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FA*IR: A Fair Top-k Ranking Algorithm
In this work, we define and solve the Fair Top-k Ranking problem, in which we want to determine a subset of k candidates from a large pool of n >> k candidates, maximizing utility (i.e., select the "best" candidates) subject to group fairness criteria. Our ranked group fairness definition extends group fairness using...
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A novel delayed-choice experimental proposal testing local decisions
Entangled states are notoriously non-separable, their sub-ensembles being only statistical mixtures yielding no coherences and no quantum interference phenomena. The interesting features of entangled states can be revealed only by coincidence counts over the (typically) two sub-ensembles of the system. In this paper ...
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Better accuracy with quantified privacy: representations learned via reconstructive adversarial network
The remarkable success of machine learning, especially deep learning, has produced a variety of cloud-based services for mobile users. Such services require an end user to send data to the service provider, which presents a serious challenge to end-user privacy. To address this concern, prior works either add noise t...
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Compositional descriptor-based recommender system accelerating the materials discovery
Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds...
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Structure Formation and Microlensing with Axion Miniclusters
If the symmetry breaking responsible for axion dark matter production occurs during the radiation-dominated epoch in the early Universe, then this produces large amplitude perturbations that collapse into dense objects known as axion miniclusters. The characteristic minicluster mass, $M_0$, is set by the mass inside ...
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Clustering Residential Electricity Load Curves via Community Detection in Network
Performing analytic of household load curves (LCs) has significant value in predicting individual electricity consumption patterns, and hence facilitate developing demand-response strategy, and finally achieve energy efficiency improvement and emission reduction. LC clustering is a widely used analytic technology, wh...
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Lie and Noether point Symmetries for a Class of Nonautonomous Dynamical Systems
We prove two general theorems which determine the Lie and the Noether point symmetries for the equations of motion of a dynamical system which moves in a general Riemannian space under the action of a time dependent potential $W(t,x)=\omega(t)V(x)$. We apply the theorems to the case of a time dependent central potent...
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Thermal Inflation with a Thermal Waterfall Scalar Field Coupled to a Light Spectator Scalar Field
A new model of thermal inflation is introduced, in which the mass of the thermal waterfall field is dependent on a light spectator scalar field. Using the $\delta N$ formalism, the "end of inflation" scenario is investigated in order to ascertain whether this model is able to produce the dominant contribution to the ...
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DeepMoTIon: Learning to Navigate Like Humans
We present a novel human-aware navigation approach, where the robot learns to mimic humans to navigate safely in crowds. The presented model referred to as DeepMoTIon, is trained with pedestrian surveillance data to predict human velocity. The robot processes LiDAR scans via the trained network to navigate to the tar...
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Multidimensional Free Poisson Limits on Free Stochastic Integral Algebras
In this paper, we prove four-moment theorems for multidimensional free Poisson limits on free Wigner chaos or the free Poisson algebra. We prove that, under mild technical conditions, a bi-indexed sequence of free stochastic integrals in free Wigner algebra or free Poisson algebra converges to a free sequence of free...
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On the finite $W$-algebra for the Lie superalgebra Q(N) in the non-regular case
In this paper we study the finite W-algebra for the queer Lie superalgebra Q(n) associated with the non-regular even nilpotent coadjoint orbits in the case when the corresponding nilpotent element has Jordan blocks each of size l. We prove that this finite W-algebra is isomorphic to a quotient of the super-Yangian of...
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SNeCT: Scalable network constrained Tucker decomposition for integrative multi-platform data analysis
Motivation: How do we integratively analyze large-scale multi-platform genomic data that are high dimensional and sparse? Furthermore, how can we incorporate prior knowledge, such as the association between genes, in the analysis systematically? Method: To solve this problem, we propose a Scalable Network Constrained...
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CANAL: A Cache Timing Analysis Framework via LLVM Transformation
A unified modeling framework for non-functional properties of a program is essential for research in software analysis and verification, since it reduces burdens on individual researchers to implement new approaches and compare existing approaches. We present CANAL, a framework that models the cache behaviors of a pr...
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Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging
Obtaining magnetic resonance images (MRI) with high resolution and generating quantitative image-based biomarkers for assessing tissue biochemistry is crucial in clinical and research applications. How- ever, acquiring quantitative biomarkers requires high signal-to-noise ratio (SNR), which is at odds with high-resol...
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Inverse problems in models of resource distribution
We continue to study the problem of modeling of substitution of production factors motivated by the need for computable mathematical models of economics that could be used as a basis in applied developments. This problem has been studied for several decades, and several connections to complex analysis and geometry ha...
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Critical behaviour in one dimension: unconventional pairing, phase separation, BEC-BCS crossover and magnetic Lifshitz transition
We study the superconducting properties of population-imbalanced ultracold Fermi mixtures in one-dimensional (1D) optical lattices that can be effectively described by the spin-imbalanced attractive Hubbard model (AHM) in the presence of a Zeeman magnetic field. We use the mean-field theory approach to obtain the gro...
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Andreev reflections and the quantum physics of black holes
We establish an analogy between superconductor-metal interfaces and the quantum physics of a black hole, using the proximity effect. We show that the metal-superconductor interface can be thought of as an event horizon and Andreev reflection from the interface is analogous to the Hawking radiation in black holes. We ...
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Wind, Sand and Water. The Orientation of the Late Roman Forts in the Kharga Oasis (Egyptian Western Desert)
The chain of late Roman fortified settlements built in the Kharga Oasis, in Egypt Western Desert, represents an interesting case study to analyse how the ancient Roman town planners interacted with the landscape. A peculiar feature of the site is the existence of a prevailing, north westerly wind, and it is possible ...
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On generalized Dold manifolds
Let $X$ be a smooth manifold with a (smooth) involution $\sigma:X\to X$ such that $Fix(\sigma)\ne \emptyset$. We call the space $P(m,X):=\mathbb{S}^m\times X/\!\sim$ where $(v,x)\sim (-v,\sigma(x))$ a generalized Dold manifold. When $X$ is an almost complex manifold and the differential $T\sigma: TX\to TX$ is conjuga...
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Pilot system development in metre-scale laboratory discharge
The pilot system development in metre-scale negative laboratory discharges is studied with ns-fast photography. The systems appear as bipolar structures in the vicinity of the negative high-voltage electrode. They appear as a result of a single negative streamer propagation and determine further discharge development...
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Abstract Interpretation of Binary Code with Memory Accesses using Polyhedra
In this paper we propose a novel methodology for static analysis of binary code using abstract interpretation. We use an abstract domain based on polyhedra and two mapping functions that associate polyhedra variables with registers and memory. We demonstrate our methodology to the problem of computing upper bounds to...
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Optimal learning via local entropies and sample compression
The aim of this paper is to provide several novel upper bounds on the excess risk with a primal focus on classification problems. We suggest two approaches and the obtained bounds are represented via the distribution dependent local entropies of the classes or the sizes of specific sample com- pression schemes. We sh...
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Domain Specific Semantic Validation of Schema.org Annotations
Since its unveiling in 2011, schema.org has become the de facto standard for publishing semantically described structured data on the web, typically in the form of web page annotations. The increasing adoption of schema.org facilitates the growth of the web of data, as well as the development of automated agents that...
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Vector-valued extensions of operators through multilinear limited range extrapolation
We give an extension of Rubio de Francia's extrapolation theorem for functions taking values in UMD Banach function spaces to the multilinear limited range setting. In particular we show how boundedness of an $m$-(sub)linear operator \[T:L^{p_1}(w_1^{p_1})\times\cdots\times L^{p_m}(w_m^{p_m})\to L^p(w^p) \] for a cer...
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Phase Diagram of Carbon Nickel Tungsten: Superatom Model
Carbon solubility in face-centered cubic Ni-W alloys and the phase diagram of C-Ni-W are investigated by means of first principle calculations and semi-grand canonical Monte Carlo simulations. With density functional theory (DFT) total energies as fitting data, we build a superatom model for efficient simulation. Mul...
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Classical solution for the linear sigma model
In this paper, the linear sigma model is studied using a method for finding analytical solutions based on Padé approximants. Using the solutions of two and three traveling waves in 1+3 dimensions we found, we are able to show a solution that is valid for an arbitrary number of bosons and traveling waves.
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The Importance of System-Level Information in Multiagent Systems Design: Cardinality and Covering Problems
A fundamental challenge in multiagent systems is to design local control algorithms to ensure a desirable collective behaviour. The information available to the agents, gathered either through communication or sensing, naturally restricts the achievable performance. Hence, it is fundamental to identify what piece of ...
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Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings
Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads...
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FLASH: A Faster Optimizer for SBSE Tasks
Most problems in search-based software engineering involve balancing conflicting objectives. Prior approaches to this task have required a large number of evaluations- making them very slow to execute and very hard to comprehend. To solve these problems, this paper introduces FLASH, a decision tree based optimizer th...
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On the complexity of generalized chromatic polynomials
J. Makowsky and B. Zilber (2004) showed that many variations of graph colorings, called CP-colorings in the sequel, give rise to graph polynomials. This is true in particular for harmonious colorings, convex colorings, mcc_t-colorings, and rainbow colorings, and many more. N. Linial (1986) showed that the chromatic p...
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Hybrid SGP4 orbit propagator
Two-Line Elements (TLEs) continue to be the sole public source of orbiter observations. The accuracy of TLE propagations through the Simplified General Perturbations-4 (SGP4) software decreases dramatically as the propagation horizon increases, and thus the period of validity of TLEs is very limited. As a result, TLE...
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PDE-Net: Learning PDEs from Data
In this paper, we present an initial attempt to learn evolution PDEs from data. Inspired by the latest development of neural network designs in deep learning, we propose a new feed-forward deep network, called PDE-Net, to fulfill two objectives at the same time: to accurately predict dynamics of complex systems and t...
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Stable components in the parameter plane of meromorphic functions of finite type
We study the parameter planes of certain one-dimensional, dynamically-defined slices of holomorphic families of meromorphic transcendental maps of finite type for which infinity is not an asymptotic value. Our planes are defined by constraining the orbits of all but one of the asymptotic values. We study the structur...
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Optimal Regulation Response of Batteries Under Cycle Aging Mechanisms
When providing frequency regulation in a pay-for-performance market, batteries need to carefully balance the trade-off between following regulation signals and their degradation costs in real-time. Existing battery control strategies either do not consider mismatch penalties in pay-for-performance markets, or cannot ...
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Spin-structures on real Bott manifolds with Kähler structures
Let M be a real Bott manifold with Kähler structure. Using Ishida characterization we give necessary and sufficient condition for the existence of the Spin-structure on M. In proof we use the technic developed in Popko, Szczepański "Cohomological rigity of oriented Hantzsche-Wendt manifolds" (Adv. Math. 302 (2016), 1...
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No difference in orbital parameters of RV-detected giant planets between 0.1 and 5 au in single vs multi-stellar systems
Our Keck/NIRC2 imaging survey searches for stellar companions around 144 systems with radial velocity (RV) detected giant planets to determine whether stellar binaries influence the planets' orbital parameters. This survey, the largest of its kind to date, finds eight confirmed binary systems and three confirmed trip...
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On overfitting and post-selection uncertainty assessments
In a regression context, when the relevant subset of explanatory variables is uncertain, it is common to use a data-driven model selection procedure. Classical linear model theory, applied naively to the selected sub-model, may not be valid because it ignores the selected sub-model's dependence on the data. We provid...
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Concept of multiple-cell cavity for axion dark matter search
In cavity-based axion dark matter search experiments exploring high mass regions, multiple-cavity design is considered to increase the detection volume within a given magnet bore. We introduce a new idea, referred to as multiple-cell cavity, which provides various benefits including a larger detection volume, simpler...
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Detecting Recycled Commodity SoCs: Exploiting Aging-Induced SRAM PUF Unreliability
A physical unclonable function (PUF), analogous to a human fingerprint, has gained an enormous amount of attention from both academia and industry. SRAM PUF is among one of the popular silicon PUF constructions that exploits random initial power-up states from SRAM cells to extract hardware intrinsic secrets for iden...
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Ginzburg-Landau-type theory of non-polarized spin superconductivity
Since the concept of spin superconductor was proposed, all the related studies concentrate on spin-polarized case. Here, we generalize the study to spin-non-polarized case. The free energy of non-polarized spin superconductor is obtained, and the Ginzburg-Landau-type equations are derived by using the variational met...
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Evolution of Anisotropic Displacement Parameters and Superconductivity with Chemical Pressure in BiS2-Based REO0.5F0.5BiS2 (RE = La, Ce, Pr, and Nd)
In order to understand the mechanisms behind the emergence of superconductivity by the chemical pressure effect in REO0.5F0.5BiS2 (RE = La, Ce, Pr, and Nd), where bulk superconductivity is induced by the substitutions with a smaller-radius RE, we performed synchrotron powder X-ray diffraction, and analyzed the crysta...
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A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
Training deep neural networks (DNNs) efficiently is a challenge due to the associated highly nonconvex optimization. The backpropagation (backprop) algorithm has long been the most widely used algorithm for gradient computation of parameters of DNNs and is used along with gradient descent-type algorithms for this opt...
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Surface zeta potential and diamond seeding on gallium nitride films
Measurement of zeta potential of Ga and N-face gallium nitride has been carried out as function of pH. Both the faces show negative zeta potential in the pH range 5.5-9. The Ga face has an isoelectric point at pH 5.5. The N-face shows higher negative zeta potential due to larger concentration of adsorbed oxygen. Zeta...
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Analysing Temporal Evolution of Interlingual Wikipedia Article Pairs
Wikipedia articles representing an entity or a topic in different language editions evolve independently within the scope of the language-specific user communities. This can lead to different points of views reflected in the articles, as well as complementary and inconsistent information. An analysis of how the infor...
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Smith Ideals of Operadic Algebras in Monoidal Model Categories
Building upon Hovey's work on Smith ideals for monoids, we develop a homotopy theory of Smith ideals for general operads in a symmetric monoidal category. For a sufficiently nice stable monoidal model category and an operad satisfying a cofibrancy condition, we show that there is a Quillen equivalence between a model...
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Phase and Power Control in the RF Magnetron Power Stations of Superconducting Accelerators
Phase and power control methods that satisfy the requirements of superconducting accelerators to magnetron RF sources were considered by a simplified kinetic model of a magnetron driven by a resonant injected signal. The model predicting and explaining stable, low noise operation of the tube below the threshold of se...
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Cohomologies of locally conformally symplectic manifolds and solvmanifolds
We study the Morse-Novikov cohomology and its almost-symplectic counterpart on manifolds admitting locally conformally symplectic structures. More precisely, we introduce lcs cohomologies and we study elliptic Hodge theory, dualities, Hard Lefschetz Condition. We consider solvmanifolds and Oeljeklaus-Toma manifolds. ...
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Frequency Offset Estimation for OFDM Systems with a Novel Frequency Domain Training Sequence
A novel frequency domain training sequence and the corresponding carrier frequency offset (CFO) estimator are proposed for orthogonal frequency division multiplexing (OFDM) systems over frequency-selective fading channels. The proposed frequency domain training sequence comprises two types of pilot tones, namely dist...
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Cusp shape and tunnel number
We show that the set of cusp shapes of hyperbolic tunnel number one manifolds is dense in the Teichmuller space of the torus. A similar result holds for tunnel number n manifolds. As a consequence, for fixed n, there are infinitely many hyperbolic tunnel number n manifolds with at most one exceptional Dehn filling. T...
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Divergence-free positive symmetric tensors and fluid dynamics
We consider $d\times d$ tensors $A(x)$ that are symmetric, positive semi-definite, and whose row-divergence vanishes identically. We establish sharp inequalities for the integral of $(\det A)^{\frac1{d-1}}$. We apply them to models of compressible inviscid fluids: Euler equations, Euler--Fourier, relativistic Euler, ...
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Admire vs. Safire: Objective comparison of CT reconstruction algorithms and their noise properties
Purpose: Siemens has developed several iterative reconstruction (IR) algorithms on their CT scanners. SAFIRE is available on most of their CT scanners. The latest algorithm, ADMIRE, is available on their newest high-end CT scanners. The aim of our study was to compare the noise reduction properties of the two IR algo...
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Occupants in simplicial complexes
Let $M$ be a smooth manifold and $K\subset M$ be a simplicial complex of codimension at least 3. Functor calculus methods lead to a homotopical formula of $M\setminus K$ in terms of spaces $M\setminus T$ where $T$ is a finite subset of $K$. This is a generalization of the author's previous work with Michael Weiss whe...
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Temporal Stability in Predictive Process Monitoring
Predictive process monitoring is concerned with the analysis of events produced during the execution of a business process in order to predict as early as possible the final outcome of an ongoing case. Traditionally, predictive process monitoring methods are optimized with respect to accuracy. However, in environment...
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Discrete Gradient Line Fields on Surfaces
A line field on a manifold is a smooth map which assigns a tangent line to all but a finite number of points of the manifold. As such, it can be seen as a generalization of vector fields. They model a number of geometric and physical properties, e.g. the principal curvature directions dynamics on surfaces or the stre...
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New Directions In Cellular Automata
We Propose A Novel Automaton Model which uses Arithmetic Operations as the Evolving Rules, each cell has the states of the Natural Numbers k = (N), a radius of r = 1/2 and operates on an arbitrary input size. The Automaton reads an Arithmetic Expression as an input and outputs another Arithmetic Expression. In Additi...
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Smart Fog: Fog Computing Framework for Unsupervised Clustering Analytics in Wearable Internet of Things
The increasing use of wearables in smart telehealth generates heterogeneous medical big data. Cloud and fog services process these data for assisting clinical procedures. IoT based ehealthcare have greatly benefited from efficient data processing. This paper proposed and evaluated use of low resource machine learning...
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Subspace Clustering via Optimal Direction Search
This letter presents a new spectral-clustering-based approach to the subspace clustering problem. Underpinning the proposed method is a convex program for optimal direction search, which for each data point d finds an optimal direction in the span of the data that has minimum projection on the other data points and n...
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The Covering Principle: A New Approach to Address Multiplicity in Hypotheses Testing
The closure and the partitioning principles have been used to build various multiple testing procedures in the past three decades. The essence of these two principles is based on parameter space partitioning. In this article, we propose a novel approach coined the covering principle from the perspective of rejection ...
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Mechanisms of Lagrangian analyticity in fluids
Certain systems of inviscid fluid dynamics have the property that for solutions that are only slightly better than differentiable in Eulerian variables, the corresponding Lagrangian trajectories are analytic in time. We elucidate the mechanisms in fluid dynamics systems that give rise to this automatic Lagrangian ana...
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How to Differentiate Collective Variables in Free Energy Codes: Computer-Algebra Code Generation and Automatic Differentiation
The proper choice of collective variables (CVs) is central to biased-sampling free energy reconstruction methods in molecular dynamics simulations. The PLUMED 2 library, for instance, provides several sophisticated CV choices, implemented in a C++ framework; however, developing new CVs is still time consuming due to ...
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Blocks of the category of smooth $\ell$-modular representations of $GL(n,F)$ and its inner forms: reduction to level-$0$
Let $G$ be an inner form of a general linear group over a non-archimedean locally compact field of residue characteristic $p$, let $R$ be an algebraically closed field of characteristic different from $p$ and let $\mathscr{R}_R(G)$ be the category of smooth representations of $G$ over $R$. In this paper, we prove tha...
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An Investigation of Newton-Sketch and Subsampled Newton Methods
The concepts of sketching and subsampling have recently received much attention by the optimization and statistics communities. In this paper, we study Newton-Sketch and Subsampled Newton (SSN) methods for the finite-sum optimization problem. We consider practical versions of the two methods in which the Newton equat...
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On angled bounce-off impact of a drop impinging on a flowing soap film
Small drops impinging angularly on thin flowing soap films frequently demonstrate the rare emergence of bulk elastic effects working in-tandem with the more common-place hydrodynamic interactions. Three collision regimes are observable: (a) drop piercing through the film, (b) it coalescing with the flow, and (c) it b...
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Fast evaluation of solid harmonic Gaussian integrals for local resolution-of-the-identity methods and range-separated hybrid functionals
An integral scheme for the efficient evaluation of two-center integrals over contracted solid harmonic Gaussian functions is presented. Integral expressions are derived for local operators that depend on the position vector of one of the two Gaussian centers. These expressions are then used to derive the formula for ...
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A note on integrating products of linear forms over the unit simplex
Integrating a product of linear forms over the unit simplex can be done in polynomial time if the number of variables n is fixed (V. Baldoni et al., 2011). In this note, we highlight that this problem is equivalent to obtaining the normalizing constant of state probabilities for a popular class of Markov processes us...
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Linearly constrained Gaussian processes
We consider a modification of the covariance function in Gaussian processes to correctly account for known linear constraints. By modelling the target function as a transformation of an underlying function, the constraints are explicitly incorporated in the model such that they are guaranteed to be fulfilled by any s...
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Racks as multiplicative graphs
We interpret augmented racks as a certain kind of multiplicative graphs and show that this point of view is natural for defining rack homology. We also define the analogue of the group algebra for these objects; in particular, we see how discrete racks give rise to Hopf algebras and Lie algebras in the Loday-Pirashvi...
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Bielliptic intermediate modular curves
We determine which of the modular curves $X_\Delta(N)$, that is, curves lying between $X_0(N)$ and $X_1(N)$, are bielliptic. Somewhat surprisingly, we find that one of these curves has exceptional automorphisms. Finally we find all $X_\Delta(N)$ that have infinitely many quadratic points over $\mathbb{Q}$.
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Behavior Revealed in Mobile Phone Usage Predicts Loan Repayment
Many households in developing countries lack formal financial histories, making it difficult for banks to extend loans, and for potential borrowers to receive them. However, many of these households have mobile phones, which generate rich data about behavior. This paper shows that behavioral signatures in mobile phon...
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Robust and structural ergodicity analysis of stochastic biomolecular networks involving synthetic antithetic integral controllers
Ergodicity and output controllability have been shown to be fundamental concepts for the analysis and synthetic design of closed-loop stochastic reaction networks, as exemplified by the use of antithetic integral feedback controllers. In [Gupta, Briat & Khammash, PLoS Comput. Biol., 2014], some ergodicity and output ...
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A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
We propose an effective method to solve the event sequence clustering problems based on a novel Dirichlet mixture model of a special but significant type of point processes --- Hawkes process. In this model, each event sequence belonging to a cluster is generated via the same Hawkes process with specific parameters, ...
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On the number of cyclic subgroups of a finite group
Let $G$ be a finite group and let $c(G)$ be the number of cyclic subgroups of $G$. We study the function $\alpha(G) = c(G)/|G|$. We explore its basic properties and we point out a connection with the probability of commutation. For many families $\mathscr{F}$ of groups we characterize the groups $G \in \mathscr{F}$ f...
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Accelerated Extra-Gradient Descent: A Novel Accelerated First-Order Method
We provide a novel accelerated first-order method that achieves the asymptotically optimal convergence rate for smooth functions in the first-order oracle model. To this day, Nesterov's Accelerated Gradient Descent (AGD) and variations thereof were the only methods achieving acceleration in this standard blackbox mod...
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Disruption of Alfvénic turbulence by magnetic reconnection in a collisionless plasma
We calculate the disruption scale $\lambda_{\rm D}$ at which sheet-like structures in dynamically aligned Alfvénic turbulence are destroyed by the onset of magnetic reconnection in a low-$\beta$ collisionless plasma. The scaling of $\lambda_{\rm D}$ depends on the order of the statistics being considered, with more i...
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New neutrino physics and the altered shapes of solar neutrino spectra
Neutrinos coming from the Sun's core are now measured with a high precision, and fundamental neutrino oscillations parameters are determined with a good accuracy. In this work, we estimate the impact that a new neutrino physics model, the so-called generalized Mikheyev-Smirnov-Wolfenstein (MSW) oscillation mechanism,...
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Searching for a Single Community in a Graph
In standard graph clustering/community detection, one is interested in partitioning the graph into more densely connected subsets of nodes. In contrast, the "search" problem of this paper aims to only find the nodes in a "single" such community, the target, out of the many communities that may exist. To do so , we ar...
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Superinjective Simplicial Maps of the Two-sided Curve Complexes on Nonorientable Surfaces
Let $N$ be a compact, connected, nonorientable surface of genus $g$ with $n$ boundary components with $g \geq 5$, $n \geq 0$. Let $\mathcal{T}(N)$ be the two-sided curve complex of $N$. If $\lambda :\mathcal{T}(N) \rightarrow \mathcal{T}(N)$ is a superinjective simplicial map, then there exists a homeomorphism $h : N...
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Geometry-Oblivious FMM for Compressing Dense SPD Matrices
We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD) matrix. For many applications, GOFMM enables an approximate matrix-vector multiplication in $N \log N$ or even $N$ time, where $N$ is the...
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Deep learning for universal linear embeddings of nonlinear dynamics
Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear is a central challenge in modern dynamical systems. These transformations have the potential to enable prediction, estimation, and control of nonlinear systems using standard linear theory. The Koopman operator has emerg...
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Mean-field modeling of the basal ganglia-thalamocortical system. II. Dynamics of parkinsonian oscillations
Neuronal correlates of Parkinson's disease (PD) include a slowing of the electroencephalogram (EEG) and enhanced synchrony at 3-7 and 7-30 Hz in the basal ganglia, thalamus, and cortex. This study describes the dynamics of a physiologically based mean-field model of the basal ganglia-thalamocortical system, and shows...
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Applying Machine Learning To Maize Traits Prediction
Heterosis is the improved or increased function of any biological quality in a hybrid offspring. We have studied yet the largest maize SNP dataset for traits prediction. We develop linear and non-linear models which consider relationships between different hybrids as well as other effect. Specially designed model pro...
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Perceptual Compressive Sensing based on Contrast Sensitivity Function: Can we avoid non-visible redundancies acquisition?
In this paper, we propose a novel CS approach in which the acquisition of non-visible information is also avoided.
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Poincaré surfaces of section around a 3-D irregular body: The case of asteroid 4179 Toutatis
In general, small bodies of the solar system, e.g., asteroids and comets, have a very irregular shape. This feature affects significantly the gravitational potential around these irregular bodies, which hinders dynamical studies. The Poincaré surface of sec- tion technique is often used to look for stable and chaotic...
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On the second Dirichlet eigenvalue of some nonlinear anisotropic elliptic operators
Let $\Omega$ be a bounded open set of $\mathbb R^{n}$, $n\ge 2$. In this paper we mainly study some properties of the second Dirichlet eigenvalue $\lambda_{2}(p,\Omega)$ of the anisotropic $p$-Laplacian \[ -\mathcal Q_{p}u:=-\textrm{div} \left(F^{p-1}(\nabla u)F_\xi (\nabla u)\right), \] where $F$ is a suitable smoot...
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A parametric level-set method for partially discrete tomography
This paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We represent the geometry of the anomaly using a level-set function, which we represent using rad...
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Using PCA and Factor Analysis for Dimensionality Reduction of Bio-informatics Data
Large volume of Genomics data is produced on daily basis due to the advancement in sequencing technology. This data is of no value if it is not properly analysed. Different kinds of analytics are required to extract useful information from this raw data. Classification, Prediction, Clustering and Pattern Extraction a...
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Three-dimensional vortex structures and dynamics in hexagonal manganites
Hexagonal manganites REMnO3 (RE, rare earths) have attracted significant attention due to their potential applications as multiferroic materials and the intriguing physics associated with the topological defects. The two-dimensional (2D) and 3D domain and vortex structure evolution of REMnO3 is predicted using the ph...
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A spectral-Galerkin turbulent channel flow solver for large-scale simulations
A fully (pseudo-)spectral solver for direct numerical simulations of large-scale turbulent channel flows is described. The solver utilizes the Chebyshev base functions suggested by J. Shen [SIAM J. Sci. Comput., 16, 1, 1995], that lead to stable and robust numerical schemes, even at very large scale. New and fast alg...
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Bi-Lagrangian structures and Teichmüller theory
This paper has two purposes: the first is to study several structures on manifolds in the general setting of real and complex differential geometry; the second is to apply this study to Teichmüller theory. We primarily focus on bi-Lagrangian structures, which are the data of a symplectic structure and a pair of trans...
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Proof of a conjecture of Abdollahi-Akbari-Maimani concerning the non-commutative graph of finite groups
The non--commuting graph $\Gamma(G)$ of a non--abelian group $G$ is defined as follows. The vertex set $V(\Gamma(G))$ of $\Gamma(G)$ is $G\setminus Z(G)$ where $Z(G)$ denotes the center of $G$ and two vertices $x$ and $y$ are adjacent if and only if $xy\neq yx$. For non--abelian finite groups $G$ and $H$ it is conjec...
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LQG Control and Sensing Co-design
Linear-Quadratic-Gaussian (LQG) control is concerned with the design of an optimal controller and estimator for linear Gaussian systems with imperfect state information. Standard LQG control assumes the set of sensor measurements to be fed to the estimator to be given. However, in many problems in networked systems a...
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Subspace Learning in The Presence of Sparse Structured Outliers and Noise
Subspace learning is an important problem, which has many applications in image and video processing. It can be used to find a low-dimensional representation of signals and images. But in many applications, the desired signal is heavily distorted by outliers and noise, which negatively affect the learned subspace. In...
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Trends in scientific research in Online Information Review. Part 2. Mapping the scientific knowledge through bibliometric and social network analyses
Objective. The purpose of this work is to analyse the knowledge structure and trends in scientific research in the Online Information Reviews journal by bibliometric analysis of key words and social network analysis of co-words. Methods. Key words included in a set of 758 papers included in the Web of Science databas...
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Balance between quantum Markov semigroups
The concept of balance between two state preserving quantum Markov semigroups on von Neumann algebras is introduced and studied as an extension of conditions appearing in the theory of quantum detailed balance. This is partly motivated by the theory of joinings. Balance is defined in terms of certain correlated state...
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Deep Stochastic Configuration Networks with Universal Approximation Property
This paper develops a randomized approach for incrementally building deep neural networks, where a supervisory mechanism is proposed to constrain the random assignment of the weights and biases, and all the hidden layers have direct links to the output layer. A fundamental result on the universal approximation proper...
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On convergence for graphexes
We study four different notions of convergence for graphexes, recently introduced by Borgs, Chayes, Cohn and Holden, and by Veitch and Roy. We give some properties of them and some relations between them. We also extend results by Veitch and Roy on convergence of empirical graphons.
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Improving text classification with vectors of reduced precision
This paper presents the analysis of the impact of a floating-point number precision reduction on the quality of text classification. The precision reduction of the vectors representing the data (e.g. TF-IDF representation in our case) allows for a decrease of computing time and memory footprint on dedicated hardware ...
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On ramification in transcendental extensions of local fields
Let $L/K$ be an extension of complete discrete valuation fields, and assume that the residue field of $K$ is perfect and of positive characteristic. The residue field of $L$ is not assumed to be perfect. In this paper, we prove a formula for the Swan conductor of the image of a character $\chi \in H^1(K, \mathbb{Q}/\...
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Local Formulas for Ehrhart Coefficients from Lattice Tiles
As shown by McMullen in 1983, the coefficients of the Ehrhart polynomial of a lattice polytope can be written as a weighted sum of facial volumes. The weights in such a local formula depend only on the outer normal cones of faces, but are far from being unique. In this paper, we develop an infinite class of such loca...
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Atypicality for Heart Rate Variability Using a Pattern-Tree Weighting Method
Heart rate variability (HRV) is a vital measure of the autonomic nervous system functionality and a key indicator of cardiovascular condition. This paper proposes a novel method, called pattern tree which is an extension of Willem's context tree to real-valued data, to investigate HRV via an atypicality framework. In...
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