cssi/SciSciGPT-SciSciNet huggingface dataset:
Sparse general Wigner-type matrices: Local law and eigenvector delocalization

We prove a local law and eigenvector delocalization for general Wigner-type matrices. Our methods allow us to get the best possible interval length and optimal eigenvector delocalization in the dense case, and the first results of such kind for the sparse case down to p=g(n)log⁡nn with g(n) → ∞. We specialize our results to the case of the stochastic block model, and we also obtain a local law for the case when the number of classes is unbounded.
Fermion induced SU( N) Yang-Mills theory

Abstract We investigate the gauge interaction induced by heavy fermions using both dimensional and lattice regularization. We study the condition under which heavy fermions induce a continuum gauge theory.
The challenge to large optical telescopes from x-ray astronomy

In the ROSAT era of the mid-1990’s, the problems facing deep X-ray surveys could be largely solved with 10 m class telescopes. In the first decade of this new millennium, with X-ray telescopes such as the Chandra X-ray Observatory and XMM-Newton in operation, deep X-ray surveys are challenging 10 m telescopes. For example, in the Chandra Deep Field surveys, � 30% of the X-ray sources have optical counterparts fainter than R = 25 (I = 24). This paper reviews current progress with 6–10 m class telescopes in following up sources discovered in deep X-ray surveys, including results from several X-ray surveys which have depended on telescopes such as Keck, VLT and HET. Topics include the prospects for detecting extreme redshift (z > 6) quasars and the first detections of normal and starburst galaxies at cosmologically interesting distances in the X-ray band. X-ray astronomy can significantly bolster the science case for the next generation of large aperture (30– 100 m) ground-based telescopes and has already provided targets for these large telescopes through the Chandra and XMM-Newton surveys. The next generation of X-ray telescopes will continue to challenge large optical telescopes; this review concludes with a discussion of prospects from new X-ray missions coming into operation on a 5–30 year timescale.
MAESTRO: AN ADAPTIVE LOW MACH NUMBER HYDRODYNAMICS ALGORITHM FOR STELLAR FLOWS

Many astrophysical phenomena are highly subsonic, requiring specialized numerical methods suitable for long-time integration. In a series of earlier papers we described the development of MAESTRO, a low Mach number stellar hydrodynamics code that can be used to simulate long-time, low-speed flows that would be prohibitively expensive to model using traditional compressible codes. MAESTRO is based on an equation set derived using low Mach number asymptotics; this equation set does not explicitly track acoustic waves and thus allows a significant increase in the time step. MAESTRO is suitable for two- and three-dimensional local atmospheric flows as well as three-dimensional full-star flows. Here, we continue the development of MAESTRO by incorporating adaptive mesh refinement (AMR). The primary difference between MAESTRO and other structured grid AMR approaches for incompressible and low Mach number flows is the presence of the time-dependent base state, whose evolution is coupled to the evolution of the full solution. We also describe how to incorporate the expansion of the base state for full-star flows, which involves a novel mapping technique between the one-dimensional base state and the Cartesian grid, as well as a number of overall improvements to the algorithm. We examine the efficiency and accuracy of our adaptive code, and demonstrate that it is suitable for further study of our initial scientific application, the convective phase of Type Ia supernovae.
Handling Attrition in Longitudinal Studies: The Case for Refreshment Samples

Panel studies typically suffer from attrition, which reduces sample size and can result in biased inferences. It is impossible to know whether or not the attrition causes bias from the observed panel data alone. Refreshment samples—new, randomly sampled respondents given the questionnaire at the same time as a subsequent wave of the panel—offer information that can be used to diagnose and adjust for bias due to attrition. We review and bolster the case for the use of refreshment samples in panel studies. We include examples of both a fully Bayesian approach for analyzing the concatenated panel and refreshment data, and a multiple imputation approach for analyzing only the original panel. For the latter, we document a positive bias in the usual multiple imputation variance estimator. We present models appropriate for three waves and two refreshment samples, including nonterminal attrition. We illustrate the three-wave analysis using the 2007–2008 Associated Press–Yahoo! News Election Poll.
Hypothesis setting and order statistic for robust genomic meta-analysis

Meta-analysis techniques have been widely developed and applied in genomic applications, especially for combining multiple transcriptomic studies. In this paper, we propose an order statistic of p-values (rth ordered p-value, rOP) across combined studies as the test statistic. We illustrate different hypothesis settings that detect gene markers differentially expressed (DE) "in all studies", "in the majority of studies", or "in one or more studies", and specify rOP as a suitable method for detecting DE genes "in the majority of studies". We develop methods to estimate the parameter r in rOP for real applications. Statistical properties such as its asymptotic behavior and a one-sided testing correction for detecting markers of concordant expression changes are explored. Power calculation and simulation show better performance of rOP compared to classical Fisher's method, Stouffer's method, minimum p-value method and maximum p-value method under the focused hypothesis setting. Theoretically, rOP is found connected to the naive vote counting method and can be viewed as a generalized form of vote counting with better statistical properties. The method is applied to three microarray meta-analysis examples including major depressive disorder, brain cancer and diabetes. The results demonstrate rOP as a more generalizable, robust and sensitive statistical framework to detect disease-related markers.
Fast counting with tensor networks

We introduce tensor network contraction algorithms for counting satisfying assignments of constraint satisfaction problems (#CSPs). We represent each arbitrary #CSP formula as a tensor network, whose full contraction yields the number of satisfying assignments of that formula, and use graph theoretical methods to determine favorable orders of contraction. We employ our heuristics for the solution of #P-hard counting boolean satisfiability (#SAT) problems, namely monotone #1-in-3SAT and #Cubic-Vertex-Cover, and find that they outperform state-of-the-art solvers by a significant margin.
$(0,2)$-deformations and the $G$-Hilbert scheme

We study first order deformations of the tangent sheaf of resolutions of Calabi-Yau threefolds that are of the form $\mathbb{C}^3/Z_r$, focusing on the cases where the orbifold has an isolated singularity. We prove a lower bound on the number of deformations for any crepant resolution of this orbifold. We show that this lower bound is achieved when the resolution used is the G-Hilbert scheme, and note that this lower bound can be found using methods from string theory. These methods lead us to a new way to construct the G-Hilbert scheme using the singlet count.
The Lerch Zeta function III. Polylogarithms and special values

This paper studies algebraic and analytic structures associated with the Lerch zeta function, complex variables viewpoint taken in part II. The Lerch transcendent $$\Phi (s,z,c) := \sum _{n=0}^\infty \frac{z^n}{ (n+c)^{s}}$$ is obtained from the Lerch zeta function $$\zeta (s, a, c)$$ by the change of variable $$z = e^{2 \pi i a}$$ . We show that it analytically continues to a maximal domain of holomorphy in three complex variables (s, z, c), as a multivalued function defined over the base manifold $${\mathbb C}\times ({\mathbb P}^{1} ({\mathbb C}) {\setminus } \{0, 1, \infty \} )\times ( {\mathbb C}{\setminus } {\mathbb Z})$$ and compute the monodromy functions describing the multivaluedness. For positive integer values $$s=m$$ and $$c=1$$ this function is closely related to the classical m-th order polylogarithm $$Li_{m}(z)$$ . We study its behavior as a function of two variables (z, c) for “special values” where $$s=m$$ is an integer. For $$m \ge 1$$ we show that it is a one-parameter deformation of $$Li_{m}(z)$$ , which satisfies a linear ODE, depending on $$c \in {\mathbb C}$$ , of order $$m+1$$ of Fuchsian type on the Riemann sphere. We determine the associated $$(m+1)$$ -dimensional monodromy representation, which is a non-algebraic deformation of the monodromy of $$Li_m(z)$$ .
MHD Equilibria and Triggers for Prominence Eruption

Magneto-hydrodynamic (MHD) simulations of the emergence of twisted magnetic flux tubes from the solar interior into the corona are discussed to illustrate how twisted and sheared coronal magnetic structures (with free magnetic energy), capable of driving filament eruptions, can form in the corona in emerging active regions. Several basic mechanisms that can disrupt the quasi-equilibrium coronal structures and trigger the release of the stored free magnetic energy are discussed. These include both ideal processes such as the onset of the helical kink instability and the torus instability of a twisted coronal flux rope structure and the non-ideal process of the onset of fast magnetic reconnections in current sheets. Representative MHD simulations of the non-linear evolution involving these mechanisms are presented.
Revisiting the saddle-point method of Perron

Perron's saddle-point method gives a way to find the complete asymptotic expansion of certain integrals that depend on a parameter going to infinity. We give two proofs of the key result. The first is a reworking of Perron's original proof, showing the clarity and simplicity that has been lost in some subsequent treatments. The second proof extends the approach of Olver which is based on Laplace's method. New results include more precise error terms and bounds for the expansion coefficients. We also treat Perron's original examples in greater detail and give a new application to the asymptotics of Sylvester waves.
Some observations on variational elasticity and its application to plates and membranes

Energies and equilibrium equations for thin elastic plates are discussed, with emphasis on several issues pertinent to recent approaches in soft condensed matter. Consequences of choice of basis, choice of invariant strain measures, and of approximating material energies as purely geometric in nature are detailed. Ambiguities in the definitions of energies based on small-strain expansions, and in a typical informal process of dimensional reduction, are noted. A simple example serves to demonstrate that a commonly used bending energy has undesirable features, and it is suggested that a new theory based on Biot strains be developed. A compact form of the variation of a plate energy is presented. Throughout, the divergence form of equations is emphasized. An appendix relates the naive approach adopted in the main text to standard quantities in continuum mechanics.
Block-simultaneous direction method of multipliers: a proximal primal-dual splitting algorithm for nonconvex problems with multiple constraints

We introduce a generalization of the linearized Alternating Direction Method of Multipliers to optimize a real-valued function f of multiple arguments with potentially multiple constraints $$g_\circ$$ on each of them. The function f may be nonconvex as long as it is convex in every argument, while the constraints $$g_\circ$$ need to be convex but not smooth. If f is smooth, the proposed Block-Simultaneous Direction Method of Multipliers (bSDMM) can be interpreted as a proximal analog to inexact coordinate descent methods under constraints. Unlike alternative approaches for joint solvers of multiple-constraint problems, we do not require linear operators $${{\mathsf {L}}}$$ of a constraint function $$g({{\mathsf {L}}}\ \cdot )$$ to be invertible or linked between each other. bSDMM is well-suited for a range of optimization problems, in particular for data analysis, where f is the likelihood function of a model and $${{\mathsf {L}}}$$ could be a transformation matrix describing e.g. finite differences or basis transforms. We apply bSDMM to the Non-negative Matrix Factorization task of a hyperspectral unmixing problem and demonstrate convergence and effectiveness of multiple constraints on both matrix factors. The algorithms are implemented in python and released as an open-source package.
Lorentz Violation in Extra Dimensions

In theories with extra dimensions it is well known that the Lorentz invariance of the D = 4+n-dimensional spacetime is lost due to the compactified nature of the n dimensions leaving invariance only in 4d. In such theories other sources of Lorentz violation may exist associated with the physics that initiated the compactification process at high scales. Here we consider the possibility of capturing some of this physics by analyzing the higher dimensional analog of the model of Colladay and Kostelecky. In that scenario a complete set of Lorentz violating operators arising from spontaneous Lorentz violation, that are not obviously Planck-scale suppressed, are added to the Standard Model action. Here we consider the influence of the analogous set of operators which break Lorentz invariance in 5d within the Universal Extra Dimensions picture. We show that such operators can greatly alter the anticipated Kaluza-Klein(KK) spectra, induce electroweak symmetry breaking at a scale related to the inverse compactification radius, yield sources of parity violation in, e.g., 4d QED/QCD and result in significant violations of KK-parity conservation produced by fermion Yukawa couplings, thus destabilizing the lightest KK particle. LV in 6d is briefly discussed.
Block Oriented Programming: Automating Data-Only Attacks

With the widespread deployment of Control-Flow Integrity (CFI), control-flow hijacking attacks, and consequently code reuse attacks, are significantly more difficult. CFI limits control flow to well-known locations, severely restricting arbitrary code execution. Assessing the remaining attack surface of an application under advanced control-flow hijack defenses such as CFI and shadow stacks remains an open problem. We introduce BOPC, a mechanism to automatically assess whether an attacker can execute arbitrary code on a binary hardened with CFI/shadow stack defenses. BOPC computes exploits for a target program from payload specifications written in a Turing-complete, high-level language called SPL that abstracts away architecture and program-specific details. SPL payloads are compiled into a program trace that executes the desired behavior on top of the target binary. The input for BOPC is an SPL payload, a starting point (e.g., from a fuzzer crash) and an arbitrary memory write primitive that allows application state corruption. To map SPL payloads to a program trace, BOPC introduces Block Oriented Programming (BOP), a new code reuse technique that utilizes entire basic blocks as gadgets along valid execution paths in the program, i.e., without violating CFI or shadow stack policies. We find that the problem of mapping payloads to program traces is NP-hard, so BOPC first reduces the search space by pruning infeasible paths and then uses heuristics to guide the search to probable paths. BOPC encodes the BOP payload as a set of memory writes. We execute 13 SPL payloads applied to 10 popular applications. BOPC successfully finds payloads and complex execution traces -- which would likely not have been found through manual analysis -- while following the target's Control-Flow Graph under an ideal CFI policy in 81% of the cases.
ANALYTIC MODELS FOR ALBEDOS, PHASE CURVES, AND POLARIZATION OF REFLECTED LIGHT FROM EXOPLANETS

New observational facilities are becoming increasingly capable of observing reflected light from transiting and directly imaged extrasolar planets. In this study, we provide an analytic framework to interpret observed phase curves, geometric albedos, and polarization of giant planet atmospheres. We compute the observables for non-conservative Rayleigh scattering in homogeneous semi-infinite atmospheres using both scalar and vector formalisms. In addition, we compute phase curves and albedos for Lambertian, isotropic, and anisotropic scattering phase functions. We provide analytic expressions for geometric albedos and spherical albedos as a function of the scattering albedo for Rayleigh scattering in semi-infinite atmospheres. Given an observed geometric albedo our prescriptions can be used to estimate the underlying scattering albedo of the atmosphere, which in turn is indicative of the scattering and absorptive properties of the atmosphere. We also study the dependence of polarization in Rayleigh scattering atmospheres on the orbital parameters of the planet-star system, particularly on the orbital inclination. We show how the orbital inclination of non-transiting exoplanets can be constrained from their observed polarization parameters. We consolidate the formalism, solution techniques, and results from analytic models available in the literature, often scattered in various sources, and present a systematic procedure to compute albedos, phase curves, and polarization of reflected light.
Signed-bit representations of real numbers

The signed-bit representation of real numbers is like the binary repre- sentation, but in addition to 0 and 1 you can also use 1. It lends itself especially well to the constructive (intuitionistic) theory of the real numbers. The first part of the paper develops and studies the signed-bit equivalents of three common notions of a real number: Dedekind cuts, Cauchy sequences, and regular sequences. This theory is then applied to homomorphisms of Riesz spaces into R. 2000 Mathematics Subject Classification 03F60 (primary); 26E40, 46S30 (sec- ondary)
On flux quantization in M-theory and the effective action

The quantization law for the antisymmetric tensor field of M-theory contains a gravitational contribution not known previously. When it is included, the low energy effective action of M-theory, including one-loop and Chern-Simons contributions, is well defined. The relation of M-theory to the E8 × E8 heterotic string greatly facilitates the analysis.
Analytic and Monte Carlo studies of jets with heavy mesons and quarkonia

We study jets with identified hadrons in which a family of jet-shape variables called angularities are measured, extending the concept of fragmenting jet functions (FJFs) to these observables. FJFs determine the fraction of energy, z, carried by an identified hadron in a jet with angularity, τ a . The FJFs are convolutions of fragmentation functions (FFs), evolved to the jet energy scale, with perturbatively calculable matching coefficients. Renormalization group equations are used to provide resummed calculations with next-to-leading logarithm prime (NLL’) accuracy. We apply this formalism to two-jet events in e + e − collisions with B mesons in the jets, and three-jet events in which a J/ψ is produced in the gluon jet. In the case of B mesons, we use a phenomenological FF extracted from e + e − collisions at the Z 0 pole evaluated at the scale μ = m b . For events with J/ψ, the FF can be evaluated in terms of Non-Relativistic QCD (NRQCD) matrix elements at the scale μ = 2m c . The z and τ a distributions from our NLL’ calculations are compared with predictions from monte carlo event generators. While we find consistency between the predictions for B mesons and the J/ψ distributions in τ a , we find the z distributions for J/ψ differ significantly. We describe an attempt to merge PYTHIA showers with NRQCD FFs that gives good agreement with NLL’ calculations of the z distributions.
Bouncing cosmology made simple

We introduce the ‘wedge diagram’, an intuitive way to illustrate how cosmological models with a classical (non-singular) bounce generically resolve fundamental problems in cosmology. These include the well-known horizon, flatness, and inhomogeneity problems; the small tensor-to-scalar ratio observed in the cosmic microwave background; the low entropy at the beginning of a hot, expanding phase; and the avoidance of quantum runaway. The same diagrammatic approach can be used to compare with other cosmological scenarios.
2014 update of the discoveries of nuclides

The 2014 update of the discovery of nuclide project is presented. Only six new nuclides were observed for the first time in 2014 while the assignments of 17 other nuclides were revised. In addition, for another 14 nuclides the laboratories where they were discovered were reassigned.
Oxytocin Administration Increases Proactive Control in Men with Overweight or Obesity: A Randomized, Double-Blind, Placebo-Controlled Crossover Study

Objective Preclinical and clinical evidence suggests that oxytocin administration decreases food intake and weight. The mechanisms underlying the anorexigenic effects of oxytocin in humans are unknown but critical to study to consider oxytocin as a neurohormonal weight loss treatment. Complementing ongoing research into metabolic and food motivation mechanisms of oxytocin, this study hypothesized that in humans, oxytocin improves cognitive control over behavior. Methods In a randomized, double-blind, placebo-controlled crossover study of 24-IU single-dose intranasal oxytocin, 10 men with overweight or obesity completed a stop-signal task assessing ability and strategy to suppress behavioral impulses, in which they performed a choice-reaction task (go task) but had to withhold their response when prompted (stop task). It was hypothesized that oxytocin would improve suppression of behavioral impulses. Results After receiving oxytocin, compared with placebo, participants showed increased reaction times in the go task (mean [M] = 936 milliseconds vs. 833 millseconds; P = 0.012; 95% CI: 29 to 178) and displayed fewer stop errors (M = 36.41% vs. 41.15%; P = 0.049; 95% CI: -9.43% to -0.03%). Conclusions Oxytocin triggers increased proactive control over behavior. Future studies need to further characterize the impact of oxytocin on cognitive control and investigate its potential role in the anorexigenic effects of oxytocin in human obesity.
Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methods.

Accurate identification of acute ischemic stroke (AIS) patient cohorts is essential for a wide range of clinical investigations. Automated phenotyping methods that leverage electronic health records (EHRs) represent a fundamentally new approach cohort identification without current laborious and ungeneralizable generation of phenotyping algorithms. We systematically compared and evaluated the ability of machine learning algorithms and case-control combinations to phenotype acute ischemic stroke patients using data from an EHR. Using structured patient data from the EHR at a tertiary-care hospital system, we built and evaluated machine learning models to identify patients with AIS based on 75 different case-control and classifier combinations. We then estimated the prevalence of AIS patients across the EHR. Finally, we externally validated the ability of the models to detect AIS patients without AIS diagnosis codes using the UK Biobank. Across all models, we found that the mean AUROC for detecting AIS was 0.963 ± 0.0520 and average precision score 0.790 ± 0.196 with minimal feature processing. Classifiers trained with cases with AIS diagnosis codes and controls with no cerebrovascular disease codes had the best average F1 score (0.832 ± 0.0383). In the external validation, we found that the top probabilities from a model-predicted AIS cohort were significantly enriched for AIS patients without AIS diagnosis codes (60–150 fold over expected). Our findings support machine learning algorithms as a generalizable way to accurately identify AIS patients without using process-intensive manual feature curation. When a set of AIS patients is unavailable, diagnosis codes may be used to train classifier models.
The impact of 1/f activity and baseline correction on the results and interpretation of time-frequency analyses of EEG/MEG data: A cautionary tale.

Typically, time-frequency analysis (TFA) of electrophysiological data is aimed at isolating narrowband signals (oscillatory activity) from broadband non-oscillatory (1/f) activity, so that changes in oscillatory activity resulting from experimental manipulations can be assessed. A widely used method to do this is to convert the data to the decibel (dB) scale through baseline division and log transformation. This procedure assumes that, for each frequency, sources of power (i.e., oscillations and 1/f activity) scale by the same factor relative to the baseline (multiplicative model). This assumption may be incorrect when signal and noise are independent contributors to the power spectrum (additive model). Using resting-state EEG data from 80 participants, we found that the level of 1/f activity and alpha power are not positively correlated within participants, in line with the additive but not the multiplicative model. Then, to assess the effects of dB conversion on data that violate the multiplicativity assumption, we simulated a mixed design study with one between-subject (noise level, i.e., level of 1/f activity) and one within-subject (signal amplitude, i.e., amplitude of oscillatory activity added onto the background 1/f activity) factor. The effect size of the noise level × signal amplitude interaction was examined as a function of noise difference between groups, following dB conversion. Findings revealed that dB conversion led to the over- or under-estimation of the true interaction effect when groups differing in 1/f levels were compared, and it also led to the emergence of illusory interactions when none were present. This is because signal amplitude was systematically underestimated in the noisier compared to the less noisy group. Hence, we recommend testing whether the level of 1/f activity differs across groups or conditions and using multiple baseline correction strategies to validate results if it does. Such a situation may be particularly common in aging, developmental, or clinical studies.
Linear space string correction algorithm using the Damerau-Levenshtein distance

The Damerau-Levenshtein (DL) distance metric has been widely used in the biological science. It tries to identify the similar region of DNA,RNA and protein sequences by transforming one sequence to the another using the substitution, insertion, deletion and transposition operations. Lowrance and Wagner have developed an O(mn) time O(mn) space algorithm to find the minimum cost edit sequence between strings of length m and n, respectively. In our previous research, we have developed algorithms that run in O(mn) time using only O(s∗min{m,n}+m+n) space, where s is the size of the alphabet comprising the strings, to compute the DL distance as well as the corresponding edit sequence. These are so far the fastest and most space efficient algorithms. In this paper, we focus on the development of algorithms whose asymptotic space complexity is linear. We develop linear space algorithms to compute the Damerau-Levenshtein (DL) distance between two strings and determine the optimal trace (corresponding edit operations.)Extensive experiments conducted on three computational platforms–Xeon E5 2603, I7-x980 and Xeon E5 2695–show that, our algorithms, in addition to using less space, are much faster than earlier algorithms. Besides using less space than the previously known algorithms,significant run-time improvement was seen for our new algorithms on all three of our experimental platforms. On all platforms, our linear-space cache-efficient algorithms reduced run time by as much as 56.4% and 57.4% in respect to compute the DL distance and an optimal edit sequences compared to previous algorithms. Our multi-core algorithms reduced the run time by up to 59.3% compared to the best previously known multi-core algorithms.
Uncertainty quantification and composition optimization for alloy additive manufacturing through a CALPHAD-based ICME framework

During powder production, the pre-alloyed powder composition often deviates from the target composition leading to undesirable properties of additive manufacturing (AM) components. Therefore, we developed a method to perform high-throughput calculation and uncertainty quantification by using a CALPHAD-based ICME framework (CALPHAD: calculations of phase diagrams, ICME: integrated computational materials engineering) to optimize the composition, and took the high-strength low-alloy steel (HSLA) as a case study. We analyzed the process–structure–property relationships for 450,000 compositions around the nominal composition of HSLA-115. Properties that are critical for the performance, such as yield strength, impact transition temperature, and weldability, were evaluated to optimize the composition. With the same uncertainty as to the initial composition, and optimized average composition has been determined, which increased the probability of achieving successful AM builds by 44.7%. The present strategy is general and can be applied to other alloy composition optimization to expand the choices of alloy for additive manufacturing. Such a method also calls for high-quality CALPHAD databases and predictive ICME models.
Magnetic confinement at a boundary approximates specular reflection

We conjecture that for a plasma in a spatial domain with a boundary, the specular reflection effect of the boundary can be approximated by a large magnetic confinement field in the near-boundary region. In this paper, we verify this conjecture for the 1.5D relativistic Vlasov-Maxwell system (RVM) on a bounded domain $\Omega = (0, 1)$ with an external confining magnetic field.
Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-adapting Scheme

Emerging virtual network functions (VNFs) bring new opportunities to network services on the edge within customers' premises. Network services are realized by chained up VNFs, which are called service function chains (SFCs). These services are deployed on commercial edge servers for higher flexibility and scalability. Despite such promises, it is still unclear how to provide highly available and cost-effective SFCs under edge resource limitations and time-varying VNF failures. In this paper, we propose a novel Reliability-aware Adaptive Deployment scheme named RAD to efficiently place and back up SFCs over both the edge and the cloud. Specifically, RAD first deploys SFCs to fully utilize edge resources. It then uses both static backups and dynamic ones created on the fly to guarantee the availability under the resource limitation of edge networks. RAD does not assume failure rates of VNFs but instead strives to find the sweet spot between the desired availability of SFCs and the backup cost. Theoretical performance bounds, extensive simulations, and small-scale experiments highlight that RAD provides significantly higher availability with lower backup costs compared with existing baselines.
How safe is safe enough? Automatic Safety Constraints Boundary Estimation for Decision-Making in Automated Vehicles

The determination of safety assurances for automated driving vehicles is one of the most critical challenges in the industry today. Several behavioral safety models for automated driving have been proposed recently and standards discussions are on the way. In this paper we present a method to automatically explore the performance of automated vehicle (AV) safety models utilizing robustness of Metric Temporal Logic (MTL) specifications as a continuous metric of safety. We present a case study of the Responsibility Sensitive Safety model (RSS), introducing a safety evaluation pipeline based on the CARLA driving simulator, RSS and a set of safety-critical driving scenarios. Our method automatically extracts safety relevant profiles for these scenarios providing practical parametric boundaries for implementation. Furthermore, we evaluate the trade-offs between safety and utility within the safe RSS parameter space through a proposed naturalistic benchmark challenge that we open-sourced. We analyze different RSS parameter configurations including assertive and more conservative settings, extracted by our specification-driven framework. Our results show that while maintaining the safety boundaries, the extracted RSS configuration for assertive driving behavior achieves the highest utility.
Patterns of Patient and Caregiver Mutual Support Connections in an Online Health Community

Online health communities offer the promise of support benefits to users, in particular because these communities enable users to find peers with similar experiences. Building mutually supportive connections between peers is a key motivation for using online health communities. However, a user's role in a community may influence the formation of peer connections. In this work, we study patterns of peer connections between two structural health roles: patient and non-professional caregiver. We examine user behavior in an online health community---CaringBridge.org---where finding peers is not explicitly supported. This context lets us use social network analysis methods to explore the growth of such connections in the wild and identify users' peer communication preferences. We investigated how connections between peers were initiated, finding that initiations are more likely between two authors who have the same role and who are close within the broader communication network. Relationships---patterns of repeated interactions---are also more likely to form and be more interactive when authors have the same role. Our results have implications for the design of systems supporting peer communication, e.g. peer-to-peer recommendation systems.
Runtime Optimization of a CNN Model for Environment Perception

For self driving cars one of the current key technologies are deep neural networks. Especially in camera based environment perception they are absolutely irreplaceable. The currently developed network models are usually executed on high end consumer or server GPUs. Also the verification of the real-time properties is mostly based on these GPUs. However, if these models are to be used in near-series applications, the question arises whether they can also be used on significantly reduced hardware. To address this question, we conduct a case study with a camera based traffic light detection system [1]. Promising optimization techniques are adapted and applied to the model to investigate potential performance gains achievable with these techniques in the context of self driving car environment perception. In particular, the trade-off between quality and speed is to be examined in detail.
What is Right about Bankruptcy Law and Wrong about its Critics

My comments in this paper focus on the papers in thus Symposium by Professors Barry Adler, James Bowers, and Philippe Aghion, Oliver Hart, and John Moore. I argue that the central points of these papers are gravely mistaken because they completely misunderstand the character of the bankruptcy caseload and procedures, they ignore some important purposes of bankruptcy reorganization, and they misstate the success rate for reorganizations. I have chosen these papers for comment for two reasons: they recommend radical changes in bankruptcy law, and they are based on the thinnest knowledge of bankruptcy practice. Incidentally, they also all take an economics approach to law.
Optimal Control of Externalities in the Presence of Income Taxation

A substantial literature examines second-best environmental policy, focusing particularly on how the Pigouvian directive that marginal taxes should equal marginal external harms needs to be modified in light of the preexisting distortion due to labor income taxation. Additional literature is motivated by the possibility that distributive concerns should amend the internalization prescription. It is demonstrated, however, that simple first-best rules – unmodified for labor supply distortion or distribution – are correct in a natural, basic formulation of the problem. Specifically, setting all commodity taxes equal to marginal harms (and subsidies equal to marginal benefits) can generate a Pareto improvement. Likewise, a marginal reform in the direction of the first-best can yield a Pareto improvement. Qualifications and explanations for differences from previous work are also presented.
Risk, return, and dividends

Abstract Using only the definition of returns, together with a transversality assumption, we demonstrate that given a dividend process, any one of three variables—expected return, return volatility, and the price–dividend ratio—completely determines the other two. By parameterizing only one of these processes, common empirical specifications place strong, and sometimes counter-factual, restrictions on the dynamics of the other variables. Our findings lend insight into the nature of the risk–return relation and the predictability of stock returns.
Modeling the Credit Card Revolution: The Role of Debt Collection and Informal Bankruptcy

In the data, most consumer defaults on unsecured credit are informal and the lending industry devotes signicant resources to debt collection. We develop a new theory of credit card lending that takes these two features into account. The two key elements of our model are moral hazard and costly state verication that relies on the use of information technology. We show that the model gives rise to a novel channel through which IT progress can aect outcomes in the credit markets, and argue that this aspect is potentially critical to understand the trends associated with the rapid expansion of credit card borrowing in the 1980s and over the 1990s. Independently, the mechanism of the model helps reconcile the high levels of defaults and indebtedness observed in the US data.
Comparing Alternative Hedge Accounting Standards: Shareholders' Perspective

We study the economic consequences of alternative hedge accounting rules in terms of managerial hedging decisions and wealth effects for shareholders. The rules we consider include the “fair-value” and “cash-flow” hedge accounting methods prescribed by the recent SFAS No. 133. We illustrate that the accounting method used influences the manager's hedge decision. We show that under no-hedge accounting, the hedge choice is different from the optimal economic hedge the firm would make under symmetric and public information. However, under a certain definition of fair-value hedge accounting, the hedging decision preserves the optimal economic hedge. We then demonstrate that long-term and future shareholders prefer a certain definition of fair-value hedge accounting to no-hedge accounting, while short-term shareholders prefer either approach depending on risk preferences and the level of uncertainty. We speculate about circumstances in which a manager would choose not to adopt fair-value hedge accounting when he has the option not to do so.
CORPORATE BANKRUPTCY REORGANIZATIONS: ESTIMATES FROM A BARGAINING MODEL*

This article uses a novel approach to measure the unobserved liquidation value of a firm that relies on the information contained in the allocations that are agreed upon in Chapter 11 negotiations. I estimate a game theoretic model that captures the influence of liquidation value on the equilibrium allocations using a newly collected data set. I find that the liquidation values are higher when the industry conditions are more favorable, and the real interest rates are higher. I use the estimated model to conduct a counterfactual experiment to quantitatively assess the impact of a mandatory liquidation on the equilibrium allocations.
Short Selling and the Weekend Effect for NYSE Securities

Using short-sale transactions data, we examine the relation between short selling and the weekend effect. We do not find that short selling is more abundant on Monday than on Friday, even for stocks that have higher Friday returns. We find that short sellers execute more short-sale volume during the middle of the week, and that the positive correlation between short selling and returns on Monday is greater, on average, than the correlation on the other days of the week. Our results are robust to subsamples of stocks with larger weekend effects and stocks that do not have listed options.
Asymmetry in earnings timeliness and persistence: a simultaneous equations approach

This study addresses simultaneity bias in piecewise linear forms of the earnings-return relation. We specify an overidentified system of simultaneous equations that incorporates both asymmetric earnings timeliness and asymmetric earnings persistence specifications and implement two-stage least squares for this piecewise linear system. Estimation of a system that is piecewise linear in endogenous variables presents several issues that are unprecedented in the accounting literature. Findings provide evidence that the asymmetric timeliness specification is particularly affected by simultaneity and that failing to correct for simultaneity results in coefficient estimates that potentially understate the degree of asymmetric earnings timeliness. Moreover, inferences regarding how conditional conservatism has evolved over time are sensitive to whether OLS or 2SLS coefficients are used as the basis of comparison.
Regularity and cohomology of determinantal thickenings

We consider the ring S=C[xij] of polynomial functions on the vector space Cm×n of complex m×n matrices. We let GL=GLm(C)×GLn(C) and consider its action via row and column operations on Cm×n (and the induced action on S). For every GL-invariant ideal I⊆S and every j⩾0, we describe the decomposition of the modules ExtSj(S/I,S) into irreducible GL-representations. For any inclusion I⊇J of GL-invariant ideals we determine the kernels and cokernels of the induced maps ExtSj(S/I,S)⟶ExtSj(S/J,S). As a consequence of our work, we give a formula for the regularity of the powers and symbolic powers of generic determinantal ideals, and in particular we determine which powers have a linear minimal free resolution. As another consequence, we characterize the GL-invariant ideals I⊆S for which the induced maps ExtSj(S/I,S)⟶HIj(S) are injective. In a different direction we verify that Kodaira vanishing, as described in work of Bhatt–Blickle–Lyubeznik–Singh–Zhang, holds for determinantal thickenings.
Politics of Sectarianism: Rethinking Religion and Politics in the Middle East

Allegations of sectarian violence and discrimination saturate popular and scholarly accounts of developments in the mena region, particularly in the wake of renewed violence in Syria and Iraq. These accounts should sound a warning bell to scholars of religion and politics. The discourse of sectarianism is a modern discourse of religion-in-politics authorized by particular authorities in particular times and places. It relies on a fixed and stable representation of the shifting roles played by that which is named as “religion” or “sect” in politics and society. The complex and often conflicting forces that come together in any given episode of violence or discrimination subvert the stable notions of sectarian motivation and causation that form the bedrock in which such accounts rest. This essay disaggregates and politicizes the discourse of sectarianism, drawing on examples from Egypt, Bahrain, and Israel. It argues for distinguishing between religious difference as construed by those in positions of power, and religious difference as construed and experienced—and at times downplayed or ignored—by individuals and communities that are subjected to, and shaped by, sectarian projects, policies, and narratives.
Now You See it, Now You Don't: Why Do Real Estate Agents Withhold Available Houses from Black Customers?

Potential home buyers may initiate contact with a real estate agent by asking to see a particular advertised house. This paper asks whether an agent's response to such a request depends on the race of the buyer or on whether the house is located in an integrated neighborhood. Like previous research about the causes of housing discrimination, this paper uses data from fair housing audits, a matched-pair technique for comparing the treatment of equally qualified black and white home buyers. However, we shift the focus from differences in the treatment of paired buyers to agent decisions concerning an individual house. Using a sample of all houses seen during the 1989 national Housing Discrimination Study, we estimate a random-effect, multinomial logit model to explain a real estate agent's joint decisions concerning whether to show each house to a black auditor and to a white auditor. We find evidence that agents interpret an initial housing request as an indication of a customer's preferences, but also are...
Applying systems principles to models of social information processing and aggressive behavior in youth

Systems perspectives view development as the product of hierarchically-organized levels of varied life processes that are continually changing and interacting as time passes. This theoretical approach may be of considerable importance to developing research programs in child social cognition, particularly since multilevel, multiprocess models of social information processing and aggressive behavior in youth are still in relatively formative stages. This paper proposes that key systems principles can be conceptually applied to social information-processing models in ways that are critical to furthering future research in social-cognitive foundations of aggressive behavior. Examples of initial applications to current social information-processing models of aggression in childhood are presented. Implications of this theoretical approach for substantive empirical research (e.g., modes of processing) are discussed and directions for methodological design (e.g., computer simulation) are proposed.
Ambiguity and Policy Making: A Cognitive Approach to Reconciling Chevron and Mead

ed from the unsurprising holdings of Chevron and Mead, the two decisions seem to articulate two approaches to judicial deference in the face of agency statutory interpretation and two corresponding rationales explaining why each mode of deference is appropriate to its context. According to Mead, Chevron deference is owed whenever "[i] t is apparent from the agency's generally conferred authority and other statutory circumstances that Congress would expect the agency to be able to speak with the force of law when it addresses ambiguity in the statute or fills a space in the enacted law." 55 In such a case, "[i] f... Congress has not directly addressed the precise question at issue, [but] the statute is silent or ambiguous... the question" is whether "the Administrator's view ... is a reasonable one."56 On the other hand, Mead/Skidmore deference is appropriate, outside the Chevron context, whenever there is value to acknowledging the "specialized experience and broader investigations and information" available to the agency and the importance of uniformity in administrative and judicial understandings of what a national law requires. 57 In those cases, " [t] he weight of [agency] judgment . . .will depend upon the thoroughness evident in its consideration, the validity of its reasoning, its consistency with earlier and later pronouncements, and all those factors which give it power to persuade, if lacking power to control." 58 All of this strikes me, however, as more complicated than is necessary. Indeed, it may be easier for all concerned to look at the judicial review of statutory interpretation not, as the Court seems to say, in terms of qualities embodied in the statutes being inter-