October 2020 arXiv papers — page 67

Christopher Lazarus, James G. Lopez, Mykel J. Kochenderfer

The airworthiness and safety of a non-pedigreed autopilot must be verified, but the cost to formally do so can be prohibitive. We can bypass formal verification of non-pedigreed components by incorporating Runtime Safety Assurance (RTSA) as mechanism to ensure safety. RTSA consists of a meta-controller that observes the inputs and outputs of a non-pedigreed

Eshed Ram, Yuval Cassuto

We study spatially coupled LDPC codes that allow access to sub-blocks much smaller than the full code block. Sub-block access is realized by a semi-global decoder that decodes a chosen target sub-block by only accessing the target, plus a prescribed number of helper sub-blocks adjacent in the code chain. This paper develops a theoretical methodology for anal

Mohammad Hamghalam, Baiying Lei, Tianfu Wang

Structural magnetic resonance imaging (MRI) has been widely utilized for analysis and diagnosis of brain diseases. Automatic segmentation of brain tumors is a challenging task for computer-aided diagnosis due to low-tissue contrast in the tumor subregions. To overcome this, we devise a novel pixel-wise segmentation framework through a convolutional 3D to 2D

Q. Abarr, H. Awaki, M. G. Baring, R. Bose

XL-Calibur is a hard X-ray (15-80 keV) polarimetry mission operating from a stabilised balloon-borne platform in the stratosphere. It builds on heritage from the X-Calibur mission, which observed the accreting neutron star GX 301-2 from Antarctica, between December 29th 2018 and January 1st 2019. The XL-Calibur design incorporates an X-ray mirror, which focu

Darshana Sedera, Sachithra Lokuge

In March 2018, a series of anti-social and racial riots in Sri Lanka led to a government-controlled ban of all social media use in the country for 14 days. This nation-wide ban included the use of all social media such as Facebook, Twitter and communication apps like WhatsApp, Viber and WeChat. Until the day of the sanctions, a population of 23 million in Sr

Xinjie Fan, Shujian Zhang, Bo Chen, Mingyuan Zhou

Attention modules, as simple and effective tools, have not only enabled deep neural networks to achieve state-of-the-art results in many domains, but also enhanced their interpretability. Most current models use deterministic attention modules due to their simplicity and ease of optimization. Stochastic counterparts, on the other hand, are less popular despi

Victor De la Pena, Paul Doukhan, Yahia Salhi

Taylor's power law (or fluctuation scaling) states that on comparable populations, the variance of each sample is approximately proportional to a power of the mean of the population. It has been shown to hold by empirical observations in a broad class of disciplines including demography, biology, economics, physics and mathematics. In particular, it has

Pranay Dighe, Erik Marchi, Srikanth Vishnubhotla, Sachin Kajarekar

In this paper, we address the task of determining whether a given utterance is directed towards a voice-enabled smart-assistant device or not. An undirected utterance is termed as a "false trigger" and false trigger mitigation (FTM) is essential for designing a privacy-centric non-intrusive smart assistant. The directedness of an utterance can be ide

Francesco Cordero, Floriana Craciun, Francesco Trequattrini, Amanda Generosi

The phase transitions between the various polymorphs of FAPbI$_{3}$ (FAPI, FA = formamidinium CH(NH$_{2}$)$_{2}^+$) are studied by anelastic, dielectric and X--ray diffraction measurements on samples pressed from $δ-$FAPI (2H phase) yellow powder. The samples become orange after application of as little as 0.2~GPa, which has been explained in terms of partia

Georgia Salanti, Adriani Nikolakopoulou, Orestis Efthimou, Dimitris Mavridis

Background: Comparative effectiveness research using network meta-analysis can present a hierarchy of competing treatments, from the least to most preferable option. However, the research question associated with the hierarchy of multiple interventions is never clearly defined in published reviews. Methods and Results: We introduce the notion of a treatment

Patrick Schulte, Rana Ali Amjad, Thomas Wiegart, Gerhard Kramer

Several applications in communication, control, and learning require approximating target distributions to within small informational divergence (I-divergence). The additional requirement of invertibility usually leads to using encoders that are one-to-one mappings, also known as distribution matchers. However, even the best one-to-one encoders have I-diverg

Will Dana

Inspired by the infinite families of finite and affine root systems, we consider a "stretching" operation on general crystallographic root systems which, on the level of Coxeter diagrams, replaces a vertex with a path of unlabeled edges. We embed a root system into its stretched versions using a similar operation on individual roots. For a fixed root

Gregory Coppola

One of the most expensive parts of maintaining a modern information-sharing platform (e.g., web search, social network) is the task of content-moderation-at-scale. Content moderation is the binary task of determining whether or not a given user-created message meets the editorial team's content guidelines for the site. The challenge is that the number of

Milad Farsi, Jun Liu

Model-based reinforcement learning techniques accelerate the learning task by employing a transition model to make predictions. In this paper, a model-based learning approach is presented that iteratively computes the optimal value function based on the most recent update of the model. Assuming a structured continuous-time model of the system in terms of a s

Hoang Van, David Kauchak, Gondy Leroy

The goal of text simplification (TS) is to transform difficult text into a version that is easier to understand and more broadly accessible to a wide variety of readers. In some domains, such as healthcare, fully automated approaches cannot be used since information must be accurately preserved. Instead, semi-automated approaches can be used that assist a hu

Yupeng Jiang, Yong Li, Yipeng Zhou, Xi Zheng

In federated learning, machine learning and deep learning models are trained globally on distributed devices. The state-of-the-art privacy-preserving technique in the context of federated learning is user-level differential privacy. However, such a mechanism is vulnerable to some specific model poisoning attacks such as Sybil attacks. A malicious adversary c

Leighton Wilson, Robert Krasny

The Poisson-Boltzmann (PB) implicit solvent model is a popular framework for studying the electrostatics of biomolecules immersed in water with dissolved salt. In this model the dielectric interface between the biomolecule and solvent is often taken to be the molecular surface or solvent-excluded surface (SES), and the quality of the SES triangulation is cri

Omar Nassef, Luis Sequeira, Elias Salam, Toktam Mahmoodi

In this paper, a framework for lane merge coordination is presented utilising a centralised system, for connected vehicles. The delivery of trajectory recommendations to the connected vehicles on the road is based on a Traffic Orchestrator and a Data Fusion as the main components. Deep Reinforcement Learning and data analysis is used to predict trajectory re

Sangwoo Cho, Kaiqiang Song, Chen Li, Dong Yu

Amongst the best means to summarize is highlighting. In this paper, we aim to generate summary highlights to be overlaid on the original documents to make it easier for readers to sift through a large amount of text. The method allows summaries to be understood in context to prevent a summarizer from distorting the original meaning, of which abstractive summ

Sebastian Sanokowski

The brain cortex, which processes visual, auditory and sensory data in the brain, is known to have many recurrent connections within its layers and from higher to lower layers. But, in the case of machine learning with neural networks, it is generally assumed that strict feed-forward architectures are suitable for static input data, such as images, whereas r

Khushal Sethi, Manan Suri

Edge caching via the placement of distributed storages throughout the network is a promising solution to reduce latency and network costs of content delivery. With the advent of the upcoming 5G future, billions of F-RAN (Fog-Radio Access Network) nodes will created and used for for the purpose of Edge Caching. Hence, the total amount of memory deployed at th

Shihshu Walter Wei

We introduce Condition W $\,$(1.2) for a smooth differential form $ω$ on a complete noncompact Riemannian manifold $M$. We prove that $ω$ is a harmonic form on $M$ if and only if $ω$ is both closed and co-closed on $M\, ,$ where $ω$ has $2$-balanced growth either for $q=2$, or for $1 < q(\ne 2) < 3\, $ with $ω$ satisfying Condition W $\,$(1.2). In particular

Varun Kompella, Roberto Capobianco, Stacy Jong, Jonathan Browne

The year 2020 has seen the COVID-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world are faced with the challenge of protecting public health, while keeping the economy running to the greatest extent possible. Epidemiological models provide insight into the spread of these types of diseases and predict the

Nelson P. K. Chan, Bayu Jayawardhana, Hector Garcia de Marina

This paper focuses on the stability analysis of a formation shape displayed by a team of mobile robots that uses heterogeneous sensing mechanism. Depending on the convenience and reliability of the local information, each robot utilizes the popular gradient-based control law which, in this paper, is either the distance-based or the bearing-only formation con

Tomer Weiss, Ilkay Yildiz, Nitin Agarwal, Esra Ataer-Cansizoglu

Creating realistic styled spaces is a complex task, which involves design know-how for what furniture pieces go well together. Interior style follows abstract rules involving color, geometry and other visual elements. Following such rules, users manually select similar-style items from large repositories of 3D furniture models, a process which is both labori

Peidong Wang, Zhuo Chen, DeLiang Wang, Jinyu Li

We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation. SSUSIES contains two methods, speaker separation using speaker inventories (SSUSI) and speaker separation using estimated speech (SSUES). SSUSI performs speaker separation with the help o

Kunihiko Tanaka, Makoto Nagai, Kazuhisa Kamegai, Takahiro Iino

We report a statistical analysis exploring the origin of the overall low star formation efficiency (SFE) of the Galactic central molecular zone (CMZ) and the SFE diversity among the CMZ clouds using a wide-field HCN $J$=4-3 map, whose optically thin critical density ($\sim10^7\,\mathrm{cm}^{-3}$) is the highest among the tracers ever used in CMZ surveys. Log

K. Ward-Duong, J. Patience, K. Follette, R. J. De Rosa

We present new near-infrared Gemini Planet Imager (GPI) spectroscopy of HD 206893 B, a substellar companion orbiting within the debris disk of its F5V star. The $J$, $H$, $K1$, and $K2$ spectra from GPI demonstrate the extraordinarily red colors of the object, confirming it as the reddest substellar object observed to date. The significant flux increase thro

Louise Welsh, Ryan Cooke, Michele Fumagalli

We investigate the intrinsic scatter in the chemical abundances of a sample of metal-poor ([Fe/H]<-2.5) Milky Way halo stars. We draw our sample from four historic surveys and focus our attention on the stellar Mg, Ca, Ni, and Fe abundances. Using these elements, we investigate the chemical enrichment of these metal-poor stars using a model of stochastic che

Andrew J. Winter, J. M. Diederik Kruijssen, Steven N. Longmore, Mélanie Chevance

Planet formation is generally described in terms of a system containing the host star and a protoplanetary disc, of which the internal properties (e.g. mass and metallicity) determine the properties of the resulting planetary system. However, (proto)planetary systems are predicted and observed to be affected by the spatially-clustered stellar formation envir

Hyungro Lee, Andre Merzky, Li Tan, Mikhail Titov

COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE recently established the Medical Therapeutics project as part of the National Virtual Biotechnology Laboratory, and tasked it with creating the computational infrastructure and metho

Leonhard Horstmeyer, Christian Kuehn, Stefan Thurner

We study the relative importance of two key control measures for epidemic spreading: endogenous social self-distancing and exogenous imposed quarantine. We use the framework of adaptive networks, moment-closure, and ordinary differential equations (ODEs) to introduce several novel models based upon susceptible-infected-recovered (SIR) dynamics. First, we com

K. Mahesh Krishna, P. Sam Johnson

We begin the study of characterizations of recently defined approximate Schauder frame (ASF) and its duals for separable Banach spaces. We show that, under some conditions, both ASF and its dual frames can be characterized for Banach spaces. We also give an operator-theoretic characterization for similarity of ASFs. Our results encode the results of Holub, L

Mark Rubin

Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do a

Cheng-Qun Pang, Lei Huang, Duo-jie Jia, Tian-Jie Zhang

Analytic solutions for the energy eigenvalues are obtained from a confined potentials of the form $br$ in 3 dimensions. The confinement is effected by linear term which is a very important part in Cornell potential. The analytic eigenvalues and numerical solutions are exactly matched.

Sakina Hansen, Christopher J. Conselice, Amelia Fraser-McKelvie, Leonardo Ferreira

Using deep machine learning we show that the internal velocities of galaxies can be retrieved from optical images trained using 4596 systems observed with the SDSS-MaNGA survey. Using only $i$-band images we show that the velocity dispersions and the rotational velocities of galaxies can be measured to an accuracy of 29 km~$\rm{s}^{-1}$ and 69 km~$\rm{s}^{-1

Chen-Hsuan Lin, Chaoyang Wang, Simon Lucey

Dense 3D object reconstruction from a single image has recently witnessed remarkable advances, but supervising neural networks with ground-truth 3D shapes is impractical due to the laborious process of creating paired image-shape datasets. Recent efforts have turned to learning 3D reconstruction without 3D supervision from RGB images with annotated 2D silhou

Matthew Francis-Landau, Tim Vieira, Jason Eisner

We present a scheme for translating logic programs, which may use aggregation and arithmetic, into algebraic expressions that denote bag relations over ground terms of the Herbrand universe. To evaluate queries against these relations, we develop an operational semantics based on term rewriting of the algebraic expressions. This approach can exploit arithmet

Samy Jelassi, Aaron Defazio

First-order stochastic optimization methods are currently the most widely used class of methods for training deep neural networks. However, the choice of the optimizer has become an ad-hoc rule that can significantly affect the performance. For instance, SGD with momentum (SGD+M) is typically used in computer vision (CV) and Adam is used for training transfo

William Gantt, Benjamin Kane, Aaron Steven White

There is growing evidence that the prevalence of disagreement in the raw annotations used to construct natural language inference datasets makes the common practice of aggregating those annotations to a single label problematic. We propose a generic method that allows one to skip the aggregation step and train on the raw annotations directly without subjecti

Tang Liu, Daniela Tuninetti

We study the secure decentralized Pliable Index CODing (PICOD) problem with circular side information sets at the users. The security constraint forbids every user to decode more than one message while a decentralized setting means there is no central transmitter in the system. Compared to the secure but centralized version of the problem, a converse bound f

Jelena Sedlar, Riste Škrekovski

In a graph G, the cardinality of the smallest ordered set of vertices that distinguishes every element of V (G)[E(G) is called the mixed metric dimension of G. In this paper we first establish the exact value of the mixed metric dimension of a unicycic graph G which is derived from the structure of G. We further consider graphs G with edge disjoint cycles in

Daniel Robert-Nicoud, Bruno Vallette

We present a novel approach to the problem of integrating homotopy Lie algebras by representing the Maurer-Cartan space functor with a universal cosimplicial object. This recovers Getzler&#39;s original functor but allows us to prove the existence of additional, previously unknown, structures and properties. Namely, we introduce a well-behaved left adjoint f

Jeremy Cohen, Mark Woodbridge

The term Research Software Engineer (RSE) was first used in the UK research community in 2012 to refer to individuals based in research environments who focus on the development of software to support and undertake research. Since then, the term has gained wide adoption and many RSE groups and teams have been set up at institutions within the UK and around t

Afsane Bahri, Zeinab Akhlaghi, Behrooz Khosravi

Let G be a finite group. A collection P={H1, ..., Hr} of subgroups of G, where r > 1, is said a non-trivial partition of G if every non-identity element of G belongs to one and only one Hi, for some 1 <=i<=r. We call a group G that does not admit any non-trivial partition a partition-free group. In this paper, we study a partition-free group G whose all prop

Bjørn Magnus Mathisen, Kerstin Bach, Espen Meidell, Håkon Måløy

Identifying individual salmon can be very beneficial for the aquaculture industry as it enables monitoring and analyzing fish behavior and welfare. For aquaculture researchers identifying individual salmon is imperative to their research. The current methods of individual salmon tagging and tracking rely on physical interaction with the fish. This process is

Yiyuan Li, Antonios Anastasopoulos, Alan W Black

Spelling normalization for low resource languages is a challenging task because the patterns are hard to predict and large corpora are usually required to collect enough examples. This work shows a comparison of a neural model and character language models with varying amounts on target language data. Our usage scenario is interactive correction with nearly

Tobias Reisch, Georg Heiler, Jan Hurt, Peter Klimek

Behavioral gender differences are known to exist for a wide range of human activities including the way people communicate, move, provision themselves, or organize leisure activities. Using mobile phone data from 1.2 million devices in Austria (15% of the population) across the first phase of the COVID-19 crisis, we quantify gender-specific patterns of commu

Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang

Ranking has always been one of the top concerns in information retrieval research. For decades, lexical matching signal has dominated the ad-hoc retrieval process, but it also has inherent defects, such as the vocabulary mismatch problem. Recently, Dense Retrieval (DR) technique has been proposed to alleviate these limitations by capturing the deep semantic

Marek Matas

Zeeman effect has been an invaluable tool for the detection and measurement of the effects of a magnetic field on the internal behavior of atoms and nuclei. Along with Mössbauer effect, it has been used to determine the magnitude of the magnetic field present in nuclei of atoms but has not been detected inside nucleons so far. In this work, we present a poss

Sandro Sousa, Vincenzo Nicosia

Socioeconomic segregation is considered one of the main factors behind the emergence of large-scale inequalities in urban areas, and its characterisation is an active area of research in urban studies. There are currently many available measures of spatial segregation, but almost all of them either depend in non-trivial ways on the scale and size of the syst

Shaohuai Shi, Xianhao Zhou, Shutao Song, Xingyao Wang

Distributed training techniques have been widely deployed in large-scale deep neural networks (DNNs) training on dense-GPU clusters. However, on public cloud clusters, due to the moderate inter-connection bandwidth between instances, traditional state-of-the-art distributed training systems cannot scale well in training large-scale models. In this paper, we

Itai Epstein, Andre J. Chaves, Daniel A. Rhodes, Bettina Frank

2D materials support unique excitations of quasi-particles that consist of a material excitation and photons called polaritons. Especially interesting are in-plane propagating polaritons which can be confined to a single monolayer and carry large momentum. In this work, we report the existence of a new type of in-plane propagating polariton, supported on mon

Milad Bakhshizadeh, Ali Kamalinejad, Mina Latifi

Uniform distribution of the points has been of interest to researchers for a long time and has applications in different areas of Mathematics and Computer Science. One of the well-known measures to evaluate the uniformity of a given distribution is Discrepancy, which assesses the difference between the Uniform distribution and the empirical distribution give

Niankai Yang, Ziyou Song, Heath Hofmann, Jing Sun

The State of Health (SOH) of lithium-ion batteries is directly related to their safety and efficiency, yet effective assessment of SOH remains challenging for real-world applications (e.g., electric vehicle). In this paper, the estimation of SOH (i.e., capacity fading) under partial discharge with different starting and final State of Charge (SOC) levels is

Rafal Pytel, Osman Semih Kayhan, Jan C. van Gemert

Occlusion degrades the performance of human pose estimation. In this paper, we introduce targeted keypoint and body part occlusion attacks. The effects of the attacks are systematically analyzed on the best performing methods. In addition, we propose occlusion specific data augmentation techniques against keypoint and part attacks. Our extensive experiments

Siddharth Mishra-Sharma, Kyle Cranmer

Mismodeling the uncertain, diffuse emission of Galactic origin can seriously bias the characterization of astrophysical gamma-ray data, particularly in the region of the Inner Milky Way where such emission can make up over 80% of the photon counts observed at ~GeV energies. We introduce a novel class of methods that use Gaussian processes and variational inf

Stefan Buschenhenke, Detlef Müller, Ana Vargas

We prove Fourier restriction estimates by means of the polynomial partitioning method for compact subsets of any sufficiently smooth hyperbolic hypersurface in threedimensional euclidean space. Our approach exploits in a crucial way the underlying hyperbolic geometry, which leads to a novel notion of strong transversality and corresponding &#34;exceptional&#

Joachim Neu, Ertem Nusret Tas, David Tse

The availability-finality dilemma says that blockchain protocols cannot be both available under dynamic participation and safe under network partition. Snap-and-chat protocols have recently been proposed as a resolution to this dilemma. A snap-and-chat protocol produces an always available ledger containing a finalized prefix ledger which is always safe and

Yunjiang Jiang, Yue Shang, Ziyang Liu, Hongwei Shen

Relevance has significant impact on user experience and business profit for e-commerce search platform. In this work, we propose a data-driven framework for search relevance prediction, by distilling knowledge from BERT and related multi-layer Transformer teacher models into simple feed-forward networks with large amount of unlabeled data. The distillation p

Benedikt Klein, Samuel J. Hall, Reinhard J. Maurer

X-ray photoemission (XPS) and Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy play an important role in investigating the structure and electronic structure of materials and surfaces. Ab-initio simulations provide crucial support for the interpretation of complex spectra containing overlapping signatures. Approximate core-hole simulation meth

Bin Chen, Kenwin Maung

In this paper, we propose a new nonparametric estimator of time-varying forecast combination weights. When the number of individual forecasts is small, we study the asymptotic properties of the local linear estimator. When the number of candidate forecasts exceeds or diverges with the sample size, we consider penalized local linear estimation with the group

Julien Berestycki, Éric Brunet, Cole Graham, Leonid Mytnik

We study the distance between the two rightmost particles in branching Brownian motion. Derrida and the second author have shown that the long-time limit $d_{12}$ of this random variable can be expressed in terms of PDEs related to the Fisher--KPP equation. We use such a representation to determine the sharp asymptotics of $\mathbb{P}(d_{12} > a)$ as $a\to+\

Dave Benson, Srikanth B. Iyengar, Henning Krause, Julia Pevtsova

We survey some methods developed in a series of papers, for classifying localising subcategories of tensor triangulated categories. We illustrate these methods by proving a new theorem, providing such a classification in the case of the stable module category of a unipotent finite supergroup scheme.

Luis Sequeira, Adam Szefer, Jamie Slome, Toktam Mahmoodi

Cooperative driving using connectivity services has been a promising avenue for autonomous vehicles, with the low latency and further reliability support provided by 5th Generation Mobile Network (5G). In this paper, we present an application for lane merge coordination based on a centralised system, for connected cars. This application delivers trajectory r

Sarah Walsh, David Murphy, Maeve Doyle, Joseph Thompson

The Educational Irish Research Satellite, EIRSAT-1, is a project developed by students at University College Dublin that aims to design, build, and launch Ireland&#39;s first satellite. EIRSAT-1 is a 2U CubeSat incorporating three novel payloads; GMOD, a gamma-ray detector, EMOD, a thermal coating management experiment, and WBC, a novel attitude control algo

A. Abdollahi, J. Bagherian, M. Khatami, Z. Shahbazi

Let $ χ$ be a virtual (generalized) character of a finite group $ G $ and $ L=L(χ)$ be the image of $ χ$ on $ G-\lbrace 1 \rbrace $. The pair $ (G, χ) $ is said to be sharp of type $ L $ if $|G|=\prod _{ l \in L} (χ(1) - l) $. If the principal character of $G$ is not an irreducible constituent of $χ$, the pair $(G,χ)$ is called normalized. In this paper, we

Ada Chan, Bobae Johnson, Mengzhen Liu, Malena Schmidt

We develop the theory of fractional revival in the quantum walk on a graph using its Laplacian matrix as the Hamiltonian. We first give a spectral characterization of Laplacian fractional revival, which leads to a polynomial time algorithm to check this phenomenon and find the earliest time when it occurs. We then apply the characterization theorem to specia

Noureddine Hadji

The static diffraction intensity distribution from large material system conceived as perfectly homogeneous system made inhomogeneous, though substitution of groups of atoms, small particles, by other groups of atoms, is explicitly expressed in terms of all possible partial contributions subsequent to the particle exchange operation. This gives the diffracte

Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett

This paper addresses the problem of localizing change points in high-dimensional linear regression models with piecewise constant regression coefficients. We develop a dynamic programming approach to estimate the locations of the change points whose performance improves upon the current state-of-the-art, even as the dimensionality, the sparsity of the regres

Emma J. Gerritse, Faegheh Hasibi, Arjen P. de Vries

Conversational AI systems are being used in personal devices, providing users with highly personalized content. Personalized knowledge graphs (PKGs) are one of the recently proposed methods to store users&#39; information in a structured form and tailor answers to their liking. Personalization, however, is prone to amplifying bias and contributing to the ech

Natalia Gorobey, Alexander Lukyanenko, A. V. Goltsev

An alternative representation of the kernel of the evolution operator in quantum electrodynamics is obtained in the form of a functional integral, in which the gauge momentum corresponding to the Gaussian constraint is excluded from the dynamics. The natural gauge condition, that arises as a result of this representation, leaves the integration only over gau

Selman Oguz

In this paper we review $G_2$ and $Spin(7)$ geometries in relation with a special type of metric structure which we call warped-like product metric. We present a general ansatz of warped-like product metric as a definition of warped-like product. Considering fiber-base decomposition, the definition of warped-like product is regarded as a generalization of mu

Xinlun Cheng, Borja Anguiano, Steven R. Majewski, Christian Hayes

Previous analyses of large databases of Milky Way stars have revealed the stellar disk of our Galaxy to be warped and that this imparts a strong signature on the kinematics of stars beyond the solar neighborhood. However, due to the limitation of accurate distance estimates, many attempts to explore the extent of these Galactic features have generally been r

Serge R. Mghabghab, Sean M. Ellison, Jeffrey A. Nanzer

Coordinating the operations of separate wireless systems at the wavelength level can lead to significant improvements in wireless capabilities. We address a fundamental challenge in distributed radio frequency system cooperation - inter-node phase alignment - which must be accomplished wirelessly, and is particularly challenging when the nodes are in relativ

John E. Hurtado

It is most common to construct the Hamiltonian function and Hamilton&#39;s canonical equations through a Legendre transformation of the Lagrangean function or through the central equation. These common perspectives, however, seem abstract and detached from classical analytical dynamics. A new and different approach is presented in which the Hamiltonian funct

Stefan Geschke, Jan Kurkofka, Ruben Melcher, Max Pitz

An end of a graph $G$ is an equivalence class of rays, where two rays are equivalent if there are infinitely many vertex-disjoint paths between them in $G$. The degree of an end is the maximum cardinality of a collection of pairwise disjoint rays in this equivalence class. Halin conjectured that the end degree can be characterised in terms of certain typical

Spyretta Leivaditi, Julien Rossi, Evangelos Kanoulas

Extracting entities and other useful information from legal contracts is an important task whose automation can help legal professionals perform contract reviews more efficiently and reduce relevant risks. In this paper, we tackle the problem of detecting two different types of elements that play an important role in a contract review, namely entities and re

Ilarion V. Melnikov, Constantinos Papageorgakis, Andrew B. Royston

We show that the leading semiclassical behavior of soliton form factors at arbitrary momentum transfer is controlled by solutions to a new wave-like integro-differential equation that describes solitons undergoing acceleration. We work in the context of two-dimensional linear sigma models with kink solitons for concreteness, but our methods are purely semicl

Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou

When autonomous agents interact in the same environment, they must often cooperate to achieve their goals. One way for agents to cooperate effectively is to form a team, make a binding agreement on a joint plan, and execute it. However, when agents are self-interested, the gains from team formation must be allocated appropriately to incentivize agreement. Va

Ruslan Aliev, Ekaterina Kondrateva, Maxim Sharaev, Oleg Bronov

Focal cortical dysplasia (FCD) is one of the most common epileptogenic lesions associated with cortical development malformations. However, the accurate detection of the FCD relies on the radiologist professionalism, and in many cases, the lesion could be missed. In this work, we solve the problem of automatic identification of FCD on magnetic resonance imag

Alexis Verschelde, Kasper Van Gasse, Bart Kuyken, Massimo Giudici

We present the detailed characterization of the phase dynamics of a telecom hybrid III-V-on-silicon passively mode-locked laser with a ring cavity. We explore the various regimes of operation as a function of gain current and saturable absorber bias voltage. We use a stepped-heterodyne measurement to quantify the spectral chirp and reconstruct the pulse enve

Bulat Burganov, Vladimir Ovuka, Matteo Savoini, Helmut Berger

The general idea of using ultrashort light pulses to control ferroic order parameters has recently attracted attention as a means to achieve control over material properties on unprecedented time scales. Much of the challenge in such work is in understanding the mechanisms by which this control can be achieved, and in particular how observables can be connec

Innocent Ndikubwayo

This paper discusses the location of zeros of polynomials in a polynomial sequence $\{P_n(z)\}$ generated by a three-term recurrence relation of the form $P_n(z)+ B(z)P_{n-1}(z) +A(z) P_{n-k}(z)=0$ with $k>2$ and the standard initial conditions $P_{0}(z)=1, P_{-1}(z)=\ldots=P_{-k+1}(z)=0,$ where $A(z)$ and $B(z)$ are arbitrary coprime real polynomials. We sh

Christoph Aistleitner, Simon Baker, Niclas Technau, Nadav Yesha

Koksma&#39;s equidistribution theorem from 1935 states that for Lebesgue almost every $α>1$, the fractional parts of the geometric progression $(α^{n})_{n\geq1}$ are equidistributed modulo one. In the present paper we sharpen this result by showing that for almost every $α>1$, the correlations of all finite orders and hence the normalized gaps of $(α^{n})_{n

Jaime Simarro, Zohaib Salahuddin, Ahmed Gouda, Anindo Saha

Identification and segmentation of breast masses in mammograms face complex challenges, owing to the highly variable nature of malignant densities with regards to their shape, contours, texture and orientation. Additionally, classifiers typically suffer from high class imbalance in region candidates, where normal tissue regions vastly outnumber malignant mas

Pierre Gervais

The aim of this paper is to extend to the spaces L^2(R^d , (1+|v|)^2k dv) the spectral study led in L^2(R^d , exp(|v|^2/2)dv) by R. Ellis and M. Pinsky on the space inhomogeneous linearized Boltzmann operator for hard spheres. More precisely, we look at the Fourier transform in the space variable of the inhomogeneous operator and consider the dual Fourier va

E. Berchio, A. Falocchi, M. Garrione

The paper deals with a nonlinear evolution equation describing the dynamics of a non homogeneous multiply hinged beam, subject to a nonlocal restoring force of displacement type. First, a spectral analysis for the associated weighted stationary problem is performed, providing a complete system of eigenfunctions. Then, a linear stability analysis for bi-modal

Clément Lagisquet, Edita Pelantová, Sébastien Tavenas, Laurent Vuillon

The Markov numbers are the positive integer solutions of the Diophantine equation $x^2 + y^2 + z^2 = 3xyz$. Already in 1880, Markov showed that all these solutions could be generated along a binary tree. So it became quite usual (and useful) to index the Markov numbers by the rationals between 0 and 1 which stand at the same place in the Stern-Brocot binary

Dongdong Zhang, Xiaohui Yuan, Ping Zhang

Electrocardiogram (ECG) is a widely used reliable, non-invasive approach for cardiovascular disease diagnosis. With the rapid growth of ECG examinations and the insufficiency of cardiologists, accurate and automatic diagnosis of ECG signals has become a hot research topic. Deep learning methods have demonstrated promising results in predictive healthcare tas

Jelena Sedlar, Riste Škrekovski

In a graph G, cardinality of the smallest ordered set of vertices that distinguishes every element of V (G) is the (vertex) metric dimension of G. Similarly, the cardinality of such a set is the edge metric dimension of G, if it distinguishes E(G). In this paper these invariants are considered first for unicyclic graphs, and it is shown that the vertex and e

Laurie Davies

The recent Covid-19 epidemic has lead to comparisons of the countries suffering from it. These are based on the number of excess deaths attributed either directly or indirectly to the epidemic. Unfortunately the data on which such comparisons rely are often incomplete and unreliable. This article discusses problems of interpretation of data even when the dat

Benjamin Hennion

If $M$ is a symplectic manifold then the space of smooth loops $\mathrm C^{\infty}(\mathrm S^1,M)$ inherits of a quasi-symplectic form. We will focus in this article on an algebraic analogue of that result. In 2004, Kapranov and Vasserot introduced and studied the formal loop space of a scheme $X$. We generalize their construction to higher dimensional loops

Salvatore Costanzo, Amélie Banc, Ameur Louhichi, Edouard Chauveau

We investigate the linear viscoelasticity of polymer gels produced by the dispersion of gluten proteins in water:ethanol binary mixtures with various ethanol contents, from pure water to 60% v/v ethanol. We show that the complex viscoelasticity of the gels exhibits a time/solvent composition superposition principle, demonstrating the self-similarity of the g

Christian J. Steinmetz, Jordi Pons, Santiago Pascual, Joan Serrà

Applications of deep learning to automatic multitrack mixing are largely unexplored. This is partly due to the limited available data, coupled with the fact that such data is relatively unstructured and variable. To address these challenges, we propose a domain-inspired model with a strong inductive bias for the mixing task. We achieve this with the applicat

Jerry Lonlac, Arnaud Doniec, Marin Lujak, Stephane Lecoeuche

Mining frequent episodes aims at recovering sequential patterns from temporal data sequences, which can then be used to predict the occurrence of related events in advance. On the other hand, gradual patterns that capture co-variation of complex attributes in the form of &#34; when X increases/decreases, Y increases/decreases&#34; play an important role in m

Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory. It aims to simulate two ways of thinking in the brain to answer questions, including reverse thinking and inertial thinking. To validate the effectiveness of our framework, we design a corresponding B

Ayan Chatterjee, Ali Shahaab, Martin W. Gerdes, Santiago Martinez

Health data is a sensitive category of personal data. It might result in a high risk to individual and health information handling rights and opportunities unless there is a palatable defense. Reasonable security standards are needed to protect electronic health records (EHR). All personal data handling needs adequate explanation. Maintaining access to medic

Mahsa Mesgaran, A. Ben Hamza

Graph convolutional networks learn effective node embeddings that have proven to be useful in achieving high-accuracy prediction results in semi-supervised learning tasks, such as node classification. However, these networks suffer from the issue of over-smoothing and shrinking effect of the graph due in large part to the fact that they diffuse features acro

Ivan H. Deutsch

The second quantum revolution has been built on a foundation of fundamental research at the intersection of physics and information science, giving rise to the discipline we now call Quantum Information Science (QIS). The quest for new knowledge and understanding drove the development of new experimental tools and rigorous theory, which defined the roadmap f