cssi/SciSciGPT-SciSciNet huggingface dataset:
Finite energy solutions to inhomogeneous nonlinear elliptic equations with sub-natural growth terms

We obtain necessary and sufficient conditions for the existence of a positive finite energy solution to the inhomogeneous quasilinear elliptic equation \[ -\Delta_{p} u = \sigma u^{q} + \mu \quad \text{on} \;\; \mathbb{R}^n \] in the sub-natural growth case $0<q<p-1$, where $\Delta_{p}$ ($1<p<\infty$) is the $p$-Laplacian, and $\sigma$, $\mu$ are positive Borel measures on $\mathbb{R}^n$. Uniqueness of such a solution is established as well. Similar inhomogeneous problems in the sublinear case $0<q<1$ are treated for the fractional Laplace operator $(-\Delta)^{\alpha}$ in place of $-\Delta_{p}$, on $\mathbb{R}^n$ for $0<\alpha<\frac{n}{2}$, and on an arbitrary domain $\Omega \subset \mathbb{R}^n$ with positive Green's function in the classical case $\alpha = 1$.
Monte Carlo Simulations of the SU(2) vacuum structure

Abstract Lattice Monte Carlo simulations are performed for the SU(2) Yang Mills gauge theory in the presence of an Abelian background with external sources to obtain information on the effective potential. The goal is to investigate the lowest Landau mode that, in the continuum one-loop effective potential, is the crucial mode for instability. It is shown that also in the lattice formulation this lowest Landau mode plays a very peculiar role, and it is important for the understanding of the vacuum properties.
Instantons and the monopole-like equations in eight dimensions

We search for an abelian description of the Yang-Mills instantons on certain eight dimensional manifolds with the special holonomies Spin(7) and SU(4). By mimicing the Seiberg-Witten theory in four dimensions, we propose a set of monopole-like equations governing the 8-dimensional U(1) connections and spinors, which are supposed to be the dual theory of the nonabelian instantons. We also give a naive test of the generalized S-duality in the abelian sector of 8-dimensional Yang-Mills theory. Some problems in this approach are pointed out.
Modeling the Effects of Inhomogeneous Aerosols on the Hot Jupiter Kepler-7b’s Atmospheric Circulation

Motivated by the observational evidence of inhomogeneous clouds in exoplanetary atmospheres, we investigate how proposed simple cloud distributions can affect atmospheric circulations and infrared emission. We simulated temperatures and winds for the hot Jupiter Kepler-7b using a three-dimensional atmospheric circulation model that included a simplified aerosol radiative transfer model. We prescribed fixed cloud distributions and scattering properties based on results previously inferred from Kepler-7b optical phase curves, including inhomogeneous aerosols centered along the western terminator and hypothetical cases in which aerosols additionally extended across much of the planet's night side. In all cases, a strong jet capable of advecting aerosols from a cooler nightside to dayside was found to persist, but only at the equator. Colder temperatures at mid- and polar-latitudes might permit aerosol to form on the dayside without the need for advection. By altering the deposition and redistribution of heat, aerosols along the western terminator produced an asymmetric heating that effectively shifts the hottest spot further east of the sub-stellar point than expected for a uniform distribution. The addition of opaque high clouds on the nightside can partly mitigate this enhanced shift by retaining heat that contributes to warming west of the hotspot. These expected differences in infrared phase curves could place constraints on proposed cloud distributions and their infrared opacities for brighter hot Jupiters.
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras

Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, developing algorithms for event measurements requires a new class of hand crafted algorithms. Deep learning has shown great success in providing model free solutions to many problems in the vision community, but existing networks have been developed with frame based images in mind, and there does not exist the wealth of labeled data for events as there does for images for supervised training. To these points, we present EV-FlowNet, a novel self-supervised deep learning pipeline for optical flow estimation for event based cameras. In particular, we introduce an image based representation of a given event stream, which is fed into a self-supervised neural network as the sole input. The corresponding grayscale images captured from the same camera at the same time as the events are then used as a supervisory signal to provide a loss function at training time, given the estimated flow from the network. We show that the resulting network is able to accurately predict optical flow from events only in a variety of different scenes, with performance competitive to image based networks. This method not only allows for accurate estimation of dense optical flow, but also provides a framework for the transfer of other self-supervised methods to the event-based domain.
ON THE LOW FALSE POSITIVE PROBABILITIES OF KEPLER PLANET CANDIDATES

We present a framework to conservatively estimate the probability that any particular planet-like transit signal observed by the Kepler mission is in fact a planet, prior to any ground-based follow-up efforts. We use Monte Carlo methods based on stellar population synthesis and Galactic structure models, and report false positive probabilities (FPPs) for every Kepler Object of Interest, assuming a 20% intrinsic occurrence rate of close-in planets in the radius range 0.5 R_⊕ 10% to <1%. Since Kepler has detected many more planetary signals than can be positively confirmed with ground-based follow-up efforts in the near term, these calculations will be crucial to using the ensemble of Kepler data to determine population characteristics of planetary systems. We also describe how our analysis complements the Kepler team's more detailed BLENDER false positive analysis for planet validation.
Microresonator Brillouin laser stabilization using a microfabricated rubidium cell.

We frequency stabilize the output of a miniature stimulated Brillouin scattering (SBS) laser to rubidium atoms in a microfabricated cell to realize a laser system with frequency stability at the 10−11 level over seven decades in averaging time. In addition, our system has the advantages of robustness, low cost and the potential for integration that would lead to still further miniaturization. The SBS laser operating at 1560 nm exhibits a spectral linewidth of 820 Hz, but its frequency drifts over a few MHz on the 1 hour timescale. By locking the second harmonic of the SBS laser to the Rb reference, we reduce this drift by a factor of 103 to the level of a few kHz over the course of an hour. For our combined SBS and Rb laser system, we measure a frequency noise of 4 × 104 Hz2/Hz at 10 Hz offset frequency which rapidly rolls off to a level of 0.2 Hz2/Hz at 100 kHz offset. The corresponding Allan deviation is ≤2 × 10−11 for averaging times spanning 10−4 to 103 s. By optically dividing the signal of the laser down to microwave frequencies, we generate an RF signal at 2 GHz with phase noise at the level of −76 dBc/Hz and −140 dBc/Hz at offset frequencies of 10 Hz and 10 kHz, respectively.
Image Classification in the Dark Using Quanta Image Sensors

State-of-the-art image classifiers are trained and tested using well-illuminated images. These images are typically captured by CMOS image sensors with at least tens of photons per pixel. However, in dark environments when the photon flux is low, image classification becomes difficult because the measured signal is suppressed by noise. In this paper, we present a new low-light image classification solution using Quanta Image Sensors (QIS). QIS are a new type of image sensors that possess photon-counting ability without compromising on pixel size and spatial resolution. Numerous studies over the past decade have demonstrated the feasibility of QIS for low-light imaging, but their usage for image classification has not been studied. This paper fills the gap by presenting a student-teacher learning scheme which allows us to classify the noisy QIS raw data. We show that with student-teacher learning, we can achieve image classification at a photon level of one photon per pixel or lower. Experimental results verify the effectiveness of the proposed method compared to existing solutions.
Open Access Legislation and Regulation in the United States: Implications for Higher Education

Accessing quality research when not part of an academic institution can be challenging. Dating back to the 1980s, open access (OA) was a response to journal publishers who restricted access to publications by requiring a subscription and limited access to knowledge. Although the OA movement seeks to remove costly barriers to accessing research, especially when funded by state and federal governments, it remains the subject of continuous debates. After providing a brief overview of OA, this article summarizes OA statutory and regulatory developments at the federal and state levels regarding free and open access to research. It compares similarities and differences among enacted and proposed legislation and describes the advantages and disadvantages of these laws. It analyzes the effects of these laws in higher education, especially on university faculty regarding tenure and promotion decisions as well as intellectual property rights to provide recommendations and best practices regarding the future of legislation and regulation in the United States.
Enhanced Normalized Mutual Information for Localization in Noisy Environments

Fine localization is a crucial task for autonomous vehicles. Although many algorithms have been explored in the literature for this specific task, the goal of getting accurate results from commodity sensors remains a challenge. As autonomous vehicles make the transition from expensive prototypes to production items, the need for inexpensive, yet reliable solutions is increasing rapidly. This article considers scenarios where images are captured with inexpensive cameras and localization takes place using pre-loaded fine maps of local roads as side information. The techniques proposed herein extend schemes based on normalized mutual information by leveraging the likelihood of shades rather than exact sensor readings for localization in noisy environments. This algorithmic enhancement, rooted in statistical signal processing, offers substantial gains in performance. Numerical simulations are used to highlight the benefits of the proposed techniques in representative application scenarios. Analysis of a Ford image set is performed to validate the core findings of this work.
Parallel Algorithms for Successive Convolution

The development of modern computing architectures with ever-increasing amounts of parallelism has allowed for the solution of previously intractable problems across a variety of scientific disciplines. Despite these advances, multiscale computing problems continue to pose an incredible challenge to modern architectures because they require resolving scales that often vary by orders of magnitude in both space and time. Such complications have led us to consider alternative discretizations for partial differential equations (PDEs) which use expansions involving integral operators to approximate spatial derivatives (Christlieb et al. in J Comput Phys 379:214–236, 2019; Christlieb et al. J Sci Comput 82:52(3):1–29, 2020; Christlieb et al. J Comput Phys 415:1–25, 2020). These constructions use explicit information within the integral terms, but treat boundary data implicitly, which contributes to the overall speed of the method. This approach is provably unconditionally stable for linear problems and stability has been demonstrated experimentally for nonlinear problems. Additionally, it is matrix-free in the sense that it is not necessary to invert linear systems and iteration is not required for nonlinear terms. Moreover, the scheme employs a fast summation algorithm that yields a method with a computational complexity of $${\mathcal {O}}(N)$$ , where N is the number of mesh points along a coordinate direction. While much work has been done to explore the theory behind these methods, their practicality in large scale computing environments is a largely unexplored topic. In this work, we explore the performance of these methods by developing a domain decomposition algorithm suitable for distributed memory systems along with shared memory algorithms. As a first pass, we derive an artificial Courant–Friedrichs–Lewy condition that enforces a nearest-neighbor (N-N) communication pattern and briefly discuss possible generalizations. We also analyze several approaches for implementing the parallel algorithms by optimizing predominant loop structures and maximizing data reuse. Using a hybrid design that employs MPI and Kokkos (Edwards and Trott in J Parallel Distrib Comput 74:3202–3216, 2014) for the distributed and shared memory components of the algorithms, respectively, we show that our methods are efficient and can sustain an update rate $$> 1\times 10^8$$ DOF/node/s. We provide results that demonstrate the scalability and versatility of our algorithms using several different PDE test problems, including a nonlinear example, which employs an adaptive time-stepping rule.
Nonlinear Modal Decoupling Based Power System Transient Stability Analysis

Nonlinear modal decoupling (NMD) was recently proposed to nonlinearly transform a multi-oscillator system into as many decoupled oscillators as the oscillation modes of interests with the original system. Those decoupled oscillators together provide a fairly accurate approximation of behaviors of the original system in an extended neighborhood of the equilibrium. Each oscillator has just one degree of freedom and hence can easily be analyzed to infer the nonlinear dynamics of the original system associated with one oscillation mode. As the first attempt of applying the NMD methodology to realistic power system models, this paper proposes an NMD-based approach for the early warning of the oscillation mode that may most likely develop into a mode of transient instability. For a multi-machine power system, the approach first derives decoupled nonlinear oscillators by a coordinates transformation, and then applies Lyapunov stability analysis to decoupled oscillators to assess the stability of the original system. For large-scale power grids, the proposed approach can be efficiently applied by conducting NMD regarding only selected modes. Case studies on a 3-machine 9-bus system and an northeast power coordinating council (NPCC) 48-machine 140-bus system show the potentials of the approach in early warning of transient instability for multi-machine systems.
Transcript assembly improves expression quantification of transposable elements in single-cell RNA-seq data.

Transposable elements (TEs) are an integral part of the host transcriptome. TE-containing noncoding RNAs (ncRNAs) show considerable tissue specificity and play important roles during development, including stem cell maintenance and cell differentiation. Recent advances in single-cell RNA-seq (scRNA-seq) revolutionized cell type-specific gene expression analysis. However, effective scRNA-seq quantification tools tailored for TEs are lacking, limiting our ability to dissect TE expression dynamics at single-cell resolution. To address this issue, we established a TE expression quantification pipeline that is compatible with scRNA-seq data generated across multiple technology platforms. We constructed TE-containing ncRNA references using bulk RNA-seq data and showed that quantifying TE expression at the transcript level effectively reduces noise. As proof of principle, we applied this strategy to mouse embryonic stem cells and successfully captured the expression profile of endogenous retroviruses in single cells. We further expanded our analysis to scRNA-seq data from early stages of mouse embryogenesis. Our results illustrated the dynamic TE expression at preimplantation stages and revealed 146 TE-containing ncRNA transcripts with substantial tissue specificity during gastrulation and early organogenesis.
A Model for Coronal Inflows and In/Out Pairs

This report presents a three-dimensional (3D) numerical magnetohydrodynamics (MHD) model of the white-light coronagraph observational phenomena known as coronal inflows and in/out pairs. Coronal inflows in the LASCO/C2 field of view (approximately 2-6 Rs) were thought to arise from the dynamic and intermittent release of solar wind plasma associated with the helmet streamer belt as the counterpart to outward-propagating streamer blobs, formed by magnetic reconnection. This interpretation was essentially confirmed with the subsequent identification of in/out pairs and the multispacecraft observations of their 3D structure. The MHD simulation results show relatively narrow lanes of density depletion form high in the corona and propagate inwards with sinuous motion which has been characterized as `tadpole-like' in coronagraph imagery. The height--time evolution and velocity profiles of the simulation inflows and in/out pairs are compared to their corresponding observations and a detailed analysis of the underlying magnetic field structure associated with the synthetic white-light and mass density evolution is presented. Understanding the physical origin of this structured component of the slow solar wind's intrinsic variability could make a significant contribution to solar wind modeling and the interpretation of remote and in-situ observations from Parker Solar Probe and Solar Orbiter.
A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes.

Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.
Adaptive Correspondence Experiments

Correspondence experiments probe for discrimination by manipulating employer perceptions of applicant characteristics. We consider the gains from dynamically adapting the number and quality of fictitious applications each employer receives to their prior callback decisions. Calibrating employer behavior to experimental data from Nunley et al. (2015), we find that it is possible to cut the number of applications required to detect a fixed number of discriminators roughly in half relative to a benchmark design with a fixed number of applications per job. These gains are achieved primarily from abandoning jobs with very low callback probabilities and those that call back Black applicants.
Trajectory Optimization for Nonlinear Multi-Agent Systems using Decentralized Learning Model Predictive Control *

We present a decentralized minimum-time trajectory optimization scheme based on learning model predictive control for multi-agent systems with nonlinear decoupled dynamics and coupled state constraints. By performing the same task iteratively, data from previous task executions is used to construct and improve local time-varying safe sets and an approximate value function. These are used in a decoupled MPC problem as terminal sets and terminal cost functions. Our framework results in a decentralized controller, which requires no communication between agents over each iteration of task execution, and guarantees persistent feasibility, finite-time closed-loop convergence, and non-decreasing performance of the global system over task iterations. Numerical experiments of a multi-vehicle collision avoidance scenario demonstrate the effectiveness of the proposed scheme.
Insects and recent climate change

Insects have diversified through more than 450 million y of Earth's changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.
A Multiperiod Newsvendor Problem with Partially Observed Demand

We consider a newsvendor problem with partially observed Markovian demand. Demand is observed if it is less than the inventory. Otherwise, only the event that it is larger than or equal to the inventory is observed. These observations are used to update the demand distribution from one period to the next. The state of the resulting dynamic programming equation is the current demand distribution, which is generally infinite dimensional. We use unnormalized probabilities to convert the nonlinear state transition equation to a linear one. This helps in proving the existence of an optimal feedback ordering policy. So as to learn more about the demand, the optimal order is set to exceed the myopic optimal order. The optimal cost decreases as the demand distribution decreases in the hazard rate order. In a special case with finitely many demand values, we characterize a near-optimal solution by establishing that the value function is piecewise linear.
Redacting proprietary information at the initial public offering

Nearly 40% of IPO firms redact information from their SEC registration filings. These firms exhibit characteristics consistent with the need to shield proprietary information from potential rivals. They experience greater underpricing, but pre-IPO insiders reduce underpricing-related wealth transfers by selling proportionately less of the firm's shares at the IPO, raising more equity financing in later seasoned equity offerings, and selling their own holdings at a relatively slow pace. The information environment of redacting firms reflects proportionately more private information than that of non-redacting firms post-IPO, but this difference abates by the fourth year. Consistent with the view that redacted proprietary information provides competitive advantages, redacting firms exhibit superior financial performance post-IPO. The results illustrate tradeoffs in balancing a firm's needs to protect proprietary information with its capital needs, investor needs for information to price securities, and pre-IPO owner liquidity needs.
Perceptions of Crime: A Multidimensional Analysis with Implications for Law and Psychology

In the last forty years, the study of social perceptions of crime in general, and the seriousness of criminal offenses in particular, has been of substantial interest to policymakers, courts, and social scientists. As a matter of criminal justice policy, consensus about how severe a crime is can serve as both a legal and societal foundation for certain criminal justice policy decisions, or about the proper punishment for that crime. From a social psychological perspective, studying individual differences in the perceptions of crime can supply valuable information both for basic knowledge about the thinking of individuals who differ on, for instance, gender, race, age, education, or political ideology, and for applied knowledge that can be used in a judicial or legislative arena. Alternatively, a hierarchy of the perceived seriousness of various criminal offenses can give insight into what is valued in a particular culture. The difficulty of defining seriousness, however, has led to substantive and methodological critiques of this literature. The present study is the latest to investigate the dimensional nature of perceptions of crime seriousness or severity, through multidimensional scaling techniques (MDS). MDS is a procedure that helps researchers uncover hidden structures in existing data by graphically plotting respondents' perceptions of perceived similarities (or dissimilarities) among various stimuli. When these stimuli are located on a plot based on such perceptions, underlying dimensions that respondents may have used (consciously or not) can be inferred. In two empirical studies I identify and validate three dimensions underlying perceptions of crime seriousness: amount of harm, infringement or deprivation of autonomy, and recklessness. I discuss implications for psychology, law, and policy.
Familial Influences on Recantation in Substantiated Child Sexual Abuse Cases

The underlying reasons for recantation in children's disclosure of child sexual abuse (CSA) have been debated in recent years. In the present study, we examined the largest sample of substantiated CSA cases involving recantations to date (n = 58 cases). We specifically matched those cases to 58 nonrecanters on key variables found to predict recantation in prior research (i.e., child age, alleged parent figure perpetrator, and caregiver unsupportiveness). Bivariate analyses revealed that children were less likely to recant when they were (1) initially removed from home postdisclosure and (2) initially separated from siblings postdisclosure. Multivariate analyses revealed that children were less likely to recant when family members (other than the nonoffending caregiver) expressed belief in the children's allegations and more likely to recant when family members (other than the nonoffending caregiver) expressed disbelief in the allegations and when visitations with the alleged perpetrator were recommended at their first hearing. Results have implications for understanding the complex ways in which social processes may motivate some children to retract previous reports of sexual abuse.
Prosecutorial Discretion and the Neglect of Juvenile Shielding Statutes

This Article reviews the failure of juvenile shielding statutes to take hold in the prosecution of cases involving child witnesses because of prosecutors’ discretionary decisions not to use these statutes. The Article investigates prosecutors’ pragmatic and doctrinal justifications for not utilizing juvenile shielding statutes and concludes that the proffered reasons are legitimate. Building on these insights, the Article concludes by offering legislative reform designed to revitalize juvenile shielding statutes. The discussion that follows proceeds in three parts. Part II describes the development of juvenile shielding laws, particularly the circumstances sparking the public and academic demand for protection of juvenile witnesses during in-court testimony, the resulting state legislative enactments of juvenile shielding statutes, and the Supreme Court’s validation of these statutes in Craig. This Part then describes evidence revealing the unexpected failure of prosecutors to use this modern and constitutional litigation device. Part III fleshes out the multiple factors that have led prosecutors to seldom use such statutes, despite expectations to the contrary. Generally, prosecutors’ concerns reflect four ideas: namely, that shielding is (1) infeasible, (2) needless, (3) ineffective, and (4) impermissible. Even in the wake of Craig, a follow-up assessment of each explanation shows them all to be legitimate. Part IV draws on the observations in Part III to suggest that legislators must pay close attention to who is granted standing to request protective measures, who falls within the protected class of witnesses, and which technologies are best utilized to effectuate shielding. Evaluation of these matters leads to three reform proposals. First, witnesses must be given authority independent from prosecutors to request shielding. Second, the class of witnesses eligible for protection should not be limited by the witness’s role in the case or the characteristics of the case or child. Third, legislative enactments should eschew reliance on electronic technologies. In essence, this Article suggests that legislative adoption of these reforms — and only legislative adoption of these reforms — will invigorate shielding laws in a way that permits them to achieve their original and salutary purposes.
Data revisions and the identification of monetary policy shocks

Abstract Monetary policy research using time-series methods has been criticized for using more information than the Federal Reserve had available. To quantify the role of this criticism, we estimate VARs with real-time data while accounting for the latent nature of many economic variables, such as output. Our estimated monetary policy shocks are closely correlated with typically estimated measures. The impulse response functions are broadly similar across estimation methods. Our evidence suggests that the use of revised data in VAR analyses of monetary policy shocks may not be a serious limitation for recursively identified systems, but presents more challenges for simultaneous systems.
How Lethal Injection Reform Constitutes Impermissible Research on Prisoners

This essay exposes how recent attempts at lethal injection reform have involved unethical and illegal research on prisoners. States are varying the doses and types of drugs used, developing methods designed for non-medical professionals to administer medical procedures, and gathering data or made provision for the gathering of data to learn from executions gone wrong. When individual prisoners are executed under these conditions, states are conducting research on them. Conducting research or experimentation on prisoners in the process of reform is problematic because it violates ethical frameworks and state laws. The Supreme Court has recently taken up the challenge of elucidating the standard for determining the constitutionality of lethal injection. If the Court suggests an approach to lethal injection reform that is akin to some of the more thoughtful and cautious approaches other courts have proposed, the Court’s decision may also contravene state laws or ethical precepts regarding research with prisoners. Thus, this paper provides important limitations on the kinds of reform that may be permissible and outlines the open questions that must be addressed before it can be determined whether the risks and uncertainties involved in lethal injection can be remedied.
The case against Microsoft: An ethical perspective

In the early summer of 1998 at a prominent ethicsconference in California, a panel of expertsﬁelding questions from the audience was takenaback by a blunt query about Microsoft.Thepanelists had been handling a number of vexingissues with insight and efﬁciency, but thisparticular inquiry seemed to throw them intodisarray.The question was simple enough – didthey think that the Microsoft Corporation was anethical company? Unable to reach any consensusabout this, the panel decided to poll the audience,which consisted of representatives from thebusiness and academic communities.The audi-ence, however, was as indecisive as the experts –just over one half of the participants agreed withthe proposition that Microsoft was not a model ofethical probity, but the remaining portion did notsee any reason to question the company’s moralrectitude.Since that conference Microsoft’s reputationhas been noticeably tarnished.In the UnitedStates the company has endured an epicanti-trust trial in which it has been forced todefend itself against accusations of harmful anti-consumer behavior.The company has also beenthe subject of several investigations initiated byother countries.In 2000, for example, theEuropean Commission began its own ofﬁcialinquiry into claims that Microsoft’s Windows2000 software was being leveraged to help thecompany solidify its control over electroniccommerce.More recently, a number of countriesin Europe and Asia have begun encouraginggovernment agencies to use open source codesoftware because they are ‘afraid that Microsofthas become too powerful in critical softwaremarkets’ (Lohr 2002).Throughout its lengthy trial in the US, Micro-soft argued with great insistence that it had donenothing wrong, that its actions were pro-compe-titive in the ‘rough and tumble’ world ofcapitalism.While many economists and corporateleaders have sided with the US government,Microsoft has not been without some ardentsupporters.For example, after the initial verdictwas handed down, the Wall Street Journal(‘Microsoft’s Real World’ 2000) described thecompany as a victim of ‘viliﬁcation and politicalgamesmanship.’ While some economists admitthat Microsoft might have played rough, theyacknowledge that rough play is not necessarilytantamount to a violation of any antitrust laws.McKenzie (2000), for example, regards Microsoftas ‘an aggressive but constrained competitor.’Even the courts have had a hard time decidingabout Microsoft.While Judge Jackson of thefederal district court found Microsoft guilty onvirtually all counts, the US Court of Appeals forthe DC District overturned much of Jackson’sruling and dismissed him for his partiality.Thisappeals court, however, did agree with Jacksonthat Microsoft was guilty of anti-competitivebehavior during its parrying with Netscape overcontrol of the browser market.Microsoft, ofcourse, has never accepted this conclusion even asit seeks to ﬁnalize a settlement with the federalgovernment.So, is Microsoft an ethical company? Thatquestion is even more difﬁcult to answer todaygiven the complicated nature of the rapidly
Optimal agenda-setter timing

We analyze the optimal timing problem of an agenda setter who can propose a project that is then voted on by a committee. The payoff consists of a common stochastic component and an idiosyncratic component that differs among committee members. The agenda setter may be biased for or against the project, relative to the median committee member, and chooses when to call the vote. We analyze how the timing decision depends on the political environment and the bias of the agenda setter. We show that both positively and negatively biased agenda setters can implement decisions that differ from those preferred by the median committee member. On analyse le timing optimal d'un maitre de l'ordre du jour qui peut proposer un projet sur lequel un comite va alors se prononcer. Le gain a deux composantes : l'une commune et stochastique, et l'autre idiosyncratique et variable selon les membres du comite. Le maitre de l'ordre du jour peut pencher en faveur ou contre le projet, par rapport au membre median du comite, et il choisit le moment du vote. On analyse comment cette decision du moment du vote depend de l'environnement politique et du biais du maitre de l'ordre du jour. On montre que les maitres de l'ordre du jour (en faveur ou contre le projet) peuvent engendrer des decisions qui different de celles preferees par le membre median du comite.
Health Outcomes Metrics and the Role of Financial Derivative Instruments in the Health Care Industry

Despite a culture of innovation, the U.S. health care system has been markedly deficient in its implementation of information technology (IT). Although recent initiatives have endeavored to remedy this shortcoming, fragmentation, high costs, information asymmetries, and evolving regulatory guidance have delayed meaningful adoption of health IT. At the same time, health IT has been heralded as a panacea that will help stakeholders attain the aspirational goals of reducing health care costs and improving health outcomes. While the extent to which existing platforms achieve these goals is debatable, there is little doubt that health IT will play an indispensible role for stakeholders throughout the health care industry. In line with the symposium theme of envisioning the next quarter century of health care law, this Essay explores emerging issues in health IT with a focus on health outcomes metrics and the role of financial derivative instruments in the health care industry. I begin by examining how aggregated patient data can be utilized to create outcomes-based measures such as health outcomes indices (HOIs). HOIs integrate multiple sources of real-world patient data to create metrics that timely and accurately measure the burden of disease, track health status, or evaluate health system performance. By accurately capturing and measuring patient outcomes over time, HOIs endeavor to provide stakeholders with a valuable tool with which to measure, assess, and predict health outcomes at the population level. Independent validation of HOIs as accurate barometers of patient outcomes will permit use of the metrics for a variety of purposes related to health economics, public health policy, and health care management. One promising avenue relates to HOI-based financial derivative instruments. HOI-based derivatives aim to provide public and private stakeholders with a dynamic opportunity with which to manage investments, capture value movements of assets, prioritize expenditures, and hedge risk.
The Press as a Watchdog for Accounting Fraud

This paper investigates the press’s role as a monitor or “watchdog” for accounting fraud. I find that the press fulfills this role by rebroadcasting information from other information intermediaries (analysts, auditors, and lawsuits) and by undertaking original investigation and analysis. Articles based on original analysis provide new information to the markets while those that rebroadcast allegations from other intermediaries do not. Consistent with a dual role for the press, I find that business-oriented press is more likely to undertake original analysis while nonbusiness periodicals focus primarily on rebroadcasting. I also investigate the determinates of press coverage, finding systematic biases in the types of firms and frauds for which articles are published. In general, the press covers firms and frauds that will be of interest to a broad set of readers and situations that are lower cost to identify and investigate.
Digital Rights and Freedoms: A Framework for Surveying Users and Analyzing Policies

Interest has been revived in the creation of a “bill of rights” for Internet users. This paper analyzes users’ rights into ten broad principles, as a basis for assessing what users regard as important and for comparing different multi-issue Internet policy proposals. Stability of the principles is demonstrated in an experimental survey, which also shows that freedoms of users to participate in the design and coding of platforms appear to be viewed as inessential relative to other rights. An analysis of users’ rights frameworks that have emerged over the past twenty years also shows that such proposals tend to leave out freedoms related to software platforms, as opposed to user data or public networks. Evaluating policy frameworks in a comparative analysis based on prior principles may help people to see what is missing and what is important as the future of the Internet continues to be debated.
ETF Arbitrage, Non-Fundamental Demand, and Return Predictability

Non-fundamental demand shocks have significant effects on asset prices, but observing these shocks is challenging. We use the exchange-traded fund (ETF) primary market to study non-fundamental demand. Unique to the ETF market, specialized arbitrageurs called authorized participants correct violations of the law of one price between an ETF and its underlying assets by creating or redeeming ETF shares. We show theoretically and empirically that creation and redemption activities (ETF flows) provide signals of non-fundamental demand shocks. A portfolio that is short high-flow ETFs and long low-flow ETFs earns excess returns of 1.1–2.0% per month, consistent with non-fundamental demand distorting asset prices away from fundamental values. Moreover, we show non-fundamental demand imposes non-trivial costs on investors, leading to underperformance.
Online and official price indexes: Measuring Argentina's inflation

Abstract Prices collected from online retailers can be used to construct daily price indexes that complement official statistics. This paper studies their ability to match official inflation estimates in five Latin American countries, with a focus on Argentina, where official statistics have been heavily criticized in recent years. The data were collected between October 2007 and March 2011 from the largest supermarket in each country. In Brazil, Chile, Colombia, and Venezuela, online price indexes approximate both the level and main dynamics of official inflation. By contrast, Argentina's online inflation rate is nearly three times higher than the official estimate.
Choiceless Choices: Deportation and the Parent-Child Relationship

Although family relationships play a central role in immigration law, immigration law ultimately makes judgments about individuals. Given that the vast majority of children live in the context of family, there are tensions between children's and parent's rights in situations where immigration law reaches different conclusions about the legal rights of parents and children to remain in the United States. These tensions are exacerbated by immigration law's conceptualization of adult parents as active rights holders and children as passive objects subject to their control. The article places the immigration framework in broader context of the parent-child relationship and explains ways in which family law does not trump, but rather transcends immigration law. One implication of this is that family courts, not immigration courts, are the ultimate decision makers in the resolution of family differences regarding separation prompted by the operation of immigration laws.
Black hole gluing in de Sitter space

We construct dynamical many-black-hole spacetimes with well-controlled asymptotic behavior as solutions of the Einstein vacuum equation with positive cosmological constant. We accomplish this by gl...
Why Some Firms Export

This paper presents a dynamic model of the export decision by a profit-maximizing fi rm. Using ap anel of U.S. manufacturing plants, we test for the role of plant characteristics, spillovers from neighboring exporters, entry costs and government export promotion expenditures. Entry and exit in the export market by U.S. plants is substantial, past exporters are apt to reenter, and plants are likely to export in consecutive years. However, we find that entry costs are significant and spillovers from the export activity of other plants negligible. State export promotion expenditures have no significant effect on the probability of exporting. Plant characteristics, especially those indicative of past success, strongly increase the probability of exporting as do
China’s Copyright Protection for Audio-Visual Works – A Comparison with Europe and the U.S.

One of the most heated debates in the current Chinese Copyright Law Revision is copyright protection of films. Individual creators/authors of films (such as a film director or script writer) have criticized the current rule, which vests copyright ownership of a film with the producer of a film, as depriving them of a fair opportunity to share in the commercial success of their work. As a result, the guilds representing individual creators have been lobbying to change the current “producer-ownership” rule to “individual creator-ownership” model, or as an alternative, leaving copyright ownership of films to be decided by contract. Not surprisingly, movie studios are objecting to such a proposed change. To build a successful movie industry, China is looking for inspiration from the Hollywood model − the U.S. copyright protection of films. Yet because China’s copyright system is based on the Continental European model, a comparison with its origin − France and Germany − seems inevitable. This paper compares copyright protection of films in France, Germany and the U.S. with China (from its first Copyright Law in 1999, its subsequent revisions until the most recent one), in terms of film authorship, ownership and remuneration scheme. In the end, the author proposes a hybrid model for China – reserving the Continental European concept of moral rights for individual authors, while vesting ownership of a film with the producer of a film, and at the same time, introducing a more balanced remuneration scheme for individual creators in a film.
A meta-analysis of hypothetical bias in stated preference valuation

Individuals are widely believed to overstate their economic valuation of a good by a factor of two or three. This paper reports the results of a meta-analysis of hypothetical bias in 28 stated preference valuation studies that report monetary willingness-to-pay and used the same mechanism for eliciting both hypothetical and actual values. The papers generated 83 observations with a median ratio of hypothetical to actual value of only 1.35, and the distribution has severe positive skewness. We find that a choice-based elicitation mechanism is important in reducing bias. We provide some evidence that the use of student subjects may be a source of bias, but since this variable is highly correlated with group experimental settings, firm conclusions cannot be drawn. There is some weak evidence that bias increases when public goods are being valued, and that some calibration methods may be effective at reducing bias. However, results are quite sensitive to model specification, which will remain a problem until a comprehensive theory of hypothetical bias is developed.