cssi/SciSciGPT-SciSciNet huggingface dataset:
Measuring the Galactic Distribution of Transiting Planets with WFIRST

The WFIRST microlensing mission will measure precise light curves and relative parallaxes for millions of stars, giving it the potential to characterize short-period transiting planets all along the line of sight and into the galactic bulge. These light curves will enable the detection of more than 100,000 transiting planets whose host stars have measured distances. Although most of these planets cannot be followed up, several thousand hot Jupiters can be confirmed directly by detection of their secondary eclipses in the WFIRST data. Additionally, some systems of small planets may be confirmed by detecting transit timing variations over the duration of the WFIRST microlensing survey. Finally, many more planets may be validated by ruling out potential false positives. The combination of WFIRST transits and microlensing will provide a complete picture of planetary system architectures, from the very shortest periods to unbound planets, as a function of galactocentric distance.
Global dynamics of nonautonomous Hindmarsh–Rose equations

Abstract Global dynamics of nonautonomous diffusive Hindmarsh–Rose equations on a three-dimensional bounded domain in neurodynamics is investigated. The existence of a pullback attractor is proved through uniform estimates showing the pullback dissipative property and the pullback asymptotical compactness. Then the existence of pullback exponential attractor is also established by proving the smoothing Lipschitz continuity in a long run of the solution process.
On an inequality of A.~Grothendieck concerning operators on $L^1$

In 1955, A. Grothendieck proved a basic inequality which shows that any bounded linear operator between L1(µ)-spaces maps (Lebesgue-) dominated sequences to dominated sequences. An elementary proof of this inequality is obtained via a new decomposition principle for the lattice of measurable functions.
A Multilevel Analysis of Persistence of Students Taking a Pre-Engineering Curriculum in High School

Using data from the 2010 Indiana, USA public high school graduating class (N=55612), this project employed a multi-level analysis to determine, what if any differences occurred in majoring in science, technology, engineering, and math and freshman to sophomore year persistence, between students attending a school that offers Project Lead the Way and students that donâ€™t, while controlling for being a PLTW student.Â Results imply that PLTW had a statistically significant impact on the students participating in the program excluding students who were eligible for free and reduced lunch. However, this impact does not appear to carry over to the rest of the student body that does not participate in PLTW. https://doi.org/10.26803/ijlter.18.12.24
Fast Search and Estimation of Bayesian Nonparametric Mixture Models Using a Classification Annealing EM Algorithm

Bayesian nonparametric (BNP) infinite-mixture models provide flexible and accurate density estimation, cluster analysis, and regression. However, for the posterior inference of such a model, MCMC a...
Multivariate Alexander quandles, I. The module sequence of a link

The multivariate Alexander module of a link L has several subsets that admit quandle operations defined using the module operations. One of them, the fundamental multivariate Alexander quandle, det...
Generalization of QCD$_3$ Symmetry-Breaking and Flavored Quiver Dualities

We extend the recently proposed symmetry breaking scenario of QCD$_{3}$ to the so-called “master” (2 + 1)d bosonization duality, which has bosonic and fermionic matter on both ends. Using anomaly arguments, a phase diagram emerges with several novel regions. We then construct 2+1 dimensional dualities for flavored quivers using node-by-node dualization. Such dualities are applicable to theories which live on domain walls in QCD$_{4}$-like theories with dynamical quarks. We also derive dualities for quivers based on orthogonal and symplectic gauge groups. Lastly, we support the conjectured dualities using holographic constructions, even though several aspects of this holographic construction remain mostly qualitative.
FPGA Energy Efficiency by Leveraging Thermal Margin

FPGA devices are continuously evolving to meet high computation and performance demand for emerging applications. As a result, cutting edge FPGAs are not energy efficient as conventionally presumed to be, and therefore, aggressive power-saving techniques have become imperative. The clock rate of an FPGA-mapped design is set based on worst-case conditions to ensure reliable operation under all circumstances. This usually leaves a considerable timing margin that can be exploited to reduce power consumption by scaling voltage without lowering clock frequency. There are hurdles for such opportunistic voltage scaling in FPGAs because (a) critical paths change with designs, making timing evaluation difficult as voltage changes, (b) each FPGA resource has particular power-delay trade-off with voltage, (c) data corruption of configuration cells and memory blocks further hampers voltage scaling. In this paper, we propose a systematical approach to leverage the available thermal headroom of FPGA-mapped designs for power and energy improvement. By comprehensively analyzing the timing and power consumption of FPGA building blocks under varying temperatures and voltages, we propose a thermal-aware voltage scaling flow that effectively utilizes the thermal margin to reduce power consumption without degrading performance. We show the proposed flow can be employed for energy optimization as well, whereby power consumption and delay are compromised to accomplish the tasks with minimum energy. Lastly, we propose a simulation framework to be able to examine the efficiency of the proposed method for other applications that are inherently tolerant to a certain amount of error, granting further power saving opportunity. Experimental results over a set of industrial benchmarks indicate up to 36% power reduction with the same performance, and 66% total energy saving when energy is the optimization target.
Recursions for rational q,t-Catalan numbers

Author(s): Gorsky, E; Mazin, M; Vazirani, M | Abstract: We give a simple recursion labeled by binary sequences which computes rational q,t-Catalan power series, both in relatively prime and non relatively prime cases. It is inspired by, but not identical to recursions due to B. Elias, M. Hogancamp, and A. Mellit, obtained in their study of link homology. We also compare our recursion with the Hogancamp-Mellit's recursion and verify a connection between the Khovanov-Rozansky homology of N,M-torus links and the rational q,t-Catalan power series for general positive N,M.
Engineers Code: Reusable Open Learning Modules for Engineering Computations

Undergraduate programs in science and engineering include at least one course in basic programming, but seldom presented in a contextualized format, where computing is a tool for thinking and learning in the discipline. We have created a series of learning modules to embed computing in engineering education, and share this content under permissive public licenses. The modules are created as a set of lessons using Jupyter notebooks, and complemented by online courses in the Open edX platform, using new integrations we developed. Learning sequences in the online course pull content dynamically from public Jupyter notebooks and assessments are autograded on-the-fly, using our Jupyter Viewer and Jupyter Grader third-party extensions for Open edX. The learning content is modularized and designed for reuse in various formats. In one of these formats—short but intense workshops—our university library is leveraging the curriculum to offer extracurricular training for all, at high demands.
Simple Graph Density Inequalities with No Sum of Squares Proofs

Establishing inequalities among graph densities is a central pursuit in extremal combinatorics. A standard tool to certify the nonnegativity of a graph density expression is to write it as a sum of squares. In this paper, we identify a simple condition under which a graph density expression cannot be a sum of squares. Using this result, we prove that the Blakley-Roy inequality does not have a sum of squares certificate when the path length is odd. We also show that the same Blakley-Roy inequalities cannot be certified by sums of squares using a multiplier of the form one plus a sum of squares. These results answer two questions raised by Lovasz. Our main tool is used again to show that the smallest open case of Sidorenko's conjectured inequality cannot be certified by a sum of squares. Finally, we show that our setup is equivalent to existing frameworks by Razborov and Lovasz-Szegedy, and thus our results hold in these settings too.
Managing Machine Learning Workflow Components

Machine Learning Workflows (MLWfs) have become essential and a disruptive approach in problem-solving over several industries. However, the development process of MLWfs may be complicated, hard to achieve, time-consuming, and error-prone. To handle this problem, in this paper, we introduce machine learning workflow management (MLWfM) as a technique to aid the development and reuse of MLWfs and their components through three aspects: representation, execution, and creation. More precisely, we discuss our approach to structure the MLWfs' components and their metadata to aid retrieval and reuse of components in new MLWfs. Also, we consider the execution of these components within a tool. The hybrid knowledge representation, called Hyperknowledge, frames our methodology, supporting the three MLWfM's aspects. To validate our approach, we show a practical use case in the Oil & Gas industry.
Learning from Peers at the Wireless Edge

The last mile connection is dominated by wireless links where heterogeneous nodes share the limited and already crowded electromagnetic spectrum. Current contention based decentralized wireless access system is reactive in nature to mitigate the interference. In this paper, we propose to use neural networks to learn and predict spectrum availability in a collaborative manner such that its availability can be predicted with a high accuracy to maximize wireless access and minimize interference between simultaneous links. Edge nodes have a wide range of sensing and computation capabilities, while often using different operator networks, who might be reluctant to share their models. Hence, we introduce a peer to peer Federated Learning model, where a local model is trained based on the sensing results of each node and shared among its peers to create a global model. The need for a base station or access point to act as centralized parameter server is replaced by empowering the edge nodes as aggregators of the local models and minimizing the communication overhead for model transmission. We generate wireless channel access data, which is used to train the local models. Simulation results for both local and global models show over 95 % accuracy in predicting channel opportunities in various network topology.
ALTERED MERISTEM PROGRAM1 regulates leaf identity independently of miR156-mediated translational repression.

In Arabidopsis, loss of the carboxypeptidase, ALTERED MERISTEM PROGRAM1 (AMP1), produces an increase in the rate of leaf initiation, an enlarged shoot apical meristem and an increase in the number of juvenile leaves. This phenotype is also observed in plants with reduced levels of miR156-targeted SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) transcription factors, suggesting that AMP1 may promote SPL activity. However, we found that the amp1 mutant phenotype is only partially corrected by elevated SPL gene expression, and that amp1 has no significant effect on SPL transcript levels, or on the level or the activity of miR156. Although AMP1 has been reported to promote miRNA-mediated translational repression, amp1 did not prevent the translational repression of the miR156 target, SPL9, or the miR159 target, MYB33. These results suggest that AMP1 regulates vegetative phase change downstream of, or in parallel to, the miR156/SPL pathway and that it is not universally required for miRNA-mediated translational repression.
Notes on Bordered Floer Homology

Bordered Heegaard Floer homology is an extension of Ozsvath-Szabos Heegaard Floer homology to 3-manifolds with boundary, enjoying good properties with respect to gluings. In these notes we will introduce the key features of bordered Heegaard Floer homology: its formal structure, a precise definition of the invariants of surfaces, a sketch of the definitions of the 3-manifold invariants, and some hints at the analysis underlying the theory. We also talk about bordered Heegaard Floer homology as a computational tool, both in theory and practice.
External-Field-Free Spin Hall Switching of Perpendicular Magnetic Nanopillar with a Dipole-Coupled Composite Structure

Spin Hall effect (SHE) induced reversal of perpendicular magnetization has attracted significant interest, due to its potential to lead to low power memory and logic devices. However, the switching requires an assisted in-plane magnetic field, which hampers its practical applications. Here, we introduce a novel approach for external-field-free spin Hall switching of a perpendicular nanomagnet by utilizing a local dipolar field arising from an adjacent in-plane magnetic layer. Robust switching of perpendicular CoFeB nanopillars in a dipole-coupled composite stack is experimentally demonstrated in the absence of any external magnetic field, in consistent with the results of micromagnetic simulation. Large in-plane compensation field of about 135 Oe and out-of-plane loop shift of about 45 Oe / 10 7 A cm-2 are obtained in the nanopillar devices with composite structure. By performing micromagnetic simulations, we confirm the composite external-field-free switching strategy can also work for a 10 x 10 nm2 circular pillar. Compared with other proposed methods for external-field-free spin Hall switching of perpendicular magnetization, the dipole-coupled composite structure is compatible with a wide range of spin Hall systems and perpendicular magnetic tunnel junctions, paving the way towards practical SHE-based MRAM and logic applications.
Coupled Simulations of Finite-Rate Ablation with Pyrolysis in Rocket Nozzles

An ablation model based on finite-rate heterogeneous reactions is incorporated into a conjugate flowfield/ablation analysis framework, relaxing the assumption of equilibrium ablation made in previo...
Anti Anti-Orientalism, or Is Chinese Law Different?

Comparative law is haunted by the perceived need to avoid Orientalism: a type of analysis that postulates a dichotomy between the object of study and “the West,” finds the object lacking in certain essential qualities (or even having the opposite qualities of those the analyst deems essential), and then declares the object to be inferior. Yet a desire to avoid the errors of an Orientalist exaggeration and condemnation of difference all too often leads to an a priori denial of fundamental difference before the inquiry has even begun. The political imperative of anti-Orientalism takes precedence over all. This Article makes three arguments. First, it argues that there exists in comparative law scholarship in general, and in Chinese law scholarship in particular, a kind of anti-Orientalist discourse that needs to be critiqued because its very methodology makes it impossible to think certain thoughts and reach certain conclusions, regardless of the data. While I do not propose to rehabilitate Orientalism, I do maintain that it is time to move beyond anti-Orientalism. Second, it argues that data about what is conventionally called the Chinese legal system mean we have to seriously entertain the possibility that it is misleading to use the conventional language of Western jurisprudence (courts, judges, laws, rights) to talk about it, and not simply dismiss arguments to that effect as Orientalist or ethnocentric. Third, it argues that how we characterize China’s putatively legal order matters. China’s increasing integration into the global economy means that American institutions will increasingly have to deal with the products of that legal order. Questions about its fundamental nature can no longer be avoided. While the Article uses China as an example, its methodological point and conclusions apply more broadly to the analysis of any putative legal system. We should not derogate difference just because it is different, but we should not be biased against finding difference in the first place.
The State of the Uniform: Attacks on Encrypted Databases Beyond the Uniform Query Distribution

Recent foundational work on leakage-abuse attacks on encrypted databases has broadened our understanding of what an adversary can accomplish with a standard leakage profile. Nevertheless, all known value reconstruction attacks succeed under strong assumptions that may not hold in the real world. The most prevalent assumption is that queries are issued uniformly at random by the client. We present the first value reconstruction attacks that succeed without any knowledge about the query or data distribution. Our approach uses the search-pattern leakage, which exists in all known structured encryption schemes but has not been fully exploited so far. At the core of our method lies a support size estimator, a technique that utilizes the repetition of search tokens with the same response to estimate distances between encrypted values without any assumptions about the underlying distribution. We develop distribution-agnostic reconstruction attacks for both range queries and k-nearest-neighbor (k-NN) queries based on information extracted from the search-pattern leakage. Our new range attack follows a different algorithmic approach than state-of-the-art attacks, which are fine-tuned to succeed under the uniformly distributed queries. Instead, we reconstruct plaintext values under a variety of skewed query distributions and even outperform the accuracy of previous approaches under the uniform query distribution. Our new k-NN attack succeeds with far fewer samples than previous attacks and scales to much larger values of k. We demonstrate the effectiveness of our attacks by experimentally testing them on a wide range of query distributions and database densities, both unknown to the adversary.
MiR-101a loaded extracellular nanovesicles as bioactive carriers for cardiac repair

Abstract Myocardial infarction (MI) remains a major cause of mortality worldwide. Despite significant advances in MI treatment, many who survive the acute event are at high risk of chronic cardiac morbidity. Here we developed a cell-free therapeutic that capitalizes on the antifibrotic effects of micro(mi)RNA-101a and exploits the multi-faceted regenerative activity of mesenchymal stem cell (MSC) extracellular nanovesicles (eNVs). While the majority of MSC eNVs require local delivery via intramyocardial injection to exert therapeutic efficacy, we have developed MSC eNVs that can be administered in a minimally invasive manner, all while remaining therapeutically active. When loaded with miR-101a, MSC eNVs substantially decreased infarct size (9.2 ± 1.7% vs. 20.0 ± 6.5%) and increased ejection fraction (53.6 ± 7.6% vs. 40.3 ± 6.0%) and fractional shortening (23.6 ± 4.3% vs. 16.6 ± 3.0%) compared to control. These findings are significant as they represent an advance in the development of minimally invasive cardio-therapies.
The phylogenetic functional conservation of Drosophila Seven-In-Absentia (SINA) E3 ligase and its two human paralogs, SIAH1 and SIAH2, in Drosophila eye development

Abstract Seven-IN-Absentia (SINA) is the most downstream signaling gatekeeper identified thus far in the RAS/EGFR pathway that controls photoreceptor cell fate determination in Drosophila. Underscoring the central importance of SINA is its phylogenetic conservation in metazoans, with over 83% amino acid identities shared between Drosophila SINA and human SINA homologs (SIAHs). SIAH is a major tumor vulnerability in multidrug-resistant and incurable cancer. SIAH inhibition is an effective strategy to shut down the tumor-driving K-RAS/EGFR/HER2 pathway activation that promotes malignant tumor growth and metastatic dissemination. To further delineate the SINA function in the RAS/EGFR pathway, a genetic modifier screen was conducted, and 28 new sina mutant alleles were isolated via ethyl methanesulfonate (EMS) and X-ray mutagenesis. Among them, 26 of the new sina mutants are embryonic, larval, or pupal lethal, and stronger than the five published sina mutants (sina1, sina2, sina3, sina4, and sina5) which are early adult lethal. By sequencing the SINA-coding region of sinaES10, sinaES26, sinaES79, and sinaES473 homozygous mutant animals, we identified three invariable amino acid residues in SINA’s RING-domain whose single point mutation ablates SINA function. To demonstrate the functional conservation of this medically important family of RING domain E3 ligases in Drosophila, we established a collection of transgenic lines, expressing either wild type (WT) or proteolysis-deficient (PD) SINA/SIAH inhibitors of Drosophila SINAWT/PD and human SIAH1WT/PD/2WT/PD under tissue-specific GAL4-drivers in Drosophila eye, wing, and salary gland. Our results showed that Drosophila SINA and human SIAH1/2 are functionally conserved. Our bioengineered SINAPD/SIAHPD inhibitors are effective in blocking the RAS-dependent neuronal cell fate determination in Drosophila.
Low-Frequency Rotational Noise in Closed-Test-Section Wind Tunnels

The effects of closed-section wind-tunnel walls on the sound field radiated from a helicopter rotor are investigated by means of numerical simulations, summarizing the findings reported by Mosher (1986). The techniques used to model the rotor and the test section (including geometry, wall absorption, and measurement location) are outlined, and the results are presented in extensive tables and graphs. It is found that first-harmonic acoustic measurements obtained in a hard-walled wind tunnel twice as wide as the rotor diameter do not accurately represent the free-field rotational noise, that the relationship between the sound-pressure levels in the wind tunnel and in the free field is complex, that multiple near-field measurements are needed to characterize the direct acoustic field of the rotor, and that absorptive linings are of little value in enlarging the accurate-measurement zone.
Effects of the price of charitable giving: Evidence from an online crowdfunding platform

Abstract A long literature has examined the effects of the price of giving – that is, the amount an individual must give for one dollar to accrue to the charitable activity itself – on donative behavior. We use data from DonorsChoose.org, an online platform linking teachers with prospective donors that are uniquely suited to addressing this question due to exogenous variation in overhead costs. An increased price of giving results in a lower likelihood of a project being funded. We also calculate the price elasticity of giving, finding estimates between −0.8 and −2. Finally, we examine the effect of competition on giving and find that increased competition reduces the likelihood of a project being funded. These results provide insight into the workings of the market for charitable gifts.
Trace Element Indicators of Fabrication Technology for Coral Red and Black Gloss Decoration on Greek Attic Pottery

Laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICPTOFMS) was used to study the trace element chemistry of coral red and black gloss slip decoration on Greek Attic pottery (6 th century BC). The distribution of trace elements in the body fabric and glaze slips were found to be correlated suggesting the raw materials came from a single source. Furthermore, the so-called high calcium and magnesium (HCM) coral red was found to be a less refined material than black gloss, with trace element characteristics suggestive of a carbonate phase in the raw material. This carbonate component may have imparted refractory properties to the HCM coral red slip material during the three-stage oxidativereductive-oxidative firing used to produce Attic pottery, allowing it to remain porous and reoxidize during the final firing step, thus creating its final red color. The so-called low calcium and magnesium (LCM) coral red, on the other hand, was found to be more refined than the HCM coral red slip which suggests that two separate firings would have been needed to produce the red color of this material.
Production location of the gelling agent Phytagel has a significant impact on Arabidopsis thaliana seedling phenotypic analysis.

BACKGROUND Recently, it was found that 1% Phytagel plates used to conduct Arabidopsis thaliana seedling phenotypic analysis no longer reproduced previously published results. This Phytagel, which is produced in China (Phytagel C), has replace American-made Phytagel (Phytagel), which is no longer commercially available. In this study, we present the impact of Phytagel produced in the United States vs. China on seedling phenotypic analysis. As a part of this study, an alternative gelling agent has been identified that is capable of reproducing previously published seedling morphometrics. RESULTS Phytagel and Phytagel C were investigated based on their ability to reproduce the subtle phenotype of the sob3-4 esc-8 double mutant. Fluence-rate-response analysis of seedlings grown on 1% Phytagel C plates failed to replicate the sob3-4 esc-8 subtle phenotype seen on 1% Phytagel. Furthermore, root penetrance analysis showed a significant difference between sob3-4 esc-8 seedlings grown on 1% Phytagel and 1% Phytagel C. It was also found that 1% Phytagel C was significantly harder than 1% Phytagel. As a replacement for Phytagel C, Gellan was tested. 1% Gellan was able to reproduce the subtle phenotype of sob3-4 esc-8. Furthermore, there was no significant difference in root penetration of the wild type or sob3-4 esc-8 seedlings between 1% Phytagel and 1% Gellan. This may be due to the significant reduction in hardness in 1% Gellan plates compared to 1% Phytagel plates. Finally, we tested additional concentrations of Gellan and found that seedlings on 0.6% Gellan looked more uniform while also being able to reproduce previously published results. CONCLUSIONS Phytagel has been the standard gelling agent for several studies involving the characterization of subtle seedling phenotypes. After production was moved to China, Phytagel C was no longer capable of reproducing these previously published results. An alternative gelling agent, Gellan, was able to reproduce previously published seedling phenotypes at both 1% and 0.6% concentrations. The information provided in this manuscript is beneficial to the scientific community as whole, specifically phenomics labs, as it details key problematic differences between gelling agents that should be performing identically (Phytagel and Phytagel C).
Colorectal Cancer Screening

Commentary In the last few years, we have seen a surge in referrals for colonoscopy because of an increase in public and physician awareness of the need for colorectal cancer (CRC) screening. Colonoscopy has become one of the most important screening tools for CRC, because it can provide diagnosis and treatment in 1 visit. In this review, Dr Rex presents the arguments for CRC screening and offers easy-to-follow guidelines for referral to a gastroenterologist. In addition, different CRC screening modalities are presented, and a compelling argument is provided for the usage of colonoscopy as the leading screening strategy. Most importantly, the limitations of screening tools commonly used by primary care physicians are discussed. – Ronnie Fass, MD, Editor
The influence of spreading rate and permeability on melt focusing beneath mid-ocean ridges

Abstract At mid-ocean ridges, oceanic crust is emplaced in a narrow neovolcanic region on the seafloor, whereas basaltic melt that forms this oceanic crust is generated in a wide region beneath as suggested by a few geophysical surveys. The combined observations suggest that melt generated in a wide region at depths has to be transported horizontally to a small region at the surface. We present results from a suite of two-phase models applied to the mid-ocean ridges, varying half-spreading rate and intrinsic mantle permeability using new openly available models, with the goal of understanding melt focusing beneath mid-ocean ridges and its relevance to the lithosphere-asthenosphere boundary (LAB). Three distinct melt focusing mechanisms are recognized in these models: 1) melting pressure focusing, 2) decompaction layers and 3) ridge suction, of which the first two play dominant roles in focusing melt. All three of these mechanisms exist in the fundamental two phase flow formulation but the manifestation depends largely on the choice of rheological model. The models also show that regardless of spreading rates, the amount of melt and melt transport patterns are sensitive to changes in intrinsic permeability, K0. In these models, the LAB is delineated by the melt-rich decompaction layers, which are essentially defined by the temperature dependent rheological and freezing boundaries. Geophysical observations place the LAB at a steeper incline as compared to the gentler profile suggested by most of our models. The models suggest that one way to reconcile this discrepancy is to have stronger melting pressure focusing mechanism as it is the only mechanism in these models that can focus melt before reaching the typical model thermal LAB. The apparent lack of observable decompaction layers in the geophysical observations hints at the possibility that melting pressure focusing could be significant. These models help improve our understanding of melt focusing beneath mid-ocean ridges and could provide new constraints for mantle rheology and permeability.
Outcome-based pricing for new pharmaceuticals via rebates

The price of new brand-name prescription drugs has been rising fast in the United States. For example, the Amgen cholesterol drug Repatha had an initial list price of $14,523 per year. Patients, ev...
Parallel Evolution of Tobramycin Resistance across Species and Environments

Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms' genetic backgrounds and environments.IMPORTANCE The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.
Generating Interpretable Poverty Maps using Object Detection in Satellite Images

Accurate local-level poverty measurement is an essential task for governments and humanitarian organizations to track the progress towards improving livelihoods and distribute scarce resources. Recent computer vision advances in using satellite imagery to predict poverty have shown increasing accuracy, but they do not generate features that are interpretable to policymakers, inhibiting adoption by practitioners. Here we demonstrate an interpretable computational framework to accurately predict poverty at a local level by applying object detectors to high resolution (30cm) satellite images. Using the weighted counts of objects as features, we achieve 0.539 Pearson's r^2 in predicting village-level poverty in Uganda, a 31% improvement over existing (and less interpretable) benchmarks. Feature importance and ablation analysis reveal intuitive relationships between object counts and poverty predictions. Our results suggest that interpretability does not have to come at the cost of performance, at least in this important domain.
Single-View View Synthesis With Multiplane Images

A recent strand of work in view synthesis uses deep learning to generate multiplane images—a camera-centric, layered 3D representation—given two or more input images at known viewpoints. We apply this representation to single-view view synthesis, a problem which is more challenging but has potentially much wider application. Our method learns to predict a multiplane image directly from a single image input, and we introduce scale-invariant view synthesis for supervision, enabling us to train on online video. We show this approach is applicable to several different datasets, that it additionally generates reasonable depth maps, and that it learns to fill in content behind the edges of foreground objects in background layers.
The Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey.

In order to understand the impact of the COVID-19 pandemic on higher education, we surveyed approximately 1500 students at one of the largest public institutions in the United States using an instrument designed to recover the causal impact of the pandemic on students' current and expected outcomes. Results show large negative effects across many dimensions. Due to COVID-19: 13% of students have delayed graduation, 40% have lost a job, internship, or job offer, and 29% expect to earn less at age 35. Moreover, these effects have been highly heterogeneous. One quarter of students increased their study time by more than 4 hours per week due to COVID-19, while another quarter decreased their study time by more than 5 hours per week. This heterogeneity often followed existing socioeconomic divides. Lower-income students are 55% more likely than their higher-income peers to have delayed graduation due to COVID-19. Finally, we show that the economic and health related shocks induced by COVID-19 vary systematically by socioeconomic factors and constitute key mediators in explaining the large (and heterogeneous) effects of the pandemic.
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News

Social media has greatly enabled people to participate in online activities at an unprecedented rate. However, this unrestricted access also exacerbates the spread of misinformation and fake news online which might cause confusion and chaos unless being detected early for its mitigation. Given the rapidly evolving nature of news events and the limited amount of annotated data, state-of-the-art systems on fake news detection face challenges due to the lack of large numbers of annotated training instances that are hard to come by for early detection. In this work, we exploit multiple weak signals from different sources given by user and content engagements (referred to as weak social supervision), and their complementary utilities to detect fake news. We jointly leverage limited amount of clean data along with weak signals from social engagements to train deep neural networks in a meta-learning framework to estimate the quality of different weak instances. Experiments on real-world datasets demonstrate that the proposed framework outperforms state-of-the-art baselines for early detection of fake news without using any user engagements at prediction time.
ALGAMES: A Fast Solver for Constrained Dynamic Games.

Dynamic games are an effective paradigm for dealing with the control of multiple interacting actors. This paper introduces ALGAMES (Augmented Lagrangian GAME-theoretic Solver), a solver that handles trajectory optimization problems with multiple actors and general nonlinear state and input constraints. Its novelty resides in satisfying the first order optimality conditions with a quasi-Newton root-finding algorithm and rigorously enforcing constraints using an augmented Lagrangian formulation. We evaluate our solver in the context of autonomous driving on scenarios with a strong level of interactions between the vehicles. We assess the robustness of the solver using Monte Carlo simulations. It is able to reliably solve complex problems like ramp merging with three vehicles three times faster than a state-of-the-art DDP-based approach. A model predictive control (MPC) implementation of the algorithm demonstrates real-time performance on complex autonomous driving scenarios with an update frequency higher than 60 Hz.
The physics of spontaneous parity-time symmetry breaking in the Kelvin–Helmholtz instability

We show that the dynamical system of an inviscid fluid with velocity shear admits parity-time (PT) symmetry, which provides a physical explanation of the well-known observation that the spectrum of the perturbation eigenmodes of the system is symmetric with respect to the real axis. It is found that the Kelvin–Helmholtz instability is triggered when and only when the PT symmetry is spontaneously broken. The analysis of PT symmetry also reveals that the relative phase between parallel velocity and pressure perturbations needs to be locked at π/2 when the instability is suppressed.
Substorm Associated Micropulsations at Synchronous Orbit

Magnetometers carried by spacecraft in synchronous orbit show that the magnetic field is almost continuously agitated by the presence of hydromagnetic waves. A variety of waves have been identified, several of which are always associated with certain phases of magnetospheric substorms. These types include Pi 2 bursts and Pi pulsations near midnight and IPDP and mixed mode Pc4-5 waves near dusk. In this report we describe the characteristics of these waves and discuss possible directions for further work.
Pricing Joint Sales and Rentals: When are Purchase Conversion Discounts Optimal?

Product sales and rentals often occur in parallel, allowing customers to choose their preferred option. In settings where consumers face significant valuation uncertainty, rentals also provide a mechanism for consumers to discover whether they like a product. For some products, such as movies and books, the rental option may yield a significant proportion of the utility associated with ownership. The convenience of renting products in digital forms (e.g., e-books) makes the managerial challenge of jointly pricing rentals and sales increasingly relevant. Rental and sales prices are interdependent not only because consumers can choose between the two options, but also because a customer may rent before purchasing. Given these considerations and allowing for consumer uncertainty, we analyze the optimal joint pricing of product rentals and sales. We show that when consumers have a relatively high probability of liking a product and will experience a significant drop in their post-rental residual utility, then the practice of allowing a portion of the rental price to apply to a future purchase is optimal.
Split Computing for Complex Object Detectors: Challenges and Preliminary Results

Following the trends of mobile and edge computing for DNN models, an intermediate option, split computing, has been attracting attentions from the research community. Previous studies empirically showed that while mobile and edge computing often would be the best options in terms of total inference time, there are some scenarios where split computing methods can achieve shorter inference time. All the proposed split computing approaches, however, focus on image classification tasks, and most are assessed with small datasets that are far from the practical scenarios. In this paper, we discuss the challenges in developing split computing methods for powerful R-CNN object detectors trained on a large dataset, COCO 2017. We extensively analyze the object detectors in terms of layer-wise tensor size and model size, and show that naive split computing methods would not reduce inference time. To the best of our knowledge, this is the first study to inject small bottlenecks to such object detectors and unveil the potential of a split computing approach.
Dynamics and synchronization of boundary coupled FitzHugh-Nagumo neural networks

Abstract In this work a new mathematical model for complex neural networks is presented by the partly diffusive FitzHugh-Nagumo equations with ensemble boundary coupling. The dissipative dynamics and boundary coupling dynamics of solutions are proved with sharp uniform estimates. The synchronization of this kind complex neural networks is proved under the condition that boundary synaptic stimulation signal strength exceeds the threshold quantitatively expressed.
Copyright and Economic Viability: Evidence from the Music Industry

Copyright provides a long term of legal excludability, ostensibly to encourage the production of new creative works. How long this term should last, and the extent to which current law aligns with the economic incentives of copyright owners, has been the subject of vigorous theoretical debate. We investigate the economic viability of content in a major creative industry—commercial music—using a novel longitudinal dataset of weekly sales and streaming counts. We find that the typical sound recording has an extremely short commercial half-life—on the order of months, rather than years or decades—but also see evidence that subscription streaming services extend the period of economic viability. Strikingly, though, we find that decay rates are sharp even for blockbuster songs, and that the patterns persist when we approximate weekly revenue. Although our results do not provide an estimate of the causal effect of copyright on incentives, they do put bounds on the problem, and suggest a misalignment between the economic realities of the music industry and the current life-plus-seventy copyright term in the United States.
Computational p-Willmore Flow with Conformal Penalty

The unsigned p-Willmore functional introduced in the work of Mondino [2011] generalizes important geometric functionals, which measure the area and Willmore energy of immersed surfaces. Presently, techniques from the work of Dziuk [2008] are adapted to compute the first variation of this functional as a weak-form system of equations, which are subsequently used to develop a model for the p-Willmore flow of closed surfaces in R3. This model is amenable to constraints on surface area and enclosed volume and is shown to decrease the p-Willmore energy monotonically. In addition, a penalty-based regularization procedure is formulated to prevent artificial mesh degeneration along the flow; inspired by a conformality condition derived in the work of Kamberov et al. [1996], this procedure encourages angle-preservation in a closed and oriented surface immersion as it evolves. Following this, a finite-element discretization of both procedures is discussed, an algorithm for running the flow is given, and an application to mesh editing is presented.
Prediction of chlorine and fluorine crystal structures at high pressure using symmetry driven structure search with geometric constraints.

The high-pressure properties of fluorine and chlorine are not yet well understood because both are highly reactive and volatile elements, which have made conducting diamond anvil cell and x-ray diffraction experiments a challenge. Here, we use ab initio methods to search for stable crystal structures of both elements at megabar pressures. We demonstrate how symmetry and geometric constraints can be combined to efficiently generate crystal structures that are composed of diatomic molecules. Our algorithm extends the symmetry driven structure search method [R. Domingos et al., Phys. Rev. B 98, 174107 (2018)] by adding constraints for the bond length and the number of atoms in a molecule while still maintaining generality. As a method of validation, we have tested our approach for dense hydrogen and reproduced the known molecular structures of Cmca-12 and Cmca-4. We apply our algorithm to study chlorine and fluorine in the pressure range of 10 GPa–4000 GPa while considering crystal structures with up to 40 atoms per unit cell. We predict chlorine to follow the same series of phase transformations as elemental iodine from Cmca to Immm to Fm3¯m, but at substantially higher pressures. We predict fluorine to transition from a C2/c to Cmca structure at 70 GPa, to a novel orthorhombic and metallic structure with P42/mmc symmetry at 2500 GPa, and finally to its cubic analog form with Pm3¯n symmetry at 3000 GPa.
Medium amplitude parallel superposition (MAPS) rheology. Part 2: Experimental protocols and data analysis

An experimental protocol is developed to directly measure the new material functions revealed by medium amplitude parallel superposition (MAPS) rheology. This protocol measures the medium amplitude response of a material to a simple shear deformation composed of three sine waves at different frequencies, revealing a rich dataset consisting of up to 19 measurements of the third-order complex modulus at distinct three-frequency coordinates. We discuss how the choice of input frequencies influences the features of the MAPS domain studied by the experiment. A polynomial interpolation method for reducing the bias of measured values from spectral leakage and reducing variance due to noise is discussed, including a derivation of the optimal range of amplitudes for the input signal. This leads to the conclusion that conducting the experiment in a stress-controlled fashion possesses a distinct advantage to the strain-controlled mode. The experimental protocol is demonstrated through measurements of the MAPS response of a model complex fluid: a surfactant solution of wormlike micelles. The resulting dataset is indeed large and feature-rich, while still acquired in a time comparable to similar medium amplitude oscillatory shear (MAOS) experiments. We demonstrate that the data represent measurements of an intrinsic material function by studying its internal consistency, compatibility with low-frequency predictions for Coleman–Noll simple fluids, and agreement with data obtained via MAOS amplitude sweeps. Finally, the data are compared to predictions from the corotational Maxwell model to demonstrate the power of MAPS rheology in determining whether a constitutive model is consistent with a material’s time-dependent response.