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Generalized weighted Ostrowski and Ostrowski-Grüss type inequalities on time scales via a parameter function
We prove generalized weighted Ostrowski and Ostrowski--Grüss type inequalities on time scales via a parameter function. In particular, our result extends a result of Dragomir and Barnett. Furthermore, we apply our results to the continuous, discrete, and quantum cases, to obtain some interesting new inequalities.
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"Found in Translation": Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models
There is an intuitive analogy of an organic chemist's understanding of a compound and a language speaker's understanding of a word. Consequently, it is possible to introduce the basic concepts and analyze potential impacts of linguistic analysis to the world of organic chemistry. In this work, we cast the reaction pr...
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Efficient Decomposition of High-Rank Tensors
Tensors are a natural way to express correlations among many physical variables, but storing tensors in a computer naively requires memory which scales exponentially in the rank of the tensor. This is not optimal, as the required memory is actually set not by the rank but by the mutual information amongst the variabl...
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Universality in Chaos: Lyapunov Spectrum and Random Matrix Theory
We propose the existence of a new universality in classical chaotic systems when the number of degrees of freedom is large: the statistical property of the Lyapunov spectrum is described by Random Matrix Theory. We demonstrate it by studying the finite-time Lyapunov exponents of the matrix model of a stringy black ho...
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Fixed points of competitive threshold-linear networks
Threshold-linear networks (TLNs) are models of neural networks that consist of simple, perceptron-like neurons and exhibit nonlinear dynamics that are determined by the network's connectivity. The fixed points of a TLN, including both stable and unstable equilibria, play a critical role in shaping its emergent dynami...
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A Decision Procedure for Herbrand Formulae without Skolemization
This paper describes a decision procedure for disjunctions of conjunctions of anti-prenex normal forms of pure first-order logic (FOLDNFs) that do not contain $\vee$ within the scope of quantifiers. The disjuncts of these FOLDNFs are equivalent to prenex normal forms whose quantifier-free parts are conjunctions of at...
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The role of relativistic many-body theory in probing new physics beyond the standard model via the electric dipole moments of diamagnetic atoms
The observation of electric dipole moments (EDMs) in atomic systems due to parity and time-reversal violating (P,T-odd) interactions can probe new physics beyond the standard model and also provide insights into the matter-antimatter asymmetry in the Universe. The EDMs of open-shell atomic systems are sensitive to th...
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Security Incident Recognition and Reporting (SIRR): An Industrial Perspective
Reports and press releases highlight that security incidents continue to plague organizations. While researchers and practitioners' alike endeavor to identify and implement realistic security solutions to prevent incidents from occurring, the ability to initially identify a security incident is paramount when researc...
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On attainability of optimal controls in coefficients for system of Hammerstein type with anisotropic p-Laplacia
In this paper we consider an optimal control problem for the coupled system of a nonlinear monotone Dirichlet problem with anisotropic p-Laplacian and matrix-valued nonsmooth controls in its coefficients and a nonlinear equation of Hammerstein type. Using the direct method in calculus of variations, we prove the exis...
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Adversarial Variational Bayes Methods for Tweedie Compound Poisson Mixed Models
The Tweedie Compound Poisson-Gamma model is routinely used for modeling non-negative continuous data with a discrete probability mass at zero. Mixed models with random effects account for the covariance structure related to the grouping hierarchy in the data. An important application of Tweedie mixed models is pricin...
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Sampling of Temporal Networks: Methods and Biases
Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one mi...
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Personalizing Path-Specific Effects
Unlike classical causal inference, which often has an average causal effect of a treatment within a population as a target, in settings such as personalized medicine, the goal is to map a given unit's characteristics to a treatment tailored to maximize the expected outcome for that unit. Obtaining high-quality mappin...
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Bridge Programs as an approach to improving diversity in physics
In most physical sciences, students from underrepresented minority (URM) groups constitute a small percentage of earned degrees at the undergraduate and graduate levels. Bridge programs can serve as an initiative to increase the number of URM students that gain access to graduate school and earn advanced degrees in p...
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NEURAL: quantitative features for newborn EEG using Matlab
Background: For newborn infants in critical care, continuous monitoring of brain function can help identify infants at-risk of brain injury. Quantitative features allow a consistent and reproducible approach to EEG analysis, but only when all implementation aspects are clearly defined. Methods: We detail quantitative...
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False Positive Reduction by Actively Mining Negative Samples for Pulmonary Nodule Detection in Chest Radiographs
Generating large quantities of quality labeled data in medical imaging is very time consuming and expensive. The performance of supervised algorithms for various tasks on imaging has improved drastically over the years, however the availability of data to train these algorithms have become one of the main bottlenecks...
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WASP-12b: A Mass-Losing Extremely Hot Jupiter
WASP-12b is an extreme hot Jupiter in a 1 day orbit, suffering profound irradiation from its F type host star. The planet is surrounded by a translucent exosphere which overfills the Roche lobe and produces line-blanketing absorption in the near-UV. The planet is losing mass. Another unusual property of the WASP-12 s...
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On the status of the Born-Oppenheimer expansion in molecular systems theory
It is shown that the adiabatic Born-Oppenheimer expansion does not satisfy the necessary condition for the applicability of perturbation theory. A simple example of an exact solution of a problem that can not be obtained from the Born-Oppenheimer expansion is given. A new version of perturbation theory for molecular ...
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Computing Tropical Prevarieties in Parallel
The computation of the tropical prevariety is the first step in the application of polyhedral methods to compute positive dimensional solution sets of polynomial systems. In particular, pretropisms are candidate leading exponents for the power series developments of the solutions. The computation of the power series ...
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3k-4 theorem for ordered groups
Recently, G. A. Freiman, M. Herzog, P. Longobardi, M. Maj proved two `structure theorems' for ordered groups \cite{FHLM}. We give elementary proof of these two theorems.
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The Extinction Properties of and Distance to the Highly Reddened Type Ia Supernova SN 2012cu
Correction of Type Ia Supernova brightnesses for extinction by dust has proven to be a vexing problem. Here we study the dust foreground to the highly reddened SN 2012cu, which is projected onto a dust lane in the galaxy NGC 4772. The analysis is based on multi-epoch, spectrophotometric observations spanning 3,300 - ...
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On Whitham and related equations
The aim of this paper is to study, via theoretical analysis and numerical simulations, the dynamics of Whitham and related equations. In particular we establish rigorous bounds between solutions of the Whitham and KdV equations and provide some insights into the dynamics of the Whitham equation in different regimes, ...
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Analytic Connectivity in General Hypergraphs
In this paper we extend the known results of analytic connectivity to non-uniform hypergraphs. We prove a modified Cheeger's inequality and also give a bound on analytic connectivity with respect to the degree sequence and diameter of a hypergraph.
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Cosmological searches for a non-cold dark matter component
We explore an extended cosmological scenario where the dark matter is an admixture of cold and additional non-cold species. The mass and temperature of the non-cold dark matter particles are extracted from a number of cosmological measurements. Among others, we consider tomographic weak lensing data and Milky Way dwa...
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F-pure threshold and height of quasi-homogeneous polynomials
We consider a quasi-homogeneous polynomial $f \in \mathbb{Z}[x_0, \ldots, x_N]$ of degree $w$ equal to the degree of $x_0 \cdots x_N$ and show that the $F$-pure threshold of the reduction $f_p \in \mathbb{F}_p[x_0, \ldots, x_N]$ is equal to the log canonical threshold if and only if the height of the Artin-Mazur form...
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Optimal VWAP execution under transient price impact
We solve the problem of optimal liquidation with volume weighted average price (VWAP) benchmark when the market impact is linear and transient. Our setting is indeed more general as it considers the case when the trading interval is not necessarily coincident with the benchmark interval: Implementation Shortfall and ...
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Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching
Cellular Electron CryoTomography (CECT) is a 3D imaging technique that captures information about the structure and spatial organization of macromolecular complexes within single cells, in near-native state and at sub-molecular resolution. Although template matching is often used to locate macromolecules in a CECT im...
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Bayesian Alignments of Warped Multi-Output Gaussian Processes
We propose a novel Bayesian approach to modelling nonlinear alignments of time series based on latent shared information. We apply the method to the real-world problem of finding common structure in the sensor data of wind turbines introduced by the underlying latent and turbulent wind field. The proposed model allow...
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Fast and unsupervised methods for multilingual cognate clustering
In this paper we explore the use of unsupervised methods for detecting cognates in multilingual word lists. We use online EM to train sound segment similarity weights for computing similarity between two words. We tested our online systems on geographically spread sixteen different language groups of the world and sh...
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Structure, magnetic susceptibility and specific heat of the spin-orbital-liquid candidate FeSc2S4 : Influence of fe off-stoichiometry
We report structural, susceptibility and specific heat studies of stoichiometric and off-stoichiometric poly- and single crystals of the A-site spinel compound FeSc2S4. In stoichiometric samples no long-range magnetic order is found down to 1.8 K. The magnetic susceptibility of these samples is field independent in t...
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Directed Information as Privacy Measure in Cloud-based Control
We consider cloud-based control scenarios in which clients with local control tasks outsource their computational or physical duties to a cloud service provider. In order to address privacy concerns in such a control architecture, we first investigate the issue of finding an appropriate privacy measure for clients wh...
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Classification of simple linearly compact Kantor triple systems over the complex numbers
Simple finite dimensional Kantor triple systems over the complex numbers are classified in terms of Satake diagrams. We prove that every simple and linearly compact Kantor triple system has finite dimension and give an explicit presentation of all the classical and exceptional systems.
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Code-division multiplexed resistive pulse sensor networks for spatio-temporal detection of particles in microfluidic devices
Spatial separation of suspended particles based on contrast in their physical or chemical properties forms the basis of various biological assays performed on lab-on-achip devices. To electronically acquire this information, we have recently introduced a microfluidic sensing platform, called Microfluidic CODES, which...
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Navigability evaluation of complex networks by greedy routing efficiency
Network navigability is a key feature of complex networked systems. For a network embedded in a geometrical space, maximization of greedy routing (GR) measures based on the node geometrical coordinates can ensure efficient greedy navigability. In PNAS, Seguin et al. (PNAS 2018, vol. 115, no. 24) define a measure for ...
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Fermion condensation and super pivotal categories
We study fermionic topological phases using the technique of fermion condensation. We give a prescription for performing fermion condensation in bosonic topological phases which contain a fermion. Our approach to fermion condensation can roughly be understood as coupling the parent bosonic topological phase to a phas...
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PIMKL: Pathway Induced Multiple Kernel Learning
Reliable identification of molecular biomarkers is essential for accurate patient stratification. While state-of-the-art machine learning approaches for sample classification continue to push boundaries in terms of performance, most of these methods are not able to integrate different data types and lack generalizati...
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pyRecLab: A Software Library for Quick Prototyping of Recommender Systems
This paper introduces pyRecLab, a software library written in C++ with Python bindings which allows to quickly train, test and develop recommender systems. Although there are several software libraries for this purpose, only a few let developers to get quickly started with the most traditional methods, permitting the...
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A unified theory of adaptive stochastic gradient descent as Bayesian filtering
We formulate stochastic gradient descent (SGD) as a Bayesian filtering problem. Inference in the Bayesian setting naturally gives rise to BRMSprop and BAdam: Bayesian variants of RMSprop and Adam. Remarkably, the Bayesian approach recovers many features of state-of-the-art adaptive SGD methods, including amoungst oth...
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Radiative effects during the assembly of direct collapse black holes
We perform a post-processing radiative feedback analysis on a 3D ab initio cosmological simulation of an atomic cooling halo under the direct collapse black hole (DCBH) scenario. We maintain the spatial resolution of the simulation by incorporating native ray-tracing on unstructured mesh data, including Monte Carlo L...
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Spin-orbit interactions in optically active materials
We investigate the inherent influence of light polarization on the intensity distribution in anisotropic media undergoing a local inhomogeneous rotation of the principal axes. Whereas in general such configuration implies a complicated interaction between geometric and dynamic phase, we show that, in a medium showing...
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Automatic White-Box Testing of First-Order Logic Ontologies
Formal ontologies are axiomatizations in a logic-based formalism. The development of formal ontologies, and their important role in the Semantic Web area, is generating considerable research on the use of automated reasoning techniques and tools that help in ontology engineering. One of the main aims is to refine and...
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Critical values in Bak-Sneppen type models
In the Bak-Sneppen model, the lowest fitness particle and its two nearest neighbors are renewed at each temporal step with a uniform (0,1) fitness distribution. The model presents a critical value that depends on the interaction criteria (two nearest neighbors) and on the update procedure (uniform). Here we calculate...
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On the correspondence of deviances and maximum likelihood and interval estimates from log-linear to logistic regression modelling
Consider a set of categorical variables $\mathcal{P}$ where at least one, denoted by $Y$, is binary. The log-linear model that describes the counts in the resulting contingency table implies a specific logistic regression model, with the binary variable as the outcome. Extending results in Christensen (1997), by also...
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ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters
We consider time-domain digital backpropagation with chromatic dispersion filters jointly optimized and quantized using machine-learning techniques. Compared to the baseline implementations, we show improved BER performance and >40% power dissipation reductions in 28-nm CMOS.
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A formalization of convex polyhedra based on the simplex method
We present a formalization of convex polyhedra in the proof assistant Coq. The cornerstone of our work is a complete implementation of the simplex method, together with the proof of its correctness and termination. This allows us to define the basic predicates over polyhedra in an effective way (i.e., as programs), a...
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Weight Spectrum of Quasi-Perfect Binary Codes with Distance 4
We consider the weight spectrum of a class of quasi-perfect binary linear codes with code distance 4. For example, extended Hamming code and Panchenko code are the known members of this class. Also, it is known that in many cases Panchenko code has the minimal number of weight 4 codewords. We give exact recursive for...
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Ultra-High Electro-Optic Activity Demonstrated in a Silicon-Organic Hybrid (SOH) Modulator
Efficient electro-optic (EO) modulators crucially rely on advanced materials that exhibit strong electro-optic activity and that can be integrated into high-speed and efficient phase shifter structures. In this paper, we demonstrate ultra-high in-device EO figures of merit of up to n3r33 = 2300 pm/V achieved in a sil...
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How the Experts Do It: Assessing and Explaining Agent Behaviors in Real-Time Strategy Games
How should an AI-based explanation system explain an agent's complex behavior to ordinary end users who have no background in AI? Answering this question is an active research area, for if an AI-based explanation system could effectively explain intelligent agents' behavior, it could enable the end users to understan...
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Entanglement Entropy of Eigenstates of Quadratic Fermionic Hamiltonians
In a seminal paper [D. N. Page, Phys. Rev. Lett. 71, 1291 (1993)], Page proved that the average entanglement entropy of subsystems of random pure states is $S_{\rm ave}\simeq\ln{\cal D}_{\rm A} - (1/2) {\cal D}_{\rm A}^2/{\cal D}$ for $1\ll{\cal D}_{\rm A}\leq\sqrt{\cal D}$, where ${\cal D}_{\rm A}$ and ${\cal D}$ ar...
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Focusing light through dynamical samples using fast closed-loop wavefront optimization
We describe a fast closed-loop optimization wavefront shaping system able to focus light through dynamic scattering media. A MEMS-based spatial light modulator (SLM), a fast photodetector and FPGA electronics are combined to implement a closed-loop optimization of a wavefront with a single mode optimization rate of 4...
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The curvature estimates for convex solutions of some fully nonlinear Hessian type equations
The curvature estimates of quotient curvature equation do not always exist even for convex setting \cite{GRW}. Thus it is natural question to find other type of elliptic equations possessing curvature estimates. In this paper, we discuss the existence of curvature estimate for fully nonlinear elliptic equations defin...
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The Compressed Model of Residual CNDS
Convolutional neural networks have achieved a great success in the recent years. Although, the way to maximize the performance of the convolutional neural networks still in the beginning. Furthermore, the optimization of the size and the time that need to train the convolutional neural networks is very far away from ...
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Chow Rings of Mp_{0,2}(N,d) and Mbar_{0,2}(P^{N-1},d) and Gromov-Witten Invariants of Projective Hypersurfaces of Degree 1 and 2
In this paper, we prove formulas that represent two-pointed Gromov-Witten invariant <O_{h^a}O_{h^b}>_{0,d} of projective hypersurfaces with d=1,2 in terms of Chow ring of Mbar_{0,2}(P^{N-1},d), the moduli spaces of stable maps from genus 0 stable curves to projective space P^{N-1}. Our formulas are based on represent...
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A Real-Time Autonomous Highway Accident Detection Model Based on Big Data Processing and Computational Intelligence
Due to increasing urban population and growing number of motor vehicles, traffic congestion is becoming a major problem of the 21st century. One of the main reasons behind traffic congestion is accidents which can not only result in casualties and losses for the participants, but also in wasted and lost time for the ...
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Asymptotic Eigenfunctions for a class of Difference Operators
We analyze a general class of difference operators $H_\varepsilon = T_\varepsilon + V_\varepsilon$ on $\ell^2(\varepsilon \mathbb{Z}^d)$, where $V_\varepsilon$ is a one-well potential and $\varepsilon$ is a small parameter. We construct formal asymptotic expansions of WKB-type for eigenfunctions associated with the l...
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Common Glass-Forming Spin-Liquid State in the Pyrochlore Magnets Dy$_2$Ti$_2$O$_7$ and Ho$_2$Ti$_2$O$_7$
Despite a well-ordered pyrochlore crystal structure and strong magnetic interactions between the Dy$^{3+}$ or Ho$^{3+}$ ions, no long range magnetic order has been detected in the pyrochlore titanates Ho$_2$Ti$_2$O$_7$ and Dy$_2$Ti$_2$O$_7$. To explore the actual magnetic phase formed by cooling these materials, we m...
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Britannia Rule the Waves
The students are introduced to navigation in general and the longitude problem in particular. A few videos provide insight into scientific and historical facts related to the issue. Then, the students learn in two steps how longitude can be derived from time measurements. They first build a Longitude Clock that visua...
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Error Forward-Propagation: Reusing Feedforward Connections to Propagate Errors in Deep Learning
We introduce Error Forward-Propagation, a biologically plausible mechanism to propagate error feedback forward through the network. Architectural constraints on connectivity are virtually eliminated for error feedback in the brain; systematic backward connectivity is not used or needed to deliver error feedback. Feed...
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CANA: A python package for quantifying control and canalization in Boolean Networks
Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work ...
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$α$-Variational Inference with Statistical Guarantees
We propose a family of variational approximations to Bayesian posterior distributions, called $\alpha$-VB, with provable statistical guarantees. The standard variational approximation is a special case of $\alpha$-VB with $\alpha=1$. When $\alpha \in(0,1]$, a novel class of variational inequalities are developed for ...
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Stable monoenergetic ion acceleration by a two color laser tweezer
In the past decades, the phenomenal progress in the development of ultraintense lasers has opened up many exciting new frontiers in laser matter physics, including laser plasma ion acceleration. Currently a major challenge in this frontier is to find simple methods to stably produce monoenergetic ion beams with suffi...
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Experimental demonstration of an ultra-compact on-chip polarization controlling structure
We demonstrated a novel on-chip polarization controlling structure, fabricated by standard 0.18-um foundry technology. It achieved polarization rotation with a size of 0.726 um * 5.27 um and can be easily extended into dynamic polarization controllers.
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Letter-Based Speech Recognition with Gated ConvNets
In the recent literature, "end-to-end" speech systems often refer to letter-based acoustic models trained in a sequence-to-sequence manner, either via a recurrent model or via a structured output learning approach (such as CTC). In contrast to traditional phone (or senone)-based approaches, these "end-to-end'' approa...
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The Frequent Network Neighborhood Mapping of the Human Hippocampus Shows Much More Frequent Neighbor Sets in Males Than in Females
In the study of the human connectome, the vertices and the edges of the network of the human brain are analyzed: the vertices of the graphs are the anatomically identified gray matter areas of the subjects; this set is exactly the same for all the subjects. The edges of the graphs correspond to the axonal fibers, con...
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Recurrent Neural Networks as Weighted Language Recognizers
We investigate the computational complexity of various problems for simple recurrent neural networks (RNNs) as formal models for recognizing weighted languages. We focus on the single-layer, ReLU-activation, rational-weight RNNs with softmax, which are commonly used in natural language processing applications. We sho...
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Classifying and Qualifying GUI Defects
Graphical user interfaces (GUIs) are integral parts of software systems that require interactions from their users. Software testers have paid special attention to GUI testing in the last decade, and have devised techniques that are effective in finding several kinds of GUI errors. However, the introduction of new ty...
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A mechanistic model of connector hubs, modularity, and cognition
The human brain network is modular--comprised of communities of tightly interconnected nodes. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities. A mechanistic understanding of these hubs and h...
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The OGLE Collection of Variable Stars. Over 450 000 Eclipsing and Ellipsoidal Binary Systems Toward the Galactic Bulge
We present a collection of 450 598 eclipsing and ellipsoidal binary systems detected in the OGLE fields toward the Galactic bulge. The collection consists of binary systems of all types: detached, semi-detached, and contact eclipsing binaries, RS CVn stars, cataclysmic variables, HW Vir binaries, double periodic vari...
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The discrete moment problem with nonconvex shape constraints
The discrete moment problem is a foundational problem in distribution-free robust optimization, where the goal is to find a worst-case distribution that satisfies a given set of moments. This paper studies the discrete moment problems with additional "shape constraints" that guarantee the worst case distribution is e...
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Some studies using capillary for flow control in a closed loop gas recirculation system
A Pilot unit of a closed loop gas (CLS) mixing and distribution system for the INO project was designed and is being operated with (1.8 x 1.9) m^2 glass RPCs (Resistive Plate Chamber). The performance of an RPC depends on the quality and quantity of gas mixture being used, a number of studies on controlling the flow ...
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Optimal Tuning of Two-Dimensional Keyboards
We give a new analysis of a tuning problem in music theory, pertaining specifically to the approximation of harmonics on a two-dimensional keyboard. We formulate the question as a linear programming problem on families of constraints and provide exact solutions for many new keyboard dimensions. We also show that an o...
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Ultra Reliable Short Message Relaying with Wireless Power Transfer
We consider a dual-hop wireless network where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source, and then uses the harvested energy to forward the source's information to the destination node. The throughput and delay metrics are investigated for a deco...
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Verifiable Light-Weight Monitoring for Certificate Transparency Logs
Trust in publicly verifiable Certificate Transparency (CT) logs is reduced through cryptography, gossip, auditing, and monitoring. The role of a monitor is to observe each and every log entry, looking for suspicious certificates that interest the entity running the monitor. While anyone can run a monitor, it requires...
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Chainspace: A Sharded Smart Contracts Platform
Chainspace is a decentralized infrastructure, known as a distributed ledger, that supports user defined smart contracts and executes user-supplied transactions on their objects. The correct execution of smart contract transactions is verifiable by all. The system is scalable, by sharding state and the execution of tr...
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On Certain Properties of Convex Functions
This note deals with certain properties of convex functions. We provide results on the convexity of the set of minima of these functions, the behaviour of their subgradient set under restriction, and optimization of these functions over an affine subspace.
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The detection of variable radio emission from the fast rotating magnetic hot B-star HR7355 and evidence for its X-ray aurorae
In this paper we investigate the multiwavelengths properties of the magnetic early B-type star HR7355. We present its radio light curves at several frequencies, taken with the Jansky Very Large Array, and X-ray spectra, taken with the XMM X-ray telescope. Modeling of the radio light curves for the Stokes I and V prov...
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In silico optimization of critical currents in superconductors
For many technological applications of superconductors the performance of a material is determined by the highest current it can carry losslessly - the critical current. In turn, the critical current can be controlled by adding non-superconducting defects in the superconductor matrix. Here we report on systematic com...
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Attracting sequences of holomorphic automorphisms that agree to a certain order
The basin of attraction of a uniformly attracting sequence of holomorphic automorphisms that agree to a certain order in the common fixed point, is biholomorphic to $\mathbb{C}^n$. We also give sufficient estimates how large this order has to be.
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Repulsive Fermi polarons with negative effective mass
Recent LENS experiment on a 3D Fermi gas has reported a negative effective mass ($m^*<0$) of Fermi polarons in the strongly repulsive regime. There naturally arise a question whether the negative $m^*$ is a precursor of the instability towards phase separation (or itinerant ferromagnetism). In this work, we make use ...
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Entropy Formula for Random $\mathbb{Z}^k$-actions
In this paper, entropies, including measure-theoretic entropy and topological entropy, are considered for random $\mathbb{Z}^k$-actions which are generated by random compositions of the generators of $\mathbb{Z}^k$-actions. Applying Pesin's theory for commutative diffeomorphisms we obtain a measure-theoretic entropy ...
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Kohn anomalies in momentum dependence of magnetic susceptibility of some three-dimensional systems
We study a question of presence of Kohn points, yielding at low temperatures non-analytic momentum dependence of magnetic susceptibility near its maximum, in electronic spectum of some three-dimensional systems. In particular, we consider one-band model on face centered cubic lattice with hopping between nearest and ...
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Stability conditions, $τ$-tilting Theory and Maximal Green Sequences
Extending the notion of maximal green sequences to an abelian category, we characterize the stability functions, as defined by Rudakov, that induce a maximal green sequence in an abelian length category. Furthermore, we use $\tau$-tilting theory to give a description of the wall and chamber structure of any finite di...
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The thermal phase curve offset on tidally- and non-tidally-locked exoplanets: A shallow water model
Using a shallow water model with time-dependent forcing we show that the peak of an exoplanet thermal phase curve is, in general, offset from secondary eclipse when the planet is rotating. That is, the planetary hot-spot is offset from the point of maximal heating (the substellar point) and may lead or lag the forcin...
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On Asymptotic Standard Normality of the Two Sample Pivot
The asymptotic solution to the problem of comparing the means of two heteroscedastic populations, based on two random samples from the populations, hinges on the pivot underpinning the construction of the confidence interval and the test statistic being asymptotically standard Normal, which is known to happen if the ...
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Breakthrough revisited: investigating the requirements for growth of dust beyond the bouncing barrier
For grain growth to proceed effectively and lead to planet formation a number of barriers to growth must be overcome. One such barrier, relevant for compact grains in the inner regions of the disc, is the `bouncing barrier' in which large grains ($\sim$ mm size) tend to bounce off each other rather than sticking. How...
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Extremely high magnetoresistance and conductivity in the type-II Weyl semimetals WP2 and MoP2
The peculiar band structure of semimetals exhibiting Dirac and Weyl crossings can lead to spectacular electronic properties such as large mobilities accompanied by extremely high magnetoresistance. In particular, two closely neighbouring Weyl points of the same chirality are protected from annihilation by structural ...
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Density and current profiles in $U_q(A^{(1)}_2)$ zero range process
The stochastic $R$ matrix for $U_q(A^{(1)}_n)$ introduced recently gives rise to an integrable zero range process of $n$ classes of particles in one dimension. For $n=2$ we investigate how finitely many first class particles fixed as defects influence the grand canonical ensemble of the second class particles. By usi...
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Crystal structure, site selectivity, and electronic structure of layered chalcogenide LaOBiPbS3
We have investigated the crystal structure of LaOBiPbS3 using neutron diffraction and synchrotron X-ray diffraction. From structural refinements, we found that the two metal sites, occupied by Bi and Pb, were differently surrounded by the sulfur atoms. Calculated bond valence sum suggested that one metal site was nea...
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Responses of Pre-transitional Materials with Stress-Generating Defects to External Stimuli: Superelasticity, Supermagnetostriction, Invar and Elinvar Effects
We considered a generic case of pre-transitional materials with static stress-generating defects, dislocations and coherent nano-precipitates, at temperatures close but above the starting temperature of martensitic transformation, Ms. Using the Phase Field Microelasticity theory and 3D simulation, we demonstrated tha...
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On The Robustness of Epsilon Skew Extension for Burr III Distribution on Real Line
The Burr III distribution is used in a wide variety of fields of lifetime data analysis, reliability theory, and financial literature, etc. It is defined on the positive axis and has two shape parameters, say $c$ and $k$. These shape parameters make the distribution quite flexible. They also control the tail behavior...
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Logics for Word Transductions with Synthesis
We introduce a logic, called LT, to express properties of transductions, i.e. binary relations from input to output (finite) words. In LT, the input/output dependencies are modelled via an origin function which associates to any position of the output word, the input position from which it originates. LT is well-suit...
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Topology and strong four fermion interactions in four dimensions
We study massless fermions interacting through a particular four fermion term in four dimensions. Exact symmetries prevent the generation of bilinear fermion mass terms. We determine the structure of the low energy effective action for the auxiliary field needed to generate the four fermion term and find it has an no...
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Augmentor: An Image Augmentation Library for Machine Learning
The generation of artificial data based on existing observations, known as data augmentation, is a technique used in machine learning to improve model accuracy, generalisation, and to control overfitting. Augmentor is a software package, available in both Python and Julia versions, that provides a high level API for ...
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Multilevel Sequential${}^2$ Monte Carlo for Bayesian Inverse Problems
The identification of parameters in mathematical models using noisy observations is a common task in uncertainty quantification. We employ the framework of Bayesian inversion: we combine monitoring and observational data with prior information to estimate the posterior distribution of a parameter. Specifically, we ar...
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Multiparameter actuation of a neutrally-stable shell: a flexible gear-less motor
We have designed and tested experimentally a morphing structure consisting of a neutrally stable thin cylindrical shell driven by a multiparameter piezoelectric actuation. The shell is obtained by plastically deforming an initially flat copper disk, so as to induce large isotropic and almost uniform inelastic curvatu...
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An Evolutionary Game for User Access Mode Selection in Fog Radio Access Networks
The fog radio access network (F-RAN) is a promising paradigm for the fifth generation wireless communication systems to provide high spectral efficiency and energy efficiency. Characterizing users to select an appropriate communication mode among fog access point (F-AP), and device-to-device (D2D) in F-RANs is critic...
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Latent Estimation of GDP, GDP per capita, and Population from Historic and Contemporary Sources
The concepts of Gross Domestic Product (GDP), GDP per capita, and population are central to the study of political science and economics. However, a growing literature suggests that existing measures of these concepts contain considerable error or are based on overly simplistic modeling choices. We address these prob...
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Portfolio Optimization under Fast Mean-reverting and Rough Fractional Stochastic Environment
Fractional stochastic volatility models have been widely used to capture the non-Markovian structure revealed from financial time series of realized volatility. On the other hand, empirical studies have identified scales in stock price volatility: both fast-time scale on the order of days and slow-scale on the order ...
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Triangle Generative Adversarial Networks
A Triangle Generative Adversarial Network ($\Delta$-GAN) is developed for semi-supervised cross-domain joint distribution matching, where the training data consists of samples from each domain, and supervision of domain correspondence is provided by only a few paired samples. $\Delta$-GAN consists of four neural netw...
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Learning Distributions of Meant Color
When a speaker says the name of a color, the color that they picture is not necessarily the same as the listener imagines. Color is a grounded semantic task, but that grounding is not a mapping of a single word (or phrase) to a single point in color-space. Proper understanding of color language requires the capacity ...
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Bose - Einstein condensation of triplons with a weakly broken U(1) symmetry
The low-temperature properties of certain quantum magnets can be described in terms of a Bose-Einstein condensation (BEC) of magnetic quasiparticles (triplons). Some mean-field approaches (MFA) to describe these systems, based on the standard grand canonical ensemble, do not take the anomalous density into account an...
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