cssi/SciSciGPT-SciSciNet huggingface dataset:
Seasonality in dynamic stochastic block models

Sociotechnological and geospatial processes exhibit time varying structure that make insight discovery challenging. This paper proposes a new statistical model for such systems, modeled as dynamic networks, to address this challenge. It assumes that vertices fall into one of k types and that the probability of edge formation at a particular time depends on the types of the incident nodes and the current time. The time dependencies are driven by unique seasonal processes, which many systems exhibit (e.g., predictable spikes in geospatial or web traffic each day). The paper defines the model as a generative process and an inference procedure to recover the seasonal processes from data when they are unknown. Evaluation with synthetic dynamic networks show the recovery of the latent seasonal processes that drive its formation.
XGNN: Towards Model-Level Explanations of Graph Neural Networks

Graphs neural networks (GNNs) learn node features by aggregating and combining neighbor information, which have achieved promising performance on many graph tasks. However, GNNs are mostly treated as black-boxes and lack human intelligible explanations. Thus, they cannot be fully trusted and used in certain application domains if GNN models cannot be explained. In this work, we propose a novel approach, known as XGNN, to interpret GNNs at the model-level. Our approach can provide high-level insights and generic understanding of how GNNs work. In particular, we propose to explain GNNs by training a graph generator so that the generated graph patterns maximize a certain prediction of the model. We formulate the graph generation as a reinforcement learning task, where for each step, the graph generator predicts how to add an edge into the current graph. The graph generator is trained via a policy gradient method based on information from the trained GNNs. In addition, we incorporate several graph rules to encourage the generated graphs to be valid. Experimental results on both synthetic and real-world datasets show that our proposed methods help understand and verify the trained GNNs. Furthermore, our experimental results indicate that the generated graphs can provide guidance on how to improve the trained GNNs.
Stochastic evolution of four species in cyclic competition

We study the stochastic evolution of four species in cyclic competition in a well mixed environment. For systems composed of a finite number N of particles these simple interaction rules result in a rich variety of extinction scenarios, from single-species domination to coexistence between non-interacting species. Using exact results and numerical simulations we discuss the temporal evolution of the system for different values of N, and for different values of the reaction rates, as well as for different initial conditions. As expected, the stochastic evolution is found to closely follow the mean-field result for large N, with notable deviations appearing in the vicinity of extinction events. Different ways of characterizing and predicting extinction events are discussed.
Calculating the Symmetry Number of Flexible Sphere Clusters

We present a theoretical and computational framework to compute the symmetry number of a flexible sphere cluster in $${\mathbb {R}}^3$$ , using a definition of symmetry that arises naturally when calculating the equilibrium probability of a cluster of spheres in the sticky-sphere limit. We define the sticky symmetry group of the cluster as the set of permutations and inversions of the spheres which preserve adjacency and can be realized by continuous deformations of the cluster that do not change the set of contacts or cause particles to overlap. The symmetry number is the size of the sticky symmetry group. We introduce a numerical algorithm to compute the sticky symmetry group and symmetry number, and show it works well on several test cases. Furthermore, we show that once the sticky symmetry group has been calculated for indistinguishable spheres, the symmetry group for partially distinguishable spheres (those with nonidentical interactions) can be efficiently obtained without repeating the laborious parts of the computations. We use our algorithm to calculate the partition functions of every possible connected cluster of six identical sticky spheres, generating data that may be used to design interactions between spheres so they self-assemble into a desired structure.
Stop search in the compressed region via semileptonic decays

In supersymmetric extensions of the Standard Model, the superpartners of the top quark (stops) play the crucial role in addressing the naturalness problem. For direct pair-production of stops with each stop decaying into a top quark plus the lightest neutralino, the standard stop searches have difficulty finding the stop for a compressed spectrum where the mass difference between the stop and the lightest neutralino is close to the top quark mass, because the events look too similar to the large $$ t\overline{t} $$ background. With an additional hard ISR jet, the two neutralinos from the stop decays are boosted in the opposite direction and they can give rise to some missing transverse energy. This may be used to distinguish the stop decays from the backgrounds. In this paper we study the semileptonic decay of such signal events for the compressed mass spectrum. Although the neutrino from the W decay also produces some missing transverse energy, its momentum can be reconstructed from the kinematic assumptions and mass-shell conditions. It can then be subtracted from the total missing transverse momentum to obtain the neutralino contribution. Because it suffers from less backgrounds, we show that the semileptonic decay channel has a better discovery reach than the fully hadronic decay channel along the compressed line $$ {m}_{\tilde{t}}-{m}_{\tilde{\chi}}\approx {m}_t $$ . With 300 fb−1, the 13 TeV LHC can discover the stop up to 500 GeV, covering the most natural parameter space region.
Uncertainty analysis of microsegregation during laser powder bed fusion

Quality control in additive manufacturing can be achieved through variation control of the quantity of interest (QoI). We choose in this work the microstructural microsegregation to be our QoI. Microsegregation results from the spatial redistribution of a solute element across the solid-liquid interface that forms during solidification of an alloy melt pool during the laser powder bed fusion process. Since the process as well as the alloy parameters contribute to the statistical variation in microstructural features, uncertainty analysis of the QoI is essential. High-throughput phase-field simulations estimate the solid-liquid interfaces that grow for the melt pool solidification conditions that were estimated from finite element simulations. Microsegregation was determined from the simulated interfaces for different process and alloy parameters. Correlation, regression, and surrogate model analyses were used to quantify the contribution of different sources of uncertainty to the QoI variability. We found negligible contributions of thermal gradient and Gibbs-Thomson coefficient and considerable contributions of solidification velocity, liquid diffusivity, and segregation coefficient on the QoI. Cumulative distribution functions and probability density functions were used to analyze the distribution of the QoI during solidification. Our approach, for the first time, identifies the uncertainty sources and frequency densities of the QoI in the solidification regime relevant to additive manufacturing.
Negative Virial Coefficients and the Dominance of Loose Packed Diagrams for D-Dimensional Hard Spheres

We study the virial coefficients B k of hard spheres in D dimensions by means of Monte-Carlo integration. We find that B 5 is positive in all dimensions but that B 6 is negative for all D≥6. For 7≤k≤17 we compute sets of Ree–Hoover diagrams and find that either for large D or large k the dominant diagrams are “loose packed.” We use these results to study the radius of convergence and the validity of the many approximations used for the equations of state for hard spheres.
DYNAMICAL EVOLUTION OF YOUNG EMBEDDED CLUSTERS: A PARAMETER SPACE SURVEY

This paper investigates the dynamical evolution of embedded stellar clusters from the protocluster stage, through the embedded star-forming phase, and out to ages of 10 Myr—after the gas has been removed from the cluster. The relevant dynamical properties of young stellar clusters are explored over a wide range of possible star formation environments using N-body simulations. Many realizations of equivalent initial conditions are used to produce robust statistical descriptions of cluster evolution including the cluster bound fraction, radial probability distributions, as well as the distributions of close encounter distances and velocities. These cluster properties are presented as a function of parameters describing the initial configuration of the cluster, including the initial cluster membership N, initial stellar velocities, cluster radii, star formation efficiency, embedding gas dispersal time, and the degree of primordial mass segregation. The results of this parameter space survey, which includes ~25,000 simulations, provide a statistical description of cluster evolution as a function of the initial conditions. We also present a compilation of the FUV radiation fields provided by these same cluster environments. The output distributions from this study can be combined with other calculations, such as disk photoevaporation models and planetary scattering cross sections, to ascertain the effects of the cluster environment on the processes involved in planet formation.
Why does structural change accelerate in recessions? The credit reallocation channel

Abstract The decline of the U.S. manufacturing share since 1960 has occurred disproportionately during recessions. Using evidence from two natural experiments—the collapse of Lehman Brothers in 2008 and U.S. interstate banking deregulation in the 1980s—I find a role for credit reallocation in explaining this phenomenon by showing that losing access to credit disproportionately hurt manufacturing firms, and that the creation of new credit disproportionately benefited nonmanufacturing firms. These results arise endogenously from a model with technology-driven structural change and fixed costs of establishing new financial relationships. The model suggests an important role for long-run industry trajectories in properly accounting for the costs and benefits of policy interventions in credit markets.
Algorithms for Verifying Deep Neural Networks

Neural networks have been widely used in many applications, such as image classification and understanding, language processing, and control of autonomous systems. These networks work by mapping inputs to outputs through a sequence of layers. At each layer, the input to that layer undergoes an affine transformation followed by a simple nonlinear transformation before being passed to the next layer. Neural networks are being used for increasingly important tasks, and in some cases, incorrect outputs can lead to costly consequences, hence validation of correctness at each layer is vital. The sheer size of the networks makes this not feasible using traditional methods. In this monograph, the authors survey a class of methods that are capable of formally verifying properties of deep neural networks. In doing so, they introduce a unified mathematical framework for verifying neural networks, classify existing methods under this framework, provide pedagogical implementations of existing methods, and compare those methods on a set of benchmark problems. Algorithms for Verifying Deep Neural Networks serves as a tutorial for students and professionals interested in this emerging field as well as a benchmark to facilitate the design of new verification algorithms.
Effective spin-mixing conductance of topological-insulator/ferromagnet and heavy-metal/ferromagnet spin-orbit-coupled interfaces: A first-principles Floquet-nonequilibrium Green function approach

The spin-mixing conductance (SMC) is a key quantity determining efficiency of spin transport across interfaces. Thus, knowledge of its precise value is required for accurate measurement of parameters quantifying numerous effects in spintronics, such as spin-orbit torque, spin Hall magnetoresistance, spin Hall effect, and spin pumping. However, the standard expression for SMC, provided by the scattering theory in terms of the reflection probability amplitudes, is inapplicable when strong spin-orbit coupling (SOC) is present directly at the interface. This is the precisely the case of topological-insulator/ferromagnet and heavy-metal/ferromagnet interfaces of great contemporary interest. We introduce an approach where first-principles Hamiltonian of these interfaces, obtained from noncollinear density functional theory (ncDFT) calculations, is combined with charge-conserving Floquet-nonequilibrium-Green-function formalism to compute directly the pumped spin current ${I}_{\mathrm{L}}^{{S}_{z}}$ into semi-infinite left lead of two-terminal heterostructures $\mathrm{Cu}/X/\mathrm{Co}/\mathrm{Cu}$ or $Y/\mathrm{Co}/\mathrm{Cu}$---where $X={\mathrm{Bi}}_{2}{\mathrm{Se}}_{3}$ and $Y=\text{Pt}$ or W---due to microwave-driven steadily precessing magnetization of the Co layer. This allows us to extract an effective SMC as a prefactor in ${I}_{\mathrm{L}}^{{S}_{z}}$ versus precession cone angle $\ensuremath{\theta}$ dependence, as long as it remains the same, ${I}^{{S}_{z}}\ensuremath{\propto}{sin}^{2}\ensuremath{\theta}$, as in the case where SOC is absent. By comparing calculations where SOC in switched off versus switched on in ncDFT calculations, we find that SOC consistently reduces the pumped spin current and therefore the effective SMC.
Assessing variable activity for Bayesian regression trees

Abstract Bayesian Additive Regression Trees (BART) are non-parametric models that can capture complex exogenous variable effects. In any regression problem, it is often of interest to learn which variables are most active. Variable activity in BART is usually measured by counting the number of times a tree splits for each variable. Such one-way counts have the advantage of fast computations. Despite their convenience, one-way counts have several issues. They are statistically unjustified, cannot distinguish between main effects and interaction effects, and become inflated when measuring interaction effects. An alternative method well-established in the literature is Soboĺ indices, a variance-based global sensitivity analysis technique. However, these indices often require Monte Carlo integration, which can be computationally expensive. This paper provides analytic expressions for Soboĺ indices for BART posterior samples. These expressions are easy to interpret and are computationally feasible. Furthermore, we will show a fascinating connection between first-order (main-effects) Soboĺ indices and one-way counts. We also introduce a novel ranking method, and use this to demonstrate that the proposed indices preserve the Soboĺ-based rank order of variable importance. Finally, we compare these methods using analytic test functions and the En-ROADS climate impacts simulator.
Foveated Model Observers for Visual Search in 3D Medical Images

Model observers have a long history of success in predicting human observer performance in clinically-relevant detection tasks. New 3D image modalities provide more signal information but vastly increase the search space to be scrutinized. Here, we compared standard linear model observers (ideal observers, non-pre-whitening matched filter with eye filter, and various versions of Channelized Hotelling models) to human performance searching in 3D 1/f2.8 filtered noise images and assessed its relationship to the more traditional location known exactly detection tasks and 2D search. We investigated two different signal types that vary in their detectability away from the point of fixation (visual periphery). We show that the influence of 3D search on human performance interacts with the signal’s detectability in the visual periphery. Detection performance for signals difficult to detect in the visual periphery deteriorates greatly in 3D search but not in 3D location known exactly and 2D search. Standard model observers do not predict the interaction between 3D search and signal type. A proposed extension of the Channelized Hotelling model (foveated search model) that processes the image with reduced spatial detail away from the point of fixation, explores the image through eye movements, and scrolls across slices can successfully predict the interaction observed in humans and also the types of errors in 3D search. Together, the findings highlight the need for foveated model observers for image quality evaluation with 3D search.
Deep Reflectance Volumes: Relightable Reconstructions from Multi-view Photometric Images.

We present a deep learning approach to reconstruct scene appearance from unstructured images captured under collocated point lighting. At the heart of Deep Reflectance Volumes is a novel volumetric scene representation consisting of opacity, surface normal and reflectance voxel grids. We present a novel physically-based differentiable volume ray marching framework to render these scene volumes under arbitrary viewpoint and lighting. This allows us to optimize the scene volumes to minimize the error between their rendered images and the captured images. Our method is able to reconstruct real scenes with challenging non-Lambertian reflectance and complex geometry with occlusions and shadowing. Moreover, it accurately generalizes to novel viewpoints and lighting, including non-collocated lighting, rendering photorealistic images that are significantly better than state-of-the-art mesh-based methods. We also show that our learned reflectance volumes are editable, allowing for modifying the materials of the captured scenes.
Exploring the pH-Dependent Structure-Dynamics-Function Relationship of Human Renin.

Renin is a pepsin-like aspartyl protease and an important drug target for the treatment of hypertension; despite three decades’ research, its pH-dependent structure-function relationship remains poorly understood. Here we employed the continuous constant pH molecular dynamics (CpHMD) simulations to decipher the acid/base roles of renin’s catalytic dyad and the conformational dynamics of the flap, which is a common structural feature among aspartyl proteases. The calculated pKa’s suggest that the catalytic Asp38 and Asp226 serve as the general base and acid, respectively, in agreement with experiment and supporting the hypothesis that renin’s neutral optimum pH is due to the substrate-induced pKa shifts of the aspartic dyad. The CpHMD data confirmed our previous hypothesis that hydrogen bond formation is the major determinant of the dyad pKa order. Additionally, our simulations showed that renin’s flap remains open regardless of pH, although a Tyr-inhibited state is occasionally formed above pH 5. These findings are discussed in comparison to the related aspartyl proteases, including β-secretases 1 and 2, capthepsin D, and plasmepsin II. Our work represents a first step towards a systematic understanding of the pH-dependent structure-dynamics-function relationships of pepsin-like aspartyl proteases that play important roles in biology and human disease states.
Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules

The use of biological networks such as protein-protein interaction and transcriptional regulatory networks is becoming an integral part of genomics research. However, these networks are not static, and during phenotypic transitions like disease onset, they can acquire new "communities" (or highly interacting groups) of genes that carry out cellular processes. Disease communities can be detected by maximizing a modularity-based score, but since biological systems and network inference algorithms are inherently noisy, it remains a challenge to determine whether these changes represent real cellular responses or whether they appeared by random chance. Here, we introduce Constrained Random Alteration of Network Edges (CRANE), a method for randomizing networks with fixed node strengths. CRANE can be used to generate a null distribution of gene regulatory networks that can in turn be used to rank the most significant changes in candidate disease communities. Compared to other approaches, such as consensus clustering or commonly used generative models, CRANE emulates biologically realistic networks and recovers simulated disease modules with higher accuracy. When applied to breast and ovarian cancer networks, CRANE improves the identification of cancer-relevant GO terms while reducing the signal from non-specific housekeeping processes.
Noise Trading, Transaction Costs, and the Relationship of Stock Returns and Trading Volume

Abstract This article constructs an economic model of a rational trader who operates in a market with transaction costs and noise trading. The level of trading affects the rational trader's marginal cost of transacting; as a result, trading volume (through its effect on marginal cost) is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.
Synthesis of anthradithiophene containing conjugated polymers via a cross-coupling strategy

New conjugated polymers that incorporate dihexylanthradithiophene (DHADT) in the main chain were prepared by Stille, Sonogashira, and Yamamoto cross-coupling polymerization reactions. The polymerization chemistry is enabled by a soluble 5,11-dibromodihexylanthradithiophene monomer that is capable of cross-coupling reactions. Five readily soluble DHADT containing polymers were prepared and characterized experimentally and computationally. These polymers possess HOMO energies of −5.18 eV to −5.43 eV and LUMO energies of −3.0 eV to −2.82 eV. The notable optical features include broad absorption and band gaps ranging from 1.62 eV to 2.15 eV. Polymers were tested in organic field effect transistors and were found to operate in the p-type regime.
Intermarriage and the Intergenerational Transmission of Ethnic Identity and Human Capital for Mexican Americans.

We investigate whether selective intermarriage and endogenous ethnic identification interact to hide some of the intergenerational progress achieved by the Mexican-origin population in the United States. In part, we do this by comparing an “objective” indicator of Mexican descent (based on the countries of birth of the respondent and his parents and grandparents) with the standard “subjective” measure of Mexican self-identification (based on the respondent’s answer to the Hispanic-origin question). For third-generation Mexican American youth, we show that ethnic attrition is substantial and could produce significant downward bias in standard measures of attainment that rely on ethnic self-identification.
The supply of public school quality

Abstract Education economists have estimated many education production functions but they have not estimated a supply curve of public school quality. In order to estimate the supply of public school quality, the price of a unit of public schooling must be found. Invoking the theory of implicit markets, the price of a unit of public school quality is derived from a series of housing market hedonic estimations, in which house price is regressed as a function of school quality. The implicit price is then inserted in an estimation of the supply of public schooling. The estimated price elasticity of supply is 0.14, suggesting that: (1) demand-side policies do not effectively raise the quantity of public schooling supplied; and (2) school funding equalization attempts are not likely to significantly change the quantity of public school outcomes supplied in either rich or poor districts.
ASSET PRICE BUBBLES IN INCOMPLETE MARKETS

This paper reviews and extends the mathematical finance literature on bubbles in complete markets. We provide a new characterization theorem for bubbles under the standard no-arbitrage framework, showing that bubbles can be of three types. Type 1 bubbles are uniformly integrable martingales, and these can exist with an infinite lifetime. Type 2 bubbles are nonuniformly integrable martingales, and these can exist for a finite, but unbounded, lifetime. Last, Type 3 bubbles are strict local martingales, and these can exist for a finite lifetime only. When one adds a no-dominance assumption (from Merton [24]), only Type 1 bubbles remain. In addition, under Merton’s no-dominance hypothesis, put–call parity holds and there are no bubbles in standard call and put options. Our analysis implies that if one believes asset price bubbles exist and are an important economic phenomena, then asset markets must be incomplete.
Inequality, Democracy, and Persistence: Is There a Political Kuznets Curve?

The aim of this paper is to provide comprehensive empirical evidence on recent theories that link democracy and income inequality for the period 1960-1995. In simple cross-country regressions I find a non-monotonic link between these two variables when using ordinary least squares, instrumental variables, and Eusufzai tests. Since these results cannot be taken as "true" time series findings, even though recent theories that explain such a link are, I also employ recent methods applied to dynamic models on panel data. These techniques allow accounting for potential simultaneity and heterogeneity problems. Using the preferred econometric methodology, I also find support for the existence of a political Kuznets curve. Moreover, it appears that income inequality is unconditionally persistent. Results hold for two different democracy proxies and when sensitivity analysis is applied.
Administrative Equal Protection: Federalism, the Fourteenth Amendment, and the Rights of the Poor

This Article intervenes in a burgeoning literature on “administrative constitutionalism,” the phenomenon of federal agencies—rather than courts—assuming significant responsibility for elaborating the meaning of the U.S. Constitution. Drawing on original historical research, I document and analyze what I call “administrative equal protection”: interpretations of the Fourteenth Amendment’s Equal Protection Clause in a key federal agency at a time when the Clause’s meaning was fiercely contested. These interpretations are particularly important because of their interplay with cooperative federalism—specifically, with states’ ability to exercise their traditional police power after accepting federal money. The Article’s argument is based on a story of change over time. In the late 1930s, when federal courts appeared reluctant to vindicate equal protection claims, the Federal Social Security Board (later to become part of the Department of Health, Education and Welfare) took a more active role via its administration of federal grants for state-run public welfare programs. Through the 1940s and 1950s, agency lawyers developed and applied a nondeferential rationality model of equal protection to assess state welfare rules. When paired with the agency’s control over generous federal subsidies, this interpretation had tangible consequences: administrators challenged some of the era’s most restrictive state welfare laws and, in the process, spread the notion that poor Americans had constitutional rights, including under the Fourteenth Amendment. In the mid-1960s, as the agency became embroiled in battles over school desegregation, administrators deftly recharacterized their constitutional interpretation as a statutory one. They saw their constitutional arguments take on new life, however, as welfare rights advocates (including former agency personnel) wielded them in court. Both developments are visible in the landmark case King v. Smith (1968). There
Rethinking Probabilistic Prediction in the Wake of the 2016 U.S. Presidential Election

To many statisticians and citizens, the outcome of the most recent U.S. presidential election represents a failure of data-driven methods on the grandest scale. This impression has led to much debate and discussion about how the election predictions went awry — Were the polls inaccurate? Were the models wrong? Did we misinterpret the probabilities? — and how they went right — Perhaps the analyses were correct even though the predictions were wrong, that’s just the nature of probabilistic forecasting. With this in mind, we analyze the election outcome with respect to a core set of effectiveness principles. Regardless of whether and how the election predictions were right or wrong, we argue that they were ineffective in conveying the extent to which the data was informative of the outcome and the level of uncertainty in making these assessments. Among other things, our analysis sheds light on the shortcomings of the classical interpretations of probability and its communication to consumers in the form of predictions. We present here an alternative approach, based on a notion of validity, which offers two immediate insights for predictive inference. First, the predictions are more conservative, arguably more realistic, and come with certain guarantees on the probability of an erroneous prediction. Second, our approach easily and naturally reflects the (possibly substantial) uncertainty about the model by outputting plausibilities instead of probabilities. Had these simple steps been taken by the popular prediction outlets, the election outcome may not have been so shocking.
No News is Good News: Voluntary Disclosure in the Face of Litigation

We study disclosure dynamics when the firm value evolves stochastically over time. The presence of litigation risk, arising from the failure to disclose unfavorable information, crowds out positive disclosures. Litigation risk mitigates firms' tendency to use inefficient disclosure policies. From a policy perspective, we show that a stricter legal environment may be an efficient way to stimulate information transmission in capital markets, particularly when the nature of information is proprietary. We model the endogeneity of litigation risk in a dynamic setting and shed light on the empirical controversy regarding whether disclosure preempts or triggers litigation.
Vaccine safety in infants and children.

Abstract:Immunization is crucial to maintaining public health. This article addresses the benefits of childhood vaccinations and educates parents on the myths surrounding possible adverse reactions.
Not again! Public perception, regulation, and nanotechnology

It is often argued that immediate government action regarding nanotechnology is needed to ensure that public opinion does not mistakenly view nanotechnology as dangerous, to restore public trust in government, and to increase the legitimacy of government action through increased public participation. This article questions whether governments can achieve these goals. As the world lurches toward regulation of nanotechnology, we should ask Why the rush? Can anticipatory action, perceived as the government doing something, fulfill the competing hopes to “restore trust,”“pave the way” for nanotechnology, “increase awareness,” and “satisfy democratic notions of accountability”? Or is government action more likely to increase existing divisions over nanotechnology's future?
Patent Fair Use 2.0

It is time to update the idea of “patent fair use” to account for the evolution of technology and of inventive paradigms in the years since O’Rourke’s seminal proposal in 2000. A fair-use-type ex post approach to cabining patent exclusivity is even more attractive as a theoretical matter now than it was in 2000. In this article I propose and justify a set of “patent fair use 2.0” factors: 1) Is there a “justifiable” failure to purchase or license? 2) Did the infringer make a substantial improvement over the patentee’s invention and was there some reason for blocking patent failure? 3) Does the availability of alternative innovation paradigms in the technological arena provide evidence of reduced importance of patent incentives? 4) Was the infringer a knowing copyist, independent inventor, or something in between? If the infringer was not a knowing copyist was her failure to locate the patent through search reasonable in light of patent search costs in the particular technology, custom in the industry, the foreseeability of infringement, and the infringer’s commercial, non-commercial, or small entity status?
Strategic Cost Shifting and State Tax Minimization

ABSTRACT: In this study, we predict and find that multistate bank holding companies strategically allocate costs among their subsidiary banks to minimize tax. In particular, we find that high tax s...
On the spread and impact of anti-dumping

In this paper two key costs of AD protection are documented. First, once AD has been adopted, countries often have a difficult time restraining its use. In recent years \′new' users have accounted for half of the overall world total. Many of the heaviest AD users are countries who did not even have an AD statute a decade ago. Second, I will show that that, on average, AD duties cause the value of imports to fall by 30–50 per cent. I find that trade falls by almost as much for settled cases as for those that result in duties. I also find that, even for those cases that are rejected, imports fall. JEL Classification: F13 A propos de la generalisation et de l'impact des mesures anti-dumping. Ce memoire souligne deux couts importants des mesures de protection anti-dumping (AD). D'abord, une fois la mesure en place, les pays ont souvent de grandes difficultes a en restreindre l'usage. Au cours des annees recentes, les “nouveaux” utilisateurs de ces mesures comptent pour la moitie de l'activite AD dans le monde. Et plusieurs des pays qui en font un usage intensif n'avaient pas de loi AD il y a une decennie. Ensuite, en moyenne, les droits de douane AD entrainent une chute des importations de l'ordre de 30%a 50%. Et le commerce chute de presque autant pour les cas ou il y a resolution du probleme que pour ceux ou un tarif de retorsion est impose. Fait interessant, il appert que les importations chutent meme dans les cas ou la plainte est rejetee.
How to Discuss a Paper: Developing and Showcasing Your Scholarly Skills

ABSTRACT: We offer this paper as a primer for accounting doctoral students and new faculty on how to discuss a paper. We believe that this topic can serve to “jump start” the engagement of students and junior faculty in developing and delivering quality discussions. We begin by emphasizing the importance and benefits of being a good discussant to both the profession and the discussant. We then outline the discussion process and provide detailed suggestions on points to consider in each phase of this process: (1) volunteering to discuss, (2) receiving the discussion assignment, (3) preparing the discussion, (4) presenting the discussion, and (5) following up with the authors after the discussion. Next, we examine data that highlight the need for additional discussant volunteers at conferences. Finally, we present possible innovations to foster high-quality discussions. This paper formalizes the ideal process typically learned through years of mentoring and conference experience.
Voluntary disclosure of accruals in earnings press releases and the pricing of accruals

This study investigates firms’ decisions to disclose accruals information in earnings press releases versus to provide it only in 10-Q filings and the impact of this disclosure on the pricing of accruals. I find that firms disclose accruals in their press releases when earnings alone are a weak indication of cash flow performance and that following these disclosures the accruals information is fully impounded into stock prices. The evidence suggests that when investor demand for accruals is likely to exist and firms disclose the information in earnings press releases, the mispricing typically associated with accruals is mitigated.
Regulatory Takings: A Chronicle of the Construction of a Constitutional Concept

In the American constitutional system the sovereign has the power to enact regulations which are necessary to the common good and general welfare. But the Fifth Amendment to the United States Constitution proscribes that: No person shall be. . .deprived of. . .property, without due process of law; nor shall private property be taken for public use, without just compensation. And the question of whether a sovereign regulation has taken private property without just compensation has puzzled the United States Supreme Court for over two hundred years in over four hundred cases. This paper chronicles the leading cases and finds that the Court's present interpretation of regulatory takings sits upon a shaky foundation of split decisions; the Court's construction of the constitutional property remains a work in progress. It finds today's Supreme Court is fundamentally split into two blocs. This Great Divide is sometimes attributed to a difference in judicial philosophy. Those in the Court's conservative wing are typically described as practitioners of judicial restraint. Those in the Court's liberal wing are said to be judicial activists who are intent on reconstructing the Constitution's language to meet the exigencies of the times. The Court's constitutional property jurisprudence belies this stereotype. Its right wing is seeking to define the Takings Clause, beyond its original meaning, so as to discourage government activity. Conversely the left wing is more than willing to give wide discretion to legislative bodies to impose regulations without paying compensation to disappointed property owners.
Slavery as a Takings Clause Violation

This Article argues that slavery was a violation of the Takings Clause of the United States Constitution. Slaves, like all people, possessed a property right of self-ownership. When the government appropriated that property, through laws establishing slavery, the rightful owners of the property - the slaves - suffered uncompensated physical, regulatory and derivative takings. Victims of slavery, like victims of other impermissible takings, are constitutionally entitled to just compensation under the Takings Clause. This Article concludes by examining some potential judicial and legislative consequences of treating slavery as a Takings Clause violation.
The Legal and Psychosocial Context of Family Violence: Toward a Social Ecological Analysis

The purpose of this special issues is to advance our understanding of family violence by utilizing a social ecological framework that both encompasses and addresses the interrelationship between the legal and psychosocial contexts of family violence (Bronfenbrenner 1979; Garbarino 1977; Goldstein 1994; Moos 1973). A social ecological framework necessitates acknowledging and understanding that human behavior is influenced by several levels of analysis rather than only immediate and intrapersonal influences. Based on this perspective, researchers must take into account social, contextual, environmental, and individual factors to fully understand a particular phenomenon such as family violence. The articles themselves reflect current scholarly and professional trends towards a more interdisciplinary, systemic approach to complex psychosocial problems such as family violence. Each of the articles has a distinct focus on a particular aspect of family violence while at the same time highlighting several common themes: the interrelationship between law and social/cultural contexts, the importance of moving beyond overly individualistic assumptions about human behavior, and the importance of procedural fairness and substantive considerations across the varied legal and extralegal contexts in which interpersonal conflicts occur.
Hermite polynomial based expansion of European option prices

Abstract We seek a closed-form series approximation of European option prices under a variety of diffusion models. The proposed convergent series are derived using the Hermite polynomial approach. Departing from the usual option pricing routine in the literature, our model assumptions have no requirements for affine dynamics or explicit characteristic functions. Moreover, convergent expansions provide a distinct insight into how and on which order the model parameters affect option prices, in contrast with small-time asymptotic expansions in the literature. With closed-form expansions, we explicitly translate model features into option prices, such as mean-reverting drift and self-exciting or skewed jumps. Numerical examples illustrate the accuracy of this approach and its advantage over alternative expansion methods.
Mark Twain’s Cat: Investment experience, categorical thinking, and stock selection

Abstract This paper examines the effect of prior investment experience in specific industries on subsequent investment decisions. Using households’ trading records from a large discount broker between 1991 and 1996, I find that prior success in a given industry increases the likelihood of subsequent purchases in the same industry. The effect is stronger for more recent experiences and for less sophisticated or diversified investors, and it is not wealth enhancing. The results suggest investors categorize industries at a highly resolved level, finer than the Fama–French ten-industry classification. Similar effects are also apparent for size- and value-based categories but at smaller magnitudes.
CHOICE-CONSTRAINED CONJOINT ANALYSIS

Choice-constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part-worth utility functions that account for “revealed preference”—those products a respondent actually selects in an independent choice situation. CCCA uses an iterative penalty function estimation procedure that successively modifies initial regressionderived part worths so that respondent choices (either actual or intended) of real brands are predicted as accurately as possible. The paper first describes the motivation and rationale for CCCA and presents the mathematics of the algorithm. As an illustration, it applies the CCCA model and penalty function estimation procedure to a limited set of synthetic data. A second application of the technique is presented that uses data obtained by a major telecommunications firm that used conjoint analysis to examine the importance of several features of residential communication devices. The paper also discusses potential extensions of the CCCA model and the kinds of marketing applications for which it might be useful.
Judicial Review of Olympic and International Sports Arbitration Awards: Trends and Observations

The Court of Arbitration for Sport (CAS), which was established by the International Olympic Committee (IOC) in 1984, is a private international arbitral institution based in Lausanne, Switzerland, that is subject to Swiss law. CAS arbitration awards collectively constitute a developing body of private international sports law. The Code of Sports-related Arbitration (CAS Code), which governs CAS arbitration proceedings, provides that a CAS award is final and binding on the parties, subject only to judicial review by the Swiss Federal Tribunal (SFT). The SFT has ruled that CAS is sufficiently independent and impartial, and that its arbitration awards have the same force and effect as judgments rendered by courts of the world’s sovereign countries. In 1993, in G. v. Federation Equestre Internationale (Gundel), the SFT determined that the
Liability of Parent Corporations for Hazardous Waste Cleanup and Damages

In its haste to address the great threat to public health and welfare posed by hazardous waste disposal, Congress did not specifically state whether parent corporations of responsible parties should be brought within the purview of CERCLA. This articles shows that economic considerations, reflected in CERCLA, favor imposing liability on parent corporations of insolvent responsible parties. A rule limiting liability would frustrate the government’s enforcement efforts and afford parent corporations a “safe harbor” for conducting overly risky hazardous waste disposal activities. To effectuate the principal purposes of CERCLA–prompt and effective cleanup of unsafe disposal sites and imposition of liability upon all responsible parties–courts should pierce the corporate veils of insolvent subsidiaries. Federal common law principles empower courts to impose liability upon parent corporations in order to implement fully Congress’s manifest intent and purpose.
Technological Change and Political Turnover: The Democratizing Effects of the Green Revolution in India

Can technological change contribute to political turnover? Influential theories suggest that technological change represents a form of creative destruction that can weaken incumbents and strengthen outsiders, leading to political turnover. This paper investigates a large-scale historical natural experiment: the impact of the green revolution on single-party dominance in India. Drawing on a theoretical framework based on models of contests, this paper argues that high-yielding variety (HYV) crops strengthened the incentives and capacity of a politically excluded group, in this case agricultural producers, to seek greater political representation. Exploiting the timing of the introduction of HYV crops, together with district-level variation in suitability for the new crop technology, instrumental variables analyses show that the green revolution played a pivotal role in the rise of agrarian opposition parties and decline of single-party dominance. The findings support theories linking technological change to political turnover, with important implications for the political economy of democratization.
The Copyright Act's Licensing Exemption for Religious Performances of Religious Works Is Unconstitutional

Copyright Law grants an exclusive right of public performance to copyright owners. 17 U.S.C. § 110(3) exempts religious performances from copyright’s licensing requirements. This article comprehensively addresses the legislative history of this religious exemption, then analyzes the exemption under modern Establishment Clause jurisprudence. Under Section 110(3), dramatic works, even when performed for-profit and with paid performers, do not need a license if the performance is sufficiently “religious.” This is a broader exemption then those granted to other non-profit organizations under 17 U.S.C. § 110. Because the § 110(3) exemption does not alleviate an exceptional burden on religious exercise, and because it imposes a significant burden on content creators, it does not meet Cutter v. Wilkinson’s standards for permissible religious accommodations. Furthermore, because the statute requires courts to evaluate the religious character of works and services, it necessitates impermissible entanglement. The religious exemption is unconstitutional.
The Right to Contract: Use of Domestic Partnership as a Strategic Alternative to the Right to Marry Same-Sex Partners

Many legal scholars writing about same-sex marriage in recent years draw an analogy to constitutional analysis of historical bans on interracial marriage, arguing that prohibitions of same-sex marriage violate the Fourteenth Amendment's Equal Protection Clause in the same manner, because such prohibitions classify on the basis of sex, and thus violate heightened scrutiny. There is another lesson, however, to be drawn from the history of constitutional protection of interracial marriage. Shortly after the Civil War, a series of cases unsuccessfully argued that the Civil Rights Act of 1866 gave black Americans the right to make contracts, including a marriage contract, with whomever they chose. While the cases were almost uniformly unsuccessful then, narrowing the focus today to domestic partnerships and other nonmarriage, but legally recognized, relationships gives the argument renewed vigor. By focusing on the contractual elements of such relationships-the contractual components of marriage, but without the social, religious, and political freight of the institution-such an argument gives even rational basis review potential value, and offers a compelling strategy for future liti-