cssi/SciSciGPT-SciSciNet huggingface dataset:
Coinvariant algebras and fake degrees for spin Weyl groups of classical type

The coinvariant algebra of a Weyl group plays a fundamental role in several areas of mathematics. The fake degrees are the graded multiplicities of the irreducible modules of a Weyl group in its coinvariant algebra, and they were computed by Steinberg, Lusztig and Beynon-Lusztig. In this paper we formulate a notion of spin coinvariant algebra for every Weyl group. Then we compute all the spin fake degrees for each classical Weyl group, which are by definition the graded multiplicities of the simple modules of a spin Weyl group in the spin coinvariant algebra. The spin fake degrees for the exceptional Weyl groups are given in a sequel.
On Hypergeometric Series Reductions from Integral Representations, the KAMPÉ de FÉRIET Function and Elsewhere

Single variable hypergeometric functions pFq arise in connection with the power series solution of the Schrodinger equation or in the summation of perturbation expansions in quantum mechanics. For these applications, it is of interest to obtain analytic expressions, and we present the reduction of a number of cases of pFp and p+1Fp, mainly for p=2 and p=3. These and related series have additional applications in quantum and statistical physics and chemistry.
Have we detected patchy reionization in quasar spectra

The Lyα forest at z 5.5 shows strong scatter in the mean transmission even when smoothed over extremely large spatial scales, 50 Mpc h-1. This has been interpreted as a signature of strongly fluctuating radiation fields or patchy reionization. To test this claim, we calculate the scatter arising solely from density fluctuations, assuming a uniform ionizing background, via analytic arguments and simulations. This scatter alone is comparable to that observed. It rises steeply with redshift and is of order unity by z ~ 6, even on ~50 Mpc h-1 scales. This arises because (1) at z ~ 6, transmission spectra, which are sensitive mainly to rare voids, are highly biased (with a linear bias factor b ≥ 4) tracers of underlying density fluctuations and (2) small-scale transverse modes are aliased to long-wavelength line-of-sight modes. Inferring patchy reionization from quasar spectra is therefore subtle and requires much more detailed modeling. Similarly, we expect density fluctuations alone to produce order unity transmission fluctuations in the z ~ 3 He II Lyα forest on the scales over which these measurements are typically made.
Chandra Observations of Candidate “True” Seyfert 2 Nuclei

The unification model for AGNs posits that Seyfert 2 galaxies are intrinsically like Seyfert 1 galaxies, but that their broad-line regions (BLRs) are hidden from our view. A Seyfert 2 nucleus that truly lacked a BLR, instead of simply having it hidden, would be a so-called true Seyfert 2. No object has as yet been conclusively proven to be one. We present a detailed analysis of four of the best true Seyfert 2 candidates discovered to date: IC 3639, NGC 3982, NGC 5283, and NGC 5427. None of the four have a broad Hα emission line, in either direct or polarized light. All four have rich, high-excitation spectra, blue continua, and HST images showing them to be unresolved sources with no host-galaxy obscuration. To check for possible obscuration on scales smaller than that resolvable by HST, we obtained X-ray observations using Chandra. All four objects show evidence of obscuration and therefore could have hidden BLRs. The picture that emerges is of moderate to high, but not necessarily Compton-thick, obscuration of the nucleus, with extranuclear soft emission extended on the hundreds of parsec scale that may originate in the narrow-line region. Since the extended soft emission compensates, in part, for the nuclear soft emission lost to absorption, both absorption and luminosity are likely to be severely underestimated unless the X-ray spectrum is of sufficient quality to distinguish the two components. This is of special concern where the source is too faint to produce a large number of counts, or where the source is too far away to resolve the extended soft X-ray-emitting region.
Review and suggested resolution of the problem of Schrodinger’s cat

AbstractThis paper reviews and suggests a resolution of the problem of definite outcomes of measurement. This problem, also known as ‘Schrodinger’s cat’, has long posed an apparent paradox because ...
Sterile Neutrino Dark Matter from Freeze-In

A sterile neutrino is a well-motivated and widely studied dark matter (DM) candidate. The most straightforward realization of sterile neutrino DM, through the Dodelson–Widrow (DW) mechanism, is now ruled out by a combination of X-ray and Lyman-α measurements. An alternative production mechanism that is becoming increasingly popular in the literature is the freeze-in mechanism, involving frameworks where a feeble coupling to a particle — usually a scalar beyond the Standard Model — in the thermal bath results in a gradual accumulation of the sterile neutrino DM abundance. This paper reviews the various motivations for realizing such frameworks in the literature, their common characteristic features and phenomenological signatures.
A low-order theory of Arctic sea ice stability

We analyze the stability of a low-order coupled sea ice and climate model and extract the essential physics governing the time scales of response as a function of greenhouse gas forcing. Under present climate conditions the stability is controlled by longwave radiation driven heat conduction. However, as greenhouse gas forcing increases and the ice cover decays, the destabilizing influence of ice-albedo feedback acts on equal footing with longwave stabilization. Both are seasonally out of phase and as the system warms towards a seasonal ice state these effects, which underlie the bifurcations between climate states, combine exhibiting a slowing-down to extend the intrinsic relaxation time scale from ~2?yr to 5?yr.
The Calabi–Yau equation on the Kodaira–Thurston manifold

We prove that the Calabi–Yau equation can be solved on the Kodaira–Thurston manifold for all given T2-invariant volume forms. This provides support for Donaldson's conjecture that Yau's theorem has an extension to symplectic 4-manifolds with compatible but non-integrable almost complex structures.
Singular Abreu Equations and Minimizers of Convex Functionals with a Convexity Constraint

We study the solvability of second boundary value problems of fourth order equations of Abreu type arising from approximation of convex functionals whose Lagrangians depend on the gradient variable, subject to a convexity constraint. These functionals arise in different scientific disciplines such as Newton's problem of minimal resistance in physics and monopolist's problem in economics. The right hand sides of our Abreu type equations are quasilinear expressions of second order; they are highly singular and a priori just measures. However, our analysis in particular shows that minimizers of the 2D Rochet-Chone model perturbed by a strictly convex lower order term, under a convexity constraint, can be approximated in the uniform norm by solutions of the second boundary value problems of singular Abreu equations.
THE ROCKSTAR PHASE-SPACE TEMPORAL HALO FINDER AND THE VELOCITY OFFSETS OF CLUSTER CORES

We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure; as such, it is named Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement). Our method is massively parallel (up to 10 5 CPUs) and runs on the very largest simulations (>10 10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). A previous paper (Knebe et al. 2011) has shown Rockstar to have class-leading recovery of halo properties; we expand on these comparisons with more tests and higher-resolution simulations. We show a significant improvement in substructure recovery as compared to other halo finders and discuss the theoretical and practical limits of simulations in this regard. Finally, we present results which demonstrate conclusively that dark matter halo cores are not at rest relative to the halo bulk or satellite average velocities and have coherent velocity offsets across a wide range of halo masses and redshifts. For massive clusters, these offsets can be up to 400 km s -1 at z = 0 and even higher at high redshifts. Our implementation is publicly available at http://code.google.com/p/rockstar. Subject headings: dark matter — galaxies: abundances — galaxies: evolution — methods: N-body simulations
Spurious Shear from the Atmosphere in Ground-based Weak-lensing Observations

Weak-lensing observations have the potential to be even more powerful than cosmic microwave background observations in constraining cosmological parameters. However, the practical limits to weak-lensing observations are not known. Most theoretical studies of weak-lensing constraints on cosmology assume that the only limits are shot noise on small scales, and cosmic variance on large scales. For future large surveys, shot noise will be so low that other, systematic errors will likely dominate. Here we examine a potential source of additive systematic error for ground-based observations: spurious power induced by the atmosphere. We show that this limit will not be a significant factor even in future massive surveys such as LSST.
Vamsa: Automated Provenance Tracking in Data Science Scripts

There has recently been a lot of ongoing research in the areas of fairness, bias and explainability of machine learning (ML) models due to the self-evident or regulatory requirements of various ML applications. We make the following observation: All of these approaches require a robust understanding of the relationship between ML models and the data used to train them. In this work, we introduce the ML provenance tracking problem: the fundamental idea is to automatically track which columns in a dataset have been used to derive the features/labels of an ML model. We discuss the challenges in capturing such information in the context of Python, the most common language used by data scientists. We then present Vamsa, a modular system that extracts provenance from Python scripts without requiring any changes to the users' code. Using 26K real data science scripts, we verify the effectiveness of Vamsa in terms of coverage, and performance. We also evaluate Vamsa's accuracy on a smaller subset of manually labeled data. Our analysis shows that Vamsa's precision and recall range from 90.4% to 99.1% and its latency is in the order of milliseconds for average size scripts. Drawing from our experience in deploying ML models in production, we also present an example in which Vamsa helps automatically identify models that are affected by data corruption issues.
Transient Stability Guarantees for Ad Hoc DC Microgrids

Ad hoc electrical networks are formed by connecting power sources and loads without planning the interconnection structure (topology) in advance. They are designed to be installed and operated by individual communities—without central oversight—and as a result are well-suited to addressing the lack of electricity access in rural and developing areas. However, ad hoc networks are not widely used, and a major technical challenge impeding their development (and deployment) is the difficulty of certifying network stability without a priori knowledge of the topology. We develop conditions on individual power sources and loads such that a microgrid comprised of many units will be stable. We use Brayton–Moser potential theory to develop design constraints on individual microgrid components that certify transient stability—guaranteeing that the system will return to a suitable equilibrium after load switching events. Our central result is that stability can be ensured by installing a parallel capacitor at each constant power load, and we derive an expression for the required capacitance.
Notes on the knot concordance invariant Upsilon

Ozsvath, Stipsicz and Szabo have defined a knot concordance invariant ϒK taking values in the group of piecewise linear functions on the closed interval [0,2]. This paper presents a description of one approach to defining ϒK and proving its basic properties.
Unidirectional light transport in dynamically modulated waveguides

Unidirectional light propagation, as in the emerging field of topological photonics, offers robust transport of light in devices despite the presence of fabrication flaws. This highly nontrivial effect, however, can only be achieved in correspondingly nontrivial structures. The authors present a significantly simplified paradigm in which dynamic modulation of a photonic waveguide conducts light in one direction, even through structural defects. This approach opens an avenue to exploring topological photonics, and to slow-light waveguides unhindered by their imperfections, which is exciting for applications in integrated optics.
Kinematics of Milky Way Satellites: Mass Estimates, Rotation Limits, and Proper Motions

In the past several years kinematic data sets from Milky Way satellite galaxies have greatly improved, furthering the evidence that these systems are the most dark matter dominated objects known. This paper discusses a maximum likelihood formalism that extracts important quantities from these kinematic data sets, including the amplitude of a rotational signal, proper motions, and the mass distributions. Using a simple model for galaxy rotation it is shown that the expected error on the amplitude of a rotational signal is 0.5 km with stars from either classical or ultra-faint satellites. As an example Sculptor is analyzed for the presence of a rotational signal; no significant detection of rotation is found, with a 90% c.l. upper limit of 2 km . A criterion for model selection is presented that determines the parameters required to describe the dark matter halo density profiles and the stellar velocity anisotropy. Applied to four data sets with a wide range of velocities, models with variable velocity anisotropy are preferred relative to those with constant velocity anisotropy, and that central dark matter profiles both less cuspy and more cuspy than Lambda-Cold Dark Matter-based fits are equally acceptable.
RECURRENT PERIHELION ACTIVITY IN (3200) PHAETHON

We present a study of planet-crossing asteroid (3200) Phaethon at three successive perihelia in 2009, 2010, and 2012, using the NASA STEREO spacecraft. Phaethon is clearly detected in 2009 and 2012, but not in 2010. In both former years, Phaethon brightened unexpectedly by {approx}1 mag at large phase angles, inconsistent with the {approx}1 mag of steady fading expected from a discrete, macroscopic body over the same phase angle range. With a perihelion distance of 0.14 AU and surface temperatures up to {approx}1000 K, a thermal origin of this anomalous brightening is strongly suspected. However, simple thermal emission from Phaethon is too weak, by a factor >10{sup 3}, to explain the brightening. Nor can ice survive on this body, ruling out comet-like sublimation. Our preferred explanation is that brightening occurs as a result of dust produced and ejected from Phaethon, perhaps by thermal fracture and/or thermal decomposition of surface minerals when near perihelion. A contribution from prompt emission by oxygen released by desiccation of surface minerals cannot be excluded. We infer an ejected mass of order 4 Multiplication-Sign 10{sup 8} a{sub mm} kg per outburst, where a{sub mm} is the mean dust radius in millimeters. For plausible dust radii, this massmore » is small compared to the estimated mass of Phaethon ({approx}2 Multiplication-Sign 10{sup 14} kg) and to the mass of the Geminid stream (10{sup 12}-10{sup 13} kg) with which Phaethon is dynamically associated. Perihelion mass-loss events like those observed in 2009 and 2012 contribute to, but do not necessarily account for the Geminids stream mass.« less
GLOBAL NUMERICAL MODELING OF ENERGETIC PROTON ACCELERATION IN A CORONAL MASS EJECTION TRAVELING THROUGH THE SOLAR CORONA

The acceleration of protons and electrons to high (sometimes GeV/nucleon) energies by solar phenomena is a key component of space weather. These solar energetic particle (SEP) events can damage spacecraft and communications, as well as present radiation hazards to humans. In-depth particle acceleration simulations have been performed for idealized magnetic fields for diffusive acceleration and particle propagation, and at the same time the quality of MHD simulations of coronal mass ejections (CMEs) has improved significantly. However, to date these two pieces of the same puzzle have remained largely decoupled. Such structures may contain not just a shock but also sizable sheath and pileup compression regions behind it, and may vary considerably with longitude and latitude based on the underlying coronal conditions. In this work, we have coupled results from a detailed global three-dimensional MHD time-dependent CME simulation to a global proton acceleration and transport model, in order to study time-dependent effects of SEP acceleration between 1.8 and 8 solar radii in the 2005 May 13 CME. We find that the source population is accelerated to at least 100 MeV, with distributions enhanced up to six orders of magnitude. Acceleration efficiency varies strongly along field lines probing different regions of the dynamically evolving CME, whose dynamics is influenced by the large-scale coronal magnetic field structure. We observe strong acceleration in sheath regions immediately behind the shock.
Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis

Interactive massively parallel computations are critical for machine learning and data analysis. These computations are a staple of the MIT Lincoln Laboratory Supercomputing Center (LLSC) and has required the LLSC to develop unique interactive supercomputing capabilities. Scaling interactive machine learning frameworks, such as TensorFlow, and data analysis environments, such as MATLAB/Octave, to tens of thousands of cores presents many technical challenges – in particular, rapidly dispatching many tasks through a scheduler, such as Slurm, and starting many instances of applications with thousands of dependencies. Careful tuning of launches and prepositioning of applications overcome these challenges and allow the launching of thousands of tasks in seconds on a 40,000-core supercomputer. Specifically, this work demonstrates launching 32,000 TensorFlow processes in 4 seconds and launching 262,000 Octave processes in 40 seconds. These capabilities allow researchers to rapidly explore novel machine learning architecture and data analysis algorithms.
Can we use epigenetics to prime chemoresistant lymphomas

Chemoresistance remains a challenging clinical problem in the treatment of many lymphoma patients. Epigenetic derangements have been implicated in both intrinsic and acquired chemoresistance. Mutations in epigenetic processes shift entire networks of signaling pathways. They influence tumor suppressors, the DNA-damage response, cell-cycle regulators, and apoptosis. Epigenetic alterations have also been implicated in contributing to immune evasion. Although increased DNA methylation at CpG sites is the most widely studied alteration, increased histone methylation and decreased histone acetylation have also been implicated in stem-like characteristics and highly aggressive disease states as demonstrated in both preclinical models of lymphoma and patient studies. These changes are nonrandom, occur in clusters, and are observed across many lymphoma subtypes. Although caution must be taken when combining epigenetic therapies with other antineoplastic agents, epigenetic therapies have rarely induced clinical meaningful responses as single agents. Epigenetic priming of chemotherapy, targeted therapies, and immunotherapies in lymphoma patients may create opportunities to overcome resistance.
iGenomics: Comprehensive DNA sequence analysis on your Smartphone.

BACKGROUND Following the miniaturization of integrated circuitry and other computer hardware over the past several decades, DNA sequencing is on a similar path. Leading this trend is the Oxford Nanopore sequencing platform, which currently offers the hand-held MinION instrument and even smaller instruments on the horizon. This technology has been used in several important applications, including the analysis of genomes of major pathogens in remote stations around the world. However, despite the simplicity of the sequencer, an equally simple and portable analysis platform is not yet available. RESULTS iGenomics is the first comprehensive mobile genome analysis application, with capabilities to align reads, call variants, and visualize the results entirely on an iOS device. Implemented in Objective-C using the FM-index, banded dynamic programming, and other high-performance bioinformatics techniques, iGenomics is optimized to run in a mobile environment. We benchmark iGenomics using a variety of real and simulated Nanopore sequencing datasets of viral and bacterial genomes and show that iGenomics has performance comparable to the popular BWA-MEM/SAMtools/IGV suite, without necessitating a laptop or server cluster. CONCLUSIONS iGenomics is available open source (https://github.com/stuckinaboot/iGenomics) and for free on Apple's App Store (https://apple.co/2HCplzr).
A 5G NR based System Architecture for Real-Time Control with Batteryless RFID Sensors

The fifth-generation wireless networking (5G) technologies have been developed to meet various time-critical use cases with ultra-reliable, low-latency and massive machine-type communications which are indispensable for tactile Internet applications. Recent advancements in very low-cost and batteryless radio-frequency identification (RFID) sensors have given promises of deploying a massive amount of such sensors for real-time sensing and control applications on a 5G New Radio (NR) network. However, the system design and performance of such applications have not been well studied. This paper proposes a novel system architecture for the representative batteryless RFID touch sensors in generic real-time control applications in a 5G NR mmWave environment. We will discuss the solution using edge computing nodes on the 5G NR base station to the implementation of the proposed system architecture. The real-time performance evaluation with the comparison of the Long-Term Evolution (LTE) networks has shown the effectiveness of the proposed system architecture.
Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach

Human behavior prediction models enable robots to anticipate how humans may react to their actions, and hence are instrumental to devising safe and proactive robot planning algorithms. However, modeling complex interaction dynamics and capturing the possibility of many possible outcomes in such interactive settings is very challenging, which has recently prompted the study of several different approaches. In this work, we provide a self-contained tutorial on a conditional variational autoencoder (CVAE) approach to human behavior prediction which, at its core, can produce a multimodal probability distribution over future human trajectories conditioned on past interactions and candidate robot future actions. Specifically, the goals of this tutorial paper are to review and build a taxonomy of state-of-the-art methods in human behavior prediction, from physics-based to purely data-driven methods, provide a rigorous yet easily accessible description of a data-driven, CVAE-based approach, highlight important design characteristics that make this an attractive model to use in the context of model-based planning for human-robot interactions, and provide important design considerations when using this class of models.
The Tax Exclusion for Employer-Sponsored Health Insurance

This paper reviews the issues raised by and the impacts of the tax exclusion for employer-sponsored health insurance. After reviewing the arguments for and against this policy, I present evidence f...
Free-form broadband flat lenses for visible imaging

The resolution of a conventional lens is governed by its numerical aperture (NA) while its light-concentration ability is governed by its f-number (f/#), both of which are dependent on the diameter and focal length of the lens. Hence, these properties for a conventional lens are inherently coupled. Here, we show that by utilizing the principle of free-form broadband diffractive optical elements (BDOEs), we can create ultra-flat optical elements that are able to concentrate incoming light over a fixed aperture to different sized focal spots engineered in the shape of a square. Hence, we are able to decouple the NA and f/# of a lens by being able to independently control the size of the input aperture and the resolution of these devices. Specifically, we designed, fabricated, and characterized three BDOE lenses operating in the visible band (450nm–750nm), each having f/# of 11.25, but with NAs of 0.00075, 0.0067, and 0.054, respectively. We further use simulations to emphasize that such decoupling is possible even at much higher NAs. Experiments confirm achromatic focusing and broadband imaging. One of the lenses exhibited a depth-of-focus almost 2 orders of magnitude larger than the diffraction limit. Such BDOE lenses can eliminate the need for anti-aliasing filters and could also be very useful in focal-plane arrays with large pixel sizes, where light collection efficiency needs to be maintained. Furthermore, by abandoning rotational symmetry, one can achieve free-form geometries in the focal spot, such as a square that can more closely match the geometry of the sensor pixel.
Deterministic Algorithms for Decremental Shortest Paths via Layered Core Decomposition

In the decremental single-source shortest paths (SSSP) problem, the input is an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges undergoing edge deletions, together with a fixed source vertex $s\in V$. The goal is to maintain a data structure that supports shortest-path queries: given a vertex $v\in V$, quickly return an (approximate) shortest path from $s$ to $v$. The decremental all-pairs shortest paths (APSP) problem is defined similarly, but now the shortest-path queries are allowed between any pair of vertices of $V$. Both problems have been studied extensively since the 80's, and algorithms with near-optimal total update time and query time have been discovered for them. Unfortunately, all these algorithms are randomized and, more importantly, they need to assume an oblivious adversary. Our first result is a deterministic algorithm for the decremental SSSP problem on weighted graphs with $O(n^{2+o(1)})$ total update time, that supports $(1+\epsilon)$-approximate shortest-path queries, with query time $O(|P|\cdot n^{o(1)})$, where $P$ is the returned path. This is the first $(1+\epsilon)$-approximation algorithm against an adaptive adversary that supports shortest-path queries in time below $O(n)$, that breaks the $O(mn)$ total update time bound of the classical algorithm of Even and Shiloah from 1981. Our second result is a deterministic algorithm for the decremental APSP problem on unweighted graphs that achieves total update time $O(n^{2.5+\delta})$, for any constant $\delta>0$, supports approximate distance queries in $O(\log\log n)$ time; the algorithm achieves an $O(1)$-multiplicative and $n^{o(1)}$-additive approximation on the path length. All previous algorithms for APSP either assume an oblivious adversary or have an $\Omega(n^{3})$ total update time when $m=\Omega(n^{2})$.
Distributed Continuous-Time Optimization with Time-Varying Objective Functions and Inequality Constraints

This paper is devoted to the distributed continuous-time optimization problem with time-varying objective functions and time-varying nonlinear inequality constraints. Different from most studied distributed optimization problems with time-invariant objective functions and constraints, the optimal solution in this paper is time varying and forms a trajectory. To minimize the global time-varying objective function subject to time-varying local constraint functions using only local information and local interaction, we present a distributed control algorithm that consists of a sliding-mode part and a Hessian-based optimization part. The asymptotical convergence of the proposed algorithm to the optimal solution is studied under suitable assumptions. The effectiveness of the proposed scheme is demonstrated through a simulation example.
Self-Supervised Poisson-Gaussian Denoising

We extend the blindspot model for self-supervised de-noising to handle Poisson-Gaussian noise and introduce an improved training scheme that avoids hyperparameters and adapts the denoiser to the test data. Self-supervised models for denoising learn to denoise from only noisy data and do not require corresponding clean images, which are difficult or impossible to acquire in some application areas of interest such as low-light microscopy. We introduce a new training strategy to handle Poisson-Gaussian noise which is the standard noise model for microscope images. Our new strategy eliminates hyperparameters from the loss function, which is important in a self-supervised regime where no ground truth data is available to guide hyperparameter tuning. We show how our denoiser can be adapted to the test data to improve performance. Our evaluations on microscope image denoising benchmarks validate our approach.
Transformation Cloaking in Elastic Plates

In this paper, we formulate the problem of elastodynamic transformation cloaking for Kirchoff–Love plates and elastic plates with both in-plane and out-of-plane displacements. A cloaking transformation maps the boundary-value problem of an isotropic and homogeneous elastic plate (virtual problem) to that of an anisotropic and inhomogeneous elastic plate with a hole surrounded by a cloak that is to be designed (physical problem). For Kirchoff–Love plates, the governing equation of the virtual plate is transformed to that of the physical plate up to an unknown scalar field. In doing so, one finds the initial stress and the initial tangential body force for the physical plate, along with a set of constraints that we call the cloaking compatibility equations. It is noted that the cloaking map needs to satisfy certain boundary and continuity conditions on the outer boundary of the cloak and the surface of the hole. In particular, the cloaking map needs to fix the outer boundary of the cloak up to the third order. Assuming a generic radial cloaking map, we show that cloaking a circular hole in Kirchoff–Love plates is not possible; the cloaking compatibility equations and the boundary conditions are the obstruction to cloaking. Next, relaxing the pure bending assumption, the transformation cloaking problem of an elastic plate in the presence of in-plane and out-of-plane displacements is formulated. In this case, there are two sets of governing equations that need to be simultaneously transformed under a cloaking map. We show that cloaking a circular hole is not possible for a general radial cloaking map; similar to Kirchoff–Love plates, the cloaking compatibility equations and the boundary conditions obstruct transformation cloaking. Our analysis suggests that the path forward for cloaking flexural waves in plates is approximate cloaking formulated as an optimal design problem.
Critical cooling rates for amorphous-to-ordered complexion transitions in Cu-rich nanocrystalline alloys

Abstract Amorphous complexions in nanocrystalline metals have the potential to improve mechanical properties and radiation tolerance, as well as resistance to grain growth. In this study, the stability of amorphous complexions in binary and ternary Cu-based alloys is investigated by observing the effect of cooling rate from high temperature on the occurrence of amorphous-to-ordered complexion transitions. Bulk Cu-Zr and Cu-Zr-Hf alloy samples were annealed to induce boundary premelting and then quenched through a procedure that induces a gradient of local cooling rate through the sample height. Amorphous complexion thickness distributions were found to be invariant to local cooling rate in the Cu-Zr-Hf alloy, demonstrating enhanced stability of the amorphous complexion structure compared to the Cu-Zr alloy, which had thinner amorphous complexions in the regions that were slowly cooled. The experimental results are used to construct time-temperature-transformation diagrams for the amorphous-to-ordered complexion transition in both the binary and ternary alloys, enabling a deeper understanding of the influence of cooling rate and grain boundary chemistry on complexion transitions. The critical cooling rate necessary to avoid complexion transitions in the ternary alloy is found to be at least three orders of magnitude slower than that for the binary alloy.
Betti spectral gluing

Abstract Given a complex reductive group G, Borel subgroup B ⊂ G , and topological surface S with boundary ∂S, we study the “Betti spectral category” DCoh N ( L o c G ( S , ∂ S ) ) of coherent sheaves with nilpotent singular support on the character stack of G-local systems on S with B-reductions along ∂S. Modifications along the components of ∂S endow DCoh N ( L o c G ( S , ∂ S ) ) with commuting actions of the affine Hecke category H G in its realization as coherent sheaves on the Steinberg stack. We prove a “spectral Verlinde formula” identifying the result of gluing two boundary components with the Hochschild homology of the corresponding H G -bimodule structure. The equivalence is compatible with Wilson line operators (the action of Perf ( L o c G ( S ) ) realized by Hecke modifications at points) as well as Verlinde loop operators (the action of the center of H G realized by Hecke modifications along closed loops). The result reduces the calculation of such “Betti spectral categories” to the case of disks, cylinders, pairs of pants, and the Mobius band. We also show how to impose arbitrary ramification conditions in terms of modules for the affine Hecke category.
Managerial Discretion and Accounting for Research and Development Costs

This study investigates the extent to which potential financial reporting benefits from capitalizing and amortizing R&D costs depend on increasing the level of discretion permitted to financial statement preparers. To provide evidence on this issue, we examine the impact of alternative accounting schemes for R&D costs on the extent to which earnings and book values jointly explain the observed distribution of share prices. One alternative requires firms to capitalize and amortize R&D outlays, but provides them with no more discretion than that permitted under current rules. The other alternatives reflect increasing discretion over which R&D costs are recognized as assets and the periods over which these assets are amortized. We find that ability to explain the distribution of share prices increases with discretion, and conclude that substantial managerial discretion is likely to be a necessary (though not sufficient) ingredient of any alternative R&D accounting scheme that is capable of producing economic...
Statins and Adverse Cardiovascular Events in Moderate-Risk Females: A Statistical and Legal Analysis with Implications for FDA Preemption Claims

This article presents: (1) meta-analyses of studies of cardioprotection of women and men by statins, including Lipitor (atorvastatin), and (2) a legal analysis of advertising promoting Lipitor as preventing heart attacks. The meta-analyses of primary prevention clinical trials show statistically significant benefits for men but not for women, and a statistically significant difference between men and women. The analyses do not support (1) statin use to reduce heart attacks in women based on extrapolation from men, or (2) approving or advertising statins as reducing heart attacks without qualification in a population that includes many women. The legal analysis raises the question of whether Lipitor's advertisements, which omit that Lipitor's clinical trial found slight increased risk for women, is consistent with the Food, Drug, and Cosmetics Act and related Food and Drug Administration (FDA) regulations. The analysis suggests that FDA regulation should not preempt state law actions challenging advertising that is not supported by FDA-approved labeling. Our findings suggesting inadequate regulation of the world's best-selling drug also counsel against courts accepting the FDA's claimed preemption of state law causes of action relating to warnings and safety. Courts evaluating preemption claims should consider actual agency performance as well as theoretical institutional competence. Billions of health-care dollars may be being wasted on statin use by women but the current regulatory regime does not create incentives to prevent such behavior.
The road mileage user-fee: Level, intensity, and predictors of public support

Abstract The road mileage user-fee is viewed as a promising alternative to the fuel tax, which in recent years has proven to be an inadequate means of financing road infrastructure. Public opposition is often thought to be a barrier to the political feasibility of the road mileage user-fee. We use a nationally representative public opinion survey to investigate the level and intensity of support for replacing the fuel tax with a general mileage user-fee and with three specific modes of administration of the fee. Our results confirm that public opposition to the adoption of mileage user-fees to address the growing revenue inadequacy of fuel taxes is high, with the number of opponents exceeding the number of supporters by a ratio of 4-1. Furthermore, public support is somewhat sensitive to respondents' belief in the user-pays principle and perceptions of the characteristics of the mode of administration. Additionally, relative to supporters, those who oppose the mileage user-fee are more likely to state that they are willing to take political action against the adoption of mileage user-fees.
Interest rate derivatives at commercial banks: An empirical investigation ☆

Abstract I analyze the effects of bank characteristics and macroeconomic shocks on interest rate risk-management behavior of commercial banks. My findings are consistent with hedging theories based on cost of financial distress and costly external financing. Banks with higher probability of financial distress manage their interest rate risk more aggressively, both by means of on-balance sheet and off-balance sheet instruments. As compared to the derivative users, the derivative non-user banks adopt conservative asset–liability management policies in tighter monetary policy regimes. Finally, I show that the derivative non-user bank's lending volume declines significantly with the contraction in the money supply. Derivative users, on the other hand, remain immune to the monetary policy shocks. My findings suggest that a potential benefit of derivatives usage is to minimize the effect of external shocks on a firm's operating policies.
Accounting standards, regulatory enforcement, and innovation

Abstract We examine the effects of accounting standards and regulatory enforcement on entrepreneurial innovation and social welfare. When the entrepreneur issues a financial report that violates the accounting standards, a regulatory agency may detect the violation and bring charges. We find that when regulatory penalties are relatively insensitive to the magnitude of the violation, optimal standards are sufficiently low that they induce full compliance, and increase as the intensity of enforcement increases. In contrast, when regulatory penalties are sensitive to the magnitude of the violation, optimal standards induce non-compliance and decline as the intensity of enforcement increases.
DOES COPYRIGHT ENFORCEMENT ENCOURAGE PIRACY

When copyright enforcement is targeted at high-value buyers such as corporate and government users, the copyright holder charges super-monopoly prices, thereby encouraging low-value buyers to switch to inferior pirated copies. We show that enlarging the copyright holder's captive market through more extensive copyright enforcement reduces prices toward the monopoly level, increases sales of legitimate copies and can increase consumer surplus. Therefore, in contrast with the case of more intensive copyright enforcement, more extensive copyright enforcement over some range can increase the incentive to generate intellectual property while also reducing the loss to consumers from monopoly power.
City CPI Convergence in Mexico

This paper tests the purchasing power parity hypothesis within a single developing country currency area: Mexico. This work stems from research in comparing price movements across countries and a growing literature on price dynamics within a single currency area. The author uses city Consumer Price Index data for 34 cities in Mexico over the period 1982–2000. He followed the standard procedure of testing for I(1) processes in relative city prices, or city real exchange rates, using univariate and panel unit root tests. The main results of the paper are: First, Mexican city relative prices are stationary—the data rejects the hypothesis that city real exchange rates contain a random walk, but only using panel unit root techniques. Finally, regional demand and supply homogeneity implies stronger evidence for price parity within regions, while there is considerable evidence of regional price convergence, regional homogeneity does not guarantee faster convergence.
DO FOREIGN FIRMS CROWD OUT DOMESTIC FIRMS? EVIDENCE FROM THE CZECH REPUBLIC

Abstract I examine how foreign presence affects the growth and survival of domestic firms. Separating a negative crowding out and positive technology spillovers, I analyze whether the crowding out effect is dynamic, that is, domestic firms cut production over time as foreign firms grow, or a static effect realized on foreign entry into the industry. Using 1994–2001 firm-level Czech data, I find evidence of both technology spillovers and crowding out. However, crowding out is only short term; after initial entry shakeout, growing foreign sales increase domestic firm growth and survival, indicating domestic demand creation effect. However, I find no such benefits from domestic competition.
Why Do Demand Curves for Stocks Slope Down

Representative agent models are inconsistent with existing empirical evidence for steep demand curves for individual stocks. This paper resolves the puzzle by proposing that stock prices are instead set by two separate classes of investors. While the market portfolio is still priced by individual investors based on their collective risk aversion, those individual investors also delegate part of their wealth to active money managers, who use that capital to price stocks in the cross section. In equilibrium, the fee charged by active managers has to equal the before-fee alpha they earn. This endogenously determines the amount of active capital and the slopes of demand curves. A calibration of the model reveals that demand curves can be steep enough to match the magnitude of many empirical findings, including the price effects for stocks entering or leaving the S&P 500 index.
A Blueprint for Blogger Involvement in Academic Legal Symposia

This essay reflects on my experience as the “featured blogger” at the 2012 Michigan State Law Review Symposium on “Gender and the Legal Profession’s Pipeline to Power” and maps out possible models for future blogger involvement in other academic legal symposia. Successful blogger involvement in live academic events requires contributors who will write under pressure and organizers who will cede control over the way the conference is interpreted and discussed by others. My involvement was an experiment at the intersection of scholarly dialogue, legal education and cyberspace. Blog-based conversations continued after the actual symposium and provided an alternate venue for perspectives that were not present at the live event. Some attorneys-to-be were reluctant to engage in live conversations about gender and power, and anonymous blog commentators labeled women who talk about discrimination as "whiners." While these silent or anonymous commentators suggest that issues of gender in the legal profession are not serious concerns for some, they indicate how difficult it is to have frank and open discussions about gender inequality.
AN EMPIRICAL INVESTIGATION OF THE COGNITIONS OF CORPORATE ENTREPRENEURS

Studies that examine cognition imply that entrepreneurs think differently than other people: most often these studies have suggested that entrepreneurs think in a way that is distinct from managers in large corporations. Furthermore, patterns found in cognition research suggest that entrepreneurs think the same when considering whether to start a new venture. Our study of innovation-based corporation entrepreneurship initiatives suggest that it is the cognition-environment nexus that is most important, not simply the manner in which entrepreneurs think. Our study indicates that entrepreneurs and managers think alike with respect to identifying opportunities and starting new ventures but organization environments differentiate the manner in which they think as they go to execute these opportunities.
Advertising Content and Television Advertising Avoidance

ABSTRACTThis article proposes a new measure of television advertising avoidance, the Passive/Active Zap (PAZ), as an occurrence of a set-top box switching channels during a commercial break after at least 5 min of inactivity prior to the break. Twenty-seven percent of eligible commercial breaks are interrupted by a PAZ. A proportional hazards model is applied to a unique dataset to estimate the impact of advertising content and commercial break characteristics on PAZ behavior. The results show that advertising avoidance is negatively associated with movie ads and positively associated with advertising for websites, auto insurance and women’s clothing. Ad avoidance also tends to rise with repeated exposures to the same ad creative, advertising aired on general-interest television networks, later hours of the evening, and rainfall.
On the Role of Clustering in Personalized PageRank Estimation

Personalized PageRank (PPR) is a measure of the importance of a node from the perspective of another (we call these nodes the target and the source, respectively). PPR has been used in many applications, such as offering a Twitter user (the source) recommendations of whom to follow (targets deemed important by PPR); additionally, PPR has been used in graph-theoretic problems such as community detection. However, computing PPR is infeasible for large networks like Twitter, so efficient estimation algorithms are necessary.In this work, we analyze the relationship between PPR estimation complexity and clustering. First, we devise algorithms to estimate PPR for many source/target pairs. In particular, we propose an enhanced version of the existing single pair estimator Bidirectional-PPR that is more useful as a primitive for many pair estimation. We then show that the common underlying graph can be leveraged to efficiently and jointly estimate PPR for many pairs rather than treating each pair separately using the primitive algorithm. Next, we show the complexity of our joint estimation scheme relates closely to the degree of clustering among the sources and targets at hand, indicating that estimating PPR for many pairs is easier when clustering occurs. Finally, we consider estimating PPR when several machines are available for parallel computation, devising a method that leverages our clustering findings, specifically the quantities computed in situ, to assign tasks to machines in a manner that reduces computation time. This demonstrates that the relationship between complexity and clustering has important consequences in a practical distributed setting.