cssi/SciSciGPT-SciSciNet huggingface dataset:
Magnetic Helicity and Large Scale Magnetic Fields: A Primer

Magnetic fields of laboratory, planetary, stellar, and galactic plasmas commonly exhibit significant order on large temporal or spatial scales compared to the otherwise random motions within the hosting system. Such ordered fields can be measured in the case of planets, stars, and galaxies, or inferred indirectly by the action of their dynamical influence, such as jets. Whether large scale fields are amplified in situ or a remnant from previous stages of an object’s history is often debated for objects without a definitive magnetic activity cycle. Magnetic helicity, a measure of twist and linkage of magnetic field lines, is a unifying tool for understanding large scale field evolution for both mechanisms of origin. Its importance stems from its two basic properties: (1) magnetic helicity is typically better conserved than magnetic energy; and (2) the magnetic energy associated with a fixed amount of magnetic helicity is minimized when the system relaxes this helical structure to the largest scale available. Here I discuss how magnetic helicity has come to help us understand the saturation of and sustenance of large scale dynamos, the need for either local or global helicity fluxes to avoid dynamo quenching, and the associated observational consequences. I also discuss how magnetic helicity acts as a hindrance to turbulent diffusion of large scale fields, and thus a helper for fossil remnant large scale field origin models in some contexts. I briefly discuss the connection between large scale fields and accretion disk theory as well. The goal here is to provide a conceptual primer to help the reader efficiently penetrate the literature.
Gradient Boosted Normalizing Flows

By chaining a sequence of differentiable invertible transformations, normalizing flows (NF) provide an expressive method of posterior approximation, exact density evaluation, and sampling. The trend in normalizing flow literature has been to devise deeper, more complex transformations to achieve greater flexibility. We propose an alternative: Gradient Boosted Normalizing Flows (GBNF) model a density by successively adding new NF components with gradient boosting. Under the boosting framework, each new NF component optimizes a sample weighted likelihood objective, resulting in new components that are fit to the residuals of the previously trained components. The GBNF formulation results in a mixture model structure, whose flexibility increases as more components are added. Moreover, GBNFs offer a wider, as opposed to strictly deeper, approach that improves existing NFs at the cost of additional training---not more complex transformations. We demonstrate the effectiveness of this technique for density estimation and, by coupling GBNF with a variational autoencoder, generative modeling of images. Our results show that GBNFs outperform their non-boosted analog, and, in some cases, produce better results with smaller, simpler flows.
Holographic renormalization of Einstein-Maxwell-Dilaton theories

We generalize the boundary value problem with a mixed boundary condition that involves the gauge and scalar fields in the context of Einstein-Maxwell-Dilaton theories. In particular, the expectation value of the dual scalar operator can be a function of the expectation value of the current operator. The properties are prevalent in a fixed charge ensemble because the conserved charge is shared by both fields through the dilaton coupling, which is also responsible for non-Fermi liquid properties. We study the on-shell action and the stress energy tensor to note practical importances of the boundary value problem. In the presence of the scalar fields, physical quantities are not fully fixed due to the finite boundary terms that manifest in the massless scalar or the scalar with mass saturating the Breitenlohner-Freedman bound.
Inflation and de Sitter holography

We develop the relation between de Sitter holography and in∞ation in detail with particular attention to cosmic density perturbations. We set up the Hamilton-Jacobi formalism to present a systematic treatment of the logarithmic corrections to a scale in- variant spectrum. Our computations can be interpreted without reference to holography, as strong infra-red efiects in gravity. This point of view may be relevant for the flne-tuning problems inherent to in∞ation.
Degrees of Projections of Rank Loci

We provide formulas for the degrees of the projections of the locus of square matrices with given rank from linear spaces spanned by a choice of matrix entries. The motivation for these computations stems from applications to “matrix rigidity”; we also view them as an excellent source of examples to test methods in intersection theory, particularly computations of Segre classes. Our results are generally expressed in terms of intersection numbers in Grassmannians, which can be computed explicitly in many cases. We observe that, surprisingly (to us), these degrees appear to match the numbers of Kekule structures of certain benzenoid hydrocarbons, and arise in many other contexts with no apparent direct connection to the enumerative geometry of rank conditions.
Competitive privacy in the smart grid: An information-theoretic approach

Advances in sensing and communication capabilities as well as power industry deregulation are driving the need for distributed state estimation at the regional transmission organizations (RTOs). This leads to a new competitive privacy problem amongst the RTOs since there is a tension between sharing data to ensure network reliability (utility/benefit to all RTOs) and withholding data for profitability and privacy reasons. The resulting tradeoff between utility, quantified via fidelity of its state estimate at each RTO, and privacy, quantified via the leakage of the state of one RTO at other RTOs, is captured precisely using a lossy source coding problem formulation for a two RTO network. For a two-RTO model, it is shown that the set of all feasible utility-privacy pairs can be achieved via a single round of communication when each RTO communicates taking into account the correlation between the measured data at both RTOs. The lossy source coding problem and solution developed here is also of independent interest.
Space- and time-dependent scaling of numbers in mathematical structures: effects on physical and geometric quantities

The relationship between the foundations of mathematics and physics is a topic of of much interest. This paper continues this exploration by examination of the effect of space- and time- dependent number scaling on theoretical descriptions of some physical and geometric quantities. Fiber bundles provide a good framework to introduce a space- and time- or space---time-dependent number scaling field. The effect of the scaling field on a few nonlocal physical and geometric quantities is described. The effect on gauge theories is to introduce a new complex scalar field into the derivatives appearing in Lagrangians. U(1) invariance of Lagrangian terms does not affect the real part of the scaling field. For this field, any mass is possible. The scaling field is also shown to affect quantum wave packets and path lengths, and geodesic equations even on flat space. Scalar fields described so far in physics are possible candidates for the scaling field. The lack of direct evidence for the field in physics restricts the scaling field in that the gradient of the field must be close to zero in a local region of cosmological space and time. There are no restrictions outside the region. It is also seen that the scaling field does not affect comparisons of computation or measurements outputs with one another. However, it does affect the assignment of numerical values to the outputs of computations or measurements. These are needed because theory predictions are in terms of numerical values.
A categorification for the Tutte polynomial

In [5], Khovanov introduced a graded homology theory for classical links and showed it yields the Jones polynomial by taking the graded Euler characteristic. This construction has sparked a good deal of interests in recent years. In [3], Helme-Guizon and Rong constructed a graded homology theory for graphs. The graded Euler characteristic of the homology groups is the chromatic polynomial of the graph.
Impact load mitigation in sandwich beams using local resonators

Dynamic response of sandwich beams with resonators embedded in the cores subjected to impact loads is studied. Using finite element models the effectiveness of various local resonator frequencies u...
Online feedback control for input-saturated robotic systems on Lie groups

In this paper, we propose an approach to designing online feedback controllers for input-saturated robotic systems evolving on Lie groups by extending the recently developed Sequential Action Control (SAC). In contrast to existing feedback controllers, our approach poses the nonconvex constrained nonlinear optimization problem as the tracking of a desired negative mode insertion gradient on the configuration space of a Lie group. This results in a closed-form feedback control law even with input saturation and thus is well suited for online application. In extending SAC to Lie groups, the associated mode insertion gradient is derived and the switching time optimization on Lie groups is studied. We demonstrate the efficacy and scalability of our approach in the 2D kinematic car on SE(2) and the 3D quadrotor on SE(3). We also implement iLQG on a quadrator model and compare to SAC, demonstrating that SAC is both faster to compute and has a larger basin of attraction. Index-Terms— sequential action control; Lie group; online feedback control; input saturation
Ideal triangulations and geometric transitions

Thurston introduced a technique for finding and deforming three-dimensional hyperbolic structures by gluing together ideal tetrahedra. We generalize this technique to study families of geometric structures that transition from hyperbolic to anti de Sitter (AdS) geometry. Our approach involves solving Thurston's gluing equations over several different shape parameter algebras. In the case of a punctured torus bundle with Anosov monodromy, we identify two components of real solutions for which there are always nearby positively oriented solutions over both the complex and pseudo-complex numbers. These complex and pseudo-complex solutions define hyperbolic and AdS structures that, after coordinate change in the projective model, may be arranged into one continuous family of real projective structures. We also study the rigidity properties of certain AdS structures with tachyon singularities.
Stellar Granulation as the Source of High-frequency Flicker in Kepler Light Curves

A large fraction of cool, low-mass stars exhibit brightness fluctuations that arise from a combination of convective granulation, acoustic oscillations, magnetic activity, and stellar rotation. Much of the short-timescale variability takes the form of stochastic noise, whose presence may limit the progress of extrasolar planet detection and characterization. In order to lay the groundwork for extracting useful information from these quasi-random signals, we focus on the origin of the granulation-driven component of the variability. We apply existing theoretical scaling relations to predict the star-integrated variability amplitudes for 508 stars with photometric light curves measured by the Kepler mission. We also derive an empirical correction factor that aims to account for the suppression of convection in F-dwarf stars with magnetic activity and shallow convection zones. So that we can make predictions of specific observational quantities, we performed Monte Carlo simulations of granulation light curves using a Lorentzian power spectrum. These simulations allowed us to reproduce the so-called flicker floor (i.e., a lower bound in the relationship between the full light-curve range and power in short-timescale fluctuations) that was found in the Kepler data. The Monte Carlo model also enabled us to convert the modeled fluctuation variance into a flicker amplitude directly comparable with observations. When the magnetic suppression factor described above is applied, the model reproduces the observed correlation between stellar surface gravity and flicker amplitude. Observationally validated models like these provide new and complementary evidence for a possible impact of magnetic activity on the properties of near-surface convection.
Braiding Statistics and Link Invariants of Bosonic/Fermionic Topological Quantum Matter in 2+1 and 3+1 dimensions

Abstract Topological Quantum Field Theories (TQFTs) pertinent to some emergent low energy phenomena of condensed matter lattice models in 2+1 and 3+1 dimensions are explored. Many of our TQFTs are highly-interacting without free quadratic analogs. Some of our bosonic TQFTs can be regarded as the continuum field theory formulation of Dijkgraaf–Witten twisted discrete gauge theories. Other bosonic TQFTs beyond the Dijkgraaf–Witten description and all fermionic TQFTs (namely the spin TQFTs) are either higher-form gauge theories where particles must have strings attached, or fermionic discrete gauge theories obtained by gauging the fermionic Symmetry-Protected Topological states (SPTs). We analytically calculate both the Abelian and non-Abelian braiding statistics data of anyonic particle and string excitations in these theories, where the statistics data can one-to-one characterize the underlying topological orders of TQFTs. Namely, we derive path integral expectation values of links formed by line and surface operators in these TQFTs. The acquired link invariants include not only the familiar Aharonov–Bohm linking number, but also Milnor triple linking number in 3 dimensions, triple and quadruple linking numbers of surfaces, and intersection number of surfaces in 4 dimensions. We also construct new spin TQFTs with the corresponding knot/link invariants of Arf(–Brown–Kervaire), Sato–Levine and others. We propose a new relation between the fermionic SPT partition function and the Rokhlin invariant. As an example, we can use these invariants and other physical observables, including ground state degeneracy, reduced modular S x y and T x y matrices, and the partition function on RP 3 manifold, to identify all ν ∈ Z 8 classes of 2+1 dimensional gauged Z 2 -Ising-symmetric Z 2 f -fermionic Topological Superconductors (realized by stacking ν layers of a pair of chiral and anti-chiral p -wave superconductors [ p + i p and p − i p ], where boundary supports non-chiral Majorana–Weyl modes) with continuum spin-TQFTs.
Quantum gravity: Meaning and measurement

A discussion of the meaning of a physical concept cannot be separated from discussion of the conditions for its ideal measurement. We assert that quantization is no more than the invocation of the quantum of action in the explanation of some process or phenomenon, and does not imply an assertion of the fundamental nature of such a process. This leads to an ecumenical approach to the problem of quantization of the gravitational field. There can be many valid approaches, each of which should be judged by the domain of its applicability to various phenomena. If two approaches have overlapping domains, the relation between them then itself becomes a subject of study. We advocate an approach to general relativity based on the unimodular group, which emphasizes the physical significance and measurability of the conformal and projective structures. A discussion of the method of matched asymptotic expansions, and of the weakness of terrestrial sources compared with astrophysical and cosmological sources, leads us to suggest theoretical studies of gravitational radiation based on retrodiction (observation) rather than prediction (experimentation).
Limit of Quasilocal Mass at Spatial Infinity

We study the limit of quasilocal mass defined in [4 and 5] for a family of spacelike 2-surfaces in spacetime. In particular, we show the limit coincides with the ADM mass at spatial infinity. The limit for coordinate spheres of a boosted slice of the Schwarzchild solution is computed explicitly and shown to give the expected energy-momentum four-vector.
Billiards with Bombs

ABSTRACTIn this article, we define a variant of billiards in which the ball bounces around a square grid erasing walls as it goes. We prove that there exist periodic tunnels with arbitrarily large period from any possible starting point, that there exist nonperiodic tunnels from any possible starting point, and that there are versions of the problem for which the same starting point and initial direction result in periodic tunnels of arbitrarily large period. We conjecture that there exist starting conditions which do not lead to tunnels, justify the conjecture with simulation evidence, and discuss the difficulty of proving it.
Accomplishing high-level tasks with modular robots

The advantage of modular self-reconfigurable robot systems is their flexibility, but this advantage can only be realized if appropriate configurations (shapes) and behaviors (controlling programs) can be selected for a given task. In this paper, we present an integrated system for addressing high-level tasks with modular robots, and demonstrate that it is capable of accomplishing challenging, multi-part tasks in hardware experiments. The system consists of four tightly integrated components: (1) a high-level mission planner, (2) a large design library spanning a wide set of functionality, (3) a design and simulation tool for populating the library with new configurations and behaviors, and (4) modular robot hardware. This paper builds on earlier work by Jing et al. (in: Robotics: science and systems, 2016), extending the original system to include environmentally adaptive parametric behaviors, which integrate motion planners and feedback controllers with the system.
Learning Data Augmentation Strategies for Object Detection

Much research on object detection focuses on building better model architectures and detection algorithms. Changing the model architecture, however, comes at the cost of adding more complexity to inference, making models slower. Data augmentation, on the other hand, doesn’t add any inference complexity, but is insufficiently studied in object detection for two reasons. First it is more difficult to design plausible augmentation strategies for object detection than for classification, because one must handle the complexity of bounding boxes if geometric transformations are applied. Secondly, data augmentation attracts less research attention perhaps because it is believed to add less value and to transfer poorly compared to advances in network architectures.
Semantic Curiosity for Active Visual Learning.

In this paper, we study the task of embodied interactive learning for object detection. Given a set of environments (and some labeling budget), our goal is to learn an object detector by having an agent select what data to obtain labels for. How should an exploration policy decide which trajectory should be labeled? One possibility is to use a trained object detector’s failure cases as an external reward. However, this will require labeling millions of frames required for training RL policies, which is infeasible. Instead, we explore a self-supervised approach for training our exploration policy by introducing a notion of semantic curiosity. Our semantic curiosity policy is based on a simple observation – the detection outputs should be consistent. Therefore, our semantic curiosity rewards trajectories with inconsistent labeling behavior and encourages the exploration policy to explore such areas. The exploration policy trained via semantic curiosity generalizes to novel scenes and helps train an object detector that outperforms baselines trained with other possible alternatives such as random exploration, prediction-error curiosity, and coverage-maximizing exploration.
Polar Codes’ Simplicity, Random Codes’ Durability

Over any discrete memoryless channel, we offer error correction codes such that: for one, their block error probabilities and code rates scale like random codes’; and for two, their encoding and decoding complexities scale like polar codes’. Quantitatively, for any constants $\pi,\rho >0$ such that $\pi +2\rho , we construct a sequence of block codes with block length ${N}$ approaching infinity, block error probability $\exp (-{N}^\pi)$ , code rate ${N}^{-\rho }$ less than the Shannon capacity, and encoding and decoding complexity ${O}({N}\log {N})$ per code block. The core theme is to incorporate polar coding (which limits the complexity to polar’s realm) with large, random, dynamic kernels (which boosts the performance to random’s realm). The putative codes are optimal in the following manner: Should $\pi +2\rho >1$ , no such codes exist over generic channels regardless of complexity.
Optimal Materials for Maximum Near-field Radiative Heat Transfer

We identify optimal material properties for near-field radiative heat transfer. We find that no typically proposed materials satisfy all criteria, but that certain bulk and 2D plasmonic materials offer 5-10X improvements beyond the state-of-the-art.
Classification of Noncoding RNA Elements Using Deep Convolutional Neural Networks

The paper proposes to employ deep convolutional neural networks (CNNs) to classify noncoding RNA (ncRNA) sequences. To this end, we first propose an efficient approach to convert the RNA sequences into images characterizing their base-pairing probability. As a result, classifying RNA sequences is converted to an image classification problem that can be efficiently solved by available CNN-based classification models. The paper also considers the folding potential of the ncRNAs in addition to their primary sequence. Based on the proposed approach, a benchmark image classification dataset is generated from the RFAM database of ncRNA sequences. In addition, three classical CNN models have been implemented and compared to demonstrate the superior performance and efficiency of the proposed approach. Extensive experimental results show the great potential of using deep learning approaches for RNA classification.
SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media.

In this paper, we present the main findings and compare the results of SemEval-2020 Task 10, Emphasis Selection for Written Text in Visual Media. The goal of this shared task is to design automatic methods for emphasis selection, i.e. choosing candidates for emphasis in textual content to enable automated design assistance in authoring. The main focus is on short text instances for social media, with a variety of examples, from social media posts to inspirational quotes. Participants were asked to model emphasis using plain text with no additional context from the user or other design considerations. SemEval-2020 Emphasis Selection shared task attracted 197 participants in the early phase and a total of 31 teams made submissions to this task. The highest-ranked submission achieved 0.823 Matchm score. The analysis of systems submitted to the task indicates that BERT and RoBERTa were the most common choice of pre-trained models used, and part of speech tag (POS) was the most useful feature. Full results can be found on the task’s website.
Molecular dynamics simulations of enantiomeric separations as an interfacial process in HPLC

Since chromatographic separation is a dynamic process, with the interactions between the drug and the chiral stationary phase mediated by the solvent, no single interacting structure, such as could be found by minimizing the energy, could possibly describe and account for the ratio of residence times in the chromatographic column for the enantiomeric pair. We describe the use of explicit-solvent fully atomistic molecular dynamics simulations, permitting all the interactions between the atoms constituting the chiral stationary phase, solvent molecules and the drug molecule. This allows us to better understand the molecular dynamic chiral recognition that provides the discrimination which results in the separation of enantiomers by high performance liquid chromatography. It also provides a means of predicting, for a given set of conditions, which enantiomer elutes first and an estimate of the expected separation factor. In this review we consider the use of molecular dynamics towards this understanding and prediction.
Optimal Vertex Fault-Tolerant Spanners in Polynomial Time

Recent work has pinned down the existentially optimal size bounds for vertex fault-tolerant spanners: for any positive integer $k$, every $n$-node graph has a $(2k-1)$-spanner on $O(f^{1-1/k} n^{1+1/k})$ edges resilient to $f$ vertex faults, and there are examples of input graphs on which this bound cannot be improved. However, these proofs work by analyzing the output spanner of a certain exponential-time greedy algorithm. In this work, we give the first algorithm that produces vertex fault tolerant spanners of optimal size and which runs in polynomial time. Specifically, we give a randomized algorithm which takes $\widetilde{O}\left( f^{1-1/k} n^{2+1/k} + mf^2\right)$ time. We also derandomize our algorithm to give a deterministic algorithm with similar bounds. This reflects an exponential improvement in runtime over [Bodwin-Patel PODC '19], the only previously known algorithm for constructing optimal vertex fault-tolerant spanners.
Automatic Open-World Reliability Assessment

Image classification in the open-world must handle out-of-distribution (OOD) images. Systems should ideally reject OOD images, or they will map atop of known classes and reduce reliability. Using open-set classifiers that can reject OOD inputs can help. However, optimal accuracy of open-set classifiers depend on the frequency of OOD data. Thus, for either standard or open-set classifiers, it is important to be able to determine when the world changes and increasing OOD inputs will result in reduced system reliability. However, during operations, we cannot directly assess accuracy as there are no labels. Thus, the reliability assessment of these classifiers must be done by human operators, made more complex because networks are not 100% accurate, so some failures are to be expected. To automate this process, herein, we formalize the open-world recognition reliability problem and propose multiple automatic reliability assessment policies to address this new problem using only the distribution of reported scores/probability data. The distributional algorithms can be applied to both classic classifiers with SoftMax as well as the open-world Extreme Value Machine (EVM) to provide automated reliability assessment. We show that all of the new algorithms significantly outperform detection using the mean of SoftMax.
Implementation and evaluation of a novel subspecialty society fellows robotic surgical course: the SGO minimally invasive academy surgical curriculum

Objective To evaluate the utility of a society-based robotic surgery training program for fellows in gynecologic oncology. Methods All participants underwent a 2-day robotic surgery training course between 2015-2017. The course included interactive didactic sessions with video, dry labs, and robotic cadaver labs. The labs encompassed a wide range of subject matter including troubleshooting, instrument variation, radical hysterectomies, and lymph node dissections. Participants completed a pre- and post-course survey using a 5-point Likert scale ranging from "not confident" to "extremely confident" on various measures. Statistical analysis was performed using SPSS Statistics v. 24. Results The response rate was high with 86% of the 70 participants completing the survey. Sixteen (26.7%) of these individuals were attending physicians and 44 (73.3%) were fellows. In general, there was a significant increase in confidence in more complex procedures and concepts such as radical hysterectomy (p=0.01), lymph node dissection (p=0.01), troubleshooting (p=0.001), and managing complications (p=0.004). Faculty comfort and practice patterns were cited as the primary reason (58.9%) for limitations during robotic procedures followed secondarily by surgical resources (34.0%). Conclusion In both gynecologic oncology fellows and attendings, this educational theory-based curriculum significantly improved confidence in the majority of procedures and concepts taught, emphasizing the value of hands-on skill labs.
An empirical investigation of methods to reduce transaction costs

Abstract Among 37 methods to reduce transaction costs, we recursively choose the best method for next period's investment in each of three portfolio strategies: levered-momentum, zero-cost momentum, and the equally-weighted market. We identify a few of the best methods and offer a framework by which additional methods can be considered. Within our framework, the best methods recapture a substantial amount of wealth and significantly improve risk-adjusted performance, both economically and statistically. Security migration can present a barrier to transaction cost reduction, as improvements occur for zero-cost momentum portfolios invested in all stocks but not for decile-momentum portfolios.
BECOMING SUPREME: THE FEDERAL FOUNDATION OF JUDICIAL SUPREMACY

One of the longstanding questions that bedevils scholars in several disciplines is how judicial power gains traction. What, in particular, explains judicial supremacy? Theories abound, but each is lacking in some way. By looking at the answer to this question in the context of the Supreme Court of the United States, we demonstrate the vital role a federal system can play in both the rise and maintenance of judicial supremacy. In a unitary (nonfederal) system, a judiciary possessing the power of judicial review may well find itself frequently at odds with - and rarely helpful to - the governing regime. In contrast, in a federal system, the judiciary can provide vital support to the central government in suppressing outlier conduct. This “vertical” supremacy - the supremacy of the Supreme Court over state and local governments - ultimately transforms itself into “horizontal” supremacy - the binding effect of judicial pronouncements over the coordinate branches of the national government. This project is theoretical and historical both: it identifies the mechanisms for the transformation from vertical to horizontal supremacy, and recounts how this occurred in the United States.
Has the affordable care act affected health care efficiency

We utilize health care input and output data to evaluate how state-level efficiency in health care has changed in the wake of the Affordable Care Act (ACA). We use a Stochastic Frontier model to estimate annual measures of technical and cost efficiency before, and after, ACA implementation. Results show that following the ACA, states’ technical efficiency scores improved and converged across states. However, cost efficiency scores declined suggesting health outputs rose by a proportionally smaller margin than health care costs. We further investigate efficiency changes for ACA-induced Medicaid expansions. We find Medicaid expansion led to decreased cost efficiency scores, but may have led to increased technical efficiency scores. Overall, results suggest the ACA represents a package of reforms that present a trade-off between technical and cost efficiency.
“Export Experience” under Borrowing Constraints

We develop a two-period, two-country, multi-good model with endogenous investment. Borrowing is subject to quantitative restrictions. We examine the eect of promoting exports in period 1 on the level of exports in period 2. We consider a number of scenarios depending on how the initial values of the policy instruments are determined and compare the ‘export-experience’ eects under the dierent scenarios.
Learning a board Balanced Scorecard to improve corporate performance

The objective of this paper is to demonstrate how the boosting approach can be used to define a data-driven board Balanced Scorecard (BSC) with applications to S&P 500 companies. Using Adaboost, we can generate alternating decision trees (ADTs) that explain the relationship between corporate governance variables, and firm performance. We also propose an algorithm to build a representative ADT based on cross-validation experiments. The representative ADT selects the most important indicators for the board BSC. As a final result, we propose a partially automated strategic planning system combining Adaboost with the board BSC for board-level or investment decisions.
Power, composition, and decision making: the behavioral consequences of institutional reform on brazil’s supremo tribunal federal

How does a court’s policy-making authority shape the nature of judicial behavior? We argue that judicial systems that limit policy-making authority also discourage the politicization of courts, encouraging judges to think narrowly about the interests of litigating parties. In contrast, granting a court high policy-making authority—affecting potentially thousands of cases and other branches of government—naturally encourages judges to consider broader ideological principles. Typically, unraveling cause and effect would be difficult, as judicial behavior and institutions are usually stable and endogenous. But an especially stark sequence of political and institutional changes in Brazil affords analytic leverage to explore these questions. A series of judicial reforms greatly expanded the Brazilian Supreme Court’s authority, and our analysis of judicial decisions shows the emergence of a political cleavage on the court after these reforms.
The cycle of violence and pathways to peace

AbstractThis article analyzes inter-group conflict through the lens of Terror Management Theory and explains how belief systems can breed animosity and hostility towards those who do not share one's beliefs. Research provides support converging with historical analyses suggesting that many of the same psychological mechanisms that lead terrorists to take aggressive actions may also motivate extreme counter-terrorist policies creating massive amounts of collateral damage. This collateral damage from violent counter-terrorist measures often intensifies the cycle of violence by assisting terrorists in recruiting support. Finally, recent research that provides hope for breaking the cycle of violence is presented.
Mortality decline, human capital investment, and economic growth

Abstract We examine the role of increased life expectancy in raising human capital investment during the process of economic growth. We develop a continuous time, overlapping generations model in which individuals make optimal schooling investment choices in the face of a constant probability of death. We present analytic results, followed by results from a calibrated version of the model using realistic estimates of the return to schooling. Mortality decline produces economically significant increases in schooling and consumption. Allowing schooling to vary endogenously produces a much larger response of consumption and capital to mortality decline than is observed when schooling is held fixed.
On the Accuracy of Different Measures of q

Tobin's q is widely accepted as a proxy for an underlying “true” q, which is assumed to characterize a firm's incentive to invest. Researchers have developed numerous methods for computing q. This article assesses the measurement quality of different proxies for q. We adapt the measurement-error consistent estimators in Erickson and Whited (2002) to estimate the extent to which variation in true unobservable q explains variation in different proxies for q. We find most proxies for q are poor: careful algorithms for calculating q do little to improve measurement quality. Using elaborate algorithms, however, depletes the number of usable observations and possibly introduces sample selection bias.
The Role of Corporate Social Responsibility in Strengthening Multiple Stakeholder Relationships: A Field Experiment:

This research relied on a field experiment involving a real-world instance of corporate philanthropy to shed light on both the scope and limitations of the strategic returns to corporate social responsibility (CSR). In particular, the authors demonstrate that the impact of CSR in the real world is not only less pervasive than has been previously acknowledged but also more multifaceted than has been previously conceptualized. The findings indicated that contingent on CSR awareness, which was rather low, stakeholders did react positively to the focal company not only in the consumption domain but in the employment and investment domains as well. Stakeholder attributions regarding the genuineness of the company’s motives moderated these effects.
The Internet and Copyright Protection: Are We Producing a Global Generation of Copyright Criminals

The advent of the Internet poses fundamental changes in social norms, politics and economics in society. The belief in cyber anarchy; "do not touch the Internet" mantra, has fundamentally altered the understanding of copyright laws amongst the present generation. Subsequently an aversion for property rights, as understood by well established copyright laws has, developed manifesting itself mainly through piracy. The evolution of technology in tandem with the Internet has further exacerbated the situation as a whole, generations that enjoy entertainment find it much easier to infringe on a litany of copyright laws. Taking into account the established norms of property or copyright protection, is it not clear, with growing copyright malcontents and malfeasance, that we are simply producing a global generation of copyright criminals. This discourse explores the veracity of this statement by taking into account the nature of the Internet, the emergence of digital copying and sharing, alongside the fluid perceptions of copyright
Were Compulsory Attendance and Child Labor Laws Effective? An Analysis from 1915 to 1939*

Abstract Were compulsory attendance and child labor laws responsible for the incredible growth in secondary schooling from 1915 to 1939? Using 1960 census data, I find that legally requiring children to attend school for 1 more year, by increasing the age required for a work permit or lowering the entrance age, increased educational attainment by about 5 percent. The effect was similar for white males and females, but there was no effect for blacks. Continuation school laws that required working children to attend school on a part‐time basis were effective for white males only. These laws increased the education only of those in the lower percentiles of the education distribution, thereby decreasing education inequality, perhaps by as much as 15 percent. States with higher levels of wealth, higher percentage of immigrants, or lower percentage of blacks were more likely to pass stringent laws. The results also suggest that these laws were not endogenous.
Portfolio Pumping, Trading Activity and Fund Performance

We develop a model of trading by an informed fund manager compensated on the basis of her fund's Net Asset Value (NAV). We show that she has an incentive to pump her portfolio by buying securities she already holds. Pumping leads to excessive trading and hurts long-term fund performance. It also biases upward measured NAVs and contributes to closed-end fund discounts. Despite such costs, it may still be optimal to base her compensation on NAV. Copyright 2013, Oxford University Press.
The Impact of Decimalization on Market Quality: An Empirical Investigation of the Toronto Stock Exchange

Abstract I address the “decimalization” debate, i.e., whether trading on cent ticks rather than fractions of a dollar reduces trading costs without diminishing liquidity. I use Toronto Stock Exchange data following their switch to decimal trading on April 15, 1996. For stocks whose minimum tick was reduced from one-eighth of a dollar to five cents, decimalization reduced spreads, while liquidity was not adversely affected. Investors' trading costs and liquidity providers' profits declined on average, but trading volume did not increase. For stocks whose minimum tick size declined from 5 cents to 1 cent, decimalization had little impact on market quality. Journal of Economic Literature Classification Numbers: G12, G15
Monetary Policy Regime Shifts and the Unusual Behavior of Real Interest Rates

A striking phenomenon of the early 1980s is the climb in real interest rates to levels unprecedented in the post-World War II period. In order to understand this phenomenon, this paper investigates the nature and timing of shifts in the real rate process to determine if the recent unusual behavior of real rates is associated with monetary policy regime changes. We find that not only are there significant shifts in the stochastic process of real interest rates in October 1979 and October 1982 when the Federal Reserve alters its behavior, but these dates are also found to be the most likely breakpoints in the real rate process. When we analyze another monetary policy regime change with many similarities to that of October 1979, the sharp rises in the discount rate in 1920, we also reach a similar conclusion; there is a striking correspondence between the monetary policy regime change and the shift in the real rate process. Other studies have examined competing explanations for the recent unusual behavior of real interest rates -- e.g.budget deficits or favorable changes in business taxation. Although these competing explanations have met with mixed success, our evidence lends substantial support to the view that monetary policy regime changes have been and continue to be an important source of shifts in the behavior of real interest rates.(This abstract was borrowed from another version of this item.)
Electoral Institutions and the National Provision of Local Public Goods

I explore the incentives under alternative electoral institutions for national politicians to efficiently provide local public goods. Using a career-concerns model which incorporates voter ideological heterogeneity and thus allows comparison of electoral-college and majoritarian elections at the national level, I show that the aggregation of votes across localities in both electoral-college and majoritarian elections results in a weakening of incentives to efficiently provide local public goods. However, this effect is not unambiguously larger for one electoral institution or the other. Rather, electoral institutions interact with voter preferences to determine incentives. Electoral-college elections provide particularly weak incentives for national politicians to efficiently provide local public goods when there is local ideological bias for the incumbent or challenger, while such bias tends to cancel out in majoritarian elections. Further, electoral-college and majoritarian elections encourage different allocations of effort by national politicians when voters differ across localities in the degree to which they value public-goods provision. When such differences are sharp, electoral-college elections result in better public-goods provision for localities whose voters value public goods less, and majoritarian elections result in better provision for localities whose voters value public goods more.
Citizens' perceptions of police misconduct: Race and neighborhood context

One of the most controversial issues in policing concerns allegations of police abuse of members of minority groups. This article examines African Americans' and whites' perceptions and experiences of three types of police misconduct: unjustified street stops of citizens, verbal abuse, and use of excessive force. The study is based on in-depth interviews with residents of three neighborhoods in Washington, DC, which vary in racial and class profile. Findings support the thesis that neighborhood context conditions residents' attitudes and reported experiences with the police. Residents of both the white and the black middle-class neighborhoods were less likely to perceive or experience police abuse in their neighborhoods than were residents of the black lower-class neighborhood. Neighborhood class position thus may be an important, but often overlooked, factor shaping citizens' attitudes and experiences. In encounters with the police outside the neighborhood, however, individuals' race becomes salient. Imp...
Without Limitation: "Groundhog Day" for Incompetent Defendants

This Article offers a brief overview of the standards for determining competency to stand trial. After examining the seminal case of Jackson v. Indiana, which held that the indefinite pre-trial detention of incompetent defendants violates due process, this Article argues that Virginia Code § 19.2-169.3, like statutes in twenty other states, violates a defendant's right to substantive due process, including the right to be free from forcible medication. This Article proposes legislation that will make the process constitutional, while addressing the concerns about the release of dangerous individuals held by the prosecutors and the community.
The Rights of Gay Prisoners: A Challenge to Protective Custody

This Note focuses on the specific issues raised by the traditional method of dealing with homosexuals in prison: isolation from the general prison population. This traditional segregation often results in almost twenty-four hour-a-day confinement to a cell, which severely limits access to programs and opportunities normally enjoyed by prisoners.This Note first discusses the history and current practice of segregation of gay prisoners' as well as the broader subject of protective custody, and then outlines the judicial response to the problems of protective custody prisoners generally and gay prisoners specifically. It then critiques the judicial confusion and resulting reluctance to scrutinize these segregation policies. Specifically, the Note argues that constitutional due process requires the implementation of procedural safeguards prior to any non-voluntary assignment into protective custody." It also challenges the constitutionality of the segregation, protective or otherwise, of any prisoner solely on the basis of his or her status as a homosexual.' Finally, this Note argues that the due process clause, the eighth amendment, and the equal protection clause of the Constitution require major changes in the treatment of all protective custody prisoners, and of gay prisoners in particular.
Decentralized Policy Implementation

This article develops a regime-splitting process model of decentralized policy implementation to integrate two theoretical approaches rooted in the tension between local flexibility and national control. The author estimates a model that simultaneously assesses the ability of each approach to explain the outcome it is meant to map onto (case-level discretion for local flexibility and aggregate responsiveness for national control) as well as each approach's extensibility to the other approach's domain. The data for the study come from the implementation of eight primary statutes by the U.S. Environmental Protection Agency's regional offices. The results are counterintuitive: the national control approach largely explains case-level discretion, the domain of local flexibility, but retains some power for explaining aggregate responsiveness. The local flexibility perspective contributes to both case-level discretion and aggregate responsiveness. Both models work outside their traditional domains, but neither ...