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Logarithmic singularities and quantum oscillations in magnetically doped topological insulators
We report magnetotransport measurements on magnetically doped (Bi,Sb)$_2$Te$_3$ films grown by molecular beam epitaxy. In Hallbar devices, logarithmic dependence on temperature and bias voltage are obseved in both the longitudinal and anomalous Hall resistance. The interplay of disorder and electron-electron interact...
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A General Algorithm to Calculate the Inverse Principal $p$-th Root of Symmetric Positive Definite Matrices
We address the general mathematical problem of computing the inverse $p$-th root of a given matrix in an efficient way. A new method to construct iteration functions that allow calculating arbitrary $p$-th roots and their inverses of symmetric positive definite matrices is presented. We show that the order of converg...
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Latent Mixture Modeling for Clustered Data
This article proposes a mixture modeling approach to estimating cluster-wise conditional distributions in clustered (grouped) data. We adapt the mixture-of-experts model to the latent distributions, and propose a model in which each cluster-wise density is represented as a mixture of latent experts with cluster-wise ...
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Fast Switching Dual Fabry-Perot-Cavity-based Optical Refractometry for Assessment of Gas Refractivity and Density - Estimates of Its Precision, Accuracy, and Temperature Dependence
Dual Fabry-Perot-Cavity-based Optical Refractometry (DFCB-OR) have been shown to have excellent potential for characterization of gases, in particular their refractivity and density. However, its performance has in practice been found to be limited by drifts. To remedy this, drift-free DFPC-OR (DF-DFCB-OR) has recent...
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Dixmier traces and residues on weak operator ideals
We develop the theory of modulated operators in general principal ideals of compact operators. For Laplacian modulated operators we establish Connes' trace formula in its local Euclidean model and a global version thereof. It expresses Dixmier traces in terms of the vector-valued Wodzicki residue. We demonstrate the ...
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Investigating early-type galaxy evolution with a multiwavelength approach. II. The UV structure of 11 galaxies with Swift-UVOT
GALEX detected a significant fraction of early-type galaxies showing Far-UV bright structures. These features suggest the occurrence of recent star formation episodes. We aim at understanding their evolutionary path[s] and the mechanisms at the origin of their UV-bright structures. We investigate with a multi-lambda ...
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Lazy Automata Techniques for WS1S
We present a new decision procedure for the logic WS1S. It originates from the classical approach, which first builds an automaton accepting all models of a formula and then tests whether its language is empty. The main novelty is to test the emptiness on the fly, while constructing a symbolic, term-based representat...
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Joint distribution of conjugate algebraic numbers: a random polynomial approach
Given a polynomial $q(z):=a_0+a_1z+\dots+a_nz^n$ and a vector of positive weights $\mathbf{w}=(w_0, w_1,\dots,w_n)$, define the $\mathbf{w}$-weighted $l_p$-norm of $q$ as $$ l_{p,\mathbf{w}}[q]:=\left(\sum_{k=0}^{n}|w_k a_k|^p\right)^{1/p},\quad p\in[1,\infty]. $$ Define the $\mathbf{w}$-weighted $l_p$-norm of an alg...
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On wrapping the Kalman filter and estimating with the SO(2) group
This paper analyzes directional tracking in 2D with the extended Kalman filter on Lie groups (LG-EKF). The study stems from the problem of tracking objects moving in 2D Euclidean space, with the observer measuring direction only, thus rendering the measurement space and object position on the circle---a non-Euclidean...
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Towards a Context-Aware IDE-Based Meta Search Engine for Recommendation about Programming Errors and Exceptions
Study shows that software developers spend about 19% of their time looking for information in the web during software development and maintenance. Traditional web search forces them to leave the working environment (e.g., IDE) and look for information in the web browser. It also does not consider the context of the p...
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Infrared Flares from M Dwarfs: a Hinderance to Future Transiting Exoplanet Studies
Many current and future exoplanet missions are pushing to infrared (IR) wavelengths where the flux contrast between the planet and star is more favorable (Deming et al. 2009), and the impact of stellar magnetic activity is decreased. Indeed, a recent analysis of starspots and faculae found these forms of stellar acti...
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Topic Identification for Speech without ASR
Modern topic identification (topic ID) systems for speech use automatic speech recognition (ASR) to produce speech transcripts, and perform supervised classification on such ASR outputs. However, under resource-limited conditions, the manually transcribed speech required to develop standard ASR systems can be severel...
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Bio-Inspired Multi-Layer Spiking Neural Network Extracts Discriminative Features from Speech Signals
Spiking neural networks (SNNs) enable power-efficient implementations due to their sparse, spike-based coding scheme. This paper develops a bio-inspired SNN that uses unsupervised learning to extract discriminative features from speech signals, which can subsequently be used in a classifier. The architecture consists...
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Zonotope hit-and-run for efficient sampling from projection DPPs
Determinantal point processes (DPPs) are distributions over sets of items that model diversity using kernels. Their applications in machine learning include summary extraction and recommendation systems. Yet, the cost of sampling from a DPP is prohibitive in large-scale applications, which has triggered an effort tow...
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Brownian motion: from kinetics to hydrodynamics
Brownian motion has served as a pilot of studies in diffusion and other transport phenomena for over a century. The foundation of Brownian motion, laid by Einstein, has generally been accepted to be far from being complete since the late 1960s, because it fails to take important hydrodynamic effects into account. The...
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Natural Time, Nowcasting and the Physics of Earthquakes: Estimation of Seismic Risk to Global Megacities
This paper describes the use of the idea of natural time to propose a new method for characterizing the seismic risk to the world's major cities at risk of earthquakes. Rather than focus on forecasting, which is the computation of probabilities of future events, we define the term seismic nowcasting, which is the com...
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Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Owing to their connection with generative adversarial networks (GANs), saddle-point problems have recently attracted considerable interest in machine learning and beyond. By necessity, most theoretical guarantees revolve around convex-concave (or even linear) problems; however, making theoretical inroads towards effi...
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Design of an Autonomous Precision Pollination Robot
Precision robotic pollination systems can not only fill the gap of declining natural pollinators, but can also surpass them in efficiency and uniformity, helping to feed the fast-growing human population on Earth. This paper presents the design and ongoing development of an autonomous robot named "BrambleBee", which ...
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A sufficiently complicated noded Schottky group of rank three
The theoretical existence of non-classical Schottky groups is due to Marden. Explicit examples of such kind of groups are only known in rank two, the first one by by Yamamoto in 1991 and later by Williams in 2009. In 2006, Maskit and the author provided a theoretical method to obtain examples of non-classical Schottk...
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DONUT: CTC-based Query-by-Example Keyword Spotting
Keyword spotting--or wakeword detection--is an essential feature for hands-free operation of modern voice-controlled devices. With such devices becoming ubiquitous, users might want to choose a personalized custom wakeword. In this work, we present DONUT, a CTC-based algorithm for online query-by-example keyword spot...
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Emulation of the space radiation environment for materials testing and radiobiological experiments
Radiobiology studies on the effects of galactic cosmic ray radiation utilize mono-energetic single-ion particle beams, where the projected doses for exploration missions are given using highly-acute exposures. This methodology does not replicate the multi-ion species and energies found in the space radiation environm...
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Convex Relaxations for Pose Graph Optimization with Outliers
Pose Graph Optimization involves the estimation of a set of poses from pairwise measurements and provides a formalization for many problems arising in mobile robotics and geometric computer vision. In this paper, we consider the case in which a subset of the measurements fed to pose graph optimization is spurious. Ou...
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Quasi-Frobenius-splitting and lifting of Calabi-Yau varieties in characteristic $p$
Extending the notion of Frobenius-splitting, we prove that every finite height Calabi-Yau variety defined over an algebraically closed field of positive characteristic can be lifted to the ring of Witt vectors of length two.
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Consistency and Asymptotic Normality of Latent Blocks Model Estimators
Latent Block Model (LBM) is a model-based method to cluster simultaneously the $d$ columns and $n$ rows of a data matrix. Parameter estimation in LBM is a difficult and multifaceted problem. Although various estimation strategies have been proposed and are now well understood empirically, theoretical guarantees about...
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Linking Generative Adversarial Learning and Binary Classification
In this note, we point out a basic link between generative adversarial (GA) training and binary classification -- any powerful discriminator essentially computes an (f-)divergence between real and generated samples. The result, repeatedly re-derived in decision theory, has implications for GA Networks (GANs), providi...
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High Speed Elephant Flow Detection Under Partial Information
In this paper we introduce a new framework to detect elephant flows at very high speed rates and under uncertainty. The framework provides exact mathematical formulas to compute the detection likelihood and introduces a new flow reconstruction lemma under partial information. These theoretical results lead to the des...
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Scalable k-Means Clustering via Lightweight Coresets
Coresets are compact representations of data sets such that models trained on a coreset are provably competitive with models trained on the full data set. As such, they have been successfully used to scale up clustering models to massive data sets. While existing approaches generally only allow for multiplicative app...
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Scaling relations in the diffusive infiltration in fractals
In a recent work on fluid infiltration in a Hele-Shaw cell with the pore-block geometry of Sierpinski carpets (SCs), the area filled by the invading fluid was shown to scale as F~t^n, with n<1/2, thus providing a macroscopic realization of anomalous diffusion [Filipovitch et al, Water Resour. Res. 52 5167 (2016)]. Th...
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Adaptive Sequential MCMC for Combined State and Parameter Estimation
In the case of a linear state space model, we implement an MCMC sampler with two phases. In the learning phase, a self-tuning sampler is used to learn the parameter mean and covariance structure. In the estimation phase, the parameter mean and covariance structure informs the proposed mechanism and is also used in a ...
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Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems
A new class of functions, called the `Information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Baye...
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Combinatorial cost: a coarse setting
The main inspiration for this paper is a paper by Elek where he introduces combinatorial cost for graph sequences. We show that having cost equal to 1 and hyperfiniteness are coarse invariants. We also show `cost-1' for box spaces behaves multiplicatively when taking subgroups. We show that graph sequences coming fro...
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Uncharted Forest a Technique for Exploratory Data Analysis
Exploratory data analysis is crucial for developing and understanding classification models from high-dimensional datasets. We explore the utility of a new unsupervised tree ensemble called uncharted forest for visualizing class associations, sample-sample associations, class heterogeneity, and uninformative classes ...
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Surface thermophysical properties investigation of the potentially hazardous asteroid (99942) Apophis
In this work, we investigate the surface thermophysical properties (thermal emissivity, thermal inertia, roughness fraction and geometric albedo) of asteroid (99942) Apophis, using the currently available thermal infrared observations of CanariCam on Gran Telescopio CANARIAS and far-infrared data by PACS of Herschel,...
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Reconfigurable cluster state generation in specially poled nonlinear waveguide arrays
We present a new approach for generating cluster states on-chip, with the state encoded in the spatial component of the photonic wavefunction. We show that for spatial encoding, a change of measurement basis can improve the practicality of cluster state algorithm implementation, and demonstrate this by simulating Gro...
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Whole planet coupling between climate, mantle, and core: Implications for the evolution of rocky planets
Earth's climate, mantle, and core interact over geologic timescales. Climate influences whether plate tectonics can take place on a planet, with cool climates being favorable for plate tectonics because they enhance stresses in the lithosphere, suppress plate boundary annealing, and promote hydration and weakening of...
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Solutions of the Helmholtz equation given by solutions of the eikonal equation
We find the form of the refractive index such that a solution, $S$, of the eikonal equation yields an exact solution, $\exp ({\rm i} k_{0} S)$, of the corresponding Helmholtz equation.
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SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation
Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a venue for assessing the current state-of...
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Modelling Luminous-Blue-Variable Isolation
Observations show that luminous blue variables (LBVs) are far more dispersed than massive O-type stars, and Smith & Tombleson suggested that these large separations are inconsistent with a single-star evolution model of LBVs. Instead, they suggested that the large distances are most consistent with binary evolution s...
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Service adoption spreading in online social networks
The collective behaviour of people adopting an innovation, product or online service is commonly interpreted as a spreading phenomenon throughout the fabric of society. This process is arguably driven by social influence, social learning and by external effects like media. Observations of such processes date back to ...
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The Amplitude-Phase Decomposition for the Magnetotelluric Impedance Tensor
The Phase Tensor (PT) marked a breakthrough in understanding and analysis of electric galvanic distortion but does not contain any impedance amplitude information and therefore cannot quantify resistivity without complementary data. We formulate a complete impedance tensor decomposition into the PT and a new Amplitud...
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Real-time Convolutional Neural Networks for Emotion and Gender Classification
In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs. We validate our models by creating a real-time vision system which accomplishes the tasks of face detection, gender classification and emotion classification simultaneously in one blende...
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Compound-Specific Chlorine Isotope Analysis of Organochlorines Using Gas Chromatography-Double Focus Magnetic-Sector High Resolution Mass Spectrometry
Compound-specific chlorine isotope analysis (CSIA-Cl) is a practicable and high-performance approach for quantification of transformation processes and pollution source apportionment of chlorinated organic compounds. This study developed a CSIA-Cl method for perchlorethylene (PCE) and trichloroethylene (TCE) using ga...
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Realization of an atomically thin mirror using monolayer MoSe2
Advent of new materials such as van der Waals heterostructures, propels new research directions in condensed matter physics and enables development of novel devices with unique functionalities. Here, we show experimentally that a monolayer of MoSe2 embedded in a charge controlled heterostructure can be used to realiz...
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Equivariant mirror symmetry for the weighted projective line
In this paper, we establish equivariant mirror symmetry for the weighted projective line. This extends the results by B. Fang, C.C. Liu and Z. Zong, where the projective line was considered [{\it Geometry \& Topology} 24:2049-2092, 2017]. More precisely, we prove the equivalence of the $R$-matrices for A-model and B-...
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Precise Recovery of Latent Vectors from Generative Adversarial Networks
Generative adversarial networks (GANs) transform latent vectors into visually plausible images. It is generally thought that the original GAN formulation gives no out-of-the-box method to reverse the mapping, projecting images back into latent space. We introduce a simple, gradient-based technique called stochastic c...
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The dependence of protostar formation on the geometry and strength of the initial magnetic field
We report results from twelve simulations of the collapse of a molecular cloud core to form one or more protostars, comprising three field strengths (mass-to-flux ratios, {\mu}, of 5, 10, and 20) and four field geometries (with values of the angle between the field and rotation axes, {\theta}, of 0°, 20°, 45°, and 90...
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Current-Voltage Characteristics of Weyl Semimetal Semiconducting Devices, Veselago Lenses and Hyperbolic Dirac Phase
The current-voltage characteristics of a new range of devices built around Weyl semimetals has been predicted using the Landauer formalism. The potential step and barrier have been reconsidered for a three-dimensional Weyl semimetals, with analogies to the two-dimensional material graphene and to optics. With the use...
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Safer Classification by Synthesis
The discriminative approach to classification using deep neural networks has become the de-facto standard in various fields. Complementing recent reservations about safety against adversarial examples, we show that conventional discriminative methods can easily be fooled to provide incorrect labels with very high con...
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A geometrical analysis of global stability in trained feedback networks
Recurrent neural networks have been extensively studied in the context of neuroscience and machine learning due to their ability to implement complex computations. While substantial progress in designing effective learning algorithms has been achieved in the last years, a full understanding of trained recurrent netwo...
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Submolecular-resolution non-invasive imaging of interfacial water with atomic force microscopy
Scanning probe microscopy (SPM) has been extensively applied to probe interfacial water in many interdisciplinary fields but the disturbance of the probes on the hydrogen-bonding structure of water has remained an intractable problem. Here we report submolecular-resolution imaging of the water clusters on a NaCl(001)...
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A Novel Stochastic Stratified Average Gradient Method: Convergence Rate and Its Complexity
SGD (Stochastic Gradient Descent) is a popular algorithm for large scale optimization problems due to its low iterative cost. However, SGD can not achieve linear convergence rate as FGD (Full Gradient Descent) because of the inherent gradient variance. To attack the problem, mini-batch SGD was proposed to get a trade...
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First observation of Ce volume collapse in CeN
On the occasion of the 80th anniversary of the first observation of Ce volume collapse in CeN a remembrance of the implications of that transcendent event is presented, along with a review of the knowledge of Ce physical properties available at that time. Coincident anniversary corresponds to the first proposal for C...
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Experimentation with MANETs of Smartphones
Mobile AdHoc NETworks (MANETs) have been identified as a key emerging technology for scenarios in which IEEE 802.11 or cellular communications are either infeasible, inefficient, or cost-ineffective. Smartphones are the most adequate network nodes in many of these scenarios, but it is not straightforward to build a n...
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Interaction between cluster synchronization and epidemic spread in community networks
In real world, there is a significant relation between human behaviors and epidemic spread. Especially, the reactions among individuals in different communities to epidemics may be different, which lead to cluster synchronization of human behaviors. So, a mathematical model that embeds community structures, behaviora...
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Focusing on a Probability Element: Parameter Selection of Message Importance Measure in Big Data
Message importance measure (MIM) is applicable to characterize the importance of information in the scenario of big data, similar to entropy in information theory. In fact, MIM with a variable parameter can make an effect on the characterization of distribution. Furthermore, by choosing an appropriate parameter of MI...
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Deep Multi-camera People Detection
This paper addresses the problem of multi-view people occupancy map estimation. Existing solutions for this problem either operate per-view, or rely on a background subtraction pre-processing. Both approaches lessen the detection performance as scenes become more crowded. The former does not exploit joint information...
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SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis
Bakground: With the proliferation of available microarray and high throughput sequencing experiments in the public domain, the use of meta-analysis methods increases. In these experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably enhance the statistical power and gi...
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Big Data Fusion to Estimate Fuel Consumption: A Case Study of Riyadh
Falling oil revenues and rapid urbanization are putting a strain on the budgets of oil producing nations which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. While fuel consumption models have started to i...
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Person Following by Autonomous Robots: A Categorical Overview
A wide range of human-robot collaborative applications in industry, search and rescue operations, healthcare, and social interactions require an autonomous robot to follow its human companion. Different operating mediums and applications pose diverse challenges by adding constraints on the choice of sensors, the degr...
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Structures, phase transitions, and magnetic properties of Co3Si from first-principles calculations
Co3Si was recently reported to exhibit remarkable magnetic properties in the nanoparticle form [Appl. Phys. Lett. 108, 152406 (2016)], yet better understanding of this material is to be promoted. Here we report a study on the crystal structures of Co3Si using adaptive genetic algorithm, and discuss its electronic and...
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Rigid realizations of modular forms in Calabi--Yau threefolds
We construct examples of modular rigid Calabi--Yau threefolds, which give a realization of some new weight 4 cusp forms.
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Steady-state analysis of single exponential vacation in a $PH/MSP/1/\infty$ queue using roots
We consider an infinite-buffer single-server queue where inter-arrival times are phase-type ($PH$), the service is provided according to Markovian service process $(MSP)$, and the server may take single, exponentially distributed vacations when the queue is empty. The proposed analysis is based on roots of the associ...
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The agreement distance of rooted phylogenetic networks
The minimal number of rooted subtree prune and regraft (rSPR) operations needed to transform one phylogenetic tree into another one induces a metric on phylogenetic trees - the rSPR-distance. The rSPR-distance between two phylogenetic trees $T$ and $T'$ can be characterised by a maximum agreement forest; a forest wit...
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Optimization of the Waiting Time for H-R Coordination
An analytical model of Human-Robot (H-R) coordination is presented for a Human-Robot system executing a collaborative task in which a high level of synchronization among the agents is desired. The influencing parameters and decision variables that affect the waiting time of the collaborating agents were analyzed. The...
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Introducing AIC model averaging in ecological niche modeling: a single-algorithm multi-model strategy to account for uncertainty in suitability predictions
Aim: The Akaike information Criterion (AIC) is widely used science to make predictions about complex phenomena based on an entire set of models weighted by Akaike weights. This approach (AIC model averaging; hereafter AvgAICc) is often preferable than alternatives based on the selection of a single model. Surprisingl...
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Extrasolar Planets and Their Host Stars
In order to understand the exoplanet, you need to understand its parent star. Astrophysical parameters of extrasolar planets are directly and indirectly dependent on the properties of their respective host stars. These host stars are very frequently the only visible component in the systems. This book describes our w...
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Modeling polypharmacy side effects with graph convolutional networks
The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases and co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Polypharmacy side effects emerge because of drug-drug interactions, in which acti...
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Musical intervals under 12-note equal temperament: a geometrical interpretation
Musical intervals in multiple of semitones under 12-note equal temperament, or more specifically pitch-class subsets of assigned cardinality ($n$-chords) are conceived as positive integer points within an Euclidean $n$-space. The number of distinct $n$-chords is inferred from combinatorics with the extension to $n=0$...
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Determining rough first order perturbations of the polyharmonic operator
We show that the knowledge of Dirichlet to Neumann map for rough $A$ and $q$ in $(-\Delta)^m +A\cdot D +q$ for $m \geq 2$ for a bounded domain in $\mathbb{R}^n$, $n \geq 3$ determines $A$ and $q$ uniquely. The unique identifiability is proved using property of products of functions in Sobolev spaces and constructing ...
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Data Science: A Three Ring Circus or a Big Tent?
This is part of a collection of discussion pieces on David Donoho's paper 50 Years of Data Science, appearing in Volume 26, Issue 4 of the Journal of Computational and Graphical Statistics (2017).
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Optimal Control of Partially Observable Piecewise Deterministic Markov Processes
In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to control the process continuously in time in such a way that the expected discounte...
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Moment-based parameter estimation in binomial random intersection graph models
Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected. This paper discusses the estimation of these parameters from a single observed ...
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Efficient Compression and Indexing of Trajectories
We present a new compressed representation of free trajectories of moving objects. It combines a partial-sums-based structure that retrieves in constant time the position of the object at any instant, with a hierarchical minimum-bounding-boxes representation that allows determining if the object is seen in a certain ...
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Denoising Linear Models with Permuted Data
The multivariate linear regression model with shuffled data and additive Gaussian noise arises in various correspondence estimation and matching problems. Focusing on the denoising aspect of this problem, we provide a characterization the minimax error rate that is sharp up to logarithmic factors. We also analyze the...
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Collisions in shape memory alloys
We present here a model for instantaneous collisions in a solid made of shape memory alloys (SMA) by means of a predictive theory which is based on the introduction not only of macroscopic velocities and temperature, but also of microscopic velocities responsible of the austenite-martensites phase changes. Assuming t...
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Big Data Meets HPC Log Analytics: Scalable Approach to Understanding Systems at Extreme Scale
Today's high-performance computing (HPC) systems are heavily instrumented, generating logs containing information about abnormal events, such as critical conditions, faults, errors and failures, system resource utilization, and about the resource usage of user applications. These logs, once fully analyzed and correla...
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Clustering Spectrum of scale-free networks
Real-world networks often have power-law degrees and scale-free properties such as ultra-small distances and ultra-fast information spreading. In this paper, we study a third universal property: three-point correlations that suppress the creation of triangles and signal the presence of hierarchy. We quantify this pro...
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Multiplex model of mental lexicon reveals explosive learning in humans
Word similarities affect language acquisition and use in a multi-relational way barely accounted for in the literature. We propose a multiplex network representation of this mental lexicon of word similarities as a natural framework for investigating large-scale cognitive patterns. Our representation accounts for sem...
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Weighted $L_{p,q}$-estimates for higher order elliptic and parabolic systems with BMO coefficients on Reifenberg flat domains
We prove weighted $L_{p,q}$-estimates for divergence type higher order elliptic and parabolic systems with irregular coefficients on Reifenberg flat domains. In particular, in the parabolic case the coefficients do not have any regularity assumptions in the time variable. As functions of the spatial variables, the le...
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Various sharp estimates for semi-discrete Riesz transforms of the second order
We give several sharp estimates for a class of combinations of second order Riesz transforms on Lie groups ${G}={G}_{x} \times {G}_{y}$ that are multiply connected, composed of a discrete abelian component ${G}_{x}$ and a connected component ${G}_{y}$ endowed with a biinvariant measure. These estimates include new sh...
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Linear Spectral Estimators and an Application to Phase Retrieval
Phase retrieval refers to the problem of recovering real- or complex-valued vectors from magnitude measurements. The best-known algorithms for this problem are iterative in nature and rely on so-called spectral initializers that provide accurate initialization vectors. We propose a novel class of estimators suitable ...
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A geometric perspective on the method of descent
We derive a representation formula for the tensorial wave equation $\Box_\bg \phi^I=F^I$ in globally hyperbolic Lorentzian spacetimes $(\M^{2+1}, \bg)$ by giving a geometric formulation of the method of descent which is applicable for any dimension.
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Detecting Changes in Hidden Markov Models
We consider the problem of sequential detection of a change in the statistical behavior of a hidden Markov model. By adopting a worst-case analysis with respect to the time of change and by taking into account the data that can be accessed by the change-imposing mechanism we offer alternative formulations of the prob...
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Towards an Empirical Study of Affine Types for Isolated Actors in Scala
LaCasa is a type system and programming model to enforce the object capability discipline in Scala, and to provide affine types. One important application of LaCasa's type system is software isolation of concurrent processes. Isolation is important for several reasons including security and data-race freedom. Moreove...
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FPGA Architecture for Deep Learning and its application to Planetary Robotics
Autonomous control systems onboard planetary rovers and spacecraft benefit from having cognitive capabilities like learning so that they can adapt to unexpected situations in-situ. Q-learning is a form of reinforcement learning and it has been efficient in solving certain class of learning problems. However, embedded...
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Boundary Layer Problems in the Viscosity-Diffusion Vanishing Limits for the Incompressible MHD Systems
In this paper, we we study boundary layer problems for the incompressible MHD systems in the presence of physical boundaries with the standard Dirichlet oundary conditions with small generic viscosity and diffusion coefficients. We identify a non-trivial class of initial data for which we can establish the uniform st...
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Why Adaptively Collected Data Have Negative Bias and How to Correct for It
From scientific experiments to online A/B testing, the previously observed data often affects how future experiments are performed, which in turn affects which data will be collected. Such adaptivity introduces complex correlations between the data and the collection procedure. In this paper, we prove that when the d...
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Machine learning of neuroimaging to diagnose cognitive impairment and dementia: a systematic review and comparative analysis
INTRODUCTION: Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear. METHODS: We systematically reviewed the literature, 2006 to late 2016, for machine learning studies differentiating healthy ageing through to dementia of various types, assess...
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Exact Diffusion for Distributed Optimization and Learning --- Part II: Convergence Analysis
Part I of this work [2] developed the exact diffusion algorithm to remove the bias that is characteristic of distributed solutions for deterministic optimization problems. The algorithm was shown to be applicable to a larger set of combination policies than earlier approaches in the literature. In particular, the com...
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Approximating meta-heuristics with homotopic recurrent neural networks
Much combinatorial optimisation problems constitute a non-polynomial (NP) hard optimisation problem, i.e., they can not be solved in polynomial time. One such problem is finding the shortest route between two nodes on a graph. Meta-heuristic algorithms such as $A^{*}$ along with mixed-integer programming (MIP) method...
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Real embedding and equivariant eta forms
In 1993, Bismut and Zhang establish a mod Z embedding formula of Atiyah-Patodi-Singer reduced eta invariants. In this paper, we explain the hidden mod Z term as a spectral flow and extend this embedding formula to the equivariant family case. In this case, the spectral flow is generalized to the equivariant chern cha...
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Hierarchical Block Sparse Neural Networks
Sparse deep neural networks(DNNs) are efficient in both memory and compute when compared to dense DNNs. But due to irregularity in computation of sparse DNNs, their efficiencies are much lower than that of dense DNNs on regular parallel hardware such as TPU. This inefficiency leads to poor/no performance benefits for...
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Are crossing dependencies really scarce?
The syntactic structure of a sentence can be modelled as a tree, where vertices correspond to words and edges indicate syntactic dependencies. It has been claimed recurrently that the number of edge crossings in real sentences is small. However, a baseline or null hypothesis has been lacking. Here we quantify the amo...
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Theory of Compact Hausdorff Shape
In this paper, we aim to establish a new shape theory, compact Hausdorff shape (CH-shape) for general Hausdorff spaces. We use the "internal" method and direct system approach on the homotopy category of compact Hausdorff spaces. Such a construction can preserve most good properties of H-shape given by Rubin and Sand...
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A Proof of the Herschel-Maxwell Theorem Using the Strong Law of Large Numbers
In this article, we use the strong law of large numbers to give a proof of the Herschel-Maxwell theorem, which characterizes the normal distribution as the distribution of the components of a spherically symmetric random vector, provided they are independent. We present shorter proofs under additional moment assumpti...
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Heating and cooling of coronal loops with turbulent suppression of parallel heat conduction
Using the "enthalpy-based thermal evolution of loops" (EBTEL) model, we investigate the hydrodynamics of the plasma in a flaring coronal loop in which heat conduction is limited by turbulent scattering of the electrons that transport the thermal heat flux. The EBTEL equations are solved analytically in each of the tw...
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How to avoid the curse of dimensionality: scalability of particle filters with and without importance weights
Particle filters are a popular and flexible class of numerical algorithms to solve a large class of nonlinear filtering problems. However, standard particle filters with importance weights have been shown to require a sample size that increases exponentially with the dimension D of the state space in order to achieve...
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Motion and Cooperative Transportation Planning for Multi-Agent Systems under Temporal Logic Formulas
This paper presents a hybrid control framework for the motion planning of a multi-agent system including N robotic agents and M objects, under high level goals expressed as Linear Temporal Logic (LTL) formulas. In particular, we design control protocols that allow the transition of the agents as well as the cooperati...
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Realistic finite temperature simulations of magnetic systems using quantum statistics
We have performed realistic atomistic simulations at finite temperatures using Monte Carlo and atomistic spin dynamics simulations incorporating quantum (Bose-Einstein) statistics. The description is much improved at low temperatures compared to classical (Boltzmann) statistics normally used in these kind of simulati...
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Effective Tensor Sketching via Sparsification
In this paper, we investigate effective sketching schemes via sparsification for high dimensional multilinear arrays or tensors. More specifically, we propose a novel tensor sparsification algorithm that retains a subset of the entries of a tensor in a judicious way, and prove that it can attain a given level of appr...
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