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A note on the role of projectivity in likelihood-based inference for random graph models
There is widespread confusion about the role of projectivity in likelihood-based inference for random graph models. The confusion is rooted in claims that projectivity, a form of marginalizability, may be necessary for likelihood-based inference and consistency of maximum likelihood estimators. We show that likelihoo...
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Alternating Double Euler Sums, Hypergeometric Identities and a Theorem of Zagier
In this work, we derive relations between generating functions of double stuffle relations and double shuffle relations to express the alternating double Euler sums $\zeta\left(\overline{r}, s\right)$, $\zeta\left(r, \overline{s}\right)$ and $\zeta\left(\overline{r}, \overline{s}\right)$ with $r+s$ odd in terms of ze...
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Achieving Dilution without Knowledge of Coordinates in the SINR Model
Considerable literature has been developed for various fundamental distributed problems in the SINR (Signal-to-Interference-plus-Noise-Ratio) model for radio transmission. A setting typically studied is when all nodes transmit a signal of the same strength, and each device only has access to knowledge about the total...
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Probing the topology of density matrices
The mixedness of a quantum state is usually seen as an adversary to topological quantization of observables. For example, exact quantization of the charge transported in a so-called Thouless adiabatic pump is lifted at any finite temperature in symmetry-protected topological insulators. Here, we show that certain dir...
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Stable Limit Theorems for Empirical Processes under Conditional Neighborhood Dependence
This paper introduces a new concept of stochastic dependence among many random variables which we call conditional neighborhood dependence (CND). Suppose that there are a set of random variables and a set of sigma algebras where both sets are indexed by the same set endowed with a neighborhood system. When the set of...
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Topological Maxwell Metal Bands in a Superconducting Qutrit
We experimentally explore the topological Maxwell metal bands by mapping the momentum space of condensed-matter models to the tunable parameter space of superconducting quantum circuits. An exotic band structure that is effectively described by the spin-1 Maxwell equations is imaged. Three-fold degenerate points dubb...
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Pressure effect and Superconductivity in $β$-Bi$_4$I$_4$ Topological Insulator
We report a detailed study of the transport coefficients of $\beta$-Bi$_4$I$_4$ quasi-one dimensional topological insulator. Electrical resistivity, thermoelectric power, thermal conductivity and Hall coefficient measurements are consistent with the possible appearance of a charge density wave order at low temperatur...
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Backprop-Q: Generalized Backpropagation for Stochastic Computation Graphs
In real-world scenarios, it is appealing to learn a model carrying out stochastic operations internally, known as stochastic computation graphs (SCGs), rather than learning a deterministic mapping. However, standard backpropagation is not applicable to SCGs. We attempt to address this issue from the angle of cost pro...
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Development of a low-alpha-emitting μ-PIC for NEWAGE direction-sensitive dark-matter search
NEWAGE is a direction-sensitive dark-matter-search experiment that uses a micro-patterned gaseous detector, or {\mu}-PIC, as the readout. The main background sources are {\alpha}-rays from radioactive contaminants in the {\mu}-PIC. We have therefore developed a low-alpha-emitting {\mu}-PICs and measured its performan...
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Online characterization of planetary surfaces: PlanetServer, an open-source analysis and visualization tool
The lack of open-source tools for hyperspectral data visualization and analysiscreates a demand for new tools. In this paper we present the new PlanetServer,a set of tools comprising a web Geographic Information System (GIS) and arecently developed Python Application Programming Interface (API) capableof visualizing ...
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GM-PHD Filter for Searching and Tracking an Unknown Number of Targets with a Mobile Sensor with Limited FOV
We study the problem of searching for and tracking a collection of moving targets using a robot with a limited Field-Of-View (FOV) sensor. The actual number of targets present in the environment is not known a priori. We propose a search and tracking framework based on the concept of Bayesian Random Finite Sets (RFSs...
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Regularity of solutions to scalar conservation laws with a force
We prove regularity estimates for entropy solutions to scalar conservation laws with a force. Based on the kinetic form of a scalar conservation law, a new decomposition of entropy solutions is introduced, by means of a decomposition in the velocity variable, adapted to the non-degeneracy properties of the flux funct...
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Coupled identical localized fermionic chains with quasi-random disorder
We analyze the ground state localization properties of an array of identical interacting spinless fermionic chains with quasi-random disorder, using non-perturbative Renormalization Group methods. In the single or two chains case localization persists while for a larger number of chains a different qualitative behavi...
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Calibrated Filtered Reduced Order Modeling
We propose a calibrated filtered reduced order model (CF-ROM) framework for the numerical simulation of general nonlinear PDEs that are amenable to reduced order modeling. The novel CF-ROM framework consists of two steps: (i) In the first step, we use explicit ROM spatial filtering of the nonlinear PDE to construct a...
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Population of collective modes in light scattering by many atoms
The interaction of light with an atomic sample containing a large number of particles gives rise to many collective (or cooperative) effects, such as multiple scattering, superradiance and subradiance, even if the atomic density is low and the incident optical intensity weak (linear optics regime). Tracing over the d...
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A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware
Technological advancement in Wireless Sensor Networks (WSN) has made it become an invaluable component of a reliable environmental monitoring system; they form the digital skin' through which to 'sense' and collect the context of the surroundings and provides information on the process leading to complex events such ...
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Readings and Misreadings of J. Willard Gibbs Elementary Principles in Statistical Mechanics
J. Willard Gibbs' Elementary Principles in Statistical Mechanics was the definitive work of one of America's greatest physicists. Gibbs' book on statistical mechanics establishes the basic principles and fundamental results that have flowered into the modern field of statistical mechanics. However, at a number of poi...
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Multilingual Adaptation of RNN Based ASR Systems
In this work, we focus on multilingual systems based on recurrent neural networks (RNNs), trained using the Connectionist Temporal Classification (CTC) loss function. Using a multilingual set of acoustic units poses difficulties. To address this issue, we proposed Language Feature Vectors (LFVs) to train language ada...
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SPIDERS: Selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys
SPIDERS (SPectroscopic IDentification of eROSITA Sources) is an SDSS-IV survey running in parallel to the eBOSS cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected AGN and galaxy cluster members detected in wide area eROSITA, XMM-Newton and ROSAT surveys. We describe the me...
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Task-specific Word Identification from Short Texts Using a Convolutional Neural Network
Task-specific word identification aims to choose the task-related words that best describe a short text. Existing approaches require well-defined seed words or lexical dictionaries (e.g., WordNet), which are often unavailable for many applications such as social discrimination detection and fake review detection. How...
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Merlin-Arthur with efficient quantum Merlin and quantum supremacy for the second level of the Fourier hierarchy
We introduce a simple sub-universal quantum computing model, which we call the Hadamard-classical circuit with one-qubit (HC1Q) model. It consists of a classical reversible circuit sandwiched by two layers of Hadamard gates, and therefore it is in the second level of the Fourier hierarchy. We show that output probabi...
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Light sterile neutrinos, dark matter, and new resonances in a $U(1)$ extension of the MSSM
We present $\psi'$MSSM, a model based on a $U(1)_{\psi'}$ extension of the minimal supersymmetric standard model. The gauge symmetry $U(1)_{\psi'}$, also known as $U(1)_N$, is a linear combination of the $U(1)_\chi$ and $U(1)_\psi$ subgroups of $E_6$. The model predicts the existence of three sterile neutrinos with m...
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Accurate halo-galaxy mocks from automatic bias estimation and particle mesh gravity solvers
Reliable extraction of cosmological information from clustering measurements of galaxy surveys requires estimation of the error covariance matrices of observables. The accuracy of covariance matrices is limited by our ability to generate sufficiently large number of independent mock catalogs that can describe the phy...
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Time-Optimal Path Tracking via Reachability Analysis
Given a geometric path, the Time-Optimal Path Tracking problem consists in finding the control strategy to traverse the path time-optimally while regulating tracking errors. A simple yet effective approach to this problem is to decompose the controller into two components: (i)~a path controller, which modulates the p...
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Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians
We consider deep classifying neural networks. We expose a structure in the derivative of the logits with respect to the parameters of the model, which is used to explain the existence of outliers in the spectrum of the Hessian. Previous works decomposed the Hessian into two components, attributing the outliers to one...
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Discrete-Time Statistical Inference for Multiscale Diffusions
We study statistical inference for small-noise-perturbed multiscale dynamical systems under the assumption that we observe a single time series from the slow process only. We construct estimators for both averaging and homogenization regimes, based on an appropriate misspecified model motivated by a second-order stoc...
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Taggle: Scalable Visualization of Tabular Data through Aggregation
Visualization of tabular data---for both presentation and exploration purposes---is a well-researched area. Although effective visual presentations of complex tables are supported by various plotting libraries, creating such tables is a tedious process and requires scripting skills. In contrast, interactive table vis...
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A parity-breaking electronic nematic phase transition in the spin-orbit coupled metal Cd$_2$Re$_2$O$_7$
Strong electron interactions can drive metallic systems toward a variety of well-known symmetry-broken phases, but the instabilities of correlated metals with strong spin-orbit coupling have only recently begun to be explored. We uncovered a multipolar nematic phase of matter in the metallic pyrochlore Cd$_2$Re$_2$O$...
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Sparse bounds for a prototypical singular Radon transform
We use a variant of the technique in [Lac17a] to give sparse L^p(log(L))^4 bounds for a class of model singular and maximal Radon transforms
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Sterile neutrinos in cosmology
Sterile neutrinos are natural extensions to the standard model of particle physics in neutrino mass generation mechanisms. If they are relatively light, less than approximately 10 keV, they can alter cosmology significantly, from the early Universe to the matter and radiation energy density today. Here, we review the...
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A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms
Probabilistic mixture models have been widely used for different machine learning and pattern recognition tasks such as clustering, dimensionality reduction, and classification. In this paper, we focus on trying to solve the most common challenges related to supervised learning algorithms by using mixture probability...
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Kinematics and workspace analysis of a 3ppps parallel robot with u-shaped base
This paper presents the kinematic analysis of the 3-PPPS parallel robot with an equilateral mobile platform and a U-shape base. The proposed design and appropriate selection of parameters allow to formulate simpler direct and inverse kinematics for the manipulator under study. The parallel singularities associated wi...
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Accurate spectroscopic redshift of the multiply lensed quasar PSOJ0147 from the Pan-STARRS survey
Context: The gravitational lensing time delay method provides a one-step determination of the Hubble constant (H0) with an uncertainty level on par with the cosmic distance ladder method. However, to further investigate the nature of the dark energy, a H0 estimate down to 1% level is greatly needed. This requires doz...
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Upper bounds on the smallest size of a saturating set in projective planes and spaces of even dimension
In a projective plane $\Pi_{q}$ (not necessarily Desarguesian) of order $q$, a point subset $\mathcal{S}$ is saturating (or dense) if any point of $\Pi_{q}\setminus \mathcal{S}$ is collinear with two points in $\mathcal{S}$. Modifying an approach of [31], we proved the following upper bound on the smallest size $s(2,...
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A Neural Representation of Sketch Drawings
We present sketch-rnn, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on thousands of crude human-drawn images representing hundreds of classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust trainin...
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Privileged Multi-label Learning
This paper presents privileged multi-label learning (PrML) to explore and exploit the relationship between labels in multi-label learning problems. We suggest that for each individual label, it cannot only be implicitly connected with other labels via the low-rank constraint over label predictors, but also its perfor...
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A Diophantine approximation problem with two primes and one $k$-th power of a prime
We refine a result of the last two Authors of [8] on a Diophantine approximation problem with two primes and a $k$-th power of a prime which was only proved to hold for $1<k<4/3$. We improve the $k$-range to $1<k\le 3$ by combining Harman's technique on the minor arc with a suitable estimate for the $L^4$-norm of the...
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Reexamining Low Rank Matrix Factorization for Trace Norm Regularization
Trace norm regularization is a widely used approach for learning low rank matrices. A standard optimization strategy is based on formulating the problem as one of low rank matrix factorization which, however, leads to a non-convex problem. In practice this approach works well, and it is often computationally faster t...
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Tier structure of strongly endotactic reaction networks
Reaction networks are mainly used to model the time-evolution of molecules of interacting chemical species. Stochastic models are typically used when the counts of the molecules are low, whereas deterministic models are used when the counts are in high abundance. In 2011, the notion of `tiers' was introduced to study...
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Relative FP-injective and FP-flat complexes and their model structures
In this paper, we introduce the notions of ${\rm FP}_n$-injective and ${\rm FP}_n$-flat complexes in terms of complexes of type ${\rm FP}_n$. We show that some characterizations analogous to that of injective, FP-injective and flat complexes exist for ${\rm FP}_n$-injective and ${\rm FP}_n$-flat complexes. We also in...
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An Interactive Tool to Explore and Improve the Ply Number of Drawings
Given a straight-line drawing $\Gamma$ of a graph $G=(V,E)$, for every vertex $v$ the ply disk $D_v$ is defined as a disk centered at $v$ where the radius of the disk is half the length of the longest edge incident to $v$. The ply number of a given drawing is defined as the maximum number of overlapping disks at some...
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Distinguishing the albedo of exoplanets from stellar activity
Light curves show the flux variation from the target star and its orbiting planets as a function of time. In addition to the transit features created by the planets, the flux also includes the reflected light component of each planet, which depends on the planetary albedo. This signal is typically referred to as phas...
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Inverse Reinforcement Learning Under Noisy Observations
We consider the problem of performing inverse reinforcement learning when the trajectory of the expert is not perfectly observed by the learner. Instead, a noisy continuous-time observation of the trajectory is provided to the learner. This problem exhibits wide-ranging applications and the specific application we co...
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Using Perturbed Underdamped Langevin Dynamics to Efficiently Sample from Probability Distributions
In this paper we introduce and analyse Langevin samplers that consist of perturbations of the standard underdamped Langevin dynamics. The perturbed dynamics is such that its invariant measure is the same as that of the unperturbed dynamics. We show that appropriate choices of the perturbations can lead to samplers th...
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Meta learning Framework for Automated Driving
The success of automated driving deployment is highly depending on the ability to develop an efficient and safe driving policy. The problem is well formulated under the framework of optimal control as a cost optimization problem. Model based solutions using traditional planning are efficient, but require the knowledg...
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MOBILITY21: Strategic Investments for Transportation Infrastructure & Technology
America's transportation infrastructure is the backbone of our economy. A strong infrastructure means a strong America - an America that competes globally, supports local and regional economic development, and creates jobs. Strategic investments in our transportation infrastructure are vital to our national security,...
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Hysteretic behaviour of metal connectors for hybrid (high- and low-grade mixed species) cross laminated timber
Cross-laminated timber (CLT) is a prefabricated solid engineered wood product made of at least three orthogonally bonded layers of solid-sawn lumber that are laminated by gluing longitudinal and transverse layers with structural adhesives to form a solid panel. Previous studies have shown that the CLT buildings can p...
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Partial Knowledge In Embeddings
Representing domain knowledge is crucial for any task. There has been a wide range of techniques developed to represent this knowledge, from older logic based approaches to the more recent deep learning based techniques (i.e. embeddings). In this paper, we discuss some of these methods, focusing on the representation...
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Impact of the latest measurement of Hubble constant on constraining inflation models
We investigate how the constraint results of inflation models are affected by considering the latest local measurement of $H_0$ in the global fit. We use the observational data, including the Planck CMB full data, the BICEP2 and Keck Array CMB B-mode data, the BAO data, and the latest measurement of Hubble constant, ...
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Ultra-light and strong: the massless harmonic oscillator and its singular path integral
In classical mechanics, a light particle bound by a strong elastic force just oscillates at high frequency in the region allowed by its initial position and velocity. In quantum mechanics, instead, the ground state of the particle becomes completely de-localized in the limit $m \to 0$. The harmonic oscillator thus ce...
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The Shannon-McMillan-Breiman theorem beyond amenable groups
We introduce a new isomorphism-invariant notion of entropy for measure preserving actions of arbitrary countable groups on probability spaces, which we call cocycle entropy. We develop methods to show that cocycle entropy satisfies many of the properties of classical amenable entropy theory, but applies in much great...
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Assistive robotic device: evaluation of intelligent algorithms
Assistive robotic devices can be used to help people with upper body disabilities gaining more autonomy in their daily life. Although basic motions such as positioning and orienting an assistive robot gripper in space allow performance of many tasks, it might be time consuming and tedious to perform more complex task...
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Solving the Brachistochrone Problem by an Influence Diagram
Influence diagrams are a decision-theoretic extension of probabilistic graphical models. In this paper we show how they can be used to solve the Brachistochrone problem. We present results of numerical experiments on this problem, compare the solution provided by the influence diagram with the optimal solution. The R...
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OH Survey along Sightlines of Galactic Observations of Terahertz C+
We have obtained OH spectra of four transitions in the $^2\Pi_{3/2}$ ground state, at 1612, 1665, 1667, and 1720 MHz, toward 51 sightlines that were observed in the Herschel project Galactic Observations of Terahertz C+. The observations cover the longitude range of (32$^\circ$, 64$^\circ$) and (189$^\circ$, 207$^\ci...
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Strain manipulation of Majorana fermions in graphene armchair nanoribbons
Graphene nanoribbons with armchair edges are studied for externally enhanced, but realistic parameter values: enhanced Rashba spin-orbit coupling due to proximity to a transition metal dichalcogenide like WS$_{2}$, and enhanced Zeeman field due to exchange coupling with a magnetic insulator like EuS under applied mag...
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Relativistic wide-angle galaxy bispectrum on the light-cone
Given the important role that the galaxy bispectrum has recently acquired in cosmology and the scale and precision of forthcoming galaxy clustering observations, it is timely to derive the full expression of the large-scale bispectrum going beyond approximated treatments which neglect integrated terms or higher-order...
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Recent progress in many-body localization
This article is a brief introduction to the rapidly evolving field of many-body localization. Rather than giving an in-depth review of the subject, our aspiration here is simply to introduce the problem and its general context, outlining a few directions where notable progress has been achieved in recent years. We ho...
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Magnetic Field Dependence of Spin Glass Free Energy Barriers
We measure the field dependence of spin glass free energy barriers in a thin amorphous Ge:Mn film through the time dependence of the magnetization. After the correlation length $\xi(t, T)$ has reached the film thickness $\mathcal {L}=155$~\AA~so that the dynamics are activated, we change the initial magnetic field by...
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Topological Structures on DMC spaces
Two channels are said to be equivalent if they are degraded from each other. The space of equivalent channels with input alphabet $X$ and output alphabet $Y$ can be naturally endowed with the quotient of the Euclidean topology by the equivalence relation. A topology on the space of equivalent channels with fixed inpu...
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The spectral element method as an efficient tool for transient simulations of hydraulic systems
This paper presents transient numerical simulations of hydraulic systems in engineering applications using the spectral element method (SEM). Along with a detailed description of the underlying numerical method, it is shown that the SEM yields highly accurate numerical approximations at modest computational costs, wh...
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Re-entrant charge order in overdoped (Bi,Pb)$_{2.12}$Sr$_{1.88}$CuO$_{6+δ}$ outside the pseudogap regime
Charge modulations are considered as a leading competitor of high-temperature superconductivity in the underdoped cuprates, and their relationship to Fermi surface reconstructions and to the pseudogap state is an important subject of current research. Overdoped cuprates, on the other hand, are widely regarded as conv...
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A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms
This paper proposes a new approach to construct high quality space-filling sample designs. First, we propose a novel technique to quantify the space-filling property and optimally trade-off uniformity and randomness in sample designs in arbitrary dimensions. Second, we connect the proposed metric (defined in the spat...
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Detection and Tracking of General Movable Objects in Large 3D Maps
This paper studies the problem of detection and tracking of general objects with long-term dynamics, observed by a mobile robot moving in a large environment. A key problem is that due to the environment scale, it can only observe a subset of the objects at any given time. Since some time passes between observations ...
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Mapping the aberrations of a wide-field spectrograph using a photonic comb
We demonstrate a new approach to calibrating the spectral-spatial response of a wide-field spectrograph using a fibre etalon comb. Conventional wide-field instruments employed on front-line telescopes are mapped with a grid of diffraction-limited holes cut into a focal plane mask. The aberrated grid pattern in the im...
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On The Asymptotic Efficiency of Selection Procedures for Independent Gaussian Populations
The field of discrete event simulation and optimization techniques motivates researchers to adjust classic ranking and selection (R&S) procedures to the settings where the number of populations is large. We use insights from extreme value theory in order to reveal the asymptotic properties of R&S procedures. Namely, ...
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DSOD: Learning Deeply Supervised Object Detectors from Scratch
We present Deeply Supervised Object Detector (DSOD), a framework that can learn object detectors from scratch. State-of-the-art object objectors rely heavily on the off-the-shelf networks pre-trained on large-scale classification datasets like ImageNet, which incurs learning bias due to the difference on both the los...
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Data Capture & Analysis to Assess Impact of Carbon Credit Schemes
Data enables Non-Governmental Organisations (NGOs) to quantify the impact of their initiatives to themselves and to others. The increasing amount of data stored today can be seen as a direct consequence of the falling costs in obtaining it. Cheap data acquisition harnesses existing communications networks to collect ...
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Conducting Simulations in Causal Inference with Networks-Based Structural Equation Models
The past decade has seen an increasing body of literature devoted to the estimation of causal effects in network-dependent data. However, the validity of many classical statistical methods in such data is often questioned. There is an emerging need for objective and practical ways to assess which causal methodologies...
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Finite Semihypergroups Built From Groups
Necessary and sufficient conditions for finite semihypergroups to be built from groups of the same order are established
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Auslander Modules
In this paper, we introduce the notion of Auslander modules, inspired from Auslander's zero-divisor conjecture (theorem) and give some interesting results for these modules. We also investigate torsion-free modules.
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Verifying Security Protocols using Dynamic Strategies
Current formal approaches have been successfully used to find design flaws in many security protocols. However, it is still challenging to automatically analyze protocols due to their large or infinite state spaces. In this paper, we propose a novel framework that can automatically verifying security protocols withou...
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Distribution uniformity of laser-accelerated proton beams
Compared with conventional accelerators, laser plasma accelerators can generate high energy ions at a greatly reduced scale, due to their TV/m acceleration gradient. A compact laser plasma accelerator (CLAPA) has been built at the Institute of Heavy Ion Physics at Peking University. It will be used for applied resear...
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Learning to Detect Human-Object Interactions
We study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among th...
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Data clustering with edge domination in complex networks
This paper presents a model for a dynamical system where particles dominate edges in a complex network. The proposed dynamical system is then extended to an application on the problem of community detection and data clustering. In the case of the data clustering problem, 6 different techniques were simulated on 10 di...
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sWSI: A Low-cost and Commercial-quality Whole Slide Imaging System on Android and iOS Smartphones
In this paper, scalable Whole Slide Imaging (sWSI), a novel high-throughput, cost-effective and robust whole slide imaging system on both Android and iOS platforms is introduced and analyzed. With sWSI, most mainstream smartphone connected to a optical eyepiece of any manually controlled microscope can be automatical...
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Predicting multicellular function through multi-layer tissue networks
Motivation: Understanding functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Results: Here we present OhmNet, a hierarchy-aware unsupervised node feature ...
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Toward Microphononic Circuits on Chip: An Evaluation of Components based on High-Contrast Evanescent Confinement of Acoustic Waves
We investigate the prospects for micron-scale acoustic wave components and circuits on chip in solid planar structures that do not require suspension. We leverage evanescent guiding of acoustic waves by high slowness contrast materials readily available in silicon complementary metal-oxide semiconductor (CMOS) proces...
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Adaptive Submodular Influence Maximization with Myopic Feedback
This paper examines the problem of adaptive influence maximization in social networks. As adaptive decision making is a time-critical task, a realistic feedback model has been considered, called myopic. In this direction, we propose the myopic adaptive greedy policy that is guaranteed to provide a (1 - 1/e)-approxima...
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Evaluation of Direct Haptic 4D Volume Rendering of Partially Segmented Data for Liver Puncture Simulation
This work presents an evaluation study using a force feedback evaluation framework for a novel direct needle force volume rendering concept in the context of liver puncture simulation. PTC/PTCD puncture interventions targeting the bile ducts have been selected to illustrate this concept. The haptic algorithms of the ...
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The Role of Big Data on Smart Grid Transition
Despite being popularly referred to as the ultimate solution for all problems of our current electric power system, smart grid is still a growing and unstable concept. It is usually considered as a set of advanced features powered by promising technological solutions. In this paper, we describe smart grid as a socio-...
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Learning Deep ResNet Blocks Sequentially using Boosting Theory
Deep neural networks are known to be difficult to train due to the instability of back-propagation. A deep \emph{residual network} (ResNet) with identity loops remedies this by stabilizing gradient computations. We prove a boosting theory for the ResNet architecture. We construct $T$ weak module classifiers, each con...
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Total energy of radial mappings
The main aim of this paper is to extend one of the main results of Iwaniec and Onninen (Arch. Ration. Mech. Anal., 194: 927-986, 2009). We prove that, the so called total energy functional defined on the class of radial streachings between annuli attains its minimum on a total energy diffeomorphism between annuli. Th...
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Divergence and Sufficiency for Convex Optimization
Logarithmic score and information divergence appear in information theory, statistics, statistical mechanics, and portfolio theory. We demonstrate that all these topics involve some kind of optimization that leads directly to regret functions and such regret functions are often given by a Bregman divergence. If the r...
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Compact linear programs for 2SAT
For each integer $n$ we present an explicit formulation of a compact linear program, with $O(n^3)$ variables and constraints, which determines the satisfiability of any 2SAT formula with $n$ boolean variables by a single linear optimization. This contrasts with the fact that the natural polytope for this problem, for...
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Distributed Protocols at the Rescue for Trustworthy Online Voting
While online services emerge in all areas of life, the voting procedure in many democracies remains paper-based as the security of current online voting technology is highly disputed. We address the issue of trustworthy online voting protocols and recall therefore their security concepts with its trust assumptions. I...
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Isomonodromy aspects of the tt* equations of Cecotti and Vafa III. Iwasawa factorization and asymptotics
This paper, the third in a series, completes our description of all (radial) solutions on C* of the tt*-Toda equations, using a combination of methods from p.d.e., isomonodromic deformations (Riemann-Hilbert method), and loop groups. We place these global solutions into the broader context of solutions which are smoo...
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Decorative Plasmonic Surfaces
Low-profile patterned plasmonic surfaces are synergized with a broad class of silicon microstructures to greatly enhance near-field nanoscale imaging, sensing, and energy harvesting coupled with far-field free-space detection. This concept has a clear impact on several key areas of interest for the MEMS community, in...
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Hamiltonian approach to slip-stacking dynamics
Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stack...
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Materials processing with intense pulsed ion beams and masked targets
Intense, pulsed ion beams locally heat materials and deliver dense electronic excitations that can induce materials modifications and phase transitions. Materials properties can potentially be stabilized by rapid quenching. Pulsed ion beams with (sub-) ns pulse lengths have recently become available for materials pro...
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Distributions of Historic Market Data -- Implied and Realized Volatility
We undertake a systematic comparison between implied volatility, as represented by VIX (new methodology) and VXO (old methodology), and realized volatility. We compare visually and statistically distributions of realized and implied variance (volatility squared) and study the distribution of their ratio. We find that...
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Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
We propose a novel method to directly learn a stochastic transition operator whose repeated application provides generated samples. Traditional undirected graphical models approach this problem indirectly by learning a Markov chain model whose stationary distribution obeys detailed balance with respect to a parameter...
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Toward a language-theoretic foundation for planning and filtering
We address problems underlying the algorithmic question of automating the co-design of robot hardware in tandem with its apposite software. Specifically, we consider the impact that degradations of a robot's sensor and actuation suites may have on the ability of that robot to complete its tasks. We introduce a new fo...
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Algebraic relations between solutions of Painlevé equations
We calculate model theoretic ranks of Painlevé equations in this article, showing in particular, that any equation in any of the Painlevé families has Morley rank one, extending results of Nagloo and Pillay (2011). We show that the type of the generic solution of any equation in the second Painlevé family is geometri...
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Pore lifetimes in cell electroporation: Complex dark pores?
We review some of the basic concepts and the possible pore structures associated with electroporation (EP) for times after electrical pulsing. We purposefully give only a short description of pore creation and subsequent evolution of pore populations, as these are adequately discussed in both reviews and original res...
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Data-driven causal path discovery without prior knowledge - a benchmark study
Causal discovery broadens the inference possibilities, as correlation does not inform about the relationship direction. The common approaches were proposed for cases in which prior knowledge is desired, when the impact of a treatment/intervention variable is discovered or to analyze time-related dependencies. In some...
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Computation of Ground States of the Gross-Pitaevskii Functional via Riemannian Optimization
In this paper we combine concepts from Riemannian Optimization and the theory of Sobolev gradients to derive a new conjugate gradient method for direct minimization of the Gross-Pitaevskii energy functional with rotation. The conservation of the number of particles constrains the minimizers to lie on a manifold corre...
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On the symplectic size of convex polytopes
In this paper we introduce a combinatorial formula for the Ekeland-Hofer-Zehnder capacity of a convex polytope in $\mathbb{R}^{2n}$. One application of this formula is a certain subadditivity property of this capacity.
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A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement
This paper will describe a novel approach to the cocktail party problem that relies on a fully convolutional neural network (FCN) architecture. The FCN takes noisy audio data as input and performs nonlinear, filtering operations to produce clean audio data of the target speech at the output. Our method learns a model...
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Tunnelling Spectroscopy of Andreev States in Graphene
A normal conductor placed in good contact with a superconductor can inherit its remarkable electronic properties. This proximity effect microscopically originates from the formation in the conductor of entangled electron-hole states, called Andreev states. Spectroscopic studies of Andreev states have been performed i...
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Volatility estimation for stochastic PDEs using high-frequency observations
We study the parameter estimation for parabolic, linear, second order, stochastic partial differential equations (SPDEs) observing a mild solution on a discrete grid in time and space. A high-frequency regime is considered where the mesh of the grid in the time variable goes to zero. Focusing on volatility estimation...
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