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An alternative definition of cobordism map of ECH
In this article, we reformulate the cobordism map of embedded contact homology, which is induced by exact symplectic cobordism and defined as direct limit of homomorphisms called filtered ECH cobordism map. The filtered ECH cobordism map is defined by counting embedded holomorphic curves with zero ECH index and we pr...
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Healthy imperfect dark matter from effective theory of mimetic cosmological perturbations
We study the stability of a recently proposed model of scalar-field matter called mimetic dark matter or imperfect dark matter. It has been known that mimetic matter with higher derivative terms suffers from gradient instabilities in scalar perturbations. To seek for an instability-free extension of imperfect dark ma...
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Disorder-protected topological entropy after a quantum quench
Topological phases of matter are considered the bedrock of novel quantum materials as well as ideal candidates for quantum computers that possess robustness at the physical level. The robustness of the topological phase at finite temperature or away from equilibrium is therefore a very desirable feature. Disorder can...
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The evolution of gravitons in accelerating cosmologies: the case of extended gravity
We discuss the production and evolution of cosmological gravitons showing how the cosmological background affects their dynamics. Besides, the detection of cosmological gravitons could constitute an extremely important signature to discriminate among different cosmological models. Here we consider the cases of scalar...
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CO2 packing polymorphism under confinement in cylindrical nanopores
We investigate the effect of cylindrical nano-confinement on the phase behaviour of a rigid model of carbon dioxide using both molecular dynamics and well tempered metadynamics. To this aim we study a simplified pore model across a parameter space comprising pore diameter, CO2-pore wall potential and CO2 density. In ...
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CLIC: Curriculum Learning and Imitation for feature Control in non-rewarding environments
In this paper, we propose an unsupervised reinforcement learning agent called CLIC for Curriculum Learning and Imitation for Control. This agent learns to control features in its environment without external rewards, and observes the actions of a third party agent, Bob, who does not necessarily provide explicit guida...
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On the structure of continua with finite length and Golab's semicontinuity theorem
The main results in this note concern the characterization of the length of continua 1 (Theorems 2.5) and the parametrization of continua with finite length (Theorem 4.4). Using these results we give two independent and relatively elementary proofs of Golab's semicontinuity theorem.
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Identifying combinatorially symmetric Hidden Markov Models
We provide a sufficient criterion for the unique parameter identification of combinatorially symmetric Hidden Markov Models based on the structure of their transition matrix. If the observed states of the chain form a zero forcing set of the graph of the Markov model then it is uniquely identifiable and an explicit r...
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Systems of small linear forms and Diophantine approximation on manifolds
We develop the theory of Diophantine approximation for systems of simultaneously small linear forms, which coefficients are drawn from any given analytic non-degenerate manifolds. This setup originates from a problem of Sprindžuk from the 1970s on approximations to several real numbers by conjugate algebraic numbers....
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Generalized Zero-Shot Learning via Synthesized Examples
We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based architecture, consisting of a probabilistic encoder and a probabilistic conditional decoder, our model can generate novel exemplars from see...
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Dependence and dependence structures: estimation and visualization using distance multivariance
Distance multivariance is a multivariate dependence measure, which can detect dependencies between an arbitrary number of random vectors each of which can have a distinct dimension. Here we discuss several new aspects and present a concise overview. We relax the required moment conditions considerably and show that d...
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Hybrid simulation scheme for volatility modulated moving average fields
We develop a simulation scheme for a class of spatial stochastic processes called volatility modulated moving averages. A characteristic feature of this model is that the behaviour of the moving average kernel at zero governs the roughness of realisations, whereas its behaviour away from zero determines the global pr...
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Thermodynamic dislocation theory for non-uniform plastic deformations
The present paper extends the thermodynamic dislocation theory developed by Langer, Bouchbinder, and Lookmann to non-uniform plastic deformations. The free energy density as well as the positive definite dissipation function are proposed. The governing equations are derived from the variational equation. As illustrat...
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Integrated Fabry-Perot cavities as a mechanism for enhancing micro-ring resonator performance
We propose and experimentally demonstrate the enhancement in the filtering quality (Q) factor of an integrated micro-ring resonator (MRR) by embedding it in an integrated Fabry-Perot (FP) cavity formed by cascaded Sagnac loop reflectors (SLRs). By utilizing coherent interference within the FP cavity to reshape the tr...
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Dark matter spin determination with directional direct detection experiments
If the dark matter particle has spin 0, only two types of WIMP-nucleon interaction can arise from the non-relativistic reduction of renormalisable single-mediator models for dark matter-quark interactions. Based on this crucial observation, we show that about 100 signal events at next generation directional detection...
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Layers and Matroids for the Traveling Salesman's Paths
Gottschalk and Vygen proved that every solution of the subtour elimination linear program for traveling salesman paths is a convex combination of more and more restrictive "generalized Gao-trees". We give a short proof of this fact, as a layered convex combination of bases of a sequence of increasingly restrictive ma...
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Understanding and Comparing Deep Neural Networks for Age and Gender Classification
Recently, deep neural networks have demonstrated excellent performances in recognizing the age and gender on human face images. However, these models were applied in a black-box manner with no information provided about which facial features are actually used for prediction and how these features depend on image prep...
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Variational discretization of a control-constrained parabolic bang-bang optimal control problem
We consider a control-constrained parabolic optimal control problem without Tikhonov term in the tracking functional. For the numerical treatment, we use variational discretization of its Tikhonov regularization: For the state and the adjoint equation, we apply Petrov-Galerkin schemes from [Daniels et al 2015] in tim...
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Determining r-Robustness of Arbitrary Digraphs Using Zero-One Linear Integer Programming
There has been an increase in the use of resilient control algorithms based on the graph theoretic properties of $r$- and $(r,s)$-robustness. These algorithms guarantee consensus of normally behaving agents in the presence of a bounded number of arbitrarily misbehaving agents if the values of the integers $r$ and $s$...
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Uncertainty quantification in graph-based classification of high dimensional data
Classification of high dimensional data finds wide-ranging applications. In many of these applications equipping the resulting classification with a measure of uncertainty may be as important as the classification itself. In this paper we introduce, develop algorithms for, and investigate the properties of, a variety...
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Defect-induced large spin-orbit splitting in the monolayer of PtSe$_2$
The effect of spin-orbit coupling (SOC) on the electronic properties of monolayer (ML) PtSe$_2$ is dictated by the presence of the crystal inversion symmetry to exhibit spin polarized band without characteristic of spin splitting. Through fully-relativistic density-functional theory calculations, we show that large s...
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Clusters of Integers with Equal Total Stopping Times in the 3x + 1 Problem
The clustering of integers with equal total stopping times has long been observed in the 3x + 1 Problem, and a number of elementary results about it have been used repeatedly in the literature. In this paper we introduce a simple recursively defined function C(n), and we use it to give a necessary and sufficient cond...
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Modelling the Milky Way's globular cluster system
We construct a model for the Galactic globular cluster system based on a realistic gravitational potential and a distribution function (DF) analytic in the action integrals. The DF comprises disc and halo components whose functional forms resemble those recently used to describe the stellar discs and stellar halo. We...
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Diversity-aware Multi-Video Summarization
Most video summarization approaches have focused on extracting a summary from a single video; we propose an unsupervised framework for summarizing a collection of videos. We observe that each video in the collection may contain some information that other videos do not have, and thus exploring the underlying compleme...
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Derivation relations and duality for the sum of multiple zeta values
We show that the duality relation for the sum of multiple zeta values with fixed weight, depth and $k_1$ is deduced from the derivation relations, which was first conjectured by N. Kawasaki and T. Tanaka.
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Machine learning techniques to select Be star candidates. An application in the OGLE-IV Gaia south ecliptic pole field
Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to train an automatic classification system. Quantities related to the magnitude de...
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Infinite-Dimensionality in Quantum Foundations: W*-algebras as Presheaves over Matrix Algebras
In this paper, W*-algebras are presented as canonical colimits of diagrams of matrix algebras and completely positive maps. In other words, matrix algebras are dense in W*-algebras.
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MSE estimates for multitaper spectral estimation and off-grid compressive sensing
We obtain estimates for the Mean Squared Error (MSE) for the multitaper spectral estimator and certain compressive acquisition methods for multi-band signals. We confirm a fact discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]: assuming bandwidth $W$ and $N$ time domain observations,...
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Communication-Free Parallel Supervised Topic Models
Embarrassingly (communication-free) parallel Markov chain Monte Carlo (MCMC) methods are commonly used in learning graphical models. However, MCMC cannot be directly applied in learning topic models because of the quasi-ergodicity problem caused by multimodal distribution of topics. In this paper, we develop an embar...
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Multilayer Network Model of Movie Script
Network models have been increasingly used in the past years to support summarization and analysis of narratives, such as famous TV series, books and news. Inspired by social network analysis, most of these models focus on the characters at play. The network model well captures all characters interactions, giving a b...
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On the Performance of Millimeter Wave-based RF-FSO Multi-hop and Mesh Networks
This paper studies the performance of multi-hop and mesh networks composed of millimeter wave (MMW)-based radio frequency (RF) and free-space optical (FSO) links. The results are obtained in cases with and without hybrid automatic repeat request (HARQ). Taking the MMW characteristics of the RF links into account, we ...
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Pi Visits Manhattan
Is it possible to draw a circle in Manhattan, using only its discrete network of streets and boulevards? In this study, we will explore the construction and properties of circular paths on an integer lattice, a discrete space where the distance between two points is not governed by the familiar Euclidean metric, but ...
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A Bernstein Inequality For Exponentially Growing Graphs
In this article we present a Bernstein inequality for sums of random variables which are defined on a graphical network whose nodes grow at an exponential rate. The inequality can be used to derive concentration inequalities in highly-connected networks. It can be useful to obtain consistency properties for nonparame...
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Monolithic InGaAs nanowire array lasers on silicon-on-insulator operating at room temperature
Chip-scale integrated light sources are a crucial component in a broad range of photonics applications. III-V semiconductor nanowire emitters have gained attention as a fascinating approach due to their superior material properties, extremely compact size, and the capability to grow directly on lattice-mismatched sil...
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DMFT study on the electron-hole asymmetry of the electron correlation strength in the high Tc cuprates
Recent experiments revealed a striking asymmetry in the phase diagram of the high temperature cuprate superconductors. The correlation effect seems strong in the hole-doped systems and weak in the electron-doped systems. On the other hand, a recent theoretical study shows that the interaction strengths (the Hubbard U...
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On the Information Theoretic Distance Measures and Bidirectional Helmholtz Machines
By establishing a connection between bi-directional Helmholtz machines and information theory, we propose a generalized Helmholtz machine. Theoretical and experimental results show that given \textit{shallow} architectures, the generalized model outperforms the previous ones substantially.
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KMS states on the C*-algebras of Fell bundles over groupoids
We consider fiberwise singly generated Fell-bundles over etale groupoids. Given a continuous real-valued 1-cocycle on the groupoid, there is a natural dynamics on the cross-sectional algebra of the Fell bundle. We study the Kubo-Martin-Schwinger equilibrium states for this dynamics. Following work of Neshveyev on equ...
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Object Detection Using Deep CNNs Trained on Synthetic Images
The need for large annotated image datasets for training Convolutional Neural Networks (CNNs) has been a significant impediment for their adoption in computer vision applications. We show that with transfer learning an effective object detector can be trained almost entirely on synthetically rendered datasets. We app...
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Breaking the 3/2 barrier for unit distances in three dimensions
We prove that every set of $n$ points in $\mathbb{R}^3$ spans $O(n^{295/197+\epsilon})$ unit distances. This is an improvement over the previous bound of $O(n^{3/2})$. A key ingredient in the proof is a new result for cutting circles in $\mathbb{R}^3$ into pseudo-segments.
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Periodic orbits of planets in binary systems
Periodic solutions of the three body problem are very important for understanding its dynamics either in a theoretical framework or in various applications in celestial mechanics. In this paper we discuss the computation and continuation of periodic orbits for planetary systems. The study is restricted to coplanar mo...
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Review of image quality measures for solar imaging
The observations of solar photosphere from the ground encounter significant problems due to the presence of Earth's turbulent atmosphere. Prior to applying image reconstruction techniques, the frames obtained in most favorable atmospheric conditions (so-called lucky frames) have to be carefully selected. However, the...
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Joint Maximum Likelihood Estimation for High-dimensional Exploratory Item Response Analysis
Multidimensional item response theory is widely used in education and psychology for measuring multiple latent traits. However, exploratory analysis of large-scale item response data with many items, respondents, and latent traits is still a challenge. In this paper, we consider a high-dimensional setting that both t...
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Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss, and Simpson's Paradox
Statistical learning using imprecise probabilities is gaining more attention because it presents an alternative strategy for reducing irreplicable findings by freeing the user from the task of making up unwarranted high-resolution assumptions. However, model updating as a mathematical operation is inherently exact, h...
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Planar segment processes with reference mark distributions, modeling and estimation
The paper deals with planar segment processes given by a density with respect to the Poisson process. Parametric models involve reference distributions of directions and/or lengths of segments. These distributions generally do not coincide with the corresponding observed distributions. Statistical methods are present...
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A Note on Bayesian Model Selection for Discrete Data Using Proper Scoring Rules
We consider the problem of choosing between parametric models for a discrete observable, taking a Bayesian approach in which the within-model prior distributions are allowed to be improper. In order to avoid the ambiguity in the marginal likelihood function in such a case, we apply a homogeneous scoring rule. For the...
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Quantum criticality in many-body parafermion chains
We construct local generalizations of 3-state Potts models with exotic critical points. We analytically show that these are described by non-diagonal modular invariant partition functions of products of $Z_3$ parafermion or $u(1)_6$ conformal field theories (CFTs). These correspond either to non-trivial permutation i...
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Simulation-based reachability analysis for nonlinear systems using componentwise contraction properties
A shortcoming of existing reachability approaches for nonlinear systems is the poor scalability with the number of continuous state variables. To mitigate this problem we present a simulation-based approach where we first sample a number of trajectories of the system and next establish bounds on the convergence or di...
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User Donations in a Crowdsourced Video System
Crowdsourced video systems like YouTube and Twitch.tv have been a major internet phenomenon and are nowadays entertaining over a billion users. In addition to video sharing and viewing, over the years they have developed new features to boost the community engagement and some managed to attract users to donate, to th...
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Dynein catch bond as a mediator of codependent bidirectional cellular transport
Intracellular bidirectional transport of cargo on Microtubule filaments is achieved by the collective action of oppositely directed dynein and kinesin motors. Experimental investigations probing the nature of bidirectional transport have found that in certain cases, inhibiting the activity of one type of motor result...
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Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices
We study the asymptotic distributions of the spiked eigenvalues and the largest nonspiked eigenvalue of the sample covariance matrix under a general covariance matrix model with divergent spiked eigenvalues, while the other eigenvalues are bounded but otherwise arbitrary. The limiting normal distribution for the spik...
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Nonparametric Poisson regression from independent and weakly dependent observations by model selection
We consider the non-parametric Poisson regression problem where the integer valued response $Y$ is the realization of a Poisson random variable with parameter $\lambda(X)$. The aim is to estimate the functional parameter $\lambda$ from independent or weakly dependent observations $(X_1,Y_1),\ldots,(X_n,Y_n)$ in a ran...
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Ontology-Aware Token Embeddings for Prepositional Phrase Attachment
Type-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignoring the inherent lexical ambiguity in language. Instead, we embed semantic concepts (or synsets) as defined in WordNet and represent a word token in a particular context by estimating a distr...
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Bayesian Detection of Abnormal ADS in Mutant Caenorhabditis elegans Embryos
Cell division timing is critical for cell fate specification and morphogenesis during embryogenesis. How division timings are regulated among cells during development is poorly understood. Here we focus on the comparison of asynchrony of division between sister cells (ADS) between wild-type and mutant individuals of ...
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Towards a constraint solver for proving confluence with invariant and equivalence of realistic CHR programs
Confluence of a nondeterministic program ensures a functional input-output relation, freeing the programmer from considering the actual scheduling strategy, and allowing optimized and perhaps parallel implementations. The more general property of confluence modulo equivalence ensures that equivalent inputs are relate...
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cGANs with Projection Discriminator
We propose a novel, projection based way to incorporate the conditional information into the discriminator of GANs that respects the role of the conditional information in the underlining probabilistic model. This approach is in contrast with most frameworks of conditional GANs used in application today, which use th...
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The QLBS Q-Learner Goes NuQLear: Fitted Q Iteration, Inverse RL, and Option Portfolios
The QLBS model is a discrete-time option hedging and pricing model that is based on Dynamic Programming (DP) and Reinforcement Learning (RL). It combines the famous Q-Learning method for RL with the Black-Scholes (-Merton) model's idea of reducing the problem of option pricing and hedging to the problem of optimal re...
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InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity
We demonstrate an approach to face attribute detection that retains or improves attribute detection accuracy across gender and race subgroups by learning demographic information prior to learning the attribute detection task. The system, which we call InclusiveFaceNet, detects face attributes by transferring race and...
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Reputation is required for cooperation to emerge in dynamic networks
Melamed, Harrell, and Simpson have recently reported on an experiment which appears to show that cooperation can arise in a dynamic network without reputational knowledge, i.e., purely via dynamics [1]. We believe that their experimental design is actually not testing this, in so far as players do know the last actio...
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Active Anomaly Detection via Ensembles
In critical applications of anomaly detection including computer security and fraud prevention, the anomaly detector must be configurable by the analyst to minimize the effort on false positives. One important way to configure the anomaly detector is by providing true labels for a few instances. We study the problem ...
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Effect of Decreasing Cobalt Content on the Electrochemical Properties and Structural Stability of Li_(1-x)Ni_(y)Co_(z)Al_(0.05)O_(2) Type Cathode Materials
In Lithium ion batteries (LIBs), proper design of cathode materials influences its intercalation behavior, overall cost, structural stability, and its impact on environment. At present, the most common type of cathode materials, NCA , has very high cobalt concentration. Since cobalt is toxic and expensive, the existi...
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Dispersive estimates for massive Dirac operators in dimension two
We study the massive two dimensional Dirac operator with an electric potential. In particular, we show that the $t^{-1}$ decay rate holds in the $L^1\to L^\infty$ setting if the threshold energies are regular. We also show these bounds hold in the presence of s-wave resonances at the threshold. We further show that, ...
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A novel agent-based simulation framework for sensing in complex adaptive environments
In this paper we present a novel Formal Agent-Based Simulation framework (FABS). FABS uses formal specification as a means of clear description of wireless sensor networks (WSN) sensing a Complex Adaptive Environment. This specification model is then used to develop an agent-based model of both the wireless sensor ne...
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Transversal fluctuations of the ASEP, stochastic six vertex model, and Hall-Littlewood Gibbsian line ensembles
We consider the ASEP and the stochastic six vertex model started with step initial data. After a long time, $T$, it is known that the one-point height function fluctuations for these systems are of order $T^{1/3}$. We prove the KPZ prediction of $T^{2/3}$ scaling in space. Namely, we prove tightness (and Brownian abs...
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Instantons in self-organizing logic gates
Self-organizing logic is a recently-suggested framework that allows the solution of Boolean truth tables "in reverse," i.e., it is able to satisfy the logical proposition of gates regardless to which terminal(s) the truth value is assigned ("terminal-agnostic logic"). It can be realized if time non-locality (memory) ...
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Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments
A robot that can carry out a natural-language instruction has been a dream since before the Jetsons cartoon series imagined a life of leisure mediated by a fleet of attentive robot helpers. It is a dream that remains stubbornly distant. However, recent advances in vision and language methods have made incredible prog...
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Dissecting spin-phonon equilibration in ferrimagnetic insulators by ultrafast lattice excitation
To gain control over magnetic order on ultrafast time scales, a fundamental understanding of the way electron spins interact with the surrounding crystal lattice is required. However, measurement and analysis even of basic collective processes such as spin-phonon equilibration have remained challenging. Here, we dire...
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Inferring health conditions from fMRI-graph data
Automated classification methods for disease diagnosis are currently in the limelight, especially for imaging data. Classification does not fully meet a clinician's needs, however: in order to combine the results of multiple tests and decide on a course of treatment, a clinician needs the likelihood of a given health...
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Rich-clubness test: how to determine whether a complex network has or doesn't have a rich-club?
The rich-club concept has been introduced in order to characterize the presence of a cohort of nodes with a large number of links (rich nodes) that tend to be well connected between each other, creating a tight group (club). Rich-clubness defines the extent to which a network displays a topological organization chara...
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Structured Variational Inference for Coupled Gaussian Processes
Sparse variational approximations allow for principled and scalable inference in Gaussian Process (GP) models. In settings where several GPs are part of the generative model, theses GPs are a posteriori coupled. For many applications such as regression where predictive accuracy is the quantity of interest, this coupl...
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Imaging anyons with scanning tunneling microscopy
Anyons are exotic quasi-particles with fractional charge that can emerge as fundamental excitations of strongly interacting topological quantum phases of matter. Unlike ordinary fermions and bosons, they may obey non-abelian statistics--a property that would help realize fault tolerant quantum computation. Non-abelia...
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Proof of Correspondence between Keys and Encoding Maps in an Authentication Code
In a former paper the authors introduced two new systematic authentication codes based on the Gray map over a Galois ring. In this paper, it is proved the one-to-one onto correspondence between keys and encoding maps for the second introduced authentication code.
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Following the density perturbations through a bounce with AdS/CFT Correspondence
A bounce universe model, known as the coupled-scalar-tachyon bounce (CSTB) universe, has been shown to solve the Horizon, Flatness and Homogeneity problems as well as the Big Bang Singularity problem. Furthermore a scale invariant spectrum of primordial density perturbations generated from the phase of pre-bounce con...
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Privacy in Information-Rich Intelligent Infrastructure
Intelligent infrastructure will critically rely on the dense instrumentation of sensors and actuators that constantly transmit streaming data to cloud-based analytics for real-time monitoring. For example, driverless cars communicate real-time location and other data to companies like Google, which aggregate regional...
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Towards equation of state for a market: A thermodynamical paradigm of economics
Foundations of equilibrium thermodynamics are the equation of state (EoS) and four postulated laws of thermodynamics. We use equilibrium thermodynamics paradigms in constructing the EoS for microeconomics system that is a market. This speculation is hoped to be first step towards whole pictures of thermodynamical par...
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On the sub-Gaussianity of the Beta and Dirichlet distributions
We obtain the optimal proxy variance for the sub-Gaussianity of Beta distribution, thus proving upper bounds recently conjectured by Elder (2016). We provide different proof techniques for the symmetrical (around its mean) case and the non-symmetrical case. The technique in the latter case relies on studying the ordi...
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Chaos in three coupled rotators: From Anosov dynamics to hyperbolic attractors
Starting from Anosov chaotic dynamics of geodesic flow on a surface of negative curvature, we develop and consider a number of self-oscillatory systems including those with hinged mechanical coupling of three rotators and a system of rotators interacting through a potential function. These results are used to design ...
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A novel analytical method for analysis of electromagnetic scattering from inhomogeneous spherical structures using duality principles
In this article, a novel analytical approach is presented for the analysis of electromagnetic (EM) scattering from radially inhomogeneous spherical structures (RISSs) based on the duality principle. According to the spherical symmetry, similar angular dependencies in all the regions are considered using spherical har...
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Causal Inference with Two Versions of Treatment
Causal effects are commonly defined as comparisons of the potential outcomes under treatment and control, but this definition is threatened by the possibility that the treatment or control condition is not well-defined, existing instead in more than one version. A simple, widely applicable analysis is proposed to add...
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Characterization of Multi-scale Invariant Random Fields
Applying certain flexible geometric sampling of a multi-scale invariant (MSI) field we provide a multi-dimensional multi-selfsimilar field which has a one to one correspondence with such sampled MSI field. This sampling enables us to characterize harmonic-like representation and spectral density function of the sampl...
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Interpretable 3D Human Action Analysis with Temporal Convolutional Networks
The discriminative power of modern deep learning models for 3D human action recognition is growing ever so potent. In conjunction with the recent resurgence of 3D human action representation with 3D skeletons, the quality and the pace of recent progress have been significant. However, the inner workings of state-of-t...
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Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
t-distributed Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization that has become widely popular in recent years. Efficient implementations of t-SNE are available, but they scale poorly to datasets with hundreds of thousands to millions of high dimensional data-points....
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An arithmetic site of Connes-Consani type for imaginary quadratic fields with class number 1
We construct, for imaginary quadratic number fields with class number 1, an arithmetic site of Connes-Consani type. The main difficulty here is that the constructions of Connes and Consani and part of their results strongly rely on the natural order existing on real numbers which is compatible with basic arithmetic o...
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Linear Matrix Inequalities for Physically-Consistent Inertial Parameter Identification: A Statistical Perspective on the Mass Distribution
With the increased application of model-based whole-body control in legged robots, there has been a resurgence of research interest into methods for accurate system identification. An important class of methods focuses on the inertial parameters of rigid-body systems. These parameters consist of the mass, first mass ...
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Simultaneous Block-Sparse Signal Recovery Using Pattern-Coupled Sparse Bayesian Learning
In this paper, we consider the block-sparse signals recovery problem in the context of multiple measurement vectors (MMV) with common row sparsity patterns. We develop a new method for recovery of common row sparsity MMV signals, where a pattern-coupled hierarchical Gaussian prior model is introduced to characterize ...
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A temperate rocky super-Earth transiting a nearby cool star
M dwarf stars, which have masses less than 60 per cent that of the Sun, make up 75 per cent of the population of the stars in the Galaxy [1]. The atmospheres of orbiting Earth-sized planets are observationally accessible via transmission spectroscopy when the planets pass in front of these stars [2,3]. Statistical re...
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Boundary driven Brownian gas
We consider a gas of independent Brownian particles on a bounded interval in contact with two particle reservoirs at the endpoints. Due to the Brownian nature of the particles, infinitely many particles enter and leave the system in each time interval. Nonetheless, the dynamics can be constructed as a Markov process ...
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Fully Resolved Numerical Simulations of Fused Deposition Modeling. Part II-Solidification, Residual Stresses, and Modeling of the Nozzle
Purpose - This paper continues the development of a comprehensive methodology for fully resolved numerical simulations of fusion deposition modeling. Design/methodology/approach - A front-tracking/finite volume method introduced in Part I to simulate the heat transfer and fluid dynamics of the deposition of a polymer...
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High Dimensional Cluster Analysis Using Path Lengths
A hierarchical scheme for clustering data is presented which applies to spaces with a high number of dimension ($N_{_{D}}>3$). The data set is first reduced to a smaller set of partitions (multi-dimensional bins). Multiple clustering techniques are used, including spectral clustering, however, new techniques are also...
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Forecasting elections using compartmental models of infections
To forecast political elections, popular pollsters gather polls and combine information from them with fundamental data such as historical trends, the national economy, and incumbency. This process is complicated, and it includes many subjective choices (e.g., when identifying likely voters, estimating turnout, and q...
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Online Learning Without Prior Information
The vast majority of optimization and online learning algorithms today require some prior information about the data (often in the form of bounds on gradients or on the optimal parameter value). When this information is not available, these algorithms require laborious manual tuning of various hyperparameters, motiva...
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Sparse Identification for Nonlinear Optical Communication Systems: SINO Method
We introduce low complexity machine learning based approach for mitigating nonlinear impairments in optical fiber communications systems. The immense intricacy of the problem calls for the development of "smart" methodology, simplifying the analysis without losing the key features that are important for recovery of t...
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Serial Correlations in Single-Subject fMRI with Sub-Second TR
When performing statistical analysis of single-subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under-estimated resulting in increased false-positive rates. Serial correlations in fMRI data are commonly ch...
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Randomization-based Inference for Bernoulli-Trial Experiments and Implications for Observational Studies
We present a randomization-based inferential framework for experiments characterized by a strongly ignorable assignment mechanism where units have independent probabilities of receiving treatment. Previous works on randomization tests often assume these probabilities are equal within blocks of units. We consider the ...
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Cloaking using complementary media for electromagnetic waves
Negative index materials are artificial structures whose refractive index has negative value over some frequency range. The study of these materials has attracted a lot of attention in the scientific community not only because of their many potential interesting applications but also because of challenges in understa...
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Deterministic parallel analysis: An improved method for selecting the number of factors and principal components
Factor analysis and principal component analysis (PCA) are used in many application areas. The first step, choosing the number of components, remains a serious challenge. Our work proposes improved methods for this important problem. One of the most popular state-of-the-art methods is Parallel Analysis (PA), which co...
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Laplacian Spectrum of non-commuting graphs of finite groups
In this paper, we compute the Laplacian spectrum of non-commuting graphs of some classes of finite non-abelian groups. Our computations reveal that the non-commuting graphs of all the groups considered in this paper are L-integral. We also obtain some conditions on a group $G$ so that its non-commuting graph is L-int...
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Application of Coulomb energy density functional for atomic nuclei: Case studies of local density approximation and generalized gradient approximation
We test the Coulomb exchange and correlation energy density functionals of electron systems for atomic nuclei in the local density approximation (LDA) and the generalized gradient approximation (GGA). For the exchange Coulomb energies, it is found that the deviation between the LDA and GGA ranges from around $ 11 \, ...
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Transient frequency control with regional cooperation for power networks
This paper proposes a centralized and a distributed sub-optimal control strategy to maintain in safe regions the real-time transient frequencies of a given collection of buses, and simultaneously preserve asymptotic stability of the entire network. In a receding horizon fashion, the centralized control input is obtai...
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Unsupervised prototype learning in an associative-memory network
Unsupervised learning in a generalized Hopfield associative-memory network is investigated in this work. First, we prove that the (generalized) Hopfield model is equivalent to a semi-restricted Boltzmann machine with a layer of visible neurons and another layer of hidden binary neurons, so it could serve as the build...
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One-Step Fabrication of pH-Responsive Membranes and Microcapsules through Interfacial H-Bond Polymer Complexation
Biocompatible microencapsulation is of widespread interest for the targeted delivery of active species in fields such as pharmaceuticals, cosmetics and agro-chemistry. Capsules obtained by the self-assembly of polymers at interfaces enable the combination of responsiveness to stimuli, biocompatibility and scaled up p...
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