cssi/SciSciGPT-SciSciNet huggingface dataset:
Stability and dynamics of skyrmions in ultrathin magnetic nanodisks under strain

Abstract Understanding the switching mechanism of magnetic skyrmions is critical for realizing their potential applications in future spintronic devices. Here we study the thermodynamic stability and dynamics of a Neel skyrmion in an ultrathin magnetic nanodisk under biaxial in-plane strains using a combination of phase-field simulations and analytical theory. We demonstrated the switching of a circular skyrmion to a variety of magnetic configurations, including an out-of-plane monodomain or an in-plane vortex under isotropic strains and to an elliptical skyrmion or a stripe domain under anisotropic strains. We successfully formulated a Lagrangian-mechanics-based model to analytically describe the switching dynamics of a skyrmion. Both our simulations and analytical model revealed that the strain-mediated breathing dynamics of skyrmions lead to a counter-intuitive phenomenon in which a lager strain may lead to slower skyrmion-to-monodomain switching.
Hierarchical PCA and Applications to Portfolio Management

It is widely known that the common risk-factors derived from PCA beyond the first eigenportfolio are generally difficult to interpret and thus to use in practical portfolio management. We explore an alternative approach (HPCA) which makes strong use of the partition of the market into sectors. We show that this approach leads to no loss of information with respect to PCA in the case of equities (constituents of the S&P 500) and also that the associated common factors admit simple interpretations. The model can also be used in markets in which the sectors have asynchronous price information, such as single-name credit default swaps, generalizing the works of Cont and Kan (2011) and Ivanov (2016).
Probenecid-Boosted Tenofovir: A Physiologically-Based Pharmacokinetic Model-Informed Strategy for On-Demand HIV Preexposure Prophylaxis.

Multiple doses of tenofovir disoproxil fumarate (TDF) together with emtricitabine is effective for HIV preexposure prophylaxis (PrEP). TDF is converted to tenofovir (TFV) in circulation, which is subsequently cleared via tubular secretion by organic ion transporters (OATs; OAT1 and OAT3). Using in vitro kinetic parameters for TFV and the OAT1 and OAT3 inhibitor probenecid, a bottom-up physiologically-based pharmacokinetic model was successfully developed for the first time that accurately describes the probenecid-TFV interaction. This model predicted an increase in TFV plasma exposure by 60%, which was within 15% of the observed clinical pharmacokinetic data, and a threefold decrease in renal cells exposure following coadministration of a 600 mg TDF dose with 2 g probenecid. When compared with multiple-dose regimens, a single-dose probenecid-boosted TDF regimen may be effective for HIV PrEP and improve adherence and safety by minimizing TFV-induced nephrotoxicity by reducing TFV accumulation in renal cells.
Eating to save the planet: Evidence from a randomized controlled trial using individual-level food purchase data

Abstract Meat consumption is a major driver of climate change. Interventions that reduce meat consumption may improve public health and promote environmental sustainability. We conducted a randomized controlled trial to examine the effects of an awareness-raising intervention on meat consumption. We randomized undergraduate classes into treatment and control groups. Treatment groups received a 50-minute lecture on how food choices affect climate change, along with information about the health benefits of reduced meat consumption. Control classrooms received a lecture on a placebo topic. We analyzed 49,301 students’ meal purchases in the college dining halls before and after the intervention. We merged food purchase data with survey data to study heterogenous treatment effects and disentangle mechanisms. Participants in the treatment group reduced their purchases of meat and increased their purchases of plant-based alternatives after the intervention. The probability of purchasing a meat-based meal fell by 4.6 percentage points (p
The Densest k Subgraph Problem in b-Outerplanar Graphs

We give an exact \(O(nk^2)\) algorithm for finding the densest k subgraph in outerplanar graphs. We extend this to an exact \(O(nk^2 8^b)\) algorithm for finding the densest k subgraph in b-outerplanar graphs. Often, when there is an exact polynomial time algorithm for a problem on b-outerplanar graphs, this algorithm can be extended to a polynomial time approximation scheme (PTAS) on planar graphs using Baker’s technique. We hypothesize that this is not possible for the densest k subgraph problem.
Infant and adult brains are coupled to the dynamics of natural communication

Infancy is the foundational period for learning from adults, and the dynamics of the social environment have long been considered central to children’s development. Here, we reveal a novel, natural...
Determining the shape of a human vocal tract from pressure measurements at the lips

The inverse problem of determining the cross-sectional area of a human vocal tract during the utterance of a vowel is considered in terms of the data consisting of the absolute value of sound pressure at the lips. If the upper lip is curved downward during the utterance, it is shown that there may be up to an $M$-fold nonuniqueness in the determination, where $M$ is the maximal number of eligible resonances associated with a related Schrodinger operator. Each of the $M$ such distinct candidates for the vocal-tract area corresponding to the same absolute pressure is uniquely determined. The mathematical theory is presented for the recovery of each candidate for the vocal-tract area, and the admissibility criterion for each of the $M$ candidates to be a vocal-tract radius is specified. On the other hand, if the upper lip is horizontal or curved upward during the utterance, then the inverse problem has a unique solution. The theory developed is illustrated with some examples.
Generating few-cycle pulses with integrated nonlinear photonics.

Ultrashort laser pulses that last only a few optical cycles have been transformative tools for studying and manipulating light–matter interactions. Few-cycle pulses are typically produced from high-peak-power lasers, either directly from a laser oscillator or through nonlinear effects in bulk or fiber materials. Now, an opportunity exists to explore the few-cycle regime with the emergence of fully integrated nonlinear photonics. Here, we experimentally and numerically demonstrate how lithographically patterned waveguides can be used to generate few-cycle laser pulses from an input seed pulse. Moreover, our work explores a design principle in which lithographically varying the group-velocity dispersion in a waveguide enables the creation of highly constant-intensity supercontinuum spectra across an octave of bandwidth. An integrated source of few-cycle pulses could broaden the range of applications for ultrafast light sources, including supporting new lab-on-a-chip systems in a scalable form factor.
Deep learning for inferring gene relationships from single-cell expression data.

Several methods were developed to mine gene–gene relationships from expression data. Examples include correlation and mutual information methods for coexpression analysis, clustering and undirected graphical models for functional assignments, and directed graphical models for pathway reconstruction. Using an encoding for gene expression data, followed by deep neural networks analysis, we present a framework that can successfully address all of these diverse tasks. We show that our method, convolutional neural network for coexpression (CNNC), improves upon prior methods in tasks ranging from predicting transcription factor targets to identifying disease-related genes to causality inference. CNNC’s encoding provides insights about some of the decisions it makes and their biological basis. CNNC is flexible and can easily be extended to integrate additional types of genomics data, leading to further improvements in its performance.
Comparing alternative cholera vaccination strategies in Maela refugee camp: using a transmission model in public health practice

Cholera is a major public health concern in displaced-person camps, which often contend with overcrowding and scarcity of resources. Maela, the largest and longest-standing refugee camp in Thailand, located along the Thai-Burmese border, experienced four cholera outbreaks between 2005 and 2010. In 2013, a cholera vaccine campaign was implemented in the camp. To assist in the evaluation of the campaign and planning for subsequent campaigns, we developed a mathematical model of cholera in Maela. We formulated a Susceptible-Infectious-Water-Recovered-based transmission model and estimated parameters using incidence data from 2010. We next evaluated the reduction in cases conferred by several immunization strategies, varying timing, effectiveness, and resources (i.e., vaccine availability). After the vaccine campaign, we generated case forecasts for the next year, to inform on-the-ground decision-making regarding whether a booster campaign was needed. We found that preexposure vaccination can substantially reduce the risk of cholera even when <50% of the population is given the full two-dose series. Additionally, the preferred number of doses per person should be considered in the context of one vs. two dose effectiveness and vaccine availability. For reactive vaccination, a trade-off between timing and effectiveness was revealed, indicating that it may be beneficial to give one dose to more people rather than two doses to fewer people, given that a two-dose schedule would incur a delay in administration of the second dose. Forecasting using realistic coverage levels predicted that there was no need for a booster campaign in 2014 (consistent with our predictions, there was not a cholera epidemic in 2014). Our analyses suggest that vaccination in conjunction with ongoing water sanitation and hygiene efforts provides an effective strategy for controlling cholera outbreaks in refugee camps. Effective preexposure vaccination depends on timing and effectiveness. If a camp is facing an outbreak, delayed distribution of vaccines can substantially alter the effectiveness of reactive vaccination, suggesting that quick distribution of vaccines may be more important than ensuring every individual receives both vaccine doses. Overall, this analysis illustrates how mathematical models can be applied in public health practice, to assist in evaluating alternative intervention strategies and inform decision-making.
Discourse Level Factors for Sentence Deletion in Text Simplification.

This paper presents a data-driven study focusing on analyzing and predicting sentence deletion — a prevalent but understudied phenomenon in document simplification — on a large English text simplification corpus. We inspect various document and discourse factors associated with sentence deletion, using a new manually annotated sentence alignment corpus we collected. We reveal that professional editors utilize different strategies to meet readability standards of elementary and middle schools. To predict whether a sentence will be deleted during simplification to a certain level, we harness automatically aligned data to train a classification model. Evaluated on our manually annotated data, our best models reached F1 scores of 65.2 and 59.7 for this task at the levels of elementary and middle school, respectively. We find that discourse level factors contribute to the challenging task of predicting sentence deletion for simplification.
Silicon-Proven Timing Signoff Methodology Using Hazard-Free Robust Path Delay Tests

Ensuring a tight correlation between pre-silicon static timing analysis (STA) and post-silicon timing analysis is essential to a robust design flow. Researchers from Intel describe a novel methodology to validate path level STA on silicon using standard scan architecture and path delay tests that are generated by commercial EDA tools.
On Racial Disparities in Recent Fatal Police Shootings

Fatal police shootings in the United States continue to be a polarizing social and political issue. Clear disagreement between racial proportions of victims and nationwide racial demographics toget...
Weak order and descents for monotone triangles

Abstract Monotone triangles are a rich extension of permutations that are in bijection with alternating sign matrices. The notions of weak order and descent sets for permutations are generalized here to monotone triangles, and shown to enjoy many analogous properties. It is shown that any linear extension of the weak order gives rise to a shelling order on a poset, recently introduced by Terwilliger, whose maximal chains are in bijection with monotone triangles; among these shellings is a family of EL-shellings. The weak order turns out to encode an action of the 0-Hecke monoid of type A on the monotone triangles, generalizing the usual bubble-sorting action on permutations. It also leads to a notion of descent set for monotone triangles, having another natural property: the surjective algebra map from the Malvenuto–Reutenauer Hopf algebra of permutations into quasisymmetric functions extends in a natural way to an algebra map out of the recently-defined Cheballah–Giraudo–Maurice algebra of alternating sign matrices.
NEW HOMOGENEOUS EINSTEIN METRICS OF NEGATIVE RICCI CURVATURE

We construct new homogeneous Einstein spaces with negative Ricci curvature in two ways: First, we give a method for classifying and constructing a class of rank one Einstein solvmanifolds whose derived algebras are two-step nilpotent. As an application, we describe an explicit continuous family of ten- dimensional Einstein manifolds with a two-dimensional parameter space, including a continuous subfamily of manifolds with negative sectional curvature. Secondly, we obtain new examples of non-symmetric Einstein solvmanifolds by modifying the algebraic structure of non-compact irreducible symmetric spaces of rank greater than one, preserving the (constant) Ricci curvature.
Acquired cystic kidney disease.

Abstract ACKD is characterized by the development of many fluid-filled renal cysts and sometimes neoplasms in the kidneys of individuals with chronic renal failure but without a history of hereditary cystic disease. The condition is seen mainly in dialysis patients, but often begins in patients with ESRD before dialysis is started. Most patients with ACKD are asymptomatic, but the disorder may be associated with such serious complications as retroperitoneal hemorrhage and metastatic renal cell carcinoma. The diagnosis of ACKD and its complications is best achieved by CT scanning, although US and MR imaging may be useful in evaluation, particularly in patients not treated with dialysis. Cyst hemorrhage is common in ACKD and may cause flank pain and hematuria. Hemorrhagic cysts may be recognized by their CT scan, sonographic, or MR imaging features. Hemorrhagic cysts may rupture into the perinephric space causing large perinephric hematomas. These can usually be treated-conservatively. Patients with ACKD, particularly those treated with dialysis, have an increased risk of renal cell carcinoma. Renal cell carcinoma may also develop in the native kidneys of renal transplant recipients with good graft function many years after transplantation. Annual imaging of the native kidneys of all dialysis patients or of transplant recipients for the development of carcinoma is not justified, however, because it has not been shown to have a significant effect on patient outcome. Screening may, however, be useful in selected dialysis patients with good general medical condition and who have known risk factors for renal cell carcinoma including prolonged dialysis, large kidneys, ACKD, and male gender. Screening of the native kidneys of transplant recipients may be performed when they are referred for US evaluation of the renal allograft.
Sentencing is Dang Hard … and So …

This essay, adapted from a speech upon receipt of the 2018 Richard P. Kern Memorial Award from the National Association of Sentencing Commissions, details why sentencing is “dang hard” and explores implications of that reality. The essay argues that the challenges of sentencing not only demand that all jurisdictions have a sentencing commission as an essential permanent agency, but also call for these commissions always to think big and to strive to work deep and wide to study all facets of modern criminal justice systems. The essay also contends that sentencing errors may be quite common and that, even if we manage to get sentencing “right” at the outset, changes in society and in individuals can make even “right” sentences wrong over time. Sensible humility about the likelihood of sentencing errors further suggests, for example: at the rule-making stage, having sentencing laws include sunset provisions and having sentencing commissions review and audit major guidelines and related sentencing practices on a regular basis; at the case-specific stage, having far more robust substantive appellate review of sentences and more robust mechanisms for parole and judicial reconsideration and clemency, and even developing more creative means to apply and revise different forms of punishment as time passes and new information is gathered.
A self-initiated cue-reward learning procedure for neural recording in rodents.

Abstract Background Single-unit recording in Pavlovian conditioning tasks requires the use of within-subject designs as well as sampling a considerable number of trials per trial type and session, which increases the total trial count. Pavlovian conditioning, on the other hand, requires a long average intertrial interval (ITI) relative to cue duration for cue-specific learning to occur. These requirements combined can make the session duration unfeasibly long. New method To circumvent this issue, we developed a self-initiated variant of the Pavlovian magazine-approach procedure in rodents. Unlike the standard procedure, where the animals passively receive the trials, the self-initiated procedure grants animals agency to self-administer and self-pace trials from a predetermined, pseudorandomized list. Critically, whereas in the standard procedure the typical ITI is in the order of minutes, our procedure uses a much shorter ITI (10 s). Results Despite such a short ITI, discrimination learning in the self-initiated procedure is comparable to that observed in the standard procedure with a typical ITI, and superior to that observed in the standard procedure with an equally short ITI. Comparison with existing method(s) The self-initiated procedure permits delivering 100 trials in a ∼1-h session, almost doubling the number of trials safely attainable over that period with the standard procedure. Conclusions The self-initiated procedure enhances the collection of neural correlates of cue-reward learning while producing good discrimination performance. Other advantages for neural recording studies include ensuring that at the start of each trial the animal is engaged, attentive and in the same location within the conditioning chamber.
The African economic growth experience and tourism receipts: A threshold analysis and quantile regression approach:

By applying threshold analysis and quantile regression techniques, we investigate the linearity of the relationship between tourism receipts and economic growth. We find that a threshold exists, be...
Sensitivity optimization for NV-diamond magnetometry

Solid-state spin systems including nitrogen-vacancy (NV) centers in diamond constitute an increasingly favored quantum sensing platform. However, present NV ensemble devices exhibit sensitivities orders of magnitude away from theoretical limits. The sensitivity shortfall both handicaps existing implementations and curtails the envisioned application space. This review analyzes present and proposed approaches to enhance the sensitivity of broadband ensemble-NV-diamond magnetometers. Improvements to the spin dephasing time, the readout fidelity, and the host diamond material properties are identified as the most promising avenues and are investigated extensively. Our analysis of sensitivity optimization establishes a foundation to stimulate development of new techniques for enhancing solid-state sensor performance.
Murine lupus is neutrophil elastase-independent in the MRL.Faslpr model

Loss of tolerance to nuclear antigens and multisystem tissue destruction is a hallmark of systemic lupus erythematosus (SLE). Although the source of autoantigen in lupus remains elusive, a compelling hypothetical source is dead cell debris that drives autoimmune activation. Prior reports suggest that neutrophil extracellular traps (NETs) and their associated death pathway, NETosis, are sources of autoantigen in SLE. However, others and we have shown that inhibition of NETs by targeting the NADPH oxidase complex and peptidylarginine deiminase 4 (PADI4) did not ameliorate disease in spontaneous murine models of SLE. Furthermore, myeloperoxidase and PADI4 deletion did not inhibit induced lupus. Since NET formation may occur independently of any one mediator, to address this controversy, we genetically deleted an additional important mediator of NETs and neutrophil effector function, neutrophil elastase (ELANE), in the MRL.Faslpr model of SLE. ELANE deficiency, and by extension ELANE-dependent NETs, had no effect on SLE nephritis, dermatitis, anti-self response, or immune composition in MRL.Faslpr mice. Taken together with prior data from our group and others, these data further challenge the paradigm that NETs and neutrophils are pathogenic in SLE.
A new hybrid algorithm - Navier-Stokes as a DSMC filter

Direct Simulation Monte Carlo (DSMC) and NavierStokes (NS) solutions are combined to investigate a coupled approach to solving mixed flow problems. DSMC, a statistical particle simulation technique used primarily for nonequilibrium high-Knudsen-number flows, is extremely computer intensive. On the other hand NS, a continuum fluid approximation valid for low Knudsen number (Kn), is much less expensive to implement. In the proposed hybrid approach, NS and DSMC codes have been used on the same computational domain to compute the properties of a test problem for two different values of Kn (0.07 and 0.14). We first discuss how each code was modified to accept data from the other, both with respect to internal flow variables and boundary conditions. In this process, DSMC may be viewed as providing the physically correct values of local boundary conditions and transport coefficients for the NS equations. The DSMC solution averaged over very few samplings, rather than without averagings, provided input to NS to produce the filtered solution field, which is very similar to DSMC converged solution. Longer use of the NS filter did not show large improvements in the solution. The total computational time for the DSMC computation was reduced by factor of two by using the NS code as a filter in this study. However, the reduction of computational time would be more significant for three-dimensional problems. The conclusion is that the long period in which statistics must be gathered in order to achieve a good DSMC solution can be virtually eliminated by a short pass through the NS computations.
Thoughts, Crimes, and Thought Crimes

Thought crimes are the stuff of dystopian fiction, not contemporary law. Or so we’re told. Yet our criminal legal system may in a sense punish thought regularly, even as our existing criminal theory lacks the resources to recognize this state of affairs for what it is — or to explain what might be wrong with it. The beginning of wisdom lies in the seeming rhetorical excesses of those who complain that certain terrorism and hate crime laws punish offenders for their malevolent intentions while purporting to punish them for their conduct. Behind this too-easily-written-off complaint is a half-buried precept of criminal jurisprudence, one that this Essay aims to excavate, elaborate, and defend: that the proper target of an offender’s punishment is always the criminal action itself, not the offender’s associated mental state conceived as a separate wrong. Taken seriously, this precept would change how we punish an assortment of criminal offenses, from attempts to hate crimes to terrorism. It also would change how we conceive the criminal law’s core axioms, especially the poorly understood but surprisingly important doctrine of concurrence.
Nonminimal Lorentz Violation in Linearized Gravity

This contribution to the CPT'19 meeting provides a brief overview of recent theoretical studies of nonminimal Lorentz violation in linearized gravity. Signatures in gravitational waves from coalescing compact binaries are discussed.
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack

The goal of a decision-based adversarial attack on a trained model is to generate adversarial examples based solely on observing output labels returned by the targeted model. We develop HopSkipJumpAttack, a family of algorithms based on a novel estimate of the gradient direction using binary information at the decision boundary. The proposed family includes both untargeted and targeted attacks optimized for l and l ∞ similarity metrics respectively. Theoretical analysis is provided for the proposed algorithms and the gradient direction estimate. Experiments show HopSkipJumpAttack requires significantly fewer model queries than several state-of-the-art decision-based adversarial attacks. It also achieves competitive performance in attacking several widely-used defense mechanisms.
Impact of Měnglà virus proteins on human and bat innate immune pathways.

Měngla virus (MLAV), identified in Rousettus bats, is a phylogenetically distinct member of the family Filoviridae Because the filoviruses Ebola virus (EBOV) and Marburg virus (MARV) modulate host innate immunity, MLAV VP35, VP40, and VP24 proteins were compared with their EBOV and MARV homologs for innate immune pathway modulation. In human and Rousettus cells, MLAV VP35 behaved like EBOV and MARV VP35s, inhibiting virus-induced activation of the interferon beta (IFN-β) promoter and interferon regulatory factor 3 (IRF3) phosphorylation. MLAV VP35 also interacted with PACT, a host protein engaged by EBOV VP35 to inhibit RIG-I signaling. MLAV VP35 also inhibits PKR activation. MLAV VP40 was demonstrated to inhibit type I IFN-induced gene expression in human and bat cells. It blocked STAT1 tyrosine phosphorylation induced either by type I IFN or overexpressed Jak1, paralleling MARV VP40. MLAV VP40 also inhibited virus-induced IFN-β promoter activation, a property shared by MARV VP40 and EBOV VP24. A Jak kinase inhibitor did not recapitulate this inhibition in the absence of viral proteins. Therefore, inhibition of Jak-STAT signaling is insufficient to explain inhibition of IFN-β promoter activation. MLAV VP24 did not inhibit IFN-induced gene expression or bind karyopherin α proteins, properties of EBOV VP24. MLAV VP24 differed from MARV VP24 in that it failed to interact with Keap1 or activate an antioxidant response element reporter gene due to the absence of a Keap1-binding motif. These functional observations support a closer relationship of MLAV to MARV than to EBOV but also are consistent with MLAV belonging to a distinct genus.IMPORTANCE EBOV and MARV, members of the family Filoviridae, are highly pathogenic zoonotic viruses that cause severe disease in humans. Both viruses use several mechanisms to modulate the host innate immune response, and these likely contribute to the severity of disease. Here, we demonstrate that MLAV, a filovirus newly discovered in a bat, suppresses antiviral type I interferon responses in both human and bat cells. Inhibitory activities are possessed by MLAV VP35 and VP40, which parallels how MARV blocks IFN responses. However, whereas MARV activates cellular antioxidant responses through an interaction between its VP24 protein and host protein Keap1, MLAV VP24 lacks a Keap1-binding motif and fails to activate this cytoprotective response. These data indicate that MLAV possesses immune-suppressing functions that could facilitate human infection. They also support the placement of MLAV in a different genus than either EBOV or MARV.
The generalized matcher game

Abstract Recently the matcher game was introduced. In this game, two players create a maximal matching by one player repeatedly choosing a vertex and the other player choosing a K 2 containing that vertex. One player tries to minimize the result and the other to maximize the result. In this paper we propose a generalization of this game where K 2 is replaced by a general graph F . We focus here on the case of F = P 3 . We provide some general results and lower bounds for the game, investigate the graphs where the game ends with all vertices taken, and calculate the value for some specific families of graphs.
Communicating Correlated Sources Over MAC and Interference Channels I: Separation-Based Schemes

We consider the two scenarios of communicating a pair $S_{1},S_{2}$ of distributed correlated sources over 2–user multiple access (MAC) and interference channels (IC), respectively. While in the MAC problem , the receiver needs to reconstruct both sources, in the IC problem , receiver $j$ needs to reconstruct $S_{j}$ . We undertake a Shannon theoretic study and focus on characterizing sufficient conditions. Building on Dueck’s findings (1981), we propose a coding scheme based on fixed block-length (B-L) codes . We characterize its information theoretic performance and characterize a new set of sufficient conditions. We identify examples of the MAC and IC problems for which the latter conditions are proven to be strictly weaker than the current known tightest.
Minerva: A Portable Machine Learning Microservice Framework for Traditional Enterprise SaaS Applications

In traditional SaaS enterprise applications, microservices are an essential ingredient to deploy machine learning (ML) models successfully. In general, microservices result in efficiencies in software service design, development, and delivery. As they become ubiquitous in the redesign of monolithic software, with the addition of machine learning, the traditional applications are also becoming increasingly intelligent. Here, we propose a portable ML microservice framework Minerva (microservices container for applied ML) as an efficient way to modularize and deploy intelligent microservices in traditional legacy SaaS applications suite, especially in the enterprise domain. We identify and discuss the needs, challenges and architecture to incorporate ML microservices in such applications. Minervas design for optimal integration with legacy applications using microservices architecture leveraging lightweight infrastructure accelerates deploying ML models in such applications.
Effect Modification and Interaction

This article discusses definitions and concepts of effect modification, interaction, synergism, and related concepts and terms. Keywords: antagonism; causal coaction; effect-measure modification; effect modification; heterogeneity of effect; interaction; synergism
"Might Not Be a Tomorrow": A Multi-Methods Approach to Anticipated Early Death and Youth Crime *

Several researchers point to the anticipation of early death, or a sense of “futurelessness,” as a contributing factor to youth crime. It is argued that young people who perceive a high probability of early death may have little reason to delay gratification for the promise of future benefits, as the future itself is discounted. Consequently, these young people tend to pursue high-risk behaviors associated with immediate rewards, which include crime and violence. Although existing studies lend support to these arguments and show a statistical relationship between anticipated early death and youth crime, this support remains tentative. Moreover, several questions remain regarding the interpretation of this relationship, the meanings that offenders attach to the prospect of early death, and the cognitive processes that link anticipated early death to youth crime. In this article, we address the limitations of previous studies using a multimethods approach, which involves the analyses of national survey data and in-depth interviews with active street offenders.
A Deletion-Contraction Relation for the Chromatic Symmetric Function

Abstract We extend the definition of the chromatic symmetric function X G to include graphs G with a vertex-weight function w : V ( G ) → N . We show how this provides the chromatic symmetric function with a natural deletion–contraction relation analogous to that of the chromatic polynomial. Using this relation we derive new properties of the chromatic symmetric function, and we give alternate proofs of many fundamental properties of X G .
Chapter 13 – Particle Physics

All matter is composed of leptons, quarks, and elementary particles called bosons, which serve as the carriers of the force between particles. The lepton family includes the electron, muon, tau, and their neutrinos. Quarks come in six types, called flavors, denoted by up (u), down (d), strange (s), charmed (c), bottom (b), and top (t) quarks. All interactions conserve the lepton numbers and the number of baryons (B). The weak interaction can change the flavor of a quark and thus violate the conservation laws associated with the quark quantum numbers (strangeness, charm, beauty, and truth). There are two general kinds of strongly interacting particles: mesons, which are composed of quark/antiquark pairs, and baryons, which consist of three quarks. The strongly interacting particles occur in isospin multiplets with all members of a multiplet having approximately the same mass. The members of an isospin multiplet all have the same value of the hypercharge Y, which is the sum of B, S, C , B~, and T. The members of each multiplet are distinguished by the charge Q and I3. Particles can also be grouped in larger families of particles called supermultiplets. The lightest mesons consist of two nonets with each consisting of nine mesons, while the lightest baryons consist of an octet with eight baryons and a decuplet with ten baryons. The interactions between leptons and quarks are described by Feynman diagrams. These diagrams describe processes by which particles interact by exchanging quanta of the interaction fields. Recent work on gauge symmetries provide a general framework for understanding the interactions between elementary particles. There are gauge symmetries associated with the electroweak and strong interactions. Associated with each gauge symmetry are gauge fields and gauge bosons which serve as carriers of the interactions. The photon and the W+, W−, and Z0 are the gauge particles associated with the electroweak interaction, while gluons serve as the gauge particles of the strong interaction.
On Experiences with PIL, an Interpretive Language, in an Undergraduate Numerical Methods Course

The University of Pittsburgh's numerical calculus course acquaints students with various algorithms for interpolation, functional approximation, numerical differentiation and integration, and solving nonlinear equations. Computational and coding efficiency, regions and rates of convergence, and effects of errors are stressed.
Fingerprinting Redox Heterogeneity in Electrodes during Extreme Fast Charging

Conventionally, battery electrodes are rationalized as homogeneous reactors. It proves to be an erroneous interpretation for fast transients, where mass transport limitations amplify underlying heterogeneities. Given the lack of observability of associated fast spatiotemporal dynamics, redox activity in inhomogeneous electrodes is superficially explored. We resort to a physics-based description to examine extreme fast charging of lithium-ion battery electrodes. Representative inhomogeneity information is extracted from electrode tomograms. We discover such electrodes to undergo preferential intercalation, localized lithium plating and nonuniform heat generation as a result of distributed long- and short-range interactions. The spatial correlations of these events with the underlying inhomogeneity are found to be nonidentical. Investigation of multiple inhomogeneity fields reveals an exponential scaling of plating severity and early onset in contrast to the homogeneous limit. Anode and cathode inhomogeneities couple nonlinearly to grow peculiar electrodeposition patterns. These mechanistic insights annotate the complex functioning of spatially nonuniform electrodes.
A Flight Capable Atomic Gravity Gradiometer With a Single Laser

We present a design for a cold atom gravity gradiometer with a single laser diode that will operate while mounted to an unmaned aerial vehicle. Our design exhibits a lightweight aluminum vacuum chamber and a novel diffraction grating magneto-optical trap.
Data privacy against innovation or against discrimination?: The case of the California Consumer Privacy Act (CCPA)

Abstract Conducting a case study on the California Consumer Privacy Act (CCPA), this paper analyzes divergent frames of privacy argued by different stakeholders. While the United States has allowed corporate self-regulation of consumer privacy, California became the first state to introduce its own privacy law in June 2018. In early 2019, California held public forums on CCPA, which then became a battleground for various stakeholders to discuss data privacy regulations. Examining 105 public comments made by 99 speakers in 7 CCPA public forums, this study identified that corporate representatives and consumer advocates differed in seven major areas: (1) the purpose of CCPA, (2) definitions of personal information and consumer, (3) operationalization of opt-out, (4) non-discrimination rules, (5) economic ramifications, (6) consumer literacy, and (7) comparison with other privacy frameworks. The findings suggest that corporate speakers follow the frame of privacy as a commodity, while consumer speakers seek the frame of privacy as a right.
Strategic trading and unobservable information acquisition

Abstract We allow a strategic trader to choose when to acquire information about an asset’s payoff, instead of endowing her with it. When the trader dynamically controls the precision of a flow of information, the optimal precision evolves stochastically and increases with market liquidity. Because the trader exploits her information gradually, the equilibrium price impact and market uncertainty are unaffected by her rate of acquisition. If she pays a fixed cost to acquire “lumpy” information at a time of her choosing, the market can break down: we show that no equilibria exist with endogenous information acquisition. Our analysis suggests caution when applying insights from standard strategic trading models to settings with information acquisition.
An empiricist's guide to modern coexistence theory for competitive communities

Abstract While most ecological theories have historically invoked niche differences as the primary mechanism allowing species coexistence, we now know that species coexistence in competitive communities actually depends on the balance of two opposing forces: niche differences (ND) that determine how species limit their own growth rate versus that of their competitor, and relative fitness differences (RFD) that establish competitive hierarchies among species. Several different empirical methods have been proposed for measuring ND and RFD in order to make predictions about coexistence of species, yet it remains unclear which method(s) are appropriate for a given empirical study and whether or not those methods actually yield the same information. Here we summarize and compare five different empirical methods, with the aim of providing a practical guide for empiricists who want to predict coexistence among species. These include two phenomenological methods that estimate ND and RFD based on observing competitive interactions among species; two mechanistic methods that estimate ND and RFD based solely on information about species’ resource requirements; and a fifth method that does not yield ND and RFD but describes the impacts of those forces within communities. Based on the specific requirements, limitations, and assumptions of each approach, we offer a series of decision steps that can be used to determine which method(s) are best for a given study system. In particular, we show there are important tradeoffs between mechanistic methods, which require detailed understanding of species niches and physiology but are more tractable experimentally, and phenomenological methods which do not require this detailed information but can be impractical for some study designs. Importantly, we show that although each method can be used to estimate ND and RFD, the methods do not always yield the same values. Therefore we caution against future syntheses that compile these estimates from different empirical studies. Finally, we highlight several areas where modern coexistence theory could benefit from additional empirical work.
Diverse maize hybrids are structurally inefficient at resisting wind induced bending forces that cause stalk lodging.

Stalk lodging (breaking of agricultural plant stalks prior to harvest) results in millions of dollars in lost revenue each year. Despite a growing body of literature on the topic of stalk lodging, the structural efficiency of maize stalks has not been investigated previously. In this study, we investigate the morphology of mature maize stalks to determine if rind tissues, which are the major load bearing component of corn stalks, are efficiently organized to withstand wind induced bending stresses that cause stalk lodging. 945 fully mature, dried commercial hybrid maize stem specimens (48 hybrids, ~ 2 replicates, ~ 10 samples per plot) were subjected to: (1) three-point-bending tests to measure their bending strength and (2) rind penetration tests to measure the cross-sectional morphology at each internode. The data were analyzed through an engineering optimization algorithm to determine the structural efficiency of the specimens. Hybrids with higher average bending strengths were found to allocate rind tissue more efficiently than weaker hybrids. However, even strong hybrids were structurally suboptimal. There remains significant room for improving the structural efficiency of maize stalks. Results also indicated that stalks are morphologically organized to resist wind loading that occurs primarily above the ear. Results are applicable to selective breeding and crop management studies seeking to reduce stalk lodging rates.
DNA content and ploidy estimation of Festuca ovina accessions by flow cytometry

Festuca ovina is a fine fescue that is used as a low-input turfgrass. The ploidy levels of F. ovina accessions held by the USDA National Plant Germplasm System (NPGS) are unknown, limiting the use of the germplasm in breeding programs. The objective of this study was to determine DNA content and estimate ploidy of these 127 accessions. Among the accessions, we identified a wide range of ploidy levels from diploid to octoploid. We also found the accessions with higher ploidy levels usually had larger seed size. These results will be informative to plant breeders and researchers using germplasm from the F. ovina collection and point to challenges in maintaining polyploid, outcrossing germplasm seed stocks in common nurseries.
Antisense oligonucleotide-mediated correction of CFTR splicing improves chloride secretion in cystic fibrosis patient-derived bronchial epithelial cells.

Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, encoding an anion channel that conducts chloride and bicarbonate across epithelial membranes. Mutations that disrupt pre-mRNA splicing occur in >15% of CF cases. One common CFTR splicing mutation is CFTR c.3718-2477C>T (3849+10 kb C>T), which creates a new 5' splice site, resulting in splicing to a cryptic exon with a premature termination codon. Splice-switching antisense oligonucleotides (ASOs) have emerged as an effective therapeutic strategy to block aberrant splicing. We test an ASO targeting the CFTR c.3718-2477C>T mutation and show that it effectively blocks aberrant splicing in primary bronchial epithelial (hBE) cells from CF patients with the mutation. ASO treatment results in long-term improvement in CFTR activity in hBE cells, as demonstrated by a recovery of chloride secretion and apical membrane conductance. We also show that the ASO is more effective at recovering chloride secretion in our assay than ivacaftor, the potentiator treatment currently available to these patients. Our findings demonstrate the utility of ASOs in correcting CFTR expression and channel activity in a manner expected to be therapeutic in patients.
The hidden null structure of the compressible Euler equations and a prelude to applications

We derive a new formulation of the compressible Euler equations exhibiting remarkable structures, including surprisingly good null structures. The new formulation comprises covariant wave equations...
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models

Recent models for unsupervised representation learning of text have employed a number of techniques to improve contextual word representations but have put little focus on discourse-level representations. We propose Conpono, an inter-sentence objective for pretraining language models that models discourse coherence and the distance between sentences. Given an anchor sentence, our model is trained to predict the text k sentences away using a sampled-softmax objective where the candidates consist of neighboring sentences and sentences randomly sampled from the corpus. On the discourse representation benchmark DiscoEval, our model improves over the previous state-of-the-art by up to 13% and on average 4% absolute across 7 tasks. Our model is the same size as BERT-Base, but outperforms the much larger BERT-Large model and other more recent approaches that incorporate discourse. We also show that Conpono yields gains of 2%-6% absolute even for tasks that do not explicitly evaluate discourse: textual entailment (RTE), common sense reasoning (COPA) and reading comprehension (ReCoRD).
Learning to Simulate and Design for Structural Engineering

The structural design process for buildings is time-consuming and laborious. To automate this process, structural engineers combine optimization methods with simulation tools to find an optimal design with minimal building mass subject to building regulations. However, structural engineers in practice often avoid optimization and compromise on a suboptimal design for the majority of buildings, due to the large size of the design space, the iterative nature of the optimization methods, and the slow simulation tools. In this work, we formulate the building structures as graphs and create an end-to-end pipeline that can learn to propose the optimal cross-sections of columns and beams by training together with a pre-trained differentiable structural simulator. The performance of the proposed structural designs is comparable to the ones optimized by genetic algorithm (GA), with all the constraints satisfied. The optimal structural design with the reduced the building mass can not only lower the material cost, but also decrease the carbon footprint.