cssi/SciSciGPT-SciSciNet huggingface dataset:
How Are Residents Trained in Neuropathology? A Survey of Neurology Program Directors in the United States

To understand the current state of neurology residents training in neuropathology, we electronically distributed a 16-item survey to 150 adult and 70 child neurology program directors (PDs). The survey inquired about their program characteristics, neuropathology curriculum and assessment methods, trainee performance, and attitudes. Descriptive analysis was used to summarize categorical variables as frequencies and percentages and continuous as means and standard deviations. We conducted a series of Mann-Whitney U and Fisher's exact tests to evaluate differences between various program characteristics. Sixty-four (29%) PDs responded to the survey, including 45 (30%) adult and 19 (27%) child neurology PDs. Thirty-one programs required a dedicated neuropathology rotation. The majority (92%) used the Residency In-Service Training Examination (RITE) to assess trainee's knowledge. Approximately 86% of the PDs agreed that neuropathology is essential and a defined curriculum is necessary during residency training. There was no difference in the RITE scores between programs. We conclude that a neuropathology rotation was felt to be essential even though the RITE scores did not differ between programs with and without a dedicated rotation. Alternative evaluation and training methods may need consideration. A future survey of all the stakeholders may be required to thoroughly understand and disseminate the neuropathology education well.
The potential for geostationary remote sensing of NO 2 to improve weather prediction

Abstract. Observations of winds in the planetary boundary layer remain sparse making it challenging to simulate and predict atmospheric conditions that are most important for describing and predicting urban air quality. Short-lived chemicals are observed as plumes whose location is affected by boundary layer winds and whose lifetime is affected by boundary layer height and mixing. Here we investigate the application of data assimilation of NO 2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of wind fields in the boundary layer.
Nodal disease burden and outcome of medullary thyroid carcinoma

BACKGROUND Medullary thyroid carcinoma (MTC) is a rare malignancy with high incidence of cervical lymph node (CLN) metastasis. We investigated the impact of nodal disease burden on survival. METHODS We searched the National Cancer Database for MTC patients treated surgically. Impact of nodal metastasis on survival was analyzed using Cox univariable and multivariable regression. RESULTS We identified 2627 patients from 2004 to 2015. Positive CLNs were identified in 1433 (54.5%), and 542 (20.6%) had >10 CLN+. Overall survival was 94.5% and 89.6% at 3 and 5 years. Patients with 11 to 20 CLN+ had significantly worse survival than patients with 1 to 10 CLN+ in univariable and multivariable analyses (HR = 3.56 (2.31-5.50) vs 2.26 (1.60-3.20); P < .0001). The ratio of positive to dissected CLN was associated with overall survival. CONCLUSIONS Higher burden of nodal disease is associated with worse survival in MTC. The number of positive nodes could be a valuable prognosticator in addition to the current staging system.
PowerNorm: Rethinking Batch Normalization in Transformers

The standard normalization method for neural network (NN) models used in Natural Language Processing (NLP) is layer normalization (LN). This is different than batch normalization (BN), which is widely-adopted in Computer Vision. The preferred use of LN in NLP is principally due to the empirical observation that a (naive/vanilla) use of BN leads to significant performance degradation for NLP tasks; however, a thorough understanding of the underlying reasons for this is not always evident. In this paper, we perform a systematic study of NLP transformer models to understand why BN has a poor performance, as compared to LN. We find that the statistics of NLP data across the batch dimension exhibit large fluctuations throughout training. This results in instability, if BN is naively implemented. To address this, we propose Power Normalization (PN), a novel normalization scheme that resolves this issue by (i) relaxing zero-mean normalization in BN, (ii) incorporating a running quadratic mean instead of per batch statistics to stabilize fluctuations, and (iii) using an approximate backpropagation for incorporating the running statistics in the forward pass. We show theoretically, under mild assumptions, that PN leads to a smaller Lipschitz constant for the loss, compared with BN. Furthermore, we prove that the approximate backpropagation scheme leads to bounded gradients. We extensively test PN for transformers on a range of NLP tasks, and we show that it significantly outperforms both LN and BN. In particular, PN outperforms LN by 0.4/0.6 BLEU on IWSLT14/WMT14 and 5.6/3.0 PPL on PTB/WikiText-103. We make our code publicly available at \url{this https URL}.
Reconstructing NBA Players

Great progress has been made in 3D body pose and shape estimation from a single photo. Yet, state-of-the-art results still suffer from errors due to challenging body poses, modeling clothing, and self occlusions. The domain of basketball games is particularly challenging, as it exhibits all of these challenges. In this paper, we introduce a new approach for reconstruction of basketball players that outperforms the state-of-the-art. Key to our approach is a new method for creating poseable, skinned models of NBA players, and a large database of meshes (derived from the NBA2K19 video game) that we are releasing to the research community. Based on these models, we introduce a new method that takes as input a single photo of a clothed player in any basketball pose and outputs a high resolution mesh and 3D pose for that player. We demonstrate substantial improvement over state-of-the-art, single-image methods for body shape reconstruction. Code and dataset are available at http://grail.cs.washington.edu/projects/nba_players/.
Local polynomial regression for pooled response data

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these...
MULTI-FLUID SIMULATIONS OF CHROMOSPHERIC MAGNETIC RECONNECTION IN A WEAKLY IONIZED REACTING PLASMA

We present results from the first self-consistent multi-fluid simulations of chromospheric magnetic reconnection in a weakly ionized reacting plasma. We simulate two-dimensional magnetic reconnection in a Harris current sheet with a numerical model which includes ion-neutral scattering collisions, ionization, recombination, optically thin radiative loss, collisional heating, and thermal conduction. In the resulting tearing mode reconnection the neutral and ion fluids become decoupled upstream from the reconnection site, creating an excess of ions in the reconnection region and therefore an ionization imbalance. Ion recombination in the reconnection region, combined with Alfvenic outflows, quickly removes ions from the reconnection site, leading to a fast reconnection rate independent of Lundquist number. In addition to allowing fast reconnection, we find that these non-equilibria partial ionization effects lead to the onset of the nonlinear secondary tearing instability at lower values of the Lundquist number than has been found in fully ionized plasmas. These simulations provide evidence that magnetic reconnection in the chromosphere could be responsible for jet-like transient phenomena such as spicules and chromospheric jets.
Topological string entanglement

We investigate how topological entanglement of Chern-Simons theory is captured in a string theoretic realization. Our explorations are motivated by a desire to understand how quantum entanglement of low energy open string degrees of freedom is encoded in string theory (beyond the oft discussed classical gravity limit). Concretely, we realize the Chern-Simons theory as the worldvolume dynamics of topological D-branes in the topological A-model string theory on a Calabi-Yau target. Via the open/closed topological string duality one can map this theory onto a pure closed topological A-model string on a different target space, one which is related to the original Calabi-Yau geometry by a geometric/conifold transition. We demonstrate how to uplift the replica construction of Chern-Simons theory directly onto the closed string and show that it provides a meaningful definition of reduced density matrices in topological string theory. Furthermore, we argue that the replica construction commutes with the geometric transition, thereby providing an explicit closed string dual for computing reduced states, and Renyi and von Neumann entropies thereof. While most of our analysis is carried out for Chern-Simons on S3, the emergent picture is rather general. Specifically, we argue that quantum entanglement on the open string side is mapped onto quantum entanglement on the closed string side and briefly comment on the implications of our result for physical holographic theories where entanglement has been argued to be crucial ingredient for the emergence of classical geometry.
Near-Equality of the Penrose Inequality for Rotationally Symmetric Riemannian Manifolds

This article is the sequel to Lee and Sormani (Stability of the Positive Mass Theorem for Rotationally Symmetric Riemannian Manifolds, 2011. Preprint), which dealt with the near-equality case of the Positive Mass Theorem. We study the near-equality case of the Penrose Inequality for the class of complete asymptotically flat rotationally symmetric Riemannian manifolds with nonnegative scalar curvature whose boundaries are outermost minimal hypersurfaces. Specifically, we prove that if the Penrose Inequality is sufficiently close to being an equality on one of these manifolds, then it must be close to a Schwarzschild space with an appended cylinder, in the sense of Lipschitz distance. Since the Lipschitz distance bounds the intrinsic flat distance on compact sets, we also obtain a result for intrinsic flat distance, which is a more appropriate distance for more general near-equality results, as discussed in Lee and Sormani (Stability of the Positive Mass Theorem for Rotationally Symmetric Riemannian Manifolds, 2011. Preprint).
Boundaries of Siegel disks: Numerical studies of their dynamics and regularity

Siegel disks are domains around fixed points of holomorphic maps in which the maps are locally linearizable (i.e., become a rotation under an appropriate change of coordinates which is analytic in a neighborhood of the origin). The dynamical behavior of the iterates of the map on the boundary of the Siegel disk exhibits strong scaling properties which have been intensively studied in the physical and mathematical literature. In the cases we study, the boundary of the Siegel disk is a Jordan curve containing a critical point of the map (we consider critical maps of different orders), and there exists a natural parametrization which transforms the dynamics on the boundary into a rotation. We compute numerically this parameterization and use methods of harmonic analysis to compute the global Holder regularity of the parametrization for different maps and rotation numbers. We obtain that the regularity of the boundaries and the scaling exponents are universal numbers in the sense of renormalization theory (i.e., they do not depend on the map when the map ranges in an open set), and only depend on the order of the critical point of the map in the boundary of the Siegel disk and the tail of the continued function expansion of the rotation number. We also discuss some possible relations between the regularity of the parametrization of the boundaries and the corresponding scaling exponents.
$L$-functions of $p$-adic characters

We define a p-adic character to be a continuous homomorphism from 1 + tFq[[t]] to ℤ*p. For p > 2, we use the ring of big Witt vectors over Fq to exhibit a bijection between p-adic characters and sequences (ci)(i,p)=1 of elements in ℤq, indexed by natural numbers relatively prime to p, and for which limi→ci = 0. To such a p-adic character we associate an L-function, and we prove that this L-function is p-adic meromorphic if the corresponding sequence (ci) is overconvergent. If more generally the sequence is C log-convergent, we show that the associated L-function is meromorphic in the open disk of radius qC. Finally, we exhibit examples of C log-convergent sequences with associated L-functions which are not meromorphic in the disk of radius qC+e for any e > 0. © 2014 by The Editorial.
Fifty years of the finite nonperiodic Toda lattice: a geometric and topological viewpoint

In 1967, Japanese physicist Morikazu Toda published a pair of seminal papers in the Journal of the Physical Society of Japan that exhibited soliton solutions to a chain of particles with nonlinear interactions between nearest neighbors. In the fifty years that followed, Toda's system of particles has been generalized in different directions, each with its own analytic, geometric, and topological characteristics. These are known collectively as the Toda lattice. This survey recounts and compares the various versions of the finite nonperiodic Toda lattice from the perspective of their geometry and topology. In particular, we highlight the polytope structure of the solution spaces as viewed through the moment map, and we explain the connection between the real indefinite Toda flows and the integral cohomology of real flag varieties.
Elliptic genera of Landau–Ginzburg models over nontrivial spaces

In this paper, we discuss elliptic genera of (2,2) and (0,2) supersymmetric Landau-Ginzburg models over nontrivial spaces, i.e., nonlinear sigma models on nontrivial noncompact manifolds with superpotential, generalizing old computations in Landau-Ginzburg models over (orbifolds of) vector spaces. For Landau-Ginzburg models in the same universality class as nonlinear sigma models, we explicitly check that the elliptic genera of the Landau-Ginzburg models match that of the nonlinear sigma models, via a Thom class computation of a form analogous to that appearing in recent studies of other properties of Landau-Ginzburg models on nontrivial spaces.
ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research

First identified in Wuhan, China, in December 2019, the outbreak of COVID-19 has been declared as a global emergency in January, and a pandemic in March 2020 by the World Health Organization (WHO). Along with this pandemic, we are also experiencing an "infodemic" of information with low credibility such as fake news and conspiracies. In this work, we present ReCOVery, a repository designed and constructed to facilitate research on combating such information regarding COVID-19. We first broadly search and investigate ~2,000 news publishers, from which 60 are identified with extreme [high or low] levels of credibility. By inheriting the credibility of the media on which they were published, a total of 2,029 news articles on coronavirus, published from January to May 2020, are collected in the repository, along with 140,820 tweets that reveal how these news articles have spread on the Twitter social network. The repository provides multimodal information of news articles on coronavirus, including textual, visual, temporal, and network information. The way that news credibility is obtained allows a trade-off between dataset scalability and label accuracy. Extensive experiments are conducted to present data statistics and distributions, as well as to provide baseline performances for predicting news credibility so that future methods can be compared. Our repository is available at http://coronavirus-fakenews.com.
Gravity’s light in the shadow of the Moon

In this essay, we look at the possibility of vacuum production of very low frequency electromagnetic radiation from a gravitational wave background (i.e. gravity’s light). We also propose that this...
Exact axisymmetric Taylor states for shaped plasmas

We present a general construction for exact analytic Taylor states in axisymmetric toroidal geometries. In this construction, the Taylor equilibria are fully determined by specifying the aspect ratio, elongation, and triangularity of the desired plasma geometry. For equilibria with a magnetic X-point, the location of the X-point must also be specified. The flexibility and simplicity of these solutions make them useful for verifying the accuracy of numerical solvers and for theoretical studies of Taylor states in laboratory experiments.
Homology stability for outer automorphism groups of free groups

We prove that the quotient map from Aut(Fn) to Out(Fn) induces an isomorphism on homology in dimension i for n at least 2i + 4. This corrects an earlier proof by the first author and significantly improves the stability range. In the course of the proof, we also prove homology stability for a sequence of groups which are natural analogs of mapping class groups of surfaces with punctures. In particular, this leads to a slight improvement on the known stability range for Aut(Fn), showing that its ith homology is independent of n for n at least 2i + 2. AMS Classification 20F65; 20F28, 57M07
Large-amplitude membrane flutter in inviscid flow

We study the large-amplitude flutter of membranes (of zero bending rigidity) with vortex sheet wakes in two-dimensional inviscid fluid flows. We apply small initial deflections and track their exponential decay or growth and subsequent large-amplitude dynamics in the space of three dimensionless parameters: membrane pretension, mass density and stretching modulus. With both ends fixed, all the membranes converge to steady deflected shapes with single humps that are nearly fore-aft symmetric, except when the deformations are unrealistically large. With leading edges fixed and trailing edges free to move in the transverse direction, the membranes flutter periodically at intermediate values of mass density. As mass density increases, the motions are increasingly aperiodic, and the amplitudes increase and spatial and temporal frequencies decrease. As mass density decreases from the periodic regime, the amplitudes decrease and spatial and temporal frequencies increase until the motions become difficult to resolve numerically. With both edges free to move in the transverse direction, the membranes flutter similarly to the fixed–free case, but also translate vertically with steady, periodic or aperiodic trajectories, and with non-zero slopes that lead to small angles of attack with respect to the oncoming flow.
Connecting quasinormal modes and heat kernels in 1-loop determinants

We connect two different approaches for calculating functional determinants on quotients of hyperbolic spacetime: the heat kernel method and the quasinormal mode method. For the example of a rotating BTZ background, we show how the image sum in the heat kernel method builds up the logarithms in the quasinormal mode method, while the thermal sum in the quasinormal mode method builds up the integrand of the heat kernel. More formally, we demonstrate how the heat kernel and quasinormal mode methods are linked via the Selberg zeta function. We show that a 1-loop partition function computed using the heat kernel method may be cast as a Selberg zeta function whose zeros encode quasinormal modes. We discuss how our work may be used to predict quasinormal modes on more complicated spacetimes.
ABOUT EXOBIOLOGY: THE CASE FOR DWARF K STARS

One of the most fundamental topics of exobiology concerns the identification of stars with environments consistent with life. Although it is believed that most types of main-sequence stars might be able to support life, particularly extremophiles, special requirements appear to be necessary for the development and sustainability of advanced life forms. From our study, orange main-sequence stars, ranging from spectral type late-G to mid-K (with a maximum at early-K), are most promising. Our analysis considers a variety of aspects, including (1) the frequency of the various types of stars, (2) the speed of stellar evolution their lifetimes, (3) the size of the stellar climatological habitable zones (CLI-HZs), (4) the strengths and persistence of their magnetic dynamo generated X-ray - UV emissions, and (5) the frequency and severity of flares, including superflares; both (4) and (5) greatly reduce the suitability of red dwarfs to host life-bearing planets. The various phenomena show pronounced dependencies on the stellar key parameters such as effective temperature and mass, permitting the assessment of the astrobiological significance of various types of stars. Thus, we developed a "Habitable-Planetary-Real-Estate Parameter" (HabPREP) that provides a measure for stars that are most suitable for planets with life. Early K stars are found to have the highest HabPREP values, indicating they may be "Goldilocks" stars for life-hosting planets. Red dwarfs are numerous, having long lifetimes, but their narrow CLI-HZs and hazards from magnetic activity make them less suitable for hosting exolife. Moreover, we provide X-ray - FUV irradiances for G0 V - M5 V stars over a wide range of ages.
Can Pulsational Instabilities Impact a Massive Star's Rotational Evolution?

We investigate whether angular momentum transport due to unstable pulsation modes can play a significant role in the rotational evolution of massive stars. We find that these modes can redistribute appreciable angular momentum, and moreover trigger shear-instability mixing in the molecular weight gradient zone adjacent to stellar cores, with significant evolutionary impact.
Higgs Parity grand unification

The vanishing of the Higgs quartic coupling of the Standard Model at high energies may be explained by spontaneous breaking of Higgs Parity. Taking Higgs Parity to originate from the Left-Right symmetry of the SO(10) gauge group, leads to a new scheme for precision gauge coupling unification that is consistent with proton decay. We compute the relevant running of couplings and threshold corrections to allow a precise correlation among Standard Model parameters. The scheme has a built-in solution for obtaining a realistic value for mb/mτ , which further improves the precision from gauge coupling unification, allowing the QCD coupling constant to be predicted to the level of 1% or, alternatively, the top quark mass to 0.2%. Future measurements of these parameters may significantly constrain the detailed structure of the theory. We also study an SO(10) embedding of quark and lepton masses, showing how large neutrino mixing is compatible with small quark mixing, and predict a normal neutrino mass hierarchy. The strong CP problem may be explained by combining Higgs Parity with space-time parity.
On Euclidean spinors and Wick rotations

Abstract We propose a continuous Wick rotation for Dirac, Majorana and Weyl spinors from Minkowski spacetime to Euclidean space which treats fermions on the same footing as bosons. The result is a recipe to construct a supersymmetric Euclidean theory from any supersymmetric Minkowski theory. This Wick rotation is identified as a complex Lorentz boost in a five-dimensional space and acts uniformly on bosons and fermions. For Majorana and Weyl spinors our approach is reminiscent of the traditional Osterwalder-Schrader approach in which spinors are “doubled” but the action is not hermitian. However, for Dirac spinors our work provides a link to the work of Schwinger and Zumino in which hermiticity is maintained but spinors are not doubled. Our work differs from recent work by Mehta since we introduce no external metric and transform only the basic fields.
Combining the hybrid functional method with dynamical mean-field theory

We present a new method to compute the electronic structure of correlated materials combining the hybrid functional method with the dynamical mean-field theory. As a test example of the method we study cerium sesquioxide, a strongly correlated Mott band insulator. The hybrid functional part improves the magnitude of the pd-band gap which is underestimated in the standard approximations to density functional theory while the dynamical mean-field theory part splits the 4f-electron spectra into a lower and an upper Hubbard band.
Replica Symmetry Breaking in Multi-species Sherrington–Kirkpatrick Model

In the Sherrington–Kirkpatrick (SK) and related mixed p-spin models, there is interest in understanding replica symmetry breaking at low temperatures. For this reason, the so-called AT line proposed by de Almeida and Thouless as a sufficient (and conjecturally necessary) condition for symmetry breaking, has been a frequent object of study in spin glass theory. In this paper, we consider the analogous condition for the multi-species SK model, which concerns the eigenvectors of a Hessian matrix. The analysis is tractable in the two-species case with positive definite variance structure, for which we derive an explicit AT temperature threshold. To our knowledge, this is the first non-asymptotic symmetry breaking condition produced for a multi-species spin glass. As possible evidence that the condition is sharp, we draw further parallel with the classical SK model and show coincidence with a separate temperature inequality guaranteeing uniqueness of the replica symmetric critical point.
Counting rational points on Kummer surfaces

We consider the problem of counting the number of rational points on the family of Kummer surfaces associated with two non-isogenous elliptic curves. For this two-parameter family we prove Manin’s unity, using the presentation of the Kummer surfaces as isotrivial elliptic fibration and as double cover of the modular elliptic surface of level two. By carrying out the rational point-count with respect to either of the two elliptic fibrations explicitly, we obtain an interesting new identity between two-parameter counting functions.
A note on the BPS spectrum of the matrix model

We calculate, using noncommutative supersymmetric Yang-Mills gauge theory, the part of the spectrum of the toroidally compactified Matrix theory which corresponds to quantized electric fluxes on two and three tori.
Bias-Variance Tradeoff of Graph Laplacian Regularizer

This letter presents a bias-variance tradeoff of graph Laplacian regularizer, which is widely used in graph signal processing and semisupervised learning tasks. The scaling law of the optimal regularization parameter is specified in terms of the spectral graph properties and a novel signal-to-noise ratio parameter, which suggests that selecting a mediocre regularization parameter is often suboptimal. The analysis is applied to three applications, including random, band-limited, and multiple-sampled graph signals. Experiments on synthetic and real-world graphs demonstrate near-optimal performance of the established analysis.
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems

In real-world classification tasks, each class often comprises multiple finer-grained "subclasses." As the subclass labels are frequently unavailable, models trained using only the coarser-grained class labels often exhibit highly variable performance across different subclasses. This phenomenon, known as hidden stratification, has important consequences for models deployed in safety-critical applications such as medicine. We propose GEORGE, a method to both measure and mitigate hidden stratification even when subclass labels are unknown. We first observe that unlabeled subclasses are often separable in the feature space of deep models, and exploit this fact to estimate subclass labels for the training data via clustering techniques. We then use these approximate subclass labels as a form of noisy supervision in a distributionally robust optimization objective. We theoretically characterize the performance of GEORGE in terms of the worst-case generalization error across any subclass. We empirically validate GEORGE on a mix of real-world and benchmark image classification datasets, and show that our approach boosts worst-case subclass accuracy by up to 22 percentage points compared to standard training techniques, without requiring any information about the subclasses.
Ground state and excitations of disordered boson systems

After an introduction to the dirty bosons problem, we present a gaussian theory for the ground state and excitations. This approach is physically equivalent to the Bogoliubov approximation. We find that ODLRO can be destroyed with sufficient disorder. The density of states and localization of the elementary excitations are discussed.
Time-dependent Models for the Afterglows of Massive Black Hole Mergers

The Laser Interferometer Space Antenna (LISA) will detect gravitational wave signals from coalescing pairs of massive black holes (MBHs) in the total mass range (105-107)/(1 + z) M ☉ out to cosmological distances. Identifying and monitoring the electromagnetic (EM) counterparts of these events would enable cosmological studies and offer new probes of gas physics around well-characterized MBHs. Milosavljevic & Phinney proposed that a circumbinary disk around a binary of mass ~106 M ☉ will emit an accretion-powered X-ray afterglow approximately one decade after the gravitational wave event. We revisit this scenario by using Green's function solutions to calculate the temporal viscous evolution and the corresponding EM signature of the circumbinary disk. Our calculations suggest that an EM counterpart may become observable as a rapidly brightening source soon after the merger, i.e., several years earlier than previously thought. The afterglow can reach super-Eddington luminosities without violating the local Eddington flux limit. It is emitted in the soft X-ray by the innermost circumbinary disk, but it may be partially reprocessed at optical and infrared frequencies. We also find that the spreading disk becomes increasingly geometrically thick close to the central object as it evolves, indicating that the innermost flow could become advective and radiatively inefficient, and generate a powerful outflow. We conclude that the mergers of MBHs detected by LISA offer unique opportunities for monitoring, on humanly tractable timescales, the viscous evolution of accretion flows and the emergence of outflows around MBHs with precisely known masses, spins, and orientations.
Are free Android app security analysis tools effective in detecting known vulnerabilities

Increasing interest in securing the Android ecosystem has spawned numerous efforts to assist app developers in building secure apps. These efforts have resulted in tools and techniques capable of detecting vulnerabilities and malicious behaviors in apps. However, there has been no evaluation of the effectiveness of these tools and techniques in detecting known vulnerabilities. The absence of such evaluations puts app developers at a disadvantage when choosing security analysis tools to secure their apps. In this regard, we evaluated the effectiveness of vulnerability detection tools for Android apps. We reviewed 64 tools and empirically evaluated 14 vulnerability detection tools against 42 known unique vulnerabilities captured by Ghera benchmarks, which are composed of both vulnerable and secure apps. Of the 20 observations from the evaluation, the main observation is existing vulnerability detection tools for Android apps are very limited in their ability to detect known vulnerabilities — all of the evaluated tools together could only detect 30 of the 42 known unique vulnerabilities. More effort is required if security analysis tools are to help developers build secure apps. We hope the observations from this evaluation will help app developers choose appropriate security analysis tools and persuade tool developers and researchers to identify and address limitations in their tools and techniques. We also hope this evaluation will catalyze or spark a conversation in the software engineering and security communities to require a more rigorous and explicit evaluation of security analysis tools and techniques.
Experimental demonstration of array-level learning with phase change synaptic devices

The computational performance of the biological brain has long attracted significant interest and has led to inspirations in operating principles, algorithms, and architectures for computing and signal processing. In this work, we focus on hardware implementation of brain-like learning in a brain-inspired architecture. We demonstrate, in hardware, that 2-D crossbar arrays of phase change synaptic devices can achieve associative learning and perform pattern recognition. Device and array-level studies using an experimental 10×10 array of phase change synaptic devices have shown that pattern recognition is robust against synaptic resistance variations and large variations can be tolerated by increasing the number of training iterations. Our measurements show that increase in initial variation from 9 % to 60 % causes required training iterations to increase from 1 to 11.
A k-Hop Collaborate Game Model: Adaptive Strategy to Maximize Total Revenue

In online social networks (OSNs), interpersonal communication and information sharing are happening all the time, and it is real time. If a user initiates an activity (game) in OSNs, she will cause a certain impact on her friendship circle naturally, namely, some users in this initiator’s friendship circle will be attracted to participate in this activity. Based on such a fact, we design a k-hop collaborated game model, which means that an activity initiated by a user can only influence those users whose distance is within k-hop from this initiator. We introduce the problem of revenue maximization under k-hop collaborate game (RMKCG), which identifies a limited number of initiators in order to obtain revenue as much as possible. The collaborated game model describes in detail how to quantify revenue and the logic behind it. We do not know how many followers would be attracted by activity in advance, and thus, we need to adopt an adaptive strategy, where the decision who is the next potential initiator depends on the results of past decisions. The adaptive RMKCG problem can be considered as a new stochastic optimization problem, and we prove it is NP-hard, adaptive monotone, but not adaptive submodular. But in some special cases, it is adaptive submodular, and thus, we design an adaptive greedy algorithm. Due to the complexity of our model, it is hard to compute the marginal gain for each candidate user, and then we propose an efficient computational method to estimate it. The effectiveness and correctness of our algorithms are validated by heavy simulation on real-world graphs finally.
The lack of rotation in a moving right angle lever

The absence of any tendency towards rotation in a moving right angle lever is given a simple explanation.
Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO

AbstractWe propose a Bayesian procedure for simultaneous variable and covariance selection using continuous spike-and-slab priors in multivariate linear regression models where q possibly correlate...
XMM-NEWTON AND CHANDRA OBSERVATIONS OF THE EJECTA-DOMINATED MIXED-MORPHOLOGY GALACTIC SUPERNOVA REMNANT G352.7–0.1

We present a spatial and spectral X-ray analysis of the Galactic supernova remnant (SNR) G352.7–0.1 using archival data from observations made with the XMM-Newton X-ray Observatory and the Chandra X-ray Observatory. Prior X-ray observations of this SNR had revealed a thermal center-filled morphology that contrasts with a shell-like radio morphology, thus establishing G352.7–0.1 as a member of the class of Galactic SNRs known as mixed-morphology SNRs (MMSNRs). Our study confirms that the X-ray emission comes from the SNR interior and must be ejecta dominated. Spectra obtained with XMM-Newton may be fit satisfactorily with a single thermal component (namely a non-equilibrium ionization component with enhanced abundances of silicon and sulfur). In contrast, spectra extracted by Chandra from certain regions of the SNR cannot always be fit by a single thermal component. For those regions, a second thermal component with solar abundances or two thermal components with different temperatures and thawed silicon and sulfur abundances (respectively) can generate a statistically acceptable fit. We argue that the former scenario is more physically plausible: on the basis of parameters of our spectral fits, we calculate physical parameters including X-ray emitting mass (∼45 M {sub ☉} for solar abundances). We find no evidence for overionizationmore » in the X-ray emitting plasma associated with the SNR: this phenomenon has been seen in other MMSNRs. We have conducted a search for a neutron star within the SNR by using a hard (2-10 keV) Chandra image but could not identify a firm candidate. We also present (for the first time) the detection of infrared emission from this SNR as detected at 24 μm by the MIPS on board Spitzer. Finally, we discuss the properties of G352.7–0.1 in the context of other ejecta-dominated MMSNRs.« less
Computing indicators of Radford algebras

We compute higher Frobenius-Schur indicators of Radford algebras in positive characteristic and find minimal polynomials of these linearly recursive sequences. As a result of Kashina, Montgomery and Ng, we obtain gauge invariants for the monoidal categories of representations of Radford algebras.
Average Peak Age-of-Information Minimization in UAV-Assisted IoT Networks

Motivated by the need to ensure timely delivery of information (e.g., status updates) in the Internet-of-Things (IoT) paradigm, this paper investigates the role of an unmanned aerial vehicle (UAV) as a mobile relay to minimize the average peak age-of-information for a source–destination pair. For this setup, we formulate an optimization problem to jointly optimize the UAV's flight trajectory as well as energy and service time allocations for packet transmissions. In order to solve this non-convex problem, we propose an efficient iterative algorithm and establish its convergence analytically. Closed-form solutions for some sub-problems are also provided. One of the sub-problems we solve in this procedure is to jointly optimize the energy and service time allocations for a given trajectory of the UAV. This problem is of interest on its own right because in some cases we may not be able to alter the UAV's trajectory based on the locations of the IoT devices (especially when its primary mission is something else). Our numerical results quantify the gains that can be achieved by additionally optimizing the UAV's trajectory.
Laboratory and Tentative Interstellar Detection of Trans-Methyl Formate Using the Publicly Available Green Bank Telescope Primos Survey

The rotational spectrum of the higher-energy trans-conformational isomer of methyl formate has been assigned for the first time using several pulsed-jet Fourier transform microwave spectrometers in the 6-60 GHz frequency range. This species has also been sought toward the Sagittarius B2(N) molecular cloud using the publicly available PRIMOS survey from the Green Bank Telescope. We detect seven absorption features in the survey that coincide with laboratory transitions of trans-methyl formate, from which we derive a column density of 3.1 (+2.6, –1.2) × 1013 cm–2 and a rotational temperature of 7.6 ± 1.5 K. This excitation temperature is significantly lower than that of the more stable cis conformer in the same source but is consistent with that of other complex molecular species recently detected in Sgr B2(N). The difference in the rotational temperatures of the two conformers suggests that they have different spatial distributions in this source. As the abundance of trans-methyl formate is far higher than would be expected if the cis and trans conformers are in thermodynamic equilibrium, processes that could preferentially form trans-methyl formate in this region are discussed. We also discuss measurements that could be performed to make this detection more certain. This manuscript demonstrates how publicly available broadband radio astronomical surveys of chemically rich molecular clouds can be used in conjunction with laboratory rotational spectroscopy to search for new molecules in the interstellar medium.
Boosting in the presence of outliers: adaptive classification with non-convex loss functions

This article examines the role and the efficiency of nonconvex loss functions for binary classification problems. In particular, we investigate how to design adaptive and effective boosting algorit...
Blow-up in Manifolds with Generalized Corners

We construct a functor from the category of manifolds with generalized corners to the category of complexes of toric monoids, and for every `refinement' of the complex associated to a manifold, we show there is a unique `blow-up', i.e., a new manifold mapping to the original one, which satisfies a universal property and whose complex realizes the refinement. This was inspired in part by the work of Gillam and Molcho, though we work with manifolds with generalized corners, as developed by Joyce, which have embedded boundary faces, for which the appropriate objects (i.e., complexes of monoids) are simpler than they would be otherwise (i.e., monoidal spaces in the sense of Kato).
Modeling Indications of Technology in Planetary Transit Light Curves-Dark-side Illumination

We analyze potential effects of an extraterrestrial civilization’s use of orbiting mirrors to illuminate the dark side of a synchronously rotating planet on planetary transit light curves. Previous efforts to detect civilizations based on side effects of planetary-scale engineering have focused on structures affecting the host star output (e.g., Dyson spheres). However, younger civilizations are likely to be less advanced in their engineering efforts, yet still capable of sending small spacecraft into orbit. Since M dwarfs are the most common type of star in the solar neighborhood, it seems plausible that many of the nearest habitable planets orbit dim, low-mass M stars, and will be in synchronous rotation. Logically, a civilization evolving on such a planet may be inspired to illuminate their planet’s dark side by placing a single large mirror at the L2 Lagrangian point, or launching a fleet of small thin mirrors into planetary orbit. We briefly examine the requirements and engineering challenges of such a collection of orbiting mirrors, then explore their impact on transit light curves. We incorporate stellar limb darkening and model a simplistic mirror fleet’s effects for transits of Earth-like (R = 0.5 to 2 ) planets which would be synchronously rotating for orbits within the habitable zone of their host star. Although such an installation is undetectable in Kepler data, the James Webb Space Telescope will provide the sensitivity necessary to detect a fleet of mirrors orbiting Earth-like habitable planets around nearby stars.
THE MASSIVE STAR POPULATION IN M101. II. SPATIAL VARIATIONS IN THE RECENT STAR FORMATION HISTORY

We investigate star formation history (SFH) as a function of radius in M101 using archival Hubble Space Telescope Advanced Camera for Surveys photometry. We derive the SFH from the resolved stellar populations in five 2' wide annuli. Binning the SFH into time frames corresponding to stellar populations traced by Hα, far-ultraviolet, and near-ultraviolet emission, we find that the fraction of stellar populations young enough to contribute in Hα is 15%-35% in the inner regions, compared to less than 5% in the outer regions. This provides a sufficient explanation for the lack of Hα emission at large radii. We also model the blue to red supergiant ratio in our five annuli, examine the effects that a metallicity gradient and variable SFH have on the predicted ratios, and compare to the observed values. We find that the radial behavior of our modeled blue to red supergiant ratios is highly sensitive to both spatial variations in the SFH and metallicity. Incorporating the derived SFH into modeled ratios, we find that we are able to reproduce the observed values at large radii (low metallicity), but at small radii (high metallicity) the modeled and observed ratios are discrepant.
Anisotropic thermal transport in bulk hexagonal boron nitride

Hexagonal boron nitride (h-BN) has received great interest in recent years as a wide band-gap analog of graphene-derived systems along with its potential in a wide range of applications, for example, as the dielectric layer for graphene devices. However, the thermal transport properties of h-BN, which can be critical for device reliability and functionality, are little studied both experimentally and theoretically. The primary challenge in the experimental measurements of the anisotropic thermal conductivity of h-BN is that typically the sample size of h-BN single crystals is too small for conventional measurement techniques, as state-of-the-art technologies synthesize h-BN single crystals with lateral sizes only up to 2.5 mm and thicknesses up to 200 \ensuremath{\mu}m. Recently developed time-domain thermoreflectance (TDTR) techniques are suitable to measure the anisotropic thermal conductivity of such small samples, as it only requires a small area of $50\ifmmode\times\else\texttimes\fi{}50\phantom{\rule{0.16em}{0ex}}\ensuremath{\mu}{\mathrm{m}}^{2}$ for the measurements. Accurate atomistic modeling of thermal transport in bulk h-BN is also challenging due to the highly anisotropic layered structure. Here we conduct an integrated experimental and theoretical study on the anisotropic thermal conductivity of bulk h-BN single crystals over the temperature range of 100--500 K using TDTR measurements with multiple modulation frequencies and a full-scale numerical calculation of the phonon Boltzmann transport equation starting from first principles. Our experimental and numerical results compare favorably for both the in-plane and the through-plane thermal conductivities. We observe unusual temperature dependence and phonon-isotope scattering in the through-plane thermal conductivity of h-BN and elucidate their origins. This paper not only provides an important benchmark of the anisotropic thermal conductivity of h-BN, but also develops fundamental insight into the nature of phonon transport in this highly anisotropic layered material.
Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards

We study an extension of the classic stochastic multi-armed bandit problem which involves multiple plays and Markovian rewards in the rested bandits setting. In order to tackle this problem we consider an adaptive allocation rule which at each stage combines the information from the sample means of all the arms, with the Kullback-Leibler upper confidence bound of a single arm which is selected in round-robin way. For rewards generated from a one-parameter exponential family of Markov chains, we provide a finite-time upper bound for the regret incurred from this adaptive allocation rule, which reveals the logarithmic dependence of the regret on the time horizon, and which is asymptotically optimal. For our analysis we devise several concentration results for Markov chains, including a maximal inequality for Markov chains, that may be of interest in their own right. As a byproduct of our analysis we also establish asymptotically optimal, finite-time guarantees for the case of multiple plays, and i.i.d. rewards drawn from a one-parameter exponential family of probability densities. Additionally, we provide simulation results that illustrate that calculating Kullback-Leibler upper confidence bounds in a round-robin way, is significantly more efficient than calculating them for every arm at each round, and that the expected regrets of those two approaches behave similarly.