cssi/SciSciGPT-SciSciNet huggingface dataset:
The synthetically produced predator odor 2,5-dihydro-2,4,5-trimethylthiazoline increases alcohol self-administration and alters basolateral amygdala response to alcohol in rats

Post-traumatic stress disorder (PTSD) is a psychiatric illness that can increase the risk for developing an alcohol use disorder (AUD). While clinical data has been useful in identifying similarities in the neurobiological bases of these disorders, preclinical models are essential for understanding the mechanism(s) by which stressors increase the risk for escalated alcohol consumption. The purpose of these studies was to examine if exposure of male Long-Evans rats to the synthetically derived predator odor 2,5-dihydro-2,4,5-trimethylthiazoline (TMT; a component of fox feces) would increase sweetened alcohol self-administration, potentially by facilitating transfer of salience towards cues, and alter neuronal response to alcohol as measured by the immediate early gene c-Fos. In experiment 1, rats exposed to repeated (4×) TMT showed reductions in port entries in Pavlovian conditioned approach and increases in sweetened alcohol self-administration. In experiment 2, rats exposed to repeated TMT showed blunted basolateral amygdala c-Fos response to alcohol. In experiment 3, rats exposed to single, but not repeated TMT, showed increases in sweetened alcohol self-administration, and no change in anxiety-like behavior or hyperarousal. In experiment 4, rats continued to show a significant corticosterone response to TMT after repeated exposures. In summary, exposure of male rats to TMT can cause escalations in sweetened alcohol self-administration and reduction in BLA response to alcohol. These studies outline and utilize a novel preclinical model that can be used to further neurobiological understanding of the emergence of escalated alcohol consumption following stress exposure.
Developmental influences on symptom expression in antipsychotic-naïve first-episode psychosis.

Background The neurodevelopmental model of psychosis was established over 30 years ago; however, the developmental influence on psychotic symptom expression - how age affects clinical presentation in first-episode psychosis - has not been thoroughly investigated. Methods Using generalized additive modeling, which allows for linear and non-linear functional forms of age-related change, we leveraged symptom data from a large sample of antipsychotic-naive individuals with first-episode psychosis (N = 340, 12-40 years, 1-12 visits), collected at the University of Pittsburgh from 1990 to 2017. We examined relationships between age and severity of perceptual and non-perceptual positive symptoms and negative symptoms. We tested for age-associated effects on change in positive or negative symptom severity following baseline assessment and explored the time-varying relationship between perceptual and non-perceptual positive symptoms across adolescent development. Results Perceptual positive symptom severity significantly decreased with increasing age (F = 7.0, p = 0.0007; q = 0.003) while non-perceptual positive symptom severity increased with age (F = 4.1, p = 0.01, q = 0.02). Anhedonia severity increased with increasing age (F = 6.7, p = 0.00035; q = 0.0003), while flat affect decreased in severity with increased age (F = 9.8, p = 0.002; q = 0.006). Findings remained significant when parental SES, IQ, and illness duration were included as covariates. There were no developmental effects on change in positive or negative symptom severity (all p > 0.25). Beginning at age 18, there was a statistically significant association between severity of non-perceptual and perceptual symptoms. This relationship increased in strength throughout adulthood. Conclusions These findings suggest that as maturation proceeds, perceptual symptoms attenuate while non-perceptual symptoms are enhanced. Findings underscore how pathological brain-behavior relationships vary as a function of development.
Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections

Motivated by the need for simulation tools for testing, verification and validation of autonomous driving systems that operate in traffic consisting of both autonomous and human-driven vehicles, we propose a game-theoretic framework for modeling the interactive behavior of vehicles at uncontrolled intersections. The proposed vehicle interaction model is based on a novel formulation of dynamic games with multiple concurrent leader-follower pairs, induced from common traffic rules. Based on simulation results for various intersection scenarios, we show that the model exhibits reasonable behavior expected in traffic, including the capability of reproducing scenarios extracted from real-world traffic data and reasonable performance in resolving traffic conflicts. The model is further validated based on the level-of-service traffic quality rating system and demonstrates manageable computational complexity compared to traditional multi-player game-theoretic models.
Markov chain Monte Carlo with neural network surrogates: application to contaminant source identification

Subsurface remediation often involves reconstruction of contaminant release history from sparse observations of solute concentration. Markov Chain Monte Carlo (MCMC), the most accurate and general method for this task, is rarely used in practice because of its high computational cost associated with multiple solves of contaminant transport equations. We propose an adaptive MCMC method, in which a transport model is replaced with a fast and accurate surrogate model in the form of a deep convolutional neural network (CNN). The CNN-based surrogate is trained on a small number of the transport model runs based on the prior knowledge of the unknown release history. Thus reduced computational cost allows one to diminish the sampling error associated with construction of the approximate likelihood function. As all MCMC strategies for source identification, our method has an added advantage of quantifying predictive uncertainty and accounting for measurement errors. Our numerical experiments demonstrate the accuracy comparable to that of MCMC with the forward transport model, which is obtained at a fraction of the computational cost of the latter.
Quandle Module Quivers

We enhance the quandle coloring quiver invariant of oriented knots and links with quandle modules. This results in a two-variable polynomial invariant which specializes to the previous quandle modu...
Learning to Rank in the Position Based Model with Bandit Feedback

Personalization is a crucial aspect of many online experiences. In particular, content ranking is often a key component in delivering sophisticated personalization results. Commonly, supervised learning-to-rank methods are applied, which suffer from bias introduced during data collection by production systems in charge of producing the ranking. To compensate for this problem, we leverage contextual multi-armed bandits. We propose novel extensions of two well-known algorithms viz. LinUCB and Linear Thompson Sampling to the ranking use-case. To account for the biases in a production environment, we employ the position-based click model. Finally, we show the validity of the proposed algorithms by conducting extensive offline experiments on synthetic datasets as well as customer facing online A/B experiments.
Gaussian variant of Freivalds’ algorithm for efficient and reliable matrix product verification

In this article, we consider the general problem of checking the correctness of matrix multiplication. Given three $n \times n$ matrices $A$, $B$, and $C$, the goal is to verify that $A \times B=C$ without carrying out the computationally costly operations of matrix multiplication and comparing the product $A \times B$ with $C$, term by term. This is especially important when some or all of these matrices are very large, and when the computing environment is prone to soft errors. Here we extend Freivalds' algorithm to a Gaussian Variant of Freivalds' Algorithm (GVFA) by projecting the product $A \times B$ as well as $C$ onto a Gaussian random vector and then comparing the resulting vectors. The computational complexity of GVFA is consistent with that of Freivalds' algorithm, which is $O(n^{2})$. However, unlike Freivalds' algorithm, whose probability of a false positive is $2^{-k}$, where $k$ is the number of iterations. Our theoretical analysis shows that when $A \times B \neq C$, GVFA produces a false positive on set of inputs of measure zero with exact arithmetic. When we introduce round-off error and floating point arithmetic into our analysis, we can show that the larger this error, the higher the probability that GVFA avoids false positives. Moreover, by iterating GVFA $k$ times, the probability of a false positive decreases as $p^k$, where $p$ is a very small value depending on the nature of the fault on the result matrix and the arithmetic system's floating-point precision. Unlike deterministic algorithms, there do not exist any fault patterns that are completely undetectable with GVFA. Thus GVFA can be used to provide efficient fault tolerance in numerical linear algebra, and it can be efficiently implemented on modern computing architectures. In particular, GVFA can be very efficiently implemented on architectures with hardware support for fused multiply-add operations.
Can You Read Me Now? Content Aware Rectification using Angle Supervision

The ubiquity of smartphone cameras has led to more and more documents being captured by cameras rather than scanned. Unlike flatbed scanners, photographed documents are often folded and crumpled, resulting in large local variance in text structure. The problem of document rectification is fundamental to the Optical Character Recognition (OCR) process on documents, and its ability to overcome geometric distortions significantly affects recognition accuracy. Despite the great progress in recent OCR systems, most still rely on a pre-process that ensures the text lines are straight and axis aligned. Recent works have tackled the problem of rectifying document images taken in-the-wild using various supervision signals and alignment means. However, they focused on global features that can be extracted from the document’s boundaries, ignoring various signals that could be obtained from the document’s content.
Business education as if people and the planet really matter

Mounting concern over capitalism’s inability to address systemic challenges in our natural world (i.e. climate change) and social world (i.e. income inequality) is prompting reexamination of capita...
Extensive or Intensive Generosity? The Price and Income Effects of Federal Grants

Knowing the responsiveness of state spending to federal subsidies along different dimensions allows for the optimal design of joint federal-state programs. Welfare is an important case in point: states have the ability to choose both the extent of welfare eligibility and the intensity of benefits provided through the program. This paper estimates the sensitivity of state spending to separate federal subsidies for increasing benefits and for increasing recipients. Because the federal match rate schedule changed several times during the early years that I study, I am able to estimate elasticities in a way that is not biased by the endogenous relationship between income, spending, and federal contributions. I find that state behavior is quite sensitive to these federal subsidies (and much more sensitive than a simple OLS regression would imply). A 10% increase in the cost of benefits causes a 3.8% decrease in benefit amounts, whereas a 10% increase in the cost of recipients causes a 2.8% decrease in the numb...
A Deep Search for Additional Satellites around the Dwarf Planet Haumea

Haumea is a dwarf planet with two known satellites, an unusually high spin rate, and a large collisional family, making it one of the most interesting objects in the outer solar system. A fully self-consistent formation scenario responsible for the satellite and family formation is still elusive, but some processes predict the initial formation of many small moons, similar to the small moons recently discovered around Pluto. Deep searches for regular satellites around Kuiper belt objects are difficult due to observational limitations, but Haumea is one of the few for which sufficient data exist. We analyze Hubble Space Telescope (HST) observations, focusing on a 10-consecutive-orbit sequence obtained in 2010 July, to search for new very small satellites. To maximize the search depth, we implement and validate a nonlinear shift-and-stack method. No additional satellites of Haumea are found, but by implanting and recovering artificial sources, we characterize our sensitivity. At distances between ~10,000 and ~350,000 km from Haumea, satellites with radii as small as ~10 km are ruled out, assuming an albedo (p ≃ 0.7) similar to Haumea. We also rule out satellites larger than ≳40 km in most of the Hill sphere using other HST data. This search method rules out objects similar in size to the small moons of Pluto. By developing clear criteria for determining the number of nonlinear rates to use, we find that far fewer shift rates are required (~35) than might be expected. The nonlinear shift-and-stack method to discover satellites (and other moving transients) is tractable, particularly in the regime where nonlinear motion begins to manifest itself.
Dark tridents at off-axis liquid argon neutrino detectors

We present dark tridents, a new channel for exploring dark sectors in short-baseline neutrino experiments. Dark tridents are clean, distinct events where, like neutrino tridents, the scattering of a very weakly coupled particle leads to the production of a lepton-antilepton pair. Dark trident production occurs in models where long-lived dark-sector particles are produced along with the neutrinos in a beam-dump environment and interact with neutrino detectors downstream, producing an on-shell boson which decays into a pair of charged leptons. We focus on a simple model where the dark matter particle interacts with the standard model exclusively through a dark photon, and concentrate on the region of parameter space where the dark photon mass is smaller than twice that of the dark matter particle and hence decays exclusively into standard-model particles. We compute event rates and discuss search strategies for dark tridents from dark matter at the current and upcoming liquid argon detectors aligned with the Booster beam at Fermilab — MicroBooNE, SBND, and ICARUS — assuming the dark sector particles are produced off-axis in the higher energy NuMI beam. We find that MicroBooNE has already recorded enough data to be competitive with existing bounds on this dark sector model, and that new regions of parameter space will be probed with future data and experiments.
Stable operations and cooperations in derived Witt theory with rational coefficients

The algebras of stable operations and cooperations in derived Witt theory with rational coefficients are computed and an additive description of cooperations in derived Witt theory is given. The answer is parallel to the well-known case of K-theory of real vector bundles in topology. In particular, we show that stable operations in derived Witt theory with rational coefficients are given by the values on the powers of Bott element.
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications

Density Estimation is one of the central areas of statistics whose purpose is to estimate the probability density function underlying the observed data. It serves as a building block for many tasks in statistical inference, visualization, and machine learning. Density Estimation is widely adopted in the domain of unsupervised learning especially for the application of clustering. As big data become pervasive in almost every area of data sciences, analyzing high-dimensional data that have many features and variables appears to be a major focus in both academia and industry. High-dimensional data pose challenges not only from the theoretical aspects of statistical inference, but also from the algorithmic/computational considerations of machine learning and data analytics. This paper reviews a collection of selected nonparametric density estimation algorithms for high-dimensional data, some of them are recently published and provide interesting mathematical insights. The important application domain of nonparametric density estimation, such as { modal clustering}, are also included in this paper. Several research directions related to density estimation and high-dimensional data analysis are suggested by the authors.
A field theory approach to the evolution of canonical helicity and energy

A redefinition of the Lagrangian of a multi-particle system in fields reformulates the single-particle, kinetic, and fluid equations governing fluid and plasma dynamics as a single set of generalized Maxwell's equations and Ohm's law for canonical force-fields. The Lagrangian includes new terms representing the coupling between the motion of particle distributions, between distributions and electromagnetic fields, with relativistic contributions. The formulation shows that the concepts of self-organization and canonical helicity transport are applicable across single-particle, kinetic, and fluid regimes, at classical and relativistic scales. The theory gives the basis for comparing canonical helicity change to energy change in general systems. For example, in a fixed, isolated system subject to non-conservative forces, a species' canonical helicity changes less than total energy only if gradients in density or distribution function are shallow.
Shear dispersion in dense granular flows

We formulate and solve a model problem of dispersion of dense granular materials in rapid shear flow down an incline. The effective dispersivity of the depth-averaged concentration of the dispersing powder is shown to vary as the Peclet number squared, as in classical Taylor–Aris dispersion of molecular solutes. An extension to generic shear profiles is presented, and possible applications to industrial and geological granular flows are noted.
Effect of metallicity on low mass X-ray binaries in globular clusters

We propose that the observed difference in the formation rates of bright low-mass X-ray binaries in metal-rich and metal-poor globular clusters can be explained by taking into account the difference in the stellar structure of main sequence donors with masses between ~0.85 Msun and ~1.25 Msun at different metallicities. This difference is caused by the absence of an outer convective zone in metal-poor main sequence stars in this mass range. In the result, magnetic braking, a powerful mechanism of orbital shrinkage, does not operate and dynamically formed main sequence - neutron star binaries fail to start mass transfer or appear as bright low-mass X-ray binaries.
Simulations of Recoiling Massive Black Holes in the Via Lactea Halo

The coalescence of a massive black hole (MBH) binary leads to the gravitational-wave recoil of the system and its ejection from the galaxy core. We have carried out N-body simulations of the motion of a M{sub BH} = 3.7 x 10{sup 6} M{sub sun} MBH remnant in the 'Via Lactea I' simulation, a Milky Way-sized dark matter halo. The black hole receives a recoil velocity of V{sub kick} = 80, 120, 200, 300, and 400 km s{sup -1} at redshift 1.5, and its orbit is followed for over 1 Gyr within a 'live' host halo, subject only to gravity and dynamical friction against the dark matter background. We show that, owing to asphericities in the dark matter potential, the orbit of the MBH is highly nonradial, resulting in a significantly increased decay timescale compared to a spherical halo. The simulations are used to construct a semi-analytic model of the motion of the MBH in a time-varying triaxial Navarro-Frenk-White dark matter halo plus a spherical stellar bulge, where the dynamical friction force is calculated directly from the velocity dispersion tensor. Such a model should offer a realistic picture of the dynamics of kicked MBHs in situations where gas drag, friction bymore » disk stars, and the flattening of the central cusp by the returning black hole are all negligible effects. We find that MBHs ejected with initial recoil velocities V{sub kick} {approx}> 500 km s{sup -1} do not return to the host center within a Hubble time. In a Milky Way-sized galaxy, a recoiling hole carrying a gaseous disk of initial mass {approx}M{sub BH} may shine as a quasar for a substantial fraction of its 'wandering' phase. The long decay timescales of kicked MBHs predicted by this study may thus be favorable to the detection of off-nuclear quasar activity.« less
Sideways adiabaticity: beyond ray optics for slowly varying metasurfaces

Optical metasurfaces (subwavelength-patterned surfaces typically described by variable effective surface impedances) are typically modeled by an approximation akin to ray optics: the reflection or transmission of an incident wave at each point of the surface is computed as if the surface were “locally uniform,” and then the total field is obtained by summing all of these local scattered fields via a Huygens principle. (Similar approximations are found in scalar diffraction theory and in ray optics for curved surfaces.) In this paper, we develop a precise theory of such approximations for variable-impedance surfaces. Not only do we obtain a type of adiabatic theorem showing that the “zeroth-order” locally uniform approximation converges in the limit as the surface varies more and more slowly, including a way to quantify the rate of convergence, but we also obtain an infinite series of higher-order corrections. These corrections, which can be computed to any desired order by performing integral operations on the surface fields, allow rapidly varying surfaces to be modeled with arbitrary accuracy, and also allow one to validate designs based on the zeroth-order approximation (which is often surprisingly accurate) without resorting to expensive brute-force Maxwell solvers. We show that our formulation works arbitrarily close to the surface, and can even compute coupling to guided modes, whereas in the far-field limit our zeroth-order result simplifies to an expression similar to what has been used by other authors.
Light-ray operators in conformal field theory

We argue that every CFT contains light-ray operators labeled by a continuous spin J. When J is a positive integer, light-ray operators become integrals of local operators over a null line. However for non-integer J , light-ray operators are genuinely nonlocal and give the analytic continuation of CFT data in spin described by Caron-Huot. A key role in our construction is played by a novel set of intrinsically Lorentzian integral transforms that generalize the shadow transform. Matrix elements of light-ray operators can be computed via the integral of a double-commutator against a conformal block. This gives a simple derivation of Caron-Huot’s Lorentzian OPE inversion formula and lets us generalize it to arbitrary four-point functions. Furthermore, we show that light-ray operators enter the Regge limit of CFT correlators, and generalize conformal Regge theory to arbitrary four-point functions. The average null energy operator is an important example of a light-ray operator. Using our construction, we find a new proof of the average null energy condition (ANEC), and furthermore generalize the ANEC to continuous spin.
ON THE MERTENS CONJECTURE FOR ELLIPTIC CURVES OVER FINITE FIELDS

We introduce an analogue of the Mertens conjecture for elliptic curves over finite fields. Using a result of Waterhouse, we classify the isogeny classes of elliptic curves for which this conjecture holds in terms of the size of the finite field and the trace of the Frobenius endomorphism acting on the curve.
FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality

FlightGoggles is a photorealistic sensor simulator for perception-driven robotic vehicles. The key contributions of FlightGoggles are twofold. First, FlightGoggles provides photorealistic exteroceptive sensor simulation using graphics assets generated with photogrammetry. Second, it provides the ability to combine (i) synthetic exteroceptive measurements generated in silico in real time and (ii) vehicle dynamics and proprioceptive measurements generated in motio by vehicle(s) in flight in a motion-capture facility. FlightGoggles is capable of simulating a virtual-reality environment around autonomous vehicle(s) in flight. While a vehicle is in flight in the Flight-Goggles virtual reality environment, exteroceptive sensors are rendered synthetically in real time while all complex dynamics are generated organically through natural interactions of the vehicle. The FlightGoggles framework allows for researchers to accelerate development by circumventing the need to estimate complex and hard-to-model interactions such as aerodynamics, motor mechanics, battery electrochemistry, and behavior of other agents. The ability to perform vehicle-in-the-loop experiments with photorealistic exteroceptive sensor simulation facilitates novel research directions involving, e.g., fast and agile autonomous flight in obstacle-rich environments, safe human interaction, and flexible sensor selection. FlightGoggles has been utilized as the main test for selecting nine teams that will advance in the AlphaPilot autonomous drone racing challenge. We survey approaches and results from the top AlphaPilot teams, which may be of independent interest. FlightGoggles is distributed as open-source software along with the photorealistic graphics assets for several simulation environments, under the MIT license at http://flightgoggles.mit.edu.
Deeper Text Understanding for IR with Contextual Neural Language Modeling

Neural networks provide new possibilities to automatically learn complex language patterns and query-document relations. Neural IR models have achieved promising results in learning query-document relevance patterns, but few explorations have been done on understanding the text content of a query or a document. This paper studies leveraging a recently-proposed contextual neural language model, BERT, to provide deeper text understanding for IR. Experimental results demonstrate that the contextual text representations from BERT are more effective than traditional word embeddings. Compared to bag-of-words retrieval models, the contextual language model can better leverage language structures, bringing large improvements on queries written in natural languages. Combining the text understanding ability with search knowledge leads to an enhanced pre-trained BERT model that can benefit related search tasks where training data are limited.
Symmetries, charges and conservation laws at causal diamonds in general relativity

We study the covariant phase space of vacuum general relativity at the null boundary of causal diamonds. The past and future components of such a null boundary each have an infinite-dimensional symmetry algebra consisting of diffeomorphisms of the 2-sphere and boost supertranslations corresponding to angle-dependent rescalings of affine parameter along the null generators. Associated to these symmetries are charges and fluxes obtained from the covariant phase space formalism using the prescription of Wald and Zoupas. By analyzing the behavior of the spacetime metric near the corners of the causal diamond, we show that the fluxes are also Hamiltonian generators of the symmetries on phase space. In particular, the supertranslation fluxes yield an infinite family of boost Hamiltonians acting on the gravitational data of causal diamonds. We show that the smoothness of the vector fields representing such symmetries at the bifurcation edge of the causal diamond implies suitable matching conditions between the symmetries on the past and future components of the null boundary. Similarly, the smoothness of the spacetime metric implies that the fluxes of all such symmetries are conserved between the past and future components of the null boundary. This establishes an infinite set of conservation laws for finite subregions in gravity analogous to those at null infinity. We also show that the symmetry algebra at the causal diamond has a non-trivial center corresponding to constant boosts. The central charges associated to these constant boosts are proportional to the area of the bifurcation edge, for any causal diamond, in analogy with the Wald entropy formula.
Massive spinning bosons on the celestial sphere

A natural extension of the Pasterski-Shao-Strominger (PSS) prescription is described, enabling the map of Minkowski space amplitudes with massive spinning external legs to the celestial sphere to be performed. An integral representation for the conformal primary wave function (CPW) of massive spinning bosons on the celestial sphere is derived explicitly for spin-one and -two. By analogy with the spin-zero case, the spinning bulk-to-boundary propagator on Euclidean AdS is employed to extend the massive CPW integral representation to arbitrary integer spin, and to describe the appropriate inverse transform of massive spinning CPWs back to the plane wave basis in Minkowski space. Subsequently, a massive spin-s momentum operator representation on the celestial sphere is determined, and used in conjunction with known Lorentz generators to derive Poincare symmetry constraints on generic massive spinning two-, three- and four-point celestial amplitude structures. Finally, as a consistency check, three-point Minkowski space amplitudes of two massless scalars and a spin-one or -two massive boson are explicitly mapped to the celestial sphere, and the resulting three-point function coefficients are confirmed to be in exact agreement with the results obtained from Poincare symmetry constraints.
Accurate Empirical Radii and Masses of Planets and Their Host Stars with Gaia Parallaxes

We present empirical measurements of the radii of 116 stars that host transiting planets. These radii are determined using only direct observables-the bolometric flux at Earth, the effective temperature, and the parallax provided by the Gaia first data release-and thus are virtually model independent, extinction being the only free parameter. We also determine each star's mass using our newly determined radius and the stellar density, itself a virtually model independent quantity from previously published transit analyses. These stellar radii and masses are in turn used to redetermine the transiting planet radii and masses, again using only direct observables. The median uncertainties on the stellar radii and masses are ~8% and ~30%, respectively, and the resulting uncertainties on the planet radii and masses are ~9% and ~22%, respectively. These accuracies are generally larger than previously published model-dependent precisions of ~5% and ~6% on the planet radii and masses, respectively, but the newly determined values are purely empirical. We additionally report radii for 242 stars hosting radial-velocity (non-transiting) planets, with median achieved accuracy of ~2%. Using our empirical stellar masses we verify that the majority of putative "retired A stars" in the sample are indeed more massive than ~1.2 Msun. Most importantly, the bolometric fluxes and angular radii reported here for a total of 498 planet host stars-with median accuracies of 1.7% and 1.8%, respectively-serve as a fundamental dataset to permit the re-determination of transiting planet radii and masses with the Gaia second data release to ~3% and ~5% accuracy, better than currently published precisions, and determined in an entirely empirical fashion.
Split-gate device for indirect excitons

We present a concept and experimental proof of principle for split-gate devices for indirect excitons (IXs). The split-gate forms a narrow channel, a point contact, for IX current. Control of IX flow through the split-gate with both gate voltage and excitation power is demonstrated.
Calculation of atom-centered partial charges for heme

Atom-centered partial charges are calculated for the Fe-heme in cytochrome P450cam for use in molecular dynamics simulations of polar substrates bound in the active site of the enzyme. Charges are fit to the electrostatic potential produced by ab initio UHF wavefunctions for an Fe-porphine model. Basis set dependence of these charges is observed using the LANL1DZ, LANL2DZ and augmented 6–31G levels of theory. Upon geometry optimization of the enzyme, these charge sets cause varying degrees of distortion of the porphyrin from its crystallographically observed conformation. Scaling the charges calculated from the augmented 6–31G basis by 75% reduces the heme distortion while preserving reasonable interactions with a polar substrate. A comparison of the calculated charges with other published values is presented.
Near-IR Spectroscopic Monitoring of Class I Protostars: Variability of Accretion and Wind Indicators

We present the results of a program that monitored the near-IR spectroscopic variability of a sample of 19 embedded protostars. Spectra were taken on time intervals from 2 days to 3 yr, over a wavelength range from 0.85 μm to 2.45 μm, for 4-9 epochs of observations per target. We found that the spectra of all targets are variable and that every emission feature observed is also variable (although not for all targets). With one exception, there were no drastic changes in the continua of the spectra, nor did any line completely disappear, nor did any line appear that was not previously apparent. This analysis focuses on understanding the connection between accretion (traced by H Br γ and CO) and the wind (traced by He I, [Fe II], and sometimes H2). For both accretion and wind tracers, the median variability was constant versus the time interval between observations; however, the maximum variability that we observed increased with the time interval between observations. Extinction is observed to vary within the minimum sampling time of 2 days, suggesting extinguishing material within a few stellar radii at high disk latitudes. The variability of [Fe II] and H2 were correlated for most (but not all) of the 7 young stellar objects showing both features, and the amplitude of the variability depends on the veiling. Although the occurrence of CO and Br γ emission are connected, their variability is uncorrelated, suggesting that these emissions originate in separate regions near the protostar (e.g., disk and wind). The variability of Br γ and wind tracers were found to be positively correlated, negatively correlated, or uncorrelated, depending on the target. The variability of Br γ, [Fe II], and H2 always lies on a plane, although the orientation of the plane in three dimensions depends on the target. While we do not understand all interactions behind the variability that we observed, we have shown that spectroscopic variability is a powerful tool toward understanding the star formation process.
A mirror theorem for the mirror quintic

The celebrated Mirror theorem states that the genus zero part of the A model (quantum cohomology, rational curves counting) of the Fermat quintic threefold is equivalent to the B model (complex deformation, variation of Hodge structure) of its mirror dual orbifold. In this article, we establish a mirror-dual statement. Namely, the B model of the Fermat quintic threefold is shown to be equivalent to the A model of its mirror, and hence establishes the mirror symmetry as a true duality. 14N35; 53D45
Distributed flow optimization and cascading effects in weighted complex networks

We investigate the effect of a specific edge weighting scheme ~(kikj)β on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter β and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we explore the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter β, we find that network resilience to cascading overloads and network throughput is optimal for the same value of β over the range of node capacities and available bandwidth.
“Slow” and Fast Rotators among Hypervelocity Stars*

We measure the projected rotational velocities of the late B-type hypervelocity stars HVS 7 and HVS 8 from high-resolution spectroscopy to be 60 ± 17 km s−1 and 260 ± 70 km s−1. The "slow" rotation of HVS 7 is in principle consistent with having originated in a binary system, assuming a high inclination angle of the stellar rotation axis. However, the fast rotation of HVS 8 is more typical of single B-type stars. HVS 8 could have therefore been ejected by a mechanism other than that proposed by Hills. We also estimate the effective temperatures and surface gravities for HVS 7 and HVS 8 and obtain an additional measurement of their radial velocities. We find evidence in support of a blue horizontal branch nature for HVS 7 and a main-sequence nature for HVS 8.
IONIC BINDING IN A SUSY BACKGROUND

From string theory and the observation of a positive vacuum energy in our universe it seems inevitable that there will eventually be a phase transition to an exactly supersymmetric (susy) universe. In this phase there will be an effective weakening of the Pauli principle due to Fermi–Bose degeneracy. As a consequence molecular binding will be significantly affected. We make some general comments on susy molecules and perform a variational principle estimate of ionic binding energies.
Conditioning moments of singular measures for entropy optimization. I

Abstract In order to process a potential moment sequence by the entropy optimization method one has to be assured that the original measure is absolutely continuous with respect to Lebesgue measure. We propose a non-linear exponential transform of the moment sequence of any measure, including singular ones, so that the entropy optimization method can still be used in the reconstruction or approximation of the original. The Cauchy transform in one variable, used for this very purpose in a classical context by A.A. Markov and followers, is replaced in higher dimensions by the Fantappie transform. Several algorithms for reconstruction from moments are sketched, while we intend to provide the numerical experiments and computational aspects in a subsequent article. The essentials of complex analysis, harmonic analysis, and entropy optimization are recalled in some detail, with the goal of making the main results more accessible to non-expert readers.
The effect of multiple particle sizes on cooling rates of chondrules produced in large‐scale shocks in the solar nebula

Chondrules represent one of the best probes of the physical conditions and processes acting in the early solar nebula. Proposed chondrule formation models are assessed based on their ability to match the meteoritic evidence, especially experimental constraints on their thermal histories. The model most consistent with chondrule thermal histories is passage through shock waves in the solar nebula. Existing models of heating by shocks generally yield a good first-order approximation to inferred chondrule cooling rates. However, they predict prolonged heating in the preshock region, which would cause volatile loss and isotopic fractionation, which are not observed. These models have typically included particles of a single (large) size, i.e., chondrule precursors, or at most, large particles accompanied by micron-sized grains. The size distribution of solids present during chondrule formation controls the opacity of the affected region, and significantly affects the thermal histories of chondrules. Micron-sized grains evaporate too quickly to prevent excessive heating of chondrule precursors. However, isolated grains in chondrule-forming regions would rapidly coagulate into fractal aggregates. Preshock heating by infrared radiation from the shock front would cause these aggregates to melt and collapse into intermediate-sized (tens of microns) particles. We show that inclusion of such particles yields chondrule cooling rates consistent with petrologic and isotopic constraints.
Absence of power-law mid-infrared conductivity in gravitational crystals

We compute conductivities of strongly-interacting and non-uniform charge densities dual to inhomogeneous anti-de Sitter-black hole spacetimes. Backreacting bulk scalars with periodic boundary profiles, we construct generalizations of ReissnerNordstrom-AdS that interpolate between those used in two previous studies — one that reports power-law scaling for the boundary optical conductivity and one that does not. We find no evidence for power-law scaling of the conductivity, thereby corroborating the previous negative result that gravitational crystals are insufficient to generate the power-law mid-infrared conductivity observed in cuprate superconductors.
Energy-Optimal Coordination of Connected and Automated Vehicles at Multiple Intersections

Urban intersections, merging roadways, roundabouts, and speed reduction zones along with the driver responses to various disturbances are the primary sources of bottlenecks in corridors that contribute to traffic congestion. The implementation of connected and automated technologies can enable a novel computational framework for real-time control aimed at optimizing energy consumption and travel time. In this paper, we propose a decentralized energy-efficient optimal control framework for two adjacent intersections. We derive a closed-form analytical solution that includes interior boundary conditions and evaluate the effectiveness of the solution through simulation. Fuel consumption and travel time are significantly reduced compared to the baseline scenario designed with conventional fixed time signalized intersections.
TESTING THE LINK BETWEEN TERRESTRIAL CLIMATE CHANGE AND GALACTIC SPIRAL ARM TRANSIT

We re-examine past suggestions of a close link between terrestrial climate change and the Sun's transit of spiral arms in its path through the Milky Way galaxy. These links produced concrete fits, deriving the unknown spiral pattern speed from terrestrial climate correlations. We test these fits against new data on spiral structure based on CO data that do not make simplifying assumptions about symmetry and circular rotation. If we compare the times of these transits with changes in the climate of Earth, the claimed correlations not only disappear, but we also find that they cannot be resurrected for any reasonable pattern speed.
SUSTAINED MAGNETOROTATIONAL TURBULENCE IN LOCAL SIMULATIONS OF STRATIFIED DISKS WITH ZERO NET MAGNETIC FLUX

We examine the effects of density stratification on magnetohydrodynamic turbulence driven by the magnetorotational instability in local simulations that adopt the shearing box approximation. Our primary result is that, even in the absence of explicit dissipation, the addition of vertical gravity leads to convergence in the turbulent energy densities and stresses as the resolution increases, contrary to results for zero net flux, unstratified boxes. The ratio of total stress to midplane pressure has a mean of ~0.01, although there can be significant fluctuations on long (50?orbits) timescales. We find that the time-averaged stresses are largely insensitive to both the radial and the vertical aspect ratios of our simulation domain. For simulations with explicit dissipation, we find that stratification extends the range of Reynolds and magnetic Prandtl numbers for which turbulence is sustained, but the behavior of such simulations on long timescales is highly variable. Confirming the results of previous studies, we find oscillations in the large-scale toroidal field with periods of ~10?orbits and describe the dynamo process that underlies these cycles. We discuss possible origins for the different convergence properties of the stratified and unstratified domains and identify open questions that remain to be answered.
Tuza's Conjecture is Asymptotically Tight for Dense Graphs

An old conjecture of Z. Tuza says that for any graph G , the ratio of the minimum size, τ 3 ( G ), of a set of edges meeting all triangles to the maximum size, ν 3 ( G ), of an edge-disjoint triangle packing is at most 2. Here, disproving a conjecture of R. Yuster, we show that for any fixed, positive α there are arbitrarily large graphs G of positive density satisfying τ 3 ( G ) > (1 − o (1))| G |/2 and ν 3 ( G ) G |/4.
A survey of the parameter space of the compressible liquid drop model as applied to the neutron star inner crust

We present a systematic survey the range of predictions of the neutron star inner crust composition, crust-core transition densities and pressures, and density range of the nuclear ‘pasta’ phases at the bottom of the crust provided by the compressible liquid drop model in the light of current experimental and theoretical constraints on model parameters. Using a Skyrme-like model for nuclear matter, we construct baseline sequences of crust models by consistently varying the density dependence of the bulk symmetry energy at nuclear saturation density, L, under two conditions: (i) that the magnitude of the symmetry energy at saturation density J is held constant, and (ii) J correlates with L under the constraint that the pure neutron matter (PNM) EoS satises the results of ab-initio calculations at low densities. Such baseline crust models facilitate consistent exploration of the L dependence of crustal properties. The remaining surface energy and symmetric nuclear matter parameters are systematically varied around the baseline, and dierent functional forms of the PNM EoS at sub-saturation densities implemented, to estimate theoretical ‘error bars’ for the baseline predictions. Inner crust composition and transition densities are shown to be most sensitive to the surface energy at very low proton fractions and to the behavior of the sub-saturation PNM EoS. Recent calculations of the energies of neutron drops suggest that the low-proton-fraction surface energy might be higher than predicted in Skyrme-like models, which our study suggests may result in a greatly reduced volume of pasta in the crust than conventionally predicted.
RATE COEFFICIENTS FOR THE COLLISIONAL EXCITATION OF MOLECULES: ESTIMATES FROM AN ARTIFICIAL NEURAL NETWORK

An artificial neural network (ANN) is investigated as a tool for estimating rate coefficients for the collisional excitation of molecules. The performance of such a tool can be evaluated by testing it on a data set of collisionally induced transitions for which rate coefficients are already known: the network is trained on a subset of that data set and tested on the remainder. Results obtained by this method are typically accurate to within a factor of ~2.1 (median value) for transitions with low excitation rates and ~1.7 for those with medium or high excitation rates, although 4% of the ANN outputs are discrepant by a factor of 10 or more. The results suggest that ANNs will be valuable in extrapolating a data set of collisional rate coefficients to include high-lying transitions that have not yet been calculated. For the asymmetric top molecules considered in this paper, the favored architecture is a cascade-correlation network that creates 16 hidden neurons during the course of training, with three input neurons to characterize the nature of the transition and one output neuron to provide the logarithm of the rate coefficient.