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Isometric copies of $l^\infty$ in Cesàro-Orlicz function spaces
We characterize Cesàro-Orlicz function spaces $Ces_{\varphi}$ containing order isomorphically isometric copy of $l^\infty$. We discuss also some useful applicable conditions sufficient for the existence of such a copy.
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Modeling non-stationary extreme dependence with stationary max-stable processes and multidimensional scaling
Modeling the joint distribution of extreme weather events in multiple locations is a challenging task with important applications. In this study, we use max-stable models to study extreme daily precipitation events in Switzerland. The non-stationarity of the spatial process at hand involves important challenges, whic...
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MOEMS deformable mirror testing in cryo for future optical instrumentation
MOEMS Deformable Mirrors (DM) are key components for next generation instruments with innovative adaptive optics systems, in existing telescopes and in the future ELTs. These DMs must perform at room temperature as well as in cryogenic and vacuum environment. Ideally, the MOEMS-DMs must be designed to operate in such...
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Remote Sensing Image Scene Classification: Benchmark and State of the Art
Remote sensing image scene classification plays an important role in a wide range of applications and hence has been receiving remarkable attention. During the past years, significant efforts have been made to develop various datasets or present a variety of approaches for scene classification from remote sensing ima...
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The Network of U.S. Mutual Fund Investments: Diversification, Similarity and Fragility throughout the Global Financial Crisis
Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We investigate the bipar...
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Removal of Salt and Pepper noise from Gray-Scale and Color Images: An Adaptive Approach
An efficient adaptive algorithm for the removal of Salt and Pepper noise from gray scale and color image is presented in this paper. In this proposed method first a 3X3 window is taken and the central pixel of the window is considered as the processing pixel. If the processing pixel is found as uncorrupted, then it i...
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On the distance and algorithms of strong product digraphs
Strong product is an efficient way to construct a larger digraph through some specific small digraphs. The large digraph constructed by the strong product method contains the factor digraphs as its subgraphs, and can retain some good properties of the factor digraphs. The distance of digraphs is one of the most basic...
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Global weak solution to the viscous two-fluid model with finite energy
In this paper, we prove the existence of global weak solutions to the compressible two-fluid Navier-Stokes equations in three dimensional space. The pressure depends on two different variables from the continuity equations. We develop an argument of variable reduction for the pressure law. This yields to the strong c...
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Privacy Preserving and Collusion Resistant Energy Sharing
Energy has been increasingly generated or collected by different entities on the power grid (e.g., universities, hospitals and householdes) via solar panels, wind turbines or local generators in the past decade. With local energy, such electricity consumers can be considered as "microgrids" which can simulataneously ...
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Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes
Word embeddings use vectors to represent words such that the geometry between vectors captures semantic relationship between the words. In this paper, we develop a framework to demonstrate how the temporal dynamics of the embedding can be leveraged to quantify changes in stereotypes and attitudes toward women and eth...
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Infinite Mixture of Inverted Dirichlet Distributions
In this work, we develop a novel Bayesian estimation method for the Dirichlet process (DP) mixture of the inverted Dirichlet distributions, which has been shown to be very flexible for modeling vectors with positive elements. The recently proposed extended variational inference (EVI) framework is adopted to derive an...
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$Ψ$ec: A Local Spectral Exterior Calculus
We introduce $\Psi$ec, a local spectral exterior calculus that provides a discretization of Cartan's exterior calculus of differential forms using wavelet functions. Our construction consists of differential form wavelets with flexible directional localization, between fully isotropic and curvelet- and ridgelet-like,...
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Ultraslow fluctuations in the pseudogap states of HgBa$_{2}$CaCu$_{2}$O$_{6+d}$
We report the transverse relaxation rates 1/$T_2$'s of the $^{63}$Cu nuclear spin-echo envelope for double-layer high-$T_c$ cuprate superconductors HgBa$_{2}$CaCu$_{2}$O$_{6+d}$ from underdoped to overdoped. The relaxation rate 1/$T_{2L}$ of the exponential function (Lorentzian component) shows a peak at 220$-$240 K ...
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Multi-Scale Wavelet Domain Residual Learning for Limited-Angle CT Reconstruction
Limited-angle computed tomography (CT) is often used in clinical applications such as C-arm CT for interventional imaging. However, CT images from limited angles suffers from heavy artifacts due to incomplete projection data. Existing iterative methods require extensive calculations but can not deliver satisfactory r...
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Helium-like atoms. The Green's function approach to the Fock expansion calculations
The renewed Green's function approach to calculating the angular Fock coefficients, $\psi_{k,p}(\alpha,\theta)$ is presented. The final formulas are simplified and specified to be applicable for analytical as well as numerical calculations. The Green's function formulas with the hyperspherical angles $\theta=0,\pi$ (...
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Butterfly Effect: Bidirectional Control of Classification Performance by Small Additive Perturbation
This paper proposes a new algorithm for controlling classification results by generating a small additive perturbation without changing the classifier network. Our work is inspired by existing works generating adversarial perturbation that worsens classification performance. In contrast to the existing methods, our w...
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Secrecy Outage Analysis for Downlink Transmissions in the Presence of Randomly Located Eavesdroppers
We analyze the secrecy outage probability in the downlink for wireless networks with spatially (Poisson) distributed eavesdroppers (EDs) under the assumption that the base station employs transmit antenna selection (TAS) to enhance secrecy performance. We compare the cases where the receiving user equipment (UE) oper...
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Defining Equitable Geographic Districts in Road Networks via Stable Matching
We introduce a novel method for defining geographic districts in road networks using stable matching. In this approach, each geographic district is defined in terms of a center, which identifies a location of interest, such as a post office or polling place, and all other network vertices must be labeled with the cen...
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End-to-end Lung Nodule Detection in Computed Tomography
Computer aided diagnostic (CAD) system is crucial for modern med-ical imaging. But almost all CAD systems operate on reconstructed images, which were optimized for radiologists. Computer vision can capture features that is subtle to human observers, so it is desirable to design a CAD system op-erating on the raw data...
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Fairness with Dynamics
It has recently been shown that if feedback effects of decisions are ignored, then imposing fairness constraints such as demographic parity or equality of opportunity can actually exacerbate unfairness. We propose to address this challenge by modeling feedback effects as the dynamics of a Markov decision processes (M...
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Exploring extra dimensions through inflationary tensor modes
Predictions of inflationary schemes can be influenced by the presence of extra dimensions. This could be of particular relevance for the spectrum of gravitational waves in models where the extra dimensions provide a brane-world solution to the hierarchy problem. Apart from models of large as well as exponentially war...
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Elements of $C^*$-algebras Attaining Their Norm in a Finite-Dimensional Representation
We characterize the class of RFD $C^*$-algebras as those containing a dense subset of elements that attain their norm under a finite-dimensional representation. We show further that this subset is the whole space precisely when every irreducible representation of the $C^*$-algebra is finite-dimensional, which is equi...
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A probability inequality for sums of independent Banach space valued random variables
Let $(\mathbf{B}, \|\cdot\|)$ be a real separable Banach space. Let $\varphi(\cdot)$ and $\psi(\cdot)$ be two continuous and increasing functions defined on $[0, \infty)$ such that $\varphi(0) = \psi(0) = 0$, $\lim_{t \rightarrow \infty} \varphi(t) = \infty$, and $\frac{\psi(\cdot)}{\varphi(\cdot)}$ is a nondecreasin...
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Including Uncertainty when Learning from Human Corrections
It is difficult for humans to efficiently teach robots how to correctly perform a task. One intuitive solution is for the robot to iteratively learn the human's preferences from corrections, where the human improves the robot's current behavior at each iteration. When learning from corrections, we argue that while th...
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Gated-Attention Architectures for Task-Oriented Language Grounding
To perform tasks specified by natural language instructions, autonomous agents need to extract semantically meaningful representations of language and map it to visual elements and actions in the environment. This problem is called task-oriented language grounding. We propose an end-to-end trainable neural architectu...
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Automatic classification of trees using a UAV onboard camera and deep learning
Automatic classification of trees using remotely sensed data has been a dream of many scientists and land use managers. Recently, Unmanned aerial vehicles (UAV) has been expected to be an easy-to-use, cost-effective tool for remote sensing of forests, and deep learning has attracted attention for its ability concerni...
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Assortative Mixing Equilibria in Social Network Games
It is known that individuals in social networks tend to exhibit homophily (a.k.a. assortative mixing) in their social ties, which implies that they prefer bonding with others of their own kind. But what are the reasons for this phenomenon? Is it that such relations are more convenient and easier to maintain? Or are t...
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Texture segmentation with Fully Convolutional Networks
In the last decade, deep learning has contributed to advances in a wide range computer vision tasks including texture analysis. This paper explores a new approach for texture segmentation using deep convolutional neural networks, sharing important ideas with classic filter bank based texture segmentation methods. Sev...
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The Beam and detector of the NA62 experiment at CERN
NA62 is a fixed-target experiment at the CERN SPS dedicated to measurements of rare kaon decays. Such measurements, like the branching fraction of the $K^{+} \rightarrow \pi^{+} \nu \bar\nu$ decay, have the potential to bring significant insights into new physics processes when comparison is made with precise theoret...
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A dequantized metaplectic knot invariant
Let $K\subset S^3$ be a knot, $X:= S^3\setminus K$ its complement, and $\mathbb{T}$ the circle group identified with $\mathbb{R}/\mathbb{Z}$. To any oriented long knot diagram of $K$, we associate a quadratic polynomial in variables bijectively associated with the bridges of the diagram such that, when the variables ...
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Persian Wordnet Construction using Supervised Learning
This paper presents an automated supervised method for Persian wordnet construction. Using a Persian corpus and a bi-lingual dictionary, the initial links between Persian words and Princeton WordNet synsets have been generated. These links will be discriminated later as correct or incorrect by employing seven feature...
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Anyon condensation and its applications
Bose condensation is central to our understanding of quantum phases of matter. Here we review Bose condensation in topologically ordered phases (also called topological symmetry breaking), where the condensing bosons have non-trivial mutual statistics with other quasiparticles in the system. We give a non-technical o...
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Group-velocity-locked vector soliton molecules in a birefringence-enhanced fiber laser
Physics phenomena of multi-soliton complexes have enriched the life of dissipative solitons in fiber lasers. By developing a birefringence-enhanced fiber laser, we report the first experimental observation of group-velocity-locked vector soliton (GVLVS) molecules. The birefringence-enhanced fiber laser facilitates th...
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Survey of Visual Question Answering: Datasets and Techniques
Visual question answering (or VQA) is a new and exciting problem that combines natural language processing and computer vision techniques. We present a survey of the various datasets and models that have been used to tackle this task. The first part of the survey details the various datasets for VQA and compares them...
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Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters
With the rise of end-to-end learning through deep learning, person detectors and re-identification (ReID) models have recently become very strong. Multi-camera multi-target (MCMT) tracking has not fully gone through this transformation yet. We intend to take another step in this direction by presenting a theoreticall...
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Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline
From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public hea...
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Redundant Perception and State Estimation for Reliable Autonomous Racing
In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences. To limit the impact of such failures, this paper presents the redundant perception and state estimation approaches developed for an autonomous race car. Redundancy in perception is achieved by e...
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Experimental study of extrinsic spin Hall effect in CuPt alloy
We have experimentally studied the effects on the spin Hall angle due to systematic addition of Pt into the light metal Cu. We perform spin torque ferromagnetic resonance measurements on Py/CuPt bilayer and find that as the Pt concentration increases, the spin Hall angle of CuPt alloy increases. Moreover, only 28% Pt...
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NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm
Deep neural networks (DNNs) have begun to have a pervasive impact on various applications of machine learning. However, the problem of finding an optimal DNN architecture for large applications is challenging. Common approaches go for deeper and larger DNN architectures but may incur substantial redundancy. To addres...
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Resonant Drag Instabilities in protoplanetary disks: the streaming instability and new, faster-growing instabilities
We identify and study a number of new, rapidly growing instabilities of dust grains in protoplanetary disks, which may be important for planetesimal formation. The study is based on the recognition that dust-gas mixtures are generically unstable to a Resonant Drag Instability (RDI), whenever the gas, absent dust, sup...
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Nonparametric Neural Networks
Automatically determining the optimal size of a neural network for a given task without prior information currently requires an expensive global search and training many networks from scratch. In this paper, we address the problem of automatically finding a good network size during a single training cycle. We introdu...
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FastTrack: Minimizing Stalls for CDN-based Over-the-top Video Streaming Systems
Traffic for internet video streaming has been rapidly increasing and is further expected to increase with the higher definition videos and IoT applications, such as 360 degree videos and augmented virtual reality applications. While efficient management of heterogeneous cloud resources to optimize the quality of expe...
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Powerful statistical inference for nested data using sufficient summary statistics
Hierarchically-organized data arise naturally in many psychology and neuroscience studies. As the standard assumption of independent and identically distributed samples does not hold for such data, two important problems are to accurately estimate group-level effect sizes, and to obtain powerful statistical tests aga...
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Beam-On-Graph: Simultaneous Channel Estimation for mmWave MIMO Systems with Multiple Users
This paper is concerned with the channel estimation problem in multi-user millimeter wave (mmWave) wireless systems with large antenna arrays. We develop a novel simultaneous-estimation with iterative fountain training (SWIFT) framework, in which multiple users estimate their channels at the same time and the require...
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On Comparison Of Experts
A policy maker faces a sequence of unknown outcomes. At each stage two (self-proclaimed) experts provide probabilistic forecasts on the outcome in the next stage. A comparison test is a protocol for the policy maker to (eventually) decide which of the two experts is better informed. The protocol takes as input the se...
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Multiscale simulation on shearing transitions of thin-film lubrication with multi-layer molecules
Shearing transitions of multi-layer molecularly thin-film lubrication systems in variations of the film-substrate coupling strength and the load are studied by using a multiscale method. Three kinds of the interlayer slips found in decreasing the coupling strength are in qualitative agreement with experimental result...
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Chirality-induced Antisymmetry in Magnetic Domain-Wall Speed
In chiral magnetic materials, numerous intriguing phenomena such as built in chiral magnetic domain walls (DWs) and skyrmions are generated by the Dzyaloshinskii Moriya interaction (DMI). The DMI also results in asymmetric DW speed under in plane magnetic field, which provides a useful scheme to measure the DMI stren...
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Strong interaction between graphene layer and Fano resonance in terahertz metamaterials
Graphene has emerged as a promising building block in the modern optics and optoelectronics due to its novel optical and electrical properties. In the mid-infrared and terahertz (THz) regime, graphene behaves like metals and supports surface plasmon resonances (SPRs). Moreover, the continuously tunable conductivity o...
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DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
Transfer learning through fine-tuning a pre-trained neural network with an extremely large dataset, such as ImageNet, can significantly accelerate training while the accuracy is frequently bottlenecked by the limited dataset size of the new target task. To solve the problem, some regularization methods, constraining ...
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The Burst Failure Influence on the $H_\infty$ Norm
In this work, we present an analysis of the Burst failure effect in the $H_\infty$ norm. We present a procedure to perform an analysis between different Markov Chain models and a numerical example. In the numerical example the results obtained pointed out that the burst failure effect in the performance does not exce...
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Cosmological Simulations in Exascale Era
The architecture of Exascale computing facilities, which involves millions of heterogeneous processing units, will deeply impact on scientific applications. Future astrophysical HPC applications must be designed to make such computing systems exploitable. The ExaNeSt H2020 EU-funded project aims to design and develop...
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Time evolution of the Luttinger model with nonuniform temperature profile
We study the time evolution of a one-dimensional interacting fermion system described by the Luttinger model starting from a nonequilibrium state defined by a smooth temperature profile $T(x)$. As a specific example we consider the case when $T(x)$ is equal to $T_L$ ($T_R$) far to the left (right). Using a series exp...
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Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
The game of chess is the most widely-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. In contra...
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Some remarks on Huisken's monotonicity formula for mean curvature flow
We discuss a monotone quantity related to Huisken's monotonicity formula and some technical consequences for mean curvature flow.
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Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors
We consider forecasting a single time series using high-dimensional predictors in the presence of a possible nonlinear forecast function. The sufficient forecasting (Fan et al., 2016) used sliced inverse regression to estimate lower-dimensional sufficient indices for nonparametric forecasting using factor models. How...
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Spectral energy distribution and radio halo of NGC 253 at low radio frequencies
We present new radio continuum observations of NGC253 from the Murchison Widefield Array at frequencies between 76 and 227 MHz. We model the broadband radio spectral energy distribution for the total flux density of NGC253 between 76 MHz and 11 GHz. The spectrum is best described as a sum of central starburst and ext...
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Emergent Phases of Fractonic Matter
Fractons are emergent particles which are immobile in isolation, but which can move together in dipolar pairs or other small clusters. These exotic excitations naturally occur in certain quantum phases of matter described by tensor gauge theories. Previous research has focused on the properties of small numbers of fr...
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Fractional Volterra Hierarchy
The generating function of cubic Hodge integrals satisfying the local Calabi-Yau condition is conjectured to be a tau function of a new integrable system which can be regarded as a fractional generalization of the Volterra lattice hierarchy, so we name it the fractional Volterra hierarchy. In this paper, we give the ...
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Deorbitalization strategies for meta-GGA exchange-correlation functionals
We explore the simplification of widely used meta-generalized-gradient approximation (mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of approximate kinetic energy density functionals (KEDFs). Such deorbitalization is motivated by the prospect of reducing computational cost while re...
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Fast counting of medium-sized rooted subgraphs
We prove that counting copies of any graph $F$ in another graph $G$ can be achieved using basic matrix operations on the adjacency matrix of $G$. Moreover, the resulting algorithm is competitive for medium-sized $F$: our algorithm recovers the best known complexity for rooted 6-clique counting and improves on the bes...
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First-principles investigation of graphitic carbon nitride monolayer with embedded Fe atom
Density-functional theory calculations with spin-polarized generalized gradient approximation and Hubbard $U$ correction is carried out to investigate the mechanical, structural, electronic and magnetic properties of graphitic heptazine with embedded $\mathrm{Fe}$ atom under bi-axial tensile strain and applied perpen...
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Courant's Nodal Domain Theorem for Positivity Preserving Forms
We introduce a notion of nodal domains for positivity preserving forms. This notion generalizes the classical ones for Laplacians on domains and on graphs. We prove the Courant nodal domain theorem in this generalized setting using purely analytical methods.
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Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges
Notifications provide a unique mechanism for increasing the effectiveness of real-time information delivery systems. However, notifications that demand users' attention at inopportune moments are more likely to have adverse effects and might become a cause of potential disruption rather than proving beneficial to use...
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Using Matching to Detect Infeasibility of Some Integer Programs
A novel matching based heuristic algorithm designed to detect specially formulated infeasible zero-one IPs is presented. The algorithm input is a set of nested doubly stochastic subsystems and a set E of instance defining variables set at zero level. The algorithm deduces additional variables at zero level until eith...
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α7 nicotinic acetylcholine receptor signaling modulates ovine fetal brain astrocytes transcriptome in response to endotoxin: comparison to microglia, implications for prenatal stress and development of autism spectrum disorder
Neuroinflammation in utero may result in lifelong neurological disabilities. Astrocytes play a pivotal role, but the mechanisms are poorly understood. No early postnatal treatment strategies exist to enhance neuroprotective potential of astrocytes. We hypothesized that agonism on {\alpha}7 nicotinic acetylcholine rec...
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Face centered cubic and hexagonal close packed skyrmion crystals in centro-symmetric magnets
Skyrmions are disk-like objects that typically form triangular crystals in two dimensional systems. This situation is analogous to the so-called "pancake vortices" of quasi-two dimensional superconductors. The way in which skyrmion disks or pancake skyrmions pile up in layered centro-symmetric materials is dictated b...
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Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
Deep convolution neural networks demonstrate impressive results in the super-resolution domain. A series of studies concentrate on improving peak signal noise ratio (PSNR) by using much deeper layers, which are not friendly to constrained resources. Pursuing a trade-off between the restoration capacity and the simpli...
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Robbins-Monro conditions for persistent exploration learning strategies
We formulate simple assumptions, implying the Robbins-Monro conditions for the $Q$-learning algorithm with the local learning rate, depending on the number of visits of a particular state-action pair (local clock) and the number of iteration (global clock). It is assumed that the Markov decision process is communicat...
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Localization in the Disordered Holstein model
The Holstein model describes the motion of a tight-binding tracer particle interacting with a field of quantum harmonic oscillators. We consider this model with an on-site random potential. Provided the hopping amplitude for the particle is small, we prove localization for matrix elements of the resolvent, in particl...
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Universal Planning Networks
A key challenge in complex visuomotor control is learning abstract representations that are effective for specifying goals, planning, and generalization. To this end, we introduce universal planning networks (UPN). UPNs embed differentiable planning within a goal-directed policy. This planning computation unrolls a f...
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Adversarial Removal of Demographic Attributes from Text Data
Recent advances in Representation Learning and Adversarial Training seem to succeed in removing unwanted features from the learned representation. We show that demographic information of authors is encoded in -- and can be recovered from -- the intermediate representations learned by text-based neural classifiers. Th...
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Superradiance phase transition in the presence of parameter fluctuations
We theoretically analyze the effect of parameter fluctuations on the superradiance phase transition in a setup where a large number of superconducting qubits are coupled to a single cavity. We include parameter fluctuations that are typical of superconducting architectures, such as fluctuations in qubit gaps, bias po...
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A Decision Support Method for Recommending Degrees of Exploration in Exploratory Testing
Exploratory testing is neither black nor white, but rather a continuum of exploration exists. In this research we propose an approach for decision support helping practitioners to distribute time between different degrees of exploratory testing on that continuum. To make the continuum manageable, five levels have bee...
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Quantum Field Theory and Coalgebraic Logic in Theoretical Computer Science
In this paper we suggest that in the framework of the Category Theory it is possible to demonstrate the mathematical and logical \textit{dual equivalence} between the category of the $q$-deformed Hopf Coalgebras and the category of the $q$-deformed Hopf Algebras in QFT, interpreted as a thermal field theory. Each pai...
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Spatiotemporal Prediction of Ambulance Demand using Gaussian Process Regression
Accurately predicting when and where ambulance call-outs occur can reduce response times and ensure the patient receives urgent care sooner. Here we present a novel method for ambulance demand prediction using Gaussian process regression (GPR) in time and geographic space. The method exhibits superior accuracy to MED...
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ArchiveWeb: collaboratively extending and exploring web archive collections - How would you like to work with your collections?
Curated web archive collections contain focused digital content which is collected by archiving organizations, groups, and individuals to provide a representative sample covering specific topics and events to preserve them for future exploration and analysis. In this paper, we discuss how to best support collaborativ...
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gl2vec: Learning Feature Representation Using Graphlets for Directed Networks
Learning network representations has a variety of applications, such as network classification. Most existing work in this area focuses on static undirected networks and do not account for presence of directed edges or temporarily changes. Furthermore, most work focuses on node representations that do poorly on tasks...
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Evidence of s-wave superconductivity in the noncentrosymmetric La$_7$Ir$_3$
Superconductivity in noncentrosymmetric compounds has attracted sustained interest in the last decades. Here we present a detailed study on the transport, thermodynamic properties and the band structure of the noncentrosymmetric superconductor La$_7$Ir$_3$ ($T_c$ $\sim$2.3 K) that was recently proposed to break the t...
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Essential Dimension of Generic Symbols in Characteristic p
In this article the $p$-essential dimension of generic symbols over fields of characteristic $p$ is studied. In particular, the $p$-essential dimension of the length $\ell$ generic $p$-symbol of degree $n+1$ is bounded below by $n+\ell$ when the base field is algebraically closed of characteristic $p$. The proof uses...
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Ask less - Scale Market Research without Annoying Your Customers
Market research is generally performed by surveying a representative sample of customers with questions that includes contexts such as psycho-graphics, demographics, attitude and product preferences. Survey responses are used to segment the customers into various groups that are useful for targeted marketing and comm...
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Adaptive Regularized Newton Method for Riemannian Optimization
Optimization on Riemannian manifolds widely arises in eigenvalue computation, density functional theory, Bose-Einstein condensates, low rank nearest correlation, image registration, and signal processing, etc. We propose an adaptive regularized Newton method which approximates the original objective function by the s...
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MPC meets SNA: A Privacy Preserving Analysis of Distributed Sensitive Social Networks
In this paper, we formalize the notion of distributed sensitive social networks (DSSNs), which encompasses networks like enmity networks, financial transaction networks, supply chain networks and sexual relationship networks. Compared to the well studied traditional social networks, DSSNs are often more challenging t...
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Lossy Image Compression with Compressive Autoencoders
We propose a new approach to the problem of optimizing autoencoders for lossy image compression. New media formats, changing hardware technology, as well as diverse requirements and content types create a need for compression algorithms which are more flexible than existing codecs. Autoencoders have the potential to ...
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A cost effective and reliable environment monitoring system for HPC applications
We present a slow control system to gather all relevant environment information necessary to effectively and reliably run an HPC (High Performance Computing) system at a high value over price ratio. The scalable and reliable overall concept is presented as well as a newly developed hardware device for sensor read out...
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Quenching the Kitaev honeycomb model
I studied the non-equilibrium response of an initial Néel state under time evolution with the Kitaev honeycomb model. This time evolution can be computed using a random sampling over all relevant flux configurations. With isotropic interactions the system quickly equilibrates into a steady state valence bond solid. A...
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Privacy-Preserving Adversarial Networks
We propose a data-driven framework for optimizing privacy-preserving data release mechanisms toward the information-theoretically optimal tradeoff between minimizing distortion of useful data and concealing sensitive information. Our approach employs adversarially-trained neural networks to implement randomized mecha...
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Antiferromagnetic structure and electronic properties of BaCr2As2 and BaCrFeAs2
The chromium arsenides BaCr2As2 and BaCrFeAs2 with ThCr2Si2 type structure (space group I4/mmm; also adopted by '122' iron arsenide superconductors) have been suggested as mother compounds for possible new superconductors. DFT-based calculations of the electronic structure evidence metallic antiferromagnetic ground s...
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Molecular Modeling of the Microstructure Evolution during the Carbonization of PAN-Based Carbon Fibers
Development of high strength carbon fibers (CFs) requires an understanding of the relationship between the processing conditions, microstructure and resulting properties. We developed a molecular model that combines kinetic Monte Carlo (KMC) and molecular dynamics (MD) techniques to predict the microstructure evoluti...
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Hyperinflation
A model of cosmological inflation is proposed in which field space is a hyperbolic plane. The inflaton never slow-rolls, and instead orbits the bottom of the potential, buoyed by a centrifugal force. Though initial velocities redshift away during inflation, in negatively curved spaces angular momentum naturally start...
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Improving on Q & A Recurrent Neural Networks Using Noun-Tagging
Often, more time is spent on finding a model that works well, rather than tuning the model and working directly with the dataset. Our research began as an attempt to improve upon a simple Recurrent Neural Network for answering "simple" first-order questions (QA-RNN), developed by Ferhan Ture and Oliver Jojic, from Co...
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Injectivity and weak*-to-weak continuity suffice for convergence rates in $\ell^1$-regularization
We show that the convergence rate of $\ell^1$-regularization for linear ill-posed equations is always $O(\delta)$ if the exact solution is sparse and if the considered operator is injective and weak*-to-weak continuous. Under the same assumptions convergence rates in case of non-sparse solutions are proven. The resul...
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A Panel Prototype for the Mu2e Straw Tube Tracker at Fermilab
The Mu2e experiment will search for coherent, neutrino-less conversion of muons into electrons in the Coulomb field of an aluminum nucleus with a sensitivity of four orders of magnitude better than previous experiments. The signature of this process is an electron with energy nearly equal to the muon mass. Mu2e relie...
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A Review on Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things (IoNT)
The current prominence and future promises of the Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things (IoNT) are extensively reviewed and a summary survey report is presented. The analysis clearly distinguishes between IoT and IoE which are wrongly considered to be the same by many peop...
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Ensemble Adversarial Training: Attacks and Defenses
Adversarial examples are perturbed inputs designed to fool machine learning models. Adversarial training injects such examples into training data to increase robustness. To scale this technique to large datasets, perturbations are crafted using fast single-step methods that maximize a linear approximation of the mode...
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X-Ray bright optically faint active galactic nuclei in the Subaru Hyper Suprime-Cam wide survey
We construct a sample of X-ray bright optically faint active galactic nuclei by combining Subaru Hyper Suprime-Cam, XMM-Newton, and infrared source catalogs. 53 X-ray sources satisfying i band magnitude fainter than 23.5 mag and X-ray counts with EPIC-PN detector larger than 70 are selected from 9.1 deg^2, and their ...
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The Goldman symplectic form on the PSL(V)-Hitchin component
This article is the second of a pair of articles about the Goldman symplectic form on the PSL(V )-Hitchin component. We show that any ideal triangulation on a closed connected surface of genus at least 2, and any compatible bridge system determine a symplectic trivialization of the tangent bundle to the Hitchin compo...
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Early Results from TUS, the First Orbital Detector of Extreme Energy Cosmic Rays
TUS is the world's first orbital detector of extreme energy cosmic rays (EECRs), which operates as a part of the scientific payload of the Lomonosov satellite since May 19, 2016. TUS employs the nocturnal atmosphere of the Earth to register ultraviolet (UV) fluorescence and Cherenkov radiation from extensive air show...
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Network-based methods for outcome prediction in the "sample space"
In this thesis we present the novel semi-supervised network-based algorithm P-Net, which is able to rank and classify patients with respect to a specific phenotype or clinical outcome under study. The peculiar and innovative characteristic of this method is that it builds a network of samples/patients, where the node...
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The geometrical origins of some distributions and the complete concentration of measure phenomenon for mean-values of functionals
We derive out naturally some important distributions such as high order normal distributions and high order exponent distributions and the Gamma distribution from a geometrical way. Further, we obtain the exact mean-values of integral form functionals in the balls of continuous functions space with $p-$norm, and show...
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The Signs in Elliptic Nets
We give a generalization of a theorem of Silverman and Stephens regarding the signs in an elliptic divisibility sequence to the case of an elliptic net. We also describe applications of this theorem in the study of the distribution of the signs in elliptic nets and generating elliptic nets using the denominators of t...
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