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Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment
Network embeddings, which learn low-dimensional representations for each vertex in a large-scale network, have received considerable attention in recent years. For a wide range of applications, vertices in a network are typically accompanied by rich textual information such as user profiles, paper abstracts, etc. We ...
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Spin Precession Experiments for Light Axionic Dark Matter
Axion-like particles are promising candidates to make up the dark matter of the universe, but it is challenging to design experiments that can detect them over their entire allowed mass range. Dark matter in general, and in particular axion-like particles and hidden photons, can be as light as roughly $10^{-22} \;\rm...
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Persistence barcodes and Laplace eigenfunctions on surfaces
We obtain restrictions on the persistence barcodes of Laplace-Beltrami eigenfunctions and their linear combinations on compact surfaces with Riemannian metrics. Some applications to uniform approximation by linear combinations of Laplace eigenfunctions are also discussed.
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DFT study of ionic liquids adsorption on circumcoronene shaped graphene
Carbon materials have a range of properties such as high electrical conductivity, high specific surface area, and mechanical flexibility are relevant for electrochemical applications. Carbon materials are utilised in energy conversion-and-storage devices along with electrolytes of complementary properties. In this wo...
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On the overestimation of the largest eigenvalue of a covariance matrix
In this paper, we use a new approach to prove that the largest eigenvalue of the sample covariance matrix of a normally distributed vector is bigger than the true largest eigenvalue with probability 1 when the dimension is infinite. We prove a similar result for the smallest eigenvalue.
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Thermodynamic Mechanism of Life and Aging
Life is a complex biological phenomenon represented by numerous chemical, physical and biological processes performed by a biothermodynamic system/cell/organism. Both living organisms and inanimate objects are subject to aging, a biological and physicochemical process characterized by changes in biological and thermo...
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Flat families of point schemes for connected graded algebras
We study truncated point schemes of connected graded algebras as families over the parameter space of varying relations for the algebras, proving that the families are flat over the open dense locus where the point schemes achieve the expected (i.e. minimal) dimension. When the truncated point scheme is zero-dimensio...
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Multi-task Learning in the Computerized Diagnosis of Breast Cancer on DCE-MRIs
Hand-crafted features extracted from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) have shown strong predictive abilities in characterization of breast lesions. However, heterogeneity across medical image datasets hinders the generalizability of these features. One of the sources of the heterogeneity...
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Real-time Distracted Driver Posture Classification
In this paper, we present a new dataset for "distracted driver" posture estimation. In addition, we propose a novel system that achieves 95.98% driving posture estimation classification accuracy. The system consists of a genetically-weighted ensemble of Convolutional Neural Networks (CNNs). We show that a weighted en...
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Time Series Cube Data Model
The purpose of this document is to create a data model and its serialization for expressing generic time series data. Already existing IVOA data models are reused as much as possible. The model is also made as generic as possible to be open to new extensions but at the same time closed for modifications. This enables...
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Markov modeling of peptide folding in the presence of protein crowders
We use Markov state models (MSMs) to analyze the dynamics of a $\beta$-hairpin-forming peptide in Monte Carlo (MC) simulations with interacting protein crowders, for two different types of crowder proteins [bovine pancreatic trypsin inhibitor (BPTI) and GB1]. In these systems, at the temperature used, the peptide can...
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Ultra-fast magnetization manipulation using single femtosecond light and hot-electrons pulse
Current induced magnetization manipulation is a key issue for spintronic application. Therefore, deterministic switching of the magnetization at the picoseconds timescale with a single electronic pulse represents a major step towards the future developments of ultrafast spintronic. Here, we have studied the ultrafast...
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Grain Boundary Resistance in Copper Interconnects from an Atomistic Model to a Neural Network
Orientation effects on the resistivity of copper grain boundaries are studied systematically with two different atomistic tight binding methods. A methodology is developed to model the resistivity of grain boundaries using the Embedded Atom Model, tight binding methods and non-equilibrum Green's functions (NEGF). The...
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Some remarkable infinite product identities involving Fibonacci and Lucas numbers
By applying the classic telescoping summation formula and its variants to identities involving inverse hyperbolic tangent functions having inverse powers of the golden ratio as arguments and employing subtle properties of the Fibonacci and Lucas numbers, we derive interesting general infinite product identities invol...
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Limit Theorems in Mallows Distance for Processes with Gibssian Dependence
In this paper, we explore the connection between convergence in distribution and Mallows distance in the context of positively associated random variables. Our results extend some known invariance principles for sequences with FKG property. Applications for processes with Gibbssian dependence structures are included....
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Localized-endemic state transition in the susceptible-infected-susceptible model on networks
It is a longstanding debate concerning the absence of threshold for the susceptible-infected-susceptible spreading model on networks with localized state. The key to resolve this controversy is the dynamical interaction pattern, which has not been uncovered. Here we show that the interaction driving the localized-end...
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Analytic approximation of solutions of parabolic partial differential equations with variable coefficients
A complete family of solutions for the one-dimensional reaction-diffusion equation \[ u_{xx}(x,t)-q(x)u(x,t) = u_t(x,t) \] with a coefficient $q$ depending on $x$ is constructed. The solutions represent the images of the heat polynomials under the action of a transmutation operator. Their use allows one to obtain an ...
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Final-State Constrained Optimal Control via a Projection Operator Approach
In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's method for Trajectory Optimization (PRONTO), which was proposed by Hauser for unconstrained optimal control problems. While in the standa...
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Robust Tracking with Model Mismatch for Fast and Safe Planning: an SOS Optimization Approach
In the pursuit of real-time motion planning, a commonly adopted practice is to compute a trajectory by running a planning algorithm on a simplified, low-dimensional dynamical model, and then employ a feedback tracking controller that tracks such a trajectory by accounting for the full, high-dimensional system dynamic...
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Robust Gaussian Stochastic Process Emulation
We consider estimation of the parameters of a Gaussian Stochastic Process (GaSP), in the context of emulation (approximation) of computer models for which the outcomes are real-valued scalars. The main focus is on estimation of the GaSP parameters through various generalized maximum likelihood methods, mostly involvi...
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Observing the Atmospheres of Known Temperate Earth-sized Planets with JWST
Nine transiting Earth-sized planets have recently been discovered around nearby late M dwarfs, including the TRAPPIST-1 planets and two planets discovered by the MEarth survey, GJ 1132b and LHS 1140b. These planets are the smallest known planets that may have atmospheres amenable to detection with JWST. We present mo...
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Front Propagation for Nonlocal KPP Reaction-Diffusion Equations in Periodic Media
We study front propagation phenomena for a large class of nonlocal KPP-type reaction-diffusion equations in oscillatory environments, which model various forms of population growth with periodic dependence. The nonlocal diffusion is an anisotropic integro-differential operator of order $\alpha \in (0,2)$.
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Distributed Functional Observers for LTI Systems
We study the problem of designing distributed functional observers for LTI systems. Specifically, we consider a setting consisting of a state vector that evolves over time according to a dynamical process. A set of nodes distributed over a communication network wish to collaboratively estimate certain functions of th...
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Wavelet eigenvalue regression for $n$-variate operator fractional Brownian motion
In this contribution, we extend the methodology proposed in Abry and Didier (2017) to obtain the first joint estimator of the real parts of the Hurst eigenvalues of $n$-variate OFBM. The procedure consists of a wavelet regression on the log-eigenvalues of the sample wavelet spectrum. The estimator is shown to be cons...
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Deep Neural Network for Analysis of DNA Methylation Data
Many researches demonstrated that the DNA methylation, which occurs in the context of a CpG, has strong correlation with diseases, including cancer. There is a strong interest in analyzing the DNA methylation data to find how to distinguish different subtypes of the tumor. However, the conventional statistical method...
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One look at the rating of scientific publications and corresponding toy-model
A toy-model of publications and citations processes is proposed. The model shows that the role of randomness in the processes is essential and cannot be ignored. Some other aspects of scientific publications rating are discussed.
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Alignment, Orientation, and Coulomb Explosion of Difluoroiodobenzene Studied with the Pixel Imaging Mass Spectrometry (PImMS) Camera
Laser-induced adiabatic alignment and mixed-field orientation of 2,6-difluoroiodobenzene (C6H3F2I) molecules are probed by Coulomb explosion imaging following either near-infrared strong-field ionization or extreme-ultraviolet multi-photon inner-shell ionization using free-electron laser pulses. The resulting photoel...
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Unsupervised Machine Learning of Open Source Russian Twitter Data Reveals Global Scope and Operational Characteristics
We developed and used a collection of statistical methods (unsupervised machine learning) to extract relevant information from a Twitter supplied data set consisting of alleged Russian trolls who (allegedly) attempted to influence the 2016 US Presidential election. These unsupervised statistical methods allow fast id...
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Distributed, scalable and gossip-free consensus optimization with application to data analysis
Distributed algorithms for solving additive or consensus optimization problems commonly rely on first-order or proximal splitting methods. These algorithms generally come with restrictive assumptions and at best enjoy a linear convergence rate. Hence, they can require many iterations or communications among agents to...
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Consistency of Maximum Likelihood for Continuous-Space Network Models
Network analysis needs tools to infer distributions over graphs of arbitrary size from a single graph. Assuming the distribution is generated by a continuous latent space model which obeys certain natural symmetry and smoothness properties, we establish three levels of consistency for non-parametric maximum likelihoo...
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Consistency Results for Stationary Autoregressive Processes with Constrained Coefficients
We consider stationary autoregressive processes with coefficients restricted to an ellipsoid, which includes autoregressive processes with absolutely summable coefficients. We provide consistency results under different norms for the estimation of such processes using constrained and penalized estimators. As an appli...
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Higher order mobile coverage control with application to localization
Most current results on coverage control using mobile sensors require that one partitioned cell is associated with precisely one sensor. In this paper, we consider a class of coverage control problems involving higher order Voronoi partitions, motivated by applications where more than one sensor is required to monito...
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Borg's Periodicity Theorems for first order self-adjoint systems with complex potentials
A self-adjoint first order system with Hermitian $\pi$-periodic potential $Q(z)$, integrable on compact sets, is considered. It is shown that all zeros of $\Delta + 2e^{-i\int_0^\pi \Im q dt}$ are double zeros if and only if this self-adjoint system is unitarily equivalent to one in which $Q(z)$ is $\frac{\pi}{2}$-pe...
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On the Ubiquity of Information Inconsistency for Conjugate Priors
Informally, "Information Inconsistency" is the property that has been observed in many Bayesian hypothesis testing and model selection procedures whereby the Bayesian conclusion does not become definitive when the data seems to become definitive. An example is that, when performing a t-test using standard conjugate p...
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Competition evolution of Rayleigh-Taylor bubbles
Material mixing induced by a Rayleigh-Taylor instability occurs ubiquitously in either nature or engineering when a light fluid pushes against a heavy fluid, accompanying with the formation and evolution of chaotic bubbles. Its general evolution involves two mechanisms: bubble-merge and bubble-competition. The former...
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Nonlinear oblique projections
We construct nonlinear oblique projections along subalgebras of nilpotent Lie algebras in terms of the Baker-Campbell-Hausdorff multiplication. We prove that these nonlinear projections are real analytic on every Schubert cell of the Grassmann manifold whose points are the subalgebras of the nilpotent Lie algebra und...
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Granger Mediation Analysis of Multiple Time Series with an Application to fMRI
It becomes increasingly popular to perform mediation analysis for complex data from sophisticated experimental studies. In this paper, we present Granger Mediation Analysis (GMA), a new framework for causal mediation analysis of multiple time series. This framework is motivated by a functional magnetic resonance imag...
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Parameterization of Sequence of MFCCs for DNN-based voice disorder detection
In this article a DNN-based system for detection of three common voice disorders (vocal nodules, polyps and cysts; laryngeal neoplasm; unilateral vocal paralysis) is presented. The input to the algorithm is (at least 3-second long) audio recording of sustained vowel sound /a:/. The algorithm was developed as part of ...
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Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems
A key challenge in multi-robot and multi-agent systems is generating solutions that are robust to other self-interested or even adversarial parties who actively try to prevent the agents from achieving their goals. The practicality of existing works addressing this challenge is limited to only small-scale synchronous...
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Structural Connectome Validation Using Pairwise Classification
In this work, we study the extent to which structural connectomes and topological derivative measures are unique to individual changes within human brains. To do so, we classify structural connectome pairs from two large longitudinal datasets as either belonging to the same individual or not. Our data is comprised of...
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Deep Robust Kalman Filter
A Robust Markov Decision Process (RMDP) is a sequential decision making model that accounts for uncertainty in the parameters of dynamic systems. This uncertainty introduces difficulties in learning an optimal policy, especially for environments with large state spaces. We propose two algorithms, RTD-DQN and Deep-RoK...
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Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach
The Fisher information matrix (FIM) is a fundamental quantity to represent the characteristics of a stochastic model, including deep neural networks (DNNs). The present study reveals novel statistics of FIM that are universal among a wide class of DNNs. To this end, we use random weights and large width limits, which...
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An extension problem and trace Hardy inequality for the sublaplacian on $H$-type groups
In this paper we study the extension problem for the sublaplacian on a $H$-type group and use the solutions to prove trace Hardy and Hardy inequalities for fractional powers of the sublaplacian.
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Centered Isotonic Regression: Point and Interval Estimation for Dose-Response Studies
Univariate isotonic regression (IR) has been used for nonparametric estimation in dose-response and dose-finding studies. One undesirable property of IR is the prevalence of piecewise-constant stretches in its estimates, whereas the dose-response function is usually assumed to be strictly increasing. We propose a sim...
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Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection
Measuring domain relevance of data and identifying or selecting well-fit domain data for machine translation (MT) is a well-studied topic, but denoising is not yet. Denoising is concerned with a different type of data quality and tries to reduce the negative impact of data noise on MT training, in particular, neural ...
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Discovering Signals from Web Sources to Predict Cyber Attacks
Cyber attacks are growing in frequency and severity. Over the past year alone we have witnessed massive data breaches that stole personal information of millions of people and wide-scale ransomware attacks that paralyzed critical infrastructure of several countries. Combating the rising cyber threat calls for a multi...
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Higher-degree Smoothness of Perturbations I
In this paper and its sequels, we give an unified treatment of the higher-degree smoothness of admissible perturbations and related results used in the global perturbation method for GW and Floer theories.
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Space Telescope and Optical Reverberation Mapping Project. V. Optical Spectroscopic Campaign and Emission-Line Analysis for NGC 5548
We present the results of an optical spectroscopic monitoring program targeting NGC 5548 as part of a larger multi-wavelength reverberation mapping campaign. The campaign spanned six months and achieved an almost daily cadence with observations from five ground-based telescopes. The H$\beta$ and He II $\lambda$4686 b...
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An Inexact Regularized Newton Framework with a Worst-Case Iteration Complexity of $\mathcal{O}(ε^{-3/2})$ for Nonconvex Optimization
An algorithm for solving smooth nonconvex optimization problems is proposed that, in the worst-case, takes $\mathcal{O}(\epsilon^{-3/2})$ iterations to drive the norm of the gradient of the objective function below a prescribed positive real number $\epsilon$ and can take $\mathcal{O}(\epsilon^{-3})$ iterations to dr...
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An inverse problem for Maxwell's equations with Lipschitz parameters
We consider an inverse boundary value problem for Maxwell's equations, which aims to recover the electromagnetic material properties of a body from measurements on the boundary. We show that a Lipschitz continuous conductivity, electric permittivity, and magnetic permeability are uniquely determined by knowledge of a...
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Context Aware Robot Navigation using Interactively Built Semantic Maps
We discuss the process of building semantic maps, how to interactively label entities in them, and how to use them to enable context-aware navigation behaviors in human environments. We utilize planar surfaces, such as walls and tables, and static objects, such as door signs, as features for our semantic mapping appr...
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Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data
Multimodal sensory data resembles the form of information perceived by humans for learning, and are easy to obtain in large quantities. Compared to unimodal data, synchronization of concepts between modalities in such data provides supervision for disentangling the underlying explanatory factors of each modality. Pre...
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Blind Gain and Phase Calibration via Sparse Spectral Methods
Blind gain and phase calibration (BGPC) is a bilinear inverse problem involving the determination of unknown gains and phases of the sensing system, and the unknown signal, jointly. BGPC arises in numerous applications, e.g., blind albedo estimation in inverse rendering, synthetic aperture radar autofocus, and sensor...
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Reconciling cooperation, biodiversity and stability in complex ecological communities
Empirical observations show that ecological communities can have a huge number of coexisting species, also with few or limited number of resources. These ecosystems are characterized by multiple type of interactions, in particular displaying cooperative behaviors. However, standard modeling of population dynamics bas...
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The Young L Dwarf 2MASS J11193254-1137466 is a Planetary-Mass Binary
We have discovered that the extremely red, low-gravity L7 dwarf 2MASS J11193254-1137466 is a 0.14" (3.6 AU) binary using Keck laser guide star adaptive optics imaging. 2MASS J11193254-1137466 has previously been identified as a likely member of the TW Hydrae Association (TWA). Using our updated photometric distance a...
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Diversity of Abundance Patterns of Light Neutron-capture Elements in Very-metal-poor Stars
We determine the abundances of neutron-capture elements from Sr to Eu for five very-metal-poor stars (-3<[Fe/H]<-2) in the Milky Way halo to reveal the origin of light neutron-capture elements. Previous spectroscopic studies have shown evidence of at least two components in the r-process; one referred to as the "main...
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Hypergames and Cyber-Physical Security for Control Systems
The identification of the Stuxnet worm in 2010 provided a highly publicized example of a cyber attack used to damage an industrial control system physically. This raised public awareness about the possibility of similar attacks against other industrial targets -- including critical infrastructure. In this paper, we u...
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Measuring the academic reputation through citation networks via PageRank
The objective assessment of the prestige of an academic institution is a difficult and hotly debated task. In the last few years, different types of University Rankings have been proposed to quantify the excellence of different research institutions in the world. Albeit met with criticism in some cases, the relevance...
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A Model Order Reduction Algorithm for Estimating the Absorption Spectrum
The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the quantum propagator's eigenspectrum for medium-to-large sized systems, traditional...
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Uniform rank gradient, cost and local-global convergence
We analyze the rank gradient of finitely generated groups with respect to sequences of subgroups of finite index that do not necessarily form a chain, by connecting it to the cost of p.m.p. actions. We generalize several results that were only known for chains before. The connection is made by the notion of local-glo...
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Optimal design of a model energy conversion device
Fuel cells, batteries, thermochemical and other energy conversion devices involve the transport of a number of (electro-)chemical species through distinct materials so that they can meet and react at specified multi-material interfaces. Therefore, morphology or arrangement of these different materials can be critical...
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Mining Communication Data in a Music Community: A Preliminary Analysis
Comments play an important role within online creative communities because they make it possible to foster the production and improvement of authors' artifacts. We investigate how comment-based communication help shape members' behavior within online creative communities. In this paper, we report the results of a pre...
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Multidimensional VlasovPoisson Simulations with High-order Monotonicity- and Positivity-preserving Schemes
We develop new numerical schemes for Vlasov--Poisson equations with high-order accuracy. Our methods are based on a spatially monotonicity-preserving (MP) scheme and are modified suitably so that positivity of the distribution function is also preserved. We adopt an efficient semi-Lagrangian time integration scheme t...
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Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy
Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, effi...
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Stable splitting of mapping spaces via nonabelian Poincaré duality
We use nonabelian Poincaré duality to recover the stable splitting of compactly supported mapping spaces, $\rm{Map_c}$$(M,\Sigma^nX)$, where $M$ is a parallelizable $n$-manifold. Our method for deriving this splitting is new, and naturally extends to give a more general stable splitting of the space of compactly supp...
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Static Gesture Recognition using Leap Motion
In this report, an automated bartender system was developed for making orders in a bar using hand gestures. The gesture recognition of the system was developed using Machine Learning techniques, where the model was trained to classify gestures using collected data. The final model used in the system reached an averag...
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B-spline-like bases for $C^2$ cubics on the Powell-Sabin 12-split
For spaces of constant, linear, and quadratic splines of maximal smoothness on the Powell-Sabin 12-split of a triangle, the so-called S-bases were recently introduced. These are simplex spline bases with B-spline-like properties on the 12-split of a single triangle, which are tied together across triangles in a Bézie...
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Synthesizing Correlations with Computational Likelihood Approach: Vitamin C Data
It is known that the primary source of dietary vitamin C is fruit and vegetables and the plasma level of vitamin C has been considered a good surrogate biomarker of vitamin C intake by fruit and vegetable consumption. To combine the information about association between vitamin C intake and the plasma level of vitami...
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Axion detection via Topological Casimir Effect
We propose a new table-top experimental configuration for the direct detection of dark matter axions with mass in the $(10^{-6} \rm eV - 10^{-2} \rm eV)$ range using non-perturbative effects in a system with non-trivial spatial topology. Different from most experimental setups found in literature on direct dark matte...
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Novel Feature-Based Clustering of Micro-Panel Data (CluMP)
Micro-panel data are collected and analysed in many research and industry areas. Cluster analysis of micro-panel data is an unsupervised learning exploratory method identifying subgroup clusters in a data set which include homogeneous objects in terms of the development dynamics of monitored variables. The supply of ...
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Ab initio effective Hamiltonians for cuprate superconductors
Ab initio low-energy effective Hamiltonians of two typical high-temperature copper-oxide superconductors, whose mother compounds are La$_2$CuO$_4$ and HgBa$_2$CuO$_4$, are derived by utilizing the multi-scale ab initio scheme for correlated electrons (MACE). The effective Hamiltonians obtained in the present study se...
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Longitudinal data analysis using matrix completion
In clinical practice and biomedical research, measurements are often collected sparsely and irregularly in time while the data acquisition is expensive and inconvenient. Examples include measurements of spine bone mineral density, cancer growth through mammography or biopsy, a progression of defect of vision, or asse...
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Emission-line Diagnostics of Nearby HII Regions Including Supernova Hosts
We present a new model of the optical nebular emission from HII regions by combin- ing the results of the Binary Population and Spectral Synthesis (bpass) code with the photoion- ization code cloudy (Ferland et al. 1998). We explore a variety of emission-line diagnostics of these star-forming HII regions and examine ...
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On monomial linearisation and supercharacters of pattern subgroups
Column closed pattern subgroups $U$ of the finite upper unitriangular groups $U_n(q)$ are defined as sets of matrices in $U_n(q)$ having zeros in a prescribed set of columns besides the diagonal ones. We explain Jedlitschky's construction of monomial linearisation and apply this to $C U$ yielding a generalisation of ...
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The Structural Fate of Individual Multicomponent Metal-Oxide Nanoparticles in Polymer Nanoreactors
Multicomponent nanoparticles can be synthesized with either homogeneous or phase-segregated architectures depending on the synthesis conditions and elements incorporated. To understand the parameters that determine their structural fate, multicomponent metal-oxide nanoparticles consisting of combinations of Co, Ni, a...
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On Compression of Unsupervised Neural Nets by Pruning Weak Connections
Unsupervised neural nets such as Restricted Boltzmann Machines(RBMs) and Deep Belif Networks(DBNs), are powerful in automatic feature extraction,unsupervised weight initialization and density estimation. In this paper,we demonstrate that the parameters of these neural nets can be dramatically reduced without affectin...
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A matrix generalization of a theorem of Fine
In 1947 Nathan Fine gave a beautiful product for the number of binomial coefficients $\binom{n}{m}$, for $m$ in the range $0 \leq m \leq n$, that are not divisible by $p$. We give a matrix product that generalizes Fine's formula, simultaneously counting binomial coefficients with $p$-adic valuation $\alpha$ for each ...
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Training Multi-Task Adversarial Network For Extracting Noise-Robust Speaker Embedding
Under noisy environments, to achieve the robust performance of speaker recognition is still a challenging task. Motivated by the promising performance of multi-task training in a variety of image processing tasks, we explore the potential of multi-task adversarial training for learning a noise-robust speaker embeddin...
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Playing Games with Bounded Entropy
In this paper, we consider zero-sum repeated games in which the maximizer is restricted to strategies requiring no more than a limited amount of randomness. Particularly, we analyze the maxmin payoff of the maximizer in two models: the first model forces the maximizer to randomize her action in each stage just by con...
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Exact Hausdorff and packing measures for random self-similar code-trees with necks
Random code-trees with necks were introduced recently to generalise the notion of $V$-variable and random homogeneous sets. While it is known that the Hausdorff and packing dimensions coincide irrespective of overlaps, their exact Hausdorff and packing measure has so far been largely ignored. In this article we consi...
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On Modules over a G-set
Let R be a commutative ring with unity, M a module over R and let S be a G-set for a finite group G. We define a set MS to be the set of elements expressed as the formal finite sum of the form similar to the elements of group ring RG. The set MS is a module over the group ring RG under the addition and the scalar mul...
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Polynomial-time algorithms for the Longest Induced Path and Induced Disjoint Paths problems on graphs of bounded mim-width
We give the first polynomial-time algorithms on graphs of bounded maximum induced matching width (mim-width) for problems that are not locally checkable. In particular, we give $n^{\mathcal{O}(w)}$-time algorithms on graphs of mim-width at most $w$, when given a decomposition, for the following problems: Longest Indu...
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Bug or Not? Bug Report Classification Using N-Gram IDF
Previous studies have found that a significant number of bug reports are misclassified between bugs and non-bugs, and that manually classifying bug reports is a time-consuming task. To address this problem, we propose a bug reports classification model with N-gram IDF, a theoretical extension of Inverse Document Freq...
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Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection
Cell nuclei detection is a challenging research topic because of limitations in cellular image quality and diversity of nuclear morphology, i.e. varying nuclei shapes, sizes, and overlaps between multiple cell nuclei. This has been a topic of enduring interest with promising recent success shown by deep learning meth...
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Anisotropic hydrodynamic turbulence in accretion disks
Recently, the vertical shear instability (VSI) has become an attractive purely hydrodynamic candidate for the anomalous angular momentum transport required for weakly ionized accretion disks. In direct three-dimensional numerical simulations of VSI turbulence in disks, a meridional circulation pattern was observed th...
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Optimal Algorithms for Distributed Optimization
In this paper, we study the optimal convergence rate for distributed convex optimization problems in networks. We model the communication restrictions imposed by the network as a set of affine constraints and provide optimal complexity bounds for four different setups, namely: the function $F(\xb) \triangleq \sum_{i=...
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Evaluation of Classical Features and Classifiers in Brain-Computer Interface Tasks
Brain-Computer Interface (BCI) uses brain signals in order to provide a new method for communication between human and outside world. Feature extraction, selection and classification are among the main matters of concerns in signal processing stage of BCI. In this article, we present our findings about the most effec...
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On exceptional compact homogeneous geometries of type C3
We provide a uniform framework to study the exceptional homogeneous compact geometries of type C3. This framework is then used to show that these are simply connected, answering a question by Kramer and Lytchak, and to calculate the full automorphism groups.
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Intensity estimation of transaction arrivals on the intraday electricity market
In the following paper we present a simple intensity estimation method of transaction arrivals on the intraday electricity market. Assuming the interarrival times distribution, we utilize a maximum likelihood estimation. The method's performance is briefly tested using German Intraday Continuous data. Despite the sim...
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Capacitive Mechanism of Oxygen Functional Groups on Carbon Surface in Supercapacitors
Oxygen functional groups are one of the most important subjects in the study of electrochemical properties of carbon materials which can change the wettability, conductivity and pore size distributions of carbon materials, and can occur redox reactions. In the electrode materials of carbon-based supercapacitors, the ...
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On conditional least squares estimation for affine diffusions based on continuous time observations
We study asymptotic properties of conditional least squares estimators for the drift parameters of two-factor affine diffusions based on continuous time observations. We distinguish three cases: subcritical, critical and supercritical. For all the drift parameters, in the subcritical and supercritical cases, asymptot...
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Discretization error estimates for penalty formulations of a linearized Canham-Helfrich type energy
This paper is concerned with minimization of a fourth-order linearized Canham-Helfrich energy subject to Dirichlet boundary conditions on curves inside the domain. Such problems arise in the modeling of the mechanical interaction of biomembranes with embedded particles. There, the curve conditions result from the imp...
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On the Humphreys conjecture on support varieties of tilting modules
Let $G$ be a simply-connected semisimple algebraic group over an algebraically closed field of characteristic $p$, assumed to be larger than the Coxeter number. The "support variety" of a $G$-module $M$ is a certain closed subvariety of the nilpotent cone of $G$, defined in terms of cohomology for the first Frobenius...
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Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks
Machine learning models have been widely used in security applications such as intrusion detection, spam filtering, and virus or malware detection. However, it is well-known that adversaries are always trying to adapt their attacks to evade detection. For example, an email spammer may guess what features spam detecti...
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Further extension of the generalized Hurwitz-Lerch Zeta function of two variables
The main aim of this paper is to give a new generalization of Hurwitz-Lerch Zeta function of two variables.Also, we investigate several interesting properties such as integral representations, summation formula and a connection with generalized hypergeometric function. To strengthen the main results we also consider ...
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A Physarum-inspired model for the probit-based stochastic user equilibrium problem
Stochastic user equilibrium is an important issue in the traffic assignment problems, tradition models for the stochastic user equilibrium problem are designed as mathematical programming problems. In this article, a Physarum-inspired model for the probit-based stochastic user equilibrium problem is proposed. There a...
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Going Higher in First-Order Quantifier Alternation Hierarchies on Words
We investigate quantifier alternation hierarchies in first-order logic on finite words. Levels in these hierarchies are defined by counting the number of quantifier alternations in formulas. We prove that one can decide membership of a regular language in the levels $\mathcal{B}{\Sigma}_2$ (finite boolean combination...
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Invariance of Ideal Limit Points
Let $\mathcal{I}$ be an analytic P-ideal [respectively, a summable ideal] on the positive integers and let $(x_n)$ be a sequence taking values in a metric space $X$. First, it is shown that the set of ideal limit points of $(x_n)$ is an $F_\sigma$-set [resp., a closet set]. Let us assume that $X$ is also separable an...
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Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching
The unprecedented demand for large amount of data has catalyzed the trend of combining human insights with machine learning techniques, which facilitate the use of crowdsourcing to enlist label information both effectively and efficiently. The classic work on crowdsourcing mainly focuses on the label inference proble...
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Learning With Errors and Extrapolated Dihedral Cosets
The hardness of the learning with errors (LWE) problem is one of the most fruitful resources of modern cryptography. In particular, it is one of the most prominent candidates for secure post-quantum cryptography. Understanding its quantum complexity is therefore an important goal. We show that under quantum polynomia...
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