cssi/SciSciGPT-SciSciNet huggingface dataset:
A Mathematical Framework for Exact Milestoning

We give a mathematical framework for exact milestoning, a recently introduced algorithm for mapping a continuous time stochastic process into a Markov chain or semi-Markov process that can be efficiently simulated and analyzed. We generalize the setting of exact milestoning and give explicit error bounds for the error in the milestoning equation for mean first passage times.
Anti De Sitter Deformation of Quaternionic Analysis and the Second Order Pole

This is a continuation of a series of papers [FL1, FL2, FL3], where we develop quaternionic analysis from the point of view of representation theory of the conformal Lie group and its Lie algebra. In this paper we continue to study the quaternionic analogues of Cauchy’s formula for the second order pole. These quaternionic analogues are closely related to regularization of infinities of vacuum polarization diagrams in four-dimensional quantum field theory. In order to add some flexibility, especially when dealing with Cauchy’s formula for the second order pole, we introduce a one-parameter deformation of quaternionic analysis. This deformation of quaternions preserves conformal invariance and has a geometric realization as anti de Sitter space sitting inside the five-dimensional Euclidean space. We show that many results of quaternionic analysis – including the Cauchy-Fueter formula – admit a simple and canonical deformation. We conclude this paper with a deformation of the quaternionic analogues of Cauchy’s formula for the second order pole.
Joint Person Segmentation and Identification in Synchronized First- and Third-Person Videos

In a world of pervasive cameras, public spaces are often captured from multiple perspectives by cameras of different types, both fixed and mobile. An important problem is to organize these heterogeneous collections of videos by finding connections between them, such as identifying correspondences between the people appearing in the videos and the people holding or wearing the cameras. In this paper, we wish to solve two specific problems: (1) given two or more synchronized third-person videos of a scene, produce a pixel-level segmentation of each visible person and identify corresponding people across different views (i.e., determine who in camera A corresponds with whom in camera B), and (2) given one or more synchronized third-person videos as well as a first-person video taken by a mobile or wearable camera, segment and identify the camera wearer in the third-person videos. Unlike previous work which requires ground truth bounding boxes to estimate the correspondences, we perform person segmentation and identification jointly. We find that solving these two problems simultaneously is mutually beneficial, because better fine-grained segmentation allows us to better perform matching across views, and information from multiple views helps us perform more accurate segmentation. We evaluate our approach on two challenging datasets of interacting people captured from multiple wearable cameras, and show that our proposed method performs significantly better than the state-of-the-art on both person segmentation and identification.
The ISO problem: Decentralized stochastic control via bidding schemes

We consider a smart-grid connecting several agents, modeled as stochastic dynamical systems, who may be electricity consumers/producers. At each discrete time instant, which may represent a 15 minute interval, each agent may consume/generate some quantity of electrical energy. The Independent System Operator (ISO) is given the task of assigning consumptions/generations to the agents so as to maximize the sum of the utilities accrued to the agents, subject to the constraint that energy generation equals consumption at each time.
Continuous Time Multi-Stage Stochastic Reserve and Unit Commitment

In this paper we introduce a continuous time multi stage stochastic optimization for scheduling generating units, their commitment, reserve capacities and their continuous time generation profiles in the day-ahead wholesale electricity market. Our formulation approximates the solution of a variational problem, in which the balance, generation capacity and ramping constraints are in continuous time. Due to the greater accuracy of our representation of ramping events this approach improves the system reliability and lowers the real-time cost.
Decomposing GR(1) games with singleton liveness guarantees for efficient synthesis

Temporal logic based synthesis approaches are often used to find trajectories that are correct-by-construction for systems with complex behavior. However, the scalability of such approaches is of concern and at times a bottleneck when transitioning from theory to practice. In this paper, we identify a class of problems in the GR(1) fragment of linear-time temporal logic (LTL) where the synthesis problem allows for a decomposition that enables easy parallelization. This decomposition also reduces the alternation depth, resulting in more efficient synthesis. A multi-agent robot gridworld example with coordination tasks is presented to demonstrate the application of the developed ideas and also to perform empirical analysis for benchmarking the decomposition-based synthesis approach.
Deep Tree Learning for Zero-Shot Face Anti-Spoofing

Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types of spoof attacks are also being created and becoming a threat to all existing systems. We define the detection of unknown spoof attacks as Zero-Shot Face Anti-spoofing (ZSFA). Previous works of ZSFA only study 1-2 types of spoof attacks, such as print/replay attacks, which limits the insight of this problem. In this work, we expand the ZSFA problem to a wide range of 13 types of spoof attacks, including print attack, replay attack, 3D mask attacks, and so on. A novel Deep Tree Network (DTN) is proposed to tackle the ZSFA. The tree is learned to partition the spoof samples into semantic sub-groups in an unsupervised fashion. When a data sample arrives, being know or unknown attacks, DTN routes it to the most similar spoof cluster, and make the binary decision. In addition, to enable the study of ZSFA, we introduce the first face anti-spoofing database that contains diverse types of spoof attacks. Experiments show that our proposed method achieves the state of the art on multiple testing protocols of ZSFA.
Effect of 60∘ dislocation on transformation stresses, nucleation, and growth for phase transformations between silicon I and silicon II under triaxial loading: Phase-field study

Abstract Stress-induced martensitic phase transformations (PTs) at a stationary 60 ∘ dislocation in single-crystalline Si are modeled by an advanced phase-field approach (PFA), which takes into account the lattice instability conditions obtained by atomistic simulations for the general stress tensor. Finite elastic, transformation, and plastic strains are considered. Finite element method (FEM) simulations elucidate two different mechanisms of nucleation and nanostructure evolution for two different stress-hysteresis cases. For a traditional finite-stress-hysteresis region, the PT starts with the barrierless nucleation of a thermodynamically-equilibrium-incomplete embryo, which loses its stability and grows forming a propagating martensitic band with distinct interfaces. However, in the unique zero-stress-hysteresis region, where PT for defect-free crystal occurs homogeneously through intermediate phases without nucleation, interfaces, and growth, the PT starts at a dislocation but spreads quasi-homogeneously, without interfaces, similar to the defect-free case; the macroscopic stress-strain curve is horizontal and without hysteresis during direct-reverse PTs. Despite large normal stresses produced by dislocation in the range of ± ( 6 − 12 ) GPa, a relatively small reduction in macroscopic PT stress by 1.6 GPa is quantitatively explained by mutually compensating contributions of stresses into lattice instability criterion.
The fractional chromatic number of the plane

The chromatic number of the plane is the chromatic number of the uncountably infinite graph that has as its vertices the points of the plane and has an edge between two points if their distance is 1. This chromatic number is denoted χ(ℝ2). The problem was introduced in 1950, and shortly thereafter it was proved that 4≤χ(ℝ2)χ≤7. These bounds are both easy to prove, but after more than 60 years they are still the best known. In this paper, we investigate χ f (ℝ2), the fractional chromatic number of the plane. The previous best bounds (rounded to five decimal places) were 3.5556≤χ f (ℝ2)≤4.3599. Here we improve the lower bound to 76/21≈3.6190.
Unique factorization and controllability of tail-biting trellis realizations via controller granule decompositions

The Conti-Boston factorization theorem (CBFT) for linear tail-biting trellis realizations is extended to group realizations with a new and simpler proof, based on a controller granule decomposition of the behavior and known controllability results for group realizations. Further controllability results are given; e.g., a trellis realization is controllable if and only if its top (controllability) granule is trivial.
Joint Multi-person Pose Estimation and Semantic Part Segmentation

Human pose estimation and semantic part segmentation are two complementary tasks in computer vision. In this paper, we propose to solve the two tasks jointly for natural multi-person images, in which the estimated pose provides object-level shape prior to regularize part segments while the part-level segments constrain the variation of pose locations. Specifically, we first train two fully convolutional neural networks (FCNs), namely Pose FCN and Part FCN, to provide initial estimation of pose joint potential and semantic part potential. Then, to refine pose joint location, the two types of potentials are fused with a fully-connected conditional random field (FCRF), where a novel segment-joint smoothness term is used to encourage semantic and spatial consistency between parts and joints. To refine part segments, the refined pose and the original part potential are integrated through a Part FCN, where the skeleton feature from pose serves as additional regularization cues for part segments. Finally, to reduce the complexity of the FCRF, we induce human detection boxes and infer the graph inside each box, making the inference forty times faster. Since theres no dataset that contains both part segments and pose labels, we extend the PASCAL VOC part dataset [6] with human pose joints and perform extensive experiments to compare our method against several most recent strategies. We show that our algorithm surpasses competing methods by 10.6% in pose estimation with much faster speed and by 1.5% in semantic part segmentation.
Semantic Adversarial Examples

Deep neural networks are known to be vulnerable to adversarial examples, i.e., images that are maliciously perturbed to fool the model. Generating adversarial examples has been mostly limited to finding small perturbations that maximize the model prediction error. Such images, however, contain artificial perturbations that make them somewhat distinguishable from natural images. This property is used by several defense methods to counter adversarial examples by applying denoising filters or training the model to be robust to small perturbations. In this paper, we introduce a new class of adversarial examples, namely "Semantic Adversarial Examples," as images that are arbitrarily perturbed to fool the model, but in such a way that the modified image semantically represents the same object as the original image. We formulate the problem of generating such images as a constrained optimization problem and develop an adversarial transformation based on the shape bias property of human cognitive system. In our method, we generate adversarial images by first converting the RGB image into the HSV (Hue, Saturation and Value) color space and then randomly shifting the Hue and Saturation components, while keeping the Value component the same. Our experimental results on CIFAR10 dataset show that the accuracy of VGG16 network on adversarial color-shifted images is 5.7%.
Lipschitz functions of perturbed operators

Abstract We prove that if f is a Lipschitz function on R , and A and B are self-adjoint operators such that rank ( A − B ) = 1 , then f ( A ) − f ( B ) belongs to the weak space S 1 , ∞ , i.e., s j ( A − B ) ⩽ const ( 1 + j ) − 1 . We deduce from this result that if A − B belongs to the trace class S 1 and f is Lipschitz, then f ( A ) − f ( B ) ∈ S Ω , i.e., ∑ j = 0 n s j ( f ( A ) − f ( B ) ) ⩽ const log ( 2 + n ) . We also obtain more general results about the behavior of double operator integrals of the form Q = ∫ ∫ ( f ( x ) − f ( y ) ) ( x − y ) − 1 d E 1 ( x ) T d E 2 ( y ) , where E 1 and E 2 are spectral measures. We show that if T ∈ S 1 , then Q ∈ S Ω and if rank T = 1 , then Q ∈ S 1 , ∞ . Finally, if T belongs to the Matsaev ideal S ω , then Q is a compact operator. To cite this article: F. Nazarov, V. Peller, C. R. Acad. Sci. Paris, Ser. I 347 (2009).
A Theory of Minimal $K$-Types for Flat $G$-Bundles

The theory of minimal K-types for p-adic reductive groups was developed in part to classify irreducible admissible representations with wild ramification. An important observation was that minimal K-types associated to such representations correspond to fundamental strata. These latter objects are triples (x, r, β), where x is a point in the Bruhat-Tits building of the reductive group G, r is a nonnegative real number, and β is a semistable functional on the degree r associated graded piece of the Moy-Prasad filtration
Sherlock: Scalable Fact Learning in Images

We study scalable and uniform understanding of facts in images. Existing visual recognition systems are typically modeled differently for each fact type such as objects, actions, and interactions. We propose a setting where all these facts can be modeled simultaneously with a capacity to understand an unbounded number of facts in a structured way. The training data comes as structured facts in images, including (1) objects (e.g., ), (2) attributes (e.g., ), (3) actions (e.g., ), and (4) interactions (e.g., ). Each fact has a semantic language view (e.g., ) and a visual view (an image with this fact). We show that learning visual facts in a structured way enables not only a uniform but also generalizable visual understanding. We propose and investigate recent and strong approaches from the multiview learning literature and also introduce two learning representation models as potential baselines. We applied the investigated methods on several datasets that we augmented with structured facts and a large scale dataset of more than 202,000 facts and 814,000 images. Our experiments show the advantage of relating facts by the structure by the proposed models compared to the designed baselines on bidirectional fact retrieval.
Blow-Up Results for Space-Time Fractional Stochastic Partial Differential Equations

Consider non-linear time-fractional stochastic reaction-diffusion equations of the following type, $$ \partial^{\beta}_{t}u_{t}(x)=-\nu(-{\Delta})^{\alpha/2} u_{t}(x)+I^{1-\beta}[b(u)+ \sigma(u)\stackrel{\cdot}{F}(t,x)] $$ in (d + 1) dimensions, where ν > 0,β ∈ (0, 1), α ∈ (0, 2]. The operator $\partial ^{\beta }_{t}$ is the Caputo fractional derivative while − (−Δ)α/2 is the generator of an isotropic α-stable Levy process and I1−β is the Riesz fractional integral operator. The forcing noise denoted by $\stackrel {\cdot }{F}(t,x)$ is a Gaussian noise. These equations might be used as a model for materials with random thermal memory. We derive non-existence (blow-up) of global random field solutions under some additional conditions, most notably on b, σ and the initial condition. Our results complement those of P. Chow in (Commun. Stoch. Anal. 3(2):211–222, 2009), Chow (J. Differential Equations 250(5):2567–2580, 2011), and Foondun et al. in (2016), Foondun and Parshad (Proc. Amer. Math. Soc. 143(9):4085–4094, 2015) among others.
Multi-objective compositions for collision-free connectivity maintenance in teams of mobile robots

Compositional barrier functions are proposed in this paper to systematically compose multiple objectives for teams of mobile robots. The objectives are first encoded as barrier functions, and then composed using AND and OR logical operators. The advantage of this approach is that compositional barrier functions can provably guarantee the simultaneous satisfaction of all composed objectives. The compositional barrier functions are applied to the example of ensuring collision avoidance and static/dynamical graph connectivity of teams of mobile robots. The resulting composite safety and connectivity barrier certificates are verified experimentally on a team of four mobile robots.
The White Dwarf Companions of Recycled Pulsars

I review what properties of the white-dwarf companions of recycled pulsars can be inferred from optical observations, and discuss how these can help us understand the characteristics and evolution of these binaries. I focus on spectroscopic observations, describing results obtained recently, and looking forward to what may come.
Satisfiability modulo ODEs

We study SMT problems over the reals containing ordinary differential equations,. They are important for formal verification of realistic hybrid systems and embedded software. We develop δ-complete algorithms for SMT formulas that are purely existentially quantified, as well as ∃∀-formulas whose universal quantification is restricted to the time variables. We demonstrate scalability of the algorithms, as implemented in our open-source solver dReal, on SMT benchmarks with several hundred nonlinear ODEs and variables.
Spectral Filtering for General Linear Dynamical Systems

We give a polynomial-time algorithm for learning latent-state linear dynamical systems without system identification, and without assumptions on the spectral radius of the system's transition matrix. The algorithm extends the recently introduced technique of spectral filtering, previously applied only to systems with a symmetric transition matrix, using a novel convex relaxation to allow for the efficient identification of phases.
The Role of Trust in Information Processing: Evidence from Security Analysts

Does an equity analyst's trust in others impact the processing of information from outside sources? We investigate this question using a measure of trust based on surveys conducted in analysts' cou...
A GLIMPSE OF THE PEOPLE OF ALTICA: OSTEOLOGICAL AND ISOTOPIC/RADIOCARBON ANALYSIS

Altica is a rare first-farming village site in the Basin of Mexico that has survived to modern times. Thus, it provides a glimpse into life during the Early–Middle Formative period. While valuable archaeological information on the village was recovered in excavation, only four burials comprising four individuals were recovered, a very small sample. Two individuals are older-aged females; the third, a middle-aged male, was accompanied by prestigious nonperishable goods and indicates that there are status differences even at this early date. The final individual was a young male buried in a deviant manner, suggesting possible foul play. While all individuals have indicators of periods of poor health, stable isotopes of carbon and nitrogen paint a more complete picture of the types of foods these individuals consumed over their lifetime. Radiogenic strontium isotopes of tooth enamel identify one individual, the young male buried in a deviant manner, as non-native to the Altica region. Thus, there is mystery in the manner of death, but even in this small sample, the wider connections Altica had that are so evident in the artefactual analysis are found in the skeletons. In addition, accelerator mass spectrometry radiocarbon dating provides a chronology of occupation through the people.
Merger signatures in low excitation radio galaxies

While no consensus governs our understanding of the origin of low redshift radio galaxies, the possibility that mergers may trigger accretion from hot cluster halo gas has spurred a recent search for such signatures. Evidence for mergers is at best tenuous, however, and even when found, generates more questions than answers. With scant evidence for minor mergers, some connection to major mergers is found in isolated environments but not where one would expect, i.e. in clusters. We provide an explanation for these recent results by Gordon et al (2019) on the relevance of major mergers in low excitation radio galaxies (LERGs) at low redshift. While LERGs are not the direct result of a merger, we describe how they form in clusters in only a few million years while that timescale is an order of magnitude longer in field environments. As a result of these different timescales, the average lifetime of a cluster LERG is estimated at an order of magnitude greater value than for field LERGs. Observing a LERG in the cluster environment, therefore, will tend to occur when greater time has passed since the major merger event that produced its high excitation radio galaxy ancestor, such that fewer signatures of that event remain visible. We provide simple estimates for the fraction of LERGs as a function of environment that are directly related to these timescales, obtaining a probability of about 7% that field LERGs will show merger signatures and 3% for clusters, showing that theory and observation match if major merger signatures remain visible for a few hundred million years.
Solute drag and dynamic phase transformations in moving grain boundaries

Abstract A discrete model and the regular solution approximation are applied to describe the effect of grain boundary motion on grain boundary phase transformations in a binary alloy. The model predicts all thermodynamic properties of the grain boundary and the solute drag force, and permits a broad exploration of the parameter space and different dynamic regimes. The grain boundary phases continue to exist in the moving grain boundary and show a dynamic hysteresis loop, a dynamic critical line, and other features that are similar to those for equilibrium phases. Grain boundary motion strongly affects the relative stability of the phases and can even stabilize phases that are absolutely unstable under equilibrium conditions. Grain boundary phase transformations are accompanied by drastic changes in the boundary mobility. The results are analyzed in the context of non-equilibrium thermodynamics. Unresolved problems and future work are discussed.
The Construction and Criminalization of Disability in School Incarceration

This Article explores how race functions to ascribe and criminalize disability. It posits that for White students in wealthy schools, disabilities or perceived disabilities are often viewed as medical conditions and treated with care and resources. For students of color, however, the construction of disability (if it exists) may be a criminalized condition that is treated as warranting punishment and segregated classrooms, possibly leading to juvenile justice system involvement. Providing a review of the K-12 disability legal regimes, this Article maps how the process of identifying a student with a disability happens in a hypercriminalized school setting. The Article argues that the school itself contributes to the construction and criminalization of disability and that the attribution of disability is a product of the subjectivity built into the law, heavily surveilled school environments, and biases held by teachers and administrators. For students of color, instead of a designation that attracts more resources, disability is one of the mechanisms through which they are criminalized. This Article culminates with a call for scholars and practitioners to understand the web that exists in the construction and criminalization of disabilities for Black and Latinx children and the role that schools and school actors play in this process.
Distributed compression for large camera arrays

We address the problem of compression for large camera arrays, and propose a distributed solution based on Wyner-Ziv coding. The proposed scheme allows independent encoding of each view with low-complexity cameras, and performs centralized decoding with side information from additional views. Experimental results are given for two light field data sets. The performance of the proposed scheme is compared with independently coding each view using JPEG2000 and a shape-adaptive JPEG-like coder. The Wyner-Ziv coder yields superior compression performance at low bit-rates. In addition, there is a great reduction in encoder complexity when compared to JPEG2000.
Convergence as period goes to infinity of spectra of periodic traveling waves toward essential spectra of a homoclinic limit

Abstract We revisit the analysis by R.A. Gardner of convergence of spectra of periodic traveling waves in the homoclinic, or infinite-period limit, extending his results to the case of essential rather than point spectra of the limiting homoclinic wave. Notably, convergence to essential spectra is seen to be of algebraic rate with respect to period as compared to the exponential rate of convergence to point spectra. In the course of the analysis, we show not only convergence of spectrum but also convergence of an appropriate renormalization of the associated periodic Evans function to the Evans function for the limiting homoclinic wave, a fact that is useful for numerical investigations.
Extracting Reproducible Time-Resolved Resting State Networks Using Dynamic Mode Decomposition

Resting state networks (RSNs) extracted from functional magnetic resonance imaging (fMRI) scans are believed to reflect the intrinsic organization and network structure of brain regions. Most traditional methods for computing RSNs typically assume these functional networks are static throughout the duration of a scan lasting 5–15 minutes. However, they are known to vary on timescales ranging from seconds to years; in addition, the dynamic properties of RSNs are affected in a wide variety of neurological disorders. Recently, there has been a proliferation of methods for characterizing RSN dynamics, yet it remains a challenge to extract reproducible time-resolved networks. In this paper, we develop a novel method based on dynamic mode decomposition (DMD) to extract networks from short windows of noisy, high-dimensional fMRI data, allowing RSNs from single scans to be resolved robustly at a temporal resolution of seconds. After validating the method on a synthetic dataset, we analyze data from 120 individuals from the Human Connectome Project and show that unsupervised clustering of DMD modes discovers RSNs at both the group (gDMD) and the single subject (sDMD) levels. The gDMD modes closely resemble canonical RSNs. Compared to established methods, sDMD modes capture individualized RSN structure that both better resembles the population RSN and better captures subject-level variation. We further leverage this time-resolved sDMD analysis to infer occupancy and transitions among RSNs with high reproducibility. This automated DMD- based method is a powerful tool to characterize spatial and temporal structures of RSNs in individual subjects.
Design and performance of voltage-controlled oscillators using TFR stacked-crystal filters

Two applications of thin-film resonator (TFR) technology are presented. These designs are: a 1-GHz voltage-controlled oscillator (VCO) with a 0.5% tuning range, and a frequency-agile 1-GHz oscillator which provides discrete frequency shifts of 4 MHz. The basic TFR frequency-control structure is a stacked-crystal filter (SCF) synthesized using multiple layers of AlN for piezoelectric transduction sandwiched between Al electrodes. Filters can be synthesized with single-mode bandpass or multiple (over-moded) bandpass characteristics. Typical performance for a single-mode double-stacked filter, when used in a 1-GHz VCO, provides an insertion loss as low as 1.5 dB, a linear phase extending over a 20-MHz passband, and an open-loop Q=80. The VCO was designed using a large-signal perturbational S-parameter technique. >
Thermal Responses of Connected HEVs Engine and Aftertreatment Systems to Eco-Driving

Connected and automated vehicles (CAVs) have been recognized as providing unprecedented opportunities for substantial fuel economy improvement through CAV-based vehicle speed trajectory optimization (eco-driving). At the same time, the implications of the CAV operation on thermal responses, including those of engine and exhaust aftertreatment system, have not been fully investigated. To this end, firstly, a sequential optimization framework for vehicle speed trajectory planning and powertrain control in hybrid electric CAVs is proposed in this paper. Next, the impact of eco-driving and power split optimization on the engine and catalytic converter thermal responses, as well as on the tailpipe emissions is characterized. Despite an average 16% improvement in fuel economy through sequential optimization, this study shows that eco-driving slows down the thermal responses, which could unfavorably affect the tailpipe emissions.
Generalizations of Menchov–Rademacher Theorem and Existence of Wave Operators in Schrödinger Evolution

We obtain generalizations of the classical Menchov–Rademacher theorem to the case of continuous orthogonal systems. These results are applied to show the existence of Moller wave operators in Schrodinger evolution.
Association of Transcarotid Artery Revascularization vs Transfemoral Carotid Artery Stenting With Stroke or Death Among Patients With Carotid Artery Stenosis

Importance Several trials have observed higher rates of perioperative stroke following transfemoral carotid artery stenting compared with carotid endarterectomy. Transcarotid artery revascularization with flow reversal was recently introduced for carotid stenting. This technique was developed to decrease stroke risk seen with the transfemoral approach; however, its outcomes, compared with transfemoral carotid artery stenting, are not well characterized. Objective To compare outcomes associated with transcarotid artery revascularization and transfemoral carotid artery stenting. Design, Setting, and Participants Exploratory propensity score–matched analysis of prospectively collected data from the Vascular Quality Initiative Transcarotid Artery Surveillance Project and Carotid Stent Registry of asymptomatic and symptomatic patients in the United States and Canada undergoing transcarotid artery revascularization and transfemoral carotid artery stenting for carotid artery stenosis, from September 2016 to April 2019. The final date for follow-up was May 29, 2019. Exposures Transcarotid artery revascularization vs transfemoral carotid artery stenting. Main Outcomes and Measures Outcomes included a composite end point of in-hospital stroke or death, stroke, death, myocardial infarction, as well as ipsilateral stroke or death at 1 year. In-hospital stroke was defined as ipsilateral or contralateral, cortical or vertebrobasilar, and ischemic or hemorrhagic stroke. Death was all-cause mortality. Results During the study period, 5251 patients underwent transcarotid artery revascularization and 6640 patients underwent transfemoral carotid artery stenting. After matching, 3286 pairs of patients who underwent transcarotid artery revascularization or transfemoral carotid artery stenting were identified (transcarotid approach: mean [SD] age, 71.7 [9.8] years; 35.7% women; transfemoral approach: mean [SD] age, 71.6 [9.3] years; 35.1% women). Transcarotid artery revascularization was associated with a lower risk of in-hospital stroke or death (1.6% vs 3.1%; absolute difference, −1.52% [95% CI, −2.29% to −0.75%]; relative risk [RR], 0.51 [95% CI, 0.37 to 0.72];P Conclusions and Relevance Among patients undergoing treatment for carotid stenosis, transcarotid artery revascularization, compared with transfemoral carotid artery stenting, was significantly associated with a lower risk of stroke or death.
Deep Learning Accelerated Light Source Experiments

Experimental protocols at synchrotron light sources typically process and validate data only after an experiment has completed, which can lead to undetected errors and cannot enable online steering. Real-time data analysis can enable both detection of, and recovery from, errors, and optimization of data acquisition. However, modern scientific instruments, such as detectors at synchrotron light sources, can generate data at GBs/sec rates. Data processing methods such as the widely used computational tomography usually require considerable computational resources, and yield poor quality reconstructions in the early stages of data acquisition when available views are sparse. We describe here how a deep convolutional neural network can be integrated into the real-time streaming tomography pipeline to enable better-quality images in the early stages of data acquisition. Compared with conventional streaming tomography processing, our method can significantly improve tomography image quality, deliver comparable images using only 32% of the data needed for conventional streaming processing, and save 68% experiment time for data acquisition.
Multidisciplinary Design Optimization of Low-Boom Supersonic Aircraft with Mission Constraints

Conceptual design of low-boom supersonic aircraft is heavily dictated by aircraft volume and lift distributions. These unique design characteristics make it a challenge to enforce mission requireme...
Tipping the scale? The workings of monetary policy through trade

The monetary policy entails demand‐augmenting and diverting effects, and its impact on the trade balance—and on other countries—depends on the magnitude of these opposing effects. Using U.S. data and a sign‐restricted structural vector autoregressive identification, we investigate the importance of these effects. Overall, the results indicate that a monetary loosening (tightening) leads to a strengthening (weakening) of the overall trade balance, indicating that demand diversion dominates. The paper also explores changes in the effects following the global financial crisis, reflecting the impaired monetary transmission mechanism.
Pinching Surface Groups in Complex Hyperbolic Plane

We construct first examples of discrete geometrically finite subgroups of PU(21) which contain parabolic elements, and are isomorphic to surface groups of genus ≥2.
Capital Flow Waves—or Ripples? Extreme Capital Flow Movements Since the Crisis

Abstract Has the occurrence of “extreme capital flow movements”—episodes of sudden surges, stops, flight and retrenchment—changed since the Global Financial Crisis (GFC)? And was the period at the outset of the Covid Crisis any different? This paper addresses these questions by updating and building on the dataset and methodology introduced in Forbes and Warnock (2012) to calculate the occurrence of sharp capital flow movements by foreigners and domestics into and out of individual countries. The results suggest that the occurrence of these extreme capital flow movements has not increased since the GFC, including during the early phases of the Covid Crisis (the first half of 2020). The drivers of these episodes, however, appear to have changed since the GFC. Extreme capital flow movements are less correlated with changes in global risk and more correlated with changes in oil prices. More generally, what used to be large global “waves” in international capital flows have more recently become more idiosyncratic “ripples”.
k-Cut: A Simple Approximately-Uniform Method for Sampling Ballots in Post-election Audits

We present an approximate sampling framework and discuss how risk-limiting audits can compensate for these approximations, while maintaining their “risk-limiting” properties. Our framework is general and can compensate for counting mistakes made during audits.
Molecular Simulation of Covalent Bond Dynamics in Liquid Silicon

Many atomic liquids can form transient covalent bonds reminiscent of those in the corresponding solid states. These directional interactions dictate many important properties of the liquid state, necessitating a quantitative, atomic-scale understanding of bonding in these complex systems. A prototypical example is liquid silicon, wherein transient covalent bonds give rise to local tetrahedral order and consequent nontrivial effects on liquid-state thermodynamics and dynamics. To further understand covalent bonding in liquid silicon, and similar liquids, we present an ab initio-simulation-based approach for quantifying the structure and dynamics of covalent bonds in condensed phases. Through the examination of structural correlations among silicon nuclei and maximally localized Wannier function centers, we develop a geometric criterion for covalent bonds in liquid Si. We use this to monitor the dynamics of transient covalent bonding in the liquid state and estimate a covalent bond lifetime. We compare covalent bond dynamics to other processes in liquid Si and similar liquids and suggest experiments to measure the covalent bond lifetime.
Feedback control solutions to network level user-equilibrium real-time dynamic traffic assignment problems

A new method for performing Dynamic Traffic Assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems that is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting. Simulation results are provided for a sample simple network to show the effectiveness of this method.
Phase transitions in the edge/concurrent vertex model

Although it is well known that some exponential family random graph model (ERGM) families exhibit phase transitions (in which small parameter changes lead to qualitative changes in graph structure)...
Explicit representation of terms defined by counter examples

Anti-unification guarantees the existence of a term which is an explicit representation of the most specific generalization of a collection of terms. This provides a formal basis for learning from examples. Here we address the dual problem of computing a generalization given a set of counter examples. Unlike learning from examples an explicit, finite representation for the generalization does not always exist. We show that the problem is decidable by providing an algorithm which, given an implicit representation will return a finite explicit representation or report that none exists. Applications of this result to the problem of negation as failure and to the representation of solutions to systems of equations and inequations are also mentioned.
The Perils of Combination Antithrombotic Therapy and Potential Resolutions

The use of antithrombotic medications is a mainstay in the treatment of patients with a variety of cardiovascular and cerebrovascular disorders. Oral anticoagulation therapy dramatically reduces stroke risk in patients with atrial fibrillation (AF); aspirin and clopidogrel reduce subsequent ischemic events in patients with coronary artery disease (CAD) and ischemic stroke; and the combination of aspirin plus clopidogrel reduces ischemic outcomes in patients with acute coronary syndromes and thrombosis after stent deployment.1,–,3 The most common clinical scenario for the combined use of oral anticoagulation and aspirin is that of patients with AF and CAD. In patients undergoing percutaneous coronary intervention (PCI) who have concomitant AF, triple therapy (TT) with warfarin, aspirin, and clopidogrel is being used with increasing frequency. Such combinations of antithrombotic medications are often used, but aside from selected situations such as the time-limited use of clopidogrel and aspirin after coronary artery stenting or acute coronary syndromes and the use of warfarin and aspirin in patients with mechanical heart valves, little evidence of benefit is available for these combined therapies in the majority of patients with cardiovascular disorders, and substantial evidence of risk is accumulating.4,5 The risk of major bleeding associated with oral anticoagulation use is quite variable but appears to be higher in clinical practice compared with clinical trials, with annual rates ranging from 3.26% to 7.20% in recent series.5,6 Older age and a prolonged international normalized ratio (INR) increase the risk. Current estimates suggest that ≈20% to 40% of patients who take oral anticoagulants are also taking an antiplatelet agent, in most cases, aspirin.5,6 The risk for major or life-threatening bleeding with the combined use of an oral anticoagulant plus aspirin appears to be significantly greater than the risk with the use …
The Nucleus Accumbens Core is Necessary to Scale Fear to Degree of Threat

Fear is adaptive when the level of the response rapidly scales to degree of threat. Using a discrimination procedure consisting of danger, uncertainty, and safety cues, we have found rapid fear scaling (within 2 s of cue presentation) in male rats. Here, we examined a possible role for the nucleus accumbens core (NAcc) in the acquisition and expression of fear scaling. In experiment 1, male Long-Evans rats received bilateral sham or neurotoxic NAcc lesions, recovered, and underwent fear discrimination. NAcc-lesioned rats were generally impaired in scaling fear to degree of threat, and specifically impaired in rapid uncertainty-safety discrimination. In experiment 2, male Long-Evans rats received NAcc transduction with halorhodopsin (Halo) or a control fluorophore. After fear scaling was established, the NAcc was illuminated during cue or control periods. NAcc-Halo rats receiving cue illumination were specifically impaired in rapid uncertainty-safety discrimination. The results reveal a general role for the NAcc in scaling fear to degree of threat, and a specific role in rapid discrimination of uncertain threat and safety.SIGNIFICANCE STATEMENT Rapidly discriminating cues for threat and safety is essential for survival and impaired threat-safety discrimination is a hallmark of stress and anxiety disorders. In two experiments, we induced nucleus accumbens core (NAcc) dysfunction in rats receiving fear discrimination consisting of cues for danger, uncertainty, and safety. Permanent NAcc dysfunction, via neurotoxic lesion, generally disrupted the ability to scale fear to degree of threat, and specifically impaired one component of scaling: rapid discrimination of uncertain threat and safety. Reversible NAcc dysfunction, via optogenetic inhibition, specifically impaired rapid discrimination of uncertain threat and safety. The results reveal that the NAcc is essential to scale fear to degree of threat, and is a plausible source of dysfunction in stress and anxiety disorders.
Nonparametric Correlation (tau)

Kendall's correlation coefficient (τ) for ranked data, often known as Kendall's tau, is based on the number of inversions in a set of ranks. Data on X and Y are replaced by their ranks, and the correlation (τ) between the ranks is computed. Keywords: Pearson correlation; Spearman's rho; rank correlations
Adjustment to monetary policy and devaluation under two-tier and fixed exchange rate regimes

Abstract The purpose of this paper is to determine whether a two-tier exchange rate regime is more effective than a fixed rate regime in increasing a country's ability to pursue an independent monetary policy. The analysis compares adjustment to a monetary policy and to a devaluation in the two exchange rate regimes in a portfolio model under imperfect assets substitutability. It is shown that a two-tier exchange rate regime is capable of reducing the current account effects of monetary injection or devaluation only in the long run. In the short run, however, we can get a larger current account response under a two-tier regime. These results reflect the trade-off between quantity and price adjustment.
Crispr/Cas9-mediated cleavages facilitate homologous recombination during genetic engineering of a large chromosomal region.

Homologous recombination over large genomic regions is difficult to achieve due to low efficiencies. Here, we report the successful engineering of a humanized mTert allele, hmTert, in the mouse genome by replacing an 18.1-kb genomic region around the mTert gene with a recombinant fragment of over 45.5 kb, using homologous recombination facilitated by the Crispr/Cas9 technology, in mouse embryonic stem cells (mESCs). In our experiments, with DNA double-strand breaks (DSBs) generated by Crispr/Cas9 system, the homologous recombination efficiency was up to 11% and 16% in two mESC lines TC1 and v6.5, respectively. Overall, we obtained a total of 27 mESC clones with heterozygous hmTert/mTert alleles and three clones with homozygous hmTert alleles. DSBs induced by Crispr/Cas9 cleavages also caused high rates of genomic DNA deletions and mutations at single-guide RNA target sites. Our results indicated that the Crispr/Cas9 system significantly increased the efficiency of homologous recombination-mediated gene editing over a large genomic region in mammalian cells, and also caused frequent mutations at unedited target sites. Overall, this strategy provides an efficient and feasible way for manipulating large chromosomal regions.
MicroRNA-1253 Regulation of WASF2 (WAVE2) and its Relevance to Racial Health Disparities

The prevalence of hypertension among African Americans (AAs) in the US is among the highest of any demographic and affects over two-thirds of AA women. Previous data from our laboratory suggest substantial differential gene expression (DGE) of mRNAs and microRNAs (miRNAs) exists within peripheral blood mononuclear cells (PBMCs) isolated from AA and white women with or without hypertension. We hypothesized that DGE by race may contribute to racial differences in hypertension. In a reanalysis of our previous dataset, we found that the Wiskott-Aldrich syndrome protein Verprolin-homologous protein 2 (WASF2 (also known as WAVE2)) is differentially expressed in AA women with hypertension, along with several other members of the actin cytoskeleton signaling pathway that plays a role in cell shape and branching of actin filaments. We performed an in silico miRNA target prediction analysis that suggested miRNA miR-1253 regulates WASF2. Transfection of miR-1253 mimics into human umbilical vein endothelial cells (HUVECs) and human aortic endothelial cells (HAECs) significantly repressed WASF2 mRNA and protein levels (p < 0.05), and a luciferase reporter assay confirmed that miR-1253 regulates the WASF2 3' UTR (p < 0.01). miR-1253 overexpression in HUVECs significantly increased HUVEC lamellipodia formation (p < 0.01), suggesting the miR-1253-WASF2 interaction may play a role in cell shape and actin cytoskeleton function. Together, we have identified novel roles for miR-1253 and WASF2 in a hypertension-related disparities context. This may ultimately lead to the discovery of additional actin-related genes which are important in the vascular-related complications of hypertension and influence the disproportionate susceptibility to hypertension among AAs in general and AA women in particular.
Measuring management practices in primary health care facilities–development and validation of management practices scorecard in Nigeria

In low- and middle-income countries, there is scarcity of validated and reliable measurement tools for health facility management, and many interventions to improve primary health care (PHC) facili...
IMAGING BURIED INTERFACIAL LATTICES WITH QUANTIZED ELECTRONS

We demonstrate that the well-known $\mathrm{Si}(111)\ensuremath{-}(7\ifmmode\times\else\texttimes\fi{}7)$ superlattice buried under as much as 100 \AA{} of crystalline Pb can be directly imaged with a scanning tunneling microscope at 77 K. The unexpected transparency of the metal and the high lateral resolution are the result of a nondiffractive scattering of the electrons at the interface. We attribute this phenomenon to a large anisotropy of the effective masses associated with the free in-plane and the quantized transverse motion of the electrons.