cssi/SciSciGPT-SciSciNet huggingface dataset:
Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance its sensitivity to flowers, we fine-tune this network using a single dataset of apple flower images. Since CNNs tend to produce coarse segmentations, we employ a refinement method to better distinguish between individual flower instances. Without any preprocessing or dataset-specific training, experimental results on images of apple, peach, and pear flowers, acquired under different conditions demonstrate the robustness and broad applicability of our method.
Multiband Probabilistic Cataloging: A Joint Fitting Approach to Point Source Detection and Deblending

Probabilistic cataloging (PCAT) outperforms traditional cataloging methods on single-band optical data in crowded fields (Portillo et al. 2017). We extend our work to multiple bands, achieving greater sensitivity ($\sim$ 0.4 mag) and greater speed (500x) compared to previous single-band results. We demonstrate the effectiveness of multiband PCAT on mock data, both in terms of recovering accurate posteriors in the catalog space, and in directly deblending sources. When applied to Sloan Digital Sky Survey (SDSS) observations of M2, taking Hubble Space Telescope data as truth, our joint fit on $r$ and $i$ band data goes $\sim0.4$ mag deeper than single-band probabilistic cataloging and has a false discovery rate less than 20\% for F606W$\leq 20$. Compared to DAOPHOT, the two-band SDSS catalog fit goes nearly 1.5 magnitudes deeper using the same data, and maintains a lower false discovery rate down to F606W$\sim 20.5$. Given recent improvements in computational speed, multiband PCAT shows promise in application to large-scale surveys and is a plausible framework for joint analysis of multi-instrument observational data.
Iterative hard thresholding for model selection in genome-wide association studies.

A genome-wide association study (GWAS) correlates marker and trait variation in a study sample. Each subject is genotyped at a multitude of SNPs (single nucleotide polymorphisms) spanning the genome. Here, we assume that subjects are randomly collected unrelateds and that trait values are normally distributed or can be transformed to normality. Over the past decade, geneticists have been remarkably successful in applying GWAS analysis to hundreds of traits. The massive amount of data produced in these studies present unique computational challenges. Penalized regression with the l1 penalty (LASSO) or minimax concave penalty (MCP) penalties is capable of selecting a handful of associated SNPs from millions of potential SNPs. Unfortunately, model selection can be corrupted by false positives and false negatives, obscuring the genetic underpinning of a trait. Here, we compare LASSO and MCP penalized regression to iterative hard thresholding (IHT). On GWAS regression data, IHT is better at model selection and comparable in speed to both methods of penalized regression. This conclusion holds for both simulated and real GWAS data. IHT fosters parallelization and scales well in problems with large numbers of causal markers. Our parallel implementation of IHT accommodates SNP genotype compression and exploits multiple CPU cores and graphics processing units (GPUs). This allows statistical geneticists to leverage commodity desktop computers in GWAS analysis and to avoid supercomputing. Availability: Source code is freely available at https://github.com/klkeys/IHT.jl.
A New Sample of (Wandering) Massive Black Holes in Dwarf Galaxies from High-resolution Radio Observations

We present a sample of nearby dwarf galaxies with radio-selected accreting massive black holes (BHs), the majority of which are non-nuclear. We observed 111 galaxies using sensitive, high-resolution observations from the Karl G. Jansky Very Large Array (VLA) in its most extended A-configuration at X-band (~8-12 GHz), yielding a typical angular resolution of ~0.25" and rms noise of ~15 uJy. Our targets were selected by cross matching galaxies with stellar masses M_stellar < 3 x 10^9 M_sun and redshifts z<0.055 in the NASA-Sloan Atlas with the VLA Faint Images of the Radio Sky at Twenty centimeters (FIRST) Survey. With our new high-resolution VLA observations, we detect compact radio sources towards 39 galaxies and carefully evaluate possible origins for the radio emission including thermal HII regions, supernova remnants, younger radio supernovae, background interlopers, and AGNs in the target galaxies. We find that 13 dwarf galaxies almost certainly host active massive BHs despite the fact that only one object was previously identified as having optical signatures of an AGN. We also identify a candidate dual radio AGN in a more massive galaxy system. The majority of the radio-detected BHs are offset from the center of the host galaxies with some systems showing signs of interactions/mergers. Our results indicate that massive BHs need not always live in the nuclei of dwarf galaxies, confirming predictions from simulations. Moreover, searches attempting to constrain BH seed formation using observations of dwarf galaxies need to account for such a population of "wandering" BHs.
Distribution-free binary classification: prediction sets, confidence intervals and calibration

We study three notions of uncertainty quantification -- calibration, confidence intervals and prediction sets -- for binary classification in the distribution-free setting, that is without making any distributional assumptions on the data. With a focus towards calibration, we establish a 'tripod' of theorems that connect these three notions for score-based classifiers. A direct implication is that distribution-free calibration is only possible, even asymptotically, using a scoring function whose level sets partition the feature space into at most countably many sets. Parametric calibration schemes such as variants of Platt scaling do not satisfy this requirement, while nonparametric schemes based on binning do. To close the loop, we derive distribution-free confidence intervals for binned probabilities for both fixed-width and uniform-mass binning. As a consequence of our 'tripod' theorems, these confidence intervals for binned probabilities lead to distribution-free calibration. We also derive extensions to settings with streaming data and covariate shift.
Two-dimensional higher-derivative supergravity and a new mechanism for supersymmetry breaking

Abstract We discuss the general form of quadratic (1,1) supergravity in two dimensions, and show that this theory is equivalent to two scalar supermultiplets coupled to nontrivial supergravity. It is demonstrated that the theory possesses stable vacua with vanishing cosmological constant which spontaneously break supersymmetry.
Fisher-KPP dynamics in diffusive Rosenzweig–MacArthur and Holling–Tanner models

We prove the existence of traveling fronts in diffusive Rosenzweig–MacArthur and Holling–Tanner population models and investigate their relation with fronts in a scalar Fisher-KPP equation. More precisely, we prove the existence of fronts in a Rosenzweig–MacArthur predator-prey model in two situations: when the prey diffuses at the rate much smaller than that of the predator and when both the predator and the prey diffuse very slowly. Both situations are captured as singular perturbations of the associated limiting systems. In the first situation we demonstrate clear relations of the fronts with the fronts in a scalar Fisher-KPP equation. Indeed, we show that the underlying dynamical system in a singular limit is reduced to a scalar Fisher-KPP equation and the fronts supported by the full system are small perturbations of the Fisher-KPP fronts. We obtain a similar result for a diffusive Holling–Tanner population model. In the second situation for the Rosenzweig–MacArthur model we prove the existence of the fronts but without observing a direct relation with Fisher-KPP equation. The analysis suggests that, in a variety of reaction–diffusion systems that rise in population modeling, parameter regimes may be found when the dynamics of the system is inherited from the scalar Fisher-KPP equation.
Exact analytic solution for the rotation of a rigid body having spherical ellipsoid of inertia and subjected to a constant torque

The exact analytic solution is introduced for the rotational motion of a rigid body having three equal principal moments of inertia and subjected to an external torque vector which is constant for an observer fixed with the body, and to arbitrary initial angular velocity. In the paper a parametrization of the rotation by three complex numbers is used. In particular, the rows of the rotation matrix are seen as elements of the unit sphere and projected, by stereographic projection, onto points on the complex plane. In this representation, the kinematic differential equation reduces to an equation of Riccati type, which is solved through appropriate choices of substitutions, thereby yielding an analytic solution in terms of confluent hypergeometric functions. The rotation matrix is recovered from the three complex rotation variables by inverse stereographic map. The results of a numerical experiment confirming the exactness of the analytic solution are reported. The newly found analytic solution is valid for any motion time length and rotation amplitude. The present paper adds a further element to the small set of special cases for which an exact solution of the rotational motion of a rigid body exists.
A Simple Approach to Learning Unsupervised Multilingual Embeddings

Recent progress on unsupervised cross-lingual embeddings in the bilingual setting has given the impetus to learning a shared embedding space for several languages. A popular framework to solve the latter problem is to solve the following two sub-problems jointly: 1) learning unsupervised word alignment between several language pairs, and 2) learning how to map the monolingual embeddings of every language to shared multilingual space. In contrast, we propose a simple approach by decoupling the above two sub-problems and solving them separately, one after another, using existing techniques. We show that this proposed approach obtains surprisingly good performance in tasks such as bilingual lexicon induction, cross-lingual word similarity, multilingual document classification, and multilingual dependency parsing. When distant languages are involved, the proposed approach shows robust behavior and outperforms existing unsupervised multilingual word embedding approaches.
Ultra-high Energy Cosmic Rays and Neutrinos from Gamma-Ray Bursts, Hypernovae and Galactic Shocks

Abstract I review gamma-ray burst models (GRBs) and observations, and discuss the possible production of ultra-high energy cosmic rays and neutrinos in both the standard internal shock models and the newer generation of photospheric and hadronic GRB models, in the light of current constraints imposed by IceCube, Auger and TA observations. I then discuss models that have been proposed to explain the recent astrophysical PeV neutrino observations, including star-forming and star-burst galaxies, hypernovae and galaxy accretion and merger shocks.
Complex Stiffness Model of Physical Human-Robot Interaction: Implications for Control of Performance Augmentation Exoskeletons

Human joint dynamic stiffness plays an important role in the stability of performance augmentation exoskeletons. In this paper, we consider a new frequency domain model of the human joint dynamics which features a complex value stiffness. This complex stiffness consists of a real stiffness and a hysteretic damping. We use it to explain the dynamic behaviors of the human connected to the exoskeleton, in particular the observed non-zero low frequency phase shift and the near constant damping ratio of the resonance as stiffness and inertia vary. We validate this concept with an elbow-joint exoskeleton testbed (attached to a subject) by experimentally varying joint stiffness behavior, exoskeleton inertia, and the strength augmentation gain. We compare three different models of elbow-joint dynamic stiffness: a model with real stiffness, viscous damping and inertia; a model with complex stiffness and inertia; and a model combining the previous two models. Our results show that the hysteretic damping term improves modeling accuracy (via a statistical F-test). Moreover, this term contributes more to model accuracy than the viscous damping term. In addition, we experimentally observe a linear relationship between the hysteretic damping and the real part of the stiffness which allows us to simplify the complex stiffness model down to a 1-parameter system. Ultimately, we design a fractional order controller to demonstrate how human hysteretic damping behavior can be exploited to improve strength amplification performance while maintaining stability.
A queueing system with on-demand servers: local stability of fluid limits

We study a system where a random flow of customers is served by servers (called agents) invited on-demand. Each invited agent arrives into the system after a random time; after each service completion, an agent returns to the system or leaves it with some fixed probabilities. Customers and/or agents may be impatient, that is, while waiting in queue, they leave the system at a certain rate (which may be zero). We consider the queue-length-based feedback scheme, which controls the number of pending agent invitations, depending on the customer and agent queue lengths and their changes. The basic objective is to minimize both customer and agent waiting times. We establish the system process fluid limits in the asymptotic regime where the customer arrival rate goes to infinity. We use the machinery of switched linear systems and common quadratic Lyapunov functions to approach the stability of fluid limits at the desired equilibrium point and derive a variety of sufficient local stability conditions. For our model, we conjecture that local stability is in fact sufficient for global stability of fluid limits; the validity of this conjecture is supported by numerical and simulation experiments. When local stability conditions do hold, simulations show good overall performance of the scheme.
Statistics of partial minima

We study pseudo-optimal solutions to multi-objective optimization problems by introducing partial minima defined as follows. Point x k-dominates x' when at least k of the coordinates of x are smaller than the corresponding coordinates of x'. A point not k-dominated by any other point in the set is a k-minimum or a partial minimum, generalizing the global minimum. We study statistical properties of partial minima for a set of N points independently distributed inside the d-dimensional unit hypercube using exact probabilistic methods and heuristic scaling techniques. The average number of partial minima, A, decays algebraically with the total number of points, A ~ N?(d?k)/k, when 1 ? k < d. Interestingly, there are k ? 1 distinct scaling laws characterizing the largest coordinates: the distribution P(yj) of the jth largest coordinate, yj, decays algebraically, , with for 1 ? j ? k ? 1. The average number of partial minima grows logarithmically, , when k = d. The full distribution of the number of minima is obtained in closed form in two dimensions.
On the effects of bursts of massive star formation during the evolution of elliptical galaxies

We consider the hypothesis that the formation of elliptical galaxies includes a phase in which star formation is mostly restricted to massive stars, with the bias towards high mass stars increasing with elliptical galaxy mass. The mass fraction of stars in this top-heavy mode of star formation is constrained by requiring the resulting stellar remnants to account for the observed increase in the mass-to-light ratio of ellipticals with increasing galaxy mass. We then consider the implications of this population of massive stars for the intracluster medium and the extragalactic background at various wavelengths. The mass and abundance ratios of metals produced by our proposed population of massive stars are consistent with the observations of the mass and abundance ratios of metals in the hot gas of galaxy clusters for most of the standard range of IMF slopes and SN II yields. The predicted energy density produced by this stellar population approaches current limits on the extragalactic background at both optical wavelengths, into which the ultraviolet radiation of the massive stars is likely to be redshifted, and far-infared wavelengths, at which starlight reprocessed by dust associated with the starburst will be observed. In either case, the background is predicted to be significantly clustered since massive ellipticals are clustered.
As a Matter of State: The Role of Thermodynamics in Magnetohydrodynamic Turbulence

Turbulence simulations play a key role in advancing the general understanding of the physical properties turbulence and in interpreting astrophysical observations of turbulent plasmas. For the sake of simplicity, however, turbulence simulations are often conducted in the isothermal limit. Given that the majority of astrophysical systems are not governed by isothermal dynamics, we aim to quantify the impact of thermodynamics on the physics of turbulence, through varying adiabatic index, $\gamma$, combined with a range of optically thin cooling functions. In this paper, we present a suite of ideal magnetohydrodynamics simulations of thermally balanced stationary turbulence in the subsonic, super-Alfvenic, high beta (ratio of thermal to magnetic pressure) regime, where turbulent dissipation is balanced by two idealized cooling functions (approximating linear cooling and free-free emission) and examine the impact of the equation of state by considering cases that correspond to isothermal, monatomic and diatomic gases. We find a strong anticorrelation between thermal and magnetic pressure independent of thermodynamics, whereas the strong anticorrelation between density and magnetic field found in the isothermal case weakens with increasing $\gamma$. Similarly, with the linear relation between variations in density and thermal pressure with sonic Mach number becomes steeper with increasing $\gamma$. This suggests that there exists a degeneracy in these relations with respect to thermodynamics and Mach number in this regime, which is dominated by slow magnetosonic modes. These results have implications for attempts to infer (e.g.) Mach numbers from (e.g.) Faraday rotation measurements, without additional information regarding the thermodynamics of the plasma. However, our results suggest that this degeneracy can be broken by utilizing higher-order moments of observable distribution functions.
Phase Separation in the Advective Cahn–Hilliard Equation

The Cahn–Hilliard equation is a classic model of phase separation in binary mixtures that exhibits spontaneous coarsening of the phases. We study the Cahn–Hilliard equation with an imposed advection term in order to model the stirring and eventual mixing of the phases. The main result is that if the imposed advection is sufficiently mixing, then no phase separation occurs, and the solution instead converges exponentially to a homogeneous mixed state. The mixing effectiveness of the imposed drift is quantified in terms of the dissipation time of the associated advection–hyperdiffusion equation, and we produce examples of velocity fields with a small dissipation time. We also study the relationship between this quantity and the dissipation time of the standard advection–diffusion equation.
Multi-Channel Neural Network for Assessing Neonatal Pain from Videos

Neonates do not have the ability to either articulate pain or communicate it non-verbally by pointing. The current clinical standard for assessing neonatal pain is intermittent and highly subjective. This discontinuity and subjectivity can lead to inconsistent assessment, and therefore, inadequate treatment. In this paper, we propose a multi-channel deep learning framework for assessing neonatal pain from videos. The proposed framework integrates information from two pain indicators or channels, namely facial expression and body movement, using convolutional neural network (CNN). It also integrates temporal information using a recurrent neural network (LSTM). The experimental results prove the efficiency and superiority of the proposed temporal and multi-channel framework as compared to existing similar methods.
Label-Efficient Learning on Point Clouds Using Approximate Convex Decompositions

The problems of shape classification and part segmentation from 3D point clouds have garnered increasing attention in the last few years. Both of these problems, however, suffer from relatively small training sets, creating the need for statistically efficient methods to learn 3D shape representations. In this paper, we investigate the use of Approximate Convex Decompositions (ACD) as a self-supervisory signal for label-efficient learning of point cloud representations. We show that using ACD to approximate ground truth segmentation provides excellent self-supervision for learning 3D point cloud representations that are highly effective on downstream tasks. We report improvements over the state-of-the-art for unsupervised representation learning on the ModelNet40 shape classification dataset and significant gains in few-shot part segmentation on the ShapeNetPart dataset. Our source code is publicly available (https://github.com/matheusgadelha/PointCloudLearningACD).
Trade in Financial Services and Capital Movements

International financial liberalization may alter saving–investment imbalances and patterns of capital flows across countries. Using a panel of OECD countries for 1990–1996, I examine how the liberalization of capital movements and financial services trade affects net private capital flows. Capital inflows tend to fall (rise) with the liberalization of commercial presence in banking and securities (insurance) services, possibly reflecting an increase (decrease) in saving. I find that capital account liberalization stimulates capital inflows, suggesting that better access to external financing helps sustain larger current account deficits. When cross-border trade is liberalized, capital inflows change insignificantly.
Injectivity of the Heisenberg X-ray transform

Abstract We initiate the study of X-ray tomography on sub-Riemannian manifolds, for which the Heisenberg group exhibits the simplest nontrivial example. With the language of the group Fourier transform, we prove an operator-valued incarnation of the Fourier Slice Theorem, and apply this new tool to show that a sufficiently regular function on the Heisenberg group is determined by its line integrals over sub-Riemannian geodesics. We also consider the family of taming metrics g ϵ approximating the sub-Riemannian metric, and show that the associated X-ray transform is injective for all ϵ > 0 . This result gives a concrete example of an injective X-ray transform in a geometry with an abundance of conjugate points.
Stability conditions and exceptional objects in triangulated categories

The goal of this paper is to study the subspace of stability condition $\Sigma_{\mathcal{E}}\subset \mathrm{Stab}(X)$ associated to an exceptional collection $\mathcal{E}$ on a projective variety $X$. Following Emanuele Macr\`{i}'s approach, we show a certain correspondence between the homotopy class of continuous loops in $\Sigma_{\mathcal{E}}$ and words of the braid group. In particular, we prove that in the case $X=\mathbb{P}^3$ and $\mathcal{E}=\{\mathcal{O},\mathcal{O}(1),\mathcal{O}(2),\mathcal{O}(3)\}$, the space $\Sigma_{\mathcal{E}}$ is a connected and simply connected 4-dimensional manifold.
Where should we go? Internet searches and tourist arrivals

The widespread availability of internet search data is a new source of high-frequency information that can potentially improve the precision of macroeconomic forecasting, especially in areas with data constraints. This paper investigates whether travel-related online search queries enhance accuracy in the forecasting of tourist arrivals to The Bahamas from the U.S. The results indicate that the forecast model incorporating internet search data provides additional information about tourist flows over a univariate approach using the traditional autoregressive integrated moving average (ARIMA) model and multivariate models with macroeconomic indicators. The Google Trends-augmented model improves predictability of tourist arrivals by about 30 percent compared to the benchmark ARIMA model and more than 20 percent compared to the model extended only with income and relative prices.
Computationally Efficient Learning of Large Scale Dynamical Systems: A Koopman Theoretic Approach

In recent years there has been a considerable drive towards data-driven analysis, discovery and control of dynamical systems. To this end, operator theoretic methods, namely, Koopman operator methods have gained a lot of interest. In general, the Koopman operator is obtained as a solution to a least-squares problem, and as such, the Koopman operator can be expressed as a closed-form solution that involves the computation of Moore-Penrose inverse of a matrix. For high dimensional systems and also if the size of the obtained data-set is large, the computation of the Moore-Penrose inverse becomes computationally challenging. In this paper, we provide an algorithm for computing the Koopman operator for high dimensional systems in a time-efficient manner. We further demonstrate the efficacy of the proposed approach on two different systems, namely a network of coupled oscillators (with state-space dimension up to 2500) and IEEE 68 bus system (with state-space dimension 204 and up to 24,000 time-points).
Group II Metabotropic Glutamate Receptors Modulate Sound Evoked and Spontaneous Activity in the Mouse Inferior Colliculus.

Little is known about the functions of Group II metabotropic glutamate receptors (mGluRs2/3) in the inferior colliculus (IC), a midbrain structure that is a major integration region of the central auditory system. We investigated how these receptors modulate sound-evoked and spontaneous firing in the mouse IC in vivo We first performed immunostaining and tested hearing thresholds to validate vesicular GABA transporter (VGAT)-ChR2 transgenic mice on a mixed CBA/CaJ x C57BL/6J genetic background. Transgenic animals allowed for optogenetic cell-type identification. Extracellular single neuron recordings were obtained before and after pharmacological mGluR2/3 activation. We observed increased sound-evoked firing, as assessed by the rate-level functions (RLFs), in a subset of both GABAergic and non-GABAergic IC neurons following mGluR2/3 pharmacological activation. These neurons also displayed elevated spontaneous excitability and were distributed throughout the IC area tested, suggesting a widespread mGluR2/3 distribution in the mouse IC.
At the Water's Edge: Coastal Settlement, Transformative Adaptation, and Well-Being in an Era of Dynamic Climate Risk.

With accelerating climate change, US coastal communities are experiencing increased flood risk intensity, resulting from accelerated sea level rise and stronger storms. These conditions place press...
Beyond Risk Shifting: The Knowledge-Transferring Role of Audit Liability Insurers*

Regulators and researchers tend to focus primarily on the risk-shifting benefits of audit liability insurance. We obtain field data from the US audit insurance industry (16 interviews and 83 survey responses) to examine whether insurers also possess characteristics favorable to transferring their private risk management knowledge to the audit firms they insure. Possessing such characteristics would enable insurers to use their relative knowledge advantage to provide a benefit to audit firms beyond risk shifting. Thus, examining this issue helps broaden our understanding of insurers’ role in auditing. We examine our data through the lens of the knowledge transfer theory and find evidence that audit liability insurers have the motivation and capacity to accumulate and transfer risk management knowledge to the audit firms they insure. We find that audit firms, particularly the small resource-constrained firms (i.e., non-Big 4 and non-second-tier), rely on and benefit from their insurers’ risk management knowledge. We also find that insurers transfer such knowledge through multiple mechanisms, including free consultative services, policy premium incentives, and CPE classes. Our results highlight the important role of audit insurers as transferors of risk management knowledge to audit firms. Broadly, our results extend knowledge transfer theory and suggest areas for future research in US and international contexts.
The Immediate Effect of COVID-19 Policies on Social-Distancing Behavior in the United States.

ObjectiveAlthough anecdotal evidence indicates the effectiveness of coronavirus disease 2019 (COVID-19) social-distancing policies, their effectiveness in relation to what is driven by public aware...
Asymmetric L–space knots

We construct the first examples of asymmetric L–space knots in S3. More specifically, we exhibit a construction of hyperbolic knots in S3 with both (i) a surgery that may be realized as a surgery on a strongly invertible link such that the result of the surgery is the double branched cover of an alternating link and (ii) trivial isometry group. In particular, this produces L–space knots in S3 which are not strongly invertible. The construction also immediately extends to produce asymmetric L–space knots in any lens space, including S1×S2.
Impacts of "Three Strikes and You're Out" on Crime Trends in California and Throughout the United States

The impacts of Three Strikes on crime in California and throughout the United States are analyzed using cross-sectional time series analysis of state-level data from 1986 to 2005. The model measures both deterrence and incapacitation effects, controlling for preexisting crime trends and economic, demographic, and policy factors. Despite limited use outside California, the presence of a Three Strikes law appears to be associated with slightly but significantly faster rates of decline in robbery, burglary, larceny, and motor vehicle theft nationwide. Three Strikes also is associated with slower declines in murder rates. Although California's law is the broadest and most frequently used Three Strikes policy, it has not produced greater incapacitation effects on crime than other states' far more limited laws. The analyses indicate that the toughest sentencing policy is not necessarily the most effective option.
What do we mean by accounting program quality? A decomposition of accounting faculty opinions

Abstract Institutional quality has been, and will continue to be, an important dimension of academic accounting. How we measure it, by increasingly featuring objective output measures, has taken the construct away from demonstrated meaningfulness among its most important constituency. This paper forms several research propositions that attempt to identify the antecedents of perceived accounting program quality. Using accounting faculty judgments about accounting programs provided to a popular press request – the Public Accounting Report – the results show that an institution's educational success is more important than its research productivity. More general school characteristics, including the program's accreditation profile and the reputation of the business school in which the program is embedded, are also significant in their direct association with perceived program quality. These more remote factors also indirectly impact program reputation through their significant direct effect on educational outcomes. Implications for further research are drawn.
ALTERNATIVE MONETARY POLICY RULES FOR SMALL OPEN ECONOMIES

This paper examines the relative merits of alternative monetary policy rules for a small open economy. Rules considered target: the exchange rate, price level, nominal income, or a monetary aggregate. The standard framework employed in previous comparisons of these rules fails to take account of important features of small open economies. In particular, the standard framework fails to consider the effects on aggregate supply of exchange rate adjustments resulting from adherence to policy rules. Incorporating these effects is shown to weaken the case for targeting nominal income and, more generally, to complicate the ranking of policy rules.
Efficient Kidney Exchange: Coincidence of Wants in Markets with Compatibility-Based Preferences

Patients needing kidney transplants may have donors who cannot donate to them because of blood or tissue incompatibility. Incompatible patient-donor pairs can exchange donor kidneys with other pairs only when there is a "double coincidence of wants." Developing infrastructure to perform three-way as well as two-way exchanges will have a substantial effect on the number of transplants that can be arranged. Larger than three-way exchanges have less impact on efficiency. In a general model of type-compatible exchanges, the size of the largest exchanges required to achieve efficiency equals the number of types.
Globalizing Standard of Patent Protection in WTO Law and Policy Options for the LDCs: The Context of Bangladesh

This Article analyzes the globalizing standard of patent protection as adopted under the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS Agreement) of the World Trade Organization (WTO) and possible options for the Least Developed Countries (LDCs) such as Bangladesh against the experiences of Brazil, India, and South Africa with special reference to pharmaceutical patent issues. The developed member countries of the WTO negotiated mandatory protections for pharmaceutical products and processes in the TRIPS Agreement on the basis that such mandatory protections will provide the necessary incentives for continued pharmaceutical innovation. In contrast, the developing countries and LDCs argued that enacting patent laws that comply
Dynamic commercial lobbying

This study explains the observed repeated personal interactions between lobbyists and policymakers. The analysis uses a dynamic model of commercial lobbying in which citizens may hire lobbyists to present policy proposals on their behalf to policymakers. It is shown that repeated interactions with lobbyists simplify a policymaker’s information problem in the presence of unverifiable information provision and allow a solution to their contracting problem. The welfare implications of these interactions depend on whether the policymakers’ information or contracting problem predominates. Further, the policymaker’s information problem and financial contributions may actually improve social welfare in comparison to the full information outcome.
The Cost of Compliance: FIN 48 and Audit Fees

ABSTRACT Effective for fiscal years beginning after December 15, 2006, FIN 48 significantly altered uncertain tax benefit (UTB) recognition and disclosure requirements relative to its predecessor standard, FAS 5. We examine the effect of the new standard on audit pricing. We first document that UTB-related audit fees increased following the implementation of FIN 48. However, we also find that this increase is primarily driven by a spike in the audit pricing of UTBs in 2007. Indeed, we find that the audit pricing of UTBs in the 2008–2012 period is not significantly different from that of the 2002–2006 period. We interpret these results to indicate that although firms incurred significant FIN 48 implementation costs, the ongoing audit pricing of UTBs under FIN 48 is similar to that of FAS 5. Our findings suggest that any potential benefits of FIN 48 may outweigh associated costs related to a temporary increase in audit fees. JEL Classifications: H25; M40; M41; M42; M48.
Accounting Education Research: Ranking Institutions and Individual Scholars

ABSTRACT: Previous rankings of accounting literature have largely ignored the subtopic of accounting education research. Given the important role that rankings play in creating incentives and bench...
COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays

During the COVID-19 pandemic, there has been an emerging need for rapid, dedicated, and point-of-care COVID19 patient disposition techniques to optimize resource utilization and clinical workflow. In view of this need, we present COVIDMobileXpert: a lightweight deep neural network (DNN) based mobile app that can use chest X-ray (CXR) for COVID-19 case screening and radiological trajectory prediction. We design and implement a novel three-player knowledge transfer and distillation (KTD) framework including a pre-trained attending physician (AP) network that extracts CXR imaging features from a large scale of lung disease CXR images, a fine-tuned resident fellow (RF) network that learns the essential CXR imaging features to discriminate COVID-19 from pneumonia and/or normal cases with a small amount of COVID-19 cases, and a trained lightweight medical student (MS) network to perform on-device COVID-19 patient triage and follow-up. To tackle the challenge of vastly similar and dominant fore-and background in medical images, we employ novel loss functions and training schemes for the MS network to learn the robust features. We demonstrate the significant potential of COVID-MobileXpert for rapid deployment via extensive experiments with diverse MS architecture and tuning parameter settings. The source codes for cloud and mobile based implementations are available from the following url: https://github.com/xinli0928/COVID-Xray.
Eastphalia as a Return to Westphalia

Prognosticators of the international scene have focused on two claims on which there is broad agreement: First, globalization is producing deep integration among nations, moving in the direction of quasi-constitutional global governance; and, second, Asia will significantly influence the world in decades to come. These two claims are in tension with each other. Asian countries have hardly been leaders in deep integration of the constitutionalist variety, though they have been effective participants in globalized markets. Projecting forward, one expects an Asia-dominated international law to emphasize traditional concerns of sovereignty, non-interference, and mutual cooperation rather than the constitutionalist vision of supranational institutions reaching deep into the way states govern themselves and treat their own populations. Eastphalia may be Westphalia without the universalism - a kinder, gentler Westphalia.
Solutions when the solution is the problem: Arraying the disarray in development

Summary. — An analytic framework for tracing three waves of efforts to provide key public services in developing countries is provided. Persistent (though not universal) failure has been the product of (a) the imperatives of large bureaucracies to discount decisions that are inherently both discretionary and transaction-intensive (and thus less able to be codified and controlled), and (b) good and bad reasons for believing that, because modern bureaucracies underpin rich country prosperity now, simply adopting their institutional form elsewhere is the surest way of facilitating development. Contemporary debates regarding the merits of incorporating more ‘‘participatory’’ approaches into public service delivery are best understood in this context. 2003 Published by Elsevier Ltd.
Are International Judges Afraid of Science?: A Comment on Mbengue

This article considers and critiques the proposition that international adjudicators are afraid or avoid determinations of scientific fact because of their discomfort with the technical expertise involved or the probabilistic judgments required of such fact-finding. It argues that this contention ignores the endemic fact-finding challenges faced by international tribunals generally, that the uncertainties attributed to “scientific” evidence are actually prevalent throughout the judicial process, that adjudicators are actually quite familiar with probabilistic judgments, and that structural constraints on courts and arbitrators and adjudicators’ own backgrounds affect how well fact-finding occurs, irrespective of whether it involves science. Finally, it suggests that to the extent international judges and arbitrators avoid confronting and answering head-on facts subject to scientific proof this may actually be a good thing.
Injecting demand through spillovers: Foreign direct investment, domestic socio-political conditions, and host-country entrepreneurial activity ☆

This study examines how foreign direct investment (FDI) spurs entrepreneurial activity in host countries. We also investigate why this relationship varies across countries because of domestic socio-political conditions. The findings from our panel analyses of 104 countries from 2000 to 2009 are consistent with our predictions that foreign direct investment positively relates to business creation and this positive effect is strongest in countries with poor institutional support, weak political stability, and low general human capital. Our work provides new insights into how cross-border investments and domestic socio-political conditions jointly influence entrepreneurial activity, especially in emerging and developing economies.
Inflation dynamics and monetary policy transmission in Vietnam and emerging Asia

Abstract This paper provides an overview of inflation developments in Vietnam in the years following the doi moi reforms, and uses empirical analysis to answer two key questions: (i) what are the key drivers of inflation in Vietnam, and what role does monetary policy play? and (ii) why has inflation in Vietnam been persistently higher than in most other emerging market economies in the region? It focuses on understanding the monetary policy transmission mechanism in Vietnam, and in understanding the extent to which monetary policy can explain why inflation in Vietnam has been higher than in other Asian emerging markets over the past decade.
Managing Credit Booms and Busts: A Pigouvian Taxation Approach

We study a dynamic model in which the interaction between debt ac- cumulation and asset prices magni…es credit booms and busts. We …nd that borrowers do not internalize these feedback eects and therefore suf- fer from excessively large booms and busts in both credit ‡ows and asset prices. We show that a Pigouvian tax on borrowing may induce borrowers to internalize these externalities and increase welfare. We calibrate the model by reference to (i) the US small and medium-sized enterprise sector and (ii) the household sector, and …nd the optimal tax to be countercycli- cal in both cases, dropping to zero in busts and rising to approximately half a percentage point of the amount of debt outstanding during booms.
ACTA and the Specter of Graduated Response

This article considers the evolution of ACTA’s “digital environment” provisions in the context of concerns raised early in the negotiations that the agreement would require signatories to mandate graduated response regimes for online copyright enforcement (a la France’s controversial HADOPI system). The Consolidated Text of ACTA released in October 2010, following the final round of negotiations in Japan, contains no provision mandating the adoption of graduated response. Such regimes are tacitly endorsed in the agreement, however, through language in the preamble and the digital environment provisions concerning the promotion of greater cooperation between rights owners and service providers. Moreover, opponents of graduated response should be wary of the fact that public law mechanisms—be they domestic or international—are not the only means by which graduated response can effectively become the law for Internet users. The United States and Ireland provide examples of the trend toward private ordering in the project of online copyright enforcement. 1 Associate Professor of Law, University of Idaho College of Law. The author would like to thank Michael Geist, David Post, and Peter Yu for their helpful comments and suggestions. The author would also like to thank Sean Flynn and the Program in Information Justice and Intellectual Property at American University for precipitating a very necessary public discussion on the public interest implications of ACTA. 2 ACTA and the Specter of Graduated Response WWW.WCL.AMERICAN.EDU/PIJIP ABSTRACT 1
Executives' horizon, internal governance and stock market liquidity

Abstract In this article, we examine whether internal governance, the process through which subordinate managers effectively monitor the chief executive officer (CEO), can improve a firm's liquidity. Using the difference in horizons between a CEO and his immediate subordinates to measure internal governance, we show that firms with better internal governance have lower information asymmetry and higher liquidity. Further, we show that internal governance is effective in enhancing liquidity for firms with CEOs close to retirement, firms that require higher firm-specific skills, and firms with experienced subordinate managers. Our results are robust to inclusion of conventional governance measures, alternative model specifications, and different measures of internal governance and liquidity.
The JOBS Act and IPO volume: Evidence that disclosure costs affect the IPO decision

Abstract In April 2012, the Jumpstart Our Business Startups Act (JOBS Act) was enacted to help revitalize the initial public offering (IPO) market, especially for small firms. During the year ending March 2014, IPO volume and the proportion of small firm issuers was the largest since 2000. Controlling for market conditions, we estimate that the JOBS Act has led to 21 additional IPOs annually, a 25% increase over pre-JOBS levels. Firms with high proprietary disclosure costs, such as biotechnology and pharmaceutical firms, increase IPO activity the most. These firms are also more likely to take advantage of the act׳s de-risking provisions, allowing firms to file the IPO confidentially while testing-the-waters.
Human Nature, the Laws of Nature, and the Nature of Environmental Law

This article explores the roles that human nature, the laws of nature, and the nature of the nation's lawmaking institutions have all played in the emergence and evolution of domestic environmental law and how the interrelated difficulties presented by each are reflected in the kinds of legal issues that surround environmental lawmaking. The article also discusses how these same difficulties impede environmental lawmaking by obscuring from lawmakers, judges, and the general population what is truly important about environmental law. Part I considers the ways in which the need for environmental law derives from the tendency of human nature to cause adverse environmental consequences and the ways in which the laws of nature make it more difficult to prevent those consequences absent the imposition of external legal rules. Part II describes how our nation's lawmaking institutions are similarly challenged by the laws of nature. This includes a discussion of how the kinds of laws necessary to bridge the gap between human nature and the laws of nature are systematically difficult for our lawmaking institutions to develop in the first instance and to maintain over time. Part III takes a closer look at one of the nation's most important legal institutions - the United States Supreme Court - and briefly discusses both its past shortcomings in environmental lawmaking and its potential in the future.