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Self-consistent dynamical model of the Broad Line Region
We develope a self-consistent description of the Broad Line Region based on the concept of the failed wind powered by the radiation pressure acting on dusty accretion disk atmosphere in Keplerian motion. The material raised high above the disk is illuminated, dust evaportes, and the matter falls back towards the disk...
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Measuring the polarization of electromagnetic fields using Rabi-rate measurements with spatial resolution: experiment and theory
When internal states of atoms are manipulated using coherent optical or radio-frequency (RF) radiation, it is essential to know the polarization of the radiation with respect to the quantization axis of the atom. We first present a measurement of the two-dimensional spatial distribution of the electric-field amplitud...
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Software-based Microarchitectural Attacks
Modern processors are highly optimized systems where every single cycle of computation time matters. Many optimizations depend on the data that is being processed. Software-based microarchitectural attacks exploit effects of these optimizations. Microarchitectural side-channel attacks leak secrets from cryptographic ...
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Pixelwise Instance Segmentation with a Dynamically Instantiated Network
Semantic segmentation and object detection research have recently achieved rapid progress. However, the former task has no notion of different instances of the same object, and the latter operates at a coarse, bounding-box level. We propose an Instance Segmentation system that produces a segmentation map where each p...
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Binary Matrix Factorization via Dictionary Learning
Matrix factorization is a key tool in data analysis; its applications include recommender systems, correlation analysis, signal processing, among others. Binary matrices are a particular case which has received significant attention for over thirty years, especially within the field of data mining. Dictionary learnin...
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Enriching Complex Networks with Word Embeddings for Detecting Mild Cognitive Impairment from Speech Transcripts
Mild Cognitive Impairment (MCI) is a mental disorder difficult to diagnose. Linguistic features, mainly from parsers, have been used to detect MCI, but this is not suitable for large-scale assessments. MCI disfluencies produce non-grammatical speech that requires manual or high precision automatic correction of trans...
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The many faces of degeneracy in conic optimization
Slater's condition -- existence of a "strictly feasible solution" -- is a common assumption in conic optimization. Without strict feasibility, first-order optimality conditions may be meaningless, the dual problem may yield little information about the primal, and small changes in the data may render the problem infe...
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Strong homotopy types of acyclic categories and $Δ$-complexes
We extend the homotopy theories based on point reduction for finite spaces and simplicial complexes to finite acyclic categories and $\Delta$-complexes, respectively. The functors of classifying spaces and face posets are compatible with these homotopy theories. In contrast with the classical settings of finite space...
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Boundary problems for the fractional and tempered fractional operators
For characterizing the Brownian motion in a bounded domain: $\Omega$, it is well-known that the boundary conditions of the classical diffusion equation just rely on the given information of the solution along the boundary of a domain; on the contrary, for the Lévy flights or tempered Lévy flights in a bounded domain,...
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Bohm's approach to quantum mechanics: Alternative theory or practical picture?
Since its inception Bohmian mechanics has been generally regarded as a hidden-variable theory aimed at providing an objective description of quantum phenomena. To date, this rather narrow conception of Bohm's proposal has caused it more rejection than acceptance. Now, after 65 years of Bohmian mechanics, should still...
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Continuous-wave virtual-state lasing from cold ytterbium atoms
While conventional lasers are based on gain media with three or four real levels, unconventional lasers including virtual levels and two-photon processes offer new opportunities. We study lasing that involves a two-photon process through a virtual lower level, which we realize in a cloud of cold ytterbium atoms that ...
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Assessment of Future Changes in Intensity-Duration-Frequency Curves for Southern Ontario using North American (NA)-CORDEX Models with Nonstationary Methods
The evaluation of possible climate change consequence on extreme rainfall has significant implications for the design of engineering structure and socioeconomic resources development. While many studies have assessed the impact of climate change on design rainfall using global and regional climate model (RCM) predict...
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Improved Algorithms for Computing the Cycle of Minimum Cost-to-Time Ratio in Directed Graphs
We study the problem of finding the cycle of minimum cost-to-time ratio in a directed graph with $ n $ nodes and $ m $ edges. This problem has a long history in combinatorial optimization and has recently seen interesting applications in the context of quantitative verification. We focus on strongly polynomial algori...
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Interplay of dust alignment, grain growth and magnetic fields in polarization: lessons from the emission-to-extinction ratio
Polarized extinction and emission from dust in the interstellar medium (ISM) are hard to interpret, as they have a complex dependence on dust optical properties, grain alignment and magnetic field orientation. This is particularly true in molecular clouds. The data available today are not yet used to their full poten...
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Asynchronous Distributed Variational Gaussian Processes for Regression
Gaussian processes (GPs) are powerful non-parametric function estimators. However, their applications are largely limited by the expensive computational cost of the inference procedures. Existing stochastic or distributed synchronous variational inferences, although have alleviated this issue by scaling up GPs to mil...
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Bayesian Unification of Gradient and Bandit-based Learning for Accelerated Global Optimisation
Bandit based optimisation has a remarkable advantage over gradient based approaches due to their global perspective, which eliminates the danger of getting stuck at local optima. However, for continuous optimisation problems or problems with a large number of actions, bandit based approaches can be hindered by slow l...
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Stacco: Differentially Analyzing Side-Channel Traces for Detecting SSL/TLS Vulnerabilities in Secure Enclaves
Intel Software Guard Extension (SGX) offers software applications enclave to protect their confidentiality and integrity from malicious operating systems. The SSL/TLS protocol, which is the de facto standard for protecting transport-layer network communications, has been broadly deployed for a secure communication ch...
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Automatic Extrinsic Calibration for Lidar-Stereo Vehicle Sensor Setups
Sensor setups consisting of a combination of 3D range scanner lasers and stereo vision systems are becoming a popular choice for on-board perception systems in vehicles; however, the combined use of both sources of information implies a tedious calibration process. We present a method for extrinsic calibration of lid...
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Representations of Super $W(2,2)$ algebra $\mathfrak{L}$
In paper, we study the representation theory of super $W(2,2)$ algebra ${\mathfrak{L}}$. We prove that ${\mathfrak{L}}$ has no mixed irreducible modules and give the classification of irreducible modules of intermediate series. We determinate the conjugate-linear anti-involution of ${\mathfrak{L}}$ and give the unita...
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Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics
Software developers frequently issue generic natural language queries for code search while using code search engines (e.g., GitHub native search, Krugle). Such queries often do not lead to any relevant results due to vocabulary mismatch problems. In this paper, we propose a novel technique that automatically identif...
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Detecting Bot Activity in the Ethereum Blockchain Network
The Ethereum blockchain network is a decentralized platform enabling smart contract execution and transactions of Ether (ETH) [1], its designated cryptocurrency. Ethereum is the second most popular cryptocurrency with a market cap of more than 100 billion USD, with hundreds of thousands of transactions executed daily...
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Near-infrared laser thermal conjunctivoplasty
Conjunctivochalasis is a common cause of tear dysfunction due to the conjunctiva becoming loose and wrinkly with age. The current solutions to this disease include either surgical excision in the operating room, or thermoreduction of the loose tissue with hot wire in the clinic. We developed a near-infrared (NIR) las...
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Superconductivity at 7.3 K in the 133-type Cr-based RbCr3As3 single crystals
Here we report the preparation and superconductivity of the 133-type Cr-based quasi-one-dimensional (Q1D) RbCr3As3 single crystals. The samples were prepared by the deintercalation of Rb+ ions from the 233-type Rb2Cr3As3 crystals which were grown from a high-temperature solution growth method. The RbCr3As3 compound c...
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Solution of parabolic free boundary problems using transmuted heat polynomials
A numerical method for free boundary problems for the equation \[ u_{xx}-q(x)u=u_t \] is proposed. The method is based on recent results from transmutation operators theory allowing one to construct efficiently a complete system of solutions for this equation generalizing the system of heat polynomials. The correspon...
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Neural-Network Quantum States, String-Bond States, and Chiral Topological States
Neural-Network Quantum States have been recently introduced as an Ansatz for describing the wave function of quantum many-body systems. We show that there are strong connections between Neural-Network Quantum States in the form of Restricted Boltzmann Machines and some classes of Tensor-Network states in arbitrary di...
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Nondestructive testing of grating imperfections using grating-based X-ray phase-contrast imaging
We reported the usage of grating-based X-ray phase-contrast imaging in nondestructive testing of grating imperfections. It was found that electroplating flaws could be easily detected by conventional absorption signal, and in particular, we observed that the grating defects resulting from uneven ultraviolet exposure ...
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End-to-End Information Extraction without Token-Level Supervision
Most state-of-the-art information extraction approaches rely on token-level labels to find the areas of interest in text. Unfortunately, these labels are time-consuming and costly to create, and consequently, not available for many real-life IE tasks. To make matters worse, token-level labels are usually not the desi...
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Lipschitz regularity of solutions to two-phase free boundary problems
We prove Lipschitz continuity of viscosity solutions to a class of two-phase free boundary problems governed by fully nonlinear operators.
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VTA: An Open Hardware-Software Stack for Deep Learning
Hardware acceleration is an enabler for ubiquitous and efficient deep learning. With hardware accelerators being introduced in datacenter and edge devices, it is time to acknowledge that hardware specialization is central to the deep learning system stack. This technical report presents the Versatile Tensor Accelerat...
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Efficient Localized Inference for Large Graphical Models
We propose a new localized inference algorithm for answering marginalization queries in large graphical models with the correlation decay property. Given a query variable and a large graphical model, we define a much smaller model in a local region around the query variable in the target model so that the marginal di...
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Multi-kink collisions in the $ϕ^6$ model
We study simultaneous collisions of two, three, and four kinks and antikinks of the $\phi^6$ model at the same spatial point. Unlike the $\phi^4$ kinks, the $\phi^6$ kinks are asymmetric and this enriches the variety of the collision scenarios. In our numerical simulations we observe both reflection and bound state f...
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InverseFaceNet: Deep Monocular Inverse Face Rendering
We introduce InverseFaceNet, a deep convolutional inverse rendering framework for faces that jointly estimates facial pose, shape, expression, reflectance and illumination from a single input image. By estimating all parameters from just a single image, advanced editing possibilities on a single face image, such as a...
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Exact partial information decompositions for Gaussian systems based on dependency constraints
The Partial Information Decomposition (PID) [arXiv:1004.2515] provides a theoretical framework to characterize and quantify the structure of multivariate information sharing. A new method (Idep) has recently been proposed for computing a two-predictor PID over discrete spaces. [arXiv:1709.06653] A lattice of maximum ...
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Deep Multimodal Subspace Clustering Networks
We present convolutional neural network (CNN) based approaches for unsupervised multimodal subspace clustering. The proposed framework consists of three main stages - multimodal encoder, self-expressive layer, and multimodal decoder. The encoder takes multimodal data as input and fuses them to a latent space represen...
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Finite-time generalization of the thermodynamic uncertainty relation
For fluctuating currents in non-equilibrium steady states, the recently discovered thermodynamic uncertainty relation expresses a fundamental relation between their variance and the overall entropic cost associated with the driving. We show that this relation holds not only for the long-time limit of fluctuations, as...
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Composition Properties of Inferential Privacy for Time-Series Data
With the proliferation of mobile devices and the internet of things, developing principled solutions for privacy in time series applications has become increasingly important. While differential privacy is the gold standard for database privacy, many time series applications require a different kind of guarantee, and...
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Landau-Ginzburg theory of cortex dynamics: Scale-free avalanches emerge at the edge of synchronization
Understanding the origin, nature, and functional significance of complex patterns of neural activity, as recorded by diverse electrophysiological and neuroimaging techniques, is a central challenge in neuroscience. Such patterns include collective oscillations emerging out of neural synchronization as well as highly ...
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Recurrent Autoregressive Networks for Online Multi-Object Tracking
The main challenge of online multi-object tracking is to reliably associate object trajectories with detections in each video frame based on their tracking history. In this work, we propose the Recurrent Autoregressive Network (RAN), a temporal generative modeling framework to characterize the appearance and motion d...
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The occurrence of transverse and longitudinal electric currents in the classical plasma under the action of N transverse electromagnetic waves
Classical plasma with arbitrary degree of degeneration of electronic gas is considered. In plasma N (N>2) collinear electromagnatic waves are propagated. It is required to find the response of plasma to these waves. Distribution function in square-law approximation on quantities of two small parameters from Vlasov eq...
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Well-posedness of a Model for the Growth of Tree Stems and Vines
The paper studies a PDE model for the growth of a tree stem or a vine, having the form of a differential inclusion with state constraints. The equations describe the elongation due to cell growth, and the response to gravity and to external obstacles. The main theorem shows that the evolution problem is well posed, u...
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Yonsei evolutionary population synthesis (YEPS). II. Spectro-photometric evolution of helium-enhanced stellar populations
The discovery of multiple stellar populations in Milky Way globular clusters (GCs) has stimulated various follow-up studies on helium-enhanced stellar populations. Here we present the evolutionary population synthesis models for the spectro-photometric evolution of simple stellar populations (SSPs) with varying initi...
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Large deviation theorem for random covariance matrices
We establish a large deviation theorem for the empirical spectral distribution of random covariance matrices whose entries are independent random variables with mean 0, variance 1 and having controlled forth moments. Some new properties of Laguerre polynomials are also given.
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Hindsight policy gradients
A reinforcement learning agent that needs to pursue different goals across episodes requires a goal-conditional policy. In addition to their potential to generalize desirable behavior to unseen goals, such policies may also enable higher-level planning based on subgoals. In sparse-reward environments, the capacity to...
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Abundances in photoionized nebulae of the Local Group and nucleosynthesis of intermediate mass stars
Photoionized nebulae, comprising HII regions and planetary nebulae, are excellent laboratories to investigate the nucleosynthesis and chemical evolution of several elements in the Galaxy and other galaxies of the Local Group. Our purpose in this investigation is threefold: (i) compare the abundances of HII regions an...
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Are Thousands of Samples Really Needed to Generate Robust Gene-List for Prediction of Cancer Outcome?
The prediction of cancer prognosis and metastatic potential immediately after the initial diagnoses is a major challenge in current clinical research. The relevance of such a signature is clear, as it will free many patients from the agony and toxic side-effects associated with the adjuvant chemotherapy automatically...
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Multi-scale analysis of lead-lag relationships in high-frequency financial markets
We propose a novel estimation procedure for scale-by-scale lead-lag relationships of financial assets observed at a high-frequency in a non-synchronous manner. The proposed estimation procedure does not require any interpolation processing of the original data and is applicable to quite fine resolution data. The vali...
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Approximations of the allelic frequency spectrum in general supercritical branching populations
We consider a general branching population where the lifetimes of individuals are i.i.d.\ with arbitrary distribution and where each individual gives birth to new individuals at Poisson times independently from each other. In addition, we suppose that individuals experience mutations at Poissonian rate $\theta$ under...
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Anomaly Detection Using Optimally-Placed Micro-PMU Sensors in Distribution Grids
As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. In this paper, focusing on Micro-Phasor Measurement Unit ($\mu$PMU) data, we propose a hi...
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Electron-Phonon Interaction in Ternary Rare-Earth Copper Antimonides LaCuSb2 and La(Cu0.8Ag0.2)Sb2 probed by Yanson Point-Contact Spectroscopy
Investigation of the electron-phonon interaction (EPI) in LaCuSb2 and La(Cu0.8Ag0.2)Sb2 compounds by Yanson point-contact spectroscopy (PCS) has been carried out. Point-contact spectra display a pronounced broad maximum in the range of 10÷20 mV caused by EPI. Variation of the position of this maximum is likely connec...
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Ultrahigh Magnetic Field Phases in Frustrated Triangular-lattice Magnet CuCrO$_2$
The magnetic phases of a triangular-lattice antiferromagnet, CuCrO$_2$, were investigated in magnetic fields along to the $c$ axis, $H$ // [001], up to 120 T. Faraday rotation and magneto-absorption spectroscopy were used to unveil the rich physics of magnetic phases. An up-up-down (UUD) magnetic structure phase was ...
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Preserving Differential Privacy in Convolutional Deep Belief Networks
The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural networks are built on users' personal and highly sensitive data, e.g., clinical records, user profiles, biomedical images, etc. However, only a few scientific studies on preserving privacy i...
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Injectivity almost everywhere and mappings with finite distortion in nonlinear elasticity
We show that a sufficient condition for the weak limit of a sequence of $W^1_q$-homeomorphisms with finite distortion to be almost everywhere injective for $q \geq n-1$, can be stated by means of composition operators. Applying this result, we study nonlinear elasticity problems with respect to these new classes of m...
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A probabilistic approach to the leader problem in random graphs
Consider the classical Erdos-Renyi random graph process wherein one starts with an empty graph on $n$ vertices at time $t=0$. At each stage, an edge is chosen uniformly at random and placed in the graph. After the original fundamental work in [19], Erdős suggested that one should view the original random graph proces...
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An improvement on LSB+ method
The Least Significant Bit (LSB) substitution is an old and simple data hiding method that could almost effortlessly be implemented in spatial or transform domain over any digital media. This method can be attacked by several steganalysis methods, because it detectably changes statistical and perceptual characteristic...
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Oxygen reduction mechanisms in nanostructured La0.8Sr0.2MnO3 cathodes for Solid Oxide Fuel Cells
In this work we outline the mechanisms contributing to the oxygen reduction reaction in nanostructured cathodes of La0.8Sr0.2MnO3 (LSM) for Solid Oxide Fuel Cells (SOFC). These cathodes, developed from LSM nanostructured tubes, can be used at lower temperatures compared to microstructured ones, and this is a crucial ...
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Learning Interpretable Models with Causal Guarantees
Machine learning has shown much promise in helping improve the quality of medical, legal, and economic decision-making. In these applications, machine learning models must satisfy two important criteria: (i) they must be causal, since the goal is typically to predict individual treatment effects, and (ii) they must b...
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Achromatic super-oscillatory lenses with sub-wavelength focusing
Lenses are crucial to light-enabled technologies. Conventional lenses have been perfected to achieve near-diffraction-limited resolution and minimal chromatic aberrations. However, such lenses are bulky and cannot focus light into a hotspot smaller than half wavelength of light. Pupil filters, initially suggested by ...
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Time-dependent linear-response variational Monte Carlo
We present the extension of variational Monte Carlo (VMC) to the calculation of electronic excitation energies and oscillator strengths using time-dependent linear-response theory. By exploiting the analogy existing between the linear method for wave-function optimisation and the generalised eigenvalue equation of li...
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Wireless Power Transfer for Distributed Estimation in Sensor Networks
This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency based energy harvesting technology. The sensors' observation is locally processed by using an uncode...
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About a non-standard interpolation problem
Using algebraic methods, and motivated by the one variable case, we study a multipoint interpolation problem in the setting of several complex variables. The duality realized by the residue generator associated with an underlying Gorenstein algebra, using the Lagrange interpolation polynomial, plays a key role in the...
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Quantum spin liquid signatures in Kitaev-like frustrated magnets
Motivated by recent experiments on $\alpha$-RuCl$_3$, we investigate a possible quantum spin liquid ground state of the honeycomb-lattice spin model with bond-dependent interactions. We consider the $K-\Gamma$ model, where $K$ and $\Gamma$ represent the Kitaev and symmetric-anisotropic interactions between spin-1/2 m...
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Equivalent electric circuit of magnetosphere-ionosphere-atmosphere interaction
The aim of this study is to investigate the magnetospheric disturbances effects on complicated nonlinear system of atmospheric processes. During substorms and storms, the ionosphere was subjected to rather a significant Joule heating, and the power of precipitating energetic particles was also great. Nevertheless, th...
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Charge polarization effects on the optical response of blue-emitting superlattices
In the new approach to study the optical response of periodic structures, successfully applied to study the optical properties of blue-emitting InGaN/GaN superlattices, the spontaneous charge polarization was neglected. To search the effect of this quantum confined Stark phenomenon we study the optical response, assu...
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Replica analysis of overfitting in regression models for time-to-event data
Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet b...
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System Description: Russell - A Logical Framework for Deductive Systems
Russell is a logical framework for the specification and implementation of deductive systems. It is a high-level language with respect to Metamath language, so inherently it uses a Metamath foundations, i.e. it doesn't rely on any particular formal calculus, but rather is a pure logical framework. The main difference...
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Spinor analysis
"Let us call the novel quantities which, in addition to the vectors and tensors, have appeared in the quantum mechanics of the spinning electron, and which in the case of the Lorentz group are quite differently transformed from tensors, as spinors for short. Is there no spinor analysis that every physicist can learn,...
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Identifiability of phylogenetic parameters from k-mer data under the coalescent
Distances between sequences based on their $k$-mer frequency counts can be used to reconstruct phylogenies without first computing a sequence alignment. Past work has shown that effective use of k-mer methods depends on 1) model-based corrections to distances based on $k$-mers and 2) breaking long sequences into bloc...
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Short-Time Nonlinear Effects in the Exciton-Polariton System
In the exciton-polariton system, a linear dispersive photon field is coupled to a nonlinear exciton field. Short-time analysis of the lossless system shows that, when the photon field is excited, the time required for that field to exhibit nonlinear effects is longer than the time required for the nonlinear Schröding...
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GTC Observations of an Overdense Region of LAEs at z=6.5
We present the results of our search for the faint galaxies near the end of the Reionisation Epoch. This has been done using very deep OSIRIS images obtained at the Gran Telescopio Canarias (GTC). Our observations focus around two close, massive Lyman Alpha Emitters (LAEs) at redshift 6.5, discovered in the SXDS fiel...
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Comment on Photothermal radiometry parametric identifiability theory for reliable and unique nondestructive coating thickness and thermophysical measurements, J. Appl. Phys. 121(9), 095101 (2017)
A recent paper [X. Guo, A. Mandelis, J. Tolev and K. Tang, J. Appl. Phys., 121, 095101 (2017)] intends to demonstrate that from the photothermal radiometry signal obtained on a coated opaque sample in 1D transfer, one should be able to identify separately the following three parameters of the coating: thermal diffusi...
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Computing the projected reachable set of switched affine systems: an application to systems biology
A fundamental question in systems biology is what combinations of mean and variance of the species present in a stochastic biochemical reaction network are attainable by perturbing the system with an external signal. To address this question, we show that the moments evolution in any generic network can be either app...
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Temporal Action Localization by Structured Maximal Sums
We address the problem of temporal action localization in videos. We pose action localization as a structured prediction over arbitrary-length temporal windows, where each window is scored as the sum of frame-wise classification scores. Additionally, our model classifies the start, middle, and end of each action as s...
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Using Transfer Learning for Image-Based Cassava Disease Detection
Cassava is the third largest source of carbohydrates for human food in the world but is vulnerable to virus diseases, which threaten to destabilize food security in sub-Saharan Africa. Novel methods of cassava disease detection are needed to support improved control which will prevent this crisis. Image recognition o...
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Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Ability to continuously learn and adapt from limited experience in nonstationary environments is an important milestone on the path towards general intelligence. In this paper, we cast the problem of continuous adaptation into the learning-to-learn framework. We develop a simple gradient-based meta-learning algorithm...
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Alpha-Divergences in Variational Dropout
We investigate the use of alternative divergences to Kullback-Leibler (KL) in variational inference(VI), based on the Variational Dropout \cite{kingma2015}. Stochastic gradient variational Bayes (SGVB) \cite{aevb} is a general framework for estimating the evidence lower bound (ELBO) in Variational Bayes. In this work...
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Curvature properties of Robinson-Trautman metric
The curvature properties of Robinson-Trautman metric have been investigated. It is shown that Robinson-Trautman metric admits several kinds of pseudosymmetric type structures such as Weyl pseudosymmetric, Ricci pseudosymmetric, pseudosymmetric Weyl conformal curvature tensor etc. Also it is shown that the difference ...
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Dehn invariant of flexible polyhedra
We prove that the Dehn invariant of any flexible polyhedron in Euclidean space of dimension greater than or equal to 3 is constant during the flexion. In dimensions 3 and 4 this implies that any flexible polyhedron remains scissors congruent to itself during the flexion. This proves the Strong Bellows Conjecture pose...
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On Evaluation of Embodied Navigation Agents
Skillful mobile operation in three-dimensional environments is a primary topic of study in Artificial Intelligence. The past two years have seen a surge of creative work on navigation. This creative output has produced a plethora of sometimes incompatible task definitions and evaluation protocols. To coordinate ongoi...
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Single Magnetic Impurity in Tilted Dirac Surface States
We utilize variational method to investigate the Kondo screening of a spin-1/2 magnetic impurity in tilted Dirac surface states with the Dirac cone tilted along the $k_y$-axis. We mainly study about the effect of the tilting term on the binding energy and the spin-spin correlation between magnetic impurity and conduc...
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Leveraging the Path Signature for Skeleton-based Human Action Recognition
Human action recognition in videos is one of the most challenging tasks in computer vision. One important issue is how to design discriminative features for representing spatial context and temporal dynamics. Here, we introduce a path signature feature to encode information from intra-frame and inter-frame contexts. ...
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How Many Subpopulations is Too Many? Exponential Lower Bounds for Inferring Population Histories
Reconstruction of population histories is a central problem in population genetics. Existing coalescent-based methods, like the seminal work of Li and Durbin (Nature, 2011), attempt to solve this problem using sequence data but have no rigorous guarantees. Determining the amount of data needed to correctly reconstruc...
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Source localization in an ocean waveguide using supervised machine learning
Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix (SCM) and used as the input. Three...
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Mining Illegal Insider Trading of Stocks: A Proactive Approach
Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock ...
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Discovery of Extreme [OIII]+H$β$ Emitting Galaxies Tracing an Overdensity at z~3.5 in CDF-South
Using deep multi-wavelength photometry of galaxies from ZFOURGE, we group galaxies at $2.5<z<4.0$ by the shape of their spectral energy distributions (SEDs). We identify a population of galaxies with excess emission in the $K_s$-band, which corresponds to [OIII]+H$\beta$ emission at $2.95<z<3.65$. This population inc...
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Predictive Simulations for Tuning Electronic and Optical Properties of SubPc Derivatives
Boron subphthalocyanine chloride is an electron donor material used in small molecule organic photovoltaics with an unusually large molecular dipole moment. Using first-principles calculations, we investigate enhancing the electronic and optical properties of boron subphthalocyanine chloride, by substituting the boro...
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Learning to attend in a brain-inspired deep neural network
Recent machine learning models have shown that including attention as a component results in improved model accuracy and interpretability, despite the concept of attention in these approaches only loosely approximating the brain's attention mechanism. Here we extend this work by building a more brain-inspired deep ne...
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Anisotropic functional Laplace deconvolution
In the present paper we consider the problem of estimating a three-dimensional function $f$ based on observations from its noisy Laplace convolution. Our study is motivated by the analysis of Dynamic Contrast Enhanced (DCE) imaging data. We construct an adaptive wavelet-Laguerre estimator of $f$, derive minimax lower...
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Prediction of many-electron wavefunctions using atomic potentials
For a given many-electron molecule, it is possible to define a corresponding one-electron Schrödinger equation, using potentials derived from simple atomic densities, whose solution predicts fairly accurate molecular orbitals for single- and multi-determinant wavefunctions for the molecule. The energy is not predicte...
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Free energy of formation of a crystal nucleus in incongruent solidification: Implication for modeling the crystallization of aqueous nitric acid droplets in type 1 polar stratospheric clouds
Using the formalism of the classical nucleation theory, we derive an expression for the reversible work $W_*$ of formation of a binary crystal nucleus in a liquid binary solution of non-stoichiometric composition (incongruent crystallization). Applied to the crystallization of aqueous nitric acid (NA) droplets, the n...
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Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer's Disease
Most machine learning classifiers give predictions for new examples accurately, yet without indicating how trustworthy predictions are. In the medical domain, this hampers their integration in decision support systems, which could be useful in the clinical practice. We use a supervised learning approach that combines...
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Parameter Sharing Deep Deterministic Policy Gradient for Cooperative Multi-agent Reinforcement Learning
Deep reinforcement learning for multi-agent cooperation and competition has been a hot topic recently. This paper focuses on cooperative multi-agent problem based on actor-critic methods under local observations settings. Multi agent deep deterministic policy gradient obtained state of art results for some multi-agen...
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Repair Strategies for Storage on Mobile Clouds
We study the data reliability problem for a community of devices forming a mobile cloud storage system. We consider the application of regenerating codes for file maintenance within a geographically-limited area. Such codes require lower bandwidth to regenerate lost data fragments compared to file replication or reco...
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Mean-variance portfolio selection under partial information with drift uncertainty
This paper studies a mean-variance portfolio selection problem under partial information with drift uncertainty. It is proved that all the contingent claims in this model are attainable in the sense of Xiong and Zhou. Further, we propose a numerical scheme to approximate the optimal portfolio. Malliavin calculus and ...
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Learning from MOM's principles: Le Cam's approach
We obtain estimation error rates for estimators obtained by aggregation of regularized median-of-means tests, following a construction of Le Cam. The results hold with exponentially large probability -- as in the gaussian framework with independent noise- under only weak moments assumptions on data and without assumi...
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On a Neumann-type series for modified Bessel functions of the first kind
In this paper, we are interested in a Neumann-type series for modified Bessel functions of the first kind which arises in the study of Dunkl operators associated with dihedral groups and as an instance of the Laguerre semigroup constructed by Ben Said-Kobayashi-Orsted. We first revisit the particular case correspondi...
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Generalized Log-sine integrals and Bell polynomials
In this paper, we investigate the integral of $x^n\log^m(\sin(x))$ for natural numbers $m$ and $n$. In doing so, we recover some well-known results and remark on some relations to the log-sine integral $\operatorname{Ls}_{n+m+1}^{(n)}(\theta)$. Later, we use properties of Bell polynomials to find a closed expression ...
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A Modern Search for Wolf-Rayet Stars in the Magellanic Clouds. III. A Third Year of Discoveries
For the past three years we have been conducting a survey for WR stars in the Large and Small Magellanic Clouds (LMC, SMC). Our previous work has resulted in the discovery of a new type of WR star in the LMC, which we are calling WN3/O3. These stars have the emission-line properties of a WN3 star (strong N V but no N...
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Mathematical modeling of Zika disease in pregnant women and newborns with microcephaly in Brazil
We propose a new mathematical model for the spread of Zika virus. Special attention is paid to the transmission of microcephaly. Numerical simulations show the accuracy of the model with respect to the Zika outbreak occurred in Brazil.
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A Noninformative Prior on a Space of Distribution Functions
In a given problem, the Bayesian statistical paradigm requires the specification of a prior distribution that quantifies relevant information about the unknowns of main interest external to the data. In cases where little such information is available, the problem under study may possess an invariance under a transfo...
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Towards a realistic NNLIF model: Analysis and numerical solver for excitatory-inhibitory networks with delay and refractory periods
The Network of Noisy Leaky Integrate and Fire (NNLIF) model describes the behavior of a neural network at mesoscopic level. It is one of the simplest self-contained mean-field models considered for that purpose. Even so, to study the mathematical properties of the model some simplifications were necessary Cáceres-Car...
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