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Plasma-based wakefield accelerators as sources of axion-like particles
We estimate the average flux density of minimally-coupled axion-like particles generated by a laser-driven plasma wakefield propagating along a constant strong magnetic field. Our calculations suggest that a terrestrial source based on this approach could generate a pulse of axion-like particles whose flux density is...
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The Large D Limit of Planar Diagrams
We show that in $\text{O}(D)$ invariant matrix theories containing a large number $D$ of complex or Hermitian matrices, one can define a $D\rightarrow\infty$ limit for which the sum over planar diagrams truncates to a tractable, yet non-trivial, sum over melon diagrams. In particular, results obtained recently in SYK...
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Trajectory Tracking Control of a Flexible Spine Robot, With and Without a Reference Input
The Underactuated Lightweight Tensegrity Robotic Assistive Spine (ULTRA Spine) project is an ongoing effort to develop a flexible, actuated backbone for quadruped robots. In this work, model-predictive control is used to track a trajectory in the robot's state space, in simulation. The state trajectory used here corr...
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Noncoherent Analog Network Coding using LDPC-coded FSK
Analog network coding (ANC) is a throughput increasing technique for the two-way relay channel (TWRC) whereby two end nodes transmit simultaneously to a relay at the same time and band, followed by the relay broadcasting the received sum of signals to the end nodes. Coherent reception under ANC is challenging due to ...
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Feature selection in weakly coherent matrices
A problem of paramount importance in both pure (Restricted Invertibility problem) and applied mathematics (Feature extraction) is the one of selecting a submatrix of a given matrix, such that this submatrix has its smallest singular value above a specified level. Such problems can be addressed using perturbation anal...
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Learning to Detect and Mitigate Cross-layer Attacks in Wireless Networks: Framework and Applications
Security threats such as jamming and route manipulation can have significant consequences on the performance of modern wireless networks. To increase the efficacy and stealthiness of such threats, a number of extremely challenging, cross-layer attacks have been recently unveiled. Although existing research has thorou...
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MHD Turbulence in spin-down flows of liquid metals
Intense spin-down flows allow one to reach high Rm in relatively small laboratory setups using moderate mass of liquid metals. The spin-down flow in toroidal channels was the first flow configuration used for studying dynamo effects in non-stationary flows. In this paper, we estimate the effect of small-scale dynamo ...
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Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks
The multi-agent path-finding (MAPF) problem has recently received a lot of attention. However, it does not capture important characteristics of many real-world domains, such as automated warehouses, where agents are constantly engaged with new tasks. In this paper, we therefore study a lifelong version of the MAPF pr...
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Examples of finite dimensional algebras which do not satisfy the derived Jordan--Hölder property
We construct a matrix algebra $\Lambda(A,B)$ from two given finite dimensional elementary algebras $A$ and $B$ and give some sufficient conditions on $A$ and $B$ under which the derived Jordan--Hölder property (DJHP) fails for $\Lambda(A,B)$. This provides finite dimensional algebras of finite global dimension which ...
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Learning retrosynthetic planning through self-play
The problem of retrosynthetic planning can be framed as one player game, in which the chemist (or a computer program) works backwards from a molecular target to simpler starting materials though a series of choices regarding which reactions to perform. This game is challenging as the combinatorial space of possible c...
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Real-space analysis of scanning tunneling microscopy topography datasets using sparse modeling approach
A sparse modeling approach is proposed for analyzing scanning tunneling microscopy topography data, which contains numerous peaks corresponding to surface atoms. The method, based on the relevance vector machine with $\mathrm{L}_1$ regularization and $k$-means clustering, enables separation of the peaks and atomic ce...
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Scattered light intensity measurements of plasma treated Polydimethylsiloxane films: A measure to detect surface modification
Polydimethylsiloxane (PDMS) films possess different chemical and physical properties based on surface modification. The bond structure of pristine PDMS films and plasma treated PDMS films differ in a particular region of silicate bonds. We have studied the surface physical properties of pristine PDMS films and plasma...
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A hierarchical Bayesian model for predicting ecological interactions using evolutionary relationships
Identifying undocumented or potential future interactions among species is a challenge facing modern ecologists. Recent link prediction methods rely on trait data, however large species interaction databases are typically sparse and covariates are limited to only a fraction of species. On the other hand, evolutionary...
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Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images
Pathological lung segmentation (PLS) is an important, yet challenging, medical image application due to the wide variability of pathological lung appearance and shape. Because PLS is often a pre-requisite for other imaging analytics, methodological simplicity and generality are key factors in usability. Along those l...
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On the Helium fingers in the intracluster medium
In this paper we investigate the convection phenomenon in the intracluster medium (the weakly-collisional magnetized inhomogeneous plasma permeating galaxy clusters) where the concentration gradient of the Helium ions is not ignorable. To this end, we build upon the general machinery employed to study the salt finger...
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Absolute frequency determination of molecular transition in the Doppler regime at kHz level of accuracy
We present absolute frequency measurement of the unperturbed P7 P7 O$_2$ B-band transition with relative standard uncertainty of $2\times10^{-11}$. We reached the level of accuracy typical for Doppler-free techniques, with Doppler-limited spectroscopy. The Doppler-limited shapes of the P7 P7 spectral line were measur...
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Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification
Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial machine learning can compromise biometric recognition systems by exploi...
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Sublinear elliptic problems under radiality. Harmonic $NA$ groups and Euclidean spaces
Let $\L $ be the Laplace operator on $\R ^d$, $d\geq 3$ or the Laplace Beltrami operator on the harmonic $NA$ group (in particular on a rank one noncompact symmetric space). For the equation $ \L u - \varphi(\cdot,u)=0$ we give necessary and sufficient conditions for the existence of entire bounded or large solutions...
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Bayesian Uncertainty Directed Trial Designs
Most Bayesian response-adaptive designs unbalance randomization rates towards the most promising arms with the goal of increasing the number of positive treatment outcomes during the study, even though the primary aim of the trial is different. We discuss Bayesian uncertainty directed designs (BUD), a class of Bayesi...
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Wasserstein Learning of Deep Generative Point Process Models
Point processes are becoming very popular in modeling asynchronous sequential data due to their sound mathematical foundation and strength in modeling a variety of real-world phenomena. Currently, they are often characterized via intensity function which limits model's expressiveness due to unrealistic assumptions on...
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Interior Structures and Tidal Heating in the TRAPPIST-1 Planets
With seven planets, the TRAPPIST-1 system has the largest number of exoplanets discovered in a single system so far. The system is of astrobiological interest, because three of its planets orbit in the habitable zone of the ultracool M dwarf. Assuming the planets are composed of non-compressible iron, rock, and H$_2$...
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A Driver-in-the Loop Fuel Economic Control Strategy for Connected Vehicles in Urban Roads
In this paper, we focus on developing driver-in-the loop fuel economic control strategy for multiple connected vehicles. The control strategy is considered to work in a driver assistance framework where the controller gives command to a driver to follow while considering the ability of the driver in following control...
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A General and Adaptive Robust Loss Function
We present a generalization of the Cauchy/Lorentzian, Geman-McClure, Welsch/Leclerc, generalized Charbonnier, Charbonnier/pseudo-Huber/L1-L2, and L2 loss functions. By introducing robustness as a continous parameter, our loss function allows algorithms built around robust loss minimization to be generalized, which im...
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Asymptotically Efficient Estimation of Smooth Functionals of Covariance Operators
Let $X$ be a centered Gaussian random variable in a separable Hilbert space ${\mathbb H}$ with covariance operator $\Sigma.$ We study a problem of estimation of a smooth functional of $\Sigma$ based on a sample $X_1,\dots ,X_n$ of $n$ independent observations of $X.$ More specifically, we are interested in functional...
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Evolution of magnetic and dielectric properties in Sr-substituted high temperature multiferroic YBaCuFeO5
We report the evolution of structural, magnetic and dielectric properties due to partial substitution of Ba by Sr in the high temperature multiferroic YBaCuFeO5. This compound exhibits ferroelectric and antiferromagnetic transitions around 200 K and these two phenomena are presumed to be coupled with each other. Our ...
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Regular Intersecting Families
We call a family of sets intersecting, if any two sets in the family intersect. In this paper we investigate intersecting families $\mathcal{F}$ of $k$-element subsets of $[n]:=\{1,\ldots, n\},$ such that every element of $[n]$ lies in the same (or approximately the same) number of members of $\mathcal{F}$. In partic...
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Stochastic Maximum Likelihood Optimization via Hypernetworks
This work explores maximum likelihood optimization of neural networks through hypernetworks. A hypernetwork initializes the weights of another network, which in turn can be employed for typical functional tasks such as regression and classification. We optimize hypernetworks to directly maximize the conditional likel...
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Magnetic resonance of rubidium atoms passing through a multi-layered transmission magnetic grating
We measured the magnetic resonance of rubidium atoms passing through periodic magnetic fields generated by two types of multilayered transmission magnetic grating. One of the gratings reported here was assembled by stacking four layers of magnetic films so that the direction of magnetization alternated at each level....
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Fast multi-output relevance vector regression
This paper aims to decrease the time complexity of multi-output relevance vector regression from O(VM^3) to O(V^3+M^3), where V is the number of output dimensions, M is the number of basis functions, and V<M. The experimental results demonstrate that the proposed method is more competitive than the existing method, w...
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Computing LPMLN Using ASP and MLN Solvers
LPMLN is a recent addition to probabilistic logic programming languages. Its main idea is to overcome the rigid nature of the stable model semantics by assigning a weight to each rule in a way similar to Markov Logic is defined. We present two implementations of LPMLN, $\text{LPMLN2ASP}$ and $\text{LPMLN2MLN}$. Syste...
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Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences
In his seminal book `The Inmates are Running the Asylum: Why High-Tech Products Drive Us Crazy And How To Restore The Sanity' [2004, Sams Indianapolis, IN, USA], Alan Cooper argues that a major reason why software is often poorly designed (from a user perspective) is that programmers are in charge of design decisions...
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Building Emotional Machines: Recognizing Image Emotions through Deep Neural Networks
An image is a very effective tool for conveying emotions. Many researchers have investigated in computing the image emotions by using various features extracted from images. In this paper, we focus on two high level features, the object and the background, and assume that the semantic information of images is a good ...
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Soft Rough Graphs
Soft set theory and rough set theory are mathematical tools to deal with uncertainties. In [3], authors combined these concepts and introduced soft rough sets. In this paper, we introduce the concepts of soft rough graphs, vertex and edge induced soft rough graphs and soft rough trees. We define some products with ex...
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PPMF: A Patient-based Predictive Modeling Framework for Early ICU Mortality Prediction
To date, developing a good model for early intensive care unit (ICU) mortality prediction is still challenging. This paper presents a patient based predictive modeling framework (PPMF) to improve the performance of ICU mortality prediction using data collected during the first 48 hours of ICU admission. PPMF consists...
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Zeros of real random polynomials spanned by OPUC
Let \( \{\varphi_i\}_{i=0}^\infty \) be a sequence of orthonormal polynomials on the unit circle with respect to a probability measure \( \mu \). We study zero distribution of random linear combinations of the form \[ P_n(z)=\sum_{i=0}^{n-1}\eta_i\varphi_i(z), \] where \( \eta_0,\dots,\eta_{n-1} \) are i.i.d. standar...
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Indirect observation of molecular disassociation in solid benzene at low temperatures
The molecular dynamics of solid benzene are extremely complex; especially below 77 K, its inner mechanics remain mostly unexplored. Benzene is also a prototypical molecular crystal that becomes energetically frustrated at low temperatures and usually unusual phenomena accompanies such scenarios. We performed dielectr...
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Green's function-based control-oriented modeling of electric field for dielectrophoresis
In this paper, we propose a novel approach to obtaining a reliable and simple mathematical model of a dielectrophoretic force for model-based feedback micromanipulation. Any such model is expected to sufficiently accurately relate the voltages (electric potentials) applied to the electrodes to the resulting forces ex...
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Hilbert Bases and Lecture Hall Partitions
In the interest of finding the minimum additive generating set for the set of $\boldsymbol{s}$-lecture hall partitions, we compute the Hilbert bases for the $\boldsymbol{s}$-lecture hall cones in certain cases. In particular, we compute the Hilbert bases for two well-studied families of sequences, namely the $1\mod k...
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CLUBB-SILHS: A parameterization of subgrid variability in the atmosphere
This document provides a detailed overview of the CLUBB-SILHS cloud and turbulence parameterization, including theoretical background, model equations, closure assumptions, simulation results, comparison with other parameterization methods, FAQs, and source code documentation.
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Relative Entropy in CFT
By using Araki's relative entropy, Lieb's convexity and the theory of singular integrals, we compute the mutual information associated with free fermions, and we deduce many results about entropies for chiral CFT's which are embedded into free fermions, and their extensions. Such relative entropies in CFT are here co...
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Approximate Supermodularity Bounds for Experimental Design
This work provides performance guarantees for the greedy solution of experimental design problems. In particular, it focuses on A- and E-optimal designs, for which typical guarantees do not apply since the mean-square error and the maximum eigenvalue of the estimation error covariance matrix are not supermodular. To ...
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A new precision measurement of the α-decay half-life of 190Pt
A laboratory measurement of the $\alpha$-decay half-life of $^{190}$Pt has been performed using a low background Frisch grid ionisation chamber. A total amount of 216.60(17) mg of natural platinum has been measured for 75.9 days. The resulting half-life is $(4.97\pm0.16)\times 10^{11}$ years, with a total uncertainty...
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Online Inverse Reinforcement Learning via Bellman Gradient Iteration
This paper develops an online inverse reinforcement learning algorithm aimed at efficiently recovering a reward function from ongoing observations of an agent's actions. To reduce the computation time and storage space in reward estimation, this work assumes that each observed action implies a change of the Q-value d...
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SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
Deep learning has the potential to revolutionize quantum chemistry as it is ideally suited to learn representations for structured data and speed up the exploration of chemical space. While convolutional neural networks have proven to be the first choice for images, audio and video data, the atoms in molecules are no...
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Generalized magnetic mirrors
We propose generalized magnetic mirrors that can be achieved by excitations of sole electric resonances. Conventional approaches to obtain magnetic mirrors rely heavily on exciting the fundamental magnetic dipoles, whereas here we reveal that besides magnetic resonances, electric resonances of higher orders can be al...
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Cryogenic readout for multiple VUV4 Multi-Pixel Photon Counters in liquid xenon
We present the performances and characterization of an array made of S13370-3050CN (VUV4 generation) Multi-Pixel Photon Counters manufactured by Hamamatsu and equipped with a low power consumption preamplifier operating at liquid xenon temperature (~ 175 K). The electronics is designed for the readout of a matrix of ...
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A Scalable Deep Neural Network Architecture for Multi-Building and Multi-Floor Indoor Localization Based on Wi-Fi Fingerprinting
One of the key technologies for future large-scale location-aware services covering a complex of multi-story buildings --- e.g., a big shopping mall and a university campus --- is a scalable indoor localization technique. In this paper, we report the current status of our investigation on the use of deep neural netwo...
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A latent spatial factor approach for synthesizing opioid associated deaths and treatment admissions in Ohio counties
Background: Opioid misuse is a major public health issue in the United States and in particular Ohio. However, the burden of the epidemic is challenging to quantify as public health surveillance measures capture different aspects of the problem. Here we synthesize county-level death and treatment counts to compare th...
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The Cost of Transportation : Spatial Analysis of US Fuel Prices
The geography of fuel prices has many various implications, from its significant impact on accessibility to being an indicator of territorial equity and transportation policy. In this paper, we study the spatio-temporal patterns of fuel price in the US at a very high resolution using a newly constructed dataset colle...
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Optimal Multi-Object Segmentation with Novel Gradient Vector Flow Based Shape Priors
Shape priors have been widely utilized in medical image segmentation to improve segmentation accuracy and robustness. A major way to encode such a prior shape model is to use a mesh representation, which is prone to causing self-intersection or mesh folding. Those problems require complex and expensive algorithms to ...
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Discovery of water at high spectral resolution in the atmosphere of 51 Peg b
We report the detection of water absorption features in the dayside spectrum of the first-known hot Jupiter, 51 Peg b, confirming the star-planet system to be a double-lined spectroscopic binary. We used high-resolution (R~100,000), 3.2 micron spectra taken with CRIRES/VLT to trace the radial-velocity shift of the wa...
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A strengthened inequality of Alon-Babai-Suzuki's conjecture on set systems with restricted intersections modulo p
Let $K=\{k_1,k_2,\ldots,k_r\}$ and $L=\{l_1,l_2,\ldots,l_s\}$ be disjoint subsets of $\{0,1,\ldots,p-1\}$, where $p$ is a prime and $A=\{A_1,A_2,\ldots,A_m\}$ be a family of subsets of $[n]$ such that $|A_i|\pmod{p}\in K$ for all $A_i\in A$ and $|A_i\cap A_j|\pmod{p}\in L$ for $i\ne j$. In 1991, Alon, Babai and Suzuk...
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Traditional and Heavy-Tailed Self Regularization in Neural Network Models
Random Matrix Theory (RMT) is applied to analyze the weight matrices of Deep Neural Networks (DNNs), including both production quality, pre-trained models such as AlexNet and Inception, and smaller models trained from scratch, such as LeNet5 and a miniature-AlexNet. Empirical and theoretical results clearly indicate ...
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Interfacial Mechanical Behaviors in Carbon Nanotube Assemblies
Interface widely exists in carbon nanotube (CNT) assembly materials, taking place at different length scales. It determines severely the mechanical properties of these assembly materials. Here I assess the mechanical properties of individual CNTs and CNT bundles, the inter-layer or inter-shell mechanics in multi-wall...
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Learning a Latent Space of Multitrack Measures
Discovering and exploring the underlying structure of multi-instrumental music using learning-based approaches remains an open problem. We extend the recent MusicVAE model to represent multitrack polyphonic measures as vectors in a latent space. Our approach enables several useful operations such as generating plausi...
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Multimodal Affect Analysis for Product Feedback Assessment
Consumers often react expressively to products such as food samples, perfume, jewelry, sunglasses, and clothing accessories. This research discusses a multimodal affect recognition system developed to classify whether a consumer likes or dislikes a product tested at a counter or kiosk, by analyzing the consumer's fac...
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Distributed Learning for Cooperative Inference
We study the problem of cooperative inference where a group of agents interact over a network and seek to estimate a joint parameter that best explains a set of observations. Agents do not know the network topology or the observations of other agents. We explore a variational interpretation of the Bayesian posterior ...
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Selection of training populations (and other subset selection problems) with an accelerated genetic algorithm (STPGA: An R-package for selection of training populations with a genetic algorithm)
Optimal subset selection is an important task that has numerous algorithms designed for it and has many application areas. STPGA contains a special genetic algorithm supplemented with a tabu memory property (that keeps track of previously tried solutions and their fitness for a number of iterations), and with a regre...
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CERES in Propositional Proof Schemata
Cut-elimination is one of the most famous problems in proof theory, and it was defined and solved for first-order sequent calculus by Gentzen in his celebrated Hauptsatz. Ceres is a different cut-elimination algorithm for first- and higher-order classical logic. Ceres was extended to proof schemata, which are templat...
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A Schur decomposition reveals the richness of structure in homogeneous, isotropic turbulence as a consequence of localised shear
An improved understanding of turbulence is essential for the effective modelling and control of industrial and geophysical processes. Homogeneous, isotropic turbulence (HIT) is the archetypal field for developing turbulence physics theory. Based on the Schur transform, we introduce an additive decomposition of the ve...
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Parametrizing filters of a CNN with a GAN
It is commonly agreed that the use of relevant invariances as a good statistical bias is important in machine-learning. However, most approaches that explicitly incorporate invariances into a model architecture only make use of very simple transformations, such as translations and rotations. Hence, there is a need fo...
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Monolayer FeSe on SrTiO$_3$
Epitaxial engineering of solid-state heterointerfaces is a leading avenue to realizing enhanced or novel electronic states of matter. As a recent example, bulk FeSe is an unconventional superconductor with a modest transition temperature ($T_c$) of 9 K. When a single atomic layer of FeSe is grown on SrTiO$_3$, howeve...
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A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
Estimating multiple sparse Gaussian Graphical Models (sGGMs) jointly for many related tasks (large $K$) under a high-dimensional (large $p$) situation is an important task. Most previous studies for the joint estimation of multiple sGGMs rely on penalized log-likelihood estimators that involve expensive and difficult...
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Quantum Spin Liquids Unveil the Genuine Mott State
The Widom line identifies the locus in the phase diagram where a supercritical gas crosses over from gas-like to a more liquid-like behavior. A similar transition exists in correlated electron liquids, where the interplay of Coulomb repulsion, bandwidth and temperature triggers between the Mott insulating state and a...
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Parameter and State Estimation in Queues and Related Stochastic Models: A Bibliography
This is an annotated bibliography on estimation and inference results for queues and related stochastic models. The purpose of this document is to collect and categorise works in the field, allowing for researchers and practitioners to explore the various types of results that exist. This bibliography attempts to inc...
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Towards a Social Virtual Reality Learning Environment in High Fidelity
Virtual Learning Environments (VLEs) are spaces designed to educate students remotely via online platforms. Although traditional VLEs such as iSocial have shown promise in educating students, they offer limited immersion that diminishes learning effectiveness. This paper outlines a virtual reality learning environmen...
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L2 Regularization versus Batch and Weight Normalization
Batch Normalization is a commonly used trick to improve the training of deep neural networks. These neural networks use L2 regularization, also called weight decay, ostensibly to prevent overfitting. However, we show that L2 regularization has no regularizing effect when combined with normalization. Instead, regulari...
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Bitwise Operations of Cellular Automaton on Gray-scale Images
Cellular Automata (CA) theory is a discrete model that represents the state of each of its cells from a finite set of possible values which evolve in time according to a pre-defined set of transition rules. CA have been applied to a number of image processing tasks such as Convex Hull Detection, Image Denoising etc. ...
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Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems
Recently, deep learning approaches with various network architectures have achieved significant performance improvement over existing iterative reconstruction methods in various imaging problems. However, it is still unclear why these deep learning architectures work for specific inverse problems. To address these is...
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Enhanced bacterial swimming speeds in macromolecular polymer solutions
The locomotion of swimming bacteria in simple Newtonian fluids can successfully be described within the framework of low Reynolds number hydrodynamics. The presence of polymers in biofluids generally increases the viscosity, which is expected to lead to slower swimming for a constant bacterial motor torque. Surprisin...
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An Algebraic Treatment of Recursion
I review the three principal methods to assign meaning to recursion in process algebra: the denotational, the operational and the algebraic approach, and I extend the latter to unguarded recursion.
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On Approximation for Fractional Stochastic Partial Differential Equations on the Sphere
This paper gives the exact solution in terms of the Karhunen-Loève expansion to a fractional stochastic partial differential equation on the unit sphere $\mathbb{S}^{2}\subset \mathbb{R}^{3}$ with fractional Brownian motion as driving noise and with random initial condition given by a fractional stochastic Cauchy pro...
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Learning Structural Node Embeddings Via Diffusion Wavelets
Nodes residing in different parts of a graph can have similar structural roles within their local network topology. The identification of such roles provides key insight into the organization of networks and can be used for a variety of machine learning tasks. However, learning structural representations of nodes is ...
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Excitonic mass gap in uniaxially strained graphene
We study the conditions for spontaneously generating an excitonic mass gap due to Coulomb interactions between anisotropic Dirac fermions in uniaxially strained graphene. The mass gap equation is realized as a self-consistent solution for the self-energy within the Hartree-Fock mean-field and static random phase appr...
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On spectral properties of high-dimensional spatial-sign covariance matrices in elliptical distributions with applications
Spatial-sign covariance matrix (SSCM) is an important substitute of sample covariance matrix (SCM) in robust statistics. This paper investigates the SSCM on its asymptotic spectral behaviors under high-dimensional elliptical populations, where both the dimension $p$ of observations and the sample size $n$ tend to inf...
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Decoupled Potential Integral Equations for Electromagnetic Scattering from Dielectric Objects
Recent work on developing novel integral equation formulations has involved using potentials as opposed to fields. This is a consequence of the additional flexibility offered by using potentials to develop well conditioned systems. Most of the work in this arena has wrestled with developing this formulation for perfe...
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High-field transport properties of a P-doped BaFe2As2 film on technical substrate
High temperature (high-Tc) superconductors like cuprates have superior critical current properties in magnetic fields over other superconductors. However, superconducting wires for high-field-magnet applications are still dominated by low-Tc Nb3Sn due probably to cost and processing issues. The recent discovery of a ...
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Construction of and efficient sampling from the simplicial configuration model
Simplicial complexes are now a popular alternative to networks when it comes to describing the structure of complex systems, primarily because they encode multi-node interactions explicitly. With this new description comes the need for principled null models that allow for easy comparison with empirical data. We prop...
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Local and 2-local derivations and automorphisms on simple Leibniz algebras
The present paper is devoted to local and 2-local derivations and automorphism of complex finite-dimensional simple Leibniz algebras. We prove that all local derivations and 2-local derivations on a finite-dimensional complex simple Leibniz algebra are automatically derivations. We show that nilpotent Leibniz algebra...
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RodFIter: Attitude Reconstruction from Inertial Measurement by Functional Iteration
Rigid motion computation or estimation is a cornerstone in numerous fields. Attitude computation can be achieved by integrating the angular velocity measured by gyroscopes, the accuracy of which is crucially important for the dead-reckoning inertial navigation. The state-of-the-art attitude algorithms have unexceptio...
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Influence Networks in International Relations
Measuring influence and determining what drives it are persistent questions in political science and in network analysis more generally. Herein we focus on the domain of international relations. Our major substantive question is: How can we determine what characteristics make an actor influential? To address the topi...
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Incorporating Feedback into Tree-based Anomaly Detection
Anomaly detectors are often used to produce a ranked list of statistical anomalies, which are examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, in realworld applications, this process can be exceedingly difficult for the analyst since a large fraction of high-ranking anom...
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Towards An Adaptive Compliant Aerial Manipulator for Contact-Based Interaction
As roles for unmanned aerial vehicles (UAV) continue to diversify, the ability to sense and interact closely with the environment becomes increasingly important. Within this paper we report on the initial flight tests of a novel adaptive compliant actuator which will allow a UAV to carry out such tasks as the "pick a...
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On the number of inequivalent Gabidulin codes
Maximum rank-distance (MRD) codes are extremal codes in the space of $m\times n$ matrices over a finite field, equipped with the rank metric. Up to generalizations, the classical examples of such codes were constructed in the 1970s and are today known as Gabidulin codes. Motivated by several recent approaches to cons...
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A Connection Between Mixing and Kac's Chaos
The Boltzmann equation is an integro-differential equation which describes the density function of the distribution of the velocities of the molecules of dilute monoatomic gases under the assumption that the energy is only transferred via collisions between the molecules. In 1956 Kac studied the Boltzmann equation an...
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The aCORN Backscatter-Suppressed Beta Spectrometer
Backscatter of electrons from a beta spectrometer, with incomplete energy deposition, can lead to undesirable effects in many types of experiments. We present and discuss the design and operation of a backscatter-suppressed beta spectrometer that was developed as part of a program to measure the electron-antineutrino...
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Deterministic Browser
Timing attacks have been a continuous threat to users' privacy in modern browsers. To mitigate such attacks, existing approaches, such as Tor Browser and Fermata, add jitters to the browser clock so that an attacker cannot accurately measure an event. However, such defenses only raise the bar for an attacker but do n...
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Can Transfer Entropy Infer Causality in Neuronal Circuits for Cognitive Processing?
Finding the causes to observed effects and establishing causal relationships between events is (and has been) an essential element of science and philosophy. Automated methods that can detect causal relationships would be very welcome, but practical methods that can infer causality are difficult to find, and the subj...
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Solvability of the Stokes Immersed Boundary Problem in Two Dimensions
We study coupled motion of a 1-D closed elastic string immersed in a 2-D Stokes flow, known as the Stokes immersed boundary problem in two dimensions. Using the fundamental solution of the Stokes equation and the Lagrangian coordinate of the string, we write the problem into a contour dynamic formulation, which is a ...
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Nonlinear Field Space Cosmology
We consider the FRW cosmological model in which the matter content of universe (playing a role of inflaton or quintessence) is given by a novel generalization of the massive scalar field. The latter is a scalar version of the recently introduced Nonlinear Field Space Theory (NFST), where physical phase space of a giv...
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Futuristic Classification with Dynamic Reference Frame Strategy
Classification is one of the widely used analytical techniques in data science domain across different business to associate a pattern which contribute to the occurrence of certain event which is predicted with some likelihood. This Paper address a lacuna of creating some time window before the prediction actually ha...
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On the normal centrosymmetric Nonnegative inverse eigenvalue problem
We give sufficient conditions of the nonnegative inverse eigenvalue problem (NIEP) for normal centrosymmetric matrices. These sufficient conditions are analogous to the sufficient conditions of the NIEP for normal matrices given by Xu [16] and Julio, Manzaneda and Soto [2].
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Spectral Dynamics of Learning Restricted Boltzmann Machines
The Restricted Boltzmann Machine (RBM), an important tool used in machine learning in particular for unsupervized learning tasks, is investigated from the perspective of its spectral properties. Starting from empirical observations, we propose a generic statistical ensemble for the weight matrix of the RBM and charac...
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Local energy decay for Lipschitz wavespeeds
We prove a logarithmic local energy decay rate for the wave equation with a wavespeed that is a compactly supported Lipschitz perturbation of unity. The key is to establish suitable resolvent estimates at high and low energy for the meromorphic continuation of the cutoff resolvent. The decay rate is the same as that ...
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Linear stability and stability of Lazarsfeld-Mukai bundles
Let $C$ be a smooth irreducible projective curve and let $(L,H^0(C,L))$ be a complete and generated linear series on $C$. Denote by $M_L$ the kernel of the evaluation map $H^0(C,L)\otimes\mathcal O_C\to L$. The exact sequence $0\to M_L\to H^0(C,L)\otimes\mathcal O_C\to L\to 0$ fits into a commutative diagram that we ...
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Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped
Controllers in robotics often consist of expert-designed heuristics, which can be hard to tune in higher dimensions. It is typical to use simulation to learn these parameters, but controllers learned in simulation often don't transfer to hardware. This necessitates optimization directly on hardware. However, collecti...
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Comparison of multi-task convolutional neural network (MT-CNN) and a few other methods for toxicity prediction
Toxicity analysis and prediction are of paramount importance to human health and environmental protection. Existing computational methods are built from a wide variety of descriptors and regressors, which makes their performance analysis difficult. For example, deep neural network (DNN), a successful approach in many...
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SIFM: A network architecture for seamless flow mobility between LTE and WiFi networks - Analysis and Testbed Implementation
This paper deals with cellular (e.g. LTE) networks that selectively offload the mobile data traffic onto WiFi (IEEE 802.11) networks to improve network performance. We propose the Seamless Internetwork Flow Mobility (SIFM) architecture that provides seamless flow-mobility support using concepts of Software Defined Ne...
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Graph sampling with determinantal processes
We present a new random sampling strategy for k-bandlimited signals defined on graphs, based on determinantal point processes (DPP). For small graphs, ie, in cases where the spectrum of the graph is accessible, we exhibit a DPP sampling scheme that enables perfect recovery of bandlimited signals. For large graphs, ie...
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Grundy dominating sequences and zero forcing sets
In a graph $G$ a sequence $v_1,v_2,\dots,v_m$ of vertices is Grundy dominating if for all $2\le i \le m$ we have $N[v_i]\not\subseteq \cup_{j=1}^{i-1}N[v_j]$ and is Grundy total dominating if for all $2\le i \le m$ we have $N(v_i)\not\subseteq \cup_{j=1}^{i-1}N(v_j)$. The length of the longest Grundy (total) dominati...
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