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A general method to describe intersystem crossing dynamics in trajectory surface hopping
Intersystem crossing is a radiationless process that can take place in a molecule irradiated by UV-Vis light, thereby playing an important role in many environmental, biological and technological processes. This paper reviews different methods to describe intersystem crossing dynamics, paying attention to semiclassic...
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Generating Synthetic Data for Real World Detection of DoS Attacks in the IoT
Denial of service attacks are especially pertinent to the internet of things as devices have less computing power, memory and security mechanisms to defend against them. The task of mitigating these attacks must therefore be redirected from the device onto a network monitor. Network intrusion detection systems can be...
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A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments
This paper reports on a data-driven, interaction-aware motion prediction approach for pedestrians in environments cluttered with static obstacles. When navigating in such workspaces shared with humans, robots need accurate motion predictions of the surrounding pedestrians. Human navigation behavior is mostly influenc...
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Performance study of SKIROC2 and SKIROC2A with BGA testboard
SKIROC2 is an ASIC to readout the silicon pad detectors for the electromagnetic calorimeter in the International Linear Collider. Characteristics of SKIROC2 and the new version of SKIROC2A, packaged with BGA, are measured with testboards and charge injection. The results on the signal-to-noise ratio of both trigger a...
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Priority effects between annual and perennial plants
Dominance by annual plants has traditionally been considered a brief early stage of ecological succession preceding inevitable dominance by competitive perennials. A more recent, alternative view suggests that interactions between annuals and perennials can result in priority effects, causing annual dominance to pers...
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Joining and decomposing reaction networks
In systems and synthetic biology, much research has focused on the behavior and design of single pathways, while, more recently, experimental efforts have focused on how cross-talk (coupling two or more pathways) or inhibiting molecular function (isolating one part of the pathway) affects systems-level behavior. Howe...
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Evidence for structural damping in a high-stress silicon nitride nanobeam and its implications for quantum optomechanics
We resolve the thermal motion of a high-stress silicon nitride nanobeam at frequencies far below its fundamental flexural resonance (3.4 MHz) using cavity-enhanced optical interferometry. Over two decades, the displacement spectrum is well-modeled by that of a damped harmonic oscillator driven by a $1/f$ thermal forc...
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Efficient, sparse representation of manifold distance matrices for classical scaling
Geodesic distance matrices can reveal shape properties that are largely invariant to non-rigid deformations, and thus are often used to analyze and represent 3-D shapes. However, these matrices grow quadratically with the number of points. Thus for large point sets it is common to use a low-rank approximation to the ...
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A First Principle Study on Iron Substituted LiNi(BO3) to use as Cathode Material for Li-ion Batteries
In this work, the structural stability and the electronic properties of LiNiBO 3 and LiFe x Ni (1-x) BO 3 are studied using first principle calculations based on density functional theory. The calculated structural parameters are in good agreement with the available theoretical data. The most stable phases of the Fe ...
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Noncommutative Knörrer type equivalences via noncommutative resolutions of singularities
We construct Knörrer type equivalences outside of the hypersurface case, namely, between singularity categories of cyclic quotient surface singularities and certain finite dimensional local algebras. This generalises Knörrer's equivalence for singularities of Dynkin type A (between Krull dimensions $2$ and $0$) and y...
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Torsion and K-theory for some free wreath products
We classify torsion actions of free wreath products of arbitrary compact quantum groups and use this to prove that if $\mathbb{G}$ is a torsion-free compact quantum group satisfying the strong Baum-Connes property, then $\mathbb{G}\wr_{\ast}S_{N}^{+}$ also satisfies the strong Baum-Connes property. We then compute th...
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High Dimensional Inference in Partially Linear Models
We propose two semiparametric versions of the debiased Lasso procedure for the model $Y_i = X_i\beta_0 + g_0(Z_i) + \epsilon_i$, where $\beta_0$ is high dimensional but sparse (exactly or approximately). Both versions are shown to have the same asymptotic normal distribution and do not require the minimal signal cond...
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The Impact of Small-Cell Bandwidth Requirements on Strategic Operators
Small-cell deployment in licensed and unlicensed spectrum is considered to be one of the key approaches to cope with the ongoing wireless data demand explosion. Compared to traditional cellular base stations with large transmission power, small-cells typically have relatively low transmission power, which makes them ...
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Optimisation approach for the Monge-Ampere equation
This paper studies the numerical approximation of solution of the Dirichlet problem for the fully nonlinear Monge-Ampere equation. In this approach, we take the advantage of reformulation the Monge-Ampere problem as an optimization problem, to which we associate a well defined functional whose minimum provides us wit...
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Coupling parallel adaptive mesh refinement with a nonoverlapping domain decomposition solver
We study the effect of adaptive mesh refinement on a parallel domain decomposition solver of a linear system of algebraic equations. These concepts need to be combined within a parallel adaptive finite element software. A prototype implementation is presented for this purpose. It uses adaptive mesh refinement with on...
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The Pragmatics of Indirect Commands in Collaborative Discourse
Today's artificial assistants are typically prompted to perform tasks through direct, imperative commands such as \emph{Set a timer} or \emph{Pick up the box}. However, to progress toward more natural exchanges between humans and these assistants, it is important to understand the way non-imperative utterances can in...
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The Dawn of the Post-Naturalness Era
In an imaginary conversation with Guido Altarelli, I express my views on the status of particle physics beyond the Standard Model and its future prospects.
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An effective likelihood-free approximate computing method with statistical inferential guarantees
Approximate Bayesian computing is a powerful likelihood-free method that has grown increasingly popular since early applications in population genetics. However, complications arise in the theoretical justification for Bayesian inference conducted from this method with a non-sufficient summary statistic. In this pape...
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The word and conjugacy problems in lacunary hyperbolic groups
We study the word and conjugacy problems in lacunary hyperbolic groups (briefly, LHG). In particular, we describe a necessary and sufficient condition for decidability of the word problem in LHG. Then, based on the graded small-cancellation theory of Olshanskii, we develop a general framework which allows us to const...
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Prediction of ultra-narrow Higgs resonance in magnon Bose-condensates
Higgs resonance modes in condensed matter systems are generally broad; meaning large decay widths or short relaxation times. This common feature has obscured and limited their observation to a select few systems. Contrary to this, the present work predicts that Higgs resonances in magnetic field induced, three-dimens...
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Better Text Understanding Through Image-To-Text Transfer
Generic text embeddings are successfully used in a variety of tasks. However, they are often learnt by capturing the co-occurrence structure from pure text corpora, resulting in limitations of their ability to generalize. In this paper, we explore models that incorporate visual information into the text representatio...
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Two-sample instrumental variable analyses using heterogeneous samples
Instrumental variable analysis is a widely used method to estimate causal effects in the presence of unmeasured confounding. When the instruments, exposure and outcome are not measured in the same sample, Angrist and Krueger (1992) suggested to use two-sample instrumental variable (TSIV) estimators that use sample mo...
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Combinatorial models for Schubert polynomials
Schubert polynomials are a basis for the polynomial ring that represent Schubert classes for the flag manifold. In this paper, we introduce and develop several new combinatorial models for Schubert polynomials that relate them to other known bases including key polynomials and fundamental slide polynomials. We unify ...
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Phase-tunable Josephson thermal router
Since the the first studies of thermodynamics, heat transport has been a crucial element for the understanding of any thermal system. Quantum mechanics has introduced new appealing ingredients for the manipulation of heat currents, such as the long-range coherence of the superconducting condensate. The latter has bee...
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Topology Analysis of International Networks Based on Debates in the United Nations
In complex, high dimensional and unstructured data it is often difficult to extract meaningful patterns. This is especially the case when dealing with textual data. Recent studies in machine learning, information theory and network science have developed several novel instruments to extract the semantics of unstructu...
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Solving the incompressible surface Navier-Stokes equation by surface finite elements
We consider a numerical approach for the incompressible surface Navier-Stokes equation on surfaces with arbitrary genus $g(\mathcal{S})$. The approach is based on a reformulation of the equation in Cartesian coordinates of the embedding $\mathbb{R}^3$, penalization of the normal component, a Chorin projection method ...
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Exploring a potential energy surface by machine learning for characterizing atomic transport
We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for the atomic transport. The proposed method generates numerous random samples of the entire potential energy surface (PES) from a probabilistic Gaussian process...
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Products of random walks on finite groups with moderate growth
In this article, we consider products of random walks on finite groups with moderate growth and discuss their cutoffs in the total variation. Based on several comparison techniques, we are able to identify the total variation cutoff of discrete time lazy random walks with the Hellinger distance cutoff of continuous t...
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A Theoretical Analysis of Sparse Recovery Stability of Dantzig Selector and LASSO
Dantzig selector (DS) and LASSO problems have attracted plenty of attention in statistical learning, sparse data recovery and mathematical optimization. In this paper, we provide a theoretical analysis of the sparse recovery stability of these optimization problems in more general settings and from a new perspective....
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Input Perturbations for Adaptive Regulation and Learning
Design of adaptive algorithms for simultaneous regulation and estimation of MIMO linear dynamical systems is a canonical reinforcement learning problem. Efficient policies whose regret (i.e. increase in the cost due to uncertainty) scales at a square-root rate of time have been studied extensively in the recent liter...
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Nearly circular domains which are integrable close to the boundary are ellipses
The Birkhoff conjecture says that the boundary of a strictly convex integrable billiard table is necessarily an ellipse. In this article, we consider a stronger notion of integrability, namely integrability close to the boundary, and prove a local version of this conjecture: a small perturbation of an ellipse of smal...
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Empirical study on social groups in pedestrian evacuation dynamics
Pedestrian crowds often include social groups, i.e. pedestrians that walk together because of social relationships. They show characteristic configurations and influence the dynamics of the entire crowd. In order to investigate the impact of social groups on evacuations we performed an empirical study with pupils. Se...
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Capacity of the Aperture-Constrained AWGN Free-Space Communication Channel
In this paper, we derive upper and lower bounds as well as a simple closed-form approximation for the capacity of the continuous-time, bandlimited, additive white Gaussian noise channel in a three-dimensional free-space electromagnetic propagation environment subject to constraints on the total effective antenna aper...
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Quasiparticle entropy in superconductor/normal metal/superconductor proximity junctions in the diffusive limit
We discuss the quasiparticle entropy and heat capacity of a dirty superconductor-normal metal-superconductor junction. In the case of short junctions, the inverse proximity effect extending in the superconducting banks plays a crucial role in determining the thermodynamic quantities. In this case, commonly used appro...
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A Kepler Study of Starspot Lifetimes with Respect to Light Curve Amplitude and Spectral Type
Wide-field high precision photometric surveys such as Kepler have produced reams of data suitable for investigating stellar magnetic activity of cooler stars. Starspot activity produces quasi-sinusoidal light curves whose phase and amplitude vary as active regions grow and decay over time. Here we investigate, firstl...
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Plasmon-Driven Acceleration in a Photo-Excited Nanotube
A plasmon-assisted channeling acceleration can be realized with a large channel, possibly at the nanometer scale. Carbon nanotubes (CNTs) are the most typical example of nano-channels that can confine a large number of channeled particles in a photon-plasmon coupling condition. This paper presents a theoretical and n...
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Towards Evaluating Size Reduction Techniques for Software Model Checking
Formal verification techniques are widely used for detecting design flaws in software systems. Formal verification can be done by transforming an already implemented source code to a formal model and attempting to prove certain properties of the model (e.g. that no erroneous state can occur during execution). Unfortu...
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Quantum-continuum simulation of underpotential deposition at electrified metal-solution interfaces
The underpotential deposition of transition metal ions is a critical step in many electrosynthetic approaches. While underpotential deposition has been intensively studied at the atomic level, first-principles calculations in vacuum can strongly underestimate the stability of underpotentially deposited metals. It has...
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Neural Expectation Maximization
Many real world tasks such as reasoning and physical interaction require identification and manipulation of conceptual entities. A first step towards solving these tasks is the automated discovery of distributed symbol-like representations. In this paper, we explicitly formalize this problem as inference in a spatial...
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Gold Standard Online Debates Summaries and First Experiments Towards Automatic Summarization of Online Debate Data
Usage of online textual media is steadily increasing. Daily, more and more news stories, blog posts and scientific articles are added to the online volumes. These are all freely accessible and have been employed extensively in multiple research areas, e.g. automatic text summarization, information retrieval, informat...
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Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
We show that Entropy-SGD (Chaudhari et al., 2017), when viewed as a learning algorithm, optimizes a PAC-Bayes bound on the risk of a Gibbs (posterior) classifier, i.e., a randomized classifier obtained by a risk-sensitive perturbation of the weights of a learned classifier. Entropy-SGD works by optimizing the bound's...
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DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems. Despite great progress, existing methods seem to have a strong bias towards low- or high-order interactions, or require expertise feature engineering. In this paper, we show that it is possible to ...
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How a small quantum bath can thermalize long localized chains
We investigate the stability of the many-body localized (MBL) phase for a system in contact with a single ergodic grain, modelling a Griffiths region with low disorder. Our numerical analysis provides evidence that even a small ergodic grain consisting of only 3 qubits can delocalize a localized chain, as soon as the...
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Transfer Learning for Brain-Computer Interfaces: An Euclidean Space Data Alignment Approach
Almost all EEG-based brain-computer interfaces (BCIs) need some labeled subject-specific data to calibrate a new subject, as neural responses are different across subjects to even the same stimulus. So, a major challenge in developing high-performance and user-friendly BCIs is to cope with such individual differences...
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Linear and bilinear restriction to certain rotationally symmetric hypersurfaces
Conditional on Fourier restriction estimates for elliptic hypersurfaces, we prove optimal restriction estimates for polynomial hypersurfaces of revolution for which the defining polynomial has non-negative coefficients. In particular, we obtain uniform--depending only on the dimension and polynomial degree--estimates...
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Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction
When a measurement falls outside the quantization or measurable range, it becomes saturated and cannot be used in classical reconstruction methods. For example, in C-arm angiography systems, which provide projection radiography, fluoroscopy, digital subtraction angiography, and are widely used for medical diagnoses a...
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Stochastic Gradient Descent on Highly-Parallel Architectures
There is an increased interest in building data analytics frameworks with advanced algebraic capabilities both in industry and academia. Many of these frameworks, e.g., TensorFlow and BIDMach, implement their compute-intensive primitives in two flavors---as multi-thread routines for multi-core CPUs and as highly-para...
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Mixed Precision Training
Deep neural networks have enabled progress in a wide variety of applications. Growing the size of the neural network typically results in improved accuracy. As model sizes grow, the memory and compute requirements for training these models also increases. We introduce a technique to train deep neural networks using h...
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An elementary representation of the higher-order Jacobi-type differential equation
We investigate the differential equation for the Jacobi-type polynomials which are orthogonal on the interval $[-1,1]$ with respect to the classical Jacobi measure and an additional point mass at one endpoint. This scale of higher-order equations was introduced by J. and R. Koekoek in 1999 essentially by using specia...
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Theory of $L$-edge spectroscopy of strongly correlated systems
X-ray absorption spectroscopy measured at the $L$-edge of transition metals (TMs) is a powerful element-selective tool providing direct information about the correlation effects in the $3d$ states. The theoretical modeling of the $2p\rightarrow3d$ excitation processes remains to be challenging for contemporary \texti...
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Pseudo-spin Skyrmions in the Phase Diagram of Cuprate Superconductors
Topological states of matter are at the root of some of the most fascinating phenomena in condensed matter physics. Here we argue that skyrmions in the pseudo-spin space related to an emerging SU(2) symmetry enlighten many mysterious properties of the pseudogap phase in under-doped cuprates. We detail the role of the...
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Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method
We consider large scale empirical risk minimization (ERM) problems, where both the problem dimension and variable size is large. In these cases, most second order methods are infeasible due to the high cost in both computing the Hessian over all samples and computing its inverse in high dimensions. In this paper, we ...
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Large covers and sharp resonances of hyperbolic surfaces
Let $\Gamma$ be a convex co-compact discrete group of isometries of the hyperbolic plane $\mathbb{H}^2$, and $X=\Gamma\backslash \mathbb{H}^2$ the associated surface. In this paper we investigate the behaviour of resonances of the Laplacian for large degree covers of $X$ given by a finite index normal subgroup of $\G...
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Computational Models of Tutor Feedback in Language Acquisition
This paper investigates the role of tutor feedback in language learning using computational models. We compare two dominant paradigms in language learning: interactive learning and cross-situational learning - which differ primarily in the role of social feedback such as gaze or pointing. We analyze the relationship ...
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Non-Saturated Throughput Analysis of Coexistence of Wi-Fi and Cellular With Listen-Before-Talk in Unlicensed Spectrum
This paper analyzes the coexistence performance of Wi-Fi and cellular networks conditioned on non-saturated traffic in the unlicensed spectrum. Under the condition, the time-domain behavior of a cellular small-cell base station (SCBS) with a listen-before-talk (LBT) procedure is modeled as a Markov chain, and it is c...
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A Dynamic Model for Traffic Flow Prediction Using Improved DRN
Real-time traffic flow prediction can not only provide travelers with reliable traffic information so that it can save people's time, but also assist the traffic management agency to manage traffic system. It can greatly improve the efficiency of the transportation system. Traditional traffic flow prediction approach...
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Think globally, fit locally under the Manifold Setup: Asymptotic Analysis of Locally Linear Embedding
Since its introduction in 2000, the locally linear embedding (LLE) has been widely applied in data science. We provide an asymptotical analysis of the LLE under the manifold setup. We show that for the general manifold, asymptotically we may not obtain the Laplace-Beltrami operator, and the result may depend on the n...
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Relative energetics of acetyl-histidine protomers with and without Zn2+ and a benchmark of energy methods
We studied acetylhistidine (AcH), bare or microsolvated with a zinc cation by simulations in isolation. First, a global search for minima of the potential energy surface combining both, empirical and first-principles methods, is performed individually for either one of five possible protonation states. Comparing the ...
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"Space is blue and birds fly through it"
Quantum mechanics is not about 'quantum states': it is about values of physical variables. I give a short fresh presentation and update on the $relational$ perspective on the theory, and a comment on its philosophical implications.
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On the Geometry of Nash and Correlated Equilibria with Cumulative Prospect Theoretic Preferences
It is known that the set of all correlated equilibria of an n-player non-cooperative game is a convex polytope and includes all the Nash equilibria. Further, the Nash equilibria all lie on the boundary of this polytope. We study the geometry of both these equilibrium notions when the players have cumulative prospect ...
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Multipoint Radiation Induced Ignition of Dust Explosions: Turbulent Clustering of Particles and Increased Transparency
It is known that unconfined dust explosions consist of a relatively weak primary (turbulent) deflagrations followed by a devastating secondary explosion. The secondary explosion may propagate with a speed of up to 1000 m/s producing overpressures of over 8-10 atm. Since detonation is the only established theory that ...
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Modeling of the Latent Embedding of Music using Deep Neural Network
While both the data volume and heterogeneity of the digital music content is huge, it has become increasingly important and convenient to build a recommendation or search system to facilitate surfacing these content to the user or consumer community. Most of the recommendation models fall into two primary species, co...
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Intense keV isolated attosecond pulse generation by orthogonally polarized multicycle midinfrared two-color laser field
We theoretically investigate the generation of intense keV attosecond pulses in an orthogonally polarized multicycle midinfrared two-color laser field. It is demonstrated that multiple continuum-like humps, which have a spectral width of about twenty orders of harmonics and an intensity of about one order higher than...
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Games with Costs and Delays
We demonstrate the usefulness of adding delay to infinite games with quantitative winning conditions. In a delay game, one of the players may delay her moves to obtain a lookahead on her opponent's moves. We show that determining the winner of delay games with winning conditions given by parity automata with costs is...
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Compile-Time Extensions to Hybrid ODEs
Reachability analysis for hybrid systems is an active area of development and has resulted in many promising prototype tools. Most of these tools allow users to express hybrid system as automata with a set of ordinary differential equations (ODEs) associated with each state, as well as rules for transitions between s...
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Sorted Concave Penalized Regression
The Lasso is biased. Concave penalized least squares estimation (PLSE) takes advantage of signal strength to reduce this bias, leading to sharper error bounds in prediction, coefficient estimation and variable selection. For prediction and estimation, the bias of the Lasso can be also reduced by taking a smaller pena...
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A New Fully Polynomial Time Approximation Scheme for the Interval Subset Sum Problem
The interval subset sum problem (ISSP) is a generalization of the well-known subset sum problem. Given a set of intervals $\left\{[a_{i,1},a_{i,2}]\right\}_{i=1}^n$ and a target integer $T,$ the ISSP is to find a set of integers, at most one from each interval, such that their sum best approximates the target $T$ but...
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Data Dependent Kernel Approximation using Pseudo Random Fourier Features
Kernel methods are powerful and flexible approach to solve many problems in machine learning. Due to the pairwise evaluations in kernel methods, the complexity of kernel computation grows as the data size increases; thus the applicability of kernel methods is limited for large scale datasets. Random Fourier Features ...
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Estimating Historical Hourly Traffic Volumes via Machine Learning and Vehicle Probe Data: A Maryland Case Study
This paper focuses on the problem of estimating historical traffic volumes between sparsely-located traffic sensors, which transportation agencies need to accurately compute statewide performance measures. To this end, the paper examines applications of vehicle probe data, automatic traffic recorder counts, and neura...
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Monitoring of Wild Pseudomonas Biofilm Strain Conditions Using Statistical Characterisation of Scanning Electron Microscopy Images
The present paper proposes a novel method of quantification of the variation in biofilm architecture, in correlation with the alteration of growth conditions that include, variations of substrate and conditioning layer. The polymeric biomaterial serving as substrates are widely used in implants and indwelling medical...
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Continuous Measurement of an Atomic Current
We are interested in dynamics of quantum many-body systems under continuous observation, and its physical realizations involving cold atoms in lattices. In the present work we focus on continuous measurement of atomic currents in lattice models, including the Hubbard model. We describe a Cavity QED setup, where measu...
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Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros
In finance, durations between successive transactions are usually modeled by the autoregressive conditional duration model based on a continuous distribution omitting frequent zero values. Zero durations can be caused by either split transactions or independent transactions. We propose a discrete model allowing for e...
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Analog Experiments on Tensile Strength of Dusty and Cometary Matter
The tensile strength of small dusty bodies in the solar system is determined by the interaction between the composing grains. In the transition regime between small and sticky dust ($\rm \mu m$) and non cohesive large grains (mm), particles still stick to each other but are easily separated. In laboratory experiments...
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On Compiling DNNFs without Determinism
State-of-the-art knowledge compilers generate deterministic subsets of DNNF, which have been recently shown to be exponentially less succinct than DNNF. In this paper, we propose a new method to compile DNNFs without enforcing determinism necessarily. Our approach is based on compiling deterministic DNNFs with the ad...
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Algebraic infinite delooping and derived destabilization
Working over the prime field of characteristic two, consequences of the Koszul duality between the Steenrod algebra and the big Dyer-Lashof algebra are studied, with an emphasis on the interplay between instability for the Steenrod algebra action and that for the Dyer-Lashof operations. The central algebraic framewor...
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WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling
To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid autoencoding inference (WHAI) for deep latent Dirichlet allocation, which infers posterior samples via a hybrid of stochastic-gradient MCMC a...
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Constraining the Dynamics of Deep Probabilistic Models
We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives of a given order are subject to inequality or equality constraints. We then cha...
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Democratizing Design for Future Computing Platforms
Information and communications technology can continue to change our world. These advances will partially depend upon designs that synergistically combine software with specialized hardware. Today open-source software incubates rapid software-only innovation. The government can unleash software-hardware innovation wi...
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EstimatedWold Representation and Spectral Density-Driven Bootstrap for Time Series
The second-order dependence structure of purely nondeterministic stationary process is described by the coefficients of the famous Wold representation. These coefficients can be obtained by factorizing the spectral density of the process. This relation together with some spectral density estimator is used in order to...
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A Polynomial Time Match Test for Large Classes of Extended Regular Expressions
In the present paper, we study the match test for extended regular expressions. We approach this NP-complete problem by introducing a novel variant of two-way multihead automata, which reveals that the complexity of the match test is determined by a hidden combinatorial property of extended regular expressions, and i...
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Anomalous Magnetism for Dirac Electrons in Two Dimensional Rashba Systems
Spin-spin correlation function response in the low electronic density regime and externally applied electric field is evaluated for 2D metallic crystals under Rashba-type coupling, fixed number of particles and two-fold energy band structure. Intrinsic Zeeman-like effect on electron spin polarization, density of stat...
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Estimating Average Treatment Effects with a Double-Index Propensity Score
We consider estimating average treatment effects (ATE) of a binary treatment in observational data when data-driven variable selection is needed to select relevant covariates from a moderately large number of available covariates $\mathbf{X}$. To leverage covariates among $\mathbf{X}$ predictive of the outcome for ef...
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Emotion Detection and Analysis on Social Media
In this paper, we address the problem of detection, classification and quantification of emotions of text in any form. We consider English text collected from social media like Twitter, which can provide information having utility in a variety of ways, especially opinion mining. Social media like Twitter and Facebook...
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HotFlip: White-Box Adversarial Examples for Text Classification
We propose an efficient method to generate white-box adversarial examples to trick a character-level neural classifier. We find that only a few manipulations are needed to greatly decrease the accuracy. Our method relies on an atomic flip operation, which swaps one token for another, based on the gradients of the one...
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Towards fully commercial, UV-compatible fiber patch cords
We present and analyze two pathways to produce commercial optical-fiber patch cords with stable long-term transmission in the ultraviolet (UV) at powers up to $\sim$ 200 mW, and typical bulk transmission between 66-75\%. Commercial fiber patch cords in the UV are of great interest across a wide variety of scientific ...
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Convex Parameterizations and Fidelity Bounds for Nonlinear Identification and Reduced-Order Modelling
Model instability and poor prediction of long-term behavior are common problems when modeling dynamical systems using nonlinear "black-box" techniques. Direct optimization of the long-term predictions, often called simulation error minimization, leads to optimization problems that are generally non-convex in the mode...
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Rydberg states of helium in electric and magnetic fields of arbitrary relative orientation
A spectroscopic study of Rydberg states of helium ($n$ = 30 and 45) in magnetic, electric and combined magnetic and electric fields with arbitrary relative orientations of the field vectors is presented. The emphasis is on two special cases where (i) the diamagnetic term is negligible and both paramagnetic Zeeman and...
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Change-point inference on volatility in noisy Itô semimartingales
This work is concerned with tests on structural breaks in the spot volatility process of a general Itô semimartingale based on discrete observations contaminated with i.i.d. microstructure noise. We construct a consistent test building up on infill asymptotic results for certain functionals of spectral spot volatilit...
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Double-diffusive erosion of the core of Jupiter
We present Direct Numerical Simulations of the transport of heat and heavy elements across a double-diffusive interface or a double-diffusive staircase, in conditions that are close to those one may expect to find near the boundary between the heavy-element rich core and the hydrogen-helium envelope of giant planets ...
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Classifying Exoplanets with Gaussian Mixture Model
Recently, Odrzywolek and Rafelski (arXiv:1612.03556) have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using the Gaussian Mixture Model, followed by information theoretic criterion (AIC an...
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Competing effects of Hund's splitting and symmetry-breaking perturbations on electronic order in Pb$_{1-x}$Sn$_{x}$Te
We study the effect of a uniform external magnetization on p-wave superconductivity on the (001) surface of the crystalline topological insulator(TCI) Pb$_{1-x}$Sn$_{x}$Te. It was shown by us in an earlier work that a chiral p-wave finite momentum pairing (FFLO) state can be stabilized in this system in the presence ...
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Partition function of Chern-Simons theory as renormalized q-dimension
We calculate $q$-dimension of $k$-th Cartan power of fundamental representation $\Lambda_0$, corresponding to affine root of affine simply laced Kac-Moody algebras, and show that in the limit $q\rightarrow 1 $, and with natural renormalization, it is equal to universal partition function of Chern-Simons theory on thr...
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Task Recommendation in Crowdsourcing Based on Learning Preferences and Reliabilities
Workers participating in a crowdsourcing platform can have a wide range of abilities and interests. An important problem in crowdsourcing is the task recommendation problem, in which tasks that best match a particular worker's preferences and reliabilities are recommended to that worker. A task recommendation scheme ...
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Elliptic Weight Functions and Elliptic q-KZ Equation
By using representation theory of the elliptic quantum group U_{q,p}(sl_N^), we present a systematic method of deriving the weight functions. The resultant sl_N type elliptic weight functions are new and give elliptic and dynamical analogues of those obtained in the trigonometric case. We then discuss some basic prop...
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Formal duality in finite cyclic groups
The notion of formal duality in finite Abelian groups appeared recently in relation to spherical designs, tight sphere packings, and energy minimizing configurations in Euclidean spaces. For finite cyclic groups it is conjectured that there are no primitive formally dual pairs besides the trivial one and the TITO con...
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Nonlinear Dynamics of Binocular Rivalry: A Comparative Study
When our eyes are presented with the same image, the brain processes it to view it as a single coherent one. The lateral shift in the position of our eyes, causes the two images to possess certain differences, which our brain exploits for the purpose of depth perception and to gauge the size of objects at different d...
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Nonstandard Analysis and Constructivism!
Almost two decades ago, Wattenberg published a paper with the title 'Nonstandard Analysis and Constructivism?' in which he speculates on a possible connection between Nonstandard Analysis and constructive mathematics. We study Wattenberg's work in light of recent research on the aforementioned connection. On one hand...
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Text-Independent Speaker Verification Using 3D Convolutional Neural Networks
In this paper, a novel method using 3D Convolutional Neural Network (3D-CNN) architecture has been proposed for speaker verification in the text-independent setting. One of the main challenges is the creation of the speaker models. Most of the previously-reported approaches create speaker models based on averaging th...
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Sequential identification of nonignorable missing data mechanisms
With nonignorable missing data, likelihood-based inference should be based on the joint distribution of the study variables and their missingness indicators. These joint models cannot be estimated from the data alone, thus requiring the analyst to impose restrictions that make the models uniquely obtainable from the ...
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Image Stitching by Line-guided Local Warping with Global Similarity Constraint
Low-textured image stitching remains a challenging problem. It is difficult to achieve good alignment and it is easy to break image structures due to insufficient and unreliable point correspondences. Moreover, because of the viewpoint variations between multiple images, the stitched images suffer from projective dis...
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