cssi/SciSciGPT-SciSciNet huggingface dataset:
Public Versus Private Provision of Pensions

The World Bank recommends that pension systems rest on three pillars: (1) redistribution, (2) forced savings, and (3) voluntary savings. There is wide agreement that the first pillar should be provided through the State and the third largely through private markets. In contrast, provision of the the second pillar is controversial. The explains that private, individual accounts are attractive primarily because they insure that all savers receive potentially equal returns. But existing public systems can be reformed to achieve a similar equitable treatment of contributors while retaining low administrative costs and providing social insurance that is either expensive or unavailable in private markets.
Hostile Work Environment and the Objective Reasonableness Conundrum: Deriving a Workable Framework from Tort Law for Addressing Knowing Harassment of Hypersensitive Employees

Part I sets forth the current structure applied to hostile work environment claims, including employer liability for such claims. Part I also addresses the differences in the hostile work environment cause of action as applied to the various classes protected under federal anti-discrimination laws.Part II discusses the treatment of hypersensitive employees under current hostile work environment analysis. Part II then sets forth a model based on the tort of intentional infliction of emotional distress, which demonstrates when and under what circumstances such individuals can be protected without imposing an undue burden on employers.Part III addresses what damages should be available to a hypersensitive employee who is harassed based on a known hypersensitivity because of his or her membership in a protected class. It also addresses whether damages should be available for injury resulting from the exacerbation of a hypersensitivity caused by an objectively hostile work environment when the harasser had no knowledge of the sensitivity. Part III discusses the applicability of the "eggshell skull" rule to such situations.
Debt vs. Equity and Asymmetric Information: A Review

Recent Nobel Prizes to Akerlof, Spence, and Stiglitz motivate this review of basic concepts and empirical evidence on information asymmetry and the choice of debt vs. equity. We first review the literature that holds investment fixed. Then we review capital structure issues related to the adverse investment selection problem of Myers-Majluf. Finally, we discuss the timing hypothesis of capital structure. Empirical studies do not consistently support one theory of capital structure under information asymmetry over the others. Thus, the review suggests that additional theoretical contributions are needed to help understand and explain findings in the empirical literature.
Measuring risk aversion from excess returns on a stock index

Abstract Measuring risk aversion from excess returns on a stock index presents two obstacles: 1. the time path of the stock-index variance needs to be modeled and estimated, and 2. other components of wealth must be accounted for. We distinguish two measures that relate the risk premium to variance: 1. the measure of risk aversion which, by the single-factor CAPM, would be the slope coefficient in the linear relation between the mean excess return and the variance of the overall risky portfolio of the representative investor, and 2. the slope coefficient in the linear relationship between the mean excess return on a stock index and its variance. Even when risk aversion is constant, the latter can vary significantly with the relative share of stocks in the risky wealth portfolio, and with the beta of unobserved wealth on stocks. We introduce a statistical model with ARCH disturbances and a time-varying parameter in the mean (TVP ARCH-M). The model decomposes the predictable component in stock returns into two parts: the time-varying price of volatility and the time-varying volatility of returns. The relative share of stocks and the beta of the excluded components of wealth on stocks are instrumented by macroeconomic variables. The ratio of corporate profit over national income and the inflation rate are found to be important forces in the dynamics of stock price volatility.
The new-Keynesian liquidity trap

Abstract Many new-Keynesian models produce a deep recession with deflation at the zero bound. These models also make unusual policy predictions: Useless government spending, technical regress, capital destruction, and forward guidance can raise output. Moreover, these predictions are larger as prices become less sticky and as changes are expected further in the future. I show that these predictions are strongly affected by equilibrium selection. For the same interest-rate path, equilibria that bound initial jumps predict mild inflation, small output variation, negative multipliers, small effects of far-off expectations and a smooth frictionless limit. Fiscal policy considerations suggest the latter equilibria.
Economic Protectionism and the Philosophy of Frederic Bastiat

Frederic Bastiat (1801-1850) was a French economist and journalist. One of his classic works, The Candlemakers’ Petition, uses the reductio ad absurdum philosophical technique to dismantle the arguments the French protectionists put forth to protect French industry in the mid-nineteenth century. His Petition has been reprinted in numerous college economics texts and it has been cited in the scholarly economics literature. But Bastiat’s writings on protectionism include much more than his Candlemakers’ Petition. This paper discusses The Candlemakers’ Petition as a starting point, then explores his other, lesser known writings on protectionism and applies his theories to current conditions.
Children's health insurance, family income, and welfare enrollment

Abstract Children from wealthier families are more likely to have health insurance than children from poorer families on average. However, the relationship between family income and health insurance is non-linear, as children near the Federal Poverty Line (FPL) are less likely to be insured than children from both wealthier families (who obtain health insurance from the private market) and poorer families (who obtain government-funded health insurance). This health insurance dip has persisted even as Medicaid has been expanded to cover those above the FPL. One explanation for this is that families who are far below the poverty line are better connected to the welfare system, and consequently, are more likely to enroll in Medicaid. This study uses data from the 2001–2013 Current Population Surveys and finds that (1) controlling for many of the determinants of eligibility, those on other forms of government assistance are more likely to have health insurance, and (2) the relationship between family income and children's health insurance status is strictly increasing after controlling for enrollment in other welfare programs.
AFFORDABLE HOUSING IN SUBURBIA: THE IMPORTANCE BUT LIMITED POWER AND EFFECTIVENESS OF THE STATE OVERRIDE TOOL

This article provides the introduction to a December, 1999 symposium on “Increasing Affordable Housing and Mobility in Three New England States and New Jersey: Comparative Perspectives on the Occasion of the Thirtieth Anniversary of the Massachusetts Comprehensive Permit Law.” It describes the origins and summarizes the essential features of zoning override laws in four states: Connecticut, Massachusetts, New Jersey and Rhode Island. It discusses their track record in meeting their various goals – producing affordable housing; increasing mobility and housing choice; and integrating the suburbs. It gives the statutes “two cheers” and then offers suggestions for their improvement.
A Constitutional Right To Discovery? Creating and Reinforcing Due Process Norms Through the Procedural Laboratory of Arbitration

Are discovery procedures in the civil context — which have become the norm in modern litigation — constitutionally required? Would Congress or states, for example, violate the due process clause by banning or severely restricting the broad use of discovery in civil cases? If no constitutional right to discovery exists in criminal cases, which can involve severe deprivations of life and liberty, then surely it should follow that no constitutional right to discovery exists in civil cases. However, the underpinnings for a due process-like norm involving a right to discovery in the civil context have begun to take root. Where can one observe such a right beginning to emerge? In the laboratory or petri dish of procedural experimentation: arbitration.This article explores an overlooked dynamic between arbitration and the more formal court system. This article’s thesis is that arbitration can help define and reinforce due process norms applicable in court, and a due process-like norm regarding discovery is beginning to develop. Courts often review arbitration agreements for fairness, and through this judicial review, courts have developed a body of law discussing and defining whether certain procedures (or the lack thereof) violate fairness norms in connection with the resolution of a particular dispute. Through this body of law exploring procedural fairness, one can identify emerging procedural norms, such as a right to discovery in certain situations. Through the procedural creativity and experimentation that occurs in arbitration, and through the judicial review of such arbitral procedures, arbitration creates countless opportunities to explore and define what constitutes the minimum bundle of procedures required for a fair hearing.
Does Takeover Activity Cause Managerial Discipline? Evidence from International M&A Laws

This paper exploits the staggered initiation of takeover laws across countries to examine whether the threat of takeover enhances managerial discipline. We show that following the passage of takeover laws, poorly performing firms experience more frequent takeovers; the propensity to replace poorly performing CEOs increases, especially in countries with weak investor protection; and directors of targeted firms are more likely to lose board seats following corporate-control events. Our findings suggest that the threat of takeover causes managerial discipline through the incentives that the market for corporate control provides to boards to monitor managers.
Humblebragging:: A distinct—and ineffective—self-presentation strategy.

Self-presentation is a fundamental aspect of social life, with myriad critical outcomes dependent on others' impressions. We identify and offer the first empirical investigation of a prevalent, yet understudied, self-presentation strategy: humblebragging. Across 9 studies, including a week-long diary study and a field experiment, we identify humblebragging-bragging masked by a complaint or humility-as a common, conceptually distinct, and ineffective form of self-presentation. We first document the ubiquity of humblebragging across several domains, from everyday life to social media. We then show that both forms of humblebragging-complaint-based or humility-based-are less effective than straightforward bragging, as they reduce liking, perceived competence, compliance with requests, and financial generosity. Despite being more common, complaint-based humblebrags are less effective than humility-based humblebrags, and are even less effective than simply complaining. We show that people choose to deploy humblebrags particularly when motivated to both elicit sympathy and impress others. Despite the belief that combining bragging with complaining or humility confers the benefits of each strategy, we find that humblebragging confers the benefits of neither, instead backfiring because it is seen as insincere. (PsycINFO Database Record
Price Causality between Adjacent Housing Markets within a Metropolitan Area: A Case Study

Executive Summary. Using quarterly housing price data, this study investigates the price relationships and the price causality between three adjacent housing markets in the Hampton Roads region in ...
No Entry to the Public Lands: Towards A Theory of A Public Trust Servitude for A Way over Abutting Private Land

When Congress established Yellowstone National Park in 1872, the policy animating national land use underwent a dramatic shift. The Yellowstone Act directed the Secretary of the Interior to adopt rules and regulations to “provide for the preservation, from injury or spoliation, of all timber, mineral deposits, natural curiosities, or wonders within said park, and their retention in their natural condition.” Protection and preservation thus became the guiding principles. This was not, however, the government’s original conception of the public lands. In fact, during the first hundred years of our nation, the policy had been one of disposal. And, if there is any truth to the quote above, then the United States government is all powerful, inasmuch as it owns more than a third of all land in the country. Most of the government-owned lands are classified as “public
Structural GARCH: The Volatility-Leverage Connection

We propose a new model of volatility where financial leverage amplifies equity volatility by what we call the “leverage multiplier”. The exact specification is motivated by standard structural models of credit; however, our parametrization departs from the classic Merton (1974) model and is, as we show, flexible and accurate enough to capture environments where the firm’s asset volatility is stochastic, asset returns can jump, and asset shocks are non-normal. As a result, our model also provides estimates of daily asset returns and asset volatility. In addition, our specification nests both a standard GARCH and the Merton model, which allows for a simple statistical test of how leverage interacts with equity volatility. Empirically, the Structural GARCH model outperforms a standard GARCH model for approximately 75% of the financial firms we analyze. We then apply the Structural GARCH model to two empirical applications: the leverage effect and systemic risk measurement.
Three Proposals for Regulating the Distribution of Home Equity

As an additional demonstration of the contribution of low-equity clustering, we conducted an empirical study that examined home equity levels of over 20,000 homeowners across eleven states from 1999q1–2011q1. Our results found that higher levels of low-equity clustering correlate with increased mortgage delinquency even after controlling for macroeconomic shocks. While imperfections in the data preclude establishing strong causal explanations, the results nonetheless serve as a heuristic evidence of the need to attend to the problem of low-equity clustering.
Louisiana's conflicts codification: Some empirical observations regarding decisional predictability

In 1992, Louisiana became the first (and still the only) state to codify its choice-of-law doctrine. The conflicts rules that it created in statutory form are far removed from the pre-conflicts-revolution rules such as the lex loci delicti rule in tort cases. Rather, the Louisiana codification consists of somewhat softer and narrower rules. This article attempts to measure whether this codification has produced any improvement in decisional predictability in Louisiana courts. As a proxy for decisional predictability it uses the affirmance rates of Louisiana courts in conflicts case before and after the codification. The article concludes that the Louisiana codification produced a statistically significant increase in the affirmance rate and thus by inference in the decisional predictablity of Louisiana conflicts decisions.
Numerical Analysis in Least Squares Regression with an Application to the Abortion-Crime Debate

Concepts of numerical analysis with applications to least squares problems are introduced in a manner the practitioner can readily apply to his or her own research problems, especially in the social sciences. Numerical analysis is mainly concerned with the accuracy and stability of numerical algorithms. We frame these concerns in terms of forward and backward error, two important concepts in helping understand the quality of the computed answers. The goal of numerical computing is to obtain correct, approximate answers to the true solution. We extended this forward and backward error framework to issues in least squares problems and check the condition of the regression problem via condition numbers. The more ill-conditioned the data are, the more sensitive the computed solution is to perturbations in the data, and the more unstable the computed solutions become. Condition numbers can also be used to signal the presence of solution degrading collinearity in regression problems. We apply the various numerical analysis tools outlined with some model diagnostics to the abortion-crime debate, and show the regression analysis used in various papers addressing the abortion-crime debate cannot be trusted.
A Framework for Conceptual Contributions in Marketing

Abstract Conceptual advances are critical to the vitality of the marketing discipline, yet recent writings suggest that conceptual advancement in the field is slowing. The author addresses this issue by developing a framework for thinking about conceptualization in marketing. A definition of conceptualization is followed by a typology of types of conceptual contributions. The types of conceptual contributions, their similarities and differences, and their importance to the field are described. Thinking skills linked to various types of conceptual contributions are also described, as are the use of tools that can facilitate these skills. The article concludes with a set of recommendations for advancing conceptualization in our field in the years to come.
Trading Locality for Time: Certifiable Randomness from Low-Depth Circuits.

The generation of certifiable randomness is the most fundamental information-theoretic task that meaningfully separates quantum devices from their classical counterparts. We propose a protocol for exponential certified randomness expansion using a single quantum device. The protocol calls for the device to implement a simple quantum circuit of constant depth on a 2D lattice of qubits. The output of the circuit can be verified classically in linear time, and is guaranteed to contain a polynomial number of certified random bits assuming that the device used to generate the output operated using a (classical or quantum) circuit of sub-logarithmic depth. This assumption contrasts with the locality assumption used for randomness certification based on Bell inequality violation and more recent proposals for randomness certification based on computational assumptions. Furthermore, to demonstrate randomness generation it is sufficient for a device to sample from the ideal output distribution within constant statistical distance. Our procedure is inspired by recent work of Bravyi et al. (Science 362(6412):308–311, 2018), who introduced a relational problem that can be solved by a constant-depth quantum circuit, but provably cannot be solved by any classical circuit of sub-logarithmic depth. We develop the discovery of Bravyi et al. into a framework for robust randomness expansion. Our results lead to a new proposal for a demonstrated quantum advantage that has some advantages compared to existing proposals. First, our proposal does not rest on any complexity-theoretic conjectures, but relies on the physical assumption that the adversarial device being tested implements a circuit of sub-logarithmic depth. Second, success on our task can be easily verified in classical linear time. Finally, our task is more noise-tolerant than most other existing proposals that can only tolerate multiplicative error, or require additional conjectures from complexity theory; in contrast, we are able to allow a small constant additive error in total variation distance between the sampled and ideal distributions.
Hitting times for Shamir’s problem

For fixed $r\geq 3$ and $n$ divisible by $r$, let ${\mathcal H}={\mathcal H}^r_{n,M}$ be the random $M$-edge $r$-graph on $V=\{1,\ldots ,n\}$; that is, ${\mathcal H}$ is chosen uniformly from the $M$-subsets of ${\mathcal K}:={V \choose r}$ ($:= \{\mbox{$r$-subsets of $V$}\}$). Shamir's Problem (circa 1980) asks, roughly, for what $M=M(n)$ is ${\mathcal H}$ likely to contain a perfect matching (that is, $n/r$ disjoint $r$-sets)? In 2008 Johansson, Vu and the author showed that this is true for $M>C_rn\log n$. More recently the author proved the asymptotically correct version of that result: for fixed $C> 1/r$ and $M> Cn\log n$, $P({\mathcal H} ~\mbox{contains a perfect matching})\rightarrow 1 \,\,\, \mbox{as $n\rightarrow\infty$}.$ The present work completes a proof, begun in that recent paper, of the definitive "hitting time" statement: $\mbox{Theorem.}$ If $A_1, \ldots ~$ is a uniform permutation of ${\mathcal K}$, ${\mathcal H}_t=\{A_1\dots A_t\}$, and \[ T=\min\{t:A_1\cup \cdots\cup A_t=V\}, \] then $P({\mathcal H}_T ~\mbox{contains a perfect matching})\rightarrow 1 \,\,\, \mbox{as $n\rightarrow\infty$}$.
Point Location and Active Learning: Learning Halfspaces Almost Optimally

Given a finite set $X\subset \mathbb{R}^{d}$ and a binary linear classifier $c:\mathbb{R}^{d}\rightarrow\{0,1\}$ , how many queries of the form $c(x)$ are required to learn the label of every point in $X$ ? Known as point location, this problem has inspired over 35 years of research in the pursuit of an optimal algorithm. Building on the prior work of Kane, Lovett, and Moran (ICALP 2018), we provide the first nearly optimal solution, a randomized linear decision tree of depth $\tilde{O}(d\log(\vert X\vert))$ , improving on the previous best of $\tilde{O}(\overline{d}^{2}\log(\vert X\vert))$ from Ezra and Sharir (Discrete and Computational Geometry, 2019). As a corollary, we also provide the first nearly optimal algorithm for actively learning halfspaces in the membership query model. En route to these results, building on the work of Carlen, Lieb, and Loss (J. Geometric Analysis 2004), as well as Dvir, Saraf, and Wigderson (STOC 2014), we prove a novel characterization of Barthe's Theorem (Inventiones Mathematicae, 1998) of independent interest. In particular, we show that $X$ may be transformed into approximate isotropic position if and only if there exists no $k$ -dimensional subspace with more than a $k/d$ -fraction of $X$ , and provide a similar characterization for exact isotropic position. The below is an extended abstract. The full work can be found at https://arxiv.org/abs/2004.11380
Noisy Student Training Using Body Language Dataset Improves Facial Expression Recognition

Facial expression recognition from videos in the wild is a challenging task due to the lack of abundant labelled training data. Large DNN (deep neural network) architectures and ensemble methods have resulted in better performance, but soon reach saturation at some point due to data inadequacy. In this paper, we use a self-training method that utilizes a combination of a labelled dataset and an unlabelled dataset (Body Language Dataset - BoLD). Experimental analysis shows that training a noisy student network iteratively helps in achieving significantly better results. Additionally, our model isolates different regions of the face and processes them independently using a multi-level attention mechanism which further boosts the performance. Our results show that the proposed method achieves state-of-the-art performance on benchmark datasets CK+ and AFEW 8.0 when compared to single models.
Fourier transforms of indicator functions, lattice point discrepancy, and the stability of integrals

We prove sharp estimates for Fourier transforms of indicator functions of bounded open sets in $${\mathbb {R}}^n$$ with real analytic boundary, as well as nontrivial lattice point discrepancy results. Both are derived from estimates on Fourier transforms of hypersurface measures. Relations with maximal averages are discussed, connecting two conjectures of Iosevich and Sawyer (Adv Math 132(1):46–119, 1997). We also prove a theorem concerning the stability under function perturbations of the growth rate of a real analytic function near a zero. This result is sharp in an appropriate sense. It implies a corresponding stability result for the local integrablity of negative powers of a real analytic function near a zero.
Active learning in a graduate quantum field theory course

This article describes how the author successfully adapted techniques drawn from the literature on active learning for use in a graduate-level course on quantum field theory. Students completed readings and online questions ahead of each class and spent class time working through problems that required them to practice the decisions and skills typical of a theoretical physicist. The instructor monitored these activities and regularly provided timely feedback to guide their thinking. Instructor-student interactions and student enthusiasm were similar to that encountered in one-on-one discussions with advanced graduate students. Course coverage was not compromised. The teaching techniques described here are well suited to other advanced courses.
Circulating clonally expanded T cells reflect functions of tumor-infiltrating T cells

Understanding the relationship between tumor and peripheral immune environments could allow longitudinal immune monitoring in cancer. Here, we examined whether T cells that share the same TCRαβ and are found in both tumor and blood can be interrogated to gain insight into the ongoing tumor T cell response. Paired transcriptome and TCRαβ repertoire of circulating and tumor-infiltrating T cells were analyzed at the single-cell level from matched tumor and blood from patients with metastatic melanoma. We found that in circulating T cells matching clonally expanded tumor-infiltrating T cells (circulating TILs), gene signatures of effector functions, but not terminal exhaustion, reflect those observed in the tumor. In contrast, features of exhaustion are displayed predominantly by tumor-exclusive T cells. Finally, genes associated with a high degree of blood-tumor TCR sharing were overexpressed in tumor tissue after immunotherapy. These data demonstrate that circulating TILs have unique transcriptional patterns that may have utility for the interrogation of T cell function in cancer immunotherapy.
On modeling hard combinatorial optimization problems as linear programs: Refutations of the "unconditional impossibility" claims

There has been a series of developments in the recent literature (by essentially a same 'circle' of authors) with the absolute/unconditioned (implicit or explicit) claim that there exists no abstraction of an NP-complete combinatorial optimisation problem in which the defining combinatorial configurations [such as 'tours' in the case of the travelling salesman problem (TSP) for example] can be modelled by a polynomial-sized system of linear constraints. The purpose of this paper is to provide general as well as specific refutations for these recent claims.
Origin of mechanical and dielectric losses from two-level systems in amorphous silicon

Amorphous silicon contains tunneling two-level systems, which are the dominant energy loss mechanisms for amorphous solids at low temperatures. These two-level systems affect both mechanical and electromagnetic oscillators and are believed to produce thermal and electromagnetic noise and energy loss. However, it is unclear whether the two-level systems that dominate mechanical and dielectric losses are the same; the former relies on the coupling between phonons and two-level systems, with an elastic field coupling constant $\ensuremath{\gamma}$ while the latter depends on a two-level systems dipole moment ${p}_{0}$, which couples to the electromagnetic field. Mechanical and dielectric loss measurements as well as structural characterization were performed on amorphous silicon thin films grown by electron beam deposition with a range of growth parameters. Samples grown at 425 ${}^{\ensuremath{\circ}}\mathrm{C}$ show a large reduction of mechanical loss (34 times) and a far smaller reduction of dielectric loss (2.3 times) compared to those grown at room temperature. Additionally, mechanical loss shows lower loss for thicker films, while dielectric loss shows lower loss for thinner films. Analysis of these results indicate that mechanical loss correlates with atomic density, while dielectric loss correlates with dangling-bond density, suggesting a different origin for these two energy dissipation processes in amorphous silicon.
Drive dependence of the Hall angle for a sliding Wigner crystal in a magnetic field

We numerically examine the depinning and sliding dynamics of a Wigner crystal in the presence of quenched disorder and a magnetic field. In the disorder-free limit, the Wigner crystal Hall angle is independent of crystal velocity, but when disorder is present, we find that the Hall angle starts near zero at the depinning threshold and increases linearly with increasing drive before reaching a saturation close to the disorder free value at the highest drives. The drive dependence is the result of a side jump effect produced when the charges move over pinning sites. The magnitude of the side jump is reduced at the higher velocities. The drive dependent Hall angle is robust for a wide range of disorder parameters and should be a generic feature of classical charges driven in the presence of quenched disorder and a magnetic field.
The vaginal microbiome in women of reproductive age with healthy weight versus overweight/obesity.

Objective The aim of this study was to evaluate the differences between the vaginal microbiome of reproductive-aged women with overweight and obesity (Ow/Ob) compared with healthy weight (HW). Methods In this case-control study, a cohort of 367 nonpregnant women (18 to 40 years) with Ow/Ob (BMI ≥25 kg/m2 ) was case-matched with 367 women with HW (BMI 18.0 to 24.9 kg/m2 ). The study was a secondary analysis of 16S rRNA vaginal microbiome surveys through the Vaginal Human Microbiome Study (VaHMP). Groups were matched on age, race/ethnicity, income, and nulliparity status. Results Mean age and BMI of Ow/Ob and HW groups were 26.8 versus 26.7 years and 37.0 versus 22.1 kg/m2 , respectively. The overall vaginal microbiome composition differed between groups (PERMANOVA, p = 0.035). Women with Ow/Ob had higher alpha diversity compared with women with HW (Wilcoxon test, Shannon index p = 0.025; inverse Simpson index p = 0.026). Lactobacillus dominance (≥30% proportional abundance) was observed in a greater proportion of women with HW (48.7%) compared with Ow/Ob (40.1%; p = 0.026). Conclusions The vaginal microbiome differs in reproductive-aged women with Ow/Ob compared with women with HW, with increased alpha diversity and decreased predominance of Lactobacillus. Observed differences in the vaginal microbiome may partially explain differences in preterm birth and bacterial vaginosis risk between these populations.
Gaussian Mixture Graphical Lasso with Application to Edge Detection in Brain Networks

Sparse inverse covariance estimation (i.e., edge detection) is an important research problem in recent years, where the goal is to discover the direct connections between a set of nodes in a networked system based upon the observed node activities. Existing works mainly focus on unimodal distributions, where it is usually assumed that the observed activities are generated from a single Gaussian distribution (i.e., one graph). However, this assumption is too strong for many real-world applications. In many real-world applications (e.g., brain networks), the node activities usually exhibit much more complex patterns that are difficult to be captured by one single Gaussian distribution. In this work, we are inspired by Latent Dirichlet Allocation (LDA) [4] and consider modeling the edge detection problem as estimating a mixture of multiple Gaussian distributions, where each corresponds to a separate sub-network. To address this problem, we propose a novel model called Gaussian Mixture Graphical Lasso (MGL). It learns the proportions of signals generated by each mixture component and their parameters iteratively via an EM framework. To obtain more interpretable networks, MGL imposes a special regularization, called Mutual Exclusivity Regularization (MER), to minimize the overlap between different sub-networks. MER also addresses the common issues in read-world data sets, i.e., noisy observations and small sample size. Through the extensive experiments on synthetic and real brain data sets, the results demonstrate that MGL can effectively discover multiple connectivity structures from the observed node activities.
Space-time points: 4D splatting on efficient grids

4D datasets, such as time-varying datasets, usually come on 4D Cartesian Cubic (CC) grids. In this paper, we explore the use of 4D Body Centered Cubic (BCC) grids to provide a more efficient sampling lattice. We use this lattice in conjunction with a point-based renderer that further reduces the data into an RLE-encoded list of relevant points. We achieve compression ranging from 50 to 80% in our experiments. Our 4D visualization approach follows the hyperslice paradigm: the user first specifies a 4D slice to extract a 3D volume, which is then viewed using a regular point-based full volume renderer. The slicing of a 4D BCC volume yields a 3D BCC volume, which theoretically has 70% of the datapoints of an equivalent CC volume. We reach compressions close to this in practice. The visual quality of the rendered BCC volume is virtually identical with that obtained from the equivalent CC volume, at 70-80% of the CC grid rendering time. Finally, we also describe a 3.5D visualization approach that uses motion blur to indicate the transition of objects along the dimension orthogonal to the extracted hyperslice in one still image. Our approach uses interleaved rendering of a motion volume and the current iso-surface volume to acid the motion blurring effect with proper occlusion and depth relationships.
Using Text Mining to Analyze Doctor-Patient Verbal Communication: A Geriatric Depression Case Study

Doctor-patient communication has been one of the main areas of research within the healthcare domain. The impact of doctor-patient communication on patient satisfaction and health outcomes has been acknowledged in the literature. The dynamics of doctor-patient communication in a geriatric setting is unique due to the limited physical and cognitive ability of elderly patients; communicating with them requires more attention, patience, and involvement. Geriatric providers are expected to be trained well to communicate with elderly patients with various levels of mental health conditions. In this study, we explored doctor-patient verbal communication patterns using text mining measures and identified differences between depression and non-depression visits. We analyzed a total of 42 doctor-patient encounters. Doctors in the visit were not aware of patients’ depression status before and during the visit. Findings showed that doctors had more feelings linked to anger, fear, and sadness when they saw depressed patients. On the other hand, non-depressed patients used more anger-related communication compared to depressed patients. In conclusion, this study states that different communication strategies and training materials should be developed to accommodate depressed geriatric patients and geriatric providers.
Improving deconvolution methods in biology through open innovation competitions: an application to the connectivity map.

Motivation Do machine learning methods improve standard deconvolution techniques for gene expression data? This article uses a unique new dataset combined with an open innovation competition to evaluate a wide range of approaches developed by 294 competitors from 20 countries. The competition's objective was to address a deconvolution problem critical to analyzing genetic perturbations from the Connectivity Map. The issue consists of separating gene expression of individual genes from raw measurements obtained from gene pairs. We evaluated the outcomes using ground-truth data (direct measurements for single genes) obtained from the same samples. Results We find that the top-ranked algorithm, based on random forest regression, beat the other methods in accuracy and reproducibility; more traditional gaussian-mixture methods performed well and tended to be faster, and the best deep learning approach yielded outcomes slightly inferior to the above methods. We anticipate researchers in the field will find the dataset and algorithms developed in this study to be a powerful research tool for benchmarking their deconvolution methods and a resource useful for multiple applications. Availability and implementation: The data is freely available at clue.io/data (section Contests) and the software is on GitHub at https://github.com/cmap/gene_deconvolution_challenge. Supplementary information Supplementary data are available at Bioinformatics online.
Leveraging health systems data to characterize a large effect variant conferring risk for liver disease in Puerto Ricans.

Summary The integration of genomic data into health systems offers opportunities to identify genomic factors underlying the continuum of rare and common disease. We applied a population-scale haplotype association approach based on identity-by-descent (IBD) in a large multi-ethnic biobank to a spectrum of disease outcomes derived from electronic health records (EHRs) and uncovered a risk locus for liver disease. We used genome sequencing and in silico approaches to fine-map the signal to a non-coding variant (c.2784−12T>C) in the gene ABCB4. In vitro analysis confirmed the variant disrupted splicing of the ABCB4 pre-mRNA. Four of five homozygotes had evidence of advanced liver disease, and there was a significant association with liver disease among heterozygotes, suggesting the variant is linked to increased risk of liver disease in an allele dose-dependent manner. Population-level screening revealed the variant to be at a carrier rate of 1.95% in Puerto Rican individuals, likely as the result of a Puerto Rican founder effect. This work demonstrates that integrating EHR and genomic data at a population scale can facilitate strategies for understanding the continuum of genomic risk for common diseases, particularly in populations underrepresented in genomic medicine.
Translation covers of some triply periodic Platonic surfaces

We study translation covers of several triply periodic polyhedral surfaces that are intrinsically Platonic. We describe their affine symmetry groups and compute the quadratic asymptotics for counting saddle connections and cylinders, including the count of cylinders weighted by area. The mathematical study of triply periodic surfaces was initiated by Novikov, motivated by the study of electron transport. The surfaces we consider are of particular interest as they admit several different explicit geometric and algebraic descriptions, as described, for example, in the second author's thesis.
The distribution relation and inverse function theorem in arithmetic geometry

Abstract We study arithmetic distribution relations and the inverse function theorem in algebraic and arithmetic geometry, with an emphasis on versions that can be applied uniformly across families of varieties and maps. In particular, we prove two explicit versions of the inverse function theorem, the first via general distribution and separation inequalities that may be of independent interest, the second via a careful implementation of classical Newton iteration.
The platform economy matures: measuring pervasiveness and exploring power

Online platforms are pervasive and powerful in today's economy. We explore the increased centrality of platforms in two ways. First, we measure the extent to which platforms are insinuating themselves into the economy. We accomplish this by analyzing the presence of platforms as intermediating organizations across all US service industries at the six-digit North American Industry Classification System (NAICS) code level. Our results show that 70% of service industries, representing over 5.2 million establishments, are potentially affected by one or more platforms. Second, we undertake a detailed firm-level case study of the mega-platform, Amazon, that demonstrates the ways that the aforementioned macro-level data is expressed by a single platform firm. This case study shows that Amazon’s growth trajectory has resulted in it entering and transforming existing industries and sectors. We conclude by reflecting upon the limitations and implications for future research.
Anticipation of temporally structured events in the brain

Learning about temporal structure is adaptive because it enables the generation of expectations. We examined how the brain uses experience in structured environments to anticipate upcoming events. During fMRI (functional magnetic resonance imaging), individuals watched a 90 s movie clip six times. Using a hidden Markov model applied to searchlights across the whole brain, we identified temporal shifts between activity patterns evoked by the first vs. repeated viewings of the movie clip. In many regions throughout the cortex, neural activity patterns for repeated viewings shifted to precede those of initial viewing by up to 15 s. This anticipation varied hierarchically in a posterior (less anticipation) to anterior (more anticipation) fashion. We also identified specific regions in which the timing of the brain's event boundaries was related to those of human-labeled event boundaries, with the timing of this relationship shifting on repeated viewings. With repeated viewing, the brain's event boundaries came to precede human-annotated boundaries by 1-4 s on average. Together, these results demonstrate a hierarchy of anticipatory signals in the human brain and link them to subjective experiences of events.
Giant terahertz polarization rotation in ultrathin films of aligned carbon nanotubes

For easy manipulation of polarization states of light for applications in communications, imaging, and information processing, an efficient mechanism is desired for rotating light polarization with a minimum interaction length. Here, we report giant polarization rotations for terahertz (THz) electromagnetic waves in ultrathin (∼45nm), high-density films of aligned carbon nanotubes. We observed polarization rotations of up to ∼20∘ and ∼110∘ for transmitted and reflected THz pulses, respectively. The amount of polarization rotation was a sensitive function of the angle between the incident THz polarization and the nanotube alignment direction, exhibiting a “magic” angle at which the total rotation through transmission and reflection becomes exactly 90°. Our model quantitatively explains these giant rotations as a result of extremely anisotropic optical constants, demonstrating that aligned carbon nanotubes promise ultrathin, broadband, and tunable THz polarization devices.
Safety During Transient Response in Direct Current Microgrids Using Control Barrier Functions

We consider the problem of guaranteeing that the transient voltages and currents stay within prescribed bounds in Direct Current (DC) microgrids, when the controller does not have access to accurate system dynamics due to the load being unknown and/or time-varying. To achieve this, we propose an optimization based controller design using control barrier functions. We show that the proposed controller has a decentralized structure and is robust with respect to the uncertainty in the precise values of the system parameters, such as the load.
Proportionality in the philosophy of punishment: From “why punish?” to “how much?”

Recent philosophical writing about punishment has been devoted mainly to the “why punish?” question. While a variety of theories — utilitarian, reciprocity based, and expressive — have been put forward to answer this question, there has been wide agreement among philosophers that the institution of legal punishment should be retained. Proponents of the various theories disagree chiefly why institutionalized punishment is necessary.The philosophical writings have paid comparatively little attention to the criteria for distributing punishments — particularly to the criteria for deciding how much to penalize convicted offenders.
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning

The attention mechanism is becoming increasingly popular in Natural Language Processing (NLP) applications, showing superior performance than convolutional and recurrent architectures. However, general-purpose platforms such as CPUs and GPUs are inefficient when performing attention inference due to complicated data movement and low arithmetic intensity. Moreover, existing NN accelerators mainly focus on optimizing convolutional or recurrent models, and cannot efficiently support attention. In this paper, we present SpAtten, an efficient algorithm-architecture co-design that leverages token sparsity, head sparsity, and quantization opportunities to reduce the attention computation and memory access. Inspired by the high redundancy of human languages, we propose the novel cascade token pruning to prune away unimportant tokens in the sentence. We also propose cascade head pruning to remove unessential heads. Cascade pruning is fundamentally different from weight pruning since there is no trainable weight in the attention mechanism, and the pruned tokens and heads are selected on the fly. To efficiently support them on hardware, we design a novel top-k engine to rank token and head importance scores with high throughput. Furthermore, we propose progressive quantization that first fetches MSBs only and performs the computation; if the confidence is low, it fetches LSBs and recomputes the attention outputs, trading computation for memory reduction.Extensive experiments on 30 benchmarks show that, on average, SpAtten reduces DRAM access by 10.0× with no accuracy loss, and achieves 1.6×, 3.0×, 162×, 347× speedup, and 1.4×, 3.2×, 1193×, 4059× energy savings over A3 accelerator, MNNFast accelerator, TITAN Xp GPU, Xeon CPU, respectively.
Stochastic PDEs on graphs as scaling limits of discrete interacting systems

Stochastic partial differential equations (SPDE) on graphs were recently introduced by Cerrai and Freidlin (Ann. Inst. Henri Poincare Probab. Stat. 53 (2017) 865–899). This class of stochastic equations in infinite dimensions provides a minimal framework for the study of the effective dynamics of much more complex systems. However, how they emerge from microscopic individual-based models is still poorly understood, partly due to complications near vertex singularities. In this work, motivated by the study of the dynamics and the genealogies of expanding populations in spatially structured environments, we obtain a new class of SPDE on graphs of Wright–Fisher type which have nontrivial boundary conditions on the vertex set. We show that these SPDE arise as scaling limits of suitably defined biased voter models (BVM), which extends the scaling limits of Durrett and Fan (Ann. Appl. Probab. 26 (2016) 3456–3490). We further obtain a convergent simulation scheme for each of these SPDE in terms of a system of Ito SDEs, which is useful when the size of the BVM is too large for stochastic simulations. These give the first rigorous connection between SPDE on graphs and more discrete models, specifically, interacting particle systems and interacting SDEs. Uniform heat kernel estimates for symmetric random walks approximating diffusions on graphs are the keys to our proofs. Some open problems are provided as further motivations of our study.