cssi/SciSciGPT-SciSciNet huggingface dataset:
Empower Entity Set Expansion via Language Model Probing

Entity set expansion, aiming at expanding a small seed entity set with new entities belonging to the same semantic class, is a critical task that benefits many downstream NLP and IR applications, such as question answering, query understanding, and taxonomy construction. Existing set expansion methods bootstrap the seed entity set by adaptively selecting context features and extracting new entities. A key challenge for entity set expansion is to avoid selecting ambiguous context features which will shift the class semantics and lead to accumulative errors in later iterations. In this study, we propose a novel iterative set expansion framework that leverages automatically generated class names to address the semantic drift issue. In each iteration, we select one positive and several negative class names by probing a pre-trained language model, and further score each candidate entity based on selected class names. Experiments on two datasets show that our framework generates high-quality class names and outperforms previous state-of-the-art methods significantly.
X-symbols for non-Abelian symmetries in tensor networks

This paper introduces a systematic bottom-up approach to deal with general non-abelian symmetries in the pair-wise tensor contraction based on X-symbols. X-symbols are shown to be equivalent to $3n\ensuremath{-}j$ symbols, as they also offer a systematic approach to tackle outer multiplicities.
A cytoskeletal protein complex is essential for division of intracellular amastigotes of Leishmania mexicana

Previous studies in Leishmania mexicana have identified the cytoskeletal protein KHARON as being important for both flagellar trafficking of the glucose transporter GT1 and for successful cytokinesis and survival of infectious amastigote forms inside mammalian macrophages. KHARON is located in three distinct regions of the cytoskeleton: the base of the flagellum, the subpellicular microtubules, and the mitotic spindle. To deconvolve the different functions for KHARON, we have identified two partner proteins, KHAP1 and KHAP2, which associate with KHARON. KHAP1 is located only in the subpellicular microtubules, whereas KHAP2 is located at the subpellicular microtubules and the base of the flagellum. Both KHAP1 and KHAP2 null mutants are unable to execute cytokinesis but are able to traffic GT1 to the flagellum. These results confirm that KHARON assembles into distinct functional complexes and that the subpellicular complex is essential for cytokinesis and viability of disease-causing amastigotes but not for flagellar membrane trafficking.
Induction of long-lived potential aestivation states in laboratory An. gambiae mosquitoes.

How anopheline mosquitoes persist through the long dry season in Africa remains a gap in our understanding of these malaria vectors. To span this period in locations such as the Sahelian zone of Mali, mosquitoes must either migrate to areas of permanent water, recolonize areas as they again become favorable, or survive in harsh conditions including high temperatures, low humidity, and an absence of surface water (required for breeding). Adult mosquitoes surviving through this season must dramatically extend their typical lifespan (averaging 2–3 weeks) to 7 months. Previous work has found evidence that the malaria mosquito An. coluzzii, survives over 200 days in the wild between rainy seasons in a presumed state of aestivation (hibernation), but this state has so far not been replicated in laboratory conditions. The inability to recapitulate aestivation in the lab hinders addressing key questions such as how this state is induced, how it affects malaria vector competence, and its impact on disease transmission. In effort to induce aestivation, we held laboratory mosquitoes in climate-controlled incubators with a range of conditions that adjusted humidity (40–85% RH), temperature (18–27 °C), and light conditions (8–12 h of light) and evaluated their survivorship. These conditions were chosen to mimic the late rainy and dry seasons as well as relevant extremes these mosquitoes may experience during aestivation. We found that by priming mosquitoes in conditions simulating the late wet season in Mali, and maintaining mosquitoes in reduced light/temperature, mean mosquito survival increased from 18.34 ± 0.65 to 48.02 ± 2.87 days, median survival increased from 19 (95% CI 17–21) to 50 days (95% CI 40–58), and the maximum longevity increased from 38 to 109 days (P-adj < 0.001). While this increase falls short of the 200 + day survival seen in field mosquitoes, this extension is substantially higher than previously found through environmental or dietary modulation and is hard to reconcile with states other than aestivation. This finding will provide a platform for future characterization of this state, and allow for comparison to field collected samples.
Keeping CALM: when distributed consistency is easy

In distributed systems theory, CALM presents a result that delineates the frontier of the possible.
A self-sustaining process theory for uniform momentum zones and internal shear layers in high Reynolds number shear flows

Many exact coherent states (ECS) arising in wall-bounded shear flows have an asymptotic structure at extreme Reynolds number asymptotic analysis is performed to explore the potential for a three-dimensional, short streamwise- and spanwise-wavelength instability of the embedded shear layers to sustain a spatially distributed array of much larger-scale, effectively inviscid streamwise roll motions. In contrast to other self-sustaining process theories, the rolls are sufficiently strong to differentially homogenize the background shear flow, thereby providing a mechanistic explanation for the formation and maintenance of UMZs and interlaced shear layers that respects the leading-order balance structure of the mean dynamics.
Towards a theory of mixing graphs: A characterization of perfect mixability

Abstract Some microfluidic lab-on-chip devices contain modules whose function is to mix two fluids, called reactant and buffer, in desired proportions. In one of the technologies for fluid mixing the process can be represented by a directed acyclic graph whose nodes represent micro-mixers and edges represent micro-channels. A micro-mixer has two input channels and two output channels; it receives two fluid droplets, one from each input, mixes them perfectly, and produces two droplets of the mixed fluid on its output channels. Such a mixing graph converts a set I of input droplets into a set T of output droplets, where the droplets are specified by their reactant concentrations. The most fundamental algorithmic question related to mixing graphs is to determine, given an input set I and a target set T, whether there is a mixing graph that converts I into T. We refer to this decision problem as mix-reachability. While the complexity of this problem remains open, we provide a solution to its natural sub-problem, called perfect mixability, in which we ask whether, given a collection C of droplets, there is a mixing graph that mixes C perfectly, producing only droplets whose concentration is the average concentration of C. We provide a complete characterization of such perfectly mixable sets and an efficient algorithm for testing perfect mixability. Further, we prove that any perfectly mixable set has a perfect-mixing graph of polynomial size, and that this graph can be computed in polynomial time.
Cell-cycle-gated feedback control mediates desensitization to interferon stimulation

Cells use molecular circuits to interpret and respond to extracellular cues, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I interferon (IFN)-responsive regulatory network operates in single human cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1/early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback loops, enabling duration-dependent desensitization to repetitive stimulations.
Oracle-efficient Online Learning and Auction Design

We consider the design of computationally efficient online learning algorithms in an adversarial setting in which the learner has access to an offline optimization oracle. We present an algorithm called Generalized Follow-the-Perturbed-Leader and provide conditions under which it is oracle-efficient while achieving vanishing regret. Our results make significant progress on an open problem raised by Hazan and Koren [31], who showed that oracle-efficient algorithms do not exist in general [30] and asked whether one can identify properties under which oracle-efficient online learning may be possible. Our auction-design framework considers an auctioneer learning an optimal auction for a sequence of adversarially selected valuations with the goal of achieving revenue that is almost as good as the optimal auction in hindsight, among a class of auctions. We give oracle-efficient learning results for: (1) VCG auctions with bidder-specific reserves in single-parameter settings, (2) envy-free item pricing in multi-item auctions, and (3) s-level auctions of Morgenstern and Roughgarden [43] for single-item settings. The last result leads to an approximation of the overall optimal Myerson auction when bidders’ valuations are drawn according to a fast-mixing Markov process, extending prior work that only gave such guarantees for the i.i.d. setting. Finally, we derive various extensions, including: (1) oracle-efficient algorithms for the contextual learning setting in which the learner has access to side information (such as bidder demographics), (2) learning with approximate oracles such as those based on Maximal-in-Range algorithms, and (3) no-regret bidding in simultaneous auctions, resolving an open problem of Daskalakis and Syrgkanis [14].
In-situ SEM based method for assessing fiber-matrix interface shear strength in CFRPs

Abstract Accurate assessment of fiber-matrix interface shear strength may play key role in understanding structural strength behavior of polymer-matrix composites, and provide additional flexibility for enabling high-performing material designs. This work presents a method for assessment of fiber-matrix interface strength in carbon fiber reinforced polymers (CFRPs). The method uses in-situ scanning electron microscopy (SEM) imaging while pushing individual fibers out of 20–30 μm thick membranes. Femtosecond laser machining has been utilized to address standing challenges associated with manufacturing high-quality fiber push-out specimens. To ensure that the specimen preparation method used did not affect the properties of the composite, a thorough study has been conducted using benchmark specimens. The benchmark specimens are prepared using a conventional lapping/polishing process. Results for two CFRPs compare fiber-matrix interface shear strength generated using free-standing samples (conventional lapping/polishing preparation) and femtosecond laser-machined specimens. Both specimen types exhibit similar strength. However, load-displacement response of the free-standing samples is overly compliant, representing specimen response rather than fiber-matrix interface material behavior. The excessive compliance is caused by inherent imperfections in the contact of the sample and the test fixture. The femtosecond laser-machined samples are free of such imperfections. Finite element analysis has been accomplished to better understand the load-displacement response.
The Psychology Underlying Biased Forecasts of COVID-19 Cases and Deaths in the United States

This paper discusses the impact of a series of psychological phenomena on the U.S. response to COVID-19, focusing on forecasts of cases and deaths. The specific phenomena comprise unrealistic optimism bias, overconfidence, anchoring and adjustment, representativeness, motivated reasoning, and groupthink.
Tau Avoids the GTP Cap at Growing Microtubule Plus-Ends.

Summary Plus-end tracking proteins (+TIPs) associate with the growing end of microtubules and mediate important cellular functions. The majority of +TIPs are directed to the plus-end through a family of end-binding proteins (EBs), which preferentially bind the stabilizing cap of GTP-tubulin present during microtubule growth. One outstanding question is whether there may exist other microtubule-associated proteins (MAPs) that preferentially bind specific nucleotide states of tubulin. Here, we report that the neuronal MAP tau preferentially binds GDP-tubulin (KD = 0.26 μM) over GMPCPP-tubulin (KD = 1.1 μM) in vitro, as well as GTP-tubulin at the tips of growing microtubules, causing tau binding to lag behind the plus-end both in vitro and in live cells. Thus, tau is a microtubule tip avoiding protein, establishing the framework for a possible new class of tip avoiding MAPs. We speculate that disease-relevant tau mutations may exert their phenotype by their failure to properly recognize GDP-tubulin.
Directional approach to gradual cover: the continuous case

The objective of the cover location models is covering demand by facilities within a given distance. The gradual (or partial) cover replaces abrupt drop from full cover to no cover by defining gradual decline in cover. In this paper we use a recently proposed rule for calculating the joint cover of a demand point by several facilities termed “directional gradual cover”. Contrary to all gradual cover models, the joint cover depends on the facilities’ directions. In order to calculate the joint cover, existing models apply the partial cover by each facility disregarding their direction. We develop a genetic algorithm to solve the facilities location problem and also solve the problem for facilities that can be located anywhere in the plane. The proposed modifications were extensively tested on a case study of covering Orange County, California.
The Weak Ideal Property and Topological Dimension Zero

Following up on previous work, we prove a number of results for -algebras with the weak ideal property or topological dimension zero, and some results for -algebras with related properties. Some of the more important results include the following: • The weak ideal property implies topological dimension zero. • For a separable -algebra , topological dimension zero is equivalent to , to having the ideal property for some (or any) Kirchberg algebra , and to being residually hereditarily in the class of all -algebras such that contains a nonzero projection. • Extending the known result for , the classes of -algebras with residual , which are residually hereditarily (properly) infinite, or which are purely infinite and have the ideal property, are closed under crossed products by arbitrary actions of abelian 2-groups. • If and are separable, one of them is exact, has the ideal property, and has the weak ideal property, then has the weak ideal property. • If is a totally disconnected locally compact Hausdorff space and is a -algebra all of whose fibers have one of the weak ideal property, topological dimension zero, residual , or the combination of pure infiniteness and the ideal property, then also has the corresponding property (for topological dimension zero, provided is separable). • Topological dimension zero, the weak ideal property, and the ideal property are all equivalent for a substantial class of separable -algebras, including all separable locally algebras. • The weak ideal property does not imply the ideal property for separable -stable -algebras. We give other related results, as well as counterexamples to several other statements one might conjecture.
M-theory pp-waves, Penrose limits and supernumerary supersymmetries

Abstract We study supersymmetric pp-waves in M-theory, their dimensional reduction to D0-branes or pp-waves in type IIA, and their T-dualisation to solutions in the type IIB theory. The general class of pp-waves that we consider encompass the Penrose limits of AdSp×Sq with (p,q)=(4,7), (7,4), (3,3), (3,2), (2,3), (2,2), but includes also many other examples that can again lead to exactly-solvable massive strings, but which do not arise from Penrose limits. All the pp-waves in D=11 have 16 “standard” Killing spinors, but in certain cases one finds additional, or “supernumerary,” Killing spinors too. These give rise to linearly-realised supersymmetries in the string or matrix models. A focus of our investigation is on the circumstances when the Killing spinors are independent of particular coordinates (x+ or transverse-space coordinates), since these will survive at the field-theory level in dimensional reduction or T-dualisation.
Breather solutions of the nonlinear wave equation

We construct series solutions to all orders for breathers of Klein-Gordon equations, in powers of an amplitude parameter epsilon, under a sign condition on the coefficients of the expansion of the nonlinearity. All terms may be computed thanks to the properties of a 1D Schrodinger equation with two-soliton potential. We prove that this series is free of poles in the unit disc of the complex epsilon plane if and only if the equation is essentially equivalent to the sine-Gordon equation. This appears to be the only result that explains both what makes the sine-Gordon equation special from a PDE point of view, and at the same time, why approximate, long-lived breathers exist. In a related paper (Classical and Quantum Gravity, 25 (2008) 245004 ) we have extended this approach to address the soliton star problem in General Relativity.
Cooling rate for microbunched electron cooling without amplification

A new framework for the derivation of an analytical formula for microbunch electron cooling.
Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates

Collision avoidance for multi-robot systems is a difficult challenge under uncertainty, non-determinism, and lack of complete information. This paper aims to propose a collision avoidance framework that accounts for both measurement uncertainty and bounded motion uncertainty. In particular, we propose Probabilistic Safety Barrier Certificates (PrSBC) using Control Barrier Functions to define the space of possible control actions that are probabilistically safe. The framework entails minimally modifying an existing unconstrained controller to determine a safe controller via a quadratic program constrained to the chance-constrained safety set. The key advantage of the approach is that no assumptions about the form of uncertainty are required other than finite support, also enabling worst-case guarantees. We demonstrate effectiveness of the approach through experiments on a realistic simulation environment.
Nonequilibrium Steady States for Certain Hamiltonian Models

We report the results of a numerical study of nonequilibrium steady states for a class of Hamiltonian models. In these models of coupled matter-energy transport, particles exchange energy through collisions with pinned-down rotating disks. In Commun. Math. Phys. 262, 237-267, 2006, Eckmann and Young studied 1D chains and showed that certain simple formulas give excellent approximations of energy and particle density profiles. Keeping the basic mode of interaction in Commun. Math. Phys. 262, 237-267, 2006, we extend their prediction scheme to a number of new settings: 2D systems on different lattices, driven by a variety of boundary (heat bath) conditions including the use of thermostats. Particle-conserving models of the same type are shown to behave similarly. The second half of this paper examines memory and finite-size effects, which appear to impact only minimally the profiles of the models tested in Commun. Math. Phys. 262, 237-267, 2006. We demonstrate that these effects can be significant or insignificant depending on the local geometry. Dynamical mechanisms are proposed, and in the case of directional bias in particle trajectories due to memory, correction schemes are derived and shown to give accurate predictions.
Cassini Ring Seismology as a Probe of Saturn’s Interior. I. Rigid Rotation

Seismology of the gas giants holds the potential to resolve long-standing questions about their internal structure and rotation state. We construct a family of Saturn interior models constrained by the gravity field and compute their adiabatic mode eigenfrequencies and corresponding Lindblad and vertical resonances in Saturn's C ring, where more than twenty waves with pattern speeds faster than the ring mean motion have been detected and characterized using high-resolution Cassini Visual and Infrared Mapping Spectrometer (VIMS) stellar occultation data. We present identifications of the fundamental modes of Saturn that appear to be the origin of these observed ring waves, and use their observed pattern speeds and azimuthal wavenumbers to estimate the bulk rotation period of Saturn's interior to be $10{\rm h}\, 33{\rm m}\, 38{\rm s}^{+1{\rm m}\, 52{\rm s}}_{-1{\rm m}\, 19{\rm s}}$ (median and 5%/95% quantiles), significantly faster than Voyager and Cassini measurements of periods in Saturn's kilometric radiation, the traditional proxy for Saturn's bulk rotation period. The global fit does not exhibit any clear systematics indicating strong differential rotation in Saturn's outer envelope.
Broadband Optical Switch based on an Achromatic Photonic Gauge Potential in Dynamically Modulated Waveguides

Switching and routing of broadband optical signals is important for a number of emerging applications involving reprogrammable optical processors and microwave photonic signal processing. Conventional optical switches, based on static refractive-index modulation, are fundamentally limited in their switching bandwidth by disperse phase shifts. The authors show that $d\phantom{\rule{0}{0ex}}y\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}m\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}c$ refractive-index modulation can lead to achromatic phase shift, and thus an optical switch with a far broader bandwidth, overcoming the limitations of conventional switches. This has the potential to open up opportunities for on-chip processing of ultrabroadband optical pulses.
Gravitational collapse and its boundary description in AdS

We provide examples of gravitational collapse and black hole formation in AdS, either from collapsing matter shells or in analogy to the Oppenheimer-Sneider solution. We then investigate boundary properties of the corresponding states. In particular, we describe the boundary two-point function corresponding to a shell outside its horizon; if the shell is quasistatically lowered into the horizon, the resulting state is the Boulware state. We also describe the more physical Hartle-Hawking state, and discuss its connection to the quasistatic shell states and to thermalization on the boundary.
Detection of the Ultraviolet Spectrum of the Hot Subdwarf Companion of 60 Cygni (B1 Ve) from a Survey of IUE Spectra of Be Stars

We used archival International Ultraviolet Explorer (IUE) high-dispersion, short wavelength spectra data to search for evidence of the spectra of hot subdwarf companions of six rapidly rotating Be stars in binary systems. We searched for the signature of a hot companion through an analysis of the cross-correlation functions (CCFs) of observed and model spectra that were separated into primary and secondary components using a Doppler tomography algorithm and adopted spectroscopic orbital solutions. A positive detection of the flux from a hot companion was made for the reconstructed secondary CCF of just one target, 60 Cygni (B1 Ve). We estimate that the companion of the Be star in 60 Cygni has kK, mass ratio , and monochromatic flux ratio in the spectral region near 1525 A. If the companions of the other target Be stars are also hot, then they must be faint and contribute less than of the UV flux (<0.6% in the case of γ Cas). We also discuss a shell episode of Pleione (28 Tau) recorded in the IUE spectran in an appendix.
AGES OF STAR CLUSTERS IN THE TIDAL TAILS OF MERGING GALAXIES

We study the stellar content in the tidal tails of three nearby merging galaxies, NGC 520, NGC 2623, and NGC 3256, using BVI imaging taken with the Advanced Camera for Surveys on board the Hubble Space Telescope. The tidal tails in all three systems contain compact and fairly massive young star clusters, embedded in a sea of diffuse, unresolved stellar light. We compare the measured colors and luminosities with predictions from population synthesis models to estimate cluster ages and find that clusters began forming in tidal tails during or shortly after the formation of the tails themselves. We find a lack of very young clusters (≤10 Myr old), implying that eventually star formation shuts off in the tails as the gas is used up or dispersed. There are a few clusters in each tail with estimated ages that are older than the modeled tails themselves, suggesting that these may have been stripped out from the original galaxy disks. The luminosity function of the tail clusters can be described by a single power-law, dN/dL ∝ Lα, with −2.6 < α < −2.0. We find a stellar age gradient across some of the tidal tails, which we interpret as a superposition of (1) newly formed stars and clusters along the dense center of the tail and (2) a sea of broadly distributed, older stellar material ejected from the progenitor galaxies.
HiPPO: Recurrent Memory with Optimal Polynomial Projections

A central problem in learning from sequential data is representing cumulative history in an incremental fashion as more data is processed. We introduce a general framework (HiPPO) for the online compression of continuous signals and discrete time series by projection onto polynomial bases. Given a measure that specifies the importance of each time step in the past, HiPPO produces an optimal solution to a natural online function approximation problem. As special cases, our framework yields a short derivation of the recent Legendre Memory Unit (LMU) from first principles, and generalizes the ubiquitous gating mechanism of recurrent neural networks such as GRUs. This formal framework yields a new memory update mechanism (HiPPO-LegS) that scales through time to remember all history, avoiding priors on the timescale. HiPPO-LegS enjoys the theoretical benefits of timescale robustness, fast updates, and bounded gradients. By incorporating the memory dynamics into recurrent neural networks, HiPPO RNNs can empirically capture complex temporal dependencies. On the benchmark permuted MNIST dataset, HiPPO-LegS sets a new state-of-the-art accuracy of 98.3%. Finally, on a novel trajectory classification task testing robustness to out-of-distribution timescales and missing data, HiPPO-LegS outperforms RNN and neural ODE baselines by 25-40% accuracy.
Self-explaining AI as an alternative to interpretable AI

The ability to explain decisions made by AI systems is highly sought after, especially in domains where human lives are at stake such as medicine or autonomous vehicles. While it is often possible to approximate the input-output relations of deep neural networks with a few human-understandable rules, the discovery of the double descent phenomena suggests that such approximations do not accurately capture the mechanism by which deep neural networks work. Double descent indicates that deep neural networks typically operate by smoothly interpolating between data points rather than by extracting a few high level rules. As a result, neural networks trained on complex real world data are inherently hard to interpret and prone to failure if asked to extrapolate. To show how we might be able to trust AI despite these problems we introduce the concept of self-explaining AI. Self-explaining AIs are capable of providing a human-understandable explanation of each decision along with confidence levels for both the decision and explanation. Some difficulties with this approach along with possible solutions are sketched. Finally, we argue it is important that deep learning based systems include a “warning light” based on techniques from applicability domain analysis to warn the user if a model is asked to extrapolate outside its training distribution.
Commensurability classes containing three knot complements

The study of the commensurability classes of hyperbolic knot complements that contain other knot complements has attracted some recent interest (see Boileau, Boyer and Walsh [4], Calegari and Dunfield [6], Goodman, Heard and Hodgson [13] Hoste and Shanahan [14], Macasieb and Mattman [15], Neumann and Reid [19], Reid [20] and Reid and Walsh [21]). A particularly interesting set of examples results from cyclic surgeries on hyperbolic knot complements, since the cyclic surgeries give rise to cyclic covers by other knot complements (see Gonzalez-Acuna and Whitten [11]). Moreover, the Cyclic Surgery Theorem of Culler, Gordon, Luecke and Shalen [8] shows that there are at most two nontrivial cyclic surgeries on a hyperbolic knot complement and so a hyperbolic knot complement has at most two nontrivial, finite sheeted covers which are other knot complements. Similarly, if a hyperbolic knot complement, S k1 is covered by another knot complement, S k2 , then S k1 admits a cyclic surgery. There are known examples of hyperbolic knot complements with exactly three knot complements in their commensurability classes. For example, the . 2; 3; 7/ pretzel knot famously admits two nontrivial cyclic surgeries by Fintushel and Stern [10] and is therefore covered by two other hyperbolic knot complements. Indeed, one can show that these three knot complements are the only knot complements in their commensurability class (see Section 4.1, case n D 1, m D 0, Section 2.1 and Reid and Walsh [21, Corollary 5.4]).
Rapid Formation of Super-Earths around M Dwarf Stars

While the recent microlensing discoveries of super-Earths orbiting two M dwarf stars have been taken as support for the core accretion mechanism of giant planet formation, we show here that these planets could also have been formed by the competing mechanism of disk instability, coupled with photoevaporative loss of their gaseous envelopes by a strong external source of UV radiation, i.e., an O star. M dwarfs that form in regions of future high-mass star formation would then be expected to have super-Earths orbiting at distances of several AU and beyond, while those that form in regions of low-mass star formation would be expected to have gas giants at those distances. Given that most stars are born in the former rather than in the latter regions, M dwarfs should have significantly more super-Earths than gas giants, as seems to be indicated by the microlensing surveys.
Finitistic Extension Degree

We introduce the finitistic extension degree of a ring and investigate rings for which it is finite. The Auslander–Reiten Conjecture is proved for rings of finite finitistic extension degree and these rings are also shown to have finite finitistic dimension. We apply these results to better understand a generalized version of the Auslander–Reiten Condition for Gorenstein rings. We also record how the finitistic extension degree behaves with respect to many change of ring procedures that arise frequently in the commutative setting.
On the number of 2-sat functions

We give an alternative proof of a conjecture of Bollobas, Brightwell and Leader, first proved by Peter Allen, stating that the number of Boolean functions definable by 2-SAT formulae is $(1+o(1))2^{\binom{n+1}{2}}$. $(1+o(1))2^{\scurvy{n+1}{2}}$ . One step in the proof determines the asymptotics of the number of ‘odd-blue-triangle-free’ graphs on n vertices.
Baryon spectroscopy with polarization observables from CLAS

The spectrum of nucleon excitations is dominated by broad and overlapping resonances. Polarization observables in photoproduction reactions are key in the study of these excitations. They give indispensable constraints to partial-wave analyses and help clarify the spectrum. A series of polarized photoproduction experiments have been performed at the Thomas Jefferson National Accelerator Facility with the CEBAF Large Acceptance Spectrometer. These measurements include data with linearly and circularly polarized tagged-photon beams, longitudinally and transversely polarized proton and deuterium targets, and recoil polarizations through the observation of the weak decay of hyperons. An overview of these studies and recent results will be given.
Flux Norm Approach to Finite Dimensional Homogenization Approximations with Non-Separated Scales and High Contrast

We consider linear divergence-form scalar elliptic equations and vectorial equations for elasticity with rough (L∞(Ω)Ω⊂R^d) coefficients a(x) that, in particular, model media with non-separated scales and high contrast in material properties. While the homogenization of PDEs with periodic or ergodic coefficients and well separated scales is now well understood, we consider here the most general case of arbitrary bounded coefficients. For such problems, we introduce explicit and optimal finite dimensional approximations of solutions that can be viewed as a theoretical Galerkin method with controlled error estimates, analogous to classical homogenization approximations. In particular, this approach allows one to analyze a given medium directly without introducing the mathematical concept of an e family of media as in classical homogenization. We define the flux norm as the L^2 norm of the potential part of the fluxes of solutions, which is equivalent to the usual H^1-norm. We show that in the flux norm, the error associated with approximating, in a properly defined finite-dimensional space, the set of solutions of the aforementioned PDEs with rough coefficients is equal to the error associated with approximating the set of solutions of the same type of PDEs with smooth coefficients in a standard space (for example, piecewise polynomial). We refer to this property as the transfer property. A simple application of this property is the construction of finite dimensional approximation spaces with errors independent of the regularity and contrast of the coefficients and with optimal and explicit convergence rates. This transfer property also provides an alternative to the global harmonic change of coordinates for the homogenization of elliptic operators that can be extended to elasticity equations. The proofs of these homogenization results are based on a new class of elliptic inequalities. These inequalities play the same role in our approach as the div-curl lemma in classical homogenization.
Engineering Dzyaloshinskii-Moriya interaction in B20 thin-film chiral magnets

Chiral magnetic $\mathrm{M}{\mathrm{n}}_{x}\mathrm{F}{\mathrm{e}}_{1\ensuremath{-}x}\mathrm{Ge}$ compounds have an antisymmetric exchange interaction that is tunable with the manganese stoichiometric fraction, $x$. Although millimeter-scale, polycrystalline bulk samples of this family of compounds have been produced, thin-film versions of these materials will be necessary for devices. In this study, we demonstrate the growth of epitaxial $\mathrm{M}{\mathrm{n}}_{x}\mathrm{F}{\mathrm{e}}_{1\ensuremath{-}x}\mathrm{Ge}$ thin films on Si(111) substrates with a pure B20 crystal structure in the stoichiometric fraction range $x$ from 0 to 0.81. Following systematic structural analysis and magnetic characterization consisting of dc magnetization measurements and microwave absorption spectroscopy, we quantify the antisymmetric exchange interaction and helical period as a function of $x$, which ranges from 200 nm to 8 nm. Our results demonstrate an approach to engineering the size of magnetic skyrmions in epitaxial films that are grown using scalable techniques.
Consistent group selection in high-dimensional linear regression

In regression problems where covariates can be naturally grouped, the group Lasso is an attractive method for variable selection since it respects the grouping structure in the data. We study the selection and estimation properties of the group Lasso in high-dimensional settings when the number of groups exceeds the sample size. We provide sufficient conditions under which the group Lasso selects a model whose dimension is comparable with the underlying model with high probability and is estimation consistent. However, the group Lasso is, in general, not selection consistent and also tends to select groups that are not important in the model. To improve the selection results, we propose an adaptive group Lasso method which is a generalization of the adaptive Lasso and requires an initial estimator. We show that the adaptive group Lasso is consistent in group selection under certain conditions if the group Lasso is used as the initial estimator.
Microparticle cloud imaging and tracking for data-driven plasma science

Oceans of image and particle track data encountered in plasma interactions with microparticle clouds motivate development and applications of machine-learning (ML) algorithms. A local-constant-velocity tracker, a Kohonen neural network or self-organizing map, the feature tracking kit, and U-Net are described and compared with each other for microparticle cloud datasets generated from exploding wires, dusty plasmas, and atmospheric plasmas. Particle density and the signal-to-noise ratio have been identified as two important factors that affect the tracking accuracy. Fast Fourier transform is used to reveal how U-Net, a deep convolutional neural network developed for non-plasma applications, achieves the improvements for noisy scenes. Viscous effects are revealed in the ballistic motions of the particles from the exploding wires and atmospheric plasmas. Subdiffusion of microparticles satisfying Δ r 2 ∝ t k ( k = 0.84 ± 0.02) is obtained from the dusty plasma datasets. Microparticle cloud imaging and tracking, when enhanced with data and ML models, present new possibilities for plasma physics.
Bandgap widening by disorder in rainbow metamaterials

Stubbed plates, i.e., thin elastic sheets endowed with pillar-like resonators, display subwavelength, locally resonant bandgaps that are primarily controlled by the intrinsic resonance properties of the pillars. In this work, we experimentally study the bandgap response of a tunable heterogeneous plate endowed with reconfigurable families of pillars. We demonstrate that, under certain circumstances, both the spectrum of resonant frequencies of the pillars and their spatial arrangement influence the filtering characteristics of the system. Specifically, both spatially graded and disordered arrangements result in bandgap widening. Moreover, the spectral range over which attenuation is achieved with random arrangements is on average wider than the one observed with graded configurations.
Stable manifolds and the transition to turbulence in pipe flow

Lower branch travelling waves and equilibria computed in pipe flow and other shear flows appear intermediate between turbulent and laminar motions. We take a step towards connecting these lower branch solutions to transition by deriving a numerical method for finding certain special disturbances of the laminar flow in a short pipe. These special disturbances cause the disturbed velocity field to approach the lower branch solution by evolving along its stable manifold. If the disturbance were slightly smaller, the flow would relaminarize, and if slightly larger, it would transition to a turbulent state.
Genus‐2 Jacobians with torsion points of large order

We produce new explicit examples of genus-2 curves over the rational numbers whose Jacobian varieties have rational torsion points of large order. In particular, we produce a family of genus-2 curves over Q whose Jacobians have a rational point of order 48, parametrized by a rank-2 elliptic curve over Q, and we exhibit a single genus-2 curve over Q whose Jacobian has a rational point of order 70, the largest order known. We also give new examples of genus-2 Jacobians with rational points of order 27, 28, and 39. Most of our examples are produced by `gluing' two elliptic curves together along their n-torsion subgroups, where n is either 2 or 3. The 2-gluing examples arise from techniques developed by the author in joint work with Lepr\'evost and Poonen 15 years ago. The 3-gluing examples are made possible by an algorithm for explicit 3-gluing over non-algebraically closed fields recently developed by the author in joint work with Br\"oker, Lauter, and Stevenhagen.
Health Care Workers Deserve Better Protections From Coronavirus Disease 2019

Among the 232,000 deaths in the US attributable to coronavirus disease 2019 (COVID-19) are more than 1336 physicians, nurses, environmental staff members, technicians, orderlies, emergency medical technicians, and other health care workers. Deaths of health care workers of COVID-19 are a testament to their ethical duties and heroic frontline efforts despite profound risks. Yet they are also an illustration of legal and policy failures to protect them from harm at their workplaces. This is not just a question of injustice for health care workers; it is a risk for every American person. As noted in this commentary, there are a host of law and policy approaches to assuring greater safety and accountability for U.S. health care workers seeking to serve amid the risks of the COVID-19 pandemic.
ON THE FORMATION OF HOT JUPITERS IN STELLAR BINARIES

We study the production of hot Jupiters (HJs) in stellar binaries. We show that the “eccentric Kozai–Lidov” (EKL) mechanism can play a key role in the dynamical evolution of a star–planet–star triple system. We run a large set of Monte Carlo simulations including the secular evolution of the orbits, general relativistic precession, and tides, and we determine the semimajor axis, eccentricity, inclination, and spin–orbit angle distributions of the HJs that are produced. We explore the effect of different tidal friction parameters on the results. We find that the efficiency of forming HJs when taking the EKL mechanism into account is higher then previously estimated. Accounting for the frequency of stellar binaries, we find that this production mechanism can account for about 30% of the observed HJ population. Current observations of spin–orbit angles are consistent with this mechanism producing ∼30% of all HJs, and up to 100% of the misaligned systems. Based on the properties of binaries without an HJ in our simulations, we predict the existence of many Jupiter-like planets with moderately eccentric and inclined orbits and semimajor axes of several AU.
ASTROPHYSICAL PRIOR INFORMATION AND GRAVITATIONAL-WAVE PARAMETER ESTIMATION

The detection of electromagnetic counterparts to gravitational waves (GWs) has great promise for the investigation of many scientific questions. While it is well known that certain orientation parameters can reduce uncertainty in other related parameters, it was also hoped that the detection of an electromagnetic signal in conjunction with a GW could augment the measurement precision of the mass and spin from the gravitational signal itself. That is, knowledge of the sky location, inclination, and redshift of a binary could break degeneracies between these extrinsic, coordinate-dependent parameters and the physical parameters that are intrinsic to the binary. In this paper, we investigate this issue by assuming perfect knowledge of extrinsic parameters, and assessing the maximal impact of this knowledge on our ability to extract intrinsic parameters. We recover similar gains in extrinsic recovery to earlier work; however, we find only modest improvements in a few intrinsic parameters—namely the primary component's spin. We thus conclude that, even in the best case, the use of additional information from electromagnetic observations does not improve the measurement of the intrinsic parameters significantly.
Influence Maximization for Fixed Heterogeneous Thresholds

Influence Maximization is a NP-hard problem of selecting the optimal set of influencers in a network. Here, we propose two new approaches to influence maximization based on two very different metrics. The first metric, termed Balanced Index (BI), is fast to compute and assigns top values to two kinds of nodes: those with high resistance to adoption, and those with large out-degree. This is done by linearly combining three properties of a node: its degree, susceptibility to new opinions, and the impact its activation will have on its neighborhood. Controlling the weights between those three terms has a huge impact on performance. The second metric, termed Group Performance Index (GPI), measures performance of each node as an initiator when it is a part of randomly selected initiator set. In each such selection, the score assigned to each teammate is inversely proportional to the number of initiators causing the desired spread. These two metrics are applicable to various cascade models; here we test them on the Linear Threshold Model with fixed and known thresholds. Furthermore, we study the impact of network degree assortativity and threshold distribution on the cascade size for metrics including ours. The results demonstrate our two metrics deliver strong performance for influence maximization.
What Bandwidth Do I Need for My Image

Computer representations of real numbers are necessarily discrete, with some finite resolution, discreteness, quantization, or minimum representable difference. We perform astrometric and photometric measurements on stars and co-add multiple observations of faint sources to demonstrate that essentially all of the scientific information in an optical astronomical image can be preserved or transmitted when the minimum representable difference is a factor of 2 finer than the root variance of the per-pixel noise. Adopting a representation this coarse reduces bandwidth for data acquisition, transmission, or storage, or permits better use of the system dynamic range, without sacrificing any information for downstream data analysis, including information on sources fainter than the minimum representable difference itself.
Towards age/rotation/magnetic activity relation with seismology

The knowledge of stellar ages directly impacts the characterization of a planetary system as it puts strong constraints on the moment when the system was born. Unfortunately, the determination of precise stellar ages is a very difficult task. Different methods can be used to do so (based on isochrones or chemical element abundances) but they usually provide large uncertainties. During its evolution a star goes through processes leading to loss of angular momentum but also changes in its magnetic activity. Building rotation, magnetic, age relations would be an asset to infer stellar ages model independently. Several attempts to build empirical relations between rotation and age (namely gyrochronology) were made with a focus on cluster stars where the age determination is easier and for young stars on the main sequence. For field stars, we can now take advantage of high-precision photometric observations where we can perform asteroseismic analyses to improve the accuracy of stellar ages. Furthermore, the variability in the light curves allow us to put strong constraints on the stellar rotation and magnetic activity. By combining these precise measurements, we are on the way of understanding and improving relations between magnetic activity, rotation, and age, in particular at different stages of stellar evolution. I will review the status on gyrochronology relationships based on observations of young cluster stars. Then I will focus on solar-like stars and describe the inferences on stellar ages, rotation, and magnetism that can be provided by high-quality photometric observations such as the ones of the Kepler mission, in particular through asteroseismic analyses.