset markets

Abstract Price volatility and investor overreactions are commonplace in experimental asset markets. Understanding the price dynamics in these markets is crucial for designing successful new trading institutions. We report on a series of experiments to test the predictions of a new momentum model using a dynamical systems approach. This model is then pitted against several standard models to predict prices, as well as against expert human forecasters. The comparative results suggest that each model has its advantages and regions of best performance. Overall, the best predictive methods are the momentum model and expert human forecasters.
Can Debt Relief Buy Growth

The purpose of the paper is twofold. First, I investigate whether numerous debt initiatives during the 1990s have had a significant effect on economic growth rates in developing countries in general. The major initiatives during that time period were negotiated as bilateral agreements under the guidance of the Paris Club of Creditors. These agreements were complemented later on by the Heavily Indebted Poor Countries (HIPC) debt relief initiative in 1996 and its “enhanced” version in 1999. I find that, on average, debt relief has no effect on growth rates of developing countries. The second question I address in this paper is whether the effect on growth rates was different for different subsets of developing countries. I find that countries that are not classified as HIPC have benefited significantly from debt relief, whereas the growth rates of HIPC countries have been unaffected.