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Direct frequency-comb spectroscopy of $6S_{1/2}$-$8S_{1/2}$ transitions of atomic cesium
Direct frequency-comb spectroscopy is used to probe the absolute frequencies of $6S_{1/2}$-$8S_{1/2}$ two-photon transitions of atomic cesium in hot vapor environment. By utilizing the coherent control method of temporally splitting the laser spectrum above and below the two-photon resonance frequency, Doppler-free a...
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Aggregation and Disaggregation of Energetic Flexibility from Distributed Energy Resources
A variety of energy resources has been identified as being flexible in their electric energy consumption or generation. This energetic flexibility can be used for various purposes such as minimizing energy procurement costs or providing ancillary services to power grids. To fully leverage the flexibility available fr...
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Mapping Walls of Indoor Environment using RGB-D Sensor
Inferring walls configuration of indoor environment could help robot "understand" the environment better. This allows the robot to execute a task that involves inter-room navigation, such as picking an object in the kitchen. In this paper, we present a method to inferring walls configuration from a moving RGB-D senso...
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The Effects of Memory Replay in Reinforcement Learning
Experience replay is a key technique behind many recent advances in deep reinforcement learning. Allowing the agent to learn from earlier memories can speed up learning and break undesirable temporal correlations. Despite its wide-spread application, very little is understood about the properties of experience replay...
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Portfolio Optimization for Cointelated Pairs: SDEs vs. Machine Learning
We investigate the problem of dynamic portfolio optimization in continuous-time, finite-horizon setting for a portfolio of two stocks and one risk-free asset. The stocks follow the Cointelation model. The proposed optimization methods are twofold. In what we call an Stochastic Differential Equation approach, we compu...
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High-mass Starless Clumps in the inner Galactic Plane: the Sample and Dust Properties
We report a sample of 463 high-mass starless clump (HMSC) candidates within $-60°<l<60°$ and $-1°<b<1°$. This sample has been singled out from 10861 ATLASGAL clumps. All of these sources are not associated with any known star-forming activities collected in SIMBAD and young stellar objects identified using color-base...
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Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
Artificial neural networks that learn to perform Principal Component Analysis (PCA) and related tasks using strictly local learning rules have been previously derived based on the principle of similarity matching: similar pairs of inputs should map to similar pairs of outputs. However, the operation of these networks...
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Exploring to learn visual saliency: The RL-IAC approach
The problem of object localization and recognition on autonomous mobile robots is still an active topic. In this context, we tackle the problem of learning a model of visual saliency directly on a robot. This model, learned and improved on-the-fly during the robot's exploration provides an efficient tool for localizi...
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Fast and Robust Shortest Paths on Manifolds Learned from Data
We propose a fast, simple and robust algorithm for computing shortest paths and distances on Riemannian manifolds learned from data. This amounts to solving a system of ordinary differential equations (ODEs) subject to boundary conditions. Here standard solvers perform poorly because they require well-behaved Jacobia...
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Typed Graph Networks
Recently, the deep learning community has given growing attention to neural architectures engineered to learn problems in relational domains. Convolutional Neural Networks employ parameter sharing over the image domain, tying the weights of neural connections on a grid topology and thus enforcing the learning of a nu...
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The effect of different in-chain impurities on the magnetic properties of the spin chain compound SrCuO$_2$ probed by NMR
The S=1/2 Heisenberg spin chain compound SrCuO2 doped with different amounts of nickel (Ni), palladium (Pd), zinc (Zn) and cobalt (Co) has been studied by means of Cu nuclear magnetic resonance (NMR). Replacing only a few of the S=1/2 Cu ions with Ni, Pd, Zn or Co has a major impact on the magnetic properties of the ...
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L-groups and the Langlands program for covering groups: a historical introduction
In this joint introduction to an Asterisque volume, we give a short discussion of the historical developments in the study of nonlinear covering groups, touching on their structure theory, representation theory and the theory of automorphic forms. This serves as a historical motivation and sets the scene for the pape...
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Uncertainty Reduction for Stochastic Processes on Complex Networks
Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally c...
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Light propagation in Extreme Conditions - The role of optically clear tissues and scattering layers in optical biomedical imaging
The field of biomedical imaging has undergone a rapid growth in recent years, mostly due to the implementation of ad-hoc designed experimental setups, theoretical support methods and numerical reconstructions. Especially for biological samples, the high number of scattering events occurring during the photon propagat...
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Design discussion on the ISDA Common Domain Model
A new initiative from the International Swaps and Derivatives Association (ISDA) aims to establish a "Common Domain Model" (ISDA CDM): a new standard for data and process representation across the full range of derivatives instruments. Design of the ISDA CDM is at an early stage and the draft definition contains cons...
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Preserving Intermediate Objectives: One Simple Trick to Improve Learning for Hierarchical Models
Hierarchical models are utilized in a wide variety of problems which are characterized by task hierarchies, where predictions on smaller subtasks are useful for trying to predict a final task. Typically, neural networks are first trained for the subtasks, and the predictions of these networks are subsequently used as...
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Atomistic simulations of dislocation/precipitation interactions in Mg-Al alloys and implications for precipitation hardening
Atomistic simulations were carried out to analyze the interaction between $< a>$ basal dislocations and precipitates in Mg-Al alloys and the associated strengthening mechanisms.
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Recovering Dense Tissue Multispectral Signal from in vivo RGB Images
Hyperspectral/multispectral imaging (HSI/MSI) contains rich information clinical applications, such as 1) narrow band imaging for vascular visualisation; 2) oxygen saturation for intraoperative perfusion monitoring and clinical decision making [1]; 3) tissue classification and identification of pathology [2]. The cur...
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Atomically thin gallium layers from solid-melt exfoliation
Among the large number of promising two-dimensional (2D) atomic layer crystals, true metallic layers are rare. Through combined theoretical and experimental approaches, we report on the stability and successful exfoliation of atomically thin gallenene sheets, having two distinct atomic arrangements along crystallogra...
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Novel Universality Classes in Ferroelectric Liquid Crystals
Starting from a Langevin formulation of a thermally perturbed nonlinear elastic model of the ferroelectric smectic-C$^*$ (SmC${*}$) liquid crystals in the presence of an electric field, this article characterizes the hitherto unexplored dynamical phase transition from a thermo-electrically forced ferroelectric SmC${}...
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Feature functional theory - binding predictor (FFT-BP) for the blind prediction of binding free energies
We present a feature functional theory - binding predictor (FFT-BP) for the protein-ligand binding affinity prediction. The underpinning assumptions of FFT-BP are as follows: i) representability: there exists a microscopic feature vector that can uniquely characterize and distinguish one protein-ligand complex from a...
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Combining and Steganography of 3D Face Textures
One of the serious issues in communication between people is hiding information from others, and the best way for this, is deceiving them. Since nowadays face images are mostly used in three dimensional format, in this paper we are going to steganography 3D face images, detecting which by curious people will be impos...
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Degree of sequentiality of weighted automata
Weighted automata (WA) are an important formalism to describe quantitative properties. Obtaining equivalent deterministic machines is a longstanding research problem. In this paper we consider WA with a set semantics, meaning that the semantics is given by the set of weights of accepting runs. We focus on multi-seque...
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On the orders of the non-Frattini elements of a finite group
Let $G$ be a finite group and let $p_1,\dots,p_n$ be distinct primes. If $G$ contains an element of order $p_1\cdots p_n,$ then there is an element in $G$ which is not contained in the Frattini subgroup of $G$ and whose order is divisible by $p_1\cdots p_n.$
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Varieties of general type with small volumes
Generalize Kobayashi's example for the Noether inequality in dimension three, we provide examples of n-folds of general type with small volumes.
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Translations in the exponential Orlicz space with Gaussian weight
We study the continuity of space translations on non-parametric exponential families based on the exponential Orlicz space with Gaussian reference density.
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Shrinkage Estimation Strategies in Generalized Ridge Regression Models Under Low/High-Dimension Regime
In this study, we propose shrinkage methods based on {\it generalized ridge regression} (GRR) estimation which is suitable for both multicollinearity and high dimensional problems with small number of samples (large $p$, small $n$). Also, it is obtained theoretical properties of the proposed estimators for Low/High D...
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A path integral approach to Bayesian inference in Markov processes
We formulate Bayesian updates in Markov processes by means of path integral techniques and derive the imaginary-time Schrödinger equation with likelihood to direct the inference incorporated as a potential for the posterior probability distribution
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Strong-coupling charge density wave in a one-dimensional topological metal
Scanning tunnelling microscopy and low energy electron diffraction show a dimerization-like reconstruction in the one-dimensional atomic chains on Bi(114) at low temperatures. While one-dimensional systems are generally unstable against such a distortion, its observation is not expected for this particular surface, s...
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$\mathfrak A$-principal Hopf hypersurfaces in complex quadrics
A real hypersurface in the complex quadric $Q^m=SO_{m+2}/SO_mSO_2$ is said to be $\mathfrak A$-principal if its unit normal vector field is singular of type $\mathfrak A$-principal everywhere. In this paper, we show that a $\mathfrak A$-principal Hopf hypersurface in $Q^m$, $m\geq3$ is an open part of a tube around a...
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On the stochastic phase stability of Ti2AlC-Cr2AlC
The quest towards expansion of the MAX design space has been accelerated with the recent discovery of several solid solution and ordered phases involving at least two MAX end members. Going beyond the nominal MAX compounds enables not only fine tuning of existing properties but also entirely new functionality. This s...
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Note on Attacking Object Detectors with Adversarial Stickers
Deep learning has proven to be a powerful tool for computer vision and has seen widespread adoption for numerous tasks. However, deep learning algorithms are known to be vulnerable to adversarial examples. These adversarial inputs are created such that, when provided to a deep learning algorithm, they are very likely...
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All or Nothing Caching Games with Bounded Queries
We determine the value of some search games where our goal is to find all of some hidden treasures using queries of bounded size. The answer to a query is either empty, in which case we lose, or a location, which contains a treasure. We prove that if we need to find $d$ treasures at $n$ possible locations with querie...
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HATS-43b, HATS-44b, HATS-45b, and HATS-46b: Four Short Period Transiting Giant Planets in the Neptune-Jupiter Mass Range
We report the discovery of four short period extrasolar planets transiting moderately bright stars from photometric measurements of the HATSouth network coupled to additional spectroscopic and photometric follow-up observations. While the planet masses range from 0.26 to 0.90 M$_J$, the radii are all approximately a ...
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Well-balanced mesh-based and meshless schemes for the shallow-water equations
We formulate a general criterion for the exact preservation of the "lake at rest" solution in general mesh-based and meshless numerical schemes for the strong form of the shallow-water equations with bottom topography. The main idea is a careful mimetic design for the spatial derivative operators in the momentum flux...
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An Enhanced Initial Margin Methodology to Manage Warehoused Credit Risk
The use of CVA to cover credit risk is widely spread, but has its limitations. Namely, dealers face the problem of the illiquidity of instruments used for hedging it, hence forced to warehouse credit risk. As a result, dealers tend to offer a limited OTC derivatives market to highly risky counterparties. Consequently...
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Ensemble Pruning based on Objection Maximization with a General Distributed Framework
Ensemble pruning, selecting a subset of individual learners from an original ensemble, alleviates the deficiencies of ensemble learning on the cost of time and space. Accuracy and diversity serve as two crucial factors while they usually conflict with each other. To balance both of them, we formalize the ensemble pru...
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Psychophysical laws as reflection of mental space properties
The paper is devoted to the relationship between psychophysics and physics of mind. The basic trends in psychophysics development are briefly discussed with special attention focused on Teghtsoonian's hypotheses. These hypotheses pose the concept of the universality of inner psychophysics and enable to speak about ps...
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Shimura curves in the Prym locus
We study Shimura curves of PEL type in $\mathsf{A}_g$ generically contained in the Prym locus. We study both the unramified Prym locus, obtained using étale double covers, and the ramified Prym locus, corresponding to double covers ramified at two points. In both cases we consider the family of all double covers comp...
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Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies
Data-driven anomaly detection methods suffer from the drawback of detecting all instances that are statistically rare, irrespective of whether the detected instances have real-world significance or not. In this paper, we are interested in the problem of specifically detecting anomalous instances that are known to hav...
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View-Invariant Recognition of Action Style Self-Dissimilarity
Self-similarity was recently introduced as a measure of inter-class congruence for classification of actions. Herein, we investigate the dual problem of intra-class dissimilarity for classification of action styles. We introduce self-dissimilarity matrices that discriminate between same actions performed by different...
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Conducting Highly Principled Data Science: A Statistician's Job and Joy
Highly Principled Data Science insists on methodologies that are: (1) scientifically justified, (2) statistically principled, and (3) computationally efficient. An astrostatistics collaboration, together with some reminiscences, illustrates the increased roles statisticians can and should play to ensure this trio, an...
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Regularizing nonlinear Schroedinger equations through partial off-axis variations
We study a class of focusing nonlinear Schroedinger-type equations derived recently by Dumas, Lannes and Szeftel within the mathematical description of high intensity laser beams [7]. These equations incorporate the possibility of a (partial) off-axis variation of the group velocity of such laser beams through a seco...
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On h-Lexicalized Restarting Automata
Following some previous studies on restarting automata, we introduce a refined model - the h-lexicalized restarting automaton (h-RLWW). We argue that this model is useful for expressing lexicalized syntax in computational linguistics. We compare the input languages, which are the languages traditionally considered in...
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Bayesian Nonparametric Inference for M/G/1 Queueing Systems
In this work, nonparametric statistical inference is provided for the continuous-time M/G/1 queueing model from a Bayesian point of view. The inference is based on observations of the inter-arrival and service times. Beside other characteristics of the system, particular interest is in the waiting time distribution w...
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Symbol Invariant of Partition and the Construction
The symbol is used to describe the Springer correspondence for the classical groups. We propose equivalent definitions of symbols for rigid partitions in the $B_n$, $C_n$, and $D_n$ theories uniformly. Analysing the new definition of symbol in detail, we give rules to construct symbol of a partition, which are easy t...
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Fairness in representation: quantifying stereotyping as a representational harm
While harms of allocation have been increasingly studied as part of the subfield of algorithmic fairness, harms of representation have received considerably less attention. In this paper, we formalize two notions of stereotyping and show how they manifest in later allocative harms within the machine learning pipeline...
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Probing the possibility of hotspots on the central neutron star in HESS J1731-347
The X-ray spectra of the neutron stars located in the centers of supernova remnants Cas A and HESS J1731-347 are well fit with carbon atmosphere models. These fits yield plausible neutron star sizes for the known or estimated distances to these supernova remnants. The evidence in favor of the presence of a pure carbo...
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Some Elementary Partition Inequalities and Their Implications
We prove various inequalities between the number of partitions with the bound on the largest part and some restrictions on occurrences of parts. We explore many interesting consequences of these partition inequalities. In particular, we show that for $L\geq 1$, the number of partitions with $l-s \leq L$ and $s=1$ is ...
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The terrestrial late veneer from core disruption of a lunar-sized impactor
Overabundances in highly siderophile elements (HSEs) of Earth's mantle can be explained by conveyance from a singular, immense (3000 km in a diameter) "Late Veneer" impactor of chondritic composition, subsequent to lunar formation and terrestrial core-closure. Such rocky objects of approximately lunar mass (about 0.0...
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A Bayesian model for lithology/fluid class prediction using a Markov mesh prior fitted from a training image
We consider a Bayesian model for inversion of observed amplitude variation with offset (AVO) data into lithology/fluid classes, and study in particular how the choice of prior distribution for the lithology/fluid classes influences the inversion results. Two distinct prior distributions are considered, a simple manua...
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Correct Brillouin zone and electronic structure of BiPd
A promising route to the realization of Majorana fermions is in non-centrosymmetric superconductors, in which spin-orbit-coupling lifts the spin degeneracy of both bulk and surface bands. A detailed assessment of the electronic structure is critical to evaluate their suitability for this through establishing the topo...
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Even faster sorting of (not only) integers
In this paper we introduce RADULS2, the fastest parallel sorter based on radix algorithm. It is optimized to process huge amounts of data making use of modern multicore CPUs. The main novelties include: extremely optimized algorithm for handling tiny arrays (up to about a hundred of records) that could appear even bi...
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Evidential Deep Learning to Quantify Classification Uncertainty
Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant model remains ignorant to its prediction confidence. Orthogonally to Bayesian neural nets that in...
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Neutron interference in the Earth's gravitational field
This work relates to the famous experiments, performed in 1975 and 1979 by Werner et al., measuring neutron interference and neutron Sagnac effects in the earth's gravitational field. Employing the method of Stodolsky in its weak field approximation, explicit expressions are derived for the two phase shifts, which tu...
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Solve For Shortest Paths Problem Within Logarithm Runtime
The Shortest Paths Problem (SPP) is no longer unresolved. Just for a large scalar of instance on this problem, even we cannot know if an algorithm achieves the computing. Those cutting-edge methods are still in the low performance. If we go to a strategy the best-first-search to deal with computing, it is awkward tha...
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A short proof of the error term in Simpson's rule
In this paper we present a short and elementary proof for the error in Simpson's rule.
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Neutrino mass and dark energy constraints from redshift-space distortions
Cosmology in the near future promises a measurement of the sum of neutrino masses, a fundamental Standard Model parameter, as well as substantially-improved constraints on the dark energy. We use the shape of the BOSS redshift-space galaxy power spectrum, in combination with CMB and supernova data, to constrain the n...
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Dielectrophoretic assembly of liquid-phase-exfoliated TiS3 nanoribbons for photodetecting applications
Liquid-phase-exfoliation is a technique capable of producing large quantities of two-dimensional material in suspension. Despite many efforts in the optimization of the exfoliation process itself not much has been done towards the integration of liquid-phase-exfoliated materials in working solid-state devices. In thi...
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Motion optimization and parameter identification for a human and lower-back exoskeleton model
Designing an exoskeleton to reduce the risk of low-back injury during lifting is challenging. Computational models of the human-robot system coupled with predictive movement simulations can help to simplify this design process. Here, we present a study that models the interaction between a human model actuated by mus...
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A dataset for Computer-Aided Detection of Pulmonary Embolism in CTA images
Todays, researchers in the field of Pulmonary Embolism (PE) analysis need to use a publicly available dataset to assess and compare their methods. Different systems have been designed for the detection of pulmonary embolism (PE), but none of them have used any public datasets. All papers have used their own private d...
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Comment on Ben-Amotz and Honig, "Average entropy dissipation in irreversible mesoscopic processes," Phys. Rev. Lett. 96, 020602 (2006)
We point out that most of the classical thermodynamics results in the paper have been known in the literature, see Kestin and Woods, for quite some time and are not new, contrary to what the authors imply. As shown by Kestin, these results are valid for quasistatic irreversible processes only and not for arbitrary ir...
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High-transmissivity Silicon Visible-wavelength Metasurface Designs based on Truncated-cone Nanoantennae
High-transmissivity all-dielectric metasurfaces have recently attracted attention towards the realization of ultra-compact optical devices and systems. Silicon based metasurfaces, in particular, are highly promising considering the possibility of monolithic integration with VLSI circuits. Realization of silicon based...
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Probabilistic Multigraph Modeling for Improving the Quality of Crowdsourced Affective Data
We proposed a probabilistic approach to joint modeling of participants' reliability and humans' regularity in crowdsourced affective studies. Reliability measures how likely a subject will respond to a question seriously; and regularity measures how often a human will agree with other seriously-entered responses comi...
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Quantum key distribution protocol with pseudorandom bases
Quantum key distribution (QKD) offers a way for establishing information-theoretically secure communications. An important part of QKD technology is a high-quality random number generator (RNG) for quantum states preparation and for post-processing procedures. In the present work, we consider a novel class of prepare...
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Deep clustering of longitudinal data
Deep neural networks are a family of computational models that have led to a dramatical improvement of the state of the art in several domains such as image, voice or text analysis. These methods provide a framework to model complex, non-linear interactions in large datasets, and are naturally suited to the analysis ...
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Economic Implications of Blockchain Platforms
In an economy with asymmetric information, the smart contract in the blockchain protocol mitigates uncertainty. Since, as a new trading platform, the blockchain triggers segmentation of market and differentiation of agents in both the sell and buy sides of the market, it recomposes the asymmetric information and gene...
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Proof Theory and Ordered Groups
Ordering theorems, characterizing when partial orders of a group extend to total orders, are used to generate hypersequent calculi for varieties of lattice-ordered groups (l-groups). These calculi are then used to provide new proofs of theorems arising in the theory of ordered groups. More precisely: an analytic calc...
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DF-SLAM: A Deep-Learning Enhanced Visual SLAM System based on Deep Local Features
As the foundation of driverless vehicle and intelligent robots, Simultaneous Localization and Mapping(SLAM) has attracted much attention these days. However, non-geometric modules of traditional SLAM algorithms are limited by data association tasks and have become a bottleneck preventing the development of SLAM. To d...
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A-NICE-MC: Adversarial Training for MCMC
Existing Markov Chain Monte Carlo (MCMC) methods are either based on general-purpose and domain-agnostic schemes which can lead to slow convergence, or hand-crafting of problem-specific proposals by an expert. We propose A-NICE-MC, a novel method to train flexible parametric Markov chain kernels to produce samples wi...
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Starobinsky-like Inflation, Supercosmology and Neutrino Masses in No-Scale Flipped SU(5)
We embed a flipped ${\rm SU}(5) \times {\rm U}(1)$ GUT model in a no-scale supergravity framework, and discuss its predictions for cosmic microwave background observables, which are similar to those of the Starobinsky model of inflation. Measurements of the tilt in the spectrum of scalar perturbations in the cosmic m...
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'Viral' Turing Machines, Computation from Noise and Combinatorial Hierarchies
The interactive computation paradigm is reviewed and a particular example is extended to form the stochastic analog of a computational process via a transcription of a minimal Turing Machine into an equivalent asynchronous Cellular Automaton with an exponential waiting times distribution of effective transitions. Fur...
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Estimating model evidence using ensemble-based data assimilation with localization - The model selection problem
IIn recent years, there has been a growing interest in applying data assimilation (DA) methods, originally designed for state estimation, to the model selection problem. In this setting, Carrassi et al. (2017) introduced the contextual formulation of model evidence (CME) and showed that CME can be efficiently compute...
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An efficient spectral-Galerkin approximation and error analysis for Maxwell transmission eigenvalue problems in spherical geometries
We propose and analyze an efficient spectral-Galerkin approximation for the Maxwell transmission eigenvalue problem in spherical geometry. Using a vector spherical harmonic expansion, we reduce the problem to a sequence of equivalent one-dimensional TE and TM modes that can be solved individually in parallel. For the...
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Mendelian randomization with fine-mapped genetic data: choosing from large numbers of correlated instrumental variables
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic varia...
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Building competitive direct acoustics-to-word models for English conversational speech recognition
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have received increasing attention compared to conventional sub-word based automatic speech recognition models using phones, characters, or context-dependent hidden Markov model states. This is because A2W models recognize words from speech without any ...
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Convolutional Dictionary Learning: Acceleration and Convergence
Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM)...
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The late-time light curve of the type Ia supernova SN 2011fe
We present late-time optical $R$-band imaging data from the Palomar Transient Factory (PTF) for the nearby type Ia supernova SN 2011fe. The stacked PTF light curve provides densely sampled coverage down to $R\simeq22$ mag over 200 to 620 days past explosion. Combining with literature data, we estimate the pseudo-bolo...
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Convergence analysis of the block Gibbs sampler for Bayesian probit linear mixed models with improper priors
In this article, we consider Markov chain Monte Carlo(MCMC) algorithms for exploring the intractable posterior density associated with Bayesian probit linear mixed models under improper priors on the regression coefficients and variance components. In particular, we construct the two-block Gibbs sampler using the dat...
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The complexity of the Multiple Pattern Matching Problem for random strings
We generalise a multiple string pattern matching algorithm, recently proposed by Fredriksson and Grabowski [J. Discr. Alg. 7, 2009], to deal with arbitrary dictionaries on an alphabet of size $s$. If $r_m$ is the number of words of length $m$ in the dictionary, and $\phi(r) = \max_m \ln(s\, m\, r_m)/m$, the complexit...
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Functoriality and uniformity in Hrushovski's groupoid-cover correspondence
The correspondence between definable connected groupoids in a theory $T$ and internal generalised imaginary sorts of $T$, established by Hrushovski in ["Groupoids, imaginaries and internal covers," Turkish Journal of Mathematics, 2012], is here extended in two ways: First, it is shown that the correspondence is in fa...
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Simple Conditions for Metastability of Continuous Markov Chains
A family $\{Q_{\beta}\}_{\beta \geq 0}$ of Markov chains is said to exhibit $\textit{metastable mixing}$ with $\textit{modes}$ $S_{\beta}^{(1)},\ldots,S_{\beta}^{(k)}$ if its spectral gap (or some other mixing property) is very close to the worst conductance $\min(\Phi_{\beta}(S_{\beta}^{(1)}), \ldots, \Phi_{\beta}(S...
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Deterministic preparation of highly non-classical macroscopic quantum states
We present a scheme to deterministically prepare non-classical quantum states of a massive mirror including highly non-Gaussian states exhibiting sizeable negativity of the Wigner function. This is achieved by exploiting the non-linear light-matter interaction in an optomechanical cavity by driving the system with op...
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On Local Optimizers of Acquisition Functions in Bayesian Optimization
Bayesian optimization is a sample-efficient method for finding a global optimum of an expensive-to-evaluate black-box function. A global solution is found by accumulating a pair of query point and corresponding function value, repeating these two procedures: (i) learning a surrogate model for the objective function u...
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One Password: An Encryption Scheme for Hiding Users' Register Information
In recent years, the attack which leverages register information (e.g. accounts and passwords) leaked from 3rd party applications to try other applications is popular and serious. We call this attack "database collision". Traditionally, people have to keep dozens of accounts and passwords for different applications t...
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The RoPES project with HARPS and HARPS-N. I. A system of super-Earths orbiting the moderately active K-dwarf HD 176986
We report the discovery of a system of two super-Earths orbiting the moderately active K-dwarf HD 176986. This work is part of the RoPES RV program of G- and K-type stars, which combines radial velocities (RVs) from the HARPS and HARPS-N spectrographs to search for short-period terrestrial planets. HD 176986 b and c ...
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On the possibility of developing quasi-cw high-power high-pressure laser on 4p-4s transition of ArI with electron beam - optical pumping: quenching of 4s (3P2) lower laser level
A new electron beam-optical procedure is proposed for quasi-cw pumping of high-pressure large-volume He-Ar laser on 4p[1/2]1 - 4s[3/2]2 argon atom transition at the wavelength of 912.5 nm. It consists of creation and maintenance of a necessary density of 4s[3/2]2 metastable state in the gain medium by a fast electron...
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An Adaptive Characteristic-wise Reconstruction WENOZ scheme for Gas Dynamic Euler Equations
Due to its excellent shock-capturing capability and high resolution, the WENO scheme family has been widely used in varieties of compressive flow simulation. However, for problems containing strong shocks and contact discontinuities, such as the Lax shock tube problem, the WENO scheme still produces numerical oscilla...
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A level set-based structural optimization code using FEniCS
This paper presents an educational code written using FEniCS, based on the level set method, to perform compliance minimization in structural optimization. We use the concept of distributed shape derivative to compute a descent direction for the compliance, which is defined as a shape functional. The use of the distr...
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Transaction Support over Redis: An Overview
This document outlines the approach to supporting cross-node transactions over a Redis cluster.
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Subgraphs and motifs in a dynamic airline network
How does the small-scale topological structure of an airline network behave as the network evolves? To address this question, we study the dynamic and spatial properties of small undirected subgraphs using 15 years of data on Southwest Airlines' domestic route service. We find that this real-world network has much in...
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On the Glitch Phenomenon
The Principle of the Glitch states that for any device which makes a discrete decision based upon a continuous range of possible inputs, there are inputs for which it will take arbitrarily long to reach a decision. The appropriate mathematical setting for studying this principle is described. This involves defining t...
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Asymptotic properties and approximation of Bayesian logspline density estimators for communication-free parallel computing methods
In this article we perform an asymptotic analysis of Bayesian parallel density estimators which are based on logspline density estimation. The parallel estimator we introduce is in the spirit of a kernel density estimator introduced in recent studies. We provide a numerical procedure that produces the density estimat...
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Tunable Weyl and Dirac states in the nonsymmorphic compound $\rm\mathbf{CeSbTe}$
Recent interest in topological semimetals has lead to the proposal of many new topological phases that can be realized in real materials. Next to Dirac and Weyl systems, these include more exotic phases based on manifold band degeneracies in the bulk electronic structure. The exotic states in topological semimetals a...
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Personalised Query Suggestion for Intranet Search with Temporal User Profiling
Recent research has shown the usefulness of using collective user interaction data (e.g., query logs) to recommend query modification suggestions for Intranet search. However, most of the query suggestion approaches for Intranet search follow an "one size fits all" strategy, whereby different users who submit an iden...
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Navigability of Random Geometric Graphs in the Universe and Other Spacetimes
Random geometric graphs in hyperbolic spaces explain many common structural and dynamical properties of real networks, yet they fail to predict the correct values of the exponents of power-law degree distributions observed in real networks. In that respect, random geometric graphs in asymptotically de Sitter spacetim...
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Learning Geometric Concepts with Nasty Noise
We study the efficient learnability of geometric concept classes - specifically, low-degree polynomial threshold functions (PTFs) and intersections of halfspaces - when a fraction of the data is adversarially corrupted. We give the first polynomial-time PAC learning algorithms for these concept classes with dimension...
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The relationship between the number of editorial board members and the scientific output of universities in the chemistry field
Editorial board members, who are considered the gatekeepers of scientific journals, play an important role in academia, and may directly or indirectly affect the scientific output of a university. In this article, we used the quantile regression method among a sample of 1,387 university in chemistry to characterize t...
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A Non-standard Standard Model
This paper examines the Standard Model under the strong-electroweak gauge group $SU_S(3)\times U_{EW}(2)$ subject to the condition $u_{EW}(2)\not\cong su_I(2)\oplus u_Y(1)$. Physically, the condition ensures that all electroweak gauge bosons interact with each other prior to symmetry breaking --- as one might expect ...
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Robust functional regression model for marginal mean and subject-specific inferences
We introduce flexible robust functional regression models, using various heavy-tailed processes, including a Student $t$-process. We propose efficient algorithms in estimating parameters for the marginal mean inferences and in predicting conditional means as well interpolation and extrapolation for the subject-specif...
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