cssi/SciSciGPT-SciSciNet huggingface dataset:
Extensive memory testing improves prediction of progression to MCI in late middle age.

Introduction Predicting risk for Alzheimer's disease when most people are likely still biomarker negative would aid earlier identification. We hypothesized that combining multiple memory tests and scores in middle-aged adults would provide useful, and non-invasive, prediction of 6-year progression to MCI. Methods We examined 849 men who were cognitively normal at baseline (mean age ± SD = 55.69 ± 2.45). Results California Verbal Learning Test learning trials was the best individual predictor of amnestic MCI (OR = 4.75). A latent factor incorporating seven measures across three memory tests provided much stronger prediction (OR = 9.88). This compared favorably with biomarker-based prediction in a study of much older adults. Discussion Neuropsychological tests are sensitive and early indicators of MCI risk at an age when few individuals are likely to have yet become biomarker positive. The single best measures may appear time- and cost-effective, but 30 additional minutes of testing and use of multiple scores within tests provide substantially improved prediction.
The Learning Challenge in the 21st Century

Truth matters, and the norms associated with a democratic society, such as the common good, responsibility, ethics, and civic engagement, are under attack with the emergence of the post-truth society. There are concerns worldwide that public education is failing us on pushing back on disinformation. And, in most countries, education systems are not providing workers with the skills necessary to compete in today's job markets. The growing mismatch between demand and supply of skills holds back economic growth and undermines opportunity. At same time, the financial returns to schooling are high in most countries. Schooling remains a good economic and social investment, and there are record numbers of children in school today. The skills that matter in the coming technological revolution are likely the same as what is needed in a media environment of disinformation. More and better education and noncognitive skills will not only prepare students for the future world of work, they will also prepare them to navigate the increasingly complex post-truth society. They will also allow young people to gain trust. In other words, better education is democratizing, to the extent that it promotes truth, values, and civic engagement.
Small Alphaherpesvirus Latency-Associated Promoters Drive Efficient and Long-Term Transgene Expression in the CNS.

Recombinant adeno-associated viruses (rAAVs) are used as gene therapy vectors to treat central nervous system (CNS) diseases. Despite their safety and broad tropism, important issues need to be corrected such as the limited payload capacity and the lack of small gene promoters providing long-term, pan-neuronal transgene expression in the CNS. Commonly used gene promoters are relatively large and can be repressed a few months after CNS transduction, risking the long-term performance of single-dose gene therapy applications. We used a whole-CNS screening approach based on systemic delivery of AAV-PHP.eB, iDisco+ tissue-clearing and light-sheet microscopy to identify three small latency-associated promoters (LAPs) from the herpesvirus pseudorabies virus (PRV). These promoters are LAP1 (404 bp), LAP2 (498 bp), and LAP1_2 (880 bp). They drive chronic transcription of the virus-encoded latency-associated transcript (LAT) during productive and latent phases of PRV infection. We observed stable, pan-neuronal transgene transcription and translation from AAV-LAPs in the CNS for 6 months post AAV transduction. In several CNS areas, the number of cells expressing the transgene was higher for LAP2 than the large conventional EF1α promoter (1,264 bp). Our data suggest that the LAPs are suitable candidates for viral vector-based CNS gene therapies requiring chronic transgene expression after one-time viral-vector administration.
Stress Drop Variation of Deep-Focus Earthquakes Based on Empirical Green's Functions

We analyze source characteristics of global, deep-focus (> 350 km) earthquakes with moment magnitudes (Mw) larger than 6.0-8.2 using teleseismic P-wave and S-wave spectra and an empirical Greens functions approach. We estimate the corner frequency assuming Brunes source model and calculate stress drops assuming a circular crack model. Based on P-wave and S-wave spectra, the one-standard deviation ranges are 3.5-369.8 MPa and 8.2-328.9 MPa, respectively. Based on the P-wave analysis, the median of our stress-drop estimates is about a factor of 10 higher than the median stress drop of shallow earthquakes with the same magnitude estimated by Allmann and Shearer (2009). This suggests that, on average, the shear stress of deep faults in the mantle transition zone is an order of magnitude higher than the shear stress of faults in the crust. The wide range of stress drops implies coexistence of multiple physical mechanisms.
Least squares auto-tuning

Least squares auto-tuning automatically finds hyper-parameters in least squares problems that minimize another (true) objective. The least squares tuning optimization problem is non-convex, so it c...
Relaxing household liquidity constraints through social security

More than a quarter of working-age households in the United States do not have sufficient savings to cover their expenditures after a month of unemployment. Recent proposals suggest giving workers early access to a small portion of their future Social Security benefits to finance their consumption during the COVID-19 pandemic. We empirically analyze their impact. Relying on data from the Survey of Consumer Finances, we build a measure of households' expected time to cash shortfall based on the incidence of COVID-induced unemployment. We show that access to 1% of future benefits allows 75% of households to maintain their current consumption for three months in case of unemployment. We then compare the efficacy of access to Social Security benefits to already legislated approaches, including early access to retirement accounts, stimulus relief checks, and expanded unemployment insurance.
FINAL MOMENTS: CONTEXTUALIZING ON-FLOOR ARCHAEOLOGICAL MATERIALS FROM CARACOL, BELIZE

The description and analysis of materials from on-floor deposits that reflect the final activity before site abandonment are key to making a determination as to what happened during the Maya collapse around a.d. 900. On-floor deposits recovered at Caracol, Belize indicate that factors like warfare, the breakdown of the site's market system, and heightened social tensions were in play prior to the abandonment of the site. In an attempt to understand the meaning of these deposits, we first examine why on-floor remains constitute an important data class for archaeology. We next look at the kinds of artifactual materials that are recovered in these deposits and then at the locations and nature of on-floor deposits at Caracol. Finally, we offer our thoughts on what they represent in the broader Maya context.
Log Diameter Rounds Algorithms for 2-Vertex and 2-Edge Connectivity.

Many modern parallel systems, such as MapReduce, Hadoop and Spark, can be modeled well by the MPC model. The MPC model captures well coarse-grained computation on large data --- data is distributed to processors, each of which has a sublinear (in the input data) amount of memory and we alternate between rounds of computation and rounds of communication, where each machine can communicate an amount of data as large as the size of its memory. This model is stronger than the classical PRAM model, and it is an intriguing question to design algorithms whose running time is smaller than in the PRAM model. In this paper, we study two fundamental problems, $2$-edge connectivity and $2$-vertex connectivity (biconnectivity). PRAM algorithms which run in $O(\log n)$ time have been known for many years. We give algorithms using roughly log diameter rounds in the MPC model. Our main results are, for an $n$-vertex, $m$-edge graph of diameter $D$ and bi-diameter $D'$, 1) a $O(\log D\log\log_{m/n} n)$ parallel time $2$-edge connectivity algorithm, 2) a $O(\log D\log^2\log_{m/n}n+\log D'\log\log_{m/n}n)$ parallel time biconnectivity algorithm, where the bi-diameter $D'$ is the largest cycle length over all the vertex pairs in the same biconnected component. Our results are fully scalable, meaning that the memory per processor can be $O(n^{\delta})$ for arbitrary constant $\delta>0$, and the total memory used is linear in the problem size. Our $2$-edge connectivity algorithm achieves the same parallel time as the connectivity algorithm of Andoni et al. (FOCS 2018). We also show an $\Omega(\log D')$ conditional lower bound for the biconnectivity problem.
Trepanation and the “Catlin Mark”

THIS PAPER deals with the confusion of a certain anomalous condition of the human skull with one type of trepanation. Evidence is presented to show that many specimens exhibited as examples of a certain type of trepanning are clear-cut cases of this congenital bilateral fenestra in the parietal bones. As is generally known, trephining was performed by ancient man' to relieve certain maladies such as headaches caused by "demons kicking up a fuss" inside the skull. The excruciatingly painful operation was performed with a crude knife, piece of glass, or sharp-edged stone. Trephining probably flourished in Neolithic times, especially in Bohemia and western Europe. Trephined skulls have been reported from Bolivia, Central America, Mexico, Peru, and various other localities. Since th-e knowledge of trephining has become common and the finding and reporting of trephined skulls is very popular, the tendency is to label nearly all skulls that appear old and which have holes of almost any sort as cases of trephining. Anomalous skulls may be seen in some of our greatest museums (P1. XXVII, a), as well as in private and small college exhibits. In the legend accompanying the "trephined" skulls in one museum, we read, "The trephine hole is usually located on the upper and posterior part of the parietal bone." Of the fourteen so-called "trephined" skulls in another museum, only four showed the holes in the parietals, while eight were clearly "trephined" in the frontals. The other two skulls were so irregularly marked that they could not be classified on this basis. Though the number is too small to warrant broad generalization, it is obvious that the trephine hole is not "usually" in the parietals. While reviewing many so-called "trephined" skulls, as well as records in the literature, I became aware that in a considerable number of those having bilaterally "trephined" parietals the fenestrae were round to oval, in about the same position, and bore a remarkable similarity in different skulls, though their proveniences might be widely separated parts of the globe. Since these aborigines of thousands of years ago certainly were not in direct communication with each other, it seems improbable that their primitive surgery would follow so constant a plan. On the other hand, if these quite uniformly paired parietal fenestrae were produced by nature, we would be no more surprised at their similarity than we are at the similarity in cases of syndactylism, brachy-
Apply Yourself: Racial and Ethnic Differences in College Application

Access to higher education begins with a student's decision whether and where to apply to college. This paper examines racial and ethnic differences in college application behavior of high school g...
Chapter 2 – Convention Confusions

Publisher Summary This chapter discusses the plane-wave solutions to the electromagnetic wave equation and reviews the wave equations for the electric and magnetic fields. In addition to the amplitude, frequency, and direction of propagation, an electromagnetic wave is characterized by the orientation of its field vectors. As an electromagnetic wave in an isotropic medium is transverse rather than longitudinal, its field vectors are normal to its wave vector. The temporal behavior of the orientation of the electric field, as observed at a fixed location along the propagation direction, determines the polarization state of the wave. The polarization state is represented by the curve traced out by the tip of the instantaneous vector. The electric field is chosen as the descriptor of the polarization state, because it exerts a much stronger force on electrons than the magnetic field. Even though polarization is referenced to the temporal variation of the orientation of the field vector, a spatial visualization of the component and resultant waves at an instant of time can be provided. Sometimes a linearly polarized wave is referred to as being plane polarized, because the wave lies in a plane. The chapter further focuses on circular polarization and Fresnel's amplitude reflection coefficients and discusses the physical significance of phase change of an electromagnetic wave.
Interaction of a Finite-span Synthetic-jet and Cross-flow over a Swept Wing

An experimental investigation was performed to study the three-dimensional flow structures and interactions of a finite-span synthetic jet with the flow over a finite and swept back wing (cross-sectional profile of the NACA 4421, AR=4, sweep angle of 30 deg), at a Reynolds number of 10 5 and zero angle of attack. Two momentum coefficients were considered, corresponding to two blowing ratios of 0.8 and 1.2. Stereoscopic PIV data was collected around the center jet in the mid-span section. The effect of the momentum coefficient (or blowing ratio) was analyzed based on the three-dimensional flow field using time-averaged and phase-averaged statistics. The study showed that, similar to the interaction of a synthetic jet with the flow over an unswept wing, the flow field in the vicinity of the synthetic-jet orifice becomes highly three-dimensional and is governed by the superposition of two kinds of flow structures: (1) streamwise structures that are associated with the finite span of the jet (edge vortices), and (2) spanwise flow structures that are generated along the orifice due to the vortex pairs that are formed by the synthetic jet. Nevertheless, over a swept wing these three-dimensional flow structures evolve almost immediately downstream to the synthetic-jet orifice and evolve into a very complex 3-D flow field.
Relocation of Collapsed Forks to the Nuclear Pore Complex Depends on Sumoylation of DNA Repair Proteins and Permits Rad51 Association

Expanded CAG repeats form stem-loop secondary structures that lead to fork stalling and collapse. Previous work has shown that these collapsed forks relocalize to nuclear pore complexes (NPCs) in late S phase in a manner dependent on replication, the nucleoporin Nup84, and the Slx5 protein, which prevents repeat fragility and instability. Here, we show that binding of the Smc5/6 complex to the collapsed fork triggers Mms21-dependent sumoylation of fork-associated DNA repair proteins, and that RPA, Rad52, and Rad59 are the key sumoylation targets that mediate relocation. The SUMO interacting motifs of Slx5 target collapsed forks to the NPC. Notably, Rad51 foci only co-localize with the repeat after it is anchored to the nuclear periphery and Rad51 exclusion from the early collapsed fork is dependent on RPA sumoylation. This pathway may provide a mechanism to constrain recombination at stalled or collapsed forks until it is required for fork restart.
Moment bounds of a class of stochastic heat equations driven by space–time colored noise in bounded domains

Abstract We consider the fractional stochastic heat type equation ∂ ∂ t u t ( x ) = − ( − Δ ) α ∕ 2 u t ( x ) + ξ σ ( u t ( x ) ) F ( t , x ) , x ∈ D , t > 0 , with nonnegative bounded initial condition, where α ∈ ( 0 , 2 ] , ξ > 0 is the noise level, σ : R → R is a globally Lipschitz function satisfying some growth conditions and the noise term F behaves in space like the Riez kernel and is possibly correlated in time and D is the unit open ball centered at the origin in R d . When the noise term is not correlated in time, we establish a change in the growth of the solution of these equations depending on the noise level ξ . On the other hand when the noise term behaves in time like the fractional Brownian motion with index H ∈ ( 1 ∕ 2 , 1 ) , We also derive explicit bounds leading to a well-known intermittency property.
SCOPE: A Normalization and Copy-Number Estimation Method for Single-Cell DNA Sequencing

Whole-genome single-cell DNA sequencing (scDNA-seq) enables characterization of copy-number profiles at the cellular level. We propose SCOPE, a normalization and copy-number estimation method for the noisy scDNA-seq data. SCOPE's main features include the following: (1) a Poisson latent factor model for normalization, which borrows information across cells and regions to estimate bias, using in silico identified negative control cells; (2) an expectation-maximization algorithm embedded in the normalization step, which accounts for the aberrant copy-number changes and allows direct ploidy estimation without the need for post hoc adjustment; and (3) a cross-sample segmentation procedure to identify breakpoints that are shared across cells with the same genetic background. We evaluate SCOPE on a diverse set of scDNA-seq data in cancer genomics and show that SCOPE offers accurate copy-number estimates and successfully reconstructs subclonal structure. A record of this paper's transparent peer review process is included in the Supplemental Information.
Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model

Recently, generating adversarial examples has become an important means of measuring robustness of a deep learning model. Adversarial examples help us identify the susceptibilities of the model and further counter those vulnerabilities by applying adversarial training techniques. In natural language domain, small perturbations in the form of misspellings or paraphrases can drastically change the semantics of the text. We propose a reinforcement learning based approach towards generating adversarial examples in black-box settings. We demonstrate that our method is able to fool well-trained models for (a) IMDB sentiment classification task and (b) AG’s news corpus news categorization task with significantly high success rates. We find that the adversarial examples generated are semantics-preserving perturbations to the original text.
Using classification methods to label tasks in process mining

We investigate a method designed to improve the accuracy of process mining in scenarios where the identification of task labels for log events is uncertain. Such situations are prevalent in business processes where events consist of communications between people, such as email messages. We examine how the accuracy of an independent task identifier, such as a classification or clustering engine, can be improved by examining the currently mined process model. First, a classification scheme based on identifying the keywords in each message is presented to provide an initial labeling. We then demonstrate how these labels can be refined by considering the likelihood that the event represents a particular task as obtained via an analysis of the current representation of the process model. This process is then repeated a number of times until the model is sufficiently refined. Results show that both keyword classification and the current process model analysis can be significantly effective on their own, and when combined have the potential to correct virtually all errors when noise is low (less than 20%), and can reduce the error rate by about 85% when noise is in the 30–40% range. Copyright © 2010 Crown in the right of Canada.
Learning-Assisted Secure End-to-End Network Slicing for Cyber-Physical Systems

There is a pressing need to interconnect physical systems such as power grid and vehicles for efficient management and safe operations. Due to the diverse features of physical systems, there is hardly a one-size-fits-all networking solution for developing cyber-physical systems. Network slicing is a promising technology that allows network operators to create multiple virtual networks on top of a shared network infrastructure. These virtual networks can be tailored to meet the requirements of different cyber-physical systems. However, it is challenging to design secure network slicing solutions that can efficiently create end-to-end network slices for diverse cyber-physical systems. In this article, we discuss the challenges and security issues of network slicing, study learning-assisted network slicing solutions, and analyze their performance under the denial-of-service attack. We also present a design and implementation of a small-scale testbed for evaluating the network slicing solutions.
My brand identity lies in the brand name: personified suggestive brand names

This research introduces personified suggestive brand names, the degree to which a brand name (1) defines a potential user of the brand or (2) portrays personal characteristics that are used by the consumer to anthropomorphize the brand. Results of four experiments show that consumers are more likely to form brand relationships and more favorable brand evaluations toward more (e.g., Smart), compared to less (e.g., Technical), personified suggestive brand names, because (1) they form a self-brand name connection with these brand names to present themselves to others and (2) they humanize the brand via these brand names. Additionally, personified suggestive brand names lead to self-brand name connections that result in brand anthropomorphism, which leads to favorable branding outcomes, particularly among Relational Interdependent Self-construal consumers, who are more likely to incorporate their relationships on their self-definitions.
Keeping Designers in the Loop: Communicating Inherent Algorithmic Trade-offs Across Multiple Objectives

Artificial intelligence algorithms have been used to enhance a wide variety of products and services, including assisting human decision making in high-stake contexts. However, these algorithms are complex and have trade-offs, notably between prediction accuracy and fairness to population subgroups. This makes it hard for designers to understand algorithms and design products or services in a way that respects users' goals, values, and needs. We proposed a method to help designers and users explore algorithms, visualize their trade-offs, and select algorithms with trade-offs consistent with their goals and needs. We evaluated our method on the problem of predicting criminal defendants' likelihood to re-offend through (i) a large-scale Amazon Mechanical Turk experiment, and (ii) in-depth interviews with domain experts. Our evaluations show that our method can help designers and users of these systems better understand and navigate algorithmic trade-offs. This paper contributes a new way of providing designers the ability to understand and control the outcomes of algorithmic systems they are creating.
Attracting random walks

This paper introduces the Attracting Random Walks model, which describes the dynamics of a system of particles on a graph with $n$ vertices. At each step, a single particle moves to an adjacent vertex (or stays at the current one) with probability proportional to the exponent of the number of other particles at a vertex. From an applied standpoint, the model captures the rich get richer phenomenon. We show that the Markov chain exhibits a phase transition in mixing time, as the parameter governing the attraction is varied. Namely, mixing time is $O(n\log n)$ when the temperature is sufficiently high and $\exp (\Omega (n))$ when temperature is sufficiently low. When $\mathcal {G}$ is the complete graph, the model is a projection of the Potts model, whose mixing properties and the critical temperature have been known previously. However, for any other graph our model is non-reversible and does not seem to admit a simple Gibbsian description of a stationary distribution. Notably, we demonstrate existence of the dynamic phase transition without decomposing the stationary distribution into phases.
Co-author Weighting in Bibliometric Methodology and Subfields of a Scientific Discipline

Collaborative work and co-authorship are fundamental to the advancement of modern science. However, it is not clear how collaboration should be measured in achievement-based metrics. Co-author weighted credit introduces distortions into the bibliometric description of a discipline. It puts great weight on collaboration - not based on the results of collaboration - but purely because of the existence of collaborations. In terms of publication and citation impact, it artificially favors some subdisciplines. In order to understand how credit is given in a co-author weighted system (like the NRC's method), we introduced credit spaces. We include a study of the discipline of physics to illustrate the method. Indicators are introduced to measure the proportion of a credit space awarded to a subfield or a set of authors.
Skin effect and winding number in disordered non-Hermitian systems

Unlike their Hermitian counterparts, non-Hermitian (NH) systems may display an exponential sensitivity to boundary conditions and an extensive number of edge-localized states in systems with open boundaries, a phenomena dubbed the ``non-Hermitian skin effect.'' The NH skin effect is one of the primary challenges to defining a topological theory of NH Hamiltonians, as the sensitivity to boundary conditions invalidates the traditional bulk-boundary correspondence. The NH skin effect has recently been connected to the winding number, a topological invariant unique to NH systems. In this paper we extend the definition of the winding number to disordered NH systems by generalizing established results on disordered Hermitian topological insulators. Our real-space winding number is self-averaging, continuous as a function of the parameters in the problem, and remains quantized even in the presence of strong disorder. We verify that our real-space formula still predicts the NH skin effect, allowing for the possibility of predicting and observing the NH skin effect in strongly disordered NH systems. We use our theory to demonstrate the NH Anderson skin effect, in which a skin effect is developed as disorder is added to a clean system, as well as explain recent results in optical funnels.
T. Dauxois’ “Non-Gaussian Distributions Under Scrutiny” Under Scrutiny

A recent paper by T. Dauxois entitled “Non-Gaussian distributions under scrutiny” is submitted to scrutiny. Several comments on its content are made, which constitute, at the same time, a brief state-of-the-art review of nonextensive statistical mechanics, a current generalization of the Boltzmann-Gibbs theory. Some inadvertences and misleading sentences are pointed out as well.
Limits to flow detection in phase contrast MRI.

Abstract Pulsed gradient spin echo (PGSE) complex signal behavior becomes dominated by attenuation rather than oscillation when displacements due to flow are similar or less than diffusive displacements. In this “slow-flow” regime, the optimal displacement encoding parameter q for phase contrast velocimetry depends on the diffusive length scale q s l o w = 1 / l D = 1 / 2 D Δ rather than the velocity encoding parameter v e n c = π / ( q Δ ) . The minimum detectable mean velocity using the difference between the phase at + q s l o w and − q s l o w is 〈 v m i n 〉 = 1 / SNR D / Δ . These theories are then validated and applied to MRI by performing PGSE echo planar imaging experiments on water flowing through a column with a bulk region and a beadpack region at controlled flow rates. Velocities as slow as 6 μm/s are detected with velocimetry. Theories, MRI experimental protocols, and validation on a controlled phantom help to bridge the gap between porous media NMR and pre-clinical phase contrast and diffusion MRI.
Formation of Gas Giant Planets

The observed physical properties and orbits of giant planets, models of their internal structure and observations of protoplanetary disks provide constraints on the formation of gas giant planets. The four largest planets in our Solar System contain considerable quantities of hydrogen and helium; these gasses could not have condensed into solid planetesimals within the protoplanetary disk. Jupiter and Saturn are mostly hydrogen and helium, but have larger percentages of heavier elements than does the Sun. Neptune and Uranus are primarily composed of elements heavier than helium. The transiting extrasolar planet HD 149026 b, which is slightly more massive than is Saturn, appears to have comparable amounts of light gases and heavy elements. The other observed transiting exoplanets are primarily hydrogen and helium, but may contain supersolar abundances of heavy elements. Spacecraft flybys and observations of satellite orbits provide estimates of the gravitational moments of the giant planets in our Solar System, which in turn provide information on the internal distribution of matter within Jupiter, Saturn, Uranus and Neptune. Atmospheric thermal structure and heat flow measurements constrain the interior temperatures of these planets. Extrasolar planets orbiting very close to their stars almost certainly formed at larger distances and migrated inwards as a consequence of gravitational interactions with their protoplanetary disks. The preponderance of evidence supports the core nucleated gas accretion model. According to this model, giant planets begin their growth by the accumulation of small solid bodies, as do terrestrial planets. However, unlike terrestrial planets, the giant planet cores grow massive enough to accumulate substantial amounts of gas before the protoplanetary disk dissipates. The primary question regarding the core nucleated growth model is under what conditions can planets develop cores sufficiently massive to accrete gas envelopes within the lifetimes of typical gaseous protoplanetary disks.
Dimension, comparison, and almost finiteness

We develop a dynamical version of some of the theory surrounding the Toms-Winter conjecture for simple separable nuclear C*-algebras and study its connections to the C*-algebra side via the crossed product. We introduce an analogue of hyperfiniteness for free actions of amenable groups on compact spaces and show that it plays the role of Z-stability in the Toms-Winter conjecture in its relation to dynamical comparison, and also that it implies Z-stability of the crossed product. This property, which we call almost finiteness, generalizes Matui's notion of the same name from the zero-dimensional setting. We also introduce a notion of tower dimension as partial analogue of nuclear dimension and study its relation to dynamical comparison and almost finiteness, as well as to the dynamical asymptotic dimension and amenability dimension of Guentner, Willett, and Yu.
The Use of Integrals in Numerical Integrations of the N -Body Problem

The numerical integration of systems of differential equations that possess integrals is often approached by using the integrals to reduce the number of degrees of freedom or by using the integrals as a partial check on the resulting solution, retaining the original number of degrees of freedom. Another use of the integrals is presented here. If the integrals have not been used to reduce the system, the solution of a numerical integration may be constrained to remain on the integral surfaces by a method that applies corrections to the solution at each integration step. The corrections are determined by using linearized forms of the integrals in a least-squares procedure. The results of an application of the method to numerical integrations of a gravitational system of 25-bodies are given. It is shown that by using the method to satisfy exactly the integrals of energy, angular momentum, and center of mass, a solution is obtained that is more accurate while using less time of calculation than if the integrals are not satisfied exactly. The relative accuracy is ascertained by forward and backward integrations of both the corrected and uncorrected solutions and by comparison with more accurate integrations using reduced step-sizes.
Rapid High-Resolution Visible Light 3D Printing.

Light-driven 3D printing to convert liquid resins into solid objects (i.e., photocuring) has traditionally been dominated by engineering disciplines, yielding the fastest build speeds and highest r...
Exploring the Potential for Collaborative Use of an App-Based Platform for n-of-1 Trials Among Healthcare Professionals That Treat Patients With Insomnia.

Background N-of-1 trials are single patient, multiple crossover, and comparative effectiveness experiments. Despite their rating as "level 1" evidence, they are not routinely used in clinical medicine to evaluate the effectiveness of treatments. Objective We explored the potential for implementing a mobile app-based n-of-1 trial platform for collaborative use by clinicians and patients to support data-driven decisions around the treatment of insomnia. Methods A survey assessing awareness and utilization of n-of-1 trials was administered to healthcare professionals that frequently treat patients with insomnia at the Icahn School of Medicine at Mount Sinai in New York City. Results A total of 45 healthcare professionals completed the survey and were included in the analysis. We found that 64% (29/45) of healthcare professionals surveyed had not heard of n-of-1 trials. After a brief description of these methods, 75% (30/40) of healthcare professionals reported that they are likely or highly likely to use an app-based n-of-1 trial at least once in the next year if the service were free and easy to offer to their patients. Conclusions An app-based n-of-1 trials platform might be a valuable tool for clinicians and patients to identify the best treatments for insomnia. The lack of awareness of n-of-1 trials coupled with receptivity to their use suggests that educational interventions may address a current barrier to wider utilization of n-of-1 trials.
Asymptotic flatness of Morrey extremals

We study the limiting behavior as $$|x|\rightarrow \infty $$ of extremal functions u for Morrey’s inequality on $$\mathbb {R}^n$$ . In particular, we compute the limit of u(x) as $$|x|\rightarrow \infty $$ and show |x||Du(x)| tends to 0. To this end, we exploit the fact that extremals are uniformly bounded and that they each satisfy a PDE of the form $$-\Delta _pu=c(\delta _{x_0}-\delta _{y_0})$$ for some $$c\in \mathbb {R}$$ and distinct $$x_0,y_0\in \mathbb {R}^n$$ . More generally, we explain how to quantitatively deduce the asymptotic flatness of bounded p-harmonic functions on exterior domains of $$\mathbb {R}^n$$ for $$p>n$$ .
Risk assessment of airborne transmission of COVID-19 by asymptomatic individuals under different practical settings

The lack of quantitative risk assessment of airborne transmission of COVID-19 under practical settings leads to large uncertainties and inconsistencies in our preventive measures. Combining in situ measurements and computational fluid dynamics simulations, we quantify the exhaled particles from normal respiratory behaviors and their transport under elevator, small classroom, and supermarket settings to evaluate the risk of inhaling potentially virus-containing particles. Our results show that the design of ventilation is critical for reducing the risk of particle encounters. Inappropriate design can significantly limit the efficiency of particle removal, create local hot spots with orders of magnitude higher risks, and enhance particle deposition causing surface contamination. Additionally, our measurements reveal the presence of a substantial fraction of faceted particles from normal breathing and its strong correlation with breathing depth.
Jet Substructure from Dark Sector Showers

We examine the robustness of collider phenomenology predictions for a dark sector scenario with QCD-like properties. Pair production of dark quarks at the LHC can result in a wide variety of signatures, depending on the details of the new physics model. A particularly challenging signal results when prompt production induces a parton shower that yields a high multiplicity of collimated dark hadrons with subsequent decays to Standard Model hadrons. The final states contain jets whose substructure encodes their non-QCD origin. This is a relatively subtle signature of strongly coupled beyond the Standard Model dynamics, and thus it is crucial that analyses incorporate systematic errors to account for the approximations that are being made when modeling the signal. We estimate theoretical uncertainties for a canonical substructure observable designed to be sensitive to the gauge structure of the underlying object, the two-point energy correlator $$ {e}_2^{\left(\beta \right)} $$ , by computing envelopes between resummed analytic distributions and numerical results from Pythia. We explore the separability against the QCD background as the confinement scale, number of colors, number of flavors, and dark quark masses are varied. Additionally, we investigate the uncertainties inherent to modeling dark sector hadronization. Simple estimates are provided that quantify one’s ability to distinguish these dark sector jets from the overwhelming QCD background. Such a search would benefit from theory advances to improve the predictions, and the increase in statistics using the data to be collected at the high luminosity LHC.
Distributed Optimization, Averaging via ADMM, and Network Topology

There has been an increasing necessity for scalable optimization methods, especially due to the explosion in the size of data sets and model complexity in modern machine learning applications. Scalable solvers often distribute the computation over a network of processing units. For simple algorithms, such as gradient descent, the dependence of the convergence time with the topology of this network is well known. However, for more involved algorithms, such as the alternating direction method of multipliers (ADMM), much less is known. At the heart of many distributed optimization algorithms, there exists a gossip subroutine which averages local information over the network, whose efficiency is crucial for the overall performance of the method. In this article, we review recent research in this area, and with the goal of isolating such a communication exchange behavior, we compare different algorithms when applied to a canonical distributed averaging consensus problem. We also show interesting connections between ADMM and the lifted Markov chains besides providing an explicit characterization of its convergence and optimal parameter tuning in terms of spectral properties of the network. Finally, we empirically study the connection between network topology and convergence rates for different algorithms on a real-world problem of sensor localization.
Exploration of the Neisseria Resistome Reveals Resistance Mechanisms in Commensals That May Be Acquired by N. gonorrhoeae through Horizontal Gene Transfer

Nonpathogenic Neisseria transfer mutations encoding antibiotic resistance to their pathogenic relative Neisseria gonorrhoeae. However, the resistance genotypes and subsequent phenotypes of nonpathogens within the genus have been described infrequently. Here, we characterize the minimum inhibitory concentrations (MICs) of a panel of Neisseria (n = 26)-including several commensal species-to a suite of diverse antibiotics. We furthermore use whole genome sequencing and the Comprehensive Antibiotic Resistance Database Resistance Gene Identifier (RGI) platform to predict putative resistance-encoding mutations. Resistant isolates to all tested antimicrobials including penicillin (n = 5/26), ceftriaxone (n = 2/26), cefixime (n = 3/26), tetracycline (n = 10/26), azithromycin (n = 11/26), and ciprofloxacin (n = 4/26) were found. In total, 63 distinct mutations were predicted by RGI to be involved in resistance. The presence of several mutations had clear associations with increased MIC such as DNA gyrase subunit A (gyrA) (S91F) and ciprofloxacin, tetracycline resistance protein (tetM) and 30S ribosomal protein S10 (rpsJ) (V57M) and tetracycline, and TEM-type β-lactamases and penicillin. However, mutations with strong associations to macrolide and cephalosporin resistance were not conclusive. This work serves as an initial exploration into the resistance-encoding mutations harbored by nonpathogenic Neisseria, which will ultimately aid in prospective surveillance for novel resistance mechanisms that may be rapidly acquired by N. gonorrhoeae.
Modern atrial fibrillation care: Becoming a pro at using PROs

EDITORIAL: Modern Atrial Fibrillation Care: Becoming a Pro at Using PROsSamuel F. Sears, PhD,1,2 Scarlett Anthony, BA,1 & Aditi Naniwadekar, MD21 Department of Psychology, East Carolina University, Greenville, NC2 Department of Cardiovascular Sciences, Brody School of Medicine, East Carolina University, Greenville, NC
Dynamical Ising model of spatially coupled ecological oscillators

Long-range synchrony from short-range interactions is a familiar pattern in biological and physical systems, many of which share a common set of 'universal' properties at the point of synchronization. Common biological systems of coupled oscillators have been shown to be members of the Ising universality class, meaning that the very simple Ising model replicates certain spatial statistics of these systems at stationarity. This observation is useful because it reveals which aspects of spatial pattern arise independently of the details governing local dynamics, resulting in both deeper understanding of and a simpler baseline model for biological synchrony. However, in many situations a system's dynamics are of greater interest than their static spatial properties. Here, we ask whether a dynamical Ising model can replicate universal and non-universal features of ecological systems, using noisy coupled metapopulation models with two-cycle dynamics as a case study. The standard Ising model makes unrealistic dynamical predictions, but the Ising model with memory corrects this by using an additional parameter to reflect the tendency for local dynamics to maintain their phase of oscillation. By fitting the two parameters of the Ising model with memory to simulated ecological dynamics, we assess the correspondence between the Ising and ecological models in several of their features (location of the critical boundary in parameter space between synchronous and asynchronous dynamics, probability of local phase changes and ability to predict future dynamics). We find that the Ising model with memory is reasonably good at representing these properties of ecological metapopulations. The correspondence between these models creates the potential for the simple and well-known Ising class of models to become a valuable tool for understanding complex biological systems.
Gravitationally bound BCS state as dark matter

We explore the possibility that fermionic dark matter undergoes a BCS transition to form a superfluid. This requires an attractive interaction between fermions and we describe a possible source of this interaction induced by torsion. We describe the gravitating fermion system with the Bogoliubov-de Gennes formalism in the local density approximation. We solve the Poisson equation along with the equations for the density and gap energy of the fermions to find a self-gravitating, superfluid solution for dark matter halos. In order to produce halos the size of dwarf galaxies, we require a particle mass of ~ 200 eV. We find a maximum attractive coupling strength before the halo becomes unstable. If dark matter halos do have a superfluid component, this raises the possibility that they contain vortex lines.
Beyond sub-Rayleigh imaging via high order correlation of speckle illumination

Second order intensity correlations of speckle illumination are extensively used in imaging applications that require going beyond the Rayleigh limit. The theoretical analysis shows that significantly improved imaging can be extracted from the study of increasingly higher order intensity cumulants. We provide experimental evidence by demonstrating resolution beyond what is achievable by second order correlations. We present results up to 20th order. We also show an increased visibility of cumulant correlations compared to moment correlations. Our findings clearly suggest the benefits of using higher order intensity cumulants in other disciplines like astronomy and biology.
Reflections on dissipation associated with thermal convection

Buoyancy-driven convection is modelled using the Navier–Stokes and entropy equations. It is first shown that the coefficient of heat capacity at constant pressure, , must in general depend explicitly on pressure (i.e. is not a function of temperature alone) in order to resolve a dissipation inconsistency. It is shown that energy dissipation in a statistically steady state is the time-averaged volume integral of and not that of . Secondly, in the framework of the anelastic equations derived with respect to the adiabatic reference state, we obtain a condition when the anelastic liquid approximation can be made, , independent of the dissipation number.
On symplectic capacities of toric domains

A toric domain is a subset of $(\mathbb{C}^n,\omega_{\text{std}})$ which is invariant under the standard rotation action of $\mathbb{T}^n$ on $\mathbb{C}^n$. For a toric domain $U$ from a certain large class for which this action is not free, we find a corresponding toric domain $V$ where the standard action is free, and for which $c(U)=c(V)$ for any symplectic capacity $c$. Michael Hutchings gives a combinatorial formula for calculating his embedded contact homology symplectic capacities for certain toric four-manifolds on which the $\mathbb{T}^2$-action is free. Our theorem allows one to extend this formula to a class of toric domains where the action is not free. We apply our theorem to compute ECH capacities for certain intersections of ellipsoids, and find that these capacities give sharp obstructions to symplectically embedding these ellipsoid intersections into balls.
A Refined Count of BPS States in the D1/D5 System

We examine the low-lying quarter BPS spectrum of a 2d conformal field theory with target Sym N (K3) at various points in the moduli space, and look at a more refined count than the ordinary elliptic genus. We compute growth of the spectrum at both the symmetric orbifold point, as well as at the supergravity point in the moduli space. Finally we do a decomposition of the spectra into $$ \mathcal{N}=4 $$ characters and discuss possible relations to interesting symmetry groups. A similar analysis is done with T 4.
Tunable Coupling Scheme for Implementing High-Fidelity Two-Qubit Gates

The prospect of computational hardware with quantum advantage relies critically on the quality of quantum-gate operations. Imperfect two-qubit gates are a major bottleneck for achieving scalable quantum-information processors. Here, we propose a generalizable and extensible scheme for a two-qubit tunable coupler that controls the qubit-qubit coupling by modulating the coupler frequency. Two-qubit gate operations can be implemented by operating the coupler in the dispersive regime, which is noninvasive to the qubit states. We investigate the performance of the scheme by simulating a universal two-qubit gate on a superconducting quantum circuit, and find that errors from known parasitic effects are strongly suppressed. The scheme is compatible with existing high-coherence hardware, thereby promising a higher gate fidelity with current technologies.
Bounds on the Heat Kernel under the Ricci Flow

We establish an estimate for the fundamental solution of the heat equation on a closed Riemannian manifold $M$ of dimension at least 3, evolving under the Ricci flow. The estimate depends on some constants arising from a Sobolev imbedding theorem. Considering the case when the scalar curvature is positive throughout the manifold, at any time, we will obtain, as a corollary, a bound similar to the one known for the fixed metric case.