cssi/SciSciGPT-SciSciNet huggingface dataset:
A non-exponential extension of Sanov's theorem via convex duality

This work is devoted to a vast extension of Sanov’s theorem, in Laplace principle form, based on alternatives to the classical convex dual pair of relative entropy and cumulant generating functional. The abstract results give rise to a number of probabilistic limit theorems and asymptotics. For instance, widely applicable non-exponential large deviation upper bounds are derived for empirical distributions and averages of independent and identically distributed samples under minimal integrability assumptions, notably accommodating heavy-tailed distributions. Other interesting manifestations of the abstract results include new results on the rate of convergence of empirical measures in Wasserstein distance, uniform large deviation bounds, and variational problems involving optimal transport costs, as well as an application to error estimates for approximate solutions of stochastic optimization problems. The proofs build on the Dupuis–Ellis weak convergence approach to large deviations as well as the duality theory for convex risk measures.
MDINFERENCE: Balancing Inference Accuracy and Latency for Mobile Applications

Deep Neural Networks are allowing mobile devices to incorporate a wide range of features into user applications. However, the computational complexity of these models makes it difficult to run them effectively on resource-constrained mobile devices. Prior work approached the problem of supporting deep learning in mobile applications by either decreasing model complexity or utilizing powerful cloud servers. These approaches each only focus on a single aspect of mobile inference and thus they often sacrifice overall performance.In this work we introduce a holistic approach to designing mobile deep inference frameworks. We first identify the key goals of accuracy and latency for mobile deep inference and the conditions that must be met to achieve them. We demonstrate our holistic approach through the design of a hypothetical framework called MDINFERENCE. This framework leverages two complementary techniques; a model selection algorithm that chooses from a set of cloud-based deep learning models to improve inference accuracy and an on-device request duplication mechanism to bound latency. Through empirically-driven simulations we show that MDINFERENCE improves aggregate accuracy over static approaches by over 40% without incurring SLA violations. Additionally, we show that with a target latency of 250ms, MDINFERENCE increased the aggregate accuracy in 99.74% cases on faster university networks and 96.84% cases on residential networks.
Resolution-Exact Planner for Thick Non-Crossing 2-Link Robots

We consider the path planning problem for a 2-link robot amidst polygonal obstacles. Our robot is parametrizable by the lengths \(\ell _{1},\ell _{2} > 0\) of its two links, the thickness \(\tau \ge 0\) of the links, and an angle \(\kappa \) that constrains the angle between the 2 links to be strictly greater than \(\kappa \). The case \(\tau > 0\) and \(\kappa \ge 0 \) corresponds to “thick non-crossing” robots. This results in a novel 4DOF configuration space \(\mathbb {R}^{2}\times (\mathbb {T}^{2}\backslash \varDelta (\kappa ))\) where \(\mathbb {T}^{2}\) is the torus and \(\varDelta (\kappa )\) the diagonal band of width \(\kappa \).
1,2,3,4,5-Pentamethylcyclopentadiene

1,2,3,4,5-Pentamethylcyclopentadiene product: 1,2,3,4,5-Pentamethylcyclopentadiene Keywords: addition, to CO; alkylation, C-alkylation; annulation, carbocyclic-[5]; cyclization, condensation; grignard and related reactions; metalation reactions, lithium; 2-bromo-2-butene (cis and trans mixture); 2-lithio-2-butene
Reconstruction of the interatomic forces from dynamic Scanning Transmission Electron Microscopy data

We explore the possibility for reconstruction of the generative physical models describing interactions between atomic units in solids from observational electron microscopy data. Here, scanning transmission electron microscopy (STEM) is used to observe the dynamic motion of Si atoms at the edge of monolayer graphene under continuous electron beam illumination. The resulting time-lapsed STEM images represent the snapshots of observed chemical states of the system. We use two approaches: potential of mean force calculation using a radial distribution function and a direct fitting of the graphene–Si interatomic pairwise potentials with force matching, to reconstruct the force fields in the materials. These studies lay the foundation for quantitative analysis of materials energetics from STEM data through the sampling of the metastable states in the chemical space of the system.
Online Learning with Continuous Variations: Dynamic Regret and Reductions

Online learning is a powerful tool for analyzing iterative algorithms. However, the classic adversarial setup sometimes fails to capture certain regularity in online problems in practice. Motivated by this, we establish a new setup, called Continuous Online Learning (COL), where the gradient of online loss function changes continuously across rounds with respect to the learner's decisions. We show that COL covers and more appropriately describes many interesting applications, from general equilibrium problems (EPs) to optimization in episodic MDPs. In particular, we show monotone EPs admits a reduction to achieving sublinear static regret in COL. Using this new setup, we revisit the difficulty of sublinear dynamic regret. We prove a fundamental equivalence between achieving sublinear dynamic regret in COL and solving certain EPs. With this insight, we offer conditions for efficient algorithms that achieve sublinear dynamic regret, even when the losses are chosen adaptively without any a priori variation budget. Furthermore, we show for COL a reduction from dynamic regret to both static regret and convergence in the associated EP, allowing us to analyze the dynamic regret of many existing algorithms.
Constant Q-curvature metrics on conic 4-manifolds

We consider the constant Q-curvature metric problem in the given conformal class on conic 4-manifolds and study related differential equations.
Interstellar Grain Alignment: Observational Status

Interstellar polarization in the optical/infrared has long been known to be due to asymmetrical dust grains aligned with the magnetic field and can potentially provide a resource effective way to probe both the topology and strength of the magnetic-field. However, to do so with confidence, the physics and variability of the alignment mechanisms must be quantitatively understood. The last 15 years has seen major advancements in both the theoretical and observational understanding of this problem. I here review the current state of the observational constraints on the grain alignment physics. While none of the three classes of proposed grain alignment theories: mechanical, paramagnetic relaxation and radiative alignment torque, can be viewed as having been empirically confirmed, the first two have failed some critical observational tests, whereas the latter has recently been given specific observational support and must now be viewed as the leading candidate.
Gradient descent algorithms for Bures-Wasserstein barycenters

We study first order methods to compute the barycenter of a probability distribution $P$ over the space of probability measures with finite second moment. We develop a framework to derive global rates of convergence for both gradient descent and stochastic gradient descent despite the fact that the barycenter functional is not geodesically convex. Our analysis overcomes this technical hurdle by employing a Polyak-\L{}ojasiewicz (PL) inequality and relies on tools from optimal transport and metric geometry. In turn, we establish a PL inequality when $P$ is supported on the Bures-Wasserstein manifold of Gaussian probability measures. It leads to the first global rates of convergence for first order methods in this context.
Universal Masking in the United States: The Role of Mandates, Health Education, and the CDC.

The Centers for Disease Control and Prevention (CDC) recommends cloth face coverings in public settings to prevent spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). Face coverings decrease the amount of infectious virus exhaled into the environment, reducing the risk an exposed person will become infected.1 Although many states and localities have ordered mask use, considerable variability and inconsistencies exist. Would a national mandate be an effective COVID-19 prevention strategy, and would it be lawful? Given the patchwork of state pandemic responses, should the CDC have enhanced funding and powers to forge a nationally coordinated response to COVID-19 and to future health emergencies?
Adaptive Workload Allocation for Multi-Human Multi-Robot Teams for Independent and Homogeneous Tasks

Multi-human multi-robot (MH-MR) systems have the ability to combine the potential advantages of robotic systems with those of having humans in the loop. Robotic systems contribute precision performance and long operation on repetitive tasks without tiring, while humans in the loop improve situational awareness and enhance decision-making abilities. A system's ability to adapt allocated workload to changing conditions and the performance of each individual (human and robot) during the mission is vital to maintaining overall system performance. Previous works from literature including market-based and optimization approaches have attempted to address the task/workload allocation problem with focus on maximizing the system output without regarding individual agent conditions, lacking in real-time processing and have mostly focused exclusively on multi-robot systems. Given the variety of possible combination of teams (autonomous robots and human-operated robots: any number of human operators operating any number of robots at a time) and the operational scale of MH-MR systems, development of a generalized framework of workload allocation has been a particularly challenging task. In this article, we present such a framework for independent homogeneous missions, capable of adaptively allocating the system workload in relation to health conditions and work performances of human-operated and autonomous robots in real-time. The framework consists of removable modular function blocks ensuring its applicability to different MH-MR scenarios. A new workload transition function block ensures smooth transition without the workload change having adverse effects on individual agents. The effectiveness and scalability of the system's workload adaptability is validated by experiments applying the proposed framework in a MH-MR patrolling scenario with changing human and robot condition, and failing robots.
Three-omega thermal-conductivity measurements with curved heater geometries

The three-omega method, a powerful technique to measure the thermal conductivity of nanometer-thick films and the interfaces between them, has historically employed straight conductive wires to act as both heaters and thermometers. When investigating stochastically prepared samples such as two-dimensional materials and nanomembranes, residue and excess material can make it difficult to fit the required millimeter-long straight wire on the sample surface. There are currently no available criteria for how diverting three-omega heater wires around obstacles affects the validity of the thermal measurement. In this Letter, we quantify the effect of the wire curvature by performing three-omega experiments with a wide range of frequencies using both curved and straight heater geometries on SiO2/Si samples. When the heating wire is curved, we find that the measured Si substrate thermal conductivity changes by only 0.2%. Similarly, we find that wire curvature has no significant effect on the determination of the thermal resistance of an ∼65 nm SiO2 layer, even for the sharpest corners considered here, for which the largest measured ratio of the thermal penetration depth of the applied thermal wave to radius of curvature of the heating wire is 4.3. This result provides useful design criteria for three-omega experiments by setting a lower bound for the maximum ratio of the thermal penetration depth to wire radius of curvature.
Chance Constraint Tuning for Optimal Power Flow

In this paper, we consider a chance-constrained formulation of the optimal power flow problem to handle uncertainties resulting from renewable generation and load variability. We propose a tuning method that iterates between solving an approximated reformulation of the optimization problem and using a posteriori sample-based evaluations to refine the reformulation. Our method is applicable to both single and joint chance constraints and does not rely on any distributional assumptions on the uncertainty. In a case study for the IEEE 24-bus system, we demonstrate that our method is computationally efficient and enforces chance constraints without over-conservatism.
The probability of choosing both hands depends on an interaction between motor capacity and limb-specific control in chronic stroke.

A goal of rehabilitation after stroke is to promote pre-stroke levels of arm use for every day, frequently bimanual, functional activities. We reasoned that, after a stroke, the choice to use one or both hands for bimanual tasks might depend not only on residual motor capacity, but also the specialized demands imposed by the task on the paretic hand. To capture spontaneous, task-specific choices, we covertly observed 50 pre-stroke right-handed chronic stroke survivors (25 each of left, LHD, and right-hemisphere damage, RHD) and 11 age-similar control adults and recorded their hand use strategies for two pairs of bimanual tasks with distinct demands: one with greater precision requirements (photo-album tasks), and another with greater stabilization requirements (letter-envelope tasks). The primary outcome was the choice to use one or both hands. Logistic regression was used to test the two hypotheses that the probability of choosing a bimanual strategy would be greater in those with less severe motor impairment and also in those with LHD. When collapsed across the four tasks, we found support for these hypotheses. Notably, however, the influence of these factors on bimanual choice varied based on task demands. For the photo–album pair, the probability of a bimanual strategy was greater for those with LHD compared to RHD, regardless of the degree of motor impairment. For the letter–envelope pair, we found a significant interaction between impairment and side of lesion in determining the likelihood of choosing both hands. Therefore, the manner in which side of lesion moderates the effect of impairment on hand use depends on the task.
Why are countries’ asset portfolios exposed to nominal exchange rates?

Abstract Most countries hold large gross asset positions, lending in their domestic currency and borrowing in foreign currency. As a result, their balance sheets are exposed to nominal exchange rate movements. We argue that when asset markets are incomplete, this exposure provides partial insurance against shocks that move exchange rates. We demonstrate that this insurance motive can simultaneously generate realistic gross asset positions and resolve the Backus-Smith puzzle: that countries’ relative consumption and real exchange rates are negatively correlated. Local perturbation methods are inaccurate in this setting as they approximate around the wrong interest rate, even when they correctly characterize the average portfolio holdings. So to accurately solve the equilibrium portfolio problem, we extend Maliar and Maliar (2015)’s global projection method.
Uniqueness of some Calabi-Yau metrics on $\mathbf{C}^n$

We consider the Calabi–Yau metrics on $$\mathbf {C}^n$$ constructed recently by Yang Li, Conlon–Rochon, and the author, that have tangent cone $$\mathbf {C}\times A_1$$ at infinity for the $$(n-1)$$ -dimensional Stenzel cone $$A_1$$ . We show that up to scaling and isometry this Calabi–Yau metric on $$\mathbf {C}^n$$ is unique. We also discuss possible generalizations to other manifolds and tangent cones.
Do You Know Your Enemy: The Role of Known Actors as Framing Devices in News Media

We examine how and why al-Qa’ida and the Islamic State of Iraq and Syria have come to dominate discourse of the international terrorist threat in the post-9/11 era, through their emergence as the primary referents for understanding terrorism, the organizations that employ it, and the actions taken to combat it. We propose a simple mechanism—based on relevance theory—wherein a given actor might attain and sustain a socially shared understanding, allowing them to function as symbolic referents in media discourse. In Study 1, we address the plausibility of this mechanism, using computer-assisted linguistic analysis to assess coverage of Foreign Terrorist Organizations in The New York Times and Wall Street Journal from 1996 to 2017. In Study 2, we conduct an inductive framing analysis aimed at identifying unique and commonly reoccurring applications of framing packages relying on known actors as framing devices. We conclude by discussing implications of these practices.
Sharp Estimate of Global Coulomb Gauge

Let $A$ be a $W^{1,2}$-connection on a principle $\text{SU}(2)$-bundle $P$ over a compact $4$-manifold $M$ whose curvature $F_A$ satisfies $\|F_A\|_{L^2(M)}\le \Lambda$. Our main result is the existence of a global section $\sigma: M\to P$ with finite singularities on $M$ such that the connection form $\sigma^*A$ satisfies the Coulomb equation $d^*(\sigma^*A)=0$ and admits a sharp estimate $\|\sigma^*A\|_{\mathcal{L}^{4,\infty}(M)}\le C(M,\Lambda)$. Here $\mathcal{L}^{4,\infty}$ is a new function space we introduce in this paper that satisfies $L^4(M)\subsetneq \mathcal{L}^{4,\infty}(M)\subsetneq L^{4-\epsilon}(M)$ for all $\epsilon>0$.
Improved Performance on Moving-Mass Hopping Robots with Parallel Elasticity

Robotic Hopping is challenging from the perspective of both modeling the dynamics as well as the mechanical design due to the short period of ground contact in which to actuate on the world. Previous work has demonstrated stable hopping on a moving-mass robot, wherein a single spring was utilized below the body of the robot. This paper finds that the addition of a spring in parallel to the actuator greatly improves the performance of moving mass hopping robots. This is demonstrated through the design of a novel one-dimensional hopping robot. For this robot, a rigorous trajectory optimization method is developed using hybrid systems models with experimentally tuned parameters. Simulation results are used to study the effects of a parallel spring on energetic efficiency, stability, and hopping effort. We find that the double-spring model had 2.5x better energy efficiency than the single-spring model, and was able to hop using 40% less peak force from the actuator. Furthermore, the double-spring model produces stable hopping without the need for stabilizing controllers. These concepts are demonstrated experimentally on a novel hopping robot, wherein hop heights up to 40cm were achieved with comparable efficiency and stability.
Robot-Supervised Learning for Object Segmentation

To be effective in unstructured and changing environments, robots must learn to recognize new objects. Deep learning has enabled rapid progress for object detection and segmentation in computer vision; however, this progress comes at the price of human annotators labeling many training examples. This paper addresses the problem of extending learning-based segmentation methods to robotics applications where annotated training data is not available. Our method enables pixelwise segmentation of grasped objects. We factor the problem of segmenting the object from the background into two sub-problems: (1) segmenting the robot manipulator and object from the background and (2) segmenting the object from the manipulator. We propose a kinematics-based foreground segmentation technique to solve (1). To solve (2), we train a self-recognition network that segments the robot manipulator. We train this network without human supervision, leveraging our foreground segmentation technique from (1) to label a training set of images containing the robot manipulator without a grasped object. We demonstrate experimentally that our method outperforms state-of-the-art adaptable in-hand object segmentation. We also show that a training set composed of automatically labelled images of grasped objects improves segmentation performance on a test set of images of the same objects in the environment.
Addressing the gap in laparoscopic common bile duct exploration training for rural surgeons: imparting procedural ability is not enough

Laparoscopic common bile duct exploration (LCBDE) is an underutilized therapy for choledocholithiasis. The driving factors of this practice gap are poorly defined. We sought to evaluate the attitudes and practice patterns of surgeons who underwent training courses using an LCBDE simulator. Surgeons completed a half-day simulator-based LCBDE curriculum at national courses, including the American College of Surgeons Advanced Skills Training for Rural Surgeons and the Society of American Gastrointestinal and Endoscopic Surgeons annual meeting. Attitudes were assessed with Likert surveys immediately before and after curriculum completion. Follow-up surveys were distributed electronically. 159 surgeons completed training during six courses. Surgeon attitudes regarding the overall superiority of LCBDE vs. ERCP shifted towards favoring LCBDE after course participation (4.0 vs 3.3; Likert scale 1–5, p < 0.001). 44% of surgeons completed follow-up surveys at a mean of 3 years post-course. Surgeons remained confident in their ability to perform LCBDE, with only 14% rating their skill as a significant barrier to practice, as compared with 43% prior to course participation (p < 0.01). However, only 28% of surgeons saw an increase in LCBDE volume. Deficiencies in operating room (OR) staff knowledge and instrument availability were the most significant barriers to post-course practice implementation and were inversely correlated with LCBDE case volume (ρ = − 0.44 and − 0.47, both p < 0.01). Surgeons for whom OR staff knowledge of LCBDE was not a significant barrier performed nearly 4 times more LCBDE than those who rated staff knowledge as a moderate, strong, or complete barrier. Surgeons trained at an LCBDE course retained long-term confidence in their procedural ability. Practice implementation was hindered by deficiencies in OR staff knowledge and instrument availability. Surgeons with knowledgeable operating room staff performed significantly more LCBDEs than those with less capable assistance. These barriers should be addressed in future curricula to improve procedural adoption.
Coronavirus infection and PARP expression dysregulate the NAD metabolome: An actionable component of innate immunity.

Poly(ADP-ribose) polymerase (PARP) superfamily members covalently link either a single ADP-ribose (ADPR) or a chain of ADPR units to proteins using NAD as the source of ADPR. Although the well-known poly(ADP-ribosylating) (PARylating) PARPs primarily function in the DNA damage response, many noncanonical mono(ADP-ribosylating) (MARylating) PARPs are associated with cellular antiviral responses. We recently demonstrated robust up-regulation of several PARPs following infection with murine hepatitis virus (MHV), a model coronavirus. Here we show that SARS-CoV-2 infection strikingly up-regulates MARylating PARPs and induces the expression of genes encoding enzymes for salvage NAD synthesis from nicotinamide (NAM) and nicotinamide riboside (NR), while down-regulating other NAD biosynthetic pathways. We show that overexpression of PARP10 is sufficient to depress cellular NAD and that the activities of the transcriptionally induced enzymes PARP7, PARP10, PARP12 and PARP14 are limited by cellular NAD and can be enhanced by pharmacological activation of NAD synthesis. We further demonstrate that infection with MHV induces a severe attack on host cell NAD+ and NADP+. Finally, we show that NAMPT activation, NAM, and NR dramatically decrease the replication of an MHV that is sensitive to PARP activity. These data suggest that the antiviral activities of noncanonical PARP isozyme activities are limited by the availability of NAD and that nutritional and pharmacological interventions to enhance NAD levels may boost innate immunity to coronaviruses.
Distributions associated with simultaneous multiple hypothesis testing

We develop the distribution for the number of hypotheses found to be statistically significant using the rule from Simes (Biometrika 73: 751–754, 1986) for controlling the family-wise error rate (FWER). We find the distribution of the number of statistically significant p-values under the null hypothesis and show this follows a normal distribution under the alternative. We propose a parametric distribution ΨI(·) to model the marginal distribution of p-values sampled from a mixture of null uniform and non-uniform distributions under different alternative hypotheses. The ΨI distribution is useful when there are many different alternative hypotheses and these are not individually well understood. We fit ΨI to data from three cancer studies and use it to illustrate the distribution of the number of notable hypotheses observed in these examples. We model dependence in sampled p-values using a latent variable. These methods can be combined to illustrate a power analysis in planning a larger study on the basis of a smaller pilot experiment.
A Frobenius group analog for Camina triples

Abstract Frobenius groups are an object of fundamental importance in finite group theory. As such, several generalizations of these groups have been considered. Some examples include: A Frobenius–Wielandt group is a triple ( G , H , L ) where H / L is almost a Frobenius complement for G; A Camina pair is a pair ( G , N ) where N is almost a Frobenius kernel for G; A Camina triple is a triple ( G , N , M ) where ( G , N ) and ( G , M ) are almost Camina pairs. In this paper we study triples ( G , N , M ) where ( G , N ) and ( G , M ) are almost Frobenius groups.
Minimal Surfaces in Hyperbolic 3‐Manifolds

In this paper, we show the existence of smoothly embedded closed minimal surfaces in infinite volume hyperbolic $3$-manifolds except some special cases.
Divergent Strategies for Learning in Males and Females

A frequent assumption in value-based decision-making tasks is that agents make decisions based on the feature dimension that reward probabilities vary on. However, in complex, multidimensional environments, stimuli can vary on multiple dimensions at once, meaning that the feature deserving the most credit for outcomes is not always obvious. As a result, individuals may vary in the strategies used to sample stimuli across dimensions, and these strategies may have an unrecognized influence on decision-making. Sex is a proxy for multiple genetic and endocrine influences on behavior, including how environments are sampled. In this study, we examined the strategies adopted by female and male mice as they learned the value of stimuli that varied in both image and location in a visually cued two-armed bandit, allowing two possible dimensions to learn about. Female mice acquired the correct image-value associations more quickly than male mice, preferring a fundamentally different strategy. Female mice were more likely to constrain their decision-space early in learning by preferentially sampling one location over which images varied. Conversely, male mice were more likely to be inconsistent, changing their choice frequently and responding to the immediate experience of stochastic rewards. Individual strategies were related to sex-biased changes in neuronal activation in early learning. Together, we find that in mice, sex is associated with divergent strategies for sampling and learning about the world, revealing substantial unrecognized variability in the approaches implemented during value-based decision making.
Probing the Rosette Nebula Stellar Bubble with Faraday Rotation

We report the results of Faraday rotation measurements of 23 background radio sources whose lines of sight pass through or close to the Rosette Nebula. We made linear polarization measurements with the Karl G. Jansky Very Large Array (VLA) at frequencies of 4.4 GHz, 4.9 GHz, and 7.6 GHz. We find the background Galactic contribution to the rotation measure in this part of the sky to be +147 rad m{sup -2}. Sources whose lines of sight pass through the nebula have an excess rotation measure of 50-750 rad m{sup -2}, which we attribute to the plasma shell of the Rosette Nebula. We consider two simple plasma shell models and how they reproduce the magnitude and sign of the rotation measure, and its dependence on distance from the center of the nebula. These two models represent different modes of interaction of the Rosette Nebula star cluster with the surrounding interstellar medium. Both can reproduce the magnitude and spatial extent of the rotation measure enhancement, given plausible free parameters. We contend that the model based on a stellar bubble more closely reproduces the observed dependence of rotation measure on distance from the center of the nebula.
Connecting Giant Planet Atmosphere and Interior Modeling: Constraints on Atmospheric Metal Enrichment

Atmospheric characterization through spectroscopic analysis, an essential tool of modern exoplanet science, can benefit significantly from the context provided by interior structure models. In particular, the planet's bulk metallicity $Z_p$ places an upper limit on potential atmospheric metallicity. Here we construct interior structure models to derive $Z_p$ and atmospheric metallicity upper limits for 403 known transiting giant exoplanets. These limits are low enough that they can usefully inform atmosphere models. Additionally, we argue that comparing $Z_p$ to the observed atmospheric metallicity gives a useful measure of how well-mixed metals are within the planet. This represents a new avenue for learning about planetary interiors. To aid in the future characterization of new planet discoveries we derive analytic prior predictions of atmosphere metallicity as a function of planet mass, and evaluate the effectiveness of our approach on Jupiter and Saturn. We we include log-linear fits for approximating the metallicities of planets not in our catalog.
Helicity at small x: oscillations generated by bringing back the quarks

We construct a numerical solution of the recently-derived large-Nc&Nf small-x helicity evolution equations [1] with the aim to establish the small-x asymptotics of the quark helicity distribution beyond the large-Nc limit explored previously in the same framework. (Here Nc and Nf are the numbers of quark colors and flavors.) While the large-Nc helicity evolution involves gluons only, the large-Nc&Nf evolution includes contributions from quarks as well. We find that adding quarks to the evolution makes quark helicity distribution oscillate as a function of x. Our numerical results in the large-Nc&Nf limit lead to the x-dependence of the flavor-singlet quark helicity distribution which is well-approximated by 1 $$ {\left.\Delta \Sigma \left(x,{Q}^2\right)\right|}_{\mathrm{large}\hbox{-} {N}_c\&{N}_f}\sim {\left(\frac{1}{x}\right)}^{\alpha_h^q}\cos \left[{\omega}_q\ln \left(\frac{1}{x}\right)+{\varphi}_q\right]. $$ The power $$ {\alpha}_h^q $$ exhibits a weak Nf-dependence, and, for all Nf values considered, remains very close to $$ {\alpha}_h^q\left({N}_f=0\right)=\left(4/\sqrt{3}\right)\sqrt{\alpha_s{N}_c/\left(2\pi \right)} $$ obtained earlier in the large-Nc limit [2, 3]. The novel oscillation frequency ωq and phase shift φq depend more strongly on the number of flavors Nf (with ωq = 0 in the pure-glue large-Nc limit). The typical period of oscillations for ∆Σ is rather long, spanning many units of rapidity. We speculate whether the oscillations we find are related to the sign variation with x seen in the strange quark helicity distribution extracted from the data [4–7].
Gyrokinetic continuum simulations of plasma turbulence in the Texas Helimak

The first gyrokinetic simulations of plasma turbulence in the Texas Helimak device, a simple magnetized torus, are presented. The device has features similar to the scrape-off layer region of tokamaks, such as bad-curvature-driven instabilities and sheath boundary conditions on the end plates, which are included in these simulations. Comparisons between simulations and measurements from the experiment show not only similarities, including equilibrium profiles and fluctuation amplitudes that approach experimental values, but also some important quantitative differences. Both experimental and simulation results exhibit turbulence statistics that are characteristic of blob transport.The first gyrokinetic simulations of plasma turbulence in the Texas Helimak device, a simple magnetized torus, are presented. The device has features similar to the scrape-off layer region of tokamaks, such as bad-curvature-driven instabilities and sheath boundary conditions on the end plates, which are included in these simulations. Comparisons between simulations and measurements from the experiment show not only similarities, including equilibrium profiles and fluctuation amplitudes that approach experimental values, but also some important quantitative differences. Both experimental and simulation results exhibit turbulence statistics that are characteristic of blob transport.
Punishment in public goods games leads to meta-stable phase transitions and hysteresis

The evolution of cooperation has been a perennial problem in evolutionary biology because cooperation can be undermined by selfish cheaters who gain an advantage in the short run, while compromising the long-term viability of the population. Evolutionary game theory has shown that under certain conditions, cooperation nonetheless evolves stably, for example if players have the opportunity to punish cheaters that benefit from a public good yet refuse to pay into the common pool. However, punishment has remained enigmatic because it is costly and difficult to maintain. On the other hand, cooperation emerges naturally in the public goods game if the synergy of the public good (the factor multiplying the public good investment) is sufficiently high. In terms of this synergy parameter, the transition from defection to cooperation can be viewed as a phase transition with the synergy as the critical parameter. We show here that punishment reduces the critical value at which cooperation occurs, but also creates the possibility of meta-stable phase transitions, where populations can 'tunnel' into the cooperating phase below the critical value. At the same time, cooperating populations are unstable even above the critical value, because a group of defectors that are large enough can 'nucleate' such a transition. We study the mean-field theoretical predictions via agent-based simulations of finite populations using an evolutionary approach where the decisions to cooperate or to punish are encoded genetically in terms of evolvable probabilities. We recover the theoretical predictions and demonstrate that the population shows hysteresis, as expected in systems that exhibit super-heating and super-cooling. We conclude that punishment can stabilize populations of cooperators below the critical point, but it is a two-edged sword: it can also stabilize defectors above the critical point.
Harnessing Avidity: Quantifying Entropic and Energetic Effects of Linker Length and Rigidity Required for Multivalent Binding of Antibodies to HIV-1 Spikes

Abstract Due to the low density of envelope (Env) spikes on the surface of HIV-1, neutralizing IgG antibodies rarely bind bivalently using both antigen-binding arms (Fabs) to crosslink between spikes (inter-spike crosslinking), instead resorting to weaker monovalent binding that is more sensitive to Env mutations. Synthetic antibodies designed to bivalently bind a single Env trimer (intra-spike crosslinking) were previously shown to exhibit increased neutralization potencies. In initial work, diFabs joined by varying lengths of rigid double-stranded DNA (dsDNA) were considered. Anticipating future experiments to improve synthetic antibodies, we investigate whether linkers with different rigidities could enhance diFab potency by modeling DNA-Fabs containing different combinations of rigid dsDNA and flexible single-stranded DNA (ssDNA) and characterizing their neutralization potential. Model predictions suggest that while a long flexible polymer may be capable of bivalent binding, it exhibits weak neutralization due to the large loss in entropic degrees of freedom when both Fabs are bound. In contrast, the strongest neutralization potencies are predicted to require a rigid linker that optimally spans the distance between two Fab binding sites on an Env trimer, and avidity can be further boosted by incorporating more Fabs into these constructs. These results inform the design of multivalent anti-HIV-1 therapeutics that utilize avidity effects to remain potent against HIV-1 in the face of the rapid mutation of Env spikes. Significance IgG antibodies utilize avidity to increase their apparent affinities through simultaneous binding of two antigen-binding Fabs – if one Fab dissociates from an antigen, the other Fab can remain attached, allowing rebinding. HIV-1 foils this strategy by having few, and highly-separated, Envelope spike targets for antibodies, forcing most IgGs to bind monovalently. Here we develop a statistical mechanics model of synthetic diFabs joined by DNA linkers of different lengths and flexibilities. This framework enables us to translate the energetic and entropic effects of the linker into the neutralization potency of a diFab. We demonstrate that the avidity of multivalent binding is enhanced by using rigid linkers or including additional Fabs capable of simultaneous binding, providing the means to quantitatively predict the potencies of other antibody designs.
On Legendrian graphs

We investigate Legendrian graphs in .R 3 ; std/. We extend the Thurston‐Bennequin number and the rotation number to Legendrian graphs. We prove that a graph can be Legendrian realized with all its cycles Legendrian unknots with tbD 1 and rotD 0 if and only if it does not contain K4 as a minor. We show that the pair .tb; rot/ does not characterize a Legendrian graph up to Legendrian isotopy if the graph contains a cut edge or a cut vertex. When we restrict to planar spatial graphs, a pair .tb; rot/ determines two Legendrian isotopy classes of the lollipop graph and a pair .tb; rot/ determines four Legendrian isotopy classes of the handcuff graph. 57M25, 57M50; 05C10
Teaching pediatric otoscopy skills to the medical student in the clinical setting: preceptor perspectives and practice.

Acute otitis media (AOM) is the most frequent indication for antibiotic treatment of children in the United States. Its diagnosis relies on visualization of the tympanic membrane, a clinical skill acquired through a deliberate approach. Instruction in pediatric otoscopy begins in medical school. Medical students receive their primary experience with pediatric otoscopy during the required pediatric clerkship, traditionally relying on an immersion, apprentice-type learning model. A better understanding of their preceptors’ clinical and teaching practices could lead to improved skill acquisition. This study investigates how pediatric preceptors (PP) and members of the Council on Medical Student Education in Pediatrics (COMSEP) perceive teaching otoscopy. A 30-item online survey was administered to a purposeful sample of PP at six institutions in 2017. A comparable 23-item survey was administered to members through the 2018 COMSEP Annual Survey. Only COMSEP members who identified themselves as teaching otoscopy to medical students were asked to complete the otoscopy-related questions on the survey. Survey respondents included 58% of PP (180/310) and 44% (152/348) of COMSEP members. Forty-one percent (62/152) of COMSEP member respondents identified themselves as teaching otoscopy and completed the otoscopy-related questions. The majority agreed that standardized curricula are needed (PP 78%, COMSEP members 97%) and that all graduating medical students should be able to perform pediatric otoscopy (PP 95%, COMSEP members 79%). Most respondents reported usefulness of the American Academy of Pediatrics (AAP) AOM guidelines (PP 95%, COMSEP members 100%). More COMSEP members than PP adhered to the AAP’s diagnostic criteria (pediatric preceptors 42%, COMSEP members 93%). The most common barriers to teaching otoscopy were a lack of assistive technology (PP 77%, COMSEP members 56%), presence of cerumen (PP 58%, COMSEP members 60%), time to teach in direct patient care (PP 46%, COMSEP members 48%), and parent anxiety (PP 62%, COMSEP members 54%). Our study identified systemic and individual practice patterns and barriers to teaching pediatric otoscopy. These results can inform education leaders in supporting and enabling preceptors in their clinical teaching. This approach can be adapted to ensure graduating medical students obtain intended core clinical skills.
All-atomic generation and noise-quadrature filtering of squeezed vacuum in hot Rb vapor

With our all-atomic squeezing and filtering setup, we demonstrate control over the noise amplitudes and manipulation of the frequency-dependent squeezing angle of a squeezed vacuum quantum state by passing it through an atomic medium with electromagnetically induced transparency (EIT). We generate low sideband frequency squeezed vacuum using the polarization self-rotation effect in a hot Rb vapor cell, and direct it through a second atomic vapor subject to EIT conditions. We use the frequency-dependent absorption of the EIT window to demonstrate an example of squeeze amplitude attenuation and squeeze angle rotation of the quantum noise quadratures of the squeezed probe. These studies have implications for quantum memory and storage as well as gravitational wave interferometric detectors.
Efficient two-electron ansatz for benchmarking quantum chemistry on a quantum computer

This paper introduces an algorithm for computing atoms and molecules with a pair of electrons for quantum computers. The authors apply the benchmark to 5- and 15-qubit IBM quantum computers, predicting the dissociation of hydrogen gas H${}_{2}$ and interstellar H${}_{3}^{+}$.
The Asymptotics of Quantum Max-Flow Min-Cut

The quantum max-flow min-cut conjecture relates the rank of a tensor network to the minimum cut in the case that all tensors in the network are identical in Calegari et al. (J Am Math Soc 23(1):107–188, 2010). This conjecture was shown to be false in Cui et al. (J Math Phys 57:062206, 2016) by an explicit counter-example. Here, we show that the conjecture is almost true, in that the ratio of the quantum max-flow to the quantum min-cut converges to 1 as the dimension N of the degrees of freedom on the edges of the network tends to infinity. The proof is based on estimating moments of the singular values of the network. We introduce a generalization of “rainbow diagrams” to tensor networks to estimate the dominant diagrams. A direct comparison of second and fourth moments lower bounds the ratio of the quantum max-flow to the quantum min-cut by a constant. To show the tighter bound that the ratio tends to 1, we consider higher moments. In addition, we show that the limiting moments as N → ∞ agree with that in a different ensemble where tensors in the network are chosen independently; this is used to show that the distributions of singular values in the two different ensembles weakly converge to the same limiting distribution. We present also a numerical study of one particular tensor network, which shows a surprising dependence of the rank deficit on N mod 4 and suggests further conjecture on the limiting behavior of the rank.
Processing of X-ray Microcalorimeter Data with Pulse Shape Variation using Principal Component Analysis

We present a method using principal component analysis (PCA) to process x-ray pulses with severe shape variation where traditional optimal filter methods fail. We demonstrate that PCA is able to noise-filter and extract energy information from x-ray pulses despite their different shapes. We apply this method to a dataset from an x-ray thermal kinetic inductance detector which has severe pulse shape variation arising from position-dependent absorption.
Energy transport in trapped ion chains

We experimentally study energy transport in chains of trapped ions. We use a pulsed excitation scheme to rapidly add energy to the local motional mode of one of the ions in the chain. Subsequent energy readout allows us to determine how the excitation has propagated throughout the chain. We observe energy revivals that persist for many cycles. We study the behavior with an increasing number of ions of up to 37 in the chain, including a zig-zag configuration. The experimental results agree with the theory of normal mode evolution. The described system provides an experimental toolbox for the study of thermodynamics of closed systems and energy transport in both classical and quantum regimes.
Photo-acoustic tomography in a rotating measurement setting

Photo-acoustic tomography (PAT) aims to leverage the photo-acoustic coupling between optical absorption of light sources and ultrasound (US) emission to obtain high contrast reconstructions of optical parameters with the high resolution of sonic waves. Quantitative PAT often involves a two-step procedure: first the map of sonic emission is reconstructed from US boundary measurements; and second optical properties of biological tissues are evaluated. We consider here a practical measurement setting in which such a separation does not apply. We assume that the optical source and an array of ultrasonic transducers are mounted on a rotating frame (in two or three dimensions) so that the light source rotates at the same time as the US measurements are acquired. As a consequence, we no longer have the option to reconstruct a map of sonic emission corresponding to a given optical illumination. We propose here a framework where the two steps are combined into one and an absorption map is directly reconstructed from the available US measurements.
On pairs of $p$-adic $L$-functions for weight-two modular forms

The point of this paper is to give an explicit p-adic analytic construction of two Iwasawa functions, Lp♯(f,T) and Lp♭(f,T), for a weight-two modular form ∑ anqn and a good prime p. This generalizes work of Pollack who worked in the supersingular case and also assumed ap = 0. These Iwasawa functions work in tandem to shed some light on the Birch and Swinnerton-Dyer conjectures in the cyclotomic direction: we bound the rank and estimate the growth of the Safarevic–Tate group in the cyclotomic direction analytically, encountering a new phenomenon for small slopes.
A Module System for Domain-Specific Languages

Domain-specific languages (DSLs) are routinely created to simplify difficult or specialized programming tasks. They expose useful abstractions and design patterns in the form of language constructs, provide static semantics to eagerly detect misuse of these constructs, and dynamic semantics to completely define how language constructs interact. However, implementing and composing DSLs is a non-trivial task, and there is a lack of tools and techniques. We address this problem by presenting a complete module system over LP for DSL construction, reuse, and composition. LP is already useful for DSL design, because it supports executable language specifications using notations familiar to language designers. We extend LP with a module system that is simple (with a few concepts), succinct (for key DSL specification scenarios), and composable (on the level of languages, compilers, and programs). These design choices reflect our use of LP for industrial DSL design. Our module system has been implemented in the formula language, and was used to build key Windows 8 device drivers via DSLs. Though we present our module system as it actually appears in our formula language, our emphasis is on concepts adaptable to other LP languages.