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Quandle rings
In this paper, a theory of quandle rings is proposed for quandles analogous to the classical theory of group rings for groups, and interconnections between quandles and associated quandle rings are explored.
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On the application of Laguerre's method to the polynomial eigenvalue problem
The polynomial eigenvalue problem arises in many applications and has received a great deal of attention over the last decade. The use of root-finding methods to solve the polynomial eigenvalue problem dates back to the work of Kublanovskaya (1969, 1970) and has received a resurgence due to the work of Bini and Nofer...
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Limiting Behaviour of the Teichmüller Harmonic Map Flow
In this paper we study the Teichmüller harmonic map flow as introduced by Rupflin and Topping [15]. It evolves pairs of maps and metrics $(u,g)$ into branched minimal immersions, or equivalently into weakly conformal harmonic maps, where $u$ maps from a fixed closed surface $M$ with metric $g$ to a general target man...
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Invariant measures for the actions of the modular group
In this note, we give a nature action of the modular group on the ends of the infinite (p + 1)-cayley tree, for each prime p. We show that there is a unique invariant probability measure for each p.
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Cartesian Fibrations and Representability
In higher category theory, we use fibrations to model presheaves. In this paper we introduce a new method to build such fibrations. Concretely, for suitable reflective subcategories of simplicial spaces, we build fibrations that model presheaves valued in that subcategory. Using this we can build Cartesian fibrations...
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Signal coupling to embedded pitch adapters in silicon sensors
We have examined the effects of embedded pitch adapters on signal formation in n-substrate silicon microstrip sensors with data from beam tests and simulation. According to simulation, the presence of the pitch adapter metal layer changes the electric field inside the sensor, resulting in slowed signal formation on t...
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Winds and radiation in unison: a new semi-analytic feedback model for cloud dissolution
Star clusters interact with the interstellar medium (ISM) in various ways, most importantly in the destruction of molecular star-forming clouds, resulting in inefficient star formation on galactic scales. On cloud scales, ionizing radiation creates \hii regions, while stellar winds and supernovae drive the ISM into t...
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Analysis-of-marginal-Tail-Means (ATM): a robust method for discrete black-box optimization
We present a new method, called Analysis-of-marginal-Tail-Means (ATM), for effective robust optimization of discrete black-box problems. ATM has important applications to many real-world engineering problems (e.g., manufacturing optimization, product design, molecular engineering), where the objective to optimize is ...
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Modular System for Shelves and Coasts (MOSSCO v1.0) - a flexible and multi-component framework for coupled coastal ocean ecosystem modelling
Shelf and coastal sea processes extend from the atmosphere through the water column and into the sea bed. These processes are driven by physical, chemical, and biological interactions at local scales, and they are influenced by transport and cross strong spatial gradients. The linkages between domains and many differ...
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How big was Galileo's impact? Percussion in the Sixth Day of the "Two New Sciences"
The Giornata Sesta about the Force of Percussion is a relatively less known Chapter from the Galileo's masterpiece "Discourse about Two New Sciences". It was first published lately (1718), long after the first edition of the Two New Sciences (1638) and Galileo's death (1642). The Giornata Sesta focuses on how to quan...
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Radar, without tears
A brief introduction to radar: principles, Doppler effect, antennas, waveforms, power budget - and future radars. [13 pages]
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A Multi-Stage Algorithm for Acoustic Physical Model Parameters Estimation
One of the challenges in computational acoustics is the identification of models that can simulate and predict the physical behavior of a system generating an acoustic signal. Whenever such models are used for commercial applications an additional constraint is the time-to-market, making automation of the sound desig...
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A Warped Product Splitting Theorem Through Weak KAM Theory
In this paper, we strengthen the splitting theorem proved in [14, 15] and provide a different approach using ideas from the weak KAM theory.
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Learning Instance Segmentation by Interaction
We present an approach for building an active agent that learns to segment its visual observations into individual objects by interacting with its environment in a completely self-supervised manner. The agent uses its current segmentation model to infer pixels that constitute objects and refines the segmentation mode...
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On convergence rate of stochastic proximal point algorithm without strong convexity, smoothness or bounded gradients
Significant parts of the recent learning literature on stochastic optimization algorithms focused on the theoretical and practical behaviour of stochastic first order schemes under different convexity properties. Due to its simplicity, the traditional method of choice for most supervised machine learning problems is ...
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Learning Texture Manifolds with the Periodic Spatial GAN
This paper introduces a novel approach to texture synthesis based on generative adversarial networks (GAN) (Goodfellow et al., 2014). We extend the structure of the input noise distribution by constructing tensors with different types of dimensions. We call this technique Periodic Spatial GAN (PSGAN). The PSGAN has s...
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Generating Representative Executions [Extended Abstract]
Analyzing the behaviour of a concurrent program is made difficult by the number of possible executions. This problem can be alleviated by applying the theory of Mazurkiewicz traces to focus only on the canonical representatives of the equivalence classes of the possible executions of the program. This paper presents ...
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Extended periodic links and HOMFLYPT polynomial
Extended strongly periodic links have been introduced by Przytycki and Sokolov as a symmetric surgery presentation of three-manifolds on which the finite cyclic group acts without fixed points. The purpose of this paper is to prove that the symmetry of these links is reflected by the first coefficients of the HOMFLYP...
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Exploring Cross-Domain Data Dependencies for Smart Homes to Improve Energy Efficiency
Over the past decade, the idea of smart homes has been conceived as a potential solution to counter energy crises or to at least mitigate its intensive destructive consequences in the residential building sector.
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Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Deep learning models can take weeks to train on a single GPU-equipped machine, necessitating scaling out DL training to a GPU-cluster. However, current distributed DL implementations can scale poorly due to substantial parameter synchronization over the network, because the high throughput of GPUs allows more data ba...
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A closed formula for illiquid corporate bonds and an application to the European market
We deduce a simple closed formula for illiquid corporate coupon bond prices when liquid bonds with similar characteristics (e.g. maturity) are present in the market for the same issuer. The key model parameter is the time-to-liquidate a position, i.e. the time that an experienced bond trader takes to liquidate a give...
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Toric Codes, Multiplicative Structure and Decoding
Long linear codes constructed from toric varieties over finite fields, their multiplicative structure and decoding. The main theme is the inherent multiplicative structure on toric codes. The multiplicative structure allows for \emph{decoding}, resembling the decoding of Reed-Solomon codes and aligns with decoding by...
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Outlier Detection by Consistent Data Selection Method
Often the challenge associated with tasks like fraud and spam detection[1] is the lack of all likely patterns needed to train suitable supervised learning models. In order to overcome this limitation, such tasks are attempted as outlier or anomaly detection tasks. We also hypothesize that out- liers have behavioral p...
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Basic quantizations of $D=4$ Euclidean, Lorentz, Kleinian and quaternionic $\mathfrak{o}^{\star}(4)$ symmetries
We construct firstly the complete list of five quantum deformations of $D=4$ complex homogeneous orthogonal Lie algebra $\mathfrak{o}(4;\mathbb{C})\cong \mathfrak{o}(3;\mathbb{C})\oplus \mathfrak{o}(3;\mathbb{C})$, describing quantum rotational symmetry of four-dimensional complex space-time, in particular we provide...
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Supervising Unsupervised Learning with Evolutionary Algorithm in Deep Neural Network
A method to control results of gradient descent unsupervised learning in a deep neural network by using evolutionary algorithm is proposed. To process crossover of unsupervisedly trained models, the algorithm evaluates pointwise fitness of individual nodes in neural network. Labeled training data is randomly sampled ...
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Inductive Representation Learning in Large Attributed Graphs
Graphs (networks) are ubiquitous and allow us to model entities (nodes) and the dependencies (edges) between them. Learning a useful feature representation from graph data lies at the heart and success of many machine learning tasks such as classification, anomaly detection, link prediction, among many others. Many e...
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Evidence for Two Hot Jupiter Formation Paths
Disk migration and high-eccentricity migration are two well-studied theories to explain the formation of hot Jupiters. The former predicts that these planets can migrate up until the planet-star Roche separation ($a_{Roche}$) and the latter predicts they will tidally circularize at a minimum distance of 2$a_{Roche}$....
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High-resolution Spectroscopy and Spectropolarimetry of Selected Delta Scuti Pulsating Variables
The combination of photometry, spectroscopy and spectropolarimetry of the chemically peculiar stars often aims to study the complex physical phenomena such as stellar pulsation, chemical inhomogeneity, magnetic field and their interplay with stellar atmosphere and circumstellar environment. The prime objective of the...
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Majority and Minority Voted Redundancy for Safety-Critical Applications
A new majority and minority voted redundancy (MMR) scheme is proposed that can provide the same degree of fault tolerance as N-modular redundancy (NMR) but with fewer function units and a less sophisticated voting logic. Example NMR and MMR circuits were implemented using a 32/28nm CMOS process and compared. The resu...
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Tight Analysis for the 3-Majority Consensus Dynamics
We present a tight analysis for the well-studied randomized 3-majority dynamics of stabilizing consensus, hence answering the main open question of Becchetti et al. [SODA'16]. Consider a distributed system of n nodes, each initially holding an opinion in {1, 2, ..., k}. The system should converge to a setting where a...
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Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique
Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale gen...
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Superlinear scaling in the urban system of England of Wales. A comparison with US cities
According to the theory of urban scaling, urban indicators scale with city size in a predictable fashion. In particular, indicators of social and economic productivity are expected to have a superlinear relation. This behavior was verified for many urban systems, but recent findings suggest that this pattern may not ...
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Extensile actomyosin?
Living cells move thanks to assemblies of actin filaments and myosin motors that range from very organized striated muscle tissue to disordered intracellular bundles. The mechanisms powering these disordered structures are debated, and all models studied so far predict that they are contractile. We reexamine this pre...
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Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and Opportunities
There is an increasing interest in exploiting mobile sensing technologies and machine learning techniques for mental health monitoring and intervention. Researchers have effectively used contextual information, such as mobility, communication and mobile phone usage patterns for quantifying individuals' mood and wellb...
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Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning
Cardiac indices estimation is of great importance during identification and diagnosis of cardiac disease in clinical routine. However, estimation of multitype cardiac indices with consistently reliable and high accuracy is still a great challenge due to the high variability of cardiac structures and complexity of tem...
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Noncommutative hyperbolic metrics
We characterize certain noncommutative domains in terms of noncommutative holomorphic equivalence via a pseudometric that we define in purely algebraic terms. We prove some properties of this pseudometric and provide an application to free probability.
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Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing
We consider the problem of estimating a regression function in the common situation where the number of features is small, where interpretability of the model is a high priority, and where simple linear or additive models fail to provide adequate performance. To address this problem, we present Maximum Variance Total...
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Basin stability for chimera states
Chimera states, namely complex spatiotemporal patterns that consist of coexisting domains of spatially coherent and incoherent dynamics, are investigated in a network of coupled identical oscillators. These intriguing spatiotemporal patterns were first reported in nonlocally coupled phase oscillators, and it was show...
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On the Usage of Databases of Educational Materials in Macedonian Education
Technologies have become important part of our lives. The steps for introducing ICTs in education vary from country to country. The Republic of Macedonia has invested with a lot in installment of hardware and software in education and in teacher training. This research was aiming to determine the situation of usage o...
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Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching
We study the neural-linear bandit model for solving sequential decision-making problems with high dimensional side information. Neural-linear bandits leverage the representation power of deep neural networks and combine it with efficient exploration mechanisms, designed for linear contextual bandits, on top of the la...
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Breaking mean-motion resonances during Type I planet migration
We present two-dimensional hydrodynamical simulations of pairs of planets migrating simultaneously in the Type I regime in a protoplanetary disc. Convergent migration naturally leads to the trapping of these planets in mean-motion resonances. Once in resonance the planets' eccentricity grows rapidly, and disc-planet ...
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The Stretch to Stray on Time: Resonant Length of Random Walks in a Transient
First-passage times in random walks have a vast number of diverse applications in physics, chemistry, biology, and finance. In general, environmental conditions for a stochastic process are not constant on the time scale of the average first-passage time, or control might be applied to reduce noise. We investigate mo...
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Hierarchical Model for Long-term Video Prediction
Video prediction has been an active topic of research in the past few years. Many algorithms focus on pixel-level predictions, which generates results that blur and disintegrate within a few frames. In this project, we use a hierarchical approach for long-term video prediction. We aim at estimating high-level structu...
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Classical Music Clustering Based on Acoustic Features
In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and performed spectral clustering to find the clusters. Based on different resolution, the output clusters ...
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Many-Body-Localization : Strong Disorder perturbative approach for the Local Integrals of Motion
For random quantum spin models, the strong disorder perturbative expansion of the Local Integrals of Motion (LIOMs) around the real-spin operators is revisited. The emphasis is on the links with other properties of the Many-Body-Localized phase, in particular the memory in the dynamics of the local magnetizations and...
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Semi-supervised Learning for Discrete Choice Models
We introduce a semi-supervised discrete choice model to calibrate discrete choice models when relatively few requests have both choice sets and stated preferences but the majority only have the choice sets. Two classic semi-supervised learning algorithms, the expectation maximization algorithm and the cluster-and-lab...
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An Analytic Criterion for Turbulent Disruption of Planetary Resonances
Mean motion commensurabilities in multi-planet systems are an expected outcome of protoplanetary disk-driven migration, and their relative dearth in the observational data presents an important challenge to current models of planet formation and dynamical evolution. One natural mechanism that can lead to the dissolut...
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Electronic structure of transferred graphene/h-BN van der Waals heterostructures with nonzero stacking angles by nano-ARPES
In van der Waals heterostructures, the periodic potential from the Moiré superlattice can be used as a control knob to modulate the electronic structure of the constituent materials. Here we present a nanoscale angle-resolved photoemission spectroscopy (Nano-ARPES) study of transferred graphene/h-BN heterostructures ...
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Automatic sequences and generalised polynomials
We conjecture that bounded generalised polynomial functions cannot be generated by finite automata, except for the trivial case when they are ultimately periodic. Using methods from ergodic theory, we are able to partially resolve this conjecture, proving that any hypothetical counterexample is periodic away from a v...
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Robust Regulation of Infinite-Dimensional Port-Hamiltonian Systems
We will give general sufficient conditions under which a controller achieves robust regulation for a boundary control and observation system. Utilizing these conditions we construct a minimal order robust controller for an arbitrary order impedance passive linear port-Hamiltonian system. The theoretical results are i...
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Existence of travelling waves and high activation energy limits for a onedimensional thermo-diffusive lean spray flame model
We provide a mathematical analysis of a thermo-diffusive combustion model of lean spray flames, for which we prove the existence of travelling waves. In the high activation energy singular limit we show the existence of two distinct combustion regimes with a sharp transition -- the diffusion limited regime and the va...
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The Motion of Small Bodies in Space-time
We consider the motion of small bodies in general relativity. The key result captures a sense in which such bodies follow timelike geodesics (or, in the case of charged bodies, Lorentz-force curves). This result clarifies the relationship between approaches that model such bodies as distributions supported on a curve...
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Extracting urban impervious surface from GF-1 imagery using one-class classifiers
Impervious surface area is a direct consequence of the urbanization, which also plays an important role in urban planning and environmental management. With the rapidly technical development of remote sensing, monitoring urban impervious surface via high spatial resolution (HSR) images has attracted unprecedented att...
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Positive and nodal single-layered solutions to supercritical elliptic problems above the higher critical exponents
We study the problem% \[ -\Delta v+\lambda v=| v| ^{p-2}v\text{ in }\Omega ,\text{\qquad}v=0\text{ on $\partial\Omega$},\text{ }% \] for $\lambda\in\mathbb{R}$ and supercritical exponents $p,$ in domains of the form% \[ \Omega:=\{(y,z)\in\mathbb{R}^{N-m-1}\times\mathbb{R}^{m+1}:(y,| z| )\in\Theta\}, \] where $m\geq1,...
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Robust, Deep and Inductive Anomaly Detection
PCA is a classical statistical technique whose simplicity and maturity has seen it find widespread use as an anomaly detection technique. However, it is limited in this regard by being sensitive to gross perturbations of the input, and by seeking a linear subspace that captures normal behaviour. The first issue has b...
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Understanding Organizational Approach towards End User Privacy
End user privacy is a critical concern for all organizations that collect, process and store user data as a part of their business. Privacy concerned users, regulatory bodies and privacy experts continuously demand organizations provide users with privacy protection. Current research lacks an understanding of organiz...
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Baryonic impact on the dark matter orbital properties of Milky Way-sized haloes
We study the orbital properties of dark matter haloes by combining a spectral method and cosmological simulations of Milky Way-sized galaxies. We compare the dynamics and orbits of individual dark matter particles from both hydrodynamic and $N$-body simulations, and find that the fraction of box, tube and resonant or...
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Extreme Value Analysis Without the Largest Values: What Can Be Done?
In this paper we are concerned with the analysis of heavy-tailed data when a portion of the extreme values is unavailable. This research was motivated by an analysis of the degree distributions in a large social network. The degree distributions of such networks tend to have power law behavior in the tails. We focus ...
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Controlling light in complex media beyond the acoustic diffraction-limit using the acousto-optic transmission matrix
Studying the internal structure of complex samples with light is an important task, but a difficult challenge due to light scattering. While the complex optical distortions induced by multiple scattering can be effectively undone with the knowledge of the medium's scattering-matrix, this matrix is generally unknown, ...
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Uniqueness and stability of Ricci flow through singularities
We verify a conjecture of Perelman, which states that there exists a canonical Ricci flow through singularities starting from an arbitrary compact Riemannian 3-manifold. Our main result is a uniqueness theorem for such flows, which, together with an earlier existence theorem of Lott and the second named author, impli...
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Reciprocal space engineering with hyperuniform gold metasurfaces
Hyperuniform geometries feature correlated disordered topologies which follow from a tailored k-space design. Here we study gold plasmonic hyperuniform metasurfaces and we report evidence of the effectiveness of k-space engineering on both light scattering and light emission experiments. The metasurfaces possess inte...
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STFT spectral loss for training a neural speech waveform model
This paper proposes a new loss using short-time Fourier transform (STFT) spectra for the aim of training a high-performance neural speech waveform model that predicts raw continuous speech waveform samples directly. Not only amplitude spectra but also phase spectra obtained from generated speech waveforms are used to...
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Spectral Properties of Continuum Fibonacci Schrödinger Operators
We study continuum Schrödinger operators on the real line whose potentials are comprised of two compactly supported square-integrable functions concatenated according to an element of the Fibonacci substitution subshift over two letters. We show that the Hausdorff dimension of the spectrum tends to one in the small-c...
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Species tree inference from genomic sequences using the log-det distance
The log-det distance between two aligned DNA sequences was introduced as a tool for statistically consistent inference of a gene tree under simple non-mixture models of sequence evolution. Here we prove that the log-det distance, coupled with a distance-based tree construction method, also permits consistent inferenc...
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Structure preserving schemes for nonlinear Fokker-Planck equations and applications
In this paper we focus on the construction of numerical schemes for nonlinear Fokker-Planck equations that preserve the structural properties, like non negativity of the solution, entropy dissipation and large time behavior. The methods here developed are second order accurate, they do not require any restriction on ...
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A Markov decision process approach to optimizing cancer therapy using multiple modalities
There are several different modalities, e.g., surgery, chemotherapy, and radiotherapy, that are currently used to treat cancer. It is common practice to use a combination of these modalities to maximize clinical outcomes, which are often measured by a balance between maximizing tumor damage and minimizing normal tiss...
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Complex Contagions with Timers
A great deal of effort has gone into trying to model social influence --- including the spread of behavior, norms, and ideas --- on networks. Most models of social influence tend to assume that individuals react to changes in the states of their neighbors without any time delay, but this is often not true in social c...
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Random Networks, Graphical Models, and Exchangeability
We study conditional independence relationships for random networks and their interplay with exchangeability. We show that, for finitely exchangeable network models, the empirical subgraph densities are maximum likelihood estimates of their theoretical counterparts. We then characterize all possible Markov structures...
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Long-Term Inertial Navigation Aided by Dynamics of Flow Field Features
A current-aided inertial navigation framework is proposed for small autonomous underwater vehicles in long-duration operations (> 1 hour), where neither frequent surfacing nor consistent bottom-tracking are available. We instantiate this concept through mid-depth, underwater navigation. This strategy mitigates dead-r...
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Catching Zika Fever: Application of Crowdsourcing and Machine Learning for Tracking Health Misinformation on Twitter
In February 2016, World Health Organization declared the Zika outbreak a Public Health Emergency of International Concern. With developing evidence it can cause birth defects, and the Summer Olympics coming up in the worst affected country, Brazil, the virus caught fire on social media. In this work, use Zika as a ca...
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Monte Carlo determination of the low-energy constants for a two-dimensional spin-1 Heisenberg model with spatial anisotropy
The low-energy constants, namely the spin stiffness $\rho_s$, the staggered magnetization density ${\cal M}_s$ per area, and the spinwave velocity $c$ of the two-dimensional (2D) spin-1 Heisenberg model on the square and rectangular lattices are determined using the first principles Monte Carlo method. In particular,...
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Explaining Parochialism: A Causal Account for Political Polarization in Changing Economic Environments
Political and social polarization are a significant cause of conflict and poor governance in many societies, thus understanding their causes is of considerable importance. Here we demonstrate that shifts in socialization strategy similar to political polarization and/or identity politics could be a constructive respo...
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A Secular Resonant Origin for the Loneliness of Hot Jupiters
Despite decades of inquiry, the origin of giant planets residing within a few tenths of an astronomical unit from their host stars remains unclear. Traditionally, these objects are thought to have formed further out before subsequently migrating inwards. However, the necessity of migration has been recently called in...
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An Incremental Slicing Method for Functional Programs
Several applications of slicing require a program to be sliced with respect to more than one slicing criterion. Program specialization, parallelization and cohesion measurement are examples of such applications. These applications can benefit from an incremental static slicing method in which a significant extent of ...
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Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters
Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of particle collisions to build expectations of what experimental data may look like under different theory modeling assumptions. Petabytes of simulated data are needed to develop analysis techniques, though they are expensive to generate usin...
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A study of ancient Khmer ephemerides
We study ancient Khmer ephemerides described in 1910 by the French engineer Faraut, in order to determine whether they rely on observations carried out in Cambodia. These ephemerides were found to be of Indian origin and have been adapted for another longitude, most likely in Burma. A method for estimating the date a...
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Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure
Model-based compression is an effective, facilitating, and expanded model of neural network models with limited computing and low power. However, conventional models of compression techniques utilize crafted features [2,3,12] and explore specialized areas for exploration and design of large spaces in terms of size, s...
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Infinite Sparse Structured Factor Analysis
Matrix factorisation methods decompose multivariate observations as linear combinations of latent feature vectors. The Indian Buffet Process (IBP) provides a way to model the number of latent features required for a good approximation in terms of regularised reconstruction error. Previous work has focussed on latent ...
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RuntimeSearch: Ctrl+F for a Running Program
Developers often try to find occurrences of a certain term in a software system. Traditionally, a text search is limited to static source code files. In this paper, we introduce a simple approach, RuntimeSearch, where the given term is searched in the values of all string expressions in a running program. When a matc...
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Accurate and Efficient Evaluation of Characteristic Modes
A new method to improve the accuracy and efficiency of characteristic mode (CM) decomposition for perfectly conducting bodies is presented. The method uses the expansion of the Green dyadic in spherical vector waves. This expansion is utilized in the method of moments (MoM) solution of the electric field integral equ...
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MUFASA: The assembly of the red sequence
We examine the growth and evolution of quenched galaxies in the Mufasa cosmological hydrodynamic simulations that include an evolving halo mass-based quenching prescription, with galaxy colours computed accounting for line-of-sight extinction to individual star particles. Mufasa reproduces the observed present-day re...
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Symmetric calorons and the rotation map
We study $SU(2)$ calorons, also known as periodic instantons, and consider invariance under isometries of $S^1\times\mathbb{R}^3$ coupled with a non-spatial isometry called the rotation map. In particular, we investigate the fixed points under various cyclic symmetry groups. Our approach utilises a construction akin ...
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Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks
Natural disasters can have catastrophic impacts on the functionality of infrastructure systems and cause severe physical and socio-economic losses. Given budget constraints, it is crucial to optimize decisions regarding mitigation, preparedness, response, and recovery practices for these systems. This requires accura...
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IMLS-SLAM: scan-to-model matching based on 3D data
The Simultaneous Localization And Mapping (SLAM) problem has been well studied in the robotics community, especially using mono, stereo cameras or depth sensors. 3D depth sensors, such as Velodyne LiDAR, have proved in the last 10 years to be very useful to perceive the environment in autonomous driving, but few meth...
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Cooperative Online Learning: Keeping your Neighbors Updated
We study an asynchronous online learning setting with a network of agents. At each time step, some of the agents are activated, requested to make a prediction, and pay the corresponding loss. The loss function is then revealed to these agents and also to their neighbors in the network. When activations are stochastic...
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FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis
Convolutional neural networks (CNNs) have massively impacted visual recognition in 2D images, and are now ubiquitous in state-of-the-art approaches. CNNs do not easily extend, however, to data that are not represented by regular grids, such as 3D shape meshes or other graph-structured data, to which traditional local...
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On a minimal counterexample to Brauer's $k(B)$-conjecture
We study Brauer's long-standing $k(B)$-conjecture on the number of characters in $p$-blocks for finite quasi-simple groups and show that their blocks do not occur as a minimal counterexample for $p\ge5$ nor in the case of abelian defect. For $p=3$ we obtain that the principal 3-blocks do not provide minimal counterex...
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The best fit for the observed galaxy Counts-in-Cell distribution function
The Sloan Digital Sky Survey (SDSS) is the first dense redshift survey encompassing a volume large enough to find the best analytic probability density function that fits the galaxy Counts-in-Cells distribution $f_V(N)$, the frequency distribution of galaxy counts in a volume $V$. Different analytic functions have be...
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Separator Reconnection at Earth's Dayside Magnetopause: MMS Observations Compared to Global Simulations
We compare a global high resolution resistive magnetohydrodynamics (MHD) simulation of Earth's magnetosphere with observations from the Magnetospheric Multiscale (MMS) constellation for a southward IMF magnetopause crossing during October 16, 2015 that was previously identified as an electron diffusion region (EDR) e...
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Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints
Algorithms for detecting communities in complex networks are generally unsupervised, relying solely on the structure of the network. However, these methods can often fail to uncover meaningful groupings that reflect the underlying communities in the data, particularly when those structures are highly overlapping. One...
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Designing Coalition-Proof Reverse Auctions over Continuous Goods
This paper investigates reverse auctions that involve continuous values of different types of goods, general nonconvex constraints, and second stage costs. We seek to design the payment rules and conditions under which coalitions of participants cannot influence the auction outcome in order to obtain higher collectiv...
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Probabilistic Line Searches for Stochastic Optimization
In deterministic optimization, line searches are a standard tool ensuring stability and efficiency. Where only stochastic gradients are available, no direct equivalent has so far been formulated, because uncertain gradients do not allow for a strict sequence of decisions collapsing the search space. We construct a pr...
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Quantum Phase transition under pressure in a heavily hydrogen-doped iron-based superconductor LaFeAsO
Hydrogen (H)-doped LaFeAsO is a prototypical iron-based superconductor. However, its phase diagram extends beyond the standard framework, where a superconducting (SC) phase follows an antiferromagnetic (AF) phase upon carrier doping; instead, the SC phase is sandwiched between two AF phases appearing in lightly and h...
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Hyperboloidal similarity coordinates and a globally stable blowup profile for supercritical wave maps
We consider co-rotational wave maps from (1+3)-dimensional Minkowski space into the three-sphere. This model exhibits an explicit blowup solution and we prove the asymptotic nonlinear stability of this solution in the whole space under small perturbations of the initial data. The key ingredient is the introduction of...
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Supersymmetry in Closed Chains of Coupled Majorana Modes
We consider a closed chain of even number of Majorana zero modes with nearest-neighbour couplings which are different site by site generically, thus no any crystal symmetry. Instead, we demonstrate the possibility of an emergent supersymmetry (SUSY), which is accompanied by gapless Fermionic excitations. In particula...
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Renormalized Hennings Invariants and 2+1-TQFTs
We construct non-semisimple $2+1$-TQFTs yielding mapping class group representations in Lyubashenko's spaces. In order to do this, we first generalize Beliakova, Blanchet and Geer's logarithmic Hennings invariants based on quantum $\mathfrak{sl}_2$ to the setting of finite-dimensional non-degenerate unimodular ribbon...
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On Improving Deep Reinforcement Learning for POMDPs
Deep Reinforcement Learning (RL) recently emerged as one of the most competitive approaches for learning in sequential decision making problems with fully observable environments, e.g., computer Go. However, very little work has been done in deep RL to handle partially observable environments. We propose a new archit...
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When to Invest in Security? Empirical Evidence and a Game-Theoretic Approach for Time-Based Security
Games of timing aim to determine the optimal defense against a strategic attacker who has the technical capability to breach a system in a stealthy fashion. Key questions arising are when the attack takes place, and when a defensive move should be initiated to reset the system resource to a known safe state. In our w...
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Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models
Humans are not only adept in recognizing what class an input instance belongs to (i.e., classification task), but perhaps more remarkably, they can imagine (i.e., generate) plausible instances of a desired class with ease, when prompted. Inspired by this, we propose a framework which allows transforming Cascade-Corre...
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Semiclassical "Divide-and-Conquer" Method for Spectroscopic Calculations of High Dimensional Molecular Systems
A new semiclassical "divide-and-conquer" method is presented with the aim of demonstrating that quantum dynamics simulations of high dimensional molecular systems are doable. The method is first tested by calculating the quantum vibrational power spectra of water, methane, and benzene - three molecules of increasing ...
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