cssi/SciSciGPT-SciSciNet huggingface dataset:
Formal oscillatory integrals and deformation quantization

We develop further the notion of a formal oscillatory integral interpreted as a functional on the amplitudes supported near a fixed non-degenerate critical point $${x_0}$$ of the phase function with zero critical value which depends on a formal parameter. We relate to a formal oscillatory integral two objects, its formal oscillatory integral kernel and the full formal asymptotic expansion at $${x_0}$$ . This formal asymptotic expansion is a formal distribution supported at $${x_0}$$ which is applied to the amplitude. We establish a correspondence between the formal oscillatory integral kernels and formal distributions based upon a number of axiomatic properties of a formal integral expressed in terms of its integral kernel. Then we consider a family of multidifferential operators related to a star product with separation of variables on a pseudo-Kahler manifold. We show that these operators evaluated at a point are given by formal oscillatory integrals. We completely identify their formal oscillatory integral kernels.
Fractional statistics and the butterfly effect

Fractional statistics and quantum chaos are both phenomena associated with the non-local storage of quantum information. In this article, we point out a connection between the butterfly effect in (1+1)-dimensional rational conformal field theories and fractional statistics in (2+1)-dimensional topologically ordered states. This connection comes from the characterization of the butterfly effect by the out-of-time-order-correlator proposed recently. We show that the late-time behavior of such correlators is determined by universal properties of the rational conformal field theory such as the modular S-matrix and conformal spins. Using the bulk-boundary correspondence between rational conformal field theories and (2+1)-dimensional topologically ordered states, we show that the late time behavior of out-of-time-order-correlators is intrinsically connected with fractional statistics in the topological order. We also propose a quantitative measure of chaos in a rational conformal field theory, which turns out to be determined by the topological entanglement entropy of the corresponding topological order.
Coupled cluster channels in the homogeneous electron gas.

We discuss diagrammatic modifications to the coupled cluster doubles (CCD) equations, wherein different groups of terms out of rings, ladders, crossed-rings, and mosaics can be removed to form approximations to the coupled cluster method, of interest due to their similarity with various types of random phase approximations. The finite uniform electron gas (UEG) is benchmarked for 14- and 54-electron systems at the complete basis set limit over a wide density range and performance of different flavours of CCD is determined. These results confirm that rings generally overcorrelate and ladders generally undercorrelate; mosaics-only CCD yields a result surprisingly close to CCD. We use a recently developed numerical analysis [J. J. Shepherd and A. Gruneis, Phys. Rev. Lett. 110, 226401 (2013)] to study the behaviours of these methods in the thermodynamic limit. We determine that the mosaics, on forming the Brueckner one-body Hamiltonian, open a gap in the effective one-particle eigenvalues at the Fermi energy. Numerical evidence is presented which shows that methods based on this renormalisation have convergent energies in the thermodynamic limit including mosaic-only CCD, which is just a renormalised MP2. All other methods including only a single channel, namely, ladder-only CCD, ring-only CCD, and crossed-ring-only CCD, appear to yield divergent energies; incorporation of mosaic terms prevents this from happening.
RESOLVING THE BLACK HOLE INFORMATION PARADOX

The recent progress in string theory strongly suggests that formation and evaporation of black holes is a unitary process. This fact makes it imperative that we find a flaw in the semiclassical reasoning that implies a loss of information. We propose a new criterion that limits the domain of classical gravity: the hypersurfaces of a foliation cannot be stretched too much. This conjectured criterion may have important consequences for the early universe.
Derived splinters in positive characteristic

This paper introduces the notion of a derived splinter. Roughly speaking, a scheme is a derived splinter if it splits off from the coherent cohomology of any proper cover. Over a field of characteristic 0, this condition characterises rational singularities, as suggested by the work of Kovacs. Our main theorem asserts that over a field of characteristic p, derived splinters are the same as (underived) splinters, i.e. schemes that split off from any finite cover. Using this result, we answer some questions of Karen Smith concerning the extension of Serre/Kodaira-type vanishing results beyond the class of ample line bundles in positive characteristic; these are purely projective geometric statements independent of singularity considerations. In fact, we can prove ‘up to finite cover’ analogues in characteristic p of many vanishing theorems known in characteristic 0. All these results fit naturally in the study of F-singularities, and are motivated by a desire to understand the direct summand conjecture.
SYZ Mirror Symmetry for Hypertoric Varieties

We construct a Lagrangian torus fibration on a smooth hypertoric variety and a corresponding SYZ mirror variety using T-duality and generating functions of open Gromov–Witten invariants. The variety is singular in general. We construct a resolution of the variety using the wall and chamber structure on the base of the SYZ fibration.
Testing molecular-cloud fragmentation theories: self-consistent analysis of OH Zeeman observations

The ambipolar-diffusion theory of star formation predicts the formation of fragments in molecular clouds with mass-to-flux ratios greater than that of the parent-cloud envelope. By contrast, scenarios of turbulence-induced fragmentation do not yield such a robust prediction. Based on this property, Crutcher et al. recently proposed an observational test that could potentially discriminate between fragmentation theories. However, the analysis applied to the data severely restricts the discriminative power of the test: the authors conclude that they can only constrain what they refer to as the ‘idealized’ ambipolar-diffusion theory that assumes initially straight– parallel magnetic field lines in the parent cloud. We present an original, self-consistent analysis of the same data taking into account the non-uniformity of the magnetic field in the cloud envelopes, which is suggested by the data themselves, and we discuss important geometrical effects that must be accounted for in using this test. We show quantitatively that the quality of current data does not allow for a strong conclusion about any fragmentation theory. Given the discriminative potential of the test, we urge for more and better-quality data.
Strings in background electric field, space / time noncommutativity and a new noncritical string theory

Searching for space/time noncommutativity we reconsider open strings in a constant background electric field. The main difference between this situation and its magnetic counterpart is that here there is a critical electric field beyond which the theory does not make sense. We show that this critical field prevents us from finding a limit in which the theory becomes a field theory on a noncommutative spacetime. However, an appropriate limit toward the critical field leads to a novel noncritical string theory on a noncommutative spacetime.
Continuity properties for divergence form boundary data homogenization problems

We study the asymptotic behavior at rational directions of the effective boundary condition in periodic homogenization of oscillating Dirichlet data. We establish a characterization for the directional limits at a rational direction in terms of a relatively simple two-dimensional boundary layer problem for the homogenized operator. Using this characterization we show continuity of the effective boundary condition for divergence form linear systems, and for divergence form nonlinear equations we give an example of discontinuity.
Forces and variational compatibility for equilibrium liquid crystal director models with coupled electric fields

Expressions are obtained for force and couple densities and stress tensors in macroscopic models for nematic liquid crystals in electric fields. The coupling between the liquid crystal orientational properties and the electric field is taken into account via a free energy of Oseen–Frank type expressed as an integral functional of the director field and the electric potential field. The variational model here also allows for a gravitational field and a magnetic field, and the differences among these three common types of force fields (gravitational, magnetic, and electric) are discussed. Also included in the free energy is a surface anchoring potential, and its effect on boundary traction and couple stress is explored. The electric field is assumed to arise from electrodes held at constant potential. Flexoelectric effects are included, and as a consequence, the material is no longer a linear dielectric medium. It is shown that the equilibrium solutions of the Euler–Lagrange equations satisfy appropriate expressions of force balance and torque balance, obtained from a virtual work principle. The development here builds from theories of Ericksen related to the notion of “variational compatibility,” and this connection is made. Comparisons are also made to the extensive literature in physics and continuum mechanics on electromagnetic field/matter interaction.
Do Metal-rich Stars Make Metal-rich Planets? New Insights on Giant Planet Formation from Host Star Abundances* **

The relationship between the compositions of giant planets and their host stars is of fundamental interest in understanding planet formation. The solar system giant planets are enhanced above solar composition in metals, both in their visible atmospheres and bulk compositions. A key question is whether the metal enrichment of giant exoplanets is correlated with that of their host stars. Thorngren et al. (2016) showed that in cool (Teq < 1000 K) giant exoplanets, the total heavy-element mass increases with total Mp and the heavy element enrichment relative to the parent star decreases with total Mp. In their work, the host star metallicity was derived from literature [Fe/H] measurements. Here we conduct a more detailed and uniform study to determine whether different host star metals (C, O, Mg, Si, Fe, and Ni) correlate with the bulk metallicity of their planets, using correlation tests and Bayesian linear fits. We present new host star abundances of 19 cool giant planet systems, and combine these with existing host star data for a total of 22 cool giant planet systems (24 planets). Surprisingly, we find no clear correlation between stellar metallicity and planetary residual metallicity (the relative amount of metal versus that expected from the planet mass alone), which is in conflict with common predictions from formation models. We also find a potential correlation between residual planet metals and stellar volatile-to-refractory element ratios. These results provide intriguing new relationships between giant planet and host star compositions for future modeling studies of planet formation.
A non-abelian Seiberg{Witten invariant for integral homology 3{spheres

A new dieomorphism invariant of integral homology 3{spheres is dened using a non-abelian \quaternionic" version of the Seiberg{Witten equations.
Controlling collective spontaneous emission with plasmonic waveguides.

We demonstrate a plasmonic route to control the collective spontaneous emission of two-level quantum emitters. Superradiance and subradiance effects are observed over distances comparable to the operating wavelength inside plasmonic nanochannels. These plasmonic waveguides can provide an effective epsilon-near-zero operation in their cut-off frequency and Fabry-Perot resonances at higher frequencies. The related plasmonic resonant modes are found to efficiently enhance the constructive (superradiance) or destructive (subradiance) interference between different quantum emitters located inside the waveguides. By increasing the number of emitters located in the elongated plasmonic channel, the superradiance effect is enhanced at the epsilon-near-zero operation, leading to a strong coherent increase in the collective spontaneous emission rate. In addition, the separation distance between neighboring emitters and their emission wavelengths can be changed to dynamically control the collective emission properties of the plasmonic system. It is envisioned that the dynamic modification between quantum superradiant and subradiant modes will find applications in quantum entanglement of qubits, low-threshold nanolasers and efficient sensors.
Digital Voicing of Silent Speech

In this paper, we consider the task of digitally voicing silent speech, where silently mouthed words are converted to audible speech based on electromyography (EMG) sensor measurements that capture muscle impulses. While prior work has focused on training speech synthesis models from EMG collected during vocalized speech, we are the first to train from EMG collected during silently articulated speech. We introduce a method of training on silent EMG by transferring audio targets from vocalized to silent signals. Our method greatly improves intelligibility of audio generated from silent EMG compared to a baseline that only trains with vocalized data, decreasing transcription word error rate from 64% to 4% in one data condition and 88% to 68% in another. To spur further development on this task, we share our new dataset of silent and vocalized facial EMG measurements.
An Empirical Calibration to Estimate Cool Dwarf Fundamental Parameters From H-Band Spectra

Interferometric radius measurements provide a direct probe of the fundamental parameters of M dwarfs. However, interferometry is within reach for only a limited sample of nearby, bright stars. We use interferometrically measured radii, bolometric luminosities, and effective temperatures to develop new empirical calibrations based on low-resolution, near-infrared spectra. We find that H-band Mg and Al spectral features are good tracers of stellar properties, and derive functions that relate effective temperature, radius, and log luminosity to these features. The standard deviations in the residuals of our best fits are, respectively, 73 K, 0.027 R ☉, and 0.049 dex (an 11% error on luminosity). Our calibrations are valid from mid K to mid M dwarf stars, roughly corresponding to temperatures between 3100 and 4800 K. We apply our H-band relationships to M dwarfs targeted by the MEarth transiting planet survey and to the cool Kepler Objects of Interest (KOIs). We present spectral measurements and estimated stellar parameters for these stars. Parallaxes are also available for many of the MEarth targets, allowing us to independently validate our calibrations by demonstrating a clear relationship between our inferred parameters and the stars' absolute K magnitudes. We identify objects with magnitudes that are too bright for their inferred luminosities as candidate multiple systems. We also use our estimated luminosities to address the applicability of near-infrared metallicity calibrations to mid and late M dwarfs. The temperatures we infer for the KOIs agree remarkably well with those from the literature; however, our stellar radii are systematically larger than those presented in previous works that derive radii from model isochrones. This results in a mean planet radius that is 15% larger than one would infer using the stellar properties from recent catalogs. Our results confirm the derived parameters from previous in-depth studies of KOIs 961 (Kepler-42), 254 (Kepler-45), and 571 (Kepler-186), the latter of which hosts a rocky planet orbiting in its star's habitable zone.
On the Neutrino Flares from the Direction of TXS 0506+056

For the first time since the discovery of high-energy cosmic neutrinos by IceCube, a multimessenger campaign identified a distant gamma ray blazar, TXS 0506+056, as the source of a high-energy neutrino. The extraordinary brightness of the blazar despite its distance suggests that it may belong to a special class of sources that produce cosmic rays. Moreover, over the last 10 years of data, the high-energy neutrino flux from the source is dominated by a previous neutrino flare in 2014, which implies that flaring sources strongly contribute to the cosmic ray flux. We investigate the contribution of this subclass of flaring blazars to the high-energy neutrino flux and examine its connection to the very high energy cosmic ray observations. We also study the high energy gamma ray emission accompanying the neutrino flare and show that the sources must be more efficient neutrino than gamma ray emitters. This conclusion is supported by the gamma-ray observations during the 2014 neutrino flare.
Discrete torsion, AdS/CFT and duality

We analyse D-branes on orbifolds with discrete torsion, extending earlier results. We analyze certain abelian orbifolds of the type 3/Γ, where Γ is given by m × n, for the most general choice of discrete torsion parameter. By comparing with the AdS/CFT correspondence, we can consider different geometries which give rise to the same physics. This identifies new mirror pairs and suggests new dualities at large N. As a by-product we also get a more geometric picture of discrete torsion.
Turbulent momentum pinch of diamagnetic flows in a tokamak

The diamagnetic flow due to the radial pressure and temperature gradients and the E???B flow due to the radial electric field induce different turbulent momentum fluxes in a tokamak. As a result, when the diamagnetic and E???B flows cancel giving zero net toroidal rotation, there will still be finite momentum transport. This may be particularly important near the plasma?wall boundary where a strong pressure drop is established and the two types of flows are similar in size and opposite in direction. The different momentum fluxes in this region can give significant intrinsic rotation peaking in the core with scaling and values similar to those observed in high confinement mode plasmas.
The interaction of long and short waves in dispersive media

The KdV equation models the propagation of long waves in dispersive media, while the NLS equation models the dynamics of narrow-bandwidth wave packets consisting of short dispersive waves. A system that couples the two equations to model the interaction of long and short waves is mathematically attractive and such a system has been studied over the last decades. We evaluate the validity of this system as a physical model, discussing two main problems. First, only the system coupling the linear Schrodinger equation with KdV has been derived in the literature. Second, the time variables appearing in the equations are of a different order. It appears that in the manuscripts that study the coupled NLS-KdV system, an assumption has been made that the coupled system can be derived, justifying its mathematical study. In fact, this is true even for the papers where the asymptotic derivation with the problems described above is presented. In addition to discussing these inconsistencies, we present an alternative system describing the interaction of long and short waves.
Coarse-graining molecular systems by spectral matching.

Coarse-graining has become an area of tremendous importance within many different research fields. For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale systems become computationally tractable. While significant progress has been made in tuning thermodynamic properties of reduced models, it remains a key challenge to ensure that relevant kinetic properties are retained by coarse-grained dynamical systems. In this study, we focus on data-driven methods to preserve the rare-event kinetics of the original system and make use of their close connection to the low-lying spectrum of the system’s generator. Building on work by Crommelin and Vanden-Eijnden [Multiscale Model. Simul. 9, 1588 (2011)], we present a general framework, called spectral matching, which directly targets the generator’s leading eigenvalue equations when learning parameters for coarse-grained models. We discuss different parametric models for effective dynamics and derive the resulting data-based regression problems. We show that spectral matching can be used to learn effective potentials which retain the slow dynamics but also to correct the dynamics induced by existing techniques, such as force matching.
Deformation and failure of amorphous, solidlike materials

Since the 1970s, theories of deformation and failure of amorphous, solidlike materials have started with models in which stress-driven, molecular rearrangements occur at localized flow defects via shear transformations. This picture is the basis for the modern theory of shear transformation zones (STZs), which is the focus of this review. We begin by describing the structure of the theory in general terms and by showing several applications, specifically, interpretation of stress-strain measurements for a bulk metallic glass, analysis of numerical simulations of shear banding, and the use of the STZ equations of motion in free-boundary calculations. In the second half of this review, we focus for simplicity on what we call an athermal model of amorphous plasticity, and use that model to illustrate how the STZ theory emerges within a systematic formulation of nonequilibrium thermodynamics.
Multi-resolution imaging and spectra of extended sources

I introduce a straightforward technique for the filtering of extended astronomical images into components of different spatial scales. For a positive original image, each component is positive definite, and the sum of all components equals the original image. In this way, the components are each individually suitable for flux measurements and broadband spectra calculations. I present an illustration of this technique on the radio galaxy Cygnus A.
Structure of polytropic stars in General Relativity

The inner structure of a star or primordial interstellar cloud is a topic of major importance in classical and relativistic astrophysics. The impact that General Relativity has on this structure has been the subject of many research papers. In this paper we consider within the context of General Relativity a prototype model for stellar structure in which the pressure and density, but not temperature and density, are related polytropically. To justify this assumption, we note that stars undergo thermodynamically irreversible processes, including the loss of heat to their surroundings. Because of these processes, the temperature may not be controlled by local pressure and gas density. The usual polytropic equation of state relating pressure $p$ and density $\rho $ may now be replaced the generalized equation $p = A(r) \rho ^{\alpha (r)}$ , where the isentropy coefficient $A(r)$ and isentropy index $\alpha (r)$ are functions of radius $r$ . Solutions for the interior stellar structure are then derived within the framework of Einstein’s equations for General Relativity. A single equation for the cumulative mass distribution of the star is obtained and the Tolman-Oppenheimer-Volkoff equation is used to derive formulae for the isentropic index and coefficient. We present analytic and numerical solutions for the generalized polytropic structure of self-gravitating stars and examine their stability. We also prove that if the isentropic index and isentropic coefficient are known, the corresponding distribution of mass within the star is uniquely determined.
Remdesivir Is Effective in Combating COVID-19 because It Is a Better Substrate than ATP for the Viral RNA-Dependent RNA Polymerase.

Summary COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently being treated using Remdesivir, a nucleoside analog that inhibits the RNA-dependent-RNA polymerase (RdRp). However, the enzymatic mechanism and efficiency of Remdesivir have not been determined, and reliable screens for new inhibitors are urgently needed. Here we present our work to optimize expression in E. coli, followed by purification and kinetic analysis of an untagged NSP12/7/8 RdRp complex. Pre-steady-state kinetic analysis shows that our reconstituted RdRp catalyzes fast (kcat = 240–680 s−1) and processive (koff = 0.013 s−1) RNA polymerization. The specificity constant (kcat/Km) for Remdesivir triphosphate (RTP) incorporation (1.29 μM−1s−1) is higher than that for the competing ATP (0.74 μM−1 s−1). This work provides the first robust analysis of RNA polymerization and RTP incorporation by the SARS-CoV-2 RdRp and sets the standard for development of informative enzyme assays to screen for new inhibitors.
Coupling Explicit and Implicit Surface Representations for Generative 3D Modeling

We propose a novel neural architecture for representing 3D surfaces, which harnesses two complementary shape representations: (i) an explicit representation via an atlas, i.e., embeddings of 2D domains into 3D; (ii) an implicit-function representation, i.e., a scalar function over the 3D volume, with its levels denoting surfaces. We make these two representations synergistic by introducing novel consistency losses that ensure that the surface created from the atlas aligns with the level-set of the implicit function. Our hybrid architecture outputs results which are superior to the output of the two equivalent single-representation networks, yielding smoother explicit surfaces with more accurate normals, and a more accurate implicit occupancy function. Additionally, our surface reconstruction step can directly leverage the explicit atlas-based representation. This process is computationally efficient, and can be directly used by differentiable rasterizers, enabling training our hybrid representation with image-based losses.
Reducing Unitary and Spectator Errors in Cross Resonance with Optimized Rotary Echoes

An important entangling quantum gate is significantly improved, leading to a demonstrable increase in quantum volume.
The Tierras Observatory: An ultra-precise photometer to characterize nearby terrestrial exoplanets

We report on the status of The Tierras Observatory at the F.L. Whipple Observatory atop Mt. Hopkins, Arizona, a refurbished 1.3-m ultra-precise fully-automated photometer. Tierras is designed to regularly achieve photometric precisions below 700 ppm from the ground, which will enable the characterization of terrestrial planet transits orbiting < 0.3R stars with 3σ significance, as well as the potential discovery of exo-moons and exo-rings. The design choices that will enable our science goals include: a four-lens focal reducer and field-flattener to increase the field-of-view of the telescope from a 11.94' to a 0.48‡ side; a custom narrow bandpass (40.2 nm FWHM) filter centered around 863.5 nm to minimize precipitable water vapor (PWV) errors known to limit ground-based photometry of red dwarfs; and a deep-depletion 4K x 4K CCD with a 300ke- full well and QE< 85% in our bandpass, operating in frame transfer mode. We are also pursuing the design⊚ of a set of baffes to minimize the significant amount of scattered light currently reaching the image plane. Tierras will begin science operations in early 2021.
Unpacking the Simple View of Reading for Struggling Adult Readers

The Simple View of Reading (SVR), which posits that reading comprehension is the product of decoding and linguistic comprehension, has been studied extensively with school-age readers. However, little is known about the intricacies of the SVR for adults who struggle with reading. This study addresses notable gaps in this literature, including the dimensionality of linguistic comprehension, the interaction between the two SVR components, and the relative contributions of components across different reading proficiency levels. With a sample of 392 struggling adult readers, confirmatory factor analyses indicated that the linguistic comprehension component encompasses the highly related yet separable constructs of oral vocabulary and listening comprehension. Structural equation modeling showed significant main effects of decoding and listening comprehension, but not oral vocabulary, on reading comprehension. In addition, the interaction among the SVR components did not uniquely contribute to variance in reading comprehension. Quantile regression models demonstrated that the unique effects of the SVR components were relatively stable in magnitude across different levels of reading comprehension performance. Implications for instruction and future research are discussed.
Attention Word Embedding

Word embedding models learn semantically rich vector representations of words and are widely used to initialize natural processing language (NLP) models. The popular continuous bag-of-words (CBOW) model of word2vec learns a vector embedding by masking a given word in a sentence and then using the other words as a context to predict it. A limitation of CBOW is that it equally weights the context words when making a prediction, which is inefficient, since some words have higher predictive value than others. We tackle this inefficiency by introducing the Attention Word Embedding (AWE) model, which integrates the attention mechanism into the CBOW model. We also propose AWE-S, which incorporates subword information. We demonstrate that AWE and AWE-S outperform the state-of-the-art word embedding models both on a variety of word similarity datasets and when used for initialization of NLP models.
Train and Deploy an Image Classifier for Disaster Response

With Deep Learning Image Classification becoming more powerful each year, it is apparent that its introduction to disaster response will increase the efficiency that responders can work with. Using several Neural Network Models, including AlexNet, ResNet, MobileNet, DenseNets, and 4-Layer CNN, we have classified flood disaster images from a large image data set with up to 79% accuracy. Our models and tutorials for working with the data set have created a foundation for others to classify other types of disasters contained in the images.
Variational Bayesian Inference for Crowdsourcing Predictions

Crowdsourcing has emerged as an effective means for performing a number of machine learning tasks such as annotation and labelling of images and other data sets. In most early settings of crowdsourcing, the task involved classification, that is assigning one of a discrete set of labels to each task. Recently, however, more complex tasks have been attempted including asking crowdsource workers to assign continuous labels, or predictions. In essence, this involves the use of crowdsourcing for function estimation. We are motivated by this problem to drive applications such as collaborative prediction, that is, harnessing the wisdom of the crowd to predict quantities more accurately. To do so, we propose a Bayesian approach aimed specifically at alleviating overfitting, a typical impediment to accurate prediction models in practice. In particular, we develop a variational Bayesian technique for two different worker noise models - one that assumes workers’ noises are independent and the other that assumes workers’ noises have a latent low-rank structure. Our evaluations on synthetic and real-world datasets demonstrate that these Bayesian approaches perform significantly better than existing non-Bayesian approaches and are thus potentially useful for this class of crowdsourcing problems.
Improving DGA-Based Malicious Domain Classifiers for Malware Defense with Adversarial Machine Learning

Domain Generation Algorithms (DGAs) are used by adversaries to establish Command and Control (C&C) server communications during cyber attacks. Blacklists of known/identified C&C domains are used as one of the defense mechanisms. However, static blacklists generated by signature-based approaches can neither keep up nor detect never-seen-before malicious domain names. To address this weakness, we applied a DGA-based malicious domain classifier using the Long Short-Term Memory (LSTM) method with a novel feature engineering technique. Our model's performance shows a greater accuracy compared to a previously reported model. Additionally, we propose a new adversarial machine learning-based method to generate never-before-seen malware-related domain families. We augment the training dataset with new samples to make the training of the models more effective in detecting never-before-seen malicious domain names. To protect blacklists of malicious domain names against adversarial access and modifications, we devise secure data containers to store and transfer blacklists.
Suppressing Frequency Fluctuations of Self-Sustained Vibrations in Underdamped Nonlinear Resonators

We study frequency fluctuations in self-sustained oscillators based on nonlinear underdamped resonators. Important types of such resonators are nano- and microelectromechanical systems. Various noise sources are considered, with the emphasis on the fundamentally unavoidable noise that comes along with dissipation from the coupling to a thermal reservoir. The formulation in terms of the action-angle variables of the resonator allows us to analyze a deeply nonlinear regime. In this regime the vibration frequency as a function of the action can have an extremum. We show that frequency fluctuations can be strongly reduced by choosing the operation point at this extremum. We suggest a practical implementation of a nanoresonator that has the appropriate property and show explicit results for the corresponding model.
Large m asymptotics for minimal partitions of the Dirichlet eigenvalue

In this paper, we study large m asymptotics of the l1 minimal m-partition problem for the Dirichlet eigenvalue. For any smooth domain Ω ⊂ ℝn such that ∣Ω∣ = 1, we prove that the limit $${\rm{lim}}_{m \to \infty}l_m^1\left(\Omega \right) = {c_0}$$ exists, and the constant c0 is independent of the shape of Ω. Here, $$l_m^1\left({\rm{\Omega}} \right)$$ denotes the minimal value of the normalized sum of the first Laplacian eigenvalues for any m-partition of Ω.
Harnessing the population statistics of subhalos to search for annihilating dark matter

The Milky Way's dark matter halo is expected to host numerous low-mass subhalos with no detectable associated stellar component. Such subhalos are invisible unless their dark matter annihilates to visible states such as photons. One of the established methods for identifying candidate subhalos is to search for individual unassociated gamma-ray sources with properties consistent with the dark matter expectation. However, robustly ruling out an astrophysical origin for any such candidate is challenging. In this work, we present a complementary approach that harnesses information about the entire population of subhalos---such as their spatial and mass distribution in the Galaxy---to search for a signal of annihilating dark matter. Using simulated data, we show that the collective emission from subhalos can imprint itself in a unique way on the statistics of observed photons, even when individual subhalos may be too dim to be resolved on their own. Additionally, we demonstrate that, for the models we consider, the signal can be identified even in the face of unresolved astrophysical point-source emission of extragalactic and Galactic origin. This establishes a new search technique for subhalos that is complementary to established methods, and that could have important ramifications for gamma-ray dark matter searches using observatories such as the Fermi Large Area Telescope and the Cherenkov Telescope Array.
A review essay on The European Guilds

Ogilvie’s The European Guilds is a major contribution to economic history and institutional economics. This review essay surveys the main contributions of Guilds, locating it in a long-standing debate over whether craft guilds contributed positively or negatively to economic development in medieval and early modern Europe. The wealth of evidence Ogilvie amasses suggests that craft guilds should be thought of as organizations that primarily benefited their members at the expense of non-members, and used regulations to extract rents and exclude outsiders.
Portfolio choice with endogenous utility: a large deviations approach

This paper provides an alternative behavioral foundation for an investor's use of power utility in the objective function and its particular risk aversion parameter. The foundation is grounded in an investor's desire to minimize the objective probability that the growth rate of invested wealth will not exceed an investor-selected target growth rate. Large deviations theory is used to show that this is equivalent to using power utility, with an argument that depends on the investor's target, and a risk aversion parameter determined by maximization. As a result, an investor's risk aversion parameter is not independent of the investment opportunity set, contrary to the standard model assumption.
The Only Game in Town: Stock-Price Consequences of Local Bias

Abstract Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. Using data on U.S. states and Census regions, we find clear-cut support for this proposition. Most of the variation in the ratio of interest comes from differences across regions in aggregate book value per capita. Regions with low population density—e.g., the Deep South—are home to relatively few firms per capita, which leads to higher stock prices via an “only-game-in-town” effect.
Debiasing the disposition effect by reducing the saliency of information about a stock's purchase price

The disposition effect refers to the empirical fact that investors have a higher propensity to sell risky assets with capital gains compared to risky assets with capital losses, and it has been associated with low trading performance. We use a stock trading laboratory experiment to investigate if it is possible to reduce subjects’ tendency to exhibit a disposition effect by making information about a stock's purchase price, and thus about capital gains and losses, less salient. We compare two experimental conditions: a high-saliency condition in which the purchase price of a stock is prominently displayed by the trading software, and a low-saliency condition in which it is not displayed at all. We find that individuals exhibit a disposition effect in the high-saliency condition, and that the effect is 25% smaller in the low-saliency condition. This suggests that it is possible to debias the disposition effect by reducing the saliency with which information about a stock's purchase price is displayed on financial statements and online trading platforms.
The ballot order effect is huge: evidence from Texas

Primary and runoff elections in Texas provide an ideal test of the ballot order hypothesis, because ballot order is randomized within each county and the state offers many counties and contests to analyze. Doing so for all statewide offices contested in the 2014 Democratic and Republican primaries and runoffs yields precise estimates of the ballot order effect across 24 different contests, including several not studied previously. Except for a few high-profile, high-information races, the ballot order effect is large, especially in down-ballot races for judicial positions. There, the empirical results indicate that going from last to first on the ballot raises a candidate’s vote share by nearly ten percentage points. The magnitude of this effect is not sensitive to demographic and economic factors.
Living Originalism: The Magical Mystery Tour

In a brilliant theoretical maneuver, Professor Jack Balkin has proposed to marry originalism and living constitutionalism. His move resembles President Jefferson’s appeal to Americans, in his First Inaugural Address, to accept that “we are all Republicans, we are all Federalists.” If Balkin’s goal is to send originalism to the same fate as the Federalist Party, he has already made substantial progress.This short essay begins with a summary of the core features of Balkin’s theory. It then turns to the recent work of Professor Steven G. Calabresi. A founder of the Federalist Society who clerked for Judge Robert Bork and Justice Antonin Scalia, Calabresi was also a special assistant to Attorney General Meese and a speechwriter for Vice President Quayle. He went on to become one of the most frequently cited academic originalists of his generation, but he has now fully converted to Balkin’s “living originalism.”Calabresi’s conversion suggests that wedding bells are ringing pretty loudly for Balkin’s union of two theories that were once thought to be irreconcilable. This essay argues that the marriage will leave originalism in much the same position as the legal death that married women experienced under the old rules of coverture.
Empirical Study on Price Momentum Strategy for Long, Short, and Long/Short Equity Portfolios: Optimal Rebalancing Period and Optimal Size

The authors start by observing that the optimal holding periods for long, short, and long/short equity portfolios must vary with transaction costs. The optimal holding period ranges from six to nine months, depending upon the type of portfolios being considered. Optimal efficiency occurs in portfolios containing between 20 and 80 securities, while efficiency is compromised in portfolios consisting of more than 100 stocks. They show that adjusted short and long/short equity portfolios9 returns exhibit graphical patterns similar to the ones in the original short and long/short equity portfolios; however, these adjusted portfolio returns are amplified.
Human Rights and emotions from the perspective of the colonised: Anthropofagi, legal surrealism and subaltern studies

The Third World can easily experience a form of ghost existence: We speak but are not heard. However, in our culture there are a number of trends and positions that are relevant to the task of thinking human rights in a new light. Among them, the critiques of rationalism advanced by Oswald de Andrade and Luis Alberto Warat in Brasil and Argentina—where there is a possibility of integrating the emotions into human rights theory. Sharing a preoccupation with those excluded from the ‘world order’ and the appeal to sensibility, Subaltern Studies have advanced some insights pointing at establishing a link between colonialism, human rights and suffering. This is the case in the work of Upendra Baxi, who has made a criticism of Western theorisations of law and crafted a fruitful encounter between the insights of Subaltern Studies and the theory of human rights.Key words: Manifesto Antropofago, emotions, legal surrealism, Subaltern Studies, decolonial theory, Eurocentrism, human rights.
Summing Up the Public Interest: A Review of "Media Diversity and Localism: Meaning and Metrics," edited by Philip M. Napoli

Philip Napoli's Media Diversity and Localism: Meaning and Metrics is a thoughtful and first of its kind compilation of some of the ongoing research and scholarship examining the concepts of localism and diversity underlying the Federal Communications Commission's public interest standard in broadcasting. The collection of essays addresses these fundamental goals from a variety of disciplines beyond the law, including political science, communications policy, sociology, and economics. These essays explore the values associated with these two goals, apply performance metrics to assess existing regulatory policies intended to preserve and promote these goals, and reflect on their meaning in the new media landscape and for current communications policy and decision-making. The volume provides a scholarly foundation for assessing some of the central questions in the ongoing media policy debates.
Two Types of Discrimination: The Familiar and the Forgotten

This essay argues that current Equal Protection doctrine fails to recognize an important conceptual distinction between two types of discrimination. Current doctrine is inadequate, according to the author, because it treats all discrimination cases as if they were instances of only one of these types. As a result, the Supreme Court mistreats discrimination cases of the forgotten variety. The author draws a distinction between proxy and non-proxy discrimination. Proxy discrimination uses the classification in the law as a means to reach a set of persons with a different, correlated trait. Non-proxy discrimination, by contrast, aims at the set defined by the classification itself. Because each has a distinct aim, each requires an examination of different moral issues. The author argues that current Equal Protection doctrine is suited for proxy discrimination only. Non-proxy cases are forced into an inappropriate doctrinal scheme with two unfortunate results. First, the Court focuses its attention on irrelevant issues and second, the Court fails to address the real and important issues that cases of non-proxy discrimination present. At the close of the Essay, the author sketches a new theory for non-proxy cases and demonstrates how this theory casts familiar issues like affirmative action and single-sex education in a new light.
Trade creating free trade areas and the undermining of multilateralism

This paper indicates that the consequences of regional trade agreements for the world trade system may be deceiving—an arrangement's apparent virtue may constitute the source of its drawback. In a model where governments have political, as well as economic, motivations, I show that a free trade area induces its members to reduce protection against the non-members, and to do so sufficiently deeply to generate overall trade creation. Trade creation amplifies the excluded countries’ access to the integrating markets, but also reduces their extra gains from multilateral liberalization. Thus, trade creation can reverse the support of the excluded countries to liberalization on a multilateral basis. This is more likely to happen when governments outside the free trade area are more responsive to special interests.
TESTING FOR RACIAL DIFFERENCES IN THE MENTAL ABILITY OF YOUNG CHILDREN

Abstract Using a new nationally representative dataset, we find minor differences in test outcomes between black and white infants that disappear with a limited set of controls. However, relative t...
Ethical Reasoning in an Equitable Relief Innocent Spouse Context

This study assessed the relationship between ethical reasoning and the decision to grant equitable relief using an innocent spouse vignette where a wife had partial knowledge of her husband's tax fraud. A path model derived from various ethics theories was tested using a sample of 357 accounting, legal, and human resource professionals, and after careful examination of the measurement and structural relationships in the path model, the results provided partial support for the study's hypotheses. Moral intensity was marginally associated with an increased recognition of an ethical issue and positively related ethical judgments made in an innocent spouse situation, and moral intensity was also negatively related to the decision to grant relief. The ethical judgment variable was positively related to the decision to grant relief, while ethical issue awareness was marginally associated with the decision to deny relief. The implications of these findings are discussed, along with the limitations of the study and suggestions for future research.
Identifying informed traders in futures markets

Abstract We use daily positions of futures market participants to identify informed traders. These data contain 8,921 unique traders. We identify between 94 and 230 traders as overnight informed and 91 as intraday informed with little overlap. Floor brokers/traders are over-represented in the overnight informed group. The intraday informed group is dominated by managed money traders/hedge funds and swap dealers, with commercial hedgers under-represented. We find that characteristics such as experience, position size, trading activity, and type of positions held offer significant predictive power for who is informed. An analysis of daily trader profits confirms that we select highly profitable traders.