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The Brown-Peterson spectrum is not $E_{2(p^2+2)}$ at odd primes
Recently, Lawson has shown that the 2-primary Brown-Peterson spectrum does not admit the structure of an $E_{12}$ ring spectrum, thus answering a question of May in the negative. We extend Lawson's result to odd primes by proving that the p-primary Brown-Peterson spectrum does not admit the structure of an $E_{2(p^2+...
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Beliefs in Markov Trees - From Local Computations to Local Valuation
This paper is devoted to expressiveness of hypergraphs for which uncertainty propagation by local computations via Shenoy/Shafer method applies. It is demonstrated that for this propagation method for a given joint belief distribution no valuation of hyperedges of a hypergraph may provide with simpler hypergraph stru...
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A model for random fire induced tree-grass coexistence in savannas
Tree-grass coexistence in savanna ecosystems depends strongly on environmental disturbances out of which crucial is fire. Most modeling attempts in the literature lack stochastic approach to fire occurrences which is essential to reflect their unpredictability. Existing models that actually include stochasticity of f...
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A depth-based method for functional time series forecasting
An approach is presented for making predictions about functional time series. The method is applied to data coming from periodically correlated processes and electricity demand, obtaining accurate point forecasts and narrow prediction bands that cover high proportions of the forecasted functional datum, for a given c...
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Dihedral Molecular Configurations Interacting by Lennard-Jones and Coulomb Forces
In this paper, we investigate periodic vibrations of a group of particles with a dihedral configuration in the plane governed by the Lennard-Jones and Coulomb forces. Using the gradient equivariant degree, we provide a full topological classification of the periodic solutions with both temporal and spatial symmetries...
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Understanding news story chains using information retrieval and network clustering techniques
Content analysis of news stories (whether manual or automatic) is a cornerstone of the communication studies field. However, much research is conducted at the level of individual news articles, despite the fact that news events (especially significant ones) are frequently presented as "stories" by news outlets: chain...
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Fair Kernel Learning
New social and economic activities massively exploit big data and machine learning algorithms to do inference on people's lives. Applications include automatic curricula evaluation, wage determination, and risk assessment for credits and loans. Recently, many governments and institutions have raised concerns about th...
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Underwater Surveying via Bearing only Cooperative Localization
Bearing only cooperative localization has been used successfully on aerial and ground vehicles. In this paper we present an extension of the approach to the underwater domain. The focus is on adapting the technique to handle the challenging visibility conditions underwater. Furthermore, data from inertial, magnetic, ...
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Sterile Neutrinos and B-L Symmetry
We revisit the relation between the neutrino masses and the spontaneous breaking of the B-L gauge symmetry. We discuss the main scenarios for Dirac and Majorana neutrinos and point out two simple mechanisms for neutrino masses. In this context the neutrino masses can be generated either at tree level or at quantum le...
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Effects of parametric uncertainties in cascaded open quantum harmonic oscillators and robust generation of Gaussian invariant states
This paper is concerned with the generation of Gaussian invariant states in cascades of open quantum harmonic oscillators governed by linear quantum stochastic differential equations. We carry out infinitesimal perturbation analysis of the covariance matrix for the invariant Gaussian state of such a system and the re...
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A computer-based recursion algorithm for automatic charge of power device of electric vehicles carrying electromagnet
This paper proposes a computer-based recursion algorithm for automatic charge of power device of electric vehicles carrying electromagnet. The charging system includes charging cable with one end connecting gang socket, electromagnetic gear driving the connecting socket and a charging pile breaking or closing, and de...
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Abelian Tensor Models on the Lattice
We consider a chain of Abelian Klebanov-Tarnopolsky fermionic tensor models coupled through quartic nearest-neighbor interactions. We characterize the gauge-singlet spectrum for small chains ($L=2,3,4,5$) and observe that the spectral statistics exhibits strong evidences in favor of quasi-many body localization.
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Distance-based Confidence Score for Neural Network Classifiers
The reliable measurement of confidence in classifiers' predictions is very important for many applications and is, therefore, an important part of classifier design. Yet, although deep learning has received tremendous attention in recent years, not much progress has been made in quantifying the prediction confidence ...
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Benford analysis of quantum critical phenomena: First digit provides high finite-size scaling exponent while first two and further are not much better
Benford's law is an empirical edict stating that the lower digits appear more often than higher ones as the first few significant digits in statistics of natural phenomena and mathematical tables. A marked proportion of such analyses is restricted to the first significant digit. We employ violation of Benford's law, ...
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A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
Two popular classes of methods for approximate inference are Markov chain Monte Carlo (MCMC) and variational inference. MCMC tends to be accurate if run for a long enough time, while variational inference tends to give better approximations at shorter time horizons. However, the amount of time needed for MCMC to exce...
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Making Sense of Bell's Theorem and Quantum Nonlocality
Bell's theorem has fascinated physicists and philosophers since his 1964 paper, which was written in response to the 1935 paper of Einstein, Podolsky, and Rosen. Bell's theorem and its many extensions have led to the claim that quantum mechanics and by inference nature herself are nonlocal in the sense that a measure...
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On Some properties of dyadic operators
In this paper, the objects of our investigation are some dyadic operators, including dyadic shifts, multilinear paraproducts and multilinear Haar multipliers. We mainly focus on the continuity and compactness of these operators. First, we consider the continuity properties of these operators. Then, by the Fréchet-Kol...
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Rationalizability and Epistemic Priority Orderings
At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own theories, through strategic reasoning. I develop and characterize epistemicall...
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Communications for Wearable Devices
Wearable devices are transforming computing and the human-computer interaction and they are a primary means for motion recognition of reflexive systems. We review basic wearable deployments and their open wireless communications. An algorithm that uses accelerometer data to provide a control and communication signal ...
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Nonlocal Nonlinear Schrödinger Equations and Their Soliton Solutions
We study standard and nonlocal nonlinear Schrödinger (NLS) equations obtained from the coupled NLS system of equations (Ablowitz-Kaup-Newell-Segur (AKNS) equations) by using standard and nonlocal reductions respectively. By using the Hirota bilinear method we first find soliton solutions of the coupled NLS system of ...
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Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning
Prediction is an appealing objective for self-supervised learning of behavioral skills, particularly for autonomous robots. However, effectively utilizing predictive models for control, especially with raw image inputs, poses a number of major challenges. How should the predictions be used? What happens when they are...
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S-Isomap++: Multi Manifold Learning from Streaming Data
Manifold learning based methods have been widely used for non-linear dimensionality reduction (NLDR). However, in many practical settings, the need to process streaming data is a challenge for such methods, owing to the high computational complexity involved. Moreover, most methods operate under the assumption that t...
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Extreme radio-wave scattering associated with hot stars
We use data on extreme radio scintillation to demonstrate that this phenomenon is associated with hot stars in the solar neighbourhood. The ionized gas responsible for the scattering is found at distances up to 1.75pc from the host star, and on average must comprise 1.E5 distinct structures per star. We detect azimut...
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Tracking network dynamics: a survey of distances and similarity metrics
From longitudinal biomedical studies to social networks, graphs have emerged as a powerful framework for describing evolving interactions between agents in complex systems. In such studies, after pre-processing, the data can be represented by a set of graphs, each representing a system's state at different points in ...
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Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces
Both neural networks and decision trees are popular machine learning methods and are widely used to solve problems from diverse domains. These two classifiers are commonly used base classifiers in an ensemble framework. In this paper, we first present a new variant of oblique decision tree based on a linear classifie...
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Graded components of local cohomology modules
Let $A$ be a regular ring containing a field of characteristic zero and let $R = A[X_1,\ldots, X_m]$. Consider $R$ as standard graded with $deg \ A = 0$ and $deg \ X_i = 1$ for all $i$. In this paper we present a comprehensive study of graded components of local cohomology modules $H^i_I(R)$ where $I$ is an \emph{arb...
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Drug Selection via Joint Push and Learning to Rank
Selecting the right drugs for the right patients is a primary goal of precision medicine. In this manuscript, we consider the problem of cancer drug selection in a learning-to-rank framework. We have formulated the cancer drug selection problem as to accurately predicting 1). the ranking positions of sensitive drugs ...
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Two-dimensional electron gas at the interface of the ferroelectric-antiferromagnetic heterostructure Ba_0.8Sr_0.2TiO_3/LaMnO_3
The temperature dependence of the electrical resistivity of the heterostructures consisting of single crystalline LaMnO$_3$ samples with different crystallographic orientations covered by the epitaxial ferroelectric Ba$_{0.8}$Sr$_{0.2}$TiO$_3$ film has been studied. Results obtained for the heterostructure have been ...
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Linear Discriminant Generative Adversarial Networks
We develop a novel method for training of GANs for unsupervised and class conditional generation of images, called Linear Discriminant GAN (LD-GAN). The discriminator of an LD-GAN is trained to maximize the linear separability between distributions of hidden representations of generated and targeted samples, while th...
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Machine learning for classification and quantification of monoclonal antibody preparations for cancer therapy
Monoclonal antibodies constitute one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. In order to guarantee the quality of those preparations prepared at hospital, quality control has to be developed. The aim of this study was to explore a ...
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Sequential noise-induced escapes for oscillatory network dynamics
It is well known that the addition of noise in a multistable system can induce random transitions between stable states. The rate of transition can be characterised in terms of the noise-free system's dynamics and the added noise: for potential systems in the presence of asymptotically low noise the well-known Kramer...
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Confluence of Conditional Term Rewrite Systems via Transformations
Conditional term rewriting is an intuitive yet complex extension of term rewriting. In order to benefit from the simpler framework of unconditional rewriting, transformations have been defined to eliminate the conditions of conditional term rewrite systems. Recent results provide confluence criteria for conditional t...
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Observation of Skyrmions at Room Temperature in Co2FeAl Heusler Alloy Ultrathin Films
Magnetic skyrmions are topological spin structures having immense potential for energy efficient spintronic devices. However, observations of skyrmions at room temperature are limited to patterned nanostructures. Here, we report the observation of stable skyrmions in unpatterned Ta/Co2FeAl(CFA)/MgO thin film heterost...
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Bayesian Nonparametric Spectral Estimation
Spectral estimation (SE) aims to identify how the energy of a signal (e.g., a time series) is distributed across different frequencies. This can become particularly challenging when only partial and noisy observations of the signal are available, where current methods fail to handle uncertainty appropriately. In this...
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Imprecise dynamic walking with time-projection control
We present a new walking foot-placement controller based on 3LP, a 3D model of bipedal walking that is composed of three pendulums to simulate falling, swing and torso dynamics. Taking advantage of linear equations and closed-form solutions of the 3LP model, our proposed controller projects intermediate states of the...
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Interplay of dilution and magnetic field in the nearest-neighbor spin-ice model on the pyrochlore lattice
We study the magnetic field effects on the diluted spin-ice materials using the replica-exchange Monte Carlo simulation. We observe five plateaus in the magnetization curve of the diluted nearest-neighbor spin-ice model on the pyrochlore lattice when a magnetic field is applied in the [111] direction. This is in cont...
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RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Process
An RNN-based forecasting approach is used to early detect anomalies in industrial multivariate time series data from a simulated Tennessee Eastman Process (TEP) with many cyber-attacks. This work continues a previously proposed LSTM-based approach to the fault detection in simpler data. It is considered necessary to ...
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Modelling of limitations of bulk heterojunction architecture in organic solar cells
Polymer solar cells are considered as very promising candidates for development of photovoltaics of the future. They are cheap and easy to fabricate, however, up to now, they possess fundamental drawback, low effectiveness. In the most popular BHJ (bulk heterojunction) architecture the actual record of efficiency is ...
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Detecting singular weak-dissipation limit for flutter onset in reversible systems
A `flutter machine' is introduced for the investigation of a singular interface between the classical and reversible Hopf bifurcations that is theoretically predicted to be generic in nonconservative reversible systems with vanishing dissipation. In particular, such a singular interface exists for the Pflüger viscoel...
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A Hand Combining Two Simple Grippers to Pick up and Arrange Objects for Assembly
This paper proposes a novel robotic hand design for assembly tasks. The idea is to combine two simple grippers -- an inner gripper which is used for precise alignment, and an outer gripper which is used for stable holding. Conventional robotic hands require complicated compliant mechanisms or complicated control stra...
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A Time Hierarchy Theorem for the LOCAL Model
The celebrated Time Hierarchy Theorem for Turing machines states, informally, that more problems can be solved given more time. The extent to which a time hierarchy-type theorem holds in the distributed LOCAL model has been open for many years. It is consistent with previous results that all natural problems in the L...
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Second sound in systems of one-dimensional fermions
We study sound in Galilean invariant systems of one-dimensional fermions. At low temperatures, we find a broad range of frequencies in which in addition to the waves of density there is a second sound corresponding to ballistic propagation of heat in the system. The damping of the second sound mode is weak, provided ...
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The equational theory of the natural join and inner union is decidable
The natural join and the inner union operations combine relations of a database. Tropashko and Spight [24] realized that these two operations are the meet and join operations in a class of lattices, known by now as the relational lattices. They proposed then lattice theory as an algebraic approach to the theory of da...
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Doping-induced spin-orbit splitting in Bi-doped ZnO nanowires
Our predictions, based on density-functional calculations, reveal that surface doping of ZnO nanowires with Bi leads to a linear-in-$k$ splitting of the conduction-band states, through spin-orbit interaction, due to the lowering of the symmetry in the presence of the dopant. This finding implies that spin polarizatio...
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A robotic vision system to measure tree traits
The autonomous measurement of tree traits, such as branching structure, branch diameters, branch lengths, and branch angles, is required for tasks such as robotic pruning of trees as well as structural phenotyping. We propose a robotic vision system called the Robotic System for Tree Shape Estimation (RoTSE) to deter...
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Resolution enhancement in in-line holography by numerical compensation of vibrations
Mechanical vibrations of components of the optical system is one of the sources of blurring of interference pattern in coherent imaging systems. The problem is especially important in holography where the resolution of the reconstructed objects depends on the effective size of the hologram, that is on the extent of t...
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Embodied Question Answering
We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the car?"). In order to answer, the agent must first intelligently navigate to explore the environment, gather information through first-perso...
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Toward Unsupervised Text Content Manipulation
Controlled generation of text is of high practical use. Recent efforts have made impressive progress in generating or editing sentences with given textual attributes (e.g., sentiment). This work studies a new practical setting of text content manipulation. Given a structured record, such as `(PLAYER: Lebron, POINTS: ...
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Unsupervised learning of object landmarks by factorized spatial embeddings
Learning automatically the structure of object categories remains an important open problem in computer vision. In this paper, we propose a novel unsupervised approach that can discover and learn landmarks in object categories, thus characterizing their structure. Our approach is based on factorizing image deformatio...
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Data-Efficient Design Exploration through Surrogate-Assisted Illumination
Design optimization techniques are often used at the beginning of the design process to explore the space of possible designs. In these domains illumination algorithms, such as MAP-Elites, are promising alternatives to classic optimization algorithms because they produce diverse, high-quality solutions in a single ru...
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Stochastic seismic waveform inversion using generative adversarial networks as a geological prior
We present an application of deep generative models in the context of partial-differential equation (PDE) constrained inverse problems. We combine a generative adversarial network (GAN) representing an a priori model that creates subsurface geological structures and their petrophysical properties, with the numerical ...
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A Capillary Surface with No Radial Limits
In 1996, Kirk Lancaster and David Siegel investigated the existence and behavior of radial limits at a corner of the boundary of the domain of solutions of capillary and other prescribed mean curvature problems with contact angle boundary data. In Theorem 3, they provide an example of a capillary surface in a unit di...
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Brain Computer Interface for Gesture Control of a Social Robot: an Offline Study
Brain computer interface (BCI) provides promising applications in neuroprosthesis and neurorehabilitation by controlling computers and robotic devices based on the patient's intentions. Here, we have developed a novel BCI platform that controls a personalized social robot using noninvasively acquired brain signals. S...
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Multi-agent Gaussian Process Motion Planning via Probabilistic Inference
This paper deals with motion planning for multiple agents by representing the problem as a simultaneous optimization of every agent's trajectory. Each trajectory is considered as a sample from a one-dimensional continuous-time Gaussian process (GP) generated by a linear time-varying stochastic differential equation d...
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Faster Algorithms for Mean-Payoff Parity Games
Graph games provide the foundation for modeling and synthesis of reactive processes. Such games are played over graphs where the vertices are controlled by two adversarial players. We consider graph games where the objective of the first player is the conjunction of a qualitative objective (specified as a parity cond...
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Similarity Function Tracking using Pairwise Comparisons
Recent work in distance metric learning has focused on learning transformations of data that best align with specified pairwise similarity and dissimilarity constraints, often supplied by a human observer. The learned transformations lead to improved retrieval, classification, and clustering algorithms due to the bet...
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Deep Boosted Regression for MR to CT Synthesis
Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction is particularly challenging for PET-MRI as neither PET nor magnetic resonance imaging (MRI) can directly image tissue attenuation properti...
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Discretisation of regularity structures
We introduce a general framework allowing to apply the theory of regularity structures to discretisations of stochastic PDEs. The approach pursued in this article is that we do not focus on any one specific discretisation procedure. Instead, we assume that we are given a scale $\varepsilon > 0$ and a "black box" desc...
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Optimization of Wireless Power Transfer Systems Enhanced by Passive Elements and Metasurfaces
This paper presents a rigorous optimization technique for wireless power transfer (WPT) systems enhanced by passive elements, ranging from simple reflectors and intermedi- ate relays all the way to general electromagnetic guiding and focusing structures, such as metasurfaces and metamaterials. At its core is a convex...
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Sharpening Jensen's Inequality
This paper proposes a new sharpened version of the Jensen's inequality. The proposed new bound is simple and insightful, is broadly applicable by imposing minimum assumptions, and provides fairly accurate result in spite of its simple form. Applications to the moment generating function, power mean inequalities, and ...
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Knotted solutions, from electromagnetism to fluid dynamics
Knotted solutions to electromagnetism and fluid dynamics are investigated, based on relations we find between the two subjects. We can write fluid dynamics in electromagnetism language, but only on an initial surface, or for linear perturbations, and we use this map to find knotted fluid solutions, as well as new ele...
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On the intersection graph of ideals of $\mathbb{Z}_m$
Let $m>1$ be an integer, and let $I(\mathbb{Z}_m)^*$ be the set of all non-zero proper ideals of $\mathbb{Z}_m$. The intersection graph of ideals of $\mathbb{Z}_m$, denoted by $G(\mathbb{Z}_m)$, is a graph with vertices $I(\mathbb{Z}_m)^*$ and two distinct vertices $I,J\in I(\mathbb{Z}_m)^*$ are adjacent if and only ...
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Optimization of Executable Formal Interpreters developed in Higher-order Theorem Proving Systems
In recent publications, we presented a novel formal symbolic process virtual machine (FSPVM) framework that combined higher-order theorem proving and symbolic execution for verifying the reliability and security of smart contracts developed in the Ethereum blockchain system without suffering the standard issues surro...
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Healthcare Robotics
Robots have the potential to be a game changer in healthcare: improving health and well-being, filling care gaps, supporting care givers, and aiding health care workers. However, before robots are able to be widely deployed, it is crucial that both the research and industrial communities work together to establish a ...
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Personalized Thread Recommendation for MOOC Discussion Forums
Social learning, i.e., students learning from each other through social interactions, has the potential to significantly scale up instruction in online education. In many cases, such as in massive open online courses (MOOCs), social learning is facilitated through discussion forums hosted by course providers. In this...
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CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model
Background: Widespread adoption of electronic health records (EHRs) has enabled secondary use of EHR data for clinical research and healthcare delivery. Natural language processing (NLP) techniques have shown promise in their capability to extract the embedded information in unstructured clinical data, and informatio...
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The same strain of Piscine orthoreovirus (PRV-1) is involved with the development of different, but related, diseases in Atlantic and Pacific Salmon in British Columbia
Piscine orthoreovirus Strain PRV-1 is the causative agent of heart and skeletal muscle inflammation (HSMI) in Atlantic salmon (Salmo salar). Given its high prevalence in net pen salmon, debate has arisen on whether PRV poses a risk to migratory salmon, especially in British Columbia (BC) where commercially important ...
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Charge transfer and metallicity in LaNiO$_3$/LaMnO$_3$ superlattices
Motivated by recent experiments, we use the $+U$ extension of the generalized gradient approximation to density functional theory to study superlattices composed of alternating layers of LaNiO$_3$ and LaMnO$_3$. For comparison we also study a rocksalt ((111) double perovskite) structure and bulk LaNiO$_3$ and LaMnO$_...
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On Learning the $cμ$ Rule in Single and Parallel Server Networks
We consider learning-based variants of the $c \mu$ rule for scheduling in single and parallel server settings of multi-class queueing systems. In the single server setting, the $c \mu$ rule is known to minimize the expected holding-cost (weighted queue-lengths summed over classes and a fixed time horizon). We focus o...
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Report: Performance comparison between C2075 and P100 GPU cards using cosmological correlation functions
In this report, some cosmological correlation functions are used to evaluate the differential performance between C2075 and P100 GPU cards. In the past, the correlation functions used in this work have been widely studied and exploited on some previous GPU architectures. The analysis of the performance indicates that...
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Crafting Adversarial Examples For Speech Paralinguistics Applications
Computational paralinguistic analysis is increasingly being used in a wide range of cyber applications, including security-sensitive applications such as speaker verification, deceptive speech detection, and medical diagnostics. While state-of-the-art machine learning techniques, such as deep neural networks, can pro...
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On the Analysis of Bacterial Cooperation with a Characterization of 2D Signal Propagation
The exchange of small molecular signals within microbial populations is generally referred to as quorum sensing (QS). QS is ubiquitous in nature and enables microorganisms to respond to fluctuations of living environments by working together. In this work, a QS-based communication system within a microbial population...
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The Ebb and Flow of Controversial Debates on Social Media
We explore how the polarization around controversial topics evolves on Twitter - over a long period of time (2011 to 2016), and also as a response to major external events that lead to increased related activity. We find that increased activity is typically associated with increased polarization; however, we find no ...
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Training of Deep Neural Networks based on Distance Measures using RMSProp
The vanishing gradient problem was a major obstacle for the success of deep learning. In recent years it was gradually alleviated through multiple different techniques. However the problem was not really overcome in a fundamental way, since it is inherent to neural networks with activation functions based on dot prod...
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Generalized Concomitant Multi-Task Lasso for sparse multimodal regression
In high dimension, it is customary to consider Lasso-type estimators to enforce sparsity. For standard Lasso theory to hold, the regularization parameter should be proportional to the noise level, yet the latter is generally unknown in practice. A possible remedy is to consider estimators, such as the Concomitant/Sca...
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A deep learning-based method for prostate segmentation in T2-weighted magnetic resonance imaging
We propose a novel automatic method for accurate segmentation of the prostate in T2-weighted magnetic resonance imaging (MRI). Our method is based on convolutional neural networks (CNNs). Because of the large variability in the shape, size, and appearance of the prostate and the scarcity of annotated training data, w...
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A note on signature of Lefschetz fibrations with planar fiber
Using theorems of Eliashberg and McDuff, Etnyre [Et] proved that the intersection form of a symplectic filling of a contact 3-manifold supported by planar open book is negative definite. In this paper, we prove a signature formula for allowable Lefschetz fibrations over $D^2$ with planar fiber by computing Maslov ind...
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Wild Bootstrapping Rank-Based Procedures: Multiple Testing in Nonparametric Split-Plot Designs
Split-plot or repeated measures designs are frequently used for planning experiments in the life or social sciences. Typical examples include the comparison of different treatments over time, where both factors may possess an additional factorial structure. For such designs, the statistical analysis usually consists ...
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Graphical Sequent Calculi for Modal Logics
The syntax of modal graphs is defined in terms of the continuous cut and broken cut following Charles Peirce's notation in the gamma part of his graphical logic of existential graphs. Graphical calculi for normal modal logics are developed based on a reformulation of the graphical calculus for classical propositional...
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Engineering a flux-dependent mobility edge in disordered zigzag chains
There has been great interest in realizing quantum simulators of charged particles in artificial gauge fields. Here, we perform the first quantum simulation explorations of the combination of artificial gauge fields and disorder. Using synthetic lattice techniques based on parametrically-coupled atomic momentum state...
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On the tensor semigroup of affine kac-moody lie algebras
In this paper, we are interested in the decomposition of the tensor product of two representations of a symmetrizable Kac-Moody Lie algebra $\mathfrak g$. Let $P\_+$ be the set of dominant integral weights. For $\lambda\in P\_+$ , $L(\lambda)$ denotes the irreducible, integrable, highest weight representation of g wi...
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Electronic and Thermodynamic Properties of the Amino- and Carboxamido-Functionalized C-60-Based Fullerenes: Towards Non-Volatile Carbon Dioxide Scavengers
Development of new greenhouse gas scavengers is actively pursued nowadays. Volatility caused solvent consumption and significant regeneration costs associated with the aqueous amine solutions motivate search for more technologically and economically advanced solutions. We hereby used hybrid density functional theory ...
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Monaural Singing Voice Separation with Skip-Filtering Connections and Recurrent Inference of Time-Frequency Mask
Singing voice separation based on deep learning relies on the usage of time-frequency masking. In many cases the masking process is not a learnable function or is not encapsulated into the deep learning optimization. Consequently, most of the existing methods rely on a post processing step using the generalized Wiene...
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Confidence Bands for Coefficients in High Dimensional Linear Models with Error-in-variables
We study high-dimensional linear models with error-in-variables. Such models are motivated by various applications in econometrics, finance and genetics. These models are challenging because of the need to account for measurement errors to avoid non-vanishing biases in addition to handle the high dimensionality of th...
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On the Power of Truncated SVD for General High-rank Matrix Estimation Problems
We show that given an estimate $\widehat{A}$ that is close to a general high-rank positive semi-definite (PSD) matrix $A$ in spectral norm (i.e., $\|\widehat{A}-A\|_2 \leq \delta$), the simple truncated SVD of $\widehat{A}$ produces a multiplicative approximation of $A$ in Frobenius norm. This observation leads to ma...
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Don't Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition
When a human drives a car along a road for the first time, they later recognize where they are on the return journey typically without needing to look in their rear-view mirror or turn around to look back, despite significant viewpoint and appearance change. Such navigation capabilities are typically attributed to ou...
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Ultra-broadband On-chip Twisted Light Emitter
On-chip twisted light emitters are essential components for orbital angular momentum (OAM) communication devices, which could address the growing demand for high-capacity communication systems by providing an additional degree of freedom for wavelength/frequency division multiplexing (WDM/FDM). Although whispering ga...
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Linear Additive Markov Processes
We introduce LAMP: the Linear Additive Markov Process. Transitions in LAMP may be influenced by states visited in the distant history of the process, but unlike higher-order Markov processes, LAMP retains an efficient parametrization. LAMP also allows the specific dependence on history to be learned efficiently from ...
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Radial and circular synchronization clusters in extended starlike network of van der Pol oscillators
We consider extended starlike networks where the hub node is coupled with several chains of nodes representing star rays. Assuming that nodes of the network are occupied by nonidentical self-oscillators we study various forms of their cluster synchronization. Radial cluster emerges when the nodes are synchronized alo...
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On the Fourth Power Moment of Fourier Coefficients of Cusp Form
Let $a(n)$ be the Fourier coefficients of a holomorphic cusp form of weight $\kappa=2n\geqslant12$ for the full modular group and $A(x)=\sum\limits_{n\leqslant x}a(n)$. In this paper, we establish an asymptotic formula of the fourth power moment of $A(x)$ and prove that \begin{equation*} \int_1^TA^4(x)\mathrm{d}x=\fr...
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Provable benefits of representation learning
There is general consensus that learning representations is useful for a variety of reasons, e.g. efficient use of labeled data (semi-supervised learning), transfer learning and understanding hidden structure of data. Popular techniques for representation learning include clustering, manifold learning, kernel-learnin...
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TherML: Thermodynamics of Machine Learning
In this work we offer a framework for reasoning about a wide class of existing objectives in machine learning. We develop a formal correspondence between this work and thermodynamics and discuss its implications.
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Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach
With the advent of Big Data, nowadays in many applications databases containing large quantities of similar time series are available. Forecasting time series in these domains with traditional univariate forecasting procedures leaves great potentials for producing accurate forecasts untapped. Recurrent neural network...
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Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
We introduce a new virtual environment for simulating a card game known as "Big 2". This is a four-player game of imperfect information with a relatively complicated action space (being allowed to play 1,2,3,4 or 5 card combinations from an initial starting hand of 13 cards). As such it poses a challenge for many cur...
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Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
We present Fashion-MNIST, a new dataset comprising of 28x28 grayscale images of 70,000 fashion products from 10 categories, with 7,000 images per category. The training set has 60,000 images and the test set has 10,000 images. Fashion-MNIST is intended to serve as a direct drop-in replacement for the original MNIST d...
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Experimental Evaluation of Book Drawing Algorithms
A $k$-page book drawing of a graph $G=(V,E)$ consists of a linear ordering of its vertices along a spine and an assignment of each edge to one of the $k$ pages, which are half-planes bounded by the spine. In a book drawing, two edges cross if and only if they are assigned to the same page and their vertices alternate...
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Probing magnetism in the vortex phase of PuCoGa$_5$ by X-ray magnetic circular dichroism
We have measured X-ray magnetic circular dichroism (XMCD) spectra at the Pu $M_{4,5}$ absorption edges from a newly-prepared high-quality single crystal of the heavy fermion superconductor $^{242}$PuCoGa$_{5}$, exhibiting a critical temperature $T_{c} = 18.7~{\rm K}$. The experiment probes the vortex phase below $T_{...
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Joint secrecy over the K-Transmitter Multiple Access Channel
This paper studies the problem of secure communication over a K-transmitter multiple access channel in the presence of an external eavesdropper, subject to a joint secrecy constraint (i.e., information leakage rate from the collection of K messages to an eavesdropper is made vanishing). As a result, we establish the ...
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Nonlinear Flexoelectricity in Non-centrosymmetric Crystals
We analytically derive the elastic, dielectric, piezoelectric, and the flexoelectric phenomenological coefficients as functions of microscopic model parameters such as ionic positions and spring constants in the two-dimensional square-lattice model with rock-salt-type ionic arrangement. Monte-Carlo simulation reveals...
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Well-posedness of nonlinear transport equation by stochastic perturbation
We are concerned with multidimensional nonlinear stochastic transport equation driven by Brownian motions. For irregular fluxes, by using stochastic BGK approximations and commutator estimates, we gain the existence and uniqueness of stochastic entropy solutions. Besides, for $BV$ initial data, the $BV$ and Hölder re...
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