cssi/SciSciGPT-SciSciNet huggingface dataset:
PMU Data Feature Considerations for Realistic, Synthetic Data Generation

It is critical that the qualities and features of synthetically-generated, PMU measurements used for grid analysis matches those of measurements obtained from field-based PMUs. This ensures that analysis results generated by researchers during grid studies replicate those outcomes typically expected by engineers in real-life situations. In this paper, essential features associated with industry PMU-derived data measurements are analyzed for input considerations in the generation of vast amounts of synthetic power system data. Inherent variabilities in PMU data as a result of the random dynamics in power system operations, oscillatory contents, and the prevalence of bad data are presented. Statistical results show that in the generation of large datasets of synthetic, grid measurements, an inclusion of different data anomalies, ambient oscillation contents, and random cases of missing data samples due to packet drops helps to improve the realism of experimental data used in power systems analysis.
Topological Elasticity of Flexible Structures

A new elastic theory describes how the microstructures of certain materials can lead to large, abrupt deformations whose origin cannot be explained with standard models.
Focused Molding Using Adhesive Pads in Mehta Casting for Early-Onset Scoliosis

Abstract Study Design Prospective clinical series. Objective To determine the effect of adhesive pads placed over the apex of scoliosis curves on curve correction 1) after the first cast and 2) after the final cast. Summary of Background Data Early-onset scoliosis is often effectively managed by serial casting. Properly localizing the apex of the molds with the cast in place is challenging. The authors explored the effectiveness of a novel technique: incorporation of adhesive pads placed over the major curve apex before Mehta casting. Methods The 27 patients who received body casts (2000–2013) were divided into 2 groups: those without and with apical adhesive pads (5–6 layers of pads placed on the major curve's apex during casting): non-pad (NP) group (n = 12) and pad (P) group (n = 15), respectively. Groups were compared regarding the percentage of Cobb angle change from the first cast and curve correction to a Cobb angle of t and chi-square tests (significance was p Results The mean percentage of major first-cast curve correction was 39% ± 18% and 56% ± 17% in the NP and P groups, respectively. Of the 26 patients out of a cast, 11 (42%) had a Cobb angle of Conclusion Adhesive pads placed over major curve(s) during Mehta casting were effective in increasing the amount of major curve correction from the first cast for idiopathic early-onset scoliosis and in decreasing curves to
Hidden Subsurface Reconstruction and Its Atomic Origins in Layered Oxide Cathodes

Structural transformations near surfaces of solid-state materials underpin functional mechanisms of a broad range of applications including catalysis, memory, and energy storage. It has been a long...
Strategies Employed by Ohio Community Colleges to Improve Labor Market Outcomes for Older Students

To remain competitive in the labor market, many middle-aged and older adults need to upgrade existing or learn new skills through occupational training and education. Furthermore, as compared with ...
Recycled asphalt shingle modified asphalt mixture design and performance evaluation

Abstract The inclusion of recycled asphalt shingles (RAS) in asphalt mixtures has become increasingly common; however, the underlying design principles vary significantly by agency. The primary objectives of this study included: (1) evaluating the ‘binder availability’ concept for RAS mixtures through a carefully designed laboratory experiment; (2) demonstrating a balanced mixture performance testing approach for the design of RAS mixtures; and (3) evaluating the field data of RAS mixtures placed in the Midwest region of the U.S. Three asphalt mixture designs with RAS contents of 0, 2.5% and 5.0%, which were designed to have nearly identical volumetric characteristics, were investigated. The binder availability was determined to be approximately 100% in the two RAS mixtures considered. In addition, Hamburg wheel tracking and disk-shaped compact tension tests were conducted to evaluate the high- and low-temperature mixture performance. As expected, the addition of RAS significantly improved the rutting resistance. Disk-shaped compact tension (DC(T)) test results demonstrated that a soft base binder effectively permitted the design of thermal-crack-resistant RAS mixtures. Field investigations indicated that the performance of pavement surfaces containing RAS was similar to that of surfaces containing only reclaimed asphalt pavement or virgin materials. This study also highlights a performance-engineered mix design approach, which is currently being adopted by several agencies in the Midwest (e.g., Illinois Tollway, Missouri DOT, etc.) and can provide mix designers a reliable approach for designing innovative asphalt mixtures with higher recycling levels and a modern, heterogeneous composition. Furthermore, the proposed approach may prove to be a simpler, more mixture-centric alternative to the primary method suggested in AASHTO PP78-17, which recommends arbitrary VMA bumping plus binder extraction, recovery, and advanced binder testing.
Massively Parallel Approximate Distance Sketches.

Data structures that allow efficient distance estimation (distance oracles, distance sketches, etc.) have been extensively studied, and are particularly well studied in centralized models and classical distributed models such as CONGEST. We initiate their study in newer (and arguably more realistic) models of distributed computation: the Congested Clique model and the Massively Parallel Computation (MPC) model. We provide efficient constructions in both of these models, but our core results are for MPC. In MPC we give two main results: an algorithm that constructs stretch/space optimal distance sketches but takes a (small) polynomial number of rounds, and an algorithm that constructs distance sketches with worse stretch but that only takes polylogarithmic rounds. Along the way, we show that other useful combinatorial structures can also be computed in MPC. In particular, one key component we use to construct distance sketches are an MPC construction of the hopsets of [Elkin and Neiman, 2016]. This result has additional applications such as the first polylogarithmic time algorithm for constant approximate single-source shortest paths for weighted graphs in the low memory MPC setting.
An Enhanced Decoding Algorithm for Coded Compressed Sensing

Coded compressed sensing is an algorithmic framework tailored to sparse recovery in very large dimensional spaces. This framework is originally envisioned for the unsourced multiple access channel, a wireless paradigm attuned to machine-type communications. Coded compressed sensing uses a divide-and-conquer approach to break the sparse recovery task into sub-components whose dimensions are amenable to conventional compressed sensing solvers. The recovered fragments are then stitched together using a low complexity decoder. This article introduces an enhanced decoding algorithm for coded compressed sensing where fragment recovery and the stitching process are executed in tandem, passing information between them. This novel scheme leads to gains in performance and a significant reduction in computational complexity. This algorithmic opportunity stems from the realization that the parity structure inherent to coded compressed sensing can be used to dynamically restrict the search space of the subsequent recovery algorithm.
Modeling Shielded Gamma-ray Source Spectra using Non-negative Matrix Factorization

Accurately identifying shielded gamma-ray sources remains a challenge to spectroscopic identification algorithms. In this paper, a data-driven approach for modeling spectral contributions from shielded sources using Non-negative Matrix Factorization (NMF) is examined. When performed on gamma-ray spectra, NMF yields spectral basis vectors that can be used to approximate various gamma-ray sources. This approach for generating source representations using NMF allows for more accurate estimates of source contributions in gamma-ray spectra in the presence of source shielding, ultimately resulting in enhanced identification capabilities for shielded sources over methods that do not account for the effects of shielding. Likelihood ratio tests are performed using NMF-based spectral models for performing simultaneous detection and identification, and this paper introduces a method for analytically computing thresholds used in hypothesis testing. Performance of this method is characterized by injecting simulated source gamma-ray spectra into background spectra measured from a mobile detection system with six 2" × 4" × 16" NaI(Tl) scintillation detectors. Specifically, background spectra injected with 60Co and 137Cs shielded by 50 mm of steel show an improvement in detection performance over an NMF-based template matching identification approach that does not account for spectral variation due to source attenuation. The methods discussed here are general enough to be broadly applicable to gamma-ray spectroscopic analysis, and can be used in applications relying on template matching.
A splice site-sensing conformational switch in U2AF2 is modulated by U2AF1 and its recurrent myelodysplasia-associated mutation.

An essential heterodimer of the U2AF1 and U2AF2 pre-mRNA splicing factors nucleates spliceosome assembly at polypyrimidine (Py) signals preceding the major class of 3' splice sites. U2AF1 frequently acquires an S34F-encoding mutation among patients with myelodysplastic syndromes (MDS). The influence of the U2AF1 subunit and its S34F mutation on the U2AF2 conformations remains unknown. Here, we employ single molecule Forster resonance energy transfer (FRET) to determine the influence of wild-type or S34F-substituted U2AF1 on the conformational dynamics of U2AF2 and its splice site RNA complexes. In the absence of RNA, the U2AF1 subunit stabilizes a high FRET value, which by structure-guided mutagenesis corresponds to a closed conformation of the tandem U2AF2 RNA recognition motifs (RRMs). When the U2AF heterodimer is bound to a strong, uridine-rich splice site, U2AF2 switches to a lower FRET value characteristic of an open, side-by-side arrangement of the RRMs. Remarkably, the U2AF heterodimer binds weak, uridine-poor Py tracts as a mixture of closed and open U2AF2 conformations, which are modulated by the S34F mutation. Shifts between open and closed U2AF2 may underlie U2AF1-dependent splicing of degenerate Py tracts and contribute to a subset of S34F-dysregulated splicing events in MDS patients.
Nanostructured Materials for Hydrogen Storage

Hydrogen generated from clean and renewable energy sources has been considered as an alternate fuel to carbon based fossil fuels for several decades. Although many advances in hydrogen production and usage have been made, storing hydrogen remains a significant challenge. Many drawbacks including energy intensive processes, low volumetric densities, and safety concerns are associated with storing hydrogen as pressured or liquefied. Solid state hydrogen storage is considered to be the most promising method as a safe and effective storage option, but there is still no material or method that satisfies the requirements for a practical approach. A feasible hydrogen storage media should address several issues including targeted storage capacities, thermodynamics and hydrogen sorption kinetics, and safety. Nanostructured materials can provide tailor-made properties for storing and releasing hydrogen to fulfill, at least, the partial requirements. This short review, not a comprehensive review of all the materials or technologies in hydrogen storage, summarizes some of the recent developments in application of nanostructures for solid state hydrogen storage; particular attention has been devoted to the most recent development of nanocomposites with tuned dehydrogenation temperatures and kinetics through the control of pore size and surface chemistry.
The innervation of cerebral blood vessels by central noradrenergic neurons

Publisher Summary This chapter describes a study analyzing the innervation of cerebral blood vessels by central noradrenergic neurons. Bilateral superior cervical ganglionectomised rats and sham operated controls were examined using the immunofluoresence technique for dopamine-β-hydroxylase (DBH) localization. The brains were examined for 7 days, 14 days and 2 months after surgery. Sham operated controls showed the typical dense noradrenergic innervation of pial vessels. Bilateral ganglionectomy resulted in the disappearance of DBH-containing fibers on pial blood vessels. The absence of the sympathetic innervation throughout the pial system was used as the criterion of complete removal of both superior cervical ganglia. By 7 days all traces of the pial vessel innervation had disappeared and in no case was there any apparent regeneration of sympathetic fibers even after 2 months. Within the brain parenchyma, superior cervical ganglionectomy resulted in no detectable decrease in the presence of noradrenergic fibers or terminals associated with small arteries and arterioles. The chapter shows small vessels as observed in the brains of superior cervical ganglionectomised rats. Varicose DBH-containing fibers were seen in close association with these small vessels.
Comparing 10 Methods for Solution Verification, and Linking to Model Validation

Grid convergence is often assumed as a given during computational analyses involving discretization of an assumed continuum process. In practical use of finite difference and finite element analyses, perfect grid convergence is rarely achieved or assured, and this fact must be addressed to make statements about model validation or the use of models in risk analysis. We have previously provided a 4-step quantitative implementation for a quantitative V&V process. One of the steps in the 4-step process is that of Solution Verification. Solution Verification is the process of assuring that a model approximating a physical reality with a discretized continuum (e.g. finite element) code converges in each discretized domain to a converged answer on the quantity of subsequent validation interest. The modeling reality is that often we are modeling a problem with a discretized code because it is neither continuous spatially (e.g. contact and impact) nor smooth in relevant physics (e.g. shocks, melting, etc). The typical result is a non-monotonic convergence plot that can lead to spurious conclusions about the order of convergence, and a lack of means to estimate residual solution verification error or uncertainty at confidence. We compare ten techniques for grid convergence assessment, each formulated to enablemore » a quantification of solution verification uncertainty at confidence and order of convergence for monotonic and nonmonotonic mesh convergence studies. The more rigorous of these methods require a minimum of four grids in a grid convergence study to quantify the grid convergence uncertainty. The methods supply the quantitative terms for solution verification error and uncertainty estimates needed for inclusion into subsequent model validation, confidence, and reliability analyses. Naturally, most such methodologies are still evolving, and this work represents the views of the authors and not necessarily the views of Lawrence Livermore National Laboratory.« less
Unconstrained and constrained mode expansions for a flexible slewing link

On considere les equations lineaires du mouvement d'une liaison pivotante flexible, uniforme, qui sont obtenues grâce au principe etendu d'Hamilton
Cell Cycle-Dependent Interleukin 1 Gene Expression by Cultured Glomerular Mesangial Cells

Abstract Glomerular mesangial cell (MC)--derived IL-1 may be an important factor in the development of the hypercellularity and sclerosis characteristic of many forms of glomerulonephritis. To define the regulation of IL-1 synthesis by human MC, Northern blot analyses were performed using specific probes for monocytic IL-1 alpha and beta mRNA. Proliferating MC expressed mRNA for both IL-1 alpha and beta, whereas nonproliferating MC contained no detectable IL-1 mRNA. Synchronized MC expressed IL-1 alpha and beta mRNA within 2 h of stimulation with serum. This serum effect could be reproduced with platelet-derived growth factor and epidermal growth factor. Immune precipitations of 35S-methionine-labeled cells indicate that the mesangial IL-1 is synthesized as a 33-kD precursor protein with a pI of 7.2. Extracellular mesangial IL-1 has a pI of 7.0 and molecular weight of 17 kD, consistent with its identification as IL-1 beta. Cellular proliferation in glomerular disease may be driven in part by peptide growth factor-mediated induction of mesangial IL-1 gene expression and protein synthesis.
Sequence-directed curvature of DNA.

PERSPECTIVES AND OVERVIEW 756 General Perspective and Overview 756 Historical Perspective 757 THE RELATIONSHIP BETWEEN SEQUENCE AND CURVATURE 759 Investigations Employing Synthetic DNA Oligomers 759 Investigations Employing Base Analogues 760 Cooperativity and Sequence-Context Effects 762
MOLECULAR DYNAMICS OF CHEMICAL REACTIONS

Molecular beam and spectroscopic techniques allow detailed study of many dynamical properties of single reactive collisions. The chemical scope of these methods is now very wide and includes certain unimolecular and termolecular reactions as well as bimolecular reactions and energy transfer processes. Results for more than 50 families of A + BC → AB + C atom transfer reactions reveal simple impulsive and persistent complex regimes that correlate with electronic structure. Recent work has found examples of AB + CD → AD + BC and AB + CD + EF → AF + BC + DE reactions that require exchange of two or three pairs of bonds in a single collision event yet proceed with practically no activation energy. Processes akin to liquid phase reactions are also becoming accessible to dynamical studies using beams of van der Waals polymers or solvation clusters.
5 – Judicial Notice

Publisher Summary Judicial notice may be defined as the recognition and acceptance of certain facts that are reasonably undisputable that a judge, under the rules of evidentiary procedure, may properly take or act upon without proof, either because the facts noticed are indisputable as a matter of notorious common knowledge or because the facts noticed are capable of being immediately verified by consultation with standard reference works. Judicial notice is a method of dispensing with the necessity for taking proof and is intended to avoid the formal introduction of evidence in limited circumstances where the fact sought to be proved is so well known that evidence in support thereof is unnecessary. Judicial notice involves the acceptance as true of certain facts and laws without the necessity of introducing evidence. In using judicial notice as a substitute for evidence, courts are generally permitted to take judicial notice at a pretrial hearing, during a trial, and at the appellate stage of a criminal case. In taking judicial notice, what passes for common knowledge will vary with the geographic area where the court sits and does not necessarily depend upon the actual knowledge of the judge.
The legal and medical necessity of abortion care amid the COVID-19 pandemic

In response to the COVID-19 pandemic, states have ordered the cessation of non-essential healthcare. Unfortunately, many conservative states have sought to capitalize on those orders to halt abortion care. In this short paper, we argue that abortion should not fall under any state's non-essential healthcare order. Major medical organizations recognize that abortion is essential healthcare that must be provided even in a pandemic, and the law recognizes abortion as a time-sensitive constitutional right. Finally, we examine the constitutional arguments as to why enforcing these orders against abortion providers should not stand constitutional scrutiny. We conclude that no public health purpose can be served by this application because abortion uses less scarce resources and involves fewer contacts with healthcare professionals than prenatal care and delivery assistance, which is continuing to be provided in this public health emergency.
Sudden stops, sectoral reallocations, and the real exchange rate

Abstract A sudden stop of capital flows into a developing country tends to be followed by a rapid switch from trade deficits to surpluses, a depreciation of the real exchange rate, and decreases in output and total factor productivity. Substantial reallocation takes place from the nontraded sector to the traded sector. We construct a multisector growth model, calibrate it to the Mexican economy, and use it to analyze Mexico's 1994–95 crisis. When subjected to a sudden stop, the model accounts for the trade balance reversal and the real exchange rate depreciation, but it cannot account for the decreases in GDP and TFP. Extending the model to include labor frictions and variable capital utilization, we still find that it cannot quantitatively account for the dynamics of output and productivity without losing the ability to account for the movements of other variables.
SilhoNet-Fisheye: Adaptation of A ROI Based Object Pose Estimation Network to Monocular Fisheye Images

There has been much recent interest in deep learning methods for monocular image based object pose estimation. While object pose estimation is an important problem for autonomous robot interaction with the physical world, and the application space for monocular-based methods is expansive, there has been little work on applying these methods with fisheye imaging systems. Also, little exists in the way of annotated fisheye image datasets on which these methods can be developed and tested. The research landscape is even more sparse for object detection methods applied in the underwater domain, fisheye image based or otherwise. In this work, we present a novel framework for adapting a ROI-based 6D object pose estimation method to work on full fisheye images. The method incorporates the gnomic projection of regions of interest from an intermediate spherical image representation to correct for the fisheye distortions. Further, we contribute a fisheye image dataset, called UWHandles, collected in natural underwater environments, with 6D object pose and 2D bounding box annotations.
Estimating and accounting for unobserved covariates in high dimensional correlated data

Many high-dimensional and high-throughput biological datasets have complex sample correlation structures, which include longitudinal and multiple tissue data, as well as data with multiple treatmen...
Moment maps, strict linear precision, and maximum likelihood degree one

Abstract We study the moment maps of a smooth projective toric variety. In particular, we characterize when the moment map coming from the quotient construction is equal to a weighted Fubini-Study moment map. This leads to an investigation into polytopes with strict linear precision, and in the process we use results from and find remarkable connections between Symplectic Geometry, Geometric Modeling, Algebraic Statistics, and Algebraic Geometry.
Boomerang: Real-Time I/O Meets Legacy Systems

This paper presents Boomerang, an I/O system that integrates a legacy non-real-time OS with one that is customized for timing-sensitive tasks. A relatively small RTOS benefits from the pre-existing libraries, drivers and services of the legacy system. Additionally, timing-critical tasks are isolated from less critical tasks by securely partitioning machine resources among the separate OSes. Boomerang guarantees end-to-end processing delays on input data that requires outputs to be generated within specific time bounds.We show how to construct composable task pipelines in Boomerang that combine functionality spanning a custom RTOS and a legacy Linux system. By dedicating time-critical I/O to the RTOS, we ensure that complementary services provided by Linux are sufficiently predictable to meet end-to-end service guarantees. While Boomerang benefits from spatial isolation, it also outperforms a standalone Linux system using deadline-based CPU reservations for pipeline tasks. We also show how Boomerang outperforms a virtualized system called ACRN, designed for automotive systems.
Emergence of Separable Manifolds in Deep Language Representations

Deep neural networks (DNNs) have shown much empirical success in solving perceptual tasks across various cognitive modalities. While they are only loosely inspired by the biological brain, recent studies report considerable similarities between representations extracted from task-optimized DNNs and neural populations in the brain. DNNs have subsequently become a popular model class to infer computational principles underlying complex cognitive functions, and in turn, they have also emerged as a natural testbed for applying methods originally developed to probe information in neural populations. In this work, we utilize mean-field theoretic manifold analysis, a recent technique from computational neuroscience that connects geometry of feature representations with linear separability of classes, to analyze language representations from large-scale contextual embedding models. We explore representations from different model families (BERT, RoBERTa, GPT, etc.) and find evidence for emergence of linguistic manifolds across layer depth (e.g., manifolds for part-of-speech tags), especially in ambiguous data (i.e, words with multiple part-of-speech tags, or part-of-speech classes including many words). In addition, we find that the emergence of linear separability in these manifolds is driven by a combined reduction of manifolds' radius, dimensionality and inter-manifold correlations.
Inferring Degrees from Incomplete Networks and Nonlinear Dynamics

Inferring topological characteristics of complex networks from observed data is critical to understand the dynamical behavior of networked systems, ranging from the Internet and the World Wide Web to biological networks and social networks. Prior studies usually focus on the structure-based estimation to infer network sizes, degree distributions, average degrees, and more. Little effort attempted to estimate the specific degree of each vertex from a sampled induced graph, which prevents us from measuring the lethality of nodes in protein networks and influencers in social networks. The current approaches dramatically fail for a tiny sampled induced graph and require a specific sampling method and a large sample size. These approaches neglect information of the vertex state, representing the dynamical behavior of the networked system, such as the biomass of species or expression of a gene, which is useful for degree estimation. We fill this gap by developing a framework to infer individual vertex degrees using both information of the sampled topology and vertex state. We combine the mean-field theory with combinatorial optimization to learn vertex degrees. Experimental results on real networks with a variety of dynamics demonstrate that our framework can produce reliable degree estimates and dramatically improve existing link prediction methods by replacing the sampled degrees with our estimated degrees.
How Useful Is Self-Supervised Pretraining for Visual Tasks?

Recent advances have spurred incredible progress in self-supervised pretraining for vision. We investigate what factors may play a role in the utility of these pretraining methods for practitioners. To do this, we evaluate various self-supervised algorithms across a comprehensive array of synthetic datasets and downstream tasks. We prepare a suite of synthetic data that enables an endless supply of annotated images as well as full control over dataset difficulty. Our experiments offer insights into how the utility of self-supervision changes as the number of available labels grows as well as how the utility changes as a function of the downstream task and the properties of the training data. We also find that linear evaluation does not correlate with finetuning performance. Code and data is available at \href{https://www.github.com/princeton-vl/selfstudy}{github.com/princeton-vl/selfstudy}.
On the expected runtime of multiple testing algorithms with bounded error

Abstract Consider testing multiple hypotheses in the setting where the p-values of all hypotheses are unknown and thus have to be approximated using Monte Carlo simulations. One class of algorithms published in the literature for this scenario provides guarantees on the correctness of their testing result through the computation of confidence statements on all approximated p-values. This article focuses on the expected runtime of such algorithms and derives a variety of finite and infinite expected runtime results.
Thermodynamics of the N = 2* flow

We discuss the thermodynamics of theN = 2 ⁄ , SU(N) gauge theory at large 't Hooft coupling. The tool we use is the non-extremal deformation of the supergravity solution of Pilch and Warner (PW) (13), dual to N = 4, SU(N) gauge theory softly broken toN = 2. We construct the exact non-extremal solution in flve-dimensional gauged supergravity and further uplift it to ten dimensions. Turning to the thermodynamics, we analytically compute the leading correction in m=T to the free energy of the non- extremal D3 branes due to the PW mass deformation, and flnd that it is positive. We also demonstrate that the mass deformation of the non-extremal D3 brane geometry induces a temperature dependent gaugino condensate. We flnd that the standard procedure of extracting theN = 2 ⁄ gauge theory thermodynamic quantities from the dual supergravity leads to a violation of the flrst law of thermodynamics. We speculate on a possible resolution of this paradox.
The revival of large consulting practices at the Big 4 and audit quality

Abstract The Big 4 have acquired numerous consulting firms since the late 2000s, and regulators are concerned that a focus on consulting practices could negatively affect audit quality through audit firm culture. Audit firms counter by arguing that expertise gained through consulting can improve knowledge brought to audits. Using a difference-in-differences design, restatements as an audit quality proxy, and enterprise resource planning- (non-enterprise resource planning-) related acquisitions as a proxy for audit- (non-audit-) related acquisitions, we find nuanced support for both positions, depending on acquisition type. Audit quality increases (decreases) at the local office level after the acquisition of consulting firms that provide services that relate (do not relate) to the audit. Semi-structured interviews of 17 highly-experienced audit practitioners suggest that consulting firm acquisitions positively (negatively) affect audit quality through expertise transfer (shifting the culture towards commercialism) when acquisitions are (are not) audit-related. Thus, the effect of consulting firm acquisitions on audit quality appears to depend on how closely the acquired services are related to the audit.
Learning Agile Robotic Locomotion Skills by Imitating Animals

Reproducing the diverse and agile locomotion skills of animals has been a longstanding challenge in robotics. While manually-designed controllers have been able to emulate many complex behaviors, building such controllers involves a time-consuming and difficult development process, often requiring substantial expertise of the nuances of each skill. Reinforcement learning provides an appealing alternative for automating the manual effort involved in the development of controllers. However, designing learning objectives that elicit the desired behaviors from an agent can also require a great deal of skill-specific expertise. In this work, we present an imitation learning system that enables legged robots to learn agile locomotion skills by imitating real-world animals. We show that by leveraging reference motion data, a single learning-based approach is able to automatically synthesize controllers for a diverse repertoire behaviors for legged robots. By incorporating sample efficient domain adaptation techniques into the training process, our system is able to learn adaptive policies in simulation that can then be quickly adapted for real-world deployment. To demonstrate the effectiveness of our system, we train an 18-DoF quadruped robot to perform a variety of agile behaviors ranging from different locomotion gaits to dynamic hops and turns.
Optimization of partial search

A quantum Grover search algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster; this is partial search. A partial search algorithm was recently suggested by Grover and Radhakrishnan. Here we optimize it. Efficiency of the search algorithm is measured by the number of queries to the oracle. The author suggests a new version of the Grover–Radhakrishnan algorithm which uses a minimal number of such queries. The algorithm can run on the same hardware that is used for the usual Grover algorithm.
Mandated Bacillus Calmette-Guérin (BCG) vaccination predicts flattened curves for the spread of COVID-19.

Bacillus Calmette-Guerin (BCG) vaccination may reduce the risk of a range of infectious diseases, and if so, it could protect against coronavirus disease 2019 (COVID-19). Here, we compared countries that mandated BCG vaccination until at least 2000 with countries that did not. To minimize any systematic effects of reporting biases, we analyzed the rate of the day-by-day increase in both confirmed cases (134 countries) and deaths (135 countries) in the first 30-day period of country-wise outbreaks. The 30-day window was adjusted to begin at the country-wise onset of the pandemic. Linear mixed models revealed a significant effect of mandated BCG policies on the growth rate of both cases and deaths after controlling for median age, gross domestic product per capita, population density, population size, net migration rate, and various cultural dimensions (e.g., individualism). Our analysis suggests that mandated BCG vaccination can be effective in the fight against COVID-19.
Identifying Unused RF Channels Using Least Matching Pursuit

Cognitive radio aims at identifying unused radio-frequency (RF) bands with the goal of re-using them opportunistically for other services. While compressive sensing (CS) has been used to identify strong signals (or interferers) in the RF spectrum from sub-Nyquist measurements, identifying unused frequencies from CS measurements appears to be uncharted territory. In this paper, we propose a novel method for identifying unused RF bands using an algorithm we call least matching pursuit (LMP). We present a sufficient condition for which LMP is guaranteed to identify unused frequency bands and develop an improved algorithm that is inspired by our theoretical result. We perform simulations for a CS-based RF whitespace detection task in order to demonstrate that LMP is able to outperform black-box approaches that build on deep neural networks.
Adverse Selection in the Marriage Market: HIV Testing and Marriage in Rural Malawi

Asymmetric information in the marriage market may cause adverse selection and delay marriage if partner quality is revealed over time. Sexual safety is an important but hidden partner attribute, especially in areas where HIV is endemic. A model of positive assortative matching with both observable (attractiveness) and hidden (sexual safety) attributes predicts that removing the asymmetric information about sexual safety accelerates marriage and pregnancy for safe respondents, and more so if they are also attractive. Frequent HIV testing may enable safe people to signal and screen. Consistent with these predictions, we show that a high-frequency, "opt-out" HIV testing intervention changed beliefs about partner's safety and accelerated marriage and pregnancy, increasing the probabilities of marriage and pregnancy by 26 and 27 percent for baseline-unmarried women over 28 months. Estimates are larger for safe and attractive respondents. Conversely, a single-test intervention lacks these effects, consistent with other HIV testing evaluations in the literature. Our findings suggest that an endogenous response to HIV risk may explain why the HIV/AIDS epidemic has coincided with systematic marriage and pregnancy delays.
Optical characteristics of young quasars as sources of the cosmic X-ray background

The sources which dominate the thermal cosmic X-ray background cannot have X-ray spectra similar to the power laws measured for bright active galactic nuclei. The optical consequences of this disparity are pursued by considering a standard model for the photoexcitation and heating of the line-emitting gas surrounding a central source (e.g., such as a quasar). The optical line emission to be associated with compact young quasar sources having the same X-ray spectrum as the X-ray background is found to be substantially different from that characteristic of typical quasars. Implications on quasar source counts and the identification of such new objects are discussed.
Monetary Policy and Domestic Investment in Nigeria: The Role of the Inflation Rate

Economic theory suggests that monetary policy can be used to stabilize an economy. However, the ability of monetary policy targets—interest rates and money supply—to stabilize an economy depends on their ability to achieve price stability. Using data from 1981 to 2018 and applying the vector error correction model, this paper seeks to determine how the changes in the inflation rate affect the ability of monetary policy tools to stabilize the Nigerian economy and stimulate investment. Empirical results suggest that the impact of the interest rates on investment depends on the level of the inflation rate. The size of the effect of interest rates on investment gets weaker as the inflation rate increases suggesting that monetary policy tools, such as the monetary policy rate (MPR), that directly change the interest rates are robust stabilization tools during periods of declining inflation rates but not relevant during periods of rising inflation rates. This is attributable to low bank lending rates. Additionally, the impact of the money supply target on investment does not depend on the level of the inflation rate. This suggests that monetary policy tools, such as open market operations, that directly change the money supply can be relevant stabilization tools during economic booms and recessions. As a result, the Central Bank of Nigeria should work to deepen the scale, capacity, and efficiency of its open market operations by ensuring that most of the people can participate with minimal transaction cost and by making different financial instruments available.
Short-termism, Managerial Talent, and Firm Value

This paper examines how the firm's choice of investment horizon interacts with rent-seeking by privately-informed, multi-tasking managers and the labor market. There are two main results. First, managers prefer longer-horizon projects that permit them to extract higher rents from firms, so short-termism involves lower agency costs and is value-maximizing for some firms. Second, when firms compete for managers, firms practicing short-termism attract better managerial talent when talent is unobservable, but larger firms that invest in long-horizon projects hire more talented managers when talent is revealed.
Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds

Human modification of landscapes includes extensive addition of linear features, such as roads and transmission lines. These can alter animal movement and space use and affect the intensity of interactions among species, including predation and competition. Effects of linear features on animal movement have seen relatively little research in avian systems, despite ample evidence of their effects in mammalian systems and that some types of linear features, including both roads and transmission lines, are substantial sources of mortality. Here, we used satellite telemetry combined with step selection functions designed to explicitly incorporate the energy landscape (el-SSFs) to investigate the effects of linear features and habitat on movements and space use of a large soaring bird, the golden eagle Aquila chrysaetos, during migration. Our sample consisted of 32 adult eagles tracked for 45 spring and 39 fall migrations from 2014 to 2017. Fitted el-SSFs indicated eagles had a strong general preference for south-facing slopes, where thermal uplift develops predictably, and that these areas are likely important aspects of migratory pathways. el-SSFs also provided evidence that roads and railroads affected movement during both spring and fall migrations, but eagles selected areas near roads to a greater degree in spring compared to fall and at higher latitudes compared to lower latitudes. During spring, time spent near linear features often occurred during slower-paced or stopover movements, perhaps in part to access carrion produced by vehicle collisions. Regardless of the behavioural mechanism of selection, use of these features could expose eagles and other soaring species to elevated risk via collision with vehicles and/or transmission lines. Linear features have previously been documented to affect the ecology of terrestrial species (e.g. large mammals) by modifying individuals' movement patterns; our work shows that these effects on movement extend to avian taxa.
Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics.

Summary Transcriptome-wide association studies (TWASs) have been widely used to integrate gene expression and genetic data for studying complex traits. Due to the computational burden, existing TWAS methods do not assess distant trans-expression quantitative trait loci (eQTL) that are known to explain important expression variation for most genes. We propose a Bayesian genome-wide TWAS (BGW-TWAS) method that leverages both cis- and trans-eQTL information for a TWAS. Our BGW-TWAS method is based on Bayesian variable selection regression, which not only accounts for cis- and trans-eQTL of the target gene but also enables efficient computation by using summary statistics from standard eQTL analyses. Our simulation studies illustrated that BGW-TWASs achieved higher power compared to existing TWAS methods that do not assess trans-eQTL information. We further applied BWG-TWAS to individual-level GWAS data (N = ∼3.3K), which identified significant associations between the genetically regulated gene expression (GReX) of ZC3H12B and Alzheimer dementia (AD) (p value = 5.42 × 10−13), neurofibrillary tangle density (p value = 1.89 × 10−6), and global measure of AD pathology (p value = 9.59 × 10−7). These associations for ZC3H12B were completely driven by trans-eQTL. Additionally, the GReX of KCTD12 was found to be significantly associated with β -amyloid (p value = 3.44 × 10−8) which was driven by both cis- and trans-eQTL. Four of the top driven trans-eQTL of ZC3H12B are located within APOC1, a known major risk gene of AD and blood lipids. Additionally, by applying BGW-TWAS with summary-level GWAS data of AD (N = ∼54K), we identified 13 significant genes including known GWAS risk genes HLA-DRB1 and APOC1, as well as ZC3H12B.
On Ergodic Embeddings of Factors

An inclusion of von Neumann factors $$M \subset \mathcal {M}$$ is ergodic if it satisfies the irreducibility condition $$M'\cap \mathcal {M}=\mathbb {C}$$ . We investigate the relation between this and several stronger ergodicity properties, such as R-ergodicity, which requires M to admit an embedding of the hyperfinite II $$_1$$ factor $$R\hookrightarrow M$$ that’s ergodic in $$\mathcal {M}$$ . We prove that if M is continuous (i.e., non type I) and contains a maximal abelian $$^*$$ -subalgebra of $$\mathcal {M}$$ , then $$M\subset \mathcal {M}$$ is R-ergodic. This shows in particular that any continuous factor contains an ergodic copy of R.
The Role of Coded Side Information in Single-Server Private Information Retrieval

We study the role of coded side information in single-server Private Information Retrieval (PIR). An instance of the single-server PIR problem includes a server that stores a database of $K$ independently and uniformly distributed messages, and a user who wants to retrieve one of these messages from the server. We consider settings in which the user initially has access to a coded side information which includes a linear combination of a subset of $M$ messages in the database. We assume that the identities of the $M$ messages that form the support set of the coded side information as well as the coding coefficients are initially unknown to the server. We consider two different models, depending on whether the support set of the coded side information includes the requested message or not. We also consider the following two privacy requirements: (i) the identities of both the demand and the support set of the coded side information need to be protected, or (ii) only the identity of the demand needs to be protected. For each model and for each of the privacy requirements, we consider the problem of designing a protocol for generating the user’s query and the server’s answer that enables the user to decode the message they need while satisfying the privacy requirement. We characterize the (scalar-linear) capacity of each setting, defined as the ratio of the number of information bits in a message to the minimum number of information bits downloaded from the server over all (scalar-linear) protocols that satisfy the privacy condition. Our converse proofs rely on new information-theoretic arguments—tailored to the setting of single-server PIR and different from the commonly-used techniques in multi-server PIR settings. We also present novel capacity-achieving scalar-linear protocols for each of the settings being considered.
Typical dynamics and fluctuation analysis of slow–fast systems driven by fractional Brownian motion

This paper studies typical dynamics and fluctuations for a slow–fast dynamical system perturbed by a small fractional Brownian noise. Based on an ergodic theorem with explicit rates of convergence,...
A mobile sex-determining region, male-specific haplotypes and rearing environment influence age at maturity in Chinook salmon.

Variation in age at maturity is an important contributor to life history and demographic variation within and among species. The optimal age at maturity can vary by sex, and the ability of each sex to evolve towards its fitness optimum depends on the genetic architecture of maturation. Using GWAS of RAD sequencing data, we show that age at maturity in Chinook salmon exhibits sex-specific genetic architecture, with age at maturity in males influenced by large (up to 20 Mb) male-specific haplotypes. These regions showed no such effect in females. We also provide evidence for translocation of the sex-determining gene between two different chromosomes. This has important implications for sexually antagonistic selection, particularly that sex linkage of adaptive genes may differ within and among populations based on chromosomal location of the sex-determining gene. Our findings will facilitate research into the genetic causes of shifting demography in Chinook salmon as well as a better understanding of sex determination in this species and Pacific salmon in general.