cssi/SciSciGPT-SciSciNet huggingface dataset:
Association of Checklist Use in Endotracheal Intubation With Clinically Important Outcomes: A Systematic Review and Meta-analysis.

Importance Endotracheal intubation of critically ill patients is a high-risk procedure. Checklists have been advocated to improve outcomes. Objective To assess whether the available evidence supports an association of use of airway checklists with improved clinical outcomes in patients undergoing endotracheal intubation. Data Sources For this systematic review and meta-analysis, PubMed (OVID), Embase, Cochrane, CINAHL, and SCOPUS were searched without limitations using the Medical Subject Heading terms and keywordsairway;management;airway management;intubation, intratracheal;checklist; andquality improvementto identify studies published between January 1, 1960, and June 1, 2019. A supplementary search of the gray literature was performed, including conference abstracts and clinical trial registries. Study Selection Full-text reviews were performed to determine final eligibility for inclusion. Included studies were randomized clinical trials or observational human studies that compared checklist use with any comparator for endotracheal intubation and assessed 1 of the predefined outcomes. Data Extraction and Synthesis Data extraction and quality assessment were performed using the Newcastle-Ottawa Scale for observational studies and Cochrane risk of bias tool for randomized clinical trials. Study results were meta-analyzed using a random-effects model. Reporting of this study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures The primary outcome was mortality. Secondary outcomes included first-pass success and known complications of endotracheal intubation, including esophageal intubation, hypoxia, hypotension, and cardiac arrest. Results The search identified 1649 unique citations of which 11 (3261 patients) met the inclusion criteria. One randomized clinical trial and 3 observational studies had a low risk of bias. Checklist use was not associated with decreased mortality (5 studies [2095 patients]; relative risk, 0.97; 95% CI, 0.80-1.18;I2 = 0%). Checklist use was associated with a decrease in hypoxic events (8 studies [3010 patients]; relative risk, 0.75; 95% CI, 0.59-0.95;I2 = 33%) but no other secondary outcomes. Studies with a low risk of bias did not demonstrate decreased hypoxia associated with checklist use. Conclusions and Relevance The findings suggest that use of airway checklists is not associated with improved clinical outcomes during and after endotracheal intubation, which may affect practitioners’ decision to use checklists in this setting.
Search for extreme ultraviolet radiation from selected stars

Results are reported for a search for EUV radiation between 140 and 430 A from selected objects which was conducted with a rocket-borne EUV filter photometer. The candidate objects included the bright planetary nebula NGC 2392 and the stars gamma Gem, alpha CMa, omicron-prime CMa, and gamma-2 Vel. Upper limits (2-sigma level) to the flux near 200 A are determined for the five objects, and estimates of the expected 200-A helium-continuum flux are derived for two of the stars on the basis of the hot-corona model. It is found that the calculated upper limits are at least two orders of magnitude higher than plausible flux estimates based on the hot-corona model. However, it is noted that uncertainties in the flux estimates are great enough to make the upper limits useful.
c-Gluing construction and slices of quasi-Fuchsian space

Given a pants decomposition $$\mathcal {PC} = \{\sigma _1, \ldots , \sigma _{\xi }\}$$ on a hyperbolizable surface $$\Sigma $$ and a vector $${{\underline{c}}}= (c_1, \ldots , c_{\xi }) \in \mathbb {R}_+^\xi $$ , we describe a plumbing construction which endows $$\Sigma $$ with a complex projective structure for which the associated holonomy representation $$\rho $$ is quasi-Fuchsian and for which $$\ell _\rho (\sigma _i) = c_i$$ . When $${{\underline{c}}}\longrightarrow \underline{0} = (0, \ldots , 0)$$ the holonomy representation associated to this construction limits to the holonomy representation defined by Kra’s plumbing construction. In addition, when $$\Sigma = \Sigma _{1,1}$$ , the holonomy representations of these structures belong to the ‘linear slice’ of quasi-Fuchsian space $$\mathcal{{QF}}(\Sigma )$$ defined by Komori and Parkonnen. We discuss some conjectures for these slices suggested by the pictures we created in joint work with Yamashita.
Automated extraction of chemical synthesis actions from experimental procedures.

Experimental procedures for chemical synthesis are commonly reported in prose in patents or in the scientific literature. The extraction of the details necessary to reproduce and validate a synthesis in a chemical laboratory is often a tedious task requiring extensive human intervention. We present a method to convert unstructured experimental procedures written in English to structured synthetic steps (action sequences) reflecting all the operations needed to successfully conduct the corresponding chemical reactions. To achieve this, we design a set of synthesis actions with predefined properties and a deep-learning sequence to sequence model based on the transformer architecture to convert experimental procedures to action sequences. The model is pretrained on vast amounts of data generated automatically with a custom rule-based natural language processing approach and refined on manually annotated samples. Predictions on our test set result in a perfect (100%) match of the action sequence for 60.8% of sentences, a 90% match for 71.3% of sentences, and a 75% match for 82.4% of sentences. Extracting experimental operations for chemical synthesis from procedures reported in prose is a tedious task. Here the authors develop a deep-learning model based on the transformer architecture to translate experimental procedures from the field of organic chemistry into synthesis actions.
Resampling-based confidence intervals for model-free robust inference on optimal treatment regimes.

We propose a new procedure for inference on optimal treatment regimes in the model-free setting, which does not require to specify an outcome regression model. Existing model-free estimators for optimal treatment regimes are usually not suitable for the purpose of inference, because they either have nonstandard asymptotic distributions or do not necessarily guarantee consistent estimation of the parameter indexing the Bayes rule due to the use of surrogate loss. We first study a smoothed robust estimator that directly targets the parameter corresponding to the Bayes decision rule for optimal treatment regimes estimation. This estimator is shown to have an asymptotic normal distribution. Furthermore, we verify that a resampling procedure provides asymptotically accurate inference for both the parameter indexing the optimal treatment regime and the optimal value function. A new algorithm is developed to calculate the proposed estimator with substantially improved speed and stability. Numerical results demonstrate the satisfactory performance of the new methods.
Transient Safety Filter Design for Grid-Forming Inverters.

Unlike conventional generators, inverter-based generation do not possess any rotational inertia. While grid-forming inverters can synthesize small (virtual) inertia via advanced feedback control loops, additional control mechanisms are needed to ensure safety and security of the power grid during transients. In this paper, we propose novel real-time safety-constrained feedback controllers ("safety filters") for droop-based (grid-forming) inverters to ensure transient security of the grid. The safety filter acts as a buffer between the network operational layer and the inverter-control layer, and only lets those dispatch control signals pass to the inverter droop-controller, which are guaranteed to not violate the safety specifications (frequency, voltage, current limits). Using a distributed barrier certificates method, we construct state-inclusive bounds on the allowable control inputs, which guarantee the satisfaction of transient safety specifications. Sum-of-square programming is used to synthesize the safety filters. Numerical simulation results are provided to illustrate the performance of the proposed safety filter in inverter- based microgrids.
A benchmark study on time series clustering

Abstract This paper presents the first time series clustering benchmark utilizing all time series datasets currently available in the University of California Riverside (UCR) archive — the state of the art repository of time series data. Specifically, the benchmark examines eight popular clustering methods representing three categories of clustering algorithms (partitional, hierarchical and density-based) and three types of distance measures (Euclidean, dynamic time warping, and shape-based), while adhering to six restrictions on datasets and methods to make the comparison as unbiased as possible. A phased evaluation approach was then designed for summarizing dataset-level assessment metrics and discussing the results. The benchmark study presented can be a useful reference for the research community on its own; and the dataset-level assessment metrics reported may be used for designing evaluation frameworks to answer different research questions.
Bayesian hierarchical methods for modeling electrical grid component failures

Abstract This paper presents a probabilistic modeling framework for component failures in electric power grids. Failure probabilities for grid components are often estimated using parametric models informed by past observations of failure. This work formulates a Bayesian hierarchical framework designed to integrate data and domain expertise to understand the failure properties of a regional power system, where variability in the expected performance of individual components gives rise to failure processes that are heterogeneous and uncertain. We use Bayesian methods to fit failure models to failure data generated in simulation. We test our algorithm by evaluating differences between the data-generating model, our Bayesian hierarchical model, and maximum likelihood parameter estimates. We evaluate how well each model can approximate the failure properties of individual components, and of the system overall. Finally, we define an upgrade policy for achieving targeted reductions in risk exposure, and compare the magnitude of upgrades recommended by each model.
Effect of Vitamin D3 Supplementation on Severe Asthma Exacerbations in Children With Asthma and Low Vitamin D Levels: The VDKA Randomized Clinical Trial.

Importance Severe asthma exacerbations cause significant morbidity and costs. Whether vitamin D3supplementation reduces severe childhood asthma exacerbations is unclear. Objective To determine whether vitamin D3supplementation improves the time to a severe exacerbation in children with asthma and low vitamin D levels. Design, Setting, and Participants The Vitamin D to Prevent Severe Asthma Exacerbations (VDKA) Study was a randomized, double-blind, placebo-controlled clinical trial of vitamin D3supplementation to improve the time to severe exacerbations in high-risk children with asthma aged 6 to 16 years taking low-dose inhaled corticosteroids and with serum 25-hydroxyvitamin D levels less than 30 ng/mL. Participants were recruited from 7 US centers. Enrollment started in February 2016, with a goal of 400 participants; the trial was terminated early (March 2019) due to futility, and follow-up ended in September 2019. Interventions Participants were randomized to vitamin D3, 4000 IU/d (n = 96), or placebo (n = 96) for 48 weeks and maintained with fluticasone propionate, 176 μg/d (6-11 years old), or 220 μg/d (12-16 years old). Main Outcomes and Measures The primary outcome was the time to a severe asthma exacerbation. Secondary outcomes included the time to a viral-induced severe exacerbation, the proportion of participants in whom the dose of inhaled corticosteroid was reduced halfway through the trial, and the cumulative fluticasone dose during the trial. Results Among 192 randomized participants (mean age, 9.8 years; 77 girls [40%]), 180 (93.8%) completed the trial. A total of 36 participants (37.5%) in the vitamin D3group and 33 (34.4%) in the placebo group had 1 or more severe exacerbations. Compared with placebo, vitamin D3supplementation did not significantly improve the time to a severe exacerbation: the mean time to exacerbation was 240 days in the vitamin D3group vs 253 days in the placebo group (mean group difference, −13.1 days [95% CI, −42.6 to 16.4]; adjusted hazard ratio, 1.13 [95% CI, 0.69 to 1.85];P = .63). Vitamin D3supplementation, compared with placebo, likewise did not significantly improve the time to a viral-induced severe exacerbation, the proportion of participants whose dose of inhaled corticosteroid was reduced, or the cumulative fluticasone dose during the trial. Serious adverse events were similar in both groups (vitamin D3group, n = 11; placebo group, n = 9). Conclusions and Relevance Among children with persistent asthma and low vitamin D levels, vitamin D3supplementation, compared with placebo, did not significantly improve the time to a severe asthma exacerbation. The findings do not support the use of vitamin D3supplementation to prevent severe asthma exacerbations in this group of patients. Trial Registration ClinicalTrials.gov Identifier:NCT02687815
Adaptive Divergence of Meiotic Recombination Rate in Ecological Speciation.

Theories predict that directional selection during adaptation to a novel habitat results in elevated meiotic recombination rate. Yet the lack of population-level recombination rate data leaves this hypothesis untested in natural populations. Here, we examine the population-level recombination rate variation in two incipient ecological species, the microcrustacean Daphnia pulex (an ephemeral-pond species) and Daphnia pulicaria (a permanent-lake species). The divergence of D. pulicaria from D. pulex involved habitat shifts from pond to lake habitats as well as strong local adaptation due to directional selection. Using a novel single-sperm genotyping approach, we estimated the male-specific recombination rate of two linkage groups in multiple populations of each species in common garden experiments and identified a significantly elevated recombination rate in D. pulicaria. Most importantly, population genetic analyses show that the divergence in recombination rate between these two species is most likely due to divergent selection in distinct ecological habitats rather than neutral evolution.
A Resource-Aware Approach to Collaborative Loop Closure Detection with Provable Performance Guarantees

This paper presents resource-aware algorithms for distributed inter-robot loop-closure detection for applications such as collaborative simultaneous localization and mapping (CSLAM) and distributed...
Is a refugee crisis a housing crisis? Only if housing supply is unresponsive

Abstract What are the impacts of large inflows of refugees on refugee-hosting housing markets? We examine the effects of the arrival of 1.3 million Syrian refugees on the housing expenditures and income of Jordanian nationals. For this purpose, we exploit that refugees disproportionately locate around the three largest refugee camps after the beginning of the Syrian conflict in 2011. Larger refugee inflows are reflected in two main trends: higher housing expenditures of all Jordanians and increments in rental income of individuals that own real estate property. The effects are explained by the large spike in rental prices that resulted from the higher demand for housing units and the unresponsive housing supply in refugee-hosting areas.
Astrochemistry and compositions of planetary systems

Abstract Planets form and obtain their compositions in disks of gas and dust around young stars. The chemical compositions of these planet-forming disks regulate all aspects of planetary compositions from bulk elemental inventories to access to water and reactive organics, i.e. a planet’s hospitality to life and its chemical origins. Disk chemical structures are in their turn governed by a combination of in situ chemical processes, and inheritance of molecules from the preceding evolutionary stages of the star formation process. In this review we present our current understanding of the chemical processes active in pre- and protostellar environments that set the initial conditions for disks, and the disk chemical processes that evolve the chemical conditions during the first million years of planet formation. We review recent observational, laboratory and theoretical discoveries that have led to the present view of the chemical environment within which planets form, and their effects on the compositions of nascent planetary systems. We also discuss the many unknowns that remain and outline some possible pathways to addressing them.
Gravity in the Exchange Rate Factor Structure

Exchange rates strongly co-vary against their base currency. We uncover a gravity equation in this factor structure: the key determinant of a country’s exchange rate beta on the common base factor is the country’s distance from the base country. The farther the country, the larger the beta. For example, the beta of the CHF/USD exchange rate on the dollar factor is determined by the distance between Switzerland and the United States. Shared language, legal origin, shared border, resource similarity and colonial linkages also significantly lower the betas. On average, the exchange rates of peripheral countries tend to have high Rsquareds in factor regressions, while central countries have low Rsquareds. A no-arbitrage model of exchange rates replicates this distance-dependent factor structure when the exposure of pricing kernels to global risk factors is more similar for closer country pairs.
Multifaceted Substrate–Ligand Interactions Promote the Copper-Catalyzed Hydroboration of Benzylidenecyclobutanes and Related Compounds

A unified synthetic strategy to access tertiary four-membered carbo/heterocyclic boronic esters is reported. Use of a Cu(I) catalyst in combination with a modified dppbz ligand enables regioselective hydroboration of various trisubstituted benzylidenecyclobutanes and carbo/heterocyclic analogs. The reaction conditions are mild, and the method tolerates a wide range of medicinally relevant heteroarenes. The protocol can be conveniently conducted on gram-scale, and the tertiary boronic ester products undergo facile diversification into valuable targets. Reaction kinetics and computational studies indicate that the migratory insertion step is turnover-limiting and accelerated by electron-withdrawing groups on the dppbz ligand. Energy decomposition analysis (EDA) calculations reveal that electron-deficient P-aryl groups on the dppbz ligand enhance the T-shaped π/π interactions with the substrate and stabilize the migratory insertion transition state.
The IAPC’s International Auditing Guidelines and its controversial IAG 13 on the auditor’s report

This paper is a historical account of the founding, organisation and early operation of the International Auditing Practices Committee (IAPC), which was one of the committees of the International F...
Multipartite quantum correlations and local recoverability

Characterizing genuine multipartite quantum correlations in quantum physical systems has historically been a challenging problem in quantum information theory. More recently, however, the total correlation or multipartite information measure has been helpful in accomplishing this goal, especially with the multipartite symmetric quantum (MSQ) discord (Piani et al. 2008 Phys. Rev. Lett. 100, 090502. ([doi:10.1103/PhysRevLett.100.090502][1])) and the conditional entanglement of multipartite information (CEMI) (Yang et al. 2008 Phys. Rev. Lett. 101, 140501. ([doi:10.1103/PhysRevLett.101.140501][2])). Here, we apply a recent and significant improvement of strong subadditivity of quantum entropy (Fawzi & Renner 2014 ( )) in order to develop these quantities further. In particular, we prove that the MSQ discord is nearly equal to zero if and only if the multipartite state for which it is evaluated is approximately locally recoverable after performing measurements on each of its systems. Furthermore, we prove that the CEMI is a faithful entanglement measure, i.e. it vanishes if and only if the multipartite state for which it is evaluated is a fully separable state. Along the way, we provide an operational interpretation of the MSQ discord in terms of the partial state distribution protocol, which in turn, as a special case, gives an interpretation for the original discord quantity. Finally, we prove an inequality that could potentially improve upon the Fawzi–Renner inequality in the multipartite context, but it remains an open question to determine whether this is so. [1]: http://dx.doi.org/10.1103/PhysRevLett.100.090502 [2]: http://dx.doi.org/10.1103/PhysRevLett.101.140501
Refined Characterization of Student Perspectives on Quantum Physics.

The perspectives of introductory classical physics students can often negatively influence how those students later interpret quantum phenomena when taking an introductory course in modern physics. A detailed exploration of student perspectives on the interpretation of quantum physics is needed, both to characterize student understanding of physics concepts, and to inform how we might teach traditional content. Our previous investigations of student perspectives on quantum physics have indicated they can be highly nuanced, and may vary both within and across contexts. In order to better understand the contextual and often seemingly contradictory stances of students on matters of interpretation, we interviewed 19 students from four introductory modern physics courses taught at the University of Colorado. We find that students have attitudes and opinions that often parallel the stances of expert physicists when arguing for their favored interpretations of quantum mechanics, allowing for more nuanced characterizations of student perspectives in terms of three key interpretive themes. We present a framework for characterizing student perspectives on quantum mechanics, and demonstrate its utility in interpreting the sometimes contradictory nature of student responses to previous surveys. We further find that students most often vacillate in their responses when what makes intuitive sense to them is not in agreement with what they consider to be a correct response, underscoring the need to distinguish between the personal and the public perspectives of introductory modern physics students.
ARITHMETIC PROGRESSIONS ON CONIC SECTIONS

The set {1, 25, 49} is a 3-term collection of integers which forms an arithmetic progression of perfect squares. We view the set {(1, 1), (5, 25), (7, 49)} as a 3-term collection of rational points on the parabola y = x2 whose y-coordinates form an arithmetic progression. In this exposition, we provide a generalization to 3-term arithmetic progressions on arbitrary conic sections with respect to a linear rational map . We explain how this construction is related to rational points on the universal elliptic curve Y2 + 4XY + 4kY = X3 + kX2 classifying those curves possessing a rational 4-torsion point.
Fingerprinting quantum emitters in hexagonal boron nitride using strain

This paper shows a new approach for identifying defects in hexagonal boron nitride through their distinctive responses to applied strain, thereby providing a means of fingerprinting the defects responsible for quantum emission.
Structural origins of electronic conduction in amorphous copper-doped alumina

We perform an ab initio modeling of amorphous copper-doped alumina ($a\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$:Cu), a prospective memory material based on resistance switching, and study the structural origin of electronic conduction in this material. We generate molecular dynamics based models of $a\text{\ensuremath{-}}{\mathrm{Al}}_{2}{\mathrm{O}}_{3}$:Cu at various Cu concentrations and study the structural, electronic, and vibrational properties as a function of Cu concentration. Cu atoms show a strong tendency to cluster in the alumina host, and metallize the system by filling the band gap uniformly for higher Cu concentrations. We also study thermal fluctuations of the HOMO-LUMO energy splitting and observe the time evolution of the size of the band gap, which can be expected to have an important impact on the conductivity. We perform a numerical computation of conduction pathways, and show its explicit dependence on Cu connectivity in the host. We present an analysis of ion dynamics and structural aspects of localization of classical normal modes in our models.
BET on Independence

We study the problem of nonparametric dependence detection. Many existing methods may suffer severe power loss due to nonuniform consistency, which we illustrate with a paradox. To avoid such power...
Coding Theorems for Noisy Permutation Channels

In this paper, we formally define and analyze the class of noisy permutation channels. The noisy permutation channel model constitutes a standard discrete memoryless channel (DMC) followed by an independent random permutation that reorders the output codeword of the DMC. While coding theoretic aspects of this model have been studied extensively, particularly in the context of reliable communication in network settings where packets undergo transpositions, and closely related models of DNA based storage systems have also been analyzed recently, we initiate an information theoretic study of this model by defining an appropriate notion of noisy permutation channel capacity . Specifically, on the achievability front, we prove a lower bound on the noisy permutation channel capacity of any DMC in terms of the rank of the stochastic matrix of the DMC. On the converse front, we establish two upper bounds on the noisy permutation channel capacity of any DMC whose stochastic matrix is strictly positive (entry-wise). Together, these bounds yield coding theorems that characterize the noisy permutation channel capacities of every strictly positive and “full rank” DMC, and our achievability proof yields a conceptually simple, computationally efficient, and capacity achieving coding scheme for such DMCs. Furthermore, we also demonstrate the relation between the well-known output degradation preorder over channels and noisy permutation channel capacity. In fact, the proof of one of our converse bounds exploits a degradation result that constructs a symmetric channel for any DMC such that the DMC is a degraded version of the symmetric channel. Finally, we illustrate some examples such as the special cases of binary symmetric channels and (general) erasure channels. Somewhat surprisingly, our results suggest that noisy permutation channel capacities are generally quite agnostic to the parameters that define the DMCs.
ELEMENTARY EXCITATIONS DUE TO ORBITAL DEGREES OF FREEDOM IN IRON-BASED SUPERCONDUCTORS

One central issue under intense debate in the study of the iron-based superconductors is the origin of the structural phase transition that changes the crystal lattice symmetry from tetragonal to orthorhombic. This structural phase transition, occurring universally in almost every family of the iron-based superconductors, breaks the lattice C4 rotational symmetry and results in an anisotropy in a number of physical properties. Due to the unique topology of the Fermi surface, both orbital- and spin-based scenarios have been proposed as the driving force. In this review, we focus on theories from the orbital-based scenario and discuss several related experiments. It is pointed out that although both scenarios lead to the same macroscopic phases and are not distinguishable in bulk measurements of the thermodynamic properties, the elementary excitations could be fundamentally different, and provide us with the possibility to resolve this long-standing debate between orbital- and spin-based theories.
Spherically symmetric vacuum solutions arising from trace dynamics modifications to gravitation

We derive the equations governing static, spherically symmetric vacuum solutions to the Einstein equations, as modified by the frame-dependent effective action (derived from trace dynamics) that gives an alternative explanation of the origin of "dark energy". We give analytic and numerical results for the solutions of these equations, first in polar coordinates, and then in isotropic coordinates. General features of the static case are that: (i) there is no horizon, since g00 is nonvanishing for finite values of the polar radius, and only vanishes (in isotropic coordinates) at the internal singularity, (ii) the Ricci scalar R vanishes identically, and (iii) there is a physical singularity at cosmological distances. The large distance singularity may be an artifact of the static restriction, since we find that the behavior at large distances is altered in a time-dependent solution using the McVittie Ansatz.
Single-base DNA discrimination via transverse ionic transport

We suggest the discrimination of single DNA bases via transverse ionic transport, namely by detecting the ionic current that flows in a channel while a single-stranded DNA is driven through an intersecting nanochannel. Our all-atom molecular dynamics simulations indeed show that the ionic currents of the four bases are statistically distinct, thus offering another possible approach to sequencing DNA.
Reflected Light Curves, Spherical and Bond Albedos of Jupiter- and Saturn-like Exoplanets

Reflected light curves observed for exoplanets indicate that a few of them host bright clouds. We estimate how the light curve and total stellar heating of a planet depends on forward and backward scattering in the clouds based on Pioneer and Cassini spacecraft images of Jupiter and Saturn. We fit analytical functions to the local reflected brightnesses of Jupiter and Saturn depending on the planet's phase. These observations cover broadbands at 0.59–0.72 and 0.39–0.5 μm, and narrowbands at 0.938 (atmospheric window), 0.889 (CH4 absorption band), and 0.24–0.28 μm. We simulate the images of the planets with a ray-tracing model, and disk-integrate them to produce the full-orbit light curves. For Jupiter, we also fit the modeled light curves to the observed full-disk brightness. We derive spherical albedos for Jupiter and Saturn, and for planets with Lambertian and Rayleigh-scattering atmospheres. Jupiter-like atmospheres can produce light curves that are a factor of two fainter at half-phase than the Lambertian planet, given the same geometric albedo at transit. The spherical albedo is typically lower than for a Lambertian planet by up to a factor of ~1.5. The Lambertian assumption will underestimate the absorption of the stellar light and the equilibrium temperature of the planetary atmosphere. We also compare our light curves with the light curves of solid bodies: the moons Enceladus and Callisto. Their strong backscattering peak within a few degrees of opposition (secondary eclipse) can lead to an even stronger underestimate of the stellar heating.
The Chiral Puzzle of Life

Biological molecules chose one of two structurally, chiral systems which are related by reflection in a mirror. It is proposed that this choice was made, causally, by magnetically polarized and physically chiral cosmic-rays, which are known to have a large role in mutagenesis. It is shown that the cosmic rays can impose a small, but persistent, chiral bias in the rate at which they induce structural changes in simple, chiral monomers that are the building blocks of biopolymers. A much larger effect should be present with helical biopolymers, in particular, those that may have been the progenitors of RNA and DNA. It is shown that the interaction can be both electrostatic, just involving the molecular electric field, and electromagnetic, also involving a magnetic field. It is argued that this bias can lead to the emergence of a single, chiral life form over an evolutionary timescale. If this mechanism dominates, then the handedness of living systems should be universal. Experiments are proposed to assess the efficacy of this process.
A TEST OF STAR FORMATION LAWS IN DISK GALAXIES. II. DEPENDENCE ON DYNAMICAL PROPERTIES

We use the observed radial profiles of the mass surface densities of total, Σ g , and molecular, ΣH2, gas, rotation velocity, and star formation rate (SFR) surface density, Σsfr, of the molecular-rich (ΣH2 ≥ ΣHI/2) regions of 16 nearby disk galaxies to test several star formation (SF) laws: a "Kennicutt-Schmidt (K-S)" law, ; a "Constant Molecular" law, Σsfr = A H2ΣH2, 2; the turbulence-regulated laws of Krumholz & McKee (KM05) and Krumholz, McKee, & Tumlinson (KMT09); a "Gas-Ω" law, ; and a shear-driven "giant molecular cloud (GMC) Collision" law, Σsfr = B CCΣ g Ω(1-0.7β), where β ≡ d ln v circ/d ln r. If allowed one free normalization parameter for each galaxy, these laws predict the SFR with rms errors of factors of 1.4-1.8. If a single normalization parameter is used by each law for the entire galaxy sample, then rms errors range from factors of 1.5-2.1. Although the Constant Molecular law gives the smallest rms errors, the improvement over the KMT, K-S, and GMC Collision laws is not especially significant, particularly given the different observational inputs that the laws utilize and the scope of included physics, which ranges from empirical relations to detailed treatment of interstellar medium processes. We next search for systematic variation of SF law parameters with local and global galactic dynamical properties of disk shear rate (related to β), rotation speed, and presence of a bar. We demonstrate with high significance that higher shear rates enhance SF efficiency per local orbital time. Such a trend is expected if GMC collisions play an important role in SF, while an opposite trend would be expected if the development of disk gravitational instabilities is the controlling physics.
On the benefits of surrogate Lagrangians in optimal control and planning algorithms

This paper explores the relationship between numerical integrators and optimal control algorithms. Specifically, the performance of the differential dynamical programming (DDP) algorithm is examined when a variational integrator and a newly proposed surrogate variational integrator are used to propagate and linearize system dynamics. Surrogate variational integrators, derived from backward error analysis, achieve higher levels of accuracy while maintaining the same integration complexity as nominal variational integrators. The increase in the integration accuracy is shown to have a large effect on the performance of the DDP algorithm. In particular, significantly more optimized inputs are computed when the surrogate variational integrator is utilized.
HOST GALAXY PROPERTIES OF THE SUBLUMINOUS GRB 120422A/SN 2012bz*

GRB 120422A is a nearby (z = 0.283) long-duration gamma-ray burst (LGRB) detected by Swift with E {sub {gamma},iso} {approx} 4.5 Multiplication-Sign 10{sup 49} erg. It is also associated with the spectroscopically confirmed broad-lined Type Ic SN 2012bz. These properties establish GRB 120422A/SN 2012bz as the sixth and newest member of the class of subluminous GRBs supernovae (SNe). Observations also show that GRB 120422A/SN 2012bz occurred at an unusually large offset ({approx}8 kpc) from the host galaxy nucleus, setting it apart from other nearby LGRBs and leading to speculation that the host environment may have undergone prior interaction activity. Here, we present spectroscopic observations using the 6.5 m Magellan telescope at Las Campanas. We extract spectra at three specific locations within the GRB/SN host galaxy, including the host nucleus, the explosion site, and the 'bridge' of diffuse emission connecting these two regions. We measure a metallicity of log(O/H) + 12 = 8.3 {+-} 0.1 and a star formation rate (SFR) per unit area of 0.08 M {sub Sun} yr{sup -1} kpc{sup -2} at the host nucleus. At the GRB/SN explosion site we measure a comparable metallicity of log(O/H) + 12 = 8.2 {+-} 0.1 but find a much lower SFRmore » per unit area of 0.01 M {sub Sun} yr{sup -1} kpc{sup -2}. We also compare the host galaxy of this event to the hosts of other LGRBs, including samples of subluminous LGRBs and cosmological LGRBs, and find no systematic metallicity difference between the environments of these different subtypes.« less
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations

This article concerns the expressive power of depth in neural nets with ReLU activations and a bounded width. We are particularly interested in the following questions: What is the minimal width w min ( d ) so that ReLU nets of width w min ( d ) (and arbitrary depth) can approximate any continuous function on the unit cube [ 0 , 1 ] d arbitrarily well? For ReLU nets near this minimal width, what can one say about the depth necessary to approximate a given function? We obtain an essentially complete answer to these questions for convex functions. Our approach is based on the observation that, due to the convexity of the ReLU activation, ReLU nets are particularly well suited to represent convex functions. In particular, we prove that ReLU nets with width d + 1 can approximate any continuous convex function of d variables arbitrarily well. These results then give quantitative depth estimates for the rate of approximation of any continuous scalar function on the d-dimensional cube [ 0 , 1 ] d by ReLU nets with width d + 3 .
A machine learning classifier for microlensing in wide-field surveys

Abstract While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ∼ 22 mag or fainter every few days, which will contribute to the detection of black holes and exoplanets through follow-up observations of microlensing events. Based on galactic models, we can expect microlensing events across a vastly wider region of the galaxy, although the cadence of these surveys (2-3 d − 1 ) is lower than traditional microlensing surveys, making efficient detection a challenge. Rapid advances are being made in the utility of time-series data to detect and classify transient events in real-time using very high data-rate surveys, but limited work has been published regarding the detection of microlensing events, particularly for when the data streams are of relatively low-cadence. In this research, we explore the utility of a Random Forest algorithm for identifying microlensing signals using time-series data, with the goal of creating an efficient machine learning classifier that can be applied to search for microlensing in wide-field surveys even with low-cadence data. We have applied and optimized our classifier using the OGLE-II microlensing dataset, in addition to testing with PTF/iPTF survey data and the currently operating ZTF, which applies the same data handling infrastructure that is envisioned for the upcoming LSST.
CNN 101: Interactive Visual Learning for Convolutional Neural Networks

The success of deep learning solving previously-thought hard problems has inspired many non-experts to learn and understand this exciting technology. However, it is often challenging for learners to take the first steps due to the complexity of deep learning models. We present our ongoing work, CNN 101, an interactive visualization system for explaining and teaching convolutional neural networks. Through tightly integrated interactive views, CNN 101 offers both overview and detailed descriptions of how a model works. Built using modern web technologies, CNN 101 runs locally in users' web browsers without requiring specialized hardware, broadening the public's education access to modern deep learning techniques.
Combining Machine Learning and Physics to Understand Glassy Systems

Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder inherent to these systems and in part to non-equilibrium effects which are difficult to treat in the standard context of statistical physics. Together these issues have resulted in a field whose theories are under-constrained by experiment and where fundamental questions are still unresolved. Mean field results have been successful in infinite dimensions but it is unclear to what extent they apply to realistic systems and assume uniform local structure. At odds with this are theories premised on the existence of structural defects. However, until recently it has been impossible to find structural signatures that are predictive of dynamics. Here we summarize and recast the results from several recent papers offering a data driven approach to building a phenomenological theory of disordered materials by combining machine learning with physical intuition.
A complete lattice technicolor model

We construct a lattice gauge theory using reduced staggered fermions and gauge fields which provides a nonperturbative realization of a complete technicolor model; one which treats both strong and weakly coupled gauge sectors on an equal footing. We show that the model is capable of developing a Higgs phase at nonzero lattice spacing via the formation of fermion condensates. We show further that while the broken symmetry associated with this phase has a vector character in the lattice theory it is realized as an axial symmetry in the continuum limit in agreement with the Vafa–Witten theorem. We discuss our result in the context of universality.
THE NUCLEAR OUTFLOWS AND FEEDBACK IN THE SEYFERT 2 GALAXY MARKARIAN 573

We present a study of outflow and feedback in the well known Seyfert 2 galaxy Markarian 573 using high-angular resolution long-slit spectrophotometry obtained with the Hubble Space Telescope Imaging Spectrograph (STIS). Through analysis of the kinematics and ionization state of a biconical outflow region emanating from the nucleus, we find that the outflow does not significantly accelerate the surrounding host-galaxy interstellar gas and is too weak to be a strong ionization mechanism in the extended emission regions. Instead, the excitation of the extended regions is consistent with photoionization by the active nucleus. From energetics arguments, we show that the nuclear outflow is slow and heavy and has a mechanical luminosity that is only ~1% of the estimated bolometric luminosity of the system. The energy in the outflow is able to mildly shape the gas in the extended regions but appears to be insufficient to unbind it, or even to plausibly disrupt star formation. These results are at odds with the picture of strong active galactic nuclei feedback that has been invoked to explain certain aspects of galaxy evolution.
New scenarios for classical and quantum mechanical systems with position-dependent mass

An inhomogeneous Kaluza–Klein compactification to four dimensions, followed by a conformal transformation, results in a system with position-dependent mass (PDM). This origin of a PDM is quite different from the condensed matter one. A substantial generalization of a previously studied nonlinear oscillator with variable mass is obtained, wherein the position dependence of the mass of a nonrelativistic particle is due to a dilatonic coupling function emerging from the extra dimension. Previously obtained solutions for such systems can be extended and reinterpreted as nonrelativistic particles interacting with dilaton fields, which, themselves, can have interesting structures. An application is presented for the nonlinear oscillator, where within the new scenario the particle is coupled to a dilatonic string.
Effects of Temperature and Near Ultraviolet Light on Current-Voltage Characteristics of Colemanite

ABSTRACTWe investigate current-voltage (I-V) characteristics of colemanite (Ca2B6O11.5H2O) at room temperature, at a high temperature of 400°F and under the influence of near ultraviolet light. We ...
Quasiminimal abstract elementary classes

We propose the notion of a quasiminimal abstract elementary class (AEC). This is an AEC satisfying four semantic conditions: countable Lowenheim–Skolem–Tarski number, existence of a prime model, closure under intersections, and uniqueness of the generic orbital type over every countable model. We exhibit a correspondence between Zilber’s quasiminimal pregeometry classes and quasiminimal AECs: any quasiminimal pregeometry class induces a quasiminimal AEC (this was known), and for any quasiminimal AEC there is a natural functorial expansion that induces a quasiminimal pregeometry class. We show in particular that the exchange axiom is redundant in Zilber’s definition of a quasiminimal pregeometry class.
Convergence of invariant densities in the small-noise limit

Let ρ0 be an invariant probability density of a deterministic dynamical system f and ρ the invariant probability density of a random perturbation of f by additive noise of amplitude . Suppose ρ0 is stochastically stable in the sense that ρ → ρ0 as → 0. Through a systematic numerical study of concrete examples, I show that: The rate of convergence of ρ to ρ0 as → 0 is frequently governed by power laws: ||ρ − ρ0||1 ~ γ for some γ > 0. When the deterministic system f exhibits exponential decay of correlations, a simple heuristic can correctly predict the exponent γ based on the structure of ρ0. The heuristic fails for systems with some 'intermittency', i.e. systems which do not exhibit exponential decay of correlations. For these examples, the convergence of ρ to ρ0 as → 0 continues to be governed by power laws but the heuristic provides only an upper bound on the power law exponent γ. Furthermore, this numerical study requires the computation of ||ρ − ρ0||1 for 1.5–2.5 decades of and provides an opportunity to discuss and compare standard numerical methods for computing invariant probability densities in some depth.
Lattice simulations for few- and many-body systems

Abstract We review the recent literature on lattice simulations for few- and many-body systems. We focus on methods that combine the framework of effective field theory with computational lattice methods. Lattice effective field theory is discussed for cold atoms as well as low-energy nucleons with and without pions. A number of different lattice formulations and computational algorithms are considered, and an effort is made to show common themes in studies of cold atoms and low-energy nuclear physics as well as common themes in work by different collaborations.
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making

ML decision-aid systems are increasingly common on the web, but their successful integration relies on people trusting them appropriately: they should use the system to fill in gaps in their ability, but recognize signals that the system might be incorrect. We measured how people’s trust in ML recommendations differs by expertise and with more system information through a task-based study of 175 adults. We used two tasks that are difficult for humans: comparing large crowd sizes and identifying similar-looking animals. Our results provide three key insights: (1) People trust incorrect ML recommendations for tasks that they perform correctly the majority of the time, even if they have high prior knowledge about ML or are given information indicating the system is not confident in its prediction; (2) Four different types of system information all increased people’s trust in recommendations; and (3) Math and logic skills may be as important as ML for decision-makers working with ML recommendations.