April 2019 arXiv papers — page 89

Tarek M. A. El-Mistikawy

The cited article contains a serious flaw. A remedy is found in articles by other authors.

Jonas Nordqvist, Juan Rivera-Letelier

In this paper, we study power series having a fixed point of multiplier 1. First, we give a closed formula for the residue fixed point index, in terms of the first coefficients of the power series. Then, we use this formula to study wildly ramified power series in positive characteristic. Among power series having a multiple fixed point of small multiplicity

Yong Tang, Yue-Liang Wu

Motivated by the Weyl scaling gauge symmetry, we present a theoretical framework to explain cosmic inflation and dark matter simultaneously. This symmetry has been resurrected in recent attempts to formulate the gauge theory of gravity. We show the inspired inflation model is well consistent with current observations and will be probed further by future expe

Tanzila Rahman, Mrigank Rochan, Yang Wang

The goal of video-based person re-identification is to match two input videos, so that the distance of the two videos is small if two videos contain the same person. A common approach for person re-identification is to first extract image features for all frames in the video, then aggregate all the features to form a video-level feature. The video-level feat

Lei Li, Felix Kohler, Joanna Dziadkowiec, Anja Røyne

Crystallization pressure drives deformation and damage in monuments, buildings and the Earth's crust. Even though the phenomenon has been known for 170 years there is no agreement between theoretical calculations of the maximum attainable pressure and that found experimentally. We have therefore developed a novel experimental technique to image the nano-

Mauricio Achigar

For an $α$-expansive homeomorphism of a compact space we give an elementary proof of the following well-known result in topological dynamics: A sufficient condition for the homeomorphism to have the shadowing property is that it has the $α$-shadowing property for one-jump pseudo orbits (known as the local product structure property). The proof relies on a re

Arnald Puy, Samuele Lo Piano, Andrea Saltelli

The PAWN index is gaining traction among the modelling community as a sensitivity measure. However, the robustness to its design parameters has not yet been scrutinized: the size ($N$) and sampling ($\varepsilon$) of the model output, the number of conditioning intervals ($n$) or the summary statistic ($θ$). Here we fill this gap by running a sensitivity ana

Sam Ferguson, Azita Mayeli, Nat Sothanaphan

Motivated by the open problem of exhibiting a subset of Euclidean space which has no exponential Riesz basis, we focus on exponential Riesz bases in finite abelian groups. We point out that that every subset of a finite abelian group has such a basis, removing interest in the existence question in this context. We then define tightness quantities for subsets

Paul Blomstedt, Diego Mesquita, Omar Rivasplata, Jarno Lintusaari

Meta-analysis aims to generalize results from multiple related statistical analyses through a combined analysis. While the natural outcome of a Bayesian study is a posterior distribution, traditional Bayesian meta-analyses proceed by combining summary statistics (i.e., point-valued estimates) computed from data. In this paper, we develop a framework for comb

Song-Jin O, Yong-Hwan Kim, Ho-Yong Rim, Hak-Chol Pak

The impact of local and nonlocal density-density interactions on the electronic instabilities in the honeycomb lattice is widely investigated. Some early studies proposed the emergence of interaction-induced topologically nontrivial phases, but recently, it was denied in several works including renormalization group calculations with refined momentum resolut

Eugene Gorsky, Paul Wedrich

We describe the universal target of annular Khovanov-Rozansky link homology functors as the homotopy category of a free symmetric monoidal category generated by one object and one endomorphism. This categorifies the ring of symmetric functions and admits categorical analogues of plethystic transformations, which we use to characterize the annular invariants

Lihua Lei, Michael I. Jordan

Stochastic-gradient-based optimization has been a core enabling methodology in applications to large-scale problems in machine learning and related areas. Despite the progress, the gap between theory and practice remains significant, with theoreticians pursuing mathematical optimality at a cost of obtaining specialized procedures in different regimes (e.g.,

Tatiana Likhomanenko, Gabriel Synnaeve, Ronan Collobert

Lexicon-free speech recognition naturally deals with the problem of out-of-vocabulary (OOV) words. In this paper, we show that character-based language models (LM) can perform as well as word-based LMs for speech recognition, in word error rates (WER), even without restricting the decoding to a lexicon. We study character-based LMs and show that convolutiona

Raghav Singhal, Xintian Han, Saad Lahlou, Rajesh Ranganath

Much of machine learning relies on comparing distributions with discrepancy measures. Stein's method creates discrepancy measures between two distributions that require only the unnormalized density of one and samples from the other. Stein discrepancies can be combined with kernels to define kernelized Stein discrepancies (KSDs). While kernels make Stein

Shan Tai Chan

We study proper holomorphic maps between bounded symmetric domains $D$ and $Ω$. In particular, when $D$ and $Ω$ are of the same rank $\ge 2$ such that all irreducible factors of $D$ are of rank $\ge 2$, we prove that any proper holomorphic map from $D$ to $Ω$ is a totally geodesic holomorphic isometric embedding with respect to certain canonical Kähler metri

Youssouf Akrour, Nouressadat Touafek, Yacine Halim

In this work we solve in closed form the system of difference equations \begin{equation*} x_{n+1}=\dfrac{ay_nx_{n-1}+bx_{n-1}+c}{y_nx_{n-1}},\; y_{n+1}=\dfrac{ax_ny_{n-1}+by_{n-1}+c}{x_ny_{n-1}},\;n=0,1,..., \end{equation*} where the initial values $x_{-1}$, $x_0$, $y_{-1}$ and $y_0$ are arbitrary nonzero real numbers and the parameters $a$, $b$ and $c$ are

Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea, Nikos Triandopoulos

In collaborative learning, multiple parties contribute their datasets to jointly deduce global machine learning models for numerous predictive tasks. Despite its efficacy, this learning paradigm fails to encompass critical application domains that involve highly sensitive data, such as healthcare and security analytics, where privacy risks limit entities to

Ye Yuan, Wenhan Yang, Wenqi Ren, Jiaying Liu

The UG$^{2+}$ challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios. In its second track, we focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light condi

Ryuichi Yamamoto, Eunwoo Song, Jae-Min Kim

This paper proposes an effective probability density distillation (PDD) algorithm for WaveNet-based parallel waveform generation (PWG) systems. Recently proposed teacher-student frameworks in the PWG system have successfully achieved a real-time generation of speech signals. However, the difficulties optimizing the PDD criteria without auxiliary losses resul

Ben David Normann, Chris Clarkson

The weak gravitational lensing formalism can be extended to the strong lensing regime by integrating a nonlinear version of the geodesic deviation equation. The resulting "roulette" expansion generalises the notion of convergence, shear and flexion to arbitrary order. The independent coefficients of this expansion are screen space gradients of the op

Katie Christensen, Hamid Kulosman

We give intrinsic characterizations of neural rings and homomorphisms between them. Also we introduce the notion of a basic monomial code map and characterize monomial code maps as compositions of basic monomial code maps. Finally, we characterize monomial isomorphisms between neural codes. Our work is based on the 2015 paper by C.~Curto and N.~Youngs about

Tang Liu, Daniela Tuninetti

The Pliable Index CODing (PICOD) problem is a variant of the Index Coding (IC) problem, where the desired messages by the users, who are equipped with message side information, is part of the optimization. This paper studies the PICOD problem where users are subject to a privacy constraint. In particular, the following spacial class of private PICODs is inve

Yuan Gao, Zixiang Cai, Lei Yu

Improving model performance is always the key problem in machine learning including deep learning. However, stand-alone neural networks always suffer from marginal effect when stacking more layers. At the same time, ensemble is an useful technique to further enhance model performance. Nevertheless, training several independent deep neural networks for ensemb

Juan Martínez-Sykora, Viggo H. Hansteen, Boris Gudiksen, Mats Carlsson

The presence of magnetic field is crucial in the transport of energy through the solar atmosphere. Recent ground-based and space-borne observations of the quiet Sun have revealed that magnetic field accumulates at photospheric heights, via a local dynamo or from small-scale flux emergence events. However, most of this small-scale magnetic field may not expan

Abhibasu Sen, Karabi Dutta Chaudhury

This non-linear relationship in the joint time-frequency domain has been studied for the Indian National Stock Exchange (NSE) with the international Gold price and WTI Crude Price being converted from Dollar to Indian National Rupee based on that week's closing exchange rate. Though a good correlation was obtained during some period, but as a whole no such c

David Sumner Lipham

We construct two connected plane sets which can be embedded into rational curves. The first is a biconnected set with a dispersion point. It answers a question of Joachim Grispolakis. The second is indecomposable. Both examples are completely metrizable.

R. Muthuganesan, V. K. Chandrasekar

Geometric discord, a measure of quantumness of bipartite system, captures minimal nonlocal effects of a quantum state due to locally invariant von Neumann projective measurements. Original version of this measure is suffered by the local ancilla problem. In this article, we propose a new version of geometric discord using affinity. This quantity satisfies al

Louis Chartrand, Mohamed Bouguessa

In the last decades, philosophers have begun using empirical data for conceptual analysis, but corpus-based conceptual analysis has so far failed to develop, in part because of the absence of reliable methods to automatically detect concepts in textual data. Previous attempts have shown that topic models can constitute efficient concept detection heuristics,

Angli Liu, Jingfei Du, Veselin Stoyanov

Traditional language models are unable to efficiently model entity names observed in text. All but the most popular named entities appear infrequently in text providing insufficient context. Recent efforts have recognized that context can be generalized between entity names that share the same type (e.g., \emph{person} or \emph{location}) and have equipped l

Changhao Chen, Igor E. Shparlinski

The authors have recently obtained a lower bound of the Hausdorff dimension of the sets of vectors $(x_1, \ldots, x_d)\in [0,1)^d$ with large Weyl sums, namely of vectors for which $$ \left| \sum_{n=1}^{N}\exp(2πi (x_1 n+\ldots +x_d n^{d})) \right| \ge N^α $$ for infinitely many integers $N \ge 1$. Here we obtain an upper bound for the Hausdorff dimension of

Shun Fujii, Shuya Tanaka, Mika Fuchida, Hikaru Amano

In this Letter, we report phase-matched four-wave mixing separated by over one-octave in a dispersion engineered crystalline microresonator. Experimental and numerical results presented here confirm that primary sidebands were generated with a frequency shift up to 140 THz, and that secondary sidebands formed a localized comb structure, known as a clustered

Danupon Nanongkai, Thatchaphol Saranurak, Sorrachai Yingchareonthawornchai

Vertex connectivity a classic extensively-studied problem. Given an integer $k$, its goal is to decide if an $n$-node $m$-edge graph can be disconnected by removing $k$ vertices. Although a linear-time algorithm was postulated since 1974 [Aho, Hopcroft and Ullman], and despite its sibling problem of edge connectivity being resolved over two decades ago [Karg

JongHae Keum, Keiji Oguiso

We will show that there is a smooth complex projective surface, birational to some Enriques surface, such that the automorphism group is discrete but not finitely generated.

Kui Fu, Peipei Shi, Yafei Song, Shiming Ge

Large convolutional neural network models have recently demonstrated impressive performance on video attention prediction. Conventionally, these models are with intensive computation and large memory. To address these issues, we design an extremely light-weight network with ultrafast speed, named UVA-Net. The network is constructed based on depth-wise convol

Yauhen Babakhin, Artsiom Sanakoyeu, Hirotoshi Kitamura

Seismic image analysis plays a crucial role in a wide range of industrial applications and has been receiving significant attention. One of the essential challenges of seismic imaging is detecting subsurface salt structure which is indispensable for identification of hydrocarbon reservoirs and drill path planning. Unfortunately, exact identification of large

Yulun Zhang, Chen Fang, Yilin Wang, Zhaowen Wang

An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices. Alternative approaches have represented styles by decomposing them into local pixel or neural patches. Despite the recent progress, most existing methods treat the semantic patterns of st

Zhao Jin, Hanpin Wang, Lei Zhang, Bowen Zhang

Owing to the massive growth in the storage demands of big data, Cloud Storage Systems (CSSs) have been put forward to improve the storage capacity. Compared with traditional storage systems, CSSs have lots of advantages, such as higher capacity, lower cost, and easier scalability. But they are also with higher complexity. In order to ensure CSSs to be reliab

Clara Bradley, James Owen Weatherall

We address a recent proposal concerning 'surplus structure' due to Nguyen et al. ['Why Surplus Structure is Not Superfluous.' Br. J. Phi. Sci. Forthcoming.] We argue that the sense of 'surplus structure' captured by their formal criterion is importantly different from---and in a sense, opposite to---another sense of 'surplus struc

Yusaku Tiba

In this paper, we study cohomology groups of vector bundles on neighborhoods of a non-pluriharmonic locus in Stein manifolds and in projective manifolds. By using our results, we show variants of the Lefschetz hyperplane theorem.

Ted Jacobson, Phuc Nguyen

We argue that the resolution to the black hole information paradox lies in a proper accounting of the implications of diffeomorphism invariance for the Hilbert space and observables of quantum gravity. The setting of asymptotically Anti-de Sitter spacetime is adopted for most of the paper, but in the framework of canonical quantum gravity, without invoking A

Yang Li, Shihao Ji

We consider network sparsification as an $L_0$-norm regularized binary optimization problem, where each unit of a neural network (e.g., weight, neuron, or channel, etc.) is attached with a stochastic binary gate, whose parameters are jointly optimized with original network parameters. The Augment-Reinforce-Merge (ARM), a recently proposed unbiased gradient e

Karthik Gajulapalli, James Liu, Tung Mai, Vijay V. Vazirani

We address the following dynamic version of the school choice question: a city, named City, admits students in two temporally-separated rounds, denoted $\mathcal{R}_1$ and $\mathcal{R}_2$. In round $\mathcal{R}_1$, the capacity of each school is fixed and mechanism $\mathcal{M}_1$ finds a student optimal stable matching. In round $\mathcal{R}_2$, certain par

Maozheng Zhao, Le Hou, Han Le, Dimitris Samaras

For the task of semantic segmentation, high-resolution (pixel-level) ground truth is very expensive to collect, especially for high resolution images such as gigapixel pathology images. On the other hand, collecting low resolution labels (labels for a block of pixels) for these high resolution images is much more cost efficient. Conventional methods trained

Hao Peng, Ankur P. Parikh, Manaal Faruqui, Bhuwan Dhingra

We propose a novel conditioned text generation model. It draws inspiration from traditional template-based text generation techniques, where the source provides the content (i.e., what to say), and the template influences how to say it. Building on the successful encoder-decoder paradigm, it first encodes the content representation from the given input text;

Takuya Okabe, Jin Yoshimura

This study presents a long-term alternative formula for stock price variation described by a geometric Brownian motion on the basis of median instead of mean or expected values. The proposed method is motivated by the observation made in remote fields, where optimality of bet-hedging or diversification strategies is explained based on a measure different fro

Mikhail Slutskii, Tameem Albash, Lev Barash, Itay Hen

The quantum adiabatic unstructured search algorithm is one of only a handful of quantum adiabatic optimization algorithms to exhibit provable speedups over their classical counterparts. With no fault tolerance theorems to guarantee the resilience of such algorithms against errors, understanding the impact of imperfections on their performance is of both scie

Ruoyang Zhang, Malay Ghosh

In recent years, shrinkage priors have received much attention in high-dimensional data analysis from a Bayesian perspective. Compared with widely used spike-and-slab priors, shrinkage priors have better computational efficiency. But the theoretical properties, especially posterior contraction rate, which is important in uncertainty quantification, are not e

Junaid Malik, Serkan Kiranyaz, Riyadh Al-Raoush, Olivier Monga

Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves around primitive techniques based on global or local adaptive thresholding that have known common drawbacks in image segmentation. Moreover,

L. P. Kaptari, A. V. Kotikov, N. Yu. Chernikova, Pengming Zhang

We present a method to extract, in the leading and next-to-leading order approximations, the longitudinal deep-inelastic scattering structure function FL(x,Q2) from the experimental data by relying on a Froissart-bounded parametrization of the transversal structure function F2(x,Q2) and, partially, on the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi equations.

C. Alduino, F. Alessandria, M. Balata, D. Biare

The CUORE experiment is the world's largest bolometric experiment. The detector consists of an array of 988 TeO2 crystals, for a total mass of 742 kg. CUORE is presently taking data at the Laboratori Nazionali del Gran Sasso, Italy, searching for the neutrinoless double beta decay of 130Te. A large custom cryogen-free cryostat allows reaching and maintai

Xudong Wang, Zhaowei Cai, Dashan Gao, Nuno Vasconcelos

Despite increasing efforts on universal representations for visual recognition, few have addressed object detection. In this paper, we develop an effective and efficient universal object detection system that is capable of working on various image domains, from human faces and traffic signs to medical CT images. Unlike multi-domain models, this universal mod

Ruadhan O'Flanagan

The sets used to construct other mathematical objects are pure sets, which means that all of their elements are sets, which are themselves pure. One set may therefore be within another, not as an element, but as an element of an element, or even deeper, inside several layers of sets within sets. The introduction of the term constituent to describe a set whic

D. Kempen, A. Piccolroaz, D. Bigoni

An elastic-visco-plastic thermomechanical model for the simulation of cold forming and subsequent sintering of ceramic powders is introduced and based on micromechanical modelling of the compaction process of granulates. Micromechanics leads to an upper-bound estimate of the compaction curve of a granular material, which compares well with other models and f

C. Katsarelis, O. Glushko, C. Tonkin, M. S. Kennedy

Printing of metallic films has been preferred for roll-to-roll processes over vacuum technologies due to faster processing times and lower processing costs. Films can be produced by depositing inks containing suspended metallic particles within a solvent and then heating the films to both remove the solvent and sinter the particles. The resulting printed str

Nguyen Anh Khoa Doan, Wolfgang Polifke, Luca Magri

We propose a physics-informed Echo State Network (ESN) to predict the evolution of chaotic systems. Compared to conventional ESNs, the physics-informed ESNs are trained to solve supervised learning tasks while ensuring that their predictions do not violate physical laws. This is achieved by introducing an additional loss function during the training of the E

Bestoun S. Ahmed

Combinatorial interaction testing has been addressed as an effective software testing technique recently. It shows its ability to reduce the number of test cases that have to be considered for software-under-test by taking the combinations of parameters as an interaction of input. This combination could be considered as input-configuration of different softw

Adnan I. Yaqzan, Issam W. Damaj, Rached N. Zantout

Modern powerful reconfigurable systems are suited in the implementation of various data-stream, data-parallel, and other applications. An application that needs real-time, fast, and reliable data processing is the global positioning system (GPS)-based vehicle tracking system (VTS). In this paper, we build on a recently produced VTS (The Aram Locator) offerin

Kenta Hama, Takashi Matsubara, Kuniaki Uehara, Jianfei Cai

With the wide development of black-box machine learning algorithms, particularly deep neural network (DNN), the practical demand for the reliability assessment is rapidly rising. On the basis of the concept that `Bayesian deep learning knows what it does not know,' the uncertainty of DNN outputs has been investigated as a reliability measure for the clas

Zihao Liu, Xiaowei Xu, Tao Liu, Qi Liu

Cloud based medical image analysis has become popular recently due to the high computation complexities of various deep neural network (DNN) based frameworks and the increasingly large volume of medical images that need to be processed. It has been demonstrated that for medical images the transmission from local to clouds is much more expensive than the comp

Adil Rajput

The topic of clickbait has garnered lot of attention since the advent of social media. Meriam-Webster defines Clickbait as something designed to make readers want to click on a hyperlink especially when the link leads to content of dubious value or interest. Clickbait is used synonymously with terms with negative connotations such as yellow journalism, tablo

Mohsen Annabestani, Mahdi Fardmanesh

This paper provides a detailed review on applications of ionic electroactive polymer (i-EAP) soft actuators as active elements of microfluidic micropumps, microvalves, and micromixers. The related works that have so far been presented by various research groups in the field have been collected in this review, which in the presented comparative procedure here

Issam Damaj, Mahmoud Imdoukh, Rached Zantout

Morphological analysis in the Arabic language is computationally intensive, has numerous forms and rules, and is intrinsically parallel. The investigation presented in this paper confirms that the effective development of parallel algorithms and the derivation of corresponding processors in hardware enable implementations with appealing performance character

Jorge C. Leitao, Joao M. V. P. Lopes, Eduardo G. Altmann

Rare events in non-linear dynamical systems are difficult to sample because of the sensitivity to perturbations of initial conditions and of complex landscapes in phase space. Here we discuss strategies to control these difficulties and succeed in obtainining an efficient sampling within a Metropolis-Hastings Monte Carlo framework. After reviewing previous s

Amirreza Nickkar, Young-Jae Lee

Autonomous vehicles (AVs) are about to be used in transportation systems in the near future. To increase the level of safety and throughput of these vehicles, dedicated lanes for AVs have been suggested in past studies as exclusive mobility infrastructure for these types of vehicles. Although these lanes can bring obvious advantages in a transportation netwo

Ali Behnoudfar, Seyyed Hossein Hosseini Zahani, Mojtaba Hatami, Mahmoud Naghibzadeh

The present volume contains the proceedings of RTEST WiP 2018, chaired by Marco Caccamo, University of Illinois at Urbana-Champaign. This event has been organized by the School of Electrical and Computer Engineering at the University of Tehran, in conjunction with the Department of Computer Engineering at Sharif University of Technology, Tehran, Iran. The to

Yu Zheng, Guang-Can Guo, Fang-Wen Sun

The motion control of a levitated nanoparticle plays a central role in optical levitation for fundamental studies and practical applications. Here, we presented a digital parametric feedback cooling based on switching between two trapping laser intensity levels with square wave modulations. The effects of modulation depth and modulation signal phase on the c

Young-Jae Lee, Amirreza Nickkar, Mana Meskar

Improving accessibility is one of the major issues in rural and suburban transportation. With the recent technological improvement of automated vehicles, it is expected that automated demand responsive transit and automated demand responsive feeder transit potentially will be options to improve mobility in rural areas. One of the main concerns for the optima

Juan Augusto Maya, Leonardo Rey Vega

In this article, we consider the detection of a localized source emitting a signal using a wireless sensor network (WSN). We consider that geographically distributed sensor nodes obtain energy measurements and compute cooperatively and in a distributed manner a statistic to decide if the source is present or absent without the need of a central node or fusio

Yiming Pan, Avraham Gover

In this article, we present a unified reciprocal quantum electrodynamics (QED) formulation of quantum light-matter interaction. For electron-light interactions, we bridge the underlying theories of Photon-Induced Near-field Electron Microscopy (PINEM), Laser-induced Particle Accelerators and radiation sources, such as Free Electron Laser (FEL), transition ra

Jonas P. Pereira, Jaziel G. Coelho, Rafael C. R. de Lima

We discuss some aspects of Pereira et al. (2018) concerning magnetars described by nonlinear theories of the electromagnetism and make the case for the Born-Infeld Lagrangian. We focus on the increase of toroidal magnetic fields in these systems with respect to ordinary magnetars and the subsequent increase of gravitational wave production. In summary, nonli

Jinwen Song, Shuai Yuan, Jinsong Xia

Photodetectors at telecommunications-band with high efficiency and high speed are becoming increasingly important as the booming of big data, 5G, internet of things, cloud computing, artificial intelligence and relevent applications. Silicon-based Germanium photodetectors exhibit great potential in reducing the cost and power dissipation, due to its compatib

Xu-Sheng Xu, Hao Zhang, Min Wang, Dong Ruan

The resonance frequency of an optical whispering gallery mode (WGM) microcavity is extremely important in its various applications. Many efforts have been made to fine tune this parameter. Here, we report the design and implementation of a function resonance tuner of an optical microcavity with resolution about 650 kHz (7 pm @ 1450 nm band), 20% of the optic

Emiliano Cristiani, Daniele Peri

In this paper, we deal with a size-variable group of pedestrians moving in a unknown confined environment and searching for an exit. Pedestrian dynamics are simulated by means of a recently introduced microscopic (agent-based) model, characterized by an exploration phase and an egress phase. First, we study the model to reveal the role of its main parameters

Stéphane Brûlé, Stefan Enoch, Sébastien Guenneau

The discovery of photonic crystals thirty years ago, in conjunction with research advances in plasmonics and metamaterials, has inspired the concept of decameter scale metasurfaces, coined seismic metamaterials, for an enhanced control of surface (Love and Rayleigh) and bulk (shear and pressure) elastodynamic waves. The powerful mathematical tools of coordin

Simon Stephan, Martin Thomas Horsch, Jadran Vrabec, Hans Hasse

The MolMod database is presented, which is openly accessible at http://molmod.boltzmann-zuse.de/ and contains presently intermolecular force fields for over 150 pure fluids. It was developed and is maintained by the Boltzmann-Zuse Society for Computational Molecular Engineering (BZS). The set of molecular models in the MolMod database provides a coherent fra

Koray Düztaş

We construct thought experiments involving the perturbations of Kerr-Newman black holes by neutral test fields to evaluate the validity of the weak form of the cosmic censorship conjecture. We first show that neglecting backreaction effects, extremal Kerr-Newman black holes which satisfy the condition $(J^2/M^4)<(1/3)$ can be overspun by scalar fields. This

Jorge Llombart, Dayana Ribas, Antonio Miguel, Luis Vicente

This paper proposes a speech enhancement method which exploits the high potential of residual connections in a Wide Residual Network architecture. This is supported on single dimensional convolutions computed alongside the time domain, which is a powerful approach to process contextually correlated representations through the temporal domain, such as speech

Kai Graban, Eva Schweickert, Robert J. Martin, Patrizio Neff

We provide a faithful translation of Hans Richter&#39;s important 1948 paper &#34;Das isotrope Elastizitätsgesetz&#34; from its original German version into English. Our introduction summarizes Richter&#39;s achievements.

Tullio Traverso, Luca Magri

When the heat released by a flame is sufficiently in phase with the acoustic pressure, a self-excited thermoacoustic oscillation can arise. These nonlinear oscillations are one of the biggest challenges faced in the design of safe and reliable gas turbines and rocket motors. In the worst-case scenario, uncontrolled thermoacoustic oscillations can shake an en

Roderick Sutherland

The ontology proposed in this paper is aimed at demonstrating that it is possible to understand the counter-intuitive predictions of quantum mechanics while still retaining much of the framework underlying classical physics, the implication being that it is better to avoid wandering into unnecessarily speculative realms without the support of conclusive evid

Samuel F. Way, Santiago Gil, Ian Anderson, Aaron Clauset

Musical tastes reflect our unique values and experiences, our relationships with others, and the places where we live. But as each of these things changes, do our tastes also change to reflect the present, or remain fixed, reflecting our past? Here, we investigate how where a person lives shapes their musical preferences, using geographic relocation to const

Daniel Reyes, Nei Lopes, Mucio A. Continentino, Christopher Thomas

In this work we study a two-band model of a superconductor in a square lattice. One band is narrow in energy and includes local Coulomb correlations between its quasi-particles. Pairing occurs in this band due to nearest neighbor attractive interactions. Extended s-wave, as well as d-wave symmetries of the superconducting order parameter are considered. The

Juliette Bruce

We study the asymptotic non-vanishing of syzygies for products of projective spaces. Generalizing the monomial methods of Ein, Erman, and Lazarsfeld \cite{einErmanLazarsfeld16} we give an explicit range in which the graded Betti numbers of $\mathbb{P}^{n_1}\times \mathbb{P}^{n_2}$ embedded by $\mathcal{O}_{\mathbb{P}^{n_1}\times\mathbb{P}^{n_2}}(d_1,d_2)$ ar

O. I. Kartavtsev, A. V. Malykh

Properties of two identical particles of mass $m$ and a distinct particle of mass $m_1$ in the universal low-energy limit of zero-range two-body interaction are studied in different sectors of total angular momentum $L$ and parity $P$. For the unambiguous formulation of the problem in the interval $μ_r(L^P) < m/m_1 \le μ_c(L^P)$ ($μ_r(1^-) \approx 8.619$ and

Jakub Byszewski, Gunther Cornelissen, Marc Houben, Lois van der Meijden

We study fixed points of iterates of dynamically affine maps (a generalisation of Lattès maps) over algebraically closed fields of positive characteristic $p$. We present and study certain hypotheses that imply a dichotomy for the Artin-Mazur zeta function of the dynamical system: it is either rational or non-holonomic, depending on specific characteristics

J. J. Esteve-Paredes, Sahar Pakdel, J. J. Palacios

We predict that long-lived excitons with very large binding energies can also exist in a single or few layers of monochalcogenides such as GaSe. Our theoretical study shows that excitons confined by a radial local strain field are unable to recombine despite of electrons and holes co-existing in space. The localized single-particle states are calculated in t

Maria Bampa

The increased adoption of Electronic Health Records(EHRs) has brought changes to the way the patient care is carried out. The rich heterogeneous and temporal data space stored in EHRs can be leveraged by machine learning models to capture the underlying information and make clinically relevant predictions. This can be exploited to support public health activ

Henok Yared Agizew

Viral hepatitis is the regularly found health problem throughout the world among other easily transmitted diseases, such as tuberculosis, human immune virus, malaria and so on. Among all hepatitis viruses, the uppermost numbers of deaths are result from the long-lasting hepatitis C infection or long-lasting hepatitis B. In order to develop this system, the k

Th. Caby, D. Faranda, S. Vaienti, P. Yiou

The extremal index is a quantity introduced in extreme value theory to measure the presence of clusters of exceedances. In the dynamical systems framework, it provides important information about the dynamics of the underlying systems. In this paper we provide a review of the meaning of the extremal index in dynamical systems. Depending on the observables us

Freek Roelofs, Heino Falcke, Christiaan Brinkerink, Monika Mościbrodzka

It has been proposed that Very Long Baseline Interferometry (VLBI) at sub-millimeter waves will allow us to image the shadow of the black hole in the center of our Milky Way, Sagittarius A* (Sgr A*), and thereby test basic predictions of general relativity. This paper presents imaging simulations of a new Space VLBI mission concept. An initial design study o

Luan Tran, Feng Liu, Xiaoming Liu

Embedding 3D morphable basis functions into deep neural networks opens great potential for models with better representation power. However, to faithfully learn those models from an image collection, it requires strong regularization to overcome ambiguities involved in the learning process. This critically prevents us from learning high fidelity face models

Marko Jereminov, Athanasios Terzakis, Martin Wagner, Amritanshu Pandey

Recent advances have shown that the circuit simulation algorithms that allow for solving highly nonlinear circuits of over one billion variables can be applicable to power system simulation and optimization problems through the use of an equivalent circuit formulation. It was demonstrated that large-scale (80k+ buses) power flow simulations can be robustly s

Wendy K. Caldwell, Geoffrey Fairchild, Sara Y. Del Valle

Influenza epidemics result in a public health and economic burden around the globe. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1-2 weeks. A means of obtaining real-time data and forecasting future outbreaks is desirable to provide more timely responses to influenza epidemics. In this work, we present the fi

Marko Jereminov, Aleksandar Jovicic, Martin R. Wagner, Gabriela Hug

An Equivalent Circuit Programming (ECP) approach that expresses the optimality conditions of an optimization problem in terms of an equivalent circuit model and uses circuit simulation techniques to solve for an optimal solution, is applied to the state estimation problem for power systems. The benefits of using an equivalent circuit formulation for incorpor

Anshuman Baruah, Atri Deshamukhya

Wormhole solutions in classical General Relativity are unstable and hence non traversable. Morris and Thorne discovered a traversable wormhole solution that required the energy momentum tensor of matter sources to violate various energy conditions and are out of the purview of the standard model of particle physics. The search for traversable wormhole soluti

Ziyuan Zhang, Luan Tran, Xi Yin, Yousef Atoum

Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as the gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and view angle. To remedy this

P. Bärtschi, C. Galloni, C. Lange, B. Kilminster

The reconstruction of the invariant mass of $τ$ lepton pairs is important for analyses containing Higgs and Z bosons decaying to $τ^{+}τ^{-}$, but highly challenging due to the neutrinos from the $τ$ lepton decays, which cannot be measured in the detector. In this paper, we demonstrate how artificial neural networks can be used to reconstruct the mass of a d

Andrea Albino, Stefano Benci, Lorenzo Tesi, Matteo Atzori

Paramagnetic molecules can show long spin-coherence times, which make them good candidates as quantum bits. Reducing the efficiency of the spin-phonon interaction is the primary challenge towards achieving long coherence times over a wide temperature range in soft molecular lattices. The lack of a microscopic understanding about the role of vibrations in spi

Massimiliano Gei, Kudzai C. K. Mutasa

This paper is concerned with the optimisation of the actuation response of electro-elastic, rank-two laminates obtained laminating a core rank-one composite with a soft phase which constitutes the shell. The analysis is performed for two classes of composites that are subjected to traction-free boundary-value problems. The results are compared with those com

Tal Kachman, Michal Moshkovitz, Michal Rosen-Zvi

Deep neural networks have become the default choice for many of the machine learning tasks such as classification and regression. Dropout, a method commonly used to improve the convergence of deep neural networks, generates an ensemble of thinned networks with extensive weight sharing. Recent studies that dropout can be viewed as an approximate variational i