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Learning to detect chest radiographs containing lung nodules using visual attention networks
Machine learning approaches hold great potential for the automated detection of lung nodules in chest radiographs, but training the algorithms requires vary large amounts of manually annotated images, which are difficult to obtain. Weak labels indicating whether a radiograph is likely to contain pulmonary nodules are...
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New conformal map for the Sinc approximation for exponentially decaying functions over the semi-infinite interval
The Sinc approximation has shown high efficiency for numerical methods in many fields. Conformal maps play an important role in the success, i.e., appropriate conformal map must be employed to elicit high performance of the Sinc approximation. Appropriate conformal maps have been proposed for typical cases; however, ...
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Evidence synthesis for stochastic epidemic models
In recent years the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the use of multiple data sources to estimate all quantities of interest. This review summarises the different types of stochastic epidemic mode...
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The multi-resonant Lugiato-Lefever model
We introduce a new model describing multiple resonances in Kerr optical cavities. It perfectly agrees quantitatively with the Ikeda map and predicts complex phenomena such as super cavity solitons and coexistence of multiple nonlinear states.
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Scalable Bayesian shrinkage and uncertainty quantification in high-dimensional regression
Bayesian shrinkage methods have generated a lot of recent interest as tools for high-dimensional regression and model selection. These methods naturally facilitate tractable uncertainty quantification and incorporation of prior information. A common feature of these models, including the Bayesian lasso, global-local ...
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Inclusion and Majorization Properties of Certain Subclasses of Multivalent Analytic Functions Involving a Linear Operator
The object of the present paper is to study certain properties and characteristics of the operator $Q_{p,\beta}^{\alpha}$defined on p-valent analytic function by using technique of differential subordination.We also obtained result involving majorization problems by applying the operator to p-valent analytic function...
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Tameness in least fixed-point logic and McColm's conjecture
We investigate fundamental model-theoretic dividing lines (the order property, the independence property, the strict order property, and the tree property 2) in the context of least fixed-point (LFP) logic over families of finite structures. We show that, unlike the first-order (FO) case, the order property and the i...
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Enhanced activity of the Southern Taurids in 2005 and 2015
The paper presents an analysis of Polish Fireball Network (PFN) observations of enhanced activity of the Southern Taurid meteor shower in 2005 and 2015. In 2005, between October 20 and November 10, seven stations of PFN determined 107 accurate orbits with 37 of them belonging to the Southern Taurid shower. In the sam...
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Comparing anticyclotomic Selmer groups of positive coranks for congruent modular forms
We study the variation of Iwasawa invariants of the anticyclotomic Selmer groups of congruent modular forms under the Heegner hypothesis. In particular, we show that even if the Selmer groups we study may have positive coranks, the mu-invariant vanishes for one modular form if and only if it vanishes for the other, a...
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Predicting the Results of LTL Model Checking using Multiple Machine Learning Algorithms
In this paper, we study how to predict the results of LTL model checking using some machine learning algorithms. Some Kripke structures and LTL formulas and their model checking results are made up data set. The approaches based on the Random Forest (RF), K-Nearest Neighbors (KNN), Decision tree (DT), and Logistic Re...
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Magnetoelectric properties of the layered room-temperature antiferromagnets BaMn2P2 and BaMn2As2
Properties of two ThCr2Si2-type materials are discussed within the context of their established structural and magnetic symmetries. Both materials develop collinear, G-type antiferromagnetic order above room temperature, and magnetic ions occupy acentric sites in centrosymmetric structures. We refute a previous conje...
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Discrete Spectrum Reconstruction using Integral Approximation Algorithm
An inverse problem in spectroscopy is considered. The objective is to restore the discrete spectrum from observed spectrum data, taking into account the spectrometer's line spread function. The problem is reduced to solution of a system of linear-nonlinear equations (SLNE) with respect to intensities and frequencies ...
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Tackling Over-pruning in Variational Autoencoders
Variational autoencoders (VAE) are directed generative models that learn factorial latent variables. As noted by Burda et al. (2015), these models exhibit the problem of factor over-pruning where a significant number of stochastic factors fail to learn anything and become inactive. This can limit their modeling power...
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Elastic collision and molecule formation of spatiotemporal light bullets in a cubic-quintic nonlinear medium
We consider the statics and dynamics of a stable, mobile three-dimensional (3D) spatiotemporal light bullet in a cubic-quintic nonlinear medium with a focusing cubic nonlinearity above a critical value and any defocusing quintic nonlinearity. The 3D light bullet can propagate with a constant velocity in any direction...
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From Query-By-Keyword to Query-By-Example: LinkedIn Talent Search Approach
One key challenge in talent search is to translate complex criteria of a hiring position into a search query, while it is relatively easy for a searcher to list examples of suitable candidates for a given position. To improve search efficiency, we propose the next generation of talent search at LinkedIn, also referre...
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Cyber-Physical System for Energy-Efficient Stadium Operation: Methodology and Experimental Validation
The environmental impacts of medium to large scale buildings receive substantial attention in research, industry, and media. This paper studies the energy savings potential of a commercial soccer stadium during day-to-day operation. Buildings of this kind are characterized by special purpose system installations like...
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On Bayesian Exponentially Embedded Family for Model Order Selection
In this paper, we derive a Bayesian model order selection rule by using the exponentially embedded family method, termed Bayesian EEF. Unlike many other Bayesian model selection methods, the Bayesian EEF can use vague proper priors and improper noninformative priors to be objective in the elicitation of parameter pri...
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Estimating solar flux density at low radio frequencies using a sky brightness model
Sky models have been used in the past to calibrate individual low radio frequency telescopes. Here we generalize this approach from a single antenna to a two element interferometer and formulate the problem in a manner to allow us to estimate the flux density of the Sun using the normalized cross-correlations (visibi...
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Revisiting Activation Regularization for Language RNNs
Recurrent neural networks (RNNs) serve as a fundamental building block for many sequence tasks across natural language processing. Recent research has focused on recurrent dropout techniques or custom RNN cells in order to improve performance. Both of these can require substantial modifications to the machine learnin...
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Non-equilibrium time dynamics of genetic evolution
Biological systems are typically highly open, non-equilibrium systems that are very challenging to understand from a statistical mechanics perspective. While statistical treatments of evolutionary biological systems have a long and rich history, examination of the time-dependent non-equilibrium dynamics has been less...
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On the scaling of entropy viscosity in high order methods
In this work, we outline the entropy viscosity method and discuss how the choice of scaling influences the size of viscosity for a simple shock problem. We present examples to illustrate the performance of the entropy viscosity method under two distinct scalings.
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An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image Classification
Convolutional neural networks (CNNs) are similar to "ordinary" neural networks in the sense that they are made up of hidden layers consisting of neurons with "learnable" parameters. These neurons receive inputs, performs a dot product, and then follows it with a non-linearity. The whole network expresses the mapping ...
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Derivation of the cutoff length from the quantum quadratic enhancement of a mass in vacuum energy constant Lambda
Ultraviolet self-interaction energies in field theory sometimes contain meaningful physical quantities. The self-energies in such as classical electrodynamics are usually subtracted from the rest mass. For the consistent treatment of energies as sources of curvature in the Einstein field equations, this study include...
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Exact MAP Inference by Avoiding Fractional Vertices
Given a graphical model, one essential problem is MAP inference, that is, finding the most likely configuration of states according to the model. Although this problem is NP-hard, large instances can be solved in practice. A major open question is to explain why this is true. We give a natural condition under which w...
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Study on a Poisson's Equation Solver Based On Deep Learning Technique
In this work, we investigated the feasibility of applying deep learning techniques to solve Poisson's equation. A deep convolutional neural network is set up to predict the distribution of electric potential in 2D or 3D cases. With proper training data generated from a finite difference solver, the strong approximati...
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On the compressibility of the transition-metal carbides and nitrides alloys Zr_xNb_{1-x}C and Zr_xNb_{1-x}N
The 4d-transition-metals carbides (ZrC, NbC) and nitrides (ZrN, NbN) in the rocksalt structure, as well as their ternary alloys, have been recently studied by means of a first-principles full potential linearized augmented plane waves method within the local density approximation. These materials are important becaus...
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On multifractals: a non-linear study of actigraphy data
This work aimed, to determine the characteristics of activity series from fractal geometry concepts application, in addition to evaluate the possibility of identifying individuals with fibromyalgia. Activity level data were collected from 27 healthy subjects and 27 fibromyalgia patients, with the use of clock-like de...
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Exact semi-separation of variables in waveguides with nonplanar boundaries
Series expansions of unknown fields $\Phi=\sum\varphi_n Z_n$ in elongated waveguides are commonly used in acoustics, optics, geophysics, water waves and other applications, in the context of coupled-mode theories (CMTs). The transverse functions $Z_n$ are determined by solving local Sturm-Liouville problems (referenc...
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Universality for eigenvalue algorithms on sample covariance matrices
We prove a universal limit theorem for the halting time, or iteration count, of the power/inverse power methods and the QR eigenvalue algorithm. Specifically, we analyze the required number of iterations to compute extreme eigenvalues of random, positive-definite sample covariance matrices to within a prescribed tole...
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Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function
We demonstrate that in residual neural networks (ResNets) dynamical isometry is achievable irrespectively of the activation function used. We do that by deriving, with the help of Free Probability and Random Matrix Theories, a universal formula for the spectral density of the input-output Jacobian at initialization, ...
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Similarity-based Multi-label Learning
Multi-label classification is an important learning problem with many applications. In this work, we propose a principled similarity-based approach for multi-label learning called SML. We also introduce a similarity-based approach for predicting the label set size. The experimental results demonstrate the effectivene...
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Burst Synchronization in A Scale-Free Neuronal Network with Inhibitory Spike-Timing-Dependent Plasticity
We are concerned about burst synchronization (BS), related to neural information processes in health and disease, in the Barabási-Albert scale-free network (SFN) composed of inhibitory bursting Hindmarsh-Rose neurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibito...
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The Arrow of Time in the collapse of collisionless self-gravitating systems: non-validity of the Vlasov-Poisson equation during violent relaxation
The collapse of a collisionless self-gravitating system, with the fast achievement of a quasi-stationary state, is driven by violent relaxation, with a typical particle interacting with the time-changing collective potential. It is traditionally assumed that this evolution is governed by the Vlasov-Poisson equation, ...
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Numerical Observation of Parafermion Zero Modes and their Stability in 2D Topological States
The possibility of realizing non-Abelian excitations (non-Abelions) in two-dimensional (2D) Abelian states of matter has generated a lot of interest recently. A well-known example of such non-Abelions are parafermion zeros modes (PFZMs) which can be realized at the endpoints of the so called genons in fractional quan...
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Stochastic Optimal Control of Epidemic Processes in Networks
We approach the development of models and control strategies of susceptible-infected-susceptible (SIS) epidemic processes from the perspective of marked temporal point processes and stochastic optimal control of stochastic differential equations (SDEs) with jumps. In contrast to previous work, this novel perspective ...
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Improved upper bounds in the moving sofa problem
The moving sofa problem, posed by L. Moser in 1966, asks for the planar shape of maximal area that can move around a right-angled corner in a hallway of unit width. It is known that a maximal area shape exists, and that its area is at least 2.2195... - the area of an explicit construction found by Gerver in 1992 - an...
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Neural correlates of episodic memory in the Memento cohort
IntroductionThe free and cued selective reminding test is used to identify memory deficits in mild cognitive impairment and demented patients. It allows assessing three processes: encoding, storage, and recollection of verbal episodic memory.MethodsWe investigated the neural correlates of these three memory processes...
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Neighborhood-Based Label Propagation in Large Protein Graphs
Understanding protein function is one of the keys to understanding life at the molecular level. It is also important in several scenarios including human disease and drug discovery. In this age of rapid and affordable biological sequencing, the number of sequences accumulating in databases is rising with an increasin...
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Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions
Compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that tar...
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Closure Properties in the Class of Multiple Context Free Groups
We show that the class of groups with $k$-multiple context-free word problem is closed under graphs of groups with finite edge groups.
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Random gauge models of the superconductor-insulator transition in two-dimensional disordered superconductors
We study numerically the superconductor-insulator transition in two-dimensional inhomogeneous superconductors with gauge disorder, described by four different quantum rotor models: a gauge glass, a flux glass, a binary phase glass and a Gaussian phase glass. The first two models, describe the combined effect of geome...
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Extended quantum field theory, index theory and the parity anomaly
We use techniques from functorial quantum field theory to provide a geometric description of the parity anomaly in fermionic systems coupled to background gauge and gravitational fields on odd-dimensional spacetimes. We give an explicit construction of a geometric cobordism bicategory which incorporates general backg...
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Learning Graphical Models Using Multiplicative Weights
We give a simple, multiplicative-weight update algorithm for learning undirected graphical models or Markov random fields (MRFs). The approach is new, and for the well-studied case of Ising models or Boltzmann machines, we obtain an algorithm that uses a nearly optimal number of samples and has quadratic running time...
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Neutron response of PARIS phoswich detector
We have studied neutron response of PARIS phoswich [LaBr$_3$(Ce)-NaI(Tl)] detector which is being developed for measuring the high energy (E$_{\gamma}$ = 5 - 30 MeV) $\gamma$ rays emitted from the decay of highly collective states in atomic nuclei. The relative neutron detection efficiency of LaBr$_3$(Ce) and NaI(Tl)...
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Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks
The mine detection in an unexplored area is an optimization problem where multiple mines, randomly distributed throughout an area, need to be discovered and disarmed in a minimum amount of time. We propose a strategy to explore an unknown area, using a stigmergy approach based on ants behavior, and a novel swarm base...
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A polynomial time knot polynomial
We present the strongest known knot invariant that can be computed effectively (in polynomial time).
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Corruption-free scheme of entering into contract: mathematical model
The main purpose of this paper is to formalize the modelling process, analysis and mathematical definition of corruption when entering into a contract between principal agent and producers. The formulation of the problem and the definition of concepts for the general case are considered. For definiteness, all calcula...
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Geometric Biplane Graphs I: Maximal Graphs
We study biplane graphs drawn on a finite planar point set $S$ in general position. This is the family of geometric graphs whose vertex set is $S$ and can be decomposed into two plane graphs. We show that two maximal biplane graphs---in the sense that no edge can be added while staying biplane---may differ in the num...
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A Multiobjective Approach to Multimicrogrid System Design
The main goal of this paper is to design a market operator (MO) and a distribution network operator (DNO) for a network of microgrids in consideration of multiple objectives. This is a high-level design and only those microgrids with nondispatchable renewable energy sources are considered. For a power grid in the net...
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Neural Architecture for Question Answering Using a Knowledge Graph and Web Corpus
In Web search, entity-seeking queries often trigger a special Question Answering (QA) system. It may use a parser to interpret the question to a structured query, execute that on a knowledge graph (KG), and return direct entity responses. QA systems based on precise parsing tend to be brittle: minor syntax variations...
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Calculating the closed ordinal Ramsey number $R^{cl}(ω\cdot 2,3)^2$
We show that $R^{cl}(\omega\cdot 2,3)^2$ is equal to $\omega^3\cdot 2$.
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A spatially explicit capture recapture model for partially identified individuals when trap detection rate is less than one
Spatially explicit capture recapture (SECR) models have gained enormous popularity to solve abundance estimation problems in ecology. In this study, we develop a novel Bayesian SECR model that disentangles the process of animal movement through a detector from the process of recording data by a detector in the face o...
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Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Obtaining models that capture imaging markers relevant for disease progression and treatment monitoring is challenging. Models are typically based on large amounts of data with annotated examples of known markers aiming at automating detection. High annotation effort and the limitation to a vocabulary of known marker...
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ZOOpt: Toolbox for Derivative-Free Optimization
Recent advances of derivative-free optimization allow efficient approximating the global optimal solutions of sophisticated functions, such as functions with many local optima, non-differentiable and non-continuous functions. This article describes the ZOOpt (this https URL) toolbox that provides efficient derivative...
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Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler
In this work, we propose a model for estimating volatility from financial time series, extending the non-Gaussian family of space-state models with exact marginal likelihood proposed by Gamerman, Santos and Franco (2013). On the literature there are models focused on estimating financial assets risk, however, most of...
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Smart Guiding Glasses for Visually Impaired People in Indoor Environment
To overcome the travelling difficulty for the visually impaired group, this paper presents a novel ETA (Electronic Travel Aids)-smart guiding device in the shape of a pair of eyeglasses for giving these people guidance efficiently and safely. Different from existing works, a novel multi sensor fusion based obstacle a...
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Recurrent Poisson Factorization for Temporal Recommendation
Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribution. There are many variants of Poisson factorization methods who show state-of-the-art performance on real-world recommendation tasks. H...
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Categorification of sign-skew-symmetric cluster algebras and some conjectures on g-vectors
Using the unfolding method given in \cite{HL}, we prove the conjectures on sign-coherence and a recurrence formula respectively of ${\bf g}$-vectors for acyclic sign-skew-symmetric cluster algebras. As a following consequence, the conjecture is affirmed in the same case which states that the ${\bf g}$-vectors of any ...
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Capacitated Bounded Cardinality Hub Routing Problem: Model and Solution Algorithm
In this paper, we address the Bounded Cardinality Hub Location Routing with Route Capacity wherein each hub acts as a transshipment node for one directed route. The number of hubs lies between a minimum and a maximum and the hub-level network is a complete subgraph. The transshipment operations take place at the hub ...
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Large Kernel Matters -- Improve Semantic Segmentation by Global Convolutional Network
One of recent trends [30, 31, 14] in network architec- ture design is stacking small filters (e.g., 1x1 or 3x3) in the entire network because the stacked small filters is more ef- ficient than a large kernel, given the same computational complexity. However, in the field of semantic segmenta- tion, where we need to p...
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Is ram-pressure stripping an efficient mechanism to remove gas in galaxies?
We study how the gas in a sample of galaxies (M* > 10e9 Msun) in clusters, obtained in a cosmological simulation, is affected by the interaction with the intra-cluster medium (ICM). The dynamical state of each elemental parcel of gas is studied using the total energy. At z ~ 2, the galaxies in the simulation are even...
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Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data
We present hidden fluid mechanics (HFM), a physics informed deep learning framework capable of encoding an important class of physical laws governing fluid motions, namely the Navier-Stokes equations. In particular, we seek to leverage the underlying conservation laws (i.e., for mass, momentum, and energy) to infer h...
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Testing Network Structure Using Relations Between Small Subgraph Probabilities
We study the problem of testing for structure in networks using relations between the observed frequencies of small subgraphs. We consider the statistics \begin{align*} T_3 & =(\text{edge frequency})^3 - \text{triangle frequency}\\ T_2 & =3(\text{edge frequency})^2(1-\text{edge frequency}) - \text{V-shape frequency} ...
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A 3D MHD simulation of SN 1006: a polarized emission study for the turbulent case
Three dimensional magnetohydrodynamical simulations were carried out in order to perform a new polarization study of the radio emission of the supernova remnant SN 1006. These simulations consider that the remnant expands into a turbulent interstellar medium (including both magnetic field and density perturbations). ...
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Hierarchical Detail Enhancing Mesh-Based Shape Generation with 3D Generative Adversarial Network
Automatic mesh-based shape generation is of great interest across a wide range of disciplines, from industrial design to gaming, computer graphics and various other forms of digital art. While most traditional methods focus on primitive based model generation, advances in deep learning made it possible to learn 3-dim...
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Combined analysis of galaxy cluster number count, thermal Sunyaev-Zel'dovich power spectrum, and bispectrum
The Sunyaev-Zel'dovich (SZ) effect is a powerful probe of the evolution of structures in the universe, and is thus highly sensitive to cosmological parameters $\sigma_8$ and $\Omega_m$, though its power is hampered by the current uncertainties on the cluster mass calibration. In this analysis we revisit constraints o...
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On short cycle enumeration in biregular bipartite graphs
A number of recent works have used a variety of combinatorial constructions to derive Tanner graphs for LDPC codes and some of these have been shown to perform well in terms of their probability of error curves and error floors. Such graphs are bipartite and many of these constructions yield biregular graphs where th...
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Exhaled breath barbotage: a new method for pulmonary surfactant dysfunction assessment
Exhaled air contains aerosol of submicron droplets of the alveolar lining fluid (ALF), which are generated in the small airways of a human lung. Since the exhaled particles are micro-samples of the ALF, their trapping opens up an opportunity to collect non-invasively a native material from respiratory tract. Recent s...
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A Computational Study of the Role of Tonal Tension in Expressive Piano Performance
Expressive variations of tempo and dynamics are an important aspect of music performances, involving a variety of underlying factors. Previous work has showed a relation between such expressive variations (in particular expressive tempo) and perceptual characteristics derived from the musical score, such as musical e...
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On the least upper bound for the settling time of a class of fixed-time stable systems
This paper deals with the convergence time analysis of a class of fixed-time stable systems with the aim to provide a new non-conservative upper bound for its settling time. Our contribution is threefold. First, we revisit a well-known class of fixed-time stable systems showing the conservatism of the classical upper...
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Self-organization and the Maximum Empower Principle in the Framework of max-plus Algebra
Self-organization is a process where order of a whole system arises out of local interactions between small components of a system. Emergy, defined as the amount of (solar) energy used to make a product or a service, is becoming an important ecological indicator. To explain observed self-organization of systems by em...
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Nonequilibrium Work and its Hamiltonian Connection for a Microstate in Nonequilibrium Statistical Thermodynamics: A Case of Mistaken Identity
Nonequilibrium work-Hamiltonian connection for a microstate plays a central role in diverse branches of statistical thermodynamics (fluctuation theorems, quantum thermodynamics, stochastic thermodynamics, etc.). We show that the change in the Hamiltonian for a microstate should be identified with the work done by it,...
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Thick Subcategories of the stable category of modules over the exterior algebra I
We study thick subcategories defined by modules of complexity one in $\underline{\md}R$, where $R$ is the exterior algebra in $n+1$ indeterminates.
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Planet-driven spiral arms in protoplanetary disks: II. Implications
We examine whether various characteristics of planet-driven spiral arms can be used to constrain the masses of unseen planets and their positions within their disks. By carrying out two-dimensional hydrodynamic simulations varying planet mass and disk gas temperature, we find that a larger number of spiral arms form ...
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Ideal structure and pure infiniteness of ample groupoid $C^*$-algebras
In this paper, we study the ideal structure of reduced $C^*$-algebras $C^*_r(G)$ associated to étale groupoids $G$. In particular, we characterize when there is a one-to-one correspondence between the closed, two-sided ideals in $C_r^*(G)$ and the open invariant subsets of the unit space $G^{(0)}$ of $G$. As a conseq...
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Nonparametric mean curvature type flows of graphs with contact angle conditions
In this paper we study nonparametric mean curvature type flows in $M\times\mathbb{R}$ which are represented as graphs $(x,u(x,t))$ over a domain in a Riemannian manifold $M$ with prescribed contact angle. The speed of $u$ is the mean curvature speed minus an admissible function $\psi(x,u,Du)$. Long time existence and...
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Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals
In this article we develop a new sequential Monte Carlo (SMC) method for multilevel (ML) Monte Carlo estimation. In particular, the method can be used to estimate expectations with respect to a target probability distribution over an infinite-dimensional and non-compact space as given, for example, by a Bayesian inve...
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Spontaneous symmetry breaking as a triangular relation between pairs of Goldstone bosons and the degenerate vacuum: Interactions of D-branes
We formulate the Nambu-Goldstone theorem as a triangular relation between pairs of Goldstone bosons with the degenerate vacuum. The vacuum degeneracy is then a natural consequence of this relation. Inside the scenario of String Theory, we then find that there is a correspondence between the way how the $D$-branes int...
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Differentially Private Dropout
Large data collections required for the training of neural networks often contain sensitive information such as the medical histories of patients, and the privacy of the training data must be preserved. In this paper, we introduce a dropout technique that provides an elegant Bayesian interpretation to dropout, and sh...
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On (in)stabilities of perturbations in mimetic models with higher derivatives
Usually when applying the mimetic model to the early universe, higher derivative terms are needed to promote the mimetic field to be dynamical. However such models suffer from the ghost and/or the gradient instabilities and simple extensions cannot cure this pathology. We point out in this paper that it is possible t...
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Quantitative Connection Between Ensemble Thermodynamics and Single-Molecule Kinetics: A Case Study Using Cryogenic Electron Microscopy and Single-Molecule Fluorescence Resonance Energy Transfer Investigations of the Ribosome
At equilibrium, thermodynamic and kinetic information can be extracted from biomolecular energy landscapes by many techniques. However, while static, ensemble techniques yield thermodynamic data, often only dynamic, single-molecule techniques can yield the kinetic data that describes transition-state energy barriers....
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Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training
Generative Adversarial Networks (GANs) have become a widely popular framework for generative modelling of high-dimensional datasets. However their training is well-known to be difficult. This work presents a rigorous statistical analysis of GANs providing straight-forward explanations for common training pathologies ...
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METAGUI 3: a graphical user interface for choosing the collective variables in molecular dynamics simulations
Molecular dynamics (MD) simulations allow the exploration of the phase space of biopolymers through the integration of equations of motion of their constituent atoms. The analysis of MD trajectories often relies on the choice of collective variables (CVs) along which the dynamics of the system is projected. We develo...
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Model compression as constrained optimization, with application to neural nets. Part II: quantization
We consider the problem of deep neural net compression by quantization: given a large, reference net, we want to quantize its real-valued weights using a codebook with $K$ entries so that the training loss of the quantized net is minimal. The codebook can be optimally learned jointly with the net, or fixed, as for bi...
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Three Skewed Matrix Variate Distributions
Three-way data can be conveniently modelled by using matrix variate distributions. Although there has been a lot of work for the matrix variate normal distribution, there is little work in the area of matrix skew distributions. Three matrix variate distributions that incorporate skewness, as well as other flexible pr...
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Anticipating Persistent Infection
We explore the emergence of persistent infection in a closed region where the disease progression of the individuals is given by the SIRS model, with an individual becoming infected on contact with another infected individual within a given range. We focus on the role of synchronization in the persistence of contagio...
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The first global-scale 30 m resolution mangrove canopy height map using Shuttle Radar Topography Mission data
No high-resolution canopy height map exists for global mangroves. Here we present the first global mangrove height map at a consistent 30 m pixel resolution derived from digital elevation model data collected through shuttle radar topography mission. Additionally, we refined the current global mangrove area maps by d...
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Direct Estimation of Regional Wall Thicknesses via Residual Recurrent Neural Network
Accurate estimation of regional wall thicknesses (RWT) of left ventricular (LV) myocardium from cardiac MR sequences is of significant importance for identification and diagnosis of cardiac disease. Existing RWT estimation still relies on segmentation of LV myocardium, which requires strong prior information and user...
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Non-dipole recollision-gated double ionization and observable effects
Using a three-dimensional semiclassical model, we study double ionization for strongly-driven He fully accounting for magnetic field effects. For linearly and slightly elliptically polarized laser fields, we show that recollisions and the magnetic field combined act as a gate. This gate favors more transverse - with ...
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A Survey of Active Attacks on Wireless Sensor Networks and their Countermeasures
Lately, Wireless Sensor Networks (WSNs) have become an emerging technology and can be utilized in some crucial circumstances like battlegrounds, commercial applications, habitat observing, buildings, smart homes, traffic surveillance and other different places. One of the foremost difficulties that WSN faces nowadays...
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A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees
We present a new Frank-Wolfe (FW) type algorithm that is applicable to minimization problems with a nonsmooth convex objective. We provide convergence bounds and show that the scheme yields so-called coreset results for various Machine Learning problems including 1-median, Balanced Development, Sparse PCA, Graph Cuts...
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The problem of boundary conditions for the shallow water equations (Russian)
The problem of choice of boundary conditions are discussed for the case of numerical integration of the shallow water equations on a substantially irregular relief. In modeling of unsteady surface water flows has a dynamic boundary partitioning liquid and dry bottom. The situation is complicated by the emergence of s...
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The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains
We introduce the exit time finite state projection (ETFSP) scheme, a truncation-based method that yields approximations to the exit distribution and occupation measure associated with the time of exit from a domain (i.e., the time of first passage to the complement of the domain) of time-homogeneous continuous-time M...
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Ontological Multidimensional Data Models and Contextual Data Qality
Data quality assessment and data cleaning are context-dependent activities. Motivated by this observation, we propose the Ontological Multidimensional Data Model (OMD model), which can be used to model and represent contexts as logic-based ontologies. The data under assessment is mapped into the context, for addition...
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Time-Assisted Authentication Protocol
Authentication is the first step toward establishing a service provider and customer (C-P) association. In a mobile network environment, a lightweight and secure authentication protocol is one of the most significant factors to enhance the degree of service persistence. This work presents a secure and lightweight key...
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Improved Bounds for Online Dominating Sets of Trees
The online dominating set problem is an online variant of the minimum dominating set problem, which is one of the most important NP-hard problems on graphs. This problem is defined as follows: Given an undirected graph $G = (V, E)$, in which $V$ is a set of vertices and $E$ is a set of edges. We say that a set $D \su...
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Systematical design and three-dimensional simulation of X-ray FEL oscillator for Shanghai Coherent Light Facility
Shanghai Coherent Light Facility (SCLF) is a quasi-CW hard X-ray free electron laser user facility which is recently proposed. Due to the high repetition rate, high quality electron beams, it is straightforward to consider an X-ray free electron laser oscillator (XFELO) operation for SCLF. The main processes for XFEL...
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Who is the infector? Epidemic models with symptomatic and asymptomatic cases
What role do asymptomatically infected individuals play in the transmission dynamics? There are many diseases, such as norovirus and influenza, where some infected hosts show symptoms of the disease while others are asymptomatically infected, i.e. do not show any symptoms. The current paper considers a class of epide...
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Calibration of a two-state pitch-wise HMM method for note segmentation in Automatic Music Transcription systems
Many methods for automatic music transcription involves a multi-pitch estimation method that estimates an activity score for each pitch. A second processing step, called note segmentation, has to be performed for each pitch in order to identify the time intervals when the notes are played. In this study, a pitch-wise...
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Action-depedent Control Variates for Policy Optimization via Stein's Identity
Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems. However, it still often suffers from the large variance issue on policy gradient estimation, which leads to poor sample efficiency during training. In this work, we propose a control variate method to ef...
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