cssi/SciSciGPT-SciSciNet huggingface dataset:
An Algorithm for Multi-Objective Multi-Agent Optimization

Multi-agent optimization problems with many objective functions have drawn much interest over the past two decades. Many works on the subject minimize the sum of objective functions, which implicitly carries a decision about the problem formulation. Indeed, it represents a special case of a multi-objective problem, in which all objectives are prioritized equally. To the best of our knowledge, multi-objective optimization applied to multi-agent systems remains largely unexplored. Therefore, we propose a distributed algorithm that allows the exploration of Pareto optimal solutions for the non-homogeneously weighted sum of objective functions. In the problems we consider, each agent has one objective function to minimize based on a gradient method. Agents update their decision variables by exchanging information with other agents in the network. Information exchanges are weighted by each agent's individual weights that encode the extent to which they prioritize other agents' objectives. This paper provides a proof of convergence, performance bounds, and explicit limits for the results of their computations. Simulation results with different sizes of networks demonstrate the efficiency of the proposed approach and how the choice of weights impacts the agents' final result.
Why is the American South Poorer

While American poverty research has devoted greater attention to poverty in the Northeast and Midwest, poverty has been persistently higher in the U.S. South than other regions. Thus, this study investigates the enduring question of why poverty is higher in the South. Specifically, it demonstrates the role of power resources as an explanation for this regional disparity, yet also considers family demography, economic structure, and racial/ethnic heterogeneity. Using six waves (2000-2016) of U.S. Census Current Population Survey data from the Luxembourg Income Study (N=1,157,914), this study employs a triangulation of analytic techniques: (1) tests of means and proportions differences, (2) multi-level linear probability models of poverty, and (2) binary decomposition of the South/Non-South poverty gap. The comparison of means associated with the power resources hypothesis yield the largest substantive differences between the South and the Non-South. In the multi-level models, adjusting for power resources yields the largest declines in the South coefficient. Binary decomposition results indicate that power resources are the second most influential factor explaining the South/Non-South poverty gap. Overall, power resources are an important source of the South/Non-South poverty gap, though economic structure and other factors certainly also play a role. Results also suggest an important interplay between power resources and race. Altogether, these results underscore the importance of the macro-level characteristics of places, including political and economic contexts, in shaping individual poverty and overall patterns of inequality.
A unified epistemological theory of information processing

What does it mean for an agent faced with choice under uncertainty to “know” something? While a variety of mathematical methods are available to construct formal models to answer this question, the combination of different approaches may lead to unsettling paradoxes. I propose a unified theory that eliminates such inconsistencies by relying on a sharp conceptual distinction between information the decision-maker observes and how much of that information she can cognitively process. The resulting model allows for natural decision-theoretic characterizations of comparing different amounts of information.
Learning to control the brain through adaptive closed-loop patterned stimulation

Objective Stimulation of neural activity is an important scientific and clinical tool, causally testing hypotheses and treating neurodegenerative and neuropsychiatric diseases. However, current stimulation approaches cannot flexibly control the pattern of activity in populations of neurons. To address this, we developed a model-free, adaptive, closed-loop stimulation (ACLS) system that learns to use multi-site electrical stimulation to control the pattern of activity of a population of neurons. Approach The ACLS system combined multi-electrode electrophysiological recordings with multi-site electrical stimulation to simultaneously record the activity of a population of 5-15 multiunit neurons and deliver spatially-patterned electrical stimulation across 4-16 sites. Using a closed-loop learning system, ACLS iteratively updated the pattern of stimulation to reduce the difference between the observed neural response and a specific target pattern of firing rates in the recorded multiunits. Main results In silico and in vivo experiments showed ACLS learns to produce specific patterns of neural activity (in ∼15 min) and was robust to noise and drift in neural responses. In visual cortex of awake mice, ACLS learned electrical stimulation patterns that produced responses similar to the natural response evoked by visual stimuli. Similar to how repetition of a visual stimulus causes an adaptation in the neural response, the response to electrical stimulation was adapted when it was preceded by the associated visual stimulus. Significance Our results show an ACLS system that can learn, in real-time, to generate specific patterns of neural activity. This work provides a framework for using model-free closed-loop learning to control neural activity.
C. elegans aversive olfactory learning generates diverse intergenerational effects

Parental experience can modulate the behavior of their progeny. While the molecular mechanisms underlying parental effects or inheritance of behavioral traits have been studied under several enviro...
Silicon Photomultipliers as a Low-Cost Fluorescence Detector for Capillary Electrophoresis.

Capillary electrophoresis (CE) is a highly efficient separation method capable of handling small sample volumes (~pL) and low (~yoctomole) detection limits, and as such is ideal for applications th...
Exoskeleton-covered soft finger with vision-based proprioception and tactile sensing

Soft robots offer significant advantages in adaptability, safety, and dexterity compared to conventional rigid-body robots. However, it is challenging to equip soft robots with accurate proprioception and tactile sensing due to their high flexibility and elasticity. In this work, we describe the development of a vision-based proprioceptive and tactile sensor for soft robots called GelFlex, which is inspired by previous GelSight sensing techniques. More specifically, we develop a novel exoskeleton-covered soft finger with embedded cameras and deep learning methods that enable high-resolution proprioceptive sensing and rich tactile sensing. To do so, we design features along the axial direction of the finger, which enable high-resolution proprioceptive sensing, and incorporate a reflective ink coating on the surface of the finger to enable rich tactile sensing. We design a highly underactuated exoskeleton with a tendon-driven mechanism to actuate the finger. Finally, we assemble 2 of the fingers together to form a robotic gripper and successfully perform a bar stock classification task, which requires both shape and tactile information. We train neural networks for proprioception and shape (box versus cylinder) classification using data from the embedded sensors. The proprioception CNN had over 99% accuracy on our testing set (all six joint angles were within 1° of error) and had an average accumulative distance error of 0.77 mm during live testing, which is better than human finger proprioception. These proposed techniques offer soft robots the high-level ability to simultaneously perceive their proprioceptive state and peripheral environment, providing potential solutions for soft robots to solve everyday manipulation tasks. We believe the methods developed in this work can be widely applied to different designs and applications.
Generalized slab universal instability and its appearance in pair plasma

A generalized linear dispersion relation of electromagnetic slab universal modes is derived, taking into account arbitrary ion charge state, electron finite Larmor radius (FLR) effects, and Debye shielding effects. As a consequence, it provides more accurate predictions and is applicable to a wider range of plasmas. We find that electron FLR effects have a weakly stabilizing effect on the slab universal instability in electron–ion plasma, while Debye shielding strongly stabilizes this instability when λD approaches ρi (λD is the Debye length and ρi is the ion gyroradius). In particular, we examine the stability criterion for this instability in electron–positron pair plasmas and find that the instability persists in this simplest plasma system as long as the pair plasma number density exceeds the critical value n c = B 2 / ( 8 π m e c 2 ).
On the Treewidth of Hanoi Graphs.

The objective of the well-known Towers of Hanoi puzzle is to move a set of disks one at a time from one of a set of pegs to another, while keeping the disks sorted on each peg. We propose an adversarial variation in which the first player forbids a set of states in the puzzle, and the second player must then convert one randomly-selected state to another without passing through forbidden states. Analyzing this version raises the question of the treewidth of Hanoi graphs. We find this number exactly for three-peg puzzles and provide nearly-tight asymptotic bounds for larger numbers of pegs.
Average Gromov hyperbolicity and the Parisi ansatz

Abstract Gromov hyperbolicity of a metric space measures the distance of the space from a perfect tree-like structure. The measure has a “worst-case” aspect to it, in the sense that it detects a region in the space which sees the maximum deviation from tree-like structure. In this article we introduce an “average-case” version of Gromov hyperbolicity, which detects whether the “most of the space”, with respect to a given probability measure, looks like a tree. The main result of the paper is that if this average hyperbolicity is small, then the space can be approximately embedded in a tree. The proof uses a weighted version of Szemeredi's regularity lemma from graph theory. The result applies to Gromov hyperbolic spaces as well, since average hyperbolicity is bounded above by Gromov hyperbolicity. As an application, we give a construction of hierarchically organized pure states in any model of a spin glass that satisfies the Parisi ultrametricity ansatz.
Viewpoint: Are food labels good?

Abstract Do people from benefit from food labels? When? By how much? Public officials face persistent challenges in answering these questions. In various nations, they use four different approaches: they refuse to do so on the ground that quantification is not feasible; they engage in breakeven analysis; they project end-states, such as economic savings or health outcomes; and they estimate willingness-to-pay for the relevant information. Each of these approaches is subject to strong objections. In principle, the willingness-to-pay question has important advantages. But for those who favor asking that question, on the ground that it is the best way to measure the welfare effects of food labels, there is a serious problem. In practice, people often lack enough information to give a sensible answer to the question how much they would be willing to pay for (more) information. People might also suffer from behavioral biases (including present bias and optimistic bias). And when preferences are labile or endogenous, even an informed and unbiased answer to the willingness to pay question may fail to capture the welfare consequences, because people may develop new tastes and values as a result of information. A good path forward is to focus on the effects of food labels on people’s actual experience, in order to capture their welfare effects, rather than to rely on how much people are willing to pay for such labels, or on whether they report, in advance, that they favor them.
Evolution of Generalists by Phenotypic Plasticity

Summary Adapting organisms face a tension between specializing their phenotypes for certain ecological tasks and developing generalist strategies that permit persistence in multiple environmental conditions. Understanding when and how generalists or specialists evolve is an important question in evolutionary dynamics. Here, we study the evolution of bacterial range expansions by selecting Escherichia coli for faster migration through porous media containing one of four different sugars supporting growth and chemotaxis. We find that selection in any one sugar drives the evolution of faster migration in all sugars. Measurements of growth and motility of all evolved lineages in all nutrient conditions reveal that the ubiquitous evolution of fast migration arises via phenotypic plasticity. Phenotypic plasticity permits evolved strains to exploit distinct strategies to achieve fast migration in each environment, irrespective of the environment in which they were evolved. Therefore, selection in a homogeneous environment drives phenotypic plasticity that improves performance in other environments.
Witten's conjecture and recursions for $\kappa$ classes

We construct a countable number of differential operators $$\widehat{L}_n$$ that annihilate a generating function for intersection numbers of $$\kappa $$ classes on $$\overline{{\mathscr {M}}}_g$$ (the $$\kappa $$ -potential). This produces recursions among intersection numbers of $$\kappa $$ classes which determine all such numbers from a single initial condition. The starting point of the work is a combinatorial formula relating intersection numbers of $$\psi $$ and $$\kappa $$ classes. Such a formula produces an exponential differential operator acting on the Gromov–Witten potential to produce the $$\kappa $$ -potential; after restricting to a hyperplane, we have an explicit change of variables relating the two generating functions, and we conjugate the “classical” Virasoro operators to obtain the operators $$\widehat{L}_n$$ .
Intersubband decay of 1-D exciton resonances in carbon nanotubes.

We have studied intersubband decay of E22 excitons in semiconducting carbon nanotubes experimentally and theoretically. Photoluminescence excitation line widths of semiconducting nanotubes with chiral indicess (n,m) can be mapped onto a connectivity grid with curves of constant (n − m) and (2n + m). Moreover, the global behavior of E22 line widths is best characterized by a strong increase with energy irrespective of their (n-m)mod(3) = ±1 family affiliation. Solution of the Bethe−Salpeter equations shows that the E22 line widths are dominated by phonon assisted coupling to higher momentum states of the E11 and E12 exciton bands. The calculations also suggest that the branching ratio for decay into exciton bands vs free carrier bands, respectively is about 10:1.
Stabilizing the Tb-based 214 cuprate by partial Pd substitution

Previously known to form only under high pressure synthetic conditions, here we report that the T′-type 214-structure cuprate based on the rare earth atom Tb is stabilized for ambient pressure synthesis through partial substitution of Pd for Cu. The new material is obtained in purest form for mixtures of nominal composition Tb1.96Cu0.8Pd0.2O4. The refined formula, in orthorhombic space group Pbca, with a = 5.5117(1) A, b = 5.5088(1) A, and c = 11.8818(1) A, is Tb2Cu0.83Pd0.17O4. An incommensurate structural modulation is seen along the a axis by electron diffraction and high resolution imaging. Magnetic susceptibility measurements reveal long-range antiferromagnetic ordering at 7.9 K, with a less pronounced feature at 95 K; a magnetic moment reorientation transition is observed to onset at a field of approximately 1.1 T at 3 K. The material is an n-type semiconductor.
Scattering equations and virtuous kinematic numerators and dual-trace functions

Inspired by recent developments on scattering equations, we present a constructive procedure for computing symmetric, amplitude-encoded, BCJ numerators for n-point gauge-theory amplitudes, thus satisfying the three virtues identified by Broedel and Carrasco. We also develop a constructive procedure for computing symmetric, amplitude-encoded dual-trace functions τ for n-point amplitudes. These can be used to obtain symmetric kinematic numerators that automatically satisfy color-kinematic duality. The S n symmetry of n-point gravity amplitudes formed from these symmetric dual-trace functions is completely manifest. Explicit expressions for four- and five-point amplitudes are presented.
Langmuir-blodgett assembly of densely aligned single-walled carbon nanotubes from bulk materials.

Single-walled carbon nanotubes (SWNTs) exhibit advanced electrical and surface properties useful for high performance nanoelectronics. Important to future manufacturing of nanotube circuits is a large-scale assembly of SWNTs into aligned forms. Despite progress in assembly and oriented synthesis, pristine SWNTs in aligned and close-packed form remain elusive and needed for high-current, -speed, and -density devices through collective operations of parallel SWNTs. Here, we develop a Langmuir−Blodgett (LB) method achieving monolayers of aligned SWNTs with dense packing, central to which is a noncovalent polymer functionalization by poly(m-phenylenevinylene-co-2,5-dioctoxy-p-phenylenevinylene) (PmPV) imparting high solubility and stability of SWNTs in an organic solvent 1,2-dichloroethane (DCE). Pressure cycling or “annealing” during LB film compression reduces hysteresis and facilitates high-degree alignment and packing of SWNTs characterized by microscopy and polarized Raman spectroscopy. The monolayer SWN...
The Hubble Constant from Gravitational Lens Time Delays

Present day estimates of the Hubble constant based on Cepheids and on the cosmic microwave background radiation are uncertain by roughly 10% (on the conservative assumption that the universe may not be perfectly flat). Gravitational lens time delay measurements can produce estimates that are less uncertain, but only if a variety of major difficulties are overcome. These include a paucity of constraints on the lensing potential, the degeneracies associated with mass sheets and the central concentration of the lensing galaxy, multiple lenses, microlensing by stars, and the small variability amplitude typical of most quasars. To date only one lens meets all of these challenges. Several suffer only from the central concentration degeneracy, which may be lifted if one is willing to assume that systems with time delays are either like better constrained systems with non-variable sources, or alternatively, like nearby galaxies. 1. Context Were we to choose at random a hundred members of the IAU and ask each of them to tell us the value of the Hubble constant and how it is measured, few if any would refer to gravitational lens time delay measurements. Most would instead refer to observations of Cepheid variables with HST or to observations of the CMB power spectrum with WMAP. These set the de facto standard against which time delay estimates must be evaluated. The Cepheids give a Hubble constant of 72 km/s/Mpc with a 10% uncertainty (Freed- man et al. 2001), a result that most of our randomly chosen astronomers would find relatively straightforward. But only a handful of them would be able to tell us how the CMB power spectrum yields a measurement of the Hubble constant. In his opening talk, David Spergel told us that three numbers are determined to high accuracy by the CMB power spectrum: the height of the first peak, the contrast between the heights of the even and odd peaks, and the distance between peaks. Ask anyone who calls himself a cosmologist how many free parameters his world model has and the number N will be larger than three. Spergel's three numbers constrain combinations of those N parameters, but do not, in particular, tightly constrain the Hubble constant. One must supplement the CMB either with observations, or alternatively, with non-observational constraints. The effects of supplementing the observed CMB power spectrum with other observa- tions, and of adopting (or declining to adopt) non-observational constraints, are shown in table 1. All of the numbers shown are taken from the analysis by Tegmark et al. (2004b). They use the first year data from the Wilkinson Microwave Anisotropy Probe (Bennett et al. 2003), the second data release of the Sloan Digital Sky Survey (Abazajian et al. 2004), the Tonry et al. (2003), data for high redshift Type Ia supernovae, and data from 6 other CMB experiments: Boomerang, DASI, MAXIMA, VSA, CBI and ACBAR.
Nonlinear simulation of an elastic tumor-host interface

We develop a computational method for simulating the nonlinear dynamics of an elastic tumor-host interface. This work is motivated by the recent linear stability analysis of a two-phase tumor model with an elastic membrane interface in 2D. Unlike the classic tumor model with surface tension, the elastic interface condition is numerically challenging due to the 4th order derivative from the Helfrich bending energy. Here we are interested in exploring the nonlinear interface dynamics in a sharp interface framework. We consider a curvature dependent bending rigidity (curvature weakening) to investigate metastasis patterns such as chains or fingers that invade the host environment. We solve the nutrient field and the Stokes flow field using a spectrally accurate boundary integral method, and update the interface using a nonstiff semi-implicit approach. Numerical results suggest curvature weakening promotes the development of branching patterns instead of encapsulated morphologies in a long period of time. For non-weakened bending rigidity, we are able to find self-similar shrinking morphologies based on marginally stable value of the apoptosis rate.
Kernel-based distance metric learning in the output space

In this paper we present two related, kernel-based Distance Metric Learning (DML) methods. Their respective models non-linearly map data from their original space to an output space, and subsequent distance measurements are performed in the output space via a Mahalanobis metric. The dimensionality of the output space can be directly controlled to facilitate the learning of a low-rank metric. Both methods allow for simultaneous inference of the associated metric and the mapping to the output space, which can be used to visualize the data, when the output space is 2-or 3-dimensional. Experimental results for a collection of classification tasks illustrate the advantages of the proposed methods over other traditional and kernel-based DML approaches.
FABRY-PEROT ABSORPTION LINE SPECTROSCOPY OF THE GALACTIC BAR. II. STELLAR METALLICITIES

We measure the Ca II {lambda}8542 line strength in 3360 stars along three lines of sight (LOS) in the Galactic bar: (l, b) {approx} ({+-}5.{sup 0}0, - 3.{sup 0}5) and Baade's window, using Fabry-Perot (FP) absorption line spectroscopy. This is the first attempt to show that reliable absorption line strengths can be measured using FP spectroscopy. The Ca II {lambda}8542 line is a good indicator of metallicity, and its calibration to [Fe/H] is determined for globular cluster red giants in previous investigations. We derive such a calibration for the bulge giants and use it to infer metallicities for our full red clump sample (2488 stars) at all three LOS. We present the stellar metallicity distributions along the major axis of the bar. We find the mean [Fe/H] = -0.09 {+-} 0.04 dex in Baade's window, and the distribution in this field to agree well with previous works. We find gradients in the mean metallicity and its dispersion with respect to Baade's window of -0.45 and -0.20 dex respectively at l = +5.{sup 0}5, and of -0.10 dex and -0.20 dex at l = -5.{sup 0}0. We detect a signature of a possible tidal stream at l = +5.{sup 0}5 inmore » both our velocity and metallicity distributions. Its radial velocity indicates that it is not associated with the Sagittarius stream. We also measure the metallicity of a bulge globular cluster NGC 6522 in our Baade's window field to be -0.90 {+-} 0.10 dex, which is in agreement with recent measurements of Zoccali et al. This agreement demonstrates the reliability of our metallicity measurements.« less
XPS on Li-Battery-Related Compounds: Analysis of Inorganic SEI Phases and a Methodology for Charge Correction

Accurate identification of chemical phases associated with the electrode and solid–electrolyte interphase (SEI) is critical for understanding and controlling interfacial degradation mechanisms in lithium-containing battery systems. To study these critical battery materials and interfaces X-ray photoelectron spectroscopy (XPS) is a widely used technique that provides quantitative chemical insights. However, due to the fact that a majority of chemical phases relevant to battery interfaces are poor electronic conductors, phase identification that relies primarily on absolute XPS core-level binding-energies (BEs) can be problematic. Charging during XPS measurements leads to BE shifts that can be difficult to correct. These difficulties are often exacerbated by the coexistence of multiple Li-containing phases in the SEI with overlapping XPS core levels. To facilitate accurate phase identification of battery-relevant phases (and electronically insulating phases in general), we propose a straightforward approach...
Limitations of atom interferometry for gravitational wave observations in space

A paper published recently (Hogan et al. in Gen. Relativ. Gravit. 43:1953–2009, 2011) suggests the use of atom interferometry between satellites in Earth orbit to observe gravitational waves. The proposed altitude and satellite separation are about 1,000 and 30 km respectively. The difference in acceleration between clouds of ultracold atoms in atom interferometers near the two satellites would be detected by using laser beams between the interferometers. Because of the measurement path being very short compared with the million km or longer measurement path for a proposed laser interferometer gravitational wave antenna in space, the sensitivity to differential fluctuations in the laser phase as seen by the atoms in the two atom interferometers is very high. Problems introduced by this high sensitivity to spurious laser beam phase changes will be described in the first part of this paper. Then other limitations on the performance and on the suggested types of sources that could be observed will be discussed.
Chord diagrams, contact-topological quantum field theory, and contact categories

We consider contact elements in the sutured Floer homology of solid tori with longitudinal sutures, as part of the .1C1/-dimensional topological quantum field theory defined by Honda, Kazez and Matiin (24). The Z2 SFH of these solid tori forms a "categorification of Pascal's triangle", and contact structures correspond bijectively to chord diagrams, or sets of disjoint properly embedded arcs in the disc. Their contact elements are distinct and form distinguished subsets of SFH of order given by the Narayana numbers. We find natural "creation and annihilation operators" which allow us to define a QFT-type basis of each SFH vector space, consisting of contact elements. Sutured Floer homology in this case reduces to the combinatorics of chord diagrams. We prove that contact elements are in bijective correspondence with comparable pairs of basis elements with respect to a certain partial order, and in a natural and explicit way. The algebraic and combinatorial structures in this description have intrinsic contact-topological meaning. In particular, the QFT-basis of SFH and its partial order have a natural interpretation in pure contact topology, related to the contact category of a disc: the partial order enables us to tell when the sutured solid cylinder obtained by "stacking" two chord diagrams has a tight contact structure. This leads us to extend Honda's notion of contact category to a "bounded" contact category, containing chord diagrams and contact structures which occur within a given contact solid cylinder. We compute this bounded contact category in certain cases. Moreover, the decomposition of a contact element into basis elements naturally gives a triple of contact structures on solid cylinders which we regard as a type of "distinguished triangle" in the contact category. We also use the algebraic structures arising among contact elements to extend the notion of contact category to a 2-category.
Recent Results from Jefferson Lab

Abstract Recent results on studies of the structure of nucleons and nuclei in the regime of strong interaction QCD are discussed. Use of high current polarized electron beams, polarized targets, and recoil polarimeters, in conjuction with modern spectrometers and detector instrumentation allow much more detailed studies of nucleon and nuclear structure than has been possible in the past. The CEBAF accelerator at Jefferson Lab was build to study the internal structure of hadrons in a regime where confinement is important and strong interaction QCD is the relevant theory. I discuss how the first experiments already make significant contributions towards an improved understanding of hadronic structure.
Neural Lander: Stable Drone Landing Control Using Learned Dynamics

Precise near-ground trajectory control is difficult for multi-rotor drones, due to the complex aerodynamic effects caused by interactions between multi-rotor airflow and the environment. Conventional control methods often fail to properly account for these complex effects and fall short in accomplishing smooth landing. In this paper, we present a novel deep-learning-based robust nonlinear controller (Neural-Lander) that improves control performance of a quadrotor during landing. Our approach combines a nominal dynamics model with a Deep Neural Network (DNN) that learns high-order interactions. We apply spectral normalization (SN) to constrain the Lipschitz constant of the DNN. Leveraging this Lipschitz property, we design a nonlinear feedback linearization controller using the learned model and prove system stability with disturbance rejection. To the best of our knowledge, this is the first DNN-based nonlinear feedback controller with stability guarantees that can utilize arbitrarily large neural nets. Experimental results demonstrate that the proposed controller significantly outperforms a Baseline Nonlinear Tracking Controller in both landing and cross-table trajectory tracking cases. We also empirically show that the DNN generalizes well to unseen data outside the training domain.
Infinite Families of Pairs of Curves Over Q with Isomorphic Jacobians

Three families of pairs of curves are presented; each pair consists of geometrically non-isomorphic curves whose Jacobians are isomorphic to one another as unpolarized abelian varieties. Each family is parametrized by an open subset of . The first family consists of pairs of genus-2 curves whose equations are given by simple expressions in the parameter; the curves in this family have reducible Jacobians. The second family also consists of pairs of genus-2 curves, but generically the curves in this family have absolutely simple Jacobians. The third family consists of pairs of genus-3 curves, one member of each pair being a hyperelliptic curve and the other a plane quartic. Examples from these families show that in general it is impossible to tell from the Jacobian of a genus-2 curve over whether or not the curve has rational points - or indeed whether or not it has real points. The families are constructed using methods that depend on earlier joint work with Franck Lepr?vost and Bjorn Poonen, and on Peter Bending's explicit description of the curves of genus 2 whose Jacobians have real multiplication by .
No semiconjugacy to a map of constant slope

We study countably piecewise continuous, piecewise monotone interval maps. We establish a necessary and sufficient criterion for the existence of a non-decreasing semiconjugacy to a map of constant slope in terms of the existence of an eigenvector of an operator acting on a space of measures. Then we give sufficient conditions under which this criterion is not satisfied. Finally, we give examples of maps not semiconjugate to a map of constant slope via a non-decreasing map. Our examples are continuous and transitive.
Lipschitz retraction of finite subsets of Hilbert spaces

Finite subset spaces of a metric space $X$ form a nested sequence under natural isometric embeddings $X=X(1)\subset X(2)\subset \cdots \,$ . We prove that this sequence admits Lipschitz retractions $X(n)\rightarrow X(n-1)$ when $X$ is a Hilbert space.
Morphism spaces in stable categories of Frobenius algebras

We present an explicit formula computing morphism spaces in the stable category of a Frobenius algebra.
SPECTRUM OF GLOBAL MAGNETOROTATIONAL INSTABILITY IN A NARROW TRANSITION LAYER

The global magnetorotational instability is investigated for a configuration in which the rotation frequency changes only in a narrow transition region. If the vertical wavelength of the unstable mode is of the same order or smaller than the width of this region, the growth rates can differ significantly from those given by a local analysis. In addition, the nonaxisymmetric spectrum admits overstable modes with a nontrivial dependence on azimuthal wavelength, a feature missed by the local theory. In the limit of vanishing transition region width, the Rayleigh-centrifugal instability is recovered in the axisymmetric case, and the Kelvin-Helmholtz instability in the nonaxisymmetric case.
Nonlinear energy transfer and current sheet development in localized Alfvén wavepacket collisions in the strong turbulence limit

In space and astrophysical plasmas, turbulence is responsible for transferring energy from large scales driven by violent events or instabilities, to smaller scales where turbulent energy is ultimately converted into plasma heat by dissipative mechanisms. The nonlinear interaction between counterpropagating Alfven waves, denoted Alfven wave collisions, drives this turbulent energy cascade, as recognized by early work with incompressible magnetohydrodynamic (MHD) equations. Recent work employing analytical calculations and nonlinear gyrokinetic simulations of Alfven wave collisions in an idealized periodic initial state have demonstrated the key properties that strong Alfven wave collisions mediate effectively the transfer of energy to smaller perpendicular scales and self-consistently generate current sheets. For the more realistic case of the collision between two initially separated Alfven wavepackets, we use a nonlinear gyrokinetic simulation to show here that these key properties persist: strong Alfven wavepacket collisions indeed facilitate the perpendicular cascade of energy and give rise to current sheets. Furthermore, the evolution shows that nonlinear interactions occur only while the wavepackets overlap, followed by a clean separation of the wavepackets with straight uniform magnetic fields and the cessation of nonlinear evolution in between collisions, even in the gyrokinetic simulation presented here which resolves dispersive and kinetic effects beyond the reach of the MHD theory.
Planetary Nebulae and How to Find Them: Color Identification in Big Broadband Surveys

Planetary nebulae (PNe) provide tests of stellar evolution, can serve as tracers of chemical evolution in the Milky Way and other galaxies, and are also used as a calibrator of the cosmological distance ladder. Current and upcoming large scale photometric surveys have the potential to complete the census of PNe in our galaxy and beyond, but it is a challenge to disambiguate partially or fully unresolved PNe from the myriad other sources observed in these surveys. Here we carry out synthetic observations of nebular models to determine $ugrizy$ color-color spaces that can successfully identify PNe among billions of other sources. As a primary result we present a grid of synthetic absolute magnitudes for PNe at various stages of their evolution, and we make comparisons with real PNe colors from the Sloan Digital Sky Survey. We find that the $r-i$ versus $g-r$, and the $r-i$ versus $u-g$, color-color diagrams show the greatest promise for cleanly separating PNe from stars, background galaxies, and quasars. Finally, we consider the potential harvest of PNe from upcoming large surveys. For example, for typical progenitor host star masses of $\sim$3 M$_\odot$, we find that the Large Synoptic Survey Telescope (LSST) should be sensitive to virtually all PNe in the Magellanic Clouds with extinction up to $A_{\rm V}$ of $\sim$5 mag; out to the distance of Andromeda, LSST would be sensitive to the youngest PNe (age less than $\sim$6800 yr) and with $A_{\rm V}$ up to 1 mag.
Solar wind charge exchange: an astrophysical nuisance

Solar wind charge-exchange (SWCX) emission is present in every X-ray observation of an astrophysical object. The emission is problematic when one cannot remove the foreground by the simultaneous measurement of a nearby field. SWCX emission is a serious impediment to the study of the diffuse hot ISM, including the galactic halo, as its contribution to diagnostic emission lines is temporally variable. Modeling the SWCX emission, in order to remove it from our observations, has proven to be more difficult than originally anticipated. This work reviews our current understanding of SWCX emission, with special attention to all the components required for future modeling tools. Since, in the absence of such a tool, observing programs can still be constructed to minimize the effect of SWCX, mitigation strategies are discussed. Although some aspects of SWCX will be very difficult to characterize, progress continues on many fronts.
Self-Induced Passive Nonreciprocal Transmission by Nonlinear Bifacial Dielectric Metasurfaces

The breaking of the Lorentz reciprocity law is a nontrivial task, since it usually requires bulky magnets or complicated time-modulation dynamic techniques to be accomplished. In this work, we present a simple and compact design of a nonlinear bifacial dielectric metasurface to achieve strong self-induced passive nonreciprocal transmission without the use of external biases. The proposed design is ideal for free-space-optics applications, can operate under both incident polarizations, and requires very low input excitation power to reach the nonreciprocal regime. It is composed of two passive silicon-based metasurfaces exhibiting Fano and Lorentzian resonances embedded in an ultrathin glass substrate. Highly asymmetric field enhancement is achieved with the proposed design that leads to strong nonreciprocity at low excitation intensities due to the large Kerr nonlinearity of silicon. Moreover, cascade designs are presented to further reduce the insertion loss, broaden the nonreciprocal intensity range, and increase the isolation ratio by enhancement of the transmission contrast. Finally, it is demonstrated that the proposed nonlinear metasurface is robust with regard to fabrication imperfections and can achieve large isolation for a relatively broad input power range even in the case of two incident waves impinging at the same time from both directions. The current work is expected to lead to several compact nonreciprocal nanophotonic devices, such as all-optical diodes, isolators, circulators, and ultrathin protective layers for sensitive optical components.
Radio Monitoring of the Tidal Disruption Event Swift J164449.3+573451. III. Late-time Jet Energetics and a Deviation from Equipartition

We present continued radio and X-ray observations of the relativistic tidal disruption event Swift J164449.3+573451 extending to $\delta t \approx 2000$ d after discovery. The radio data were obtained with the VLA as part of a long-term program to monitor the energy and dynamical evolution of the relativistic jet and to characterize the parsec-scale environment around a previously dormant supermassive black hole. We combine these data with $\textit{Chandra}$ X-ray observations and demonstrate that the X-ray emission following the sharp decline at $\delta t \approx 500$ d is due to the forward shock. Using the X-ray data, in conjunction with optical/NIR data, we constrain the synchrotron cooling frequency and the microphysical properties of the outflow for the first time. We find that the cooling frequency evolves through the optical/NIR band at $\delta t \approx 10 - 200$ d, corresponding to a magnetic field energy density fraction of $\epsilon_B \approx 10^{-3}$, well below equipartition; the X-ray data demonstrate that this deviation from equipartition holds to at least $\delta t \approx 2000$ d. We thus recalculate the physical properties of the jet over the lifetime of the event, no longer assuming equipartition. We find a total kinetic energy of $E_K \approx 4 \times 10^{51}$ erg and a transition to non-relativistic expansion on the timescale of our latest observations ($\delta t \approx 700$ d). The density profile is approximately $R^{-3/2}$ at $\lesssim 0.3$ pc and $\gtrsim 0.7$ pc, with a plateau at intermediate scales, characteristic of Bondi accretion. Based on its evolution thus far, we predict that Sw 1644+57 will be detectable at centimeter wavelengths for decades to centuries with existing and upcoming radio facilities. Similar off-axis events should be detectable to $z \sim 2$, but with a slow evolution that may inhibit their recognition as transient events.
Re-evaluating Evaluation in Text Summarization

Automated evaluation metrics as a stand-in for manual evaluation are an essential part of the development of text-generation tasks such as text summarization. However, while the field has progressed, our standard metrics have not -- for nearly 20 years ROUGE has been the standard evaluation in most summarization papers. In this paper, we make an attempt to re-evaluate the evaluation method for text summarization: assessing the reliability of automatic metrics using top-scoring system outputs, both abstractive and extractive, on recently popular datasets for both system-level and summary-level evaluation settings. We find that conclusions about evaluation metrics on older datasets do not necessarily hold on modern datasets and systems. We release a dataset of human judgments that are collected from 25 top-scoring neural summarization systems (14 abstractive and 11 extractive).
Turbulence Modeling in the Age of Data

Data from experiments and direct simulations of turbulence have historically been used to calibrate simple engineering models such as those based on the Reynolds-averaged Navier–Stokes (RANS) equations. In the past few years, with the availability of large and diverse data sets, researchers have begun to explore methods to systematically inform turbulence models with data, with the goal of quantifying and reducing model uncertainties. This review surveys recent developments in bounding uncertainties in RANS models via physical constraints, in adopting statistical inference to characterize model coefficients and estimate discrepancy, and in using machine learning to improve turbulence models. Key principles, achievements, and challenges are discussed. A central perspective advocated in this review is that by exploiting foundational knowledge in turbulence modeling and physical constraints, researchers can use data-driven approaches to yield useful predictive models.
Pebble Delivery for Inside-Out Planet Formation

Inside-Out Planet Formation (IOPF; Chatterjee & Tan 2014, hereafter CT14) is a scenario for sequential in situ planet formation at the pressure traps of retreating dead zone inner boundaries (DZIBs) motivated to explain the many systems with tightly packed inner planets (STIPs) discovered by Kepler. The scenario involves build-up of a pebble-dominated protoplanetary ring, supplied by radial drift of pebbles from the outer disk. It may also involve further build-up of planetary masses to gap-opening scales via continued pebble accretion. Here we study radial drift & growth of pebbles delivered to the DZIB in fiducial IOPF disk models.
Where Does The Dark Matter Begin

While there is convincing evidence that the central regions ( strong gravitational lenses. I review the determination of mass distributions using gravitational lenses using image positions, statistics, stellar dynamics, time delays and microlensing. While the present situation is confusing, there is little doubt that the existing problems can be resolved by further observations.To search for other articles by the author(s) go to: http://adsabs.harvard.edu/abstract_service.html
Involutive bordered Floer homology

We give a bordered extension of involutive HF-hat and use it to give an algorithm to compute involutive HF-hat for general 3-manifolds. We also explain how the mapping class group action on HF-hat can be computed using bordered Floer homology. As applications, we prove that involutive HF-hat satisfies a surgery exact triangle and compute HFI-hat of the branched double covers of all 10-crossing knots.
Right mainstem bronchial atresia successfully corrected with slide tracheobronchoplasty.

Mainstem bronchial atresia (MBA) is a rare and fatal entity with no survivors reported to date. We describe a neonate born at 36 weeks gestational age (GA) with right MBA who underwent successful slide tracheobronchoplasty at 32 days of life. It is theorized that during fetal life a transient fistulous connection developed, allowing right lung decompression and left lung development.
Symbolic regression in materials science

The authors showcase the potential of symbolic regression as an analytic method for use in materials research. First, the authors briefly describe the current state-of-the-art method, genetic programming-based symbolic regression (GPSR), and recent advances in symbolic regression techniques. Next, the authors discuss industrial applications of symbolic regression and its potential applications in materials science. The authors then present two GPSR use-cases: formulating a transformation kinetics law and showing the learning scheme discovers the well-known Johnson–Mehl–Avrami–Kolmogorov form, and learning the Landau free energy functional form for the displacive tilt transition in perovskite LaNiO3. Finally, the authors propose that symbolic regression techniques should be considered by materials scientists as an alternative to other machine learning-based regression models for learning from data.
An in situ measurement of the radio-frequency attenuation in ice at Summit Station, Greenland

We report an in situ measurement of the electric field attenuation length L α at radio frequencies for the bulk ice at Summit Station, Greenland, made by broadcasting radio-frequency signals vertically through the ice and measuring the relative power in the return ground bounce signal. We find the depth-averaged field attenuation length to be at 75 MHz. While this measurement has clear radioglaciological applications, the radio clarity of the ice also has implications for the detection of ultra-high energy (UHE) astrophysical particles via their radio emission in dielectric media such as ice. Assuming a reliable extrapolation to higher frequencies, the measured attenuation length at Summit Station is comparable to previously measured radio-frequency attenuation lengths at candidate particle detector sites around the world, and strengthens the case for Summit Station as a promising northern site for UHE neutrino detection.