cssi/SciSciGPT-SciSciNet huggingface dataset:
The Critical Role of Instructional Response for Identifying Dyslexia and Other Learning Disabilities

This article addresses the nature of dyslexia and best practices for identification and treatment within the context of multitier systems of support (MTSS). We initially review proposed definitions of dyslexia to identify key commonalities and differences in proposed attributes. We then review empirical evidence for proposed definitional attributes, focusing on key sources of controversy, including the role of IQ, instructional response, as well as issues of etiology and immutability. We argue that current empirical evidence supports a dyslexia classification marked by specific deficits in reading and spelling words combined with inadequate response to evidence-based instruction. We then propose a "hybrid" dyslexia identification process built to gather data relevant to these markers of dyslexia. We argue that this assessment process is best implemented within school-wide MTSS because it leverages data routinely collected in well-implemented MTSS, including documentation of student progress and fidelity of implementation. In contrast with other proposed methods for learning disability (LD) identification, the proposed "hybrid" method demonstrates strong evidence for valid decision-making and directly informs intervention.
Situational Awareness Enhanced through Social Media Analytics: A Survey of First Responders

Socialmedia data has been increasingly used to facilitate situational awareness during events and emergencies such as natural disasters. While researchers have investigated several methods to summarize, visualize or mine the data for analysis, first responders have not been able to fully leverage research advancements largely due to the gap between academic research and deployed, functional systems. In this paper, we explore the opportunities and barriers for the effective use of social media data from first responders' perspective. We present the summary of several detailed interviews with first responders on their use of social media for situational awareness. We further assess the impact of SMART—a social media visual analytics system—on first responder operations.
On a spectral theorem of Weyl

Abstract We give a new proof of a theorem of Weyl on the continuous part of the spectrum of Sturm–Liouville operators on the half-line with asymptotically constant coefficients. Earlier arguments, due to Weyl and Kodaira, depended on particular features of Green’s functions for linear ordinary differential operators. We use a concept of asymptotic containment of C ∗ -algebra representations that has geometric origins. We apply the concept elsewhere to the Plancherel formula for spherical functions on reductive groups.
The Top Quark: Past, Present, and Future

In this talk I discuss the widespread impact of the top quark on phenomena in elementary particle physics as codified through the Standard Model (SM), its important role in motivating the possibility of physics beyond the Standard Model (BSM), and its use as a signal for detailed studies of the SM and searches for BSM physics.
Modeling metasurfaces using discrete-space impulse response technique

Metasurfaces are arrays of subwavelength meta-atoms that shape waves in a compact and planar form factor. Analysis and design of metasurfaces require methods for modeling their interactions with wa...
Assessing the Quality of Published Surveys in Ophthalmology.

Surveys are an important research modality in ophthalmology, but their quality has not been rigorously assessed. This study evaluated the quality of published ophthalmic surveys.Three survey method...
Path Oblivious Heap: Optimal and Practical Oblivious Priority Queue

We propose Path Oblivious Heap, an extremely simple, practical, and optimal oblivious priority queue. Our construction also implies a practical and optimal oblivious sorting algorithm which we call Path Oblivious Sort. Not only are our algorithms asymptotically optimal, we show that their practical performance is only a small constant factor worse than insecure baselines. More specificially, assuming roughly logarithmic client private storage, Path Oblivious Heap consumes 2× to 7× more bandwidth than the ordinary insecure binary heap; and Path Oblivious Sort consumes 4.5× to 6× more bandwidth than the insecure Merge Sort. We show that these performance results improve existing works by 1-2 orders of magnitude. Finally, we evaluate our algorithm for a multi-party computation scenario and show 7x to 8x reduction in the number of symmetric encryptions relative to the state of the art1.
Uniqueness and ergodicity of stationary directed polymers on $\mathbb Z^2$

We study the ergodic theory of stationary directed nearest-neighbor polymer models on $$\mathbb {Z}^2$$ , with i.i.d. weights. Such models are equivalent to specifying a stationary distribution on the space of weights and correctors that satisfy certain consistency conditions. We show that for a prescribed weight distribution and corrector mean, there is at most one stationary polymer distribution which is ergodic under the $$e_1$$ or $$e_2$$ shift. Further, if the weights have more than two moments and the corrector mean vector is an extreme point of the superdifferential of the limiting free energy, then the corrector distribution is ergodic under each of the $$e_1$$ and $$e_2$$ shifts.
Strategic pricing in a differentiated product oligopoly model: fluid milk in Boston

In an imperfectly competitive industry, differentiated products compete with each other with price rather than quantity as the strategic variable. Several previous studies have employed a generalized Nash–Bertrand model: Liang (1989), Cotterill (1994), Cotterill et al. (2000), and Kinoshita et al. (2002); however, only Liang has explored the theoretical foundations of that model. This article generalizes the Liang two-good model to three goods. A surprising and important result follows. Price-conjectural variations do not exist in models with three or more goods. Price-reaction functions, however, exist in multiple-good models. We estimate them jointly with a brand-level demand system to evaluate the total impact of a brand manager's price change on own quantity. In a differentiated product market, this is a useful addition to a partial demand elasticity approach, because a change in one brand's price typically engenders a price reaction by other brands that affects own quantity via substantial cross-price elasticities among substitutes. Strategic pricing in the Boston fluid milk market was also influenced by the existence of a raw milk price support program, the Northeast Dairy Compact. We find that the advent of the Compact was a focal point event that crystallized a shift away from Nash–Bertrand to more cooperative pricing. If the downstream market is not competitive, one needs to consider strategic price reactions when designing and evaluating agricultural price programs.
Nonequilibrium molecular dynamics

Abstract MOLECULAR DYNAMICS has been generalized in order to stimulate a variety of NONEQUILIBRIUM systems. This generalization has been achieved by adopting microscopic mechanical definitions of macroscopic thermodynamic and hydrodynamic variables, such as temperature and stress. Some of the problems already treated include rapid plastic deformation, intense heat conduction, strong shockwaves simulation, and far-from-equilibrium phase transformations. Continuing advances in technique and in the modeling of interatomic forces, coupled with qualitative improvements in computer hardware, are enabling such simulations to approximate real-world microscale and nanoscale experiments.
History of Intelligence Measurement

The history of intelligence measurement can be roughly divided into three chronological periods: the first (1870–1920s), a period of initial interest in defining intelligence and the establishment and use of intelligence tests; the second (1930s–1960s), a period of repudiation of the hereditarian assumptions underlying the tests; and the third (1969 to present), a period of resurgence of belief in the connection between intelligence and heredity. Keywords: heredity; IQ ; coefficient of correlation; immigration restriction; factor analysis; twin studies
Inequality and Volatility Moderation in Russia: Evidence from Micro-Level Panel Data on Consumption and Income

Abstract We construct key household and individual economic variables using a panel micro data set from the Russia Longitudinal Monitoring Survey (RLMS) for 1994–2005. We analyze cross-sectional income and consumption inequality trends and find that inequality decreased during the 2000–2005 economic recovery. The decrease appears to be driven by falling volatility of transitory income shocks. The response of consumption to permanent and transitory income shocks becomes weaker later in the sample, consistent with greater self-insurance against permanent shocks and greater smoothing of transitory shocks. Finally, expenditure and income inequality in Russia are not far apart.
Chapter 4 – Input: Gateway to the Computer

Publisher Summary Computers input information from a variety of input devices. Punched cards are declining in use because cards are bulky, expensive, in short supply, are not reusable, have a small capacity, and have file integrity problems. Verification is the “repunching” of cards to be sure that they were punched correctly. It is an expensive and time-consuming process that is being replaced by editing and checking programs. Key-to-tape and key-to-disk systems facilitate high-speed and accurate data entry onto reusable magnetic tapes and disks. Terminal-oriented systems allow users to access the computer on-line. With punched-card data entry, users operate offline from the computer. Touch sensing allows users to point to characters, words, or symbols on the screen of a cathode ray tube (CRT) to initiate the actions that they wish to take. It is one of the most user-friendly interfaces. Source data automation techniques capture data automatically from source documents in computer-readable form so that manual data entry is eliminated.
Identifying Consumer Preferences for Nutrition Information on Grocery Store Shelf Labels

Nutrition labels can potentially benefit consumers by increasing product knowledge and reducing search costs. However, the global increase in obesity rates leads one to question the effectiveness of current nutrition information formats. Alternative formats for providing nutrition information may be more effective. Shoppers at a major grocery chain participated in choice experiments designed to identify preferences for nutrition information provided on grocery store shelf labels. Shoppers demonstrate a strong affinity for shelf-label nutrition information and the presentation of the nutrition information significantly affects their preferences as well. Several demographic variables help to explain differences in preferences.
Finite element analysis and modal testing of a rotating wind turbine

A finite element procedure, which includes geometric stiffening, and centrifugal and Coriolis terms resulting from the use of a rotating coordinate system, has been developed to compute the mode shapes and frequencies of rotating structures. Special application of this capability has been made to Darrieus, vertical axis wind turbines. In a parallel development effort, a technique for the modal testing of a rotating vertical axis wind turbine has been established to measure modal parameters directly. Results from the predictive and experimental techniques for the modal frequencies and mode shapes are compared over a wide range of rotational speeds.
Cases Relating to Chapter 8 – Competency of Evidence and Witnesses

Publisher Summary This chapter presents several case studies related to competency of evidence and witnesses. These cases include the case of United States versus Phibbs, and State versus Wells. In the first case, the defendants, Raymond Huckelby, Diane Whited, Robert Phibbs, Victor Rojas, and Robert Murr appeal their convictions arising from their participation in a cocaine distribution ring operating in Tennessee and Kentucky. In addition, Phibbs and Rojas challenge the appropriateness of their sentences. In the second case, the Appellant, Jerome Wells, appeals from his conviction in the Summit County Court of Common Pleas of one count of gross sexual imposition. This Court reverses and remands for a new trial. Following a jury trial, Wells was convicted of the lesser included offense of gross sexual imposition.
Efficient unitary method for simulation of driven quantum dot systems

Density matrices evolved according the von Neumann equation are commonly used to simulate the dynamics of driven quantum systems. However, computational methods using density matrices are often too slow to explore the large parameter spaces of solid state quantum systems. Here we develop a unitary computation method to quickly perform simulations for closed quantum systems, where dissipation to the environment can be ignored. We use three techniques to optimize simulations, apply them to six time-dependent pulses for a semiconductor quantum dot qubit system, and predict the dynamic evolutions. We compare computational times between our unitary method and the density matrix method for a variety of image sizes. As an example, we implement our unitary method for a realistic four-state system [Z. Shi, et al., Nat. Commun. 5, 3020 (2014)], and find that it is over two orders of magnitude faster than the corresponding density matrix method implemented in the popular quantum simulation software QuTiP.
Impact of Voucher Design on Public School Performance: Evidence from Florida and Milwaukee Voucher Programs

This article compares two alternative voucher designs implemented in the U.S. The Milwaukee program was a “voucher shock” program that made low-income students eligible for vouchers. The Florida program was an accountability-tied voucher program that faced failing schools with “threat of vouchers” and stigma. In the context of a formal theoretical model, the study argues that the threatened schools will improve under the Florida-type program and this improvement will exceed that of the corresponding treated schools under the Milwaukee-type program. Using school-level scores from Florida and Wisconsin, and a difference-in-differences estimation strategy in trends, it then finds strong support in favor of these predictions.
The Impact of Information on Land Development: a Dynamic and Stochastic Analysis

In a two period model of land development, Arrow and Fisher, and Henry have shown that when development is both indivisible and irreversible, a developer who ignores the possibility of obtaining new information about the outcome of such development will invariably underestimate the benefits of preservation and hence favor development. This paper extends aspects of this literature by (i) studying the development question in a dynamic and stochastic framework, and (ii) explicitly incorporating an information production function into the analysis. In such a setting, I ask and answer the question concerning when development should take place.
Direct Arsenic Removal from Water Using Non-Membrane, Low-Temperature Directional Solvent Extraction

Arsenic (As) poisoning in water is a critical global problem. Current arsenic removal techniques involving chemical reaction, ion exchange, or membrane processes can be expensive, inaccessible, or ...
What is it about bicycling? Evidence from Davis, California

Abstract Enjoyment of alternatives to driving can make up for what are often longer travel times in the mode choice calculus. In particular, studies show that liking of bicycling is a significant predictor of bicycling, but few studies have systematically explored what it is about bicycling that people like. We address this question in an exploratory analysis of positive statements about bicycling drawn from 54 in-depth interviews with residents of Davis, California about their experiences with bicycling over their lifetimes. Eight themes emerged from our analysis of these statements: activities, bonding, sensations, feelings, pride, convenience, nice places, and memories. The incidence of themes differs across stages of life and gender. Participants often talked about the freedom and excitement of bicycling when they were children, for example, but tended to focus on convenience and health benefits when talking about bicycling as adults. These results reinforce findings from previous studies while adding new dimensions. This study provides a starting point for further research as well as guidance for the development of policies and programs to encourage more bicycling.
Pediatric donor heart allocation in the United States, 2006-2017: Current patterns and potential for improvement.

OBJECTIVE To understand current donor heart allocation practices for pediatric transplantation. BACKGROUND Despite high waitlist mortality rates among pediatric patients awaiting transplant, a substantial proportion of donor hearts go unused. Analysis of UNOS match run data may identify opportunities to optimize organ utilization. METHODS Using UNOS/OPTN data, we evaluated all match runs for pediatric (<18 years) donor hearts from 1/1/2006 to 3/31/2017. We assessed final disposition of donor hearts, reasons for donor refusal, and other match run characteristics. Variation in total offers made per organ, and refusal rates by OPOs were also evaluated. RESULTS Of 7585 pediatric potential donor hearts, 2226 (29.3%) were refused. Hearts accepted underwent a median of 2 offers (IQR: 1-5), compared to 11 (IQR: 5-24) for refused donor hearts. Organ refusal rates decreased from 36.9% in 2006-2009 to 22.3% in 2014-2017 (P < .001). Reasons for refusal included quality (80.9%), size mismatch (57.5%), and known/suspected crossmatch positivity (39.1%). Among 1800 hearts deemed "poor quality" by ≥1 transplant program, less than half (46.6%) were coded "poor quality" by multiple refusing programs. Organ refusal rates ranged from 13.5% to 83.3% across OPOs, and there was no correlation between refusal rates and median number of offers made by the OPO. CONCLUSION Although more organs are being used over time, 1 in 5 available pediatric donor hearts are still discarded. The lack of donor evaluation consensus and wide variability in donor refusal rates indicates a need for standardization of donor assessment and match run processes across OPOs.
Broken Bricks and the Pick-up Sticks Problem

We generalize the well-known broken stick problem in several ways, including a discrete “brick” analogue and a sequential “pick-up sticks/bricks” version. The limit behavior of the broken brick pro...
Representations for Stable Off-Policy Reinforcement Learning

Reinforcement learning with function approximation can be unstable and even divergent, especially when combined with off-policy learning and Bellman updates. In deep reinforcement learning, these issues have been dealt with empirically by adapting and regularizing the representation, in particular with auxiliary tasks. This suggests that representation learning may provide a means to guarantee stability. In this paper, we formally show that there are indeed nontrivial state representations under which the canonical TD algorithm is stable, even when learning off-policy. We analyze representation learning schemes that are based on the transition matrix of a policy, such as proto-value functions, along three axes: approximation error, stability, and ease of estimation. In the most general case, we show that a Schur basis provides convergence guarantees, but is difficult to estimate from samples. For a fixed reward function, we find that an orthogonal basis of the corresponding Krylov subspace is an even better choice. We conclude by empirically demonstrating that these stable representations can be learned using stochastic gradient descent, opening the door to improved techniques for representation learning with deep networks.
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution

Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple neighboring frames (supporting frames). Due to varying motion of cameras or objects, the reference frame and each support frame are not aligned. Therefore, temporal alignment is a challenging yet important problem for VSR. Previous VSR methods usually utilize optical flow between the reference frame and each supporting frame to warp the supporting frame for temporal alignment. However, both inaccurate flow and the image-level warping strategy will lead to artifacts in the warped supporting frames. To overcome the limitation, we propose a temporally-deformable alignment network (TDAN) to adaptively align the reference frame and each supporting frame at the feature level without computing optical flow. The TDAN uses features from both the reference frame and each supporting frame to dynamically predict offsets of sampling convolution kernels. By using the corresponding kernels, TDAN transforms supporting frames to align with the reference frame. To predict the HR video frame, a reconstruction network taking aligned frames and the reference frame is utilized. Experimental results demonstrate that the TDAN is capable of alleviating occlusions and artifacts for temporal alignment and the TDAN-based VSR model outperforms several recent state-of-the-art VSR networks with a comparable or even much smaller model size. The source code and pre-trained models are released in https://github.com/YapengTian/TDAN-VSR.
Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand

Summary Least-squares estimates of the response of gasoline consumption to a change in the gasoline price are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. Gasoline buyers increase purchases before tax increases and delay purchases before tax decreases, rendering the tax instrument endogenous. Including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower elasticity estimates. Copyright © 2016 John Wiley & Sons, Ltd.
Is average correlation related to expected returns: evidence from global markets

We examine whether average country-level stock market correlation is related to global equity returns. Previous research focusing on the U.S. suggests that average firm-level correlation captures s...
Active Voltage-Ripple Compensation in an Integrated Generator-Rectifier System

An integrated generator-rectifier system can produce high conversion efficiency and reduce the size of the active rectifier in high-power ac-to-dc conversion. A major disadvantage of this system is the use of bulky filter capacitors with passive rectifiers to obtain a low voltage-ripple dc bus. These filters are the main contributor to the overall system size, weight, cost, and failure, as well as to the low power factor at the ac ports powering the passive rectifiers. This article presents an alternative approach: integrating the function of the filter elements into the active rectifier. A voltage opposite the passive-rectifier ripple component is synthesized at the active-rectifier dc-side by modulating the ac-side current. Compensation occurs due to the series connection of the rectifier dc outputs. In addition, an overall control architecture is proposed to use the active rectifier both as a filter element and a dc-bus voltage regulator. Simulation on a 3-MW, 4.9-kV dc system shows the total dc-bus-voltage ripple factor is reduced by 57%, while the power factor at the passive-rectifier ac sides is 0.95. The proposed control architecture achieves regulation of the dc-bus voltage at variable dc-bus current and variable generator speed conditions. Experimental results corroborate the findings.
Direct numerical simulation of compressible free shear flows

Direct numerical simulations of compressible free shear layers in open domains are conducted. Compact finite-difference schemes of spectral-like accuracy are used for the simulations. Both temporally-growing and spatially-growing mixing layers are studied. The effect of intrinsic compressibility on the evolution of vortices is studied. The use of convective Mach number is validated. Details of vortex roll up and pairing are studied. Acoustic radiation from vortex roll up, pairing and shape oscillations is studied and quantified.
A robust nonlinear low-dimensional manifold for single cell RNA-seq data

Modern developments in single-cell sequencing technologies enable broad insights into cellular state. Single-cell RNA sequencing (scRNA-seq) can be used to explore cell types, states, and developmental trajectories to broaden our understanding of cellular heterogeneity in tissues and organs. Analysis of these sparse, high-dimensional experimental results requires dimension reduction. Several methods have been developed to estimate low-dimensional embeddings for filtered and normalized single-cell data. However, methods have yet to be developed for unfiltered and unnormalized count data that estimate uncertainty in the low-dimensional space. We present a nonlinear latent variable model with robust, heavy-tailed error and adaptive kernel learning to estimate low-dimensional nonlinear structure in scRNA-seq data. Gene expression in a single cell is modeled as a noisy draw from a Gaussian process in high dimensions from low-dimensional latent positions. This model is called the Gaussian process latent variable model (GPLVM). We model residual errors with a heavy-tailed Student’s t-distribution to estimate a manifold that is robust to technical and biological noise found in normalized scRNA-seq data. We compare our approach to common dimension reduction tools across a diverse set of scRNA-seq data sets to highlight our model’s ability to enable important downstream tasks such as clustering, inferring cell developmental trajectories, and visualizing high throughput experiments on available experimental data. We show that our adaptive robust statistical approach to estimate a nonlinear manifold is well suited for raw, unfiltered gene counts from high-throughput sequencing technologies for visualization, exploration, and uncertainty estimation of cell states.
Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization.

We analyze the efficacy of modern neuro-evolutionary strategies for continuous control optimization. Overall the results collected on a wide variety of qualitatively different benchmark problems indicate that these methods are generally effective and scale well with respect to the number of parameters and the complexity of the problem and are relatively robust with respect to the setting of hyper-parameters. The comparison of the most promising methods indicates that the OpenAI-ES algorithm outperforms or equals the other algorithms on all considered problems. Moreover, we demonstrate how the reward functions optimized for reinforcement learning methods are not necessarily effective for evolutionary strategies and vice versa. This finding has important consequences since it implies that the comparison performed to date are biased toward one or the other class of algorithm and since it might lead to reconsideration of the relatively efficacy of the two classes of algorithms
X -Secure T -Private Information Retrieval From MDS Coded Storage With Byzantine and Unresponsive Servers

The problem of $X$ -secure $T$ -private information retrieval from MDS coded storage is studied in this paper, where the user wishes to privately retrieve one out of $K$ independent messages that are distributed over $N$ servers according to an MDS code. It is guaranteed that any group of up to $X$ colluding servers learn nothing about the messages and that any group of up to $T$ colluding servers learn nothing about the identity of desired message. A lower bound of achievable rates is proved by presenting a novel scheme based on cross-subspace alignment and a successive decoding with interference cancellation strategy. For large number of messages $(K\rightarrow \infty)$ the achieved rate, which we conjecture to be optimal, improves upon the best known rates previously reported in the literature by Raviv and Karpuk, and generalizes an achievable rate for MDS-TPIR previously found by Freij-Hollanti et al. that is also conjectured to be asymptotically optimal. The setting is then expanded to allow unresponsive and Byzantine servers. Finally, the scheme is applied to find a new lower convex hull of (download, upload) pairs of secure and private distributed matrix multiplication that generalizes, and in certain asymptotic settings strictly improves upon the best known previous results.
ADNC-RS, a clinical-genetic risk score, predicts Alzheimer’s pathology in autopsy-confirmed Parkinson’s disease and Dementia with Lewy bodies

Growing evidence suggests overlap between Alzheimer's disease (AD) and Parkinson's disease (PD) pathophysiology in a subset of patients. Indeed, 50-80% of autopsy cases with a primary clinicopathological diagnosis of Lewy body disease (LBD)-most commonly manifesting during life as PD-have concomitant amyloid-beta and tau pathology, the defining pathologies of AD. Here we evaluated common genetic variants in genome-wide association with AD as predictors of concomitant AD pathology in the brains of people with a primary clinicopathological diagnosis of PD or Dementia with Lewy Bodies (DLB), diseases both characterized by neuronal Lewy bodies. In the first stage of our study, 127 consecutive autopsy-confirmed cases of PD or DLB from a single center were assessed for AD neuropathological change (ADNC), and these same cases were genotyped at 20 single nucleotide polymorphisms (SNPs) found by genome-wide association study to associate with risk for AD. In these 127 training set individuals, we developed a logistic regression model predicting the presence of ADNC, using backward stepwise regression for model selection and tenfold cross-validation to estimate performance. The best-fit model generated a risk score for ADNC (ADNC-RS) based on age at disease onset and genotype at three SNPs (APOE, BIN1, and SORL1 loci), with an area under the receiver operating curve (AUC) of 0.751 in our training set. In the replication stage of our study, we assessed model performance in a separate test set of the next 81 individuals genotyped in our center. In the test set, the AUC was 0.781, and individuals with ADNC-RS in the top quintile had four-fold increased likelihood of having AD pathology at autopsy compared with those in each of the lowest two quintiles. Finally, in the validation stage of our study, we applied our ADNC-RS model to 70 LBD individuals from 20 Alzheimer's Disease Research Centers (ADRC) whose autopsy and genetic data were available in the National Alzheimer's Coordinating Center (NACC) database. In this validation set, the AUC was 0.754. Thus, in patients with autopsy-confirmed PD or DLB, a simple model incorporating three AD-risk SNPs and age at disease onset substantially enriches for concomitant AD pathology at autopsy, with implications for identifying LBD patients in which targeting amyloid-beta or tau is a therapeutic strategy.
The Compelling Case for Stronger and More Effective Leverage Regulation in Banking

AbstractExcessive leverage (indebtedness) in banking endangers the public and distorts the economy. Yet current and proposed regulations only tweak previous regulations that failed to provide financial stability. This paper discusses the forces that have led to this situation, some of which appear to be misunderstood. The benefits to society of requiring that financial institutions use significantly more equity funding than the status quo are large, while any costs are entirely private because of banks’ ability to shift some of their costs to others when they use debt. Without quantitative analysis, I outline improved regulations and how they can be implemented.
SHEARer: highly-efficient hyperdimensional computing by software-hardware enabled multifold approximation

Hyperdimensional computing (HD) is an emerging paradigm for machine learning based on the evidence that the brain computes on high-dimensional, distributed, representations of data. The main operation of HD is encoding, which transfers the input data to hyperspace by mapping each input feature to a hypervector, followed by a bundling procedure that adds up the hypervectors to realize the encoding hypervector. The operations of HD are simple and highly parallelizable, but the large number of operations hampers the efficiency of HD in embedded domain. In this paper, we propose SHEARer, an algorithmhardware co-optimization to improve the performance and energy consumption of HD computing. We gain insight from a prudent scheme of approximating the hypervectors that, thanks to error resiliency of HD, has minimal impact on accuracy while provides high prospect for hardware optimization. Unlike previous works that generate the encoding hypervectors in full precision and then and then perform ex-post quantization, we compute the encoding hypervectors in an approximate manner that saves resources yet affords high accuracy. We also propose a novel FPGA architecture that achieves striking performance through massive parallelism with low power consumption. Moreover, we develop a software framework that enables training HD models by emulating the proposed approximate encodings. The FPGA implementation of SHEARer achieves an average throughput boost of 104,904× (15.7×) and energy savings of up to 56,044× (301×) compared to state-of-the-art encoding methods implemented on Raspberry Pi 3 (GeForce GTX 1080 Ti) using practical machine learning datasets.
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere

We present a significantly-improved data-driven global weather forecasting framework using a deep convolutional neural network (CNN) to forecast several basic atmospheric variables on a global grid...
Borel reducibility and symmetric models

We develop a correspondence between the study of Borel equivalence relations induced by closed subgroups of $S_\infty$, and the study of symmetric models and weak choice principles, and apply it to prove a conjecture of Hjorth-Kechris-Louveau (1998). For example, we show that the equivalence relation $\cong^\ast_{\omega+1,0}$ is strictly below $\cong^\ast_{\omega+1,<\omega}$ in Borel reducibility. By results of Hjorth-Kechris-Louveau, $\cong^\ast_{\omega+1,<\omega}$ provides invariants for $\Sigma^0_{\omega+1}$ equivalence relations induced by actions of $S_\infty$, while $\cong^\ast_{\omega+1,0}$ provides invariants for $\Sigma^0_{\omega+1}$ equivalence relations induced by actions of abelian closed subgroups of $S_\infty$. We further apply these techniques to study the Friedman-Stanley jumps. For example, we find an equivalence relation $F$, Borel bireducible with $=^{++}$, so that $F\restriction C$ is not Borel reducible to $=^{+}$ for any non-meager set $C$. This answers a question of Zapletal, arising from the results of Kanovei-Sabok-Zapletal (2013). For these proofs we analyze the symmetric models $M_n$, $n<\omega$, developed by Monro (1973), and extend the construction past $\omega$, through all countable ordinals. This answers a question of Karagila (2019).
Computational Analysis of a Three-Dimensional High-Velocity Oxygen Fuel (HVOF) Thermal Spray Torch

An analysis of a high-velocity oxygen fuel thermal spray torch is presented using computational fluid dynamics (CFD). Three-dimensional CFD results are presented for a curved aircap used for coating interior surfaces such as engine cylinder bores. The device analyzed is similar to the Metco diamond jet rotating wire torch, but wire feed is not simulated. The feed gases are injected through an axisymmetric nozzle into the curved aircap. Argon is injected through the center of the nozzle. Premixed propylene and oxygen are introduced from an annulus in the nozzle, while cooling air is injected between the nozzle and the interior wall of the aircap. The combustion process is modeled assuming instantaneous chemistry. A standard, two-equation, k-e turbulence model is employed for the turbulent flow field. An implicit, iterative, finite volume numerical technique is used to solve the coupled conservation of mass, momentum, and energy equations for the gas in a sequential manner. Computed flow fields inside and outside the aircap are presented and discussed.
Is Corporate Social Responsibility Related to Corporate Tax Avoidance? Evidence from a Natural Experiment

We employ states’ enactment of constituency statutes as plausibly exogenous shocks to the marginal cost of corporate social responsibility (CSR) and examine the relation between CSR and corporate tax avoidance. We find almost no evidence of an association between the enactment of constituency statutes and tax avoidance. We use confidence intervals and other analysis to rule out low power as an explanation. Using an instrumental variables design, we find evidence that third-party CSR scores increase following constituency statutes, yet without a detectable impact on tax avoidance. The lack of results across multiple proxies and specifications suggests firms decouple CSR from tax policy. Our study introduces a strong identification strategy common in management research to the accounting literature, producing a novel no-result finding on a popular research question.
A Complete Equational Axiomatisation of Partial Differentiation.

Abstract We formalise the well-known rules of partial differentiation in a version of equational logic with function variables and binding constructs. We prove the resulting theory is complete with respect to polynomial interpretations. The proof makes use of Severi's interpolation theorem that all multivariate Hermite problems are solvable. We also present a number of related results, such as decidability and equational completeness.
One Powell generator is redundant

In 1980 J. Powell proposed that five specific elements sufficed to generate the Goeritz group of any Heegaard splitting of $S^3$. This conjecture remains unresolved for genus $g \geq 4$. Here a short argument shows that one of his proposed generators is redundant, in fact a consequence of three of the other four.
Infrared satellite-derived sea surface skin temperature sensitivity to aerosol vertical distribution ̶ Field data analysis and model simulations

Abstract Sea surface temperature is an Essential Climate Variable. The radiative impact of mineral dust is one of the major contributors to inaccuracies in the satellite-retrieved sea surface skin temperature (SSTskin). Different aerosol dust vertical distributions have varying effects on the satellite-derived SSTskin. To further investigate the physical mechanisms of aerosol effects on Terra MODerate-resolution Imaging Spectroradiometers (MODIS) derived SSTskin, the aerosol radiative effects were studied with a field-data match-up analysis and radiative transfer simulations. The field data are measurements of the SSTskin derived from highly accurate ship-based infrared spectrometers vertical atmospheric temperature and water vapor radiosonde profiles. The aerosol dust concentrations in three-dimensions from the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 have been used as input to radiative transfer simulations. Based on the analysis of field data and simulations, we have empirically determined that the sensitivity of the Terra MODIS retrieved SSTskin accuracies is related to 1) dust concentration in the atmosphere, 2) the dust layer altitude, and 3) the dust layer temperature. As the aerosol altitude increases, the effect on the SSTskin retrievals becomes more negative in proportion to the temperature contrast with the sea surface. SSTskin differences, satellite-derived - surface measurements, for a given aerosol layer optical depth vary between −3 K and 1 K according to our match-up comparisons and radiative transfer simulations.
Biliaison of sheaves

We define an equivalence relation among coherent sheaves on a projective variety called biliaison. We prove the existence of sheaves that are minimal in a biliaison class in a suitable sense, and show that all sheaves in the same class can be obtained from a minimal one using certain deformations and other basic moves. Our results generalize the main theorems of liaison theory of subvarieties to sheaves, and provide a framework to study sheaves and subvarieties simultaneously.
New approximations for the area of the Mandelbrot set

Due to its fractal nature, much about the area of the Mandelbrot set $M$ remains to be understood. While a series formula has been derived by Ewing and Schober to calculate the area of $M$ by considering its complement inside the Riemann sphere, to date the exact value of this area remains unknown. This paper presents new improved upper bounds for the area based on a parallel computing algorithm and for the 2-adic valuation of the series coefficients in terms of the sum-of-digits function.
Diversity and Inclusion Metrics in Subset Selection

The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives. When considering the relevance of ethical concepts to subset selection problems, the concepts of diversity and inclusion are additionally applicable in order to create outputs that account for social power and access differentials. We introduce metrics based on these concepts, which can be applied together, separately, and in tandem with additional fairness constraints. Results from human subject experiments lend support to the proposed criteria. Social choice methods can additionally be leveraged to aggregate and choose preferable sets, and we detail how these may be applied.
Convective Wavelength Shifts in the Spectra of Late-Type Stars

We present ultrahigh-resolution spectra for a set of nearby F-G-K stars on, or close to, the main sequence. The wavelength shifts of stellar lines relative to their laboratory wavelengths are measured for more than a thousand Fe I lines per star, finding a clear correlation with line depth. The observed patterns are interpreted as convective blueshifts that become more prominent for weaker lines, which are formed in deeper atmospheric layers. A morphological sequence with spectral type or effective temperature is apparent. Two K giant stars have also been studied. The velocity span between weak and strong lines for these stars is larger than for the dwarfs and subgiants of similar spectral types. Our results show that convective wavelength shifts may seriously compromise the accuracy of absolute spectroscopic radial velocities but that an empirical correction may be applied to measured velocities.
Spreading Speeds and Traveling Waves for Non-cooperative Reaction-Diffusion Systems

Much has been studied on the spreading speed and traveling wave solutions for cooperative reaction–diffusion systems. In this paper, we shall establish the spreading speed for a large class of non-cooperative reaction–diffusion systems and characterize the spreading speed as the slowest speed of a family of non-constant traveling wave solutions. Our results are applied to a partially cooperative system describing interactions between ungulates and grass.
Nonlinear plasma waves driven by short ultrarelativistic electron bunches

We advance a theory of quasistatic approximation and investigate the excitation of nonlinear plasma waves by the driving beam of ultrarelativistic electrons using a novel electrostatic-like particle-in-cell code. Assuming that the beam occupies an infinitesimally small volume, we find the radius and the length of the plasma bubble formed in the wake of the driver for varying values of the beam charge. The mechanism of bubble formation is explained by developing simple models of the bubble at large charges. Plasma electrons expelled by the driver charge excite secondary plasma waves, which complicate the plasma electron flow near the bubble boundary.
Dark defect charge dynamics in bulk chemical-vapor-deposition-grown diamonds probed via nitrogen vacancy centers

Although chemical vapor deposition (CVD) is one of the preferred routes to synthetic diamond crystals, a full knowledge of the point defects produced during growth is still incomplete. Here we exploit the charge and spin properties of nitrogen vacancy (NV) centers in type-1b CVD diamond to expose an optically and magnetically dark point defect, so far virtually unnoticed despite an abundance comparable to (if not greater than) that of substitutional nitrogen. Indirectly detected photoluminescence spectroscopy indicates a donor state 1.6 eV above the valence band, although the defect's microscopic structure and composition remain elusive. Our results may prove relevant to the growing set of applications that rely on CVD-grown single-crystal diamond.
Justification of Logarithmic Loss via the Benefit of Side Information

We consider a natural measure of relevance: the reduction in optimal prediction risk in the presence of side information. For any given loss function, this relevance measure captures the benefit of side information for performing inference on a random variable under this loss function. When such a measure satisfies a natural data processing property, and the random variable of interest has alphabet size greater than two, we show that it is uniquely characterized by the mutual information, and the corresponding loss function coincides with logarithmic loss. In doing so, our work provides a new characterization of mutual information, and justifies its use as a measure of relevance. When the alphabet is binary, we characterize the only admissible forms the measure of relevance can assume while obeying the specified data processing property. Our results naturally extend to measuring the causal influence between stochastic processes, where we unify different causality measures in the literature as instantiations of directed information.
Dynamics of Majorana-based qubits operated with an array of tunable gates

We study the dynamics of Majorana zero modes that are shuttled via local tuning of the electrochemical potential in a superconducting wire. By performing time-dependent simulations of microscopic lattice models, we show that diabatic corrections associated with the moving Majorana modes are quantitatively captured by a simple Landau-Zener description. We further simulate a Rabi-oscillation protocol in a specific qubit design with four Majorana zero modes in a single wire and quantify constraints on the timescales for performing qubit operations in this setup. Our simulations utilize a Majorana representation of the system, which greatly simplifies simulations of superconductors at the mean-field level.
WHY HOLES ARE NOT LIKE ELECTRONS IV: HOLE UNDRESSING AND SPIN CURRENT IN THE SUPERCONDUCTING STATE

In paper III of this series we proposed a scenario of superconductivity driven by hole "undressing" that involved a complete redistribution of the occupation of single particle energy levels: the holes near the top of the band were proposed to all condense to the bottom of the band. Here we consider a less drastic redistribution involving electrons with a definite spin chirality and show that it is in fact energetically favored by the Coulomb exchange matrix element J over the scenario proposed earlier. It is shown that spin splitting with chiral states reduces the Coulomb repulsion and hence that the Coulomb repulsion promotes spin splitting. Superconductors are proposed to possess a spin-split hole "core" at the bottom of the electronic conduction band in addition to a spin-split Fermi surface. The Dirac sea is proposed to play a key role. The new scenario leads naturally to the existence of a spin current in the superconducting state and is consistent with the Spin Meissner effect and negative charge e...