October 2020 arXiv papers — page 76

Calin Iulian Martin, Ronald Quirchmayr

We construct an explicit steady stratified purely azimuthal flow for the governing equations of geophysical fluid dynamics. These equations are considered in a setting that applies to the Antarctic Circumpolar Current, accounting for eddy viscosity and forcing terms.

Davide Corsi, Enrico Marchesini, Alessandro Farinelli

Groundbreaking successes have been achieved by Deep Reinforcement Learning (DRL) in solving practical decision-making problems. Robotics, in particular, can involve high-cost hardware and human interactions. Hence, scrupulous evaluations of trained models are required to avoid unsafe behaviours in the operational environment. However, designing metrics to me

Armeen Taeb, Parikshit Shah, Venkat Chandrasekaran

Fitting a graphical model to a collection of random variables given sample observations is a challenging task if the observed variables are influenced by latent variables, which can induce significant confounding statistical dependencies among the observed variables. We present a new convex relaxation framework based on regularized conditional likelihood for

Berenice Anne Neumann

Mean field games allow to describe tractable models of dynamic games with a continuum of players, explicit interaction and heterogeneous states. Thus, these models are of great interest for socio-economic applications. A particular class of these models are games with finite state and action space, for which recently in Neumann (2020a) a semi-explicit repres

Dejan Vinković, Miljenko Čemeljić

We explore dust flow in the hottest parts of protoplanetary discs using the forces of gravity, gas drag and radiation pressure. Our main focus is on the optically thin regions of dusty disc, where the dust is exposed to the most extreme heating conditions and dynamical perturbations: the surface of optically thick disc and the inner dust sublimation zone. We

Jie Chen, Baoxiang Wang

In this paper, we study the almost sure scattering for the Klein-Gordon equations with Sobolev critical power. We obtain the almost sure scattering with random initial data in $H^s \times H^{s-1}$; $11/12 < s < 1$ for $d = 4$, $15/16 < s < 1$ for $d = 5$. We use the induction on scales and bushes argument in [9] where the model equation is wave equation. For

Shengshan Qin, Chen Fang, Fu-chun Zhang, Jiangping Hu

We show that standard impurities, magnetic or nonmagnetic, weak or strong, can cause topological phase transitions inside the vortex cores of a conventional s-wave superconductor. Because of the nonzero angular momentum of Cooper pairs in the vortex cores, the vortex bound states in a two dimensional superconductor are sensitive to impurities in a way simila

Abdullatif Köksal, Arzucan Özgür

Relation classification is one of the key topics in information extraction, which can be used to construct knowledge bases or to provide useful information for question answering. Current approaches for relation classification are mainly focused on the English language and require lots of training data with human annotations. Creating and annotating a large

Ding Peng, Philip N. H. Nakashima

We have integrated density functional theory (DFT) into quantitative convergent-beam electron diffraction (QCBED) to create a synergy between experiment and theory called QCBED-DFT. This synergy resides entirely in the electron density which, in real materials, gives rise to the experimental CBED patterns used by QCBED-DFT to refine DFT model parameters. We

Grigoris Panotopoulos, Angel Rincon, Ilidio Lopes

We investigate the properties of relativistic stars made of dark energy. We model stellar structure assuming i) isotropic perfect fluid and ii) a dark energy inspired equation of state, the generalized equation of state of Chaplygin gas, as we will be calling it. The mass-to-radius profiles, the tidal Love numbers as well as the ten lowest radial oscillation

O. I. Hryhorchak

We have developed the technique of a quantum wave impedance determination for the sequence of not only constant potentials but also for potentials of forms for which the solution of a Shrödinger equation exists at least in terms of special functions. The method was applied for a deformed double-barrier system and as a result the dependence of a transmission

Shaili Sett, Arup Kumar Raychaudhuri

We report an investigation on the observation of ultrahigh photoresponse (photogain, G_Pc>106) in single nanowire photodetectors of diameter < 100 nm. The investigation which is a combination of experimental observations and a theoretical analysis of the ultrahigh optical response of semiconductor nanowires, has been carried out with emphasis on Ge nanowires

Parastoo Sadeghi, Ni Ding, Thierry Rakotoarivelo

We study the problem of privacy preservation in data sharing, where $S$ is a sensitive variable to be protected and $X$ is a non-sensitive useful variable correlated with $S$. Variable $X$ is randomized into variable $Y$, which will be shared or released according to $p_{Y|X}(y|x)$. We measure privacy leakage by \emph{information privacy} (also known as \emp

Xiao-Yu Guo, Yuan-Fang Li, Gholamreza Haffari

Complex question answering (CQA) over raw text is a challenging task. A prominent approach to this task is based on the programmer-interpreter framework, where the programmer maps the question into a sequence of reasoning actions which is then executed on the raw text by the interpreter. Learning an effective CQA model requires large amounts of human-annotat

M. Tiwari, K. M. Menten, F. Wyrowski, A. Giannetti

Messier 8 (M8), one of the brightest HII regions in our Galaxy, is associated with two prominent massive star-forming regions: M8-Main, the particularly bright part of the large scale HII region (mainly) ionised by the stellar system Herschel 36 (Her 36) and M8 East (M8 E), which is mainly powered by a deeply embedded young stellar object (YSO), a bright inf

Jean-Marc Foucaut, William K. George, Michel Stanislas, Christophe Cuvier

An SPIV experiment using two orthogonal planes simultaneously was performed in the LML boundary layer facility to specifically measure all of the derivative moments needed to estimate the dissipation rate of the Turbulence Kinetic Energy. The Reynolds number was $Re_θ= 7500$ or $Re_τ= 2300$. A detailed analysis of the errors in derivative measurements was ca

Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han

This paper proposes a latent space energy-based prior model for semi-supervised learning. The model stands on a generator network that maps a latent vector to the observed example. The energy term of the prior model couples the latent vector and a symbolic one-hot vector, so that classification can be based on the latent vector inferred from the observed exa

Igor Krichever, Sergei Lando, Alexandra Skripchenko

A meromorphic differential on a Riemann surface is said to be {\it real-normalized} if all its periods are real. Real-normalized differentials on Riemann surfaces of given genus with prescribed orders of their poles form real orbifolds whose topology is closely related to that of moduli spaces of Riemann surfaces with marked points. Our goal is to develop to

Honglin Yuan, Remco C. Veltkamp, Georgios Albanis, Nikolaos Zioulis

6D pose estimation is crucial for augmented reality, virtual reality, robotic manipulation and visual navigation. However, the problem is challenging due to the variety of objects in the real world. They have varying 3D shape and their appearances in captured images are affected by sensor noise, changing lighting conditions and occlusions between objects. Di

Mauricio Misquero

The aim of this article is to propose a model, that is a planar version of the Full Two-Body Problem, and discuss the existence and stability of a relevant periodic solution. Consider two homogeneous ellipsoids orbiting around each other in fixed coplanar Keplerian orbits. Moreover, their respective spin axes are assumed to be perpendicular to the orbital pl

Bo Pang, Tian Han, Ying Nian Wu

Deep generative models have recently been applied to molecule design. If the molecules are encoded in linear SMILES strings, modeling becomes convenient. However, models relying on string representations tend to generate invalid samples and duplicates. Prior work addressed these issues by building models on chemically-valid fragments or explicitly enforcing

Gideok Kim, K. Son, Y. E. Suyolcu, L. Miao

Topological transport phenomena in magnetic materials are a major topic of current condensed matter research. One of the most widely studied phenomena is the ``topological Hall effect&#39;&#39; (THE), which is generated via spin-orbit interactions between conduction electrons and topological spin textures such as skyrmions. We report a comprehensive set of H

William K. George, Michel Stanislas, Jean-Marc Foucaut, Jean-Philippe Laval

An experiment was performed using Dual-plane-SPIV in the LMFL boundary layer facility to determine all of the derivative moments needed to estimate the average dissipation rate of the turbulent kinetic energy, $\varepsilon$, and its Reynolds stress counterpart the dissipation tensor, $\varepsilon_{ij}$. For this experiment, the Reynolds number was $Re_θ= 750

Michel Stanislas, Jean Marc Foucaut, William K. George, Christophe Cuvier

An experiment was performed using SPIV in the LMFL boundary layer facility to determine all the derivative moments needed to estimate the average dissipation rate of the turbulence kinetic energy, $\varepsilon = 2 ν\langle s_{ij}s_{ij} \rangle$ where $s_{ij}$ is the fluctuating strain-rate and $\langle~\rangle$ denotes ensemble averages. Also measured were a

Jiateng Liu, Wenming Zheng, Yuan Zong

Correctly perceiving micro-expression is difficult since micro-expression is an involuntary, repressed, and subtle facial expression, and efficiently revealing the subtle movement changes and capturing the significant segments in a micro-expression sequence is the key to micro-expression recognition (MER). To handle the crucial issue, in this paper, we first

Nawell Ould Moussa, Tigran Mansuryan, Charles Henri Hage, Marc Fabert

Beam self-cleaning (BSC) in graded-index (GRIN) multimode fibres (MMFs) has been recently reported by different research groups. Driven by the interplay between Kerr effect and beam self-imaging, BSC counteracts random mode coupling, and forces laser beams to recover a quasi-single mode profile at the output of GRIN fibres. Here we show that the associated s

Marc Hovemann

We will prove that under certain conditions on the parameters the operators $T^{+}f = \max(f,0)$ and $ Tf = |f| $ are bounded mappings on the Triebel-Lizorkin-Morrey and Besov-Morrey spaces. Moreover we will show that some of the conditions we mentioned before are also necessary. Furthermore we prove that for $p < u $ in many cases the Triebel-Lizorkin-Morre

Philipp Jeitner, Haya Shulman, Michael Waidner

We demonstrate the first practical off-path time shifting attacks against NTP as well as against Man-in-the-Middle (MitM) secure Chronos-enhanced NTP. Our attacks exploit the insecurity of DNS allowing us to redirect the NTP clients to attacker controlled servers. We perform large scale measurements of the attack surface in NTP clients and demonstrate the th

Pierfrancesco Ardino, Yahui Liu, Elisa Ricci, Bruno Lepri

Manipulating images of complex scenes to reconstruct, insert and/or remove specific object instances is a challenging task. Complex scenes contain multiple semantics and objects, which are frequently cluttered or ambiguous, thus hampering the performance of inpainting models. Conventional techniques often rely on structural information such as object contour

Andrea Scotti, Alan. R. Denton, Monia Brugnoni, Ralf Schweins

Solutions of microgels have been widely used as model systems to gain insight into atomic condensed matter and complex fluids. We explore the thermodynamic phase behavior of hollow microgels, which are distinguished from conventional colloids by possessing a central cavity. Small-angle neutron and X-ray scattering are used to probe hollow microgels in crowde

Philipp Jeitner, Haya Shulman, Michael Waidner

Many applications and protocols depend on the ability to generate a pool of servers to conduct majority-based consensus mechanisms and often this is done by doing plain DNS queries. A recent off-path attack [1] against NTP and security enhanced NTP with Chronos [2] showed that relying on DNS for generating the pool of NTP servers introduces a weak link. In t

Mohammad Sadrosadati, Amirhossein Mirhosseini, Ali Hajiabadi, Seyed Borna Ehsani

Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, and large silicon area provisioning. Prior work proposes hierarchical register file to reduce the regist

Simgeon Oh, Ji-Hee Kim, Hee Min Hwang, Doyoung Kim

Black TiO2 with/without noble metal has been proposed for visible photocatalyst, still leaving poor catalyst efficiency. Alternatively, phase-mixed TiO2 such as anatase and rutile has been commonly used for visible catalysts with the inevitable inclusion of noble metal. Here, we perform a noble metal-free visible photocatalyst blue TiO2 with type-II band-ali

Anton Mallasto, Markus Heinonen, Samuel Kaski

In machine learning and computer vision, optimal transport has had significant success in learning generative models and defining metric distances between structured and stochastic data objects, that can be cast as probability measures. The key element of optimal transport is the so called lifting of an \emph{exact} cost (distance) function, defined on the s

Denis Novitsky, Dmitry Lyakhov, Dominik Michels, Dmitrii Redka

Unique and flexible properties of non-Hermitian photonic systems attract ever-increasing attention via delivering a whole bunch of novel optical effects and allowing for efficient tuning light-matter interactions on nano- and microscales. Together with an increasing demand for the fast and spatially compact methods of light governing, this peculiar approach

Marco Cogoni, Giovanni Busonera

The urban networks of London and New York City are investigated as directed graphs within the paradigm of graph percolation. It has been recently observed that urban networks show a critical percolation transition when a fraction of edges are removed. The resulting strongly connected components form a cluster structure whose size distribution follows a power

T. Sperling, J. Eislöffel, C. Fischer, B. Nisini

We present SOFIA/FIFI-LS observations of five prototypical, low-mass Class I outflows (HH111, SVS13, HH26, HH34, HH30) in the far-infrared [OI]63mum and [OI]145mum transitions. The obtained spectroscopic [OI]63mum and [OI]145mum maps enable us to study the spatial extent of warm, low-excitation atomic gas within outflows driven by Class I protostars. These [

Rita Giuliano, Milto Hadjikyriakou

In this work we prove an asymptotic result, that under some conditions on the involved distribution functions, is valid for any Oppenheim expansion, extending a classical result proven by W. Vervaat in 1972 for denominators of the Luroth case. Furthermore, we study the convergence in distribution of weighted sums of a sequence of independent random variables

Phan Thi Hong Hanh, Pham Dinh Thanh, Huynh Thi Thanh Binh

In literature, Clustered Shortest-Path Tree Problem (CluSPT) is an NP-hard problem. Previous studies often search for an optimal solution in relatively large space. To enhance the performance of the search process, two approaches are proposed: the first approach seeks for solutions as a set of edges. From the original graph, we generate a new graph whose ver

Grzegorz Ficht, Hafez Farazi, Diego Rodriguez, Dmytro Pavlichenko

For several years, high development and production costs of humanoid robots restricted researchers interested in working in the field. To overcome this problem, several research groups have opted to work with simulated or smaller robots, whose acquisition costs are significantly lower. However, due to scale differences and imperfect simulation replicability,

Zijun Bian, Katherine J. Rae, Adam F. McKenzie, Ben C. King

We present an InP-based epitaxially regrown photonic crystal surface emitting laser diode, lasing in quasi- CW conditions at 1523nm.

Andrea Canidio, Gabriele Costa, Letterio Galletta

We propose PrYVeCT, a private-yet-verifiable contact tracing system. PrYVeCT works also as an authorization framework allowing for the definition of fine-grained policies, which a certain facility can define and apply to better model its own access rules. Users are authorized to access the facility only when they exhibit a contact trace that complies with th

Małgorzata Domino, Michał Romaszewski, Tomasz Jasiński, Małgorzata Maśko

Infrared thermography (IRT) is a valuable diagnostic tool in equine veterinary medicine however, little is known about its application in donkeys. The aim was to find patterns in thermal images of donkeys and horses, and determine if these patterns share similarities. The study was carried out on 18 donkeys and 16 horses. All equids underwent thermal imaging

M. Gangi, M. Giarrusso, M. Munari, C. Ferrara

We present a long-term optical spectroscopic study of the post-AGB binary system 89 Herculis, with the aim to characterize the relationship between photospheric instabilities and dynamics in the close circumstellar environment of the system. This study is based on spectra acquired with the high-resolution Catania Astrophysical Observatory Spectropolarimeter

Alireza Hajijafarassar, Filipe Martinho, Fredrik Stulen, Sigbjørn Grini

Following the recent success of monolithically integrated Perovskite/Si tandem solar cells, great interest has been raised in searching for alternative wide bandgap top-cell materials with prospects of a fully earth-abundant, stable and efficient tandem solar cell. Thin film chalcogenides (TFCs) such as the Cu2ZnSnS4 (CZTS) could be suitable top-cell materia

Yixin Wang, Yao Zhang, Jiang Tian, Cheng Zhong

Though deep learning has achieved advanced performance recently, it remains a challenging task in the field of medical imaging, as obtaining reliable labeled training data is time-consuming and expensive. In this paper, we propose a double-uncertainty weighted method for semi-supervised segmentation based on the teacher-student model. The teacher model provi

Jathushan Rajasegaran, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan

Meta-learning stands for &#39;learning to learn&#39; such that generalization to new tasks is achieved. Among these methods, Gradient-based meta-learning algorithms are a specific sub-class that excel at quick adaptation to new tasks with limited data. This demonstrates their ability to acquire transferable knowledge, a capability that is central to human le

Ludovic Godard-Cadillac

In a recent article by Gravejat and Smets, it is built smooth solutions to the inviscid surface quasi-geostrophic equation that have the form of a traveling wave. In this article we work back on their construction to provide solution to a more general class of quasi-geostrophic equation where the half-laplacian is replaced by any fractional laplacian.

Nicolas Gastineau, Wahabou Abdou, Nader Mbarek, Olivier Togni

In this paper, we present two deterministic leader election algorithms for programmable matter on the face-centered cubic grid. The face-centered cubic grid is a 3-dimensional 12-regular infinite grid that represents an optimal way to pack spheres (i.e., spherical particles or modules in the context of the programmable matter) in the 3-dimensional space. Whi

René Aid, Andrea Cosso, Huyên Pham

We formulate an equilibrium model of intraday trading in electricity markets. Agents face balancing constraints between their customers consumption plus intraday sales and their production plus intraday purchases. They have continuously updated forecast of their customers consumption at maturity with decreasing volatility error. Forecasts are prone to idiosy

Mohammed Haroon Dupty, Wee Sun Lee

Graph neural network models have been extensively used to learn node representations for graph structured data in an end-to-end setting. These models often rely on localized first order approximations of spectral graph convolutions and hence are unable to capture higher-order relational information between nodes. Probabilistic Graphical Models form another c

Christopher E. O&#39;Lone, Harpreet S. Dhillon, R. Michael Buehrer

This paper presents a stochastic geometry-based analysis of propagation statistics for 5G millimeter wave (mm-wave) cellular. In particular, the time-of-arrival (TOA) and angle-of-arrival (AOA) distributions of the first-arriving multipath component (MPC) are derived. These statistics find their utility in many applications such as cellular-based localizatio

Yusheng Huang, Dong Chu, Yong Deng, Kang Hao Cheong

Physarum polycephalum inspired algorithm (PPA), also known as the Physarum Solver, has attracted great attention. By modelling real-world problems into a graph with network flow and adopting proper equations to calculate the distance between the nodes in the graph, PPA could be used to solve system optimization problems or user equilibrium problems. However,

Thierry Klein, Agnès Lagnoux, Pierre Petit

Asymptotics deviation probabilities of the sum S n = X 1 + $\times$ $\times$ $\times$ + X n of independent and identically distributed real-valued random variables have been extensively investigated , in particular when X 1 is not exponentially integrable. For instance, A.V. Nagaev formulated exact asymptotics results for P(S n > x n) when X 1 has a semiexpo

Michael Ulrich, Claudius Gläser, Fabian Timm

This paper presents an novel object type classification method for automotive applications which uses deep learning with radar reflections. The method provides object class information such as pedestrian, cyclist, car, or non-obstacle. The method is both powerful and efficient, by using a light-weight deep learning approach on reflection level radar data. It

Valerie Brien, Manuel Dossot, Hervé Rinnert, Sajjad Hussain Sajjad

In the prospect of understanding the photoluminescence mechanisms of AlN films doped with erbium and targeting photonic applications we have synthesized non doped and Er-doped AlN films with different crystallized nanostructures by using PVD magnetron sputtering. Their crystalline morphology and their visible photoluminescence properties were precisely measu

Josh Brunner, Erik D. Demaine, Dylan Hendrickson, Julian Wellman

We prove PSPACE-completeness of two classic types of Chess problems when generalized to n-by-n boards. A &#34;retrograde&#34; problem asks whether it is possible for a position to be reached from a natural starting position, i.e., whether the position is &#34;valid&#34; or &#34;legal&#34; or &#34;reachable&#34;. Most real-world retrograde Chess problems ask

Boliang Zhang, Spencer Whitehead, Lifu Huang, Heng Ji

Many name tagging approaches use local contextual information with much success, but fail when the local context is ambiguous or limited. We present a new framework to improve name tagging by utilizing local, document-level, and corpus-level contextual information. We retrieve document-level context from other sentences within the same document and corpus-le

Mayank Shekhar Jha, Philippe Weber, Didier Theilliol, Jean-Christophe Ponsart

Health-aware control (HAC) has emerged as one of the domains where control synthesis is sought based upon the failure prognostics of system/component or the Remaining Useful Life (RUL) predictions of critical components. The fact that mathematical dynamic (transition) models of RUL are rarely available, makes it difficult for RUL information to be incorporat

Yi Zhang, Akash Doshi, Rob Liston, Wai-tian Tan

In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) correction, and equalization modules of IEEE 802.11ax based orthogonal frequency division multiplexing (OFDM) receivers. We first train DeepWiPHY with a synthetic dataset, which is generated

Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li

Recently, many machine learning and statistical models such as non-linear regressions, the Single Index, Multi-index, Varying Coefficient Index Models and Two-layer Neural Networks can be reduced to or be seen as a special case of a new model which is called the \textit{Stochastic Linear Combination of Non-linear Regressions} model. However, due to the high

Ningyu Tang, Di Li, Nannan Yue, Pei Zuo

We have conducted OH 18 cm survey toward 141 molecular clouds in various environments, including 33 optical dark clouds, 98 Planck Galactic cold clumps (PGCCs) and 10 Spitzer dark clouds with the Arecibo telescope. The deviations from local thermal equilibrium are common for intensity ratios of both OH main lines and satellite lines. Line intensity of OH 166

Anne Bouillard

Computing accurate deterministic performance bounds is a strong need for communication technologies having strong requirements on latency and reliability. Beyond new scheduling protocols such as TSN, the FIFO policy remains at work within each class of communication. In this paper, we focus on computing deterministic performance bounds in FIFO networks in th

Max Lein

The topological classification of hermitian operators is solely determined by the presence or absence of certain discrete symmetries. For non-hermitian operators we in addition need to specify the type of spectral gap. They come in the flavor of a point gap or a line gap. Since the presence of a line gap implies the existence of a point gap, there is usually

Sheng Shen, Tianqing Zhu, Di Wu, Wei Wang

Federated learning is an improved version of distributed machine learning that further offloads operations which would usually be performed by a central server. The server becomes more like an assistant coordinating clients to work together rather than micro-managing the workforce as in traditional DML. One of the greatest advantages of federated learning is

Kai Wu, J. Andrew Zhang, Xiaojing Huang, Y. Jay Guo

Enabled by the advancement in radio frequency technologies, the convergence of radar and communication systems becomes increasingly promising and is envisioned as a key feature of future 6G networks. Recently, the frequency-hopping (FH) MIMO radar is introduced to underlay dual-function radar-communication (DFRC) systems. Superior to many previous radar-cent

Sebastian Berndt, Klaus Jansen, Alexandra Lassota

We consider ILPs, where each variable corresponds to an integral point within a polytope $\mathcal{P}$, i. e., ILPs of the form $\min\{c^{\top}x\mid \sum_{p\in\mathcal P\cap \mathbb Z^d} x_p p = b, x\in\mathbb Z^{|\mathcal P\cap \mathbb Z^d|}_{\ge 0}\}$. The distance between an optimal fractional solution and an optimal integral solution (called proximity) i

Yang Yang, Junmei Hao, Canjia Li, Zili Wang

As a concise form of user reviews, tips have unique advantages to explain the search results, assist users&#39; decision making, and further improve user experience in vertical search scenarios. Existing work on tip generation does not take query into consideration, which limits the impact of tips in search scenarios. To address this issue, this paper propos

Jiajun Li, Nagamalleswararao Dasari, Martin Eckstein

We study the photoinduced ultrafast dynamics in relativistic Mott insulators, i.e., Mott insulators with strong spin-orbit coupling. For this purpose, we consider a minimal one-band Hubbard model on lattices with square and triangular symmetries, as relevant for layered transition metal compounds such as Sr$_2$IrO$_4$. Depending on the lattice and the spin-o

Tiezheng Yu, Dan Su, Wenliang Dai, Pascale Fung

Lay summarization aims to generate lay summaries of scientific papers automatically. It is an essential task that can increase the relevance of science for all of society. In this paper, we build a lay summary generation system based on the BART model. We leverage sentence labels as extra supervision signals to improve the performance of lay summarization. I

Sayantan Roy, Subroto Mukerjee, Manas Kulkarni

In this paper, we look at four generalizations of the one dimensional Aubry-Andre-Harper (AAH) model which possess mobility edges. We map out a phase diagram in terms of population imbalance, and look at the system size dependence of the steady state imbalance. We find non-monotonic behaviour of imbalance with system parameters, which contradicts the idea th

Olivier Bernard, Liudi Lu, Jacques Marie, Julien Salomon

We present a coupled model describing growth of microalgae in a raceway cultivation process, accounting for hydrodynamics. Our approach combines a biological model (based on the Han model) and shallow water dynamics equations that model the fluid into the raceway. We then describe an optimization procedure dealing with the topography to maximize the biomass

Albert Weichselbraun, Philipp Kuntschik, Sandro Hörler

Performing company valuations within the domain of biotechnology, pharmacy and medical technology is a challenging task, especially when considering the unique set of risks biotech start-ups face when entering new markets. Companies specialized in global valuation services, therefore, combine valuation models and past experience with heterogeneous metrics an

Olivier Bernard, Liudi Lu, Julien Salomon

This paper focuses on mixing strategies to enhance the growth of microalgae in a raceway pond. The flow is assumed to be laminar and the Han model describing the dynamics of the photosystems is used as a basis to determine growth rate as a function of light history. A device controlling the mixing is assumed, which means that the order of the cells along the

Scott Leask, Vincent McDonell

Recent deep learning extensions in Koopman theory have enabled compact, interpretable representations of nonlinear dynamical systems which are amenable to linear analysis. Deep Koopman networks attempt to learn the Koopman eigenfunctions which capture the coordinate transformation to globally linearize system dynamics. These eigenfunctions can be linked to u

Kohei Yamamichi, Xian-Hua Han

Rain streak removal in a single image is a very challenging task due to its ill-posed nature in essence. Recently, the end-to-end learning techniques with deep convolutional neural networks (DCNN) have made great progress in this task. However, the conventional DCNN-based deraining methods have struggled to exploit deeper and more complex network architectur

Lu Wen, Zhiqiang Li, Yan He

We theoretically study the band structure and optical conductivity of twisted bilayer graphene (TBG) near the magic angle considering the effects of lattice relaxation. We show that the optical conductivity spectrum is characterized by a series of peaks associated with the van Hove singularities in the band structure, and the peak energies evolve systematica

Qiuyue Liu, Jing Yang, Keqin Feng

Several discrete geometry problems are closely related to the arithmetic theory of elliptic curves defined on the rational fields $\mathbb{Q}$. In this paper we consider the $θ$-congruent number for $θ=\fracπ{3}$ and $\frac{2π}{3}$ and tiling number n. For the case that $n\geqslant 2$ is square-free odd integer, we determine all $n$ such that the Selmer rank

Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan

In this paper, we introduce a convenient framework for studying (adversarial) generative models from a statistical perspective. It consists in modeling the generative device as a smooth transformation of the unit hypercube of a dimension that is much smaller than that of the ambient space and measuring the quality of the generative model by means of an integ

Min Yong Jeong, Seo Hyoung Chang, Hyeong Jun Lee, Jae-Hoon Sim

By means of density functional theory plus dynamical mean-field theory (DFT+DMFT) calculations and resonant inelastic x-ray scattering (RIXS) experiments, we investigate the high-pressure phases of the spin-orbit-coupled $J_{\rm{eff}}=3/2$ insulator GaTa$_4$Se$_8$. Its metallic phase, derived from the Mott state by applying pressure, is found to carry $J_{\r

David Eppstein

We study the graphs formed from instances of the stable matching problem by connecting pairs of elements with an edge when there exists a stable matching in which they are matched. Our results include the NP-completeness of recognizing these graphs, an exact recognition algorithm that is singly exponential in the number of edges of the given graph, and an al

Hiba F. Fayoumi

Let $(X,\bullet )$ be a groupoid (binary algebra) and $Bin(X\dot{)}$ denote the collection of all groupoids defined on $X$. We introduce two methods of factorization for this binary system under the binary groupoid product \textquotedblleft $\diamond $\textquotedblright\ in the semigroup $\left( Bin\left( X\right) ,\diamond \right) $. We conclude that a stro

Yuan Mei, Xiangming Sun, Nu Xu

We propose a novel charge sensing concept for high-pressure Time Projection Chamber (TPC) to search for Neutrinoless Double-Beta Decay (NLDBD) with ton-scale isotope mass and beyond. A meter-sized plane, tiled with an array of CMOS integrated sensors called Topmetal that directly collect charge without gas avalanche gain, is to be deployed into a high-pressu

Hiba F. Fayoumi

In this paper we introduce the notion of the center $ZBin(X)$ in the semigroup $Bin(X)$ of all binary systems on a set $X$, and show that if $(X,\bullet)\in ZBin(X)$, then $x\not=y$ implies $\{x,y\}=\{x\bullet y,y\bullet x\}$.Moreover, we show that a groupoid $(X,\bullet )\in ZBin(X)$ if and only if it is a locally-zero groupoid.

Nelda Raju, Khondokar Fida Hasan

The new wave of computing allows users to explore their time in the Internet of Things (IoT) by connecting their smart devices over the network for data transfer without human interventions. While this swing increases the pace in IoT, time synchronization became a demanding feature on IoT devices for real-time applications. In this paper, we describe two syn

Nakul Agarwal, Yi-Ting Chen, Behzad Dariush, Ming-Hsuan Yang

Spatio-temporal action localization is an important problem in computer vision that involves detecting where and when activities occur, and therefore requires modeling of both spatial and temporal features. This problem is typically formulated in the context of supervised learning, where the learned classifiers operate on the premise that both training and t

Tetsuya Furukawa, Yuta Watanabe, Naoki Ogasawara, Kaya Kobayashi

Chiral matter has a structure that lacks inversion, mirror, and rotoreflection symmetry; thus, a given chiral material has either a right- or left-handed structure. In chiral matter, electricity and magnetism can be coupled in an exotic manner beyond the classical electromagnetism (e.g., magneto chiral effect in chiral magnets). In this paper, we give a firm

Hyunseung Chung, Woo-Jeoung Nam, Seong-Whan Lee

Remote sensing image retrieval (RSIR) is the process of ranking database images depending on the degree of similarity compared to the query image. As the complexity of RSIR increases due to the diversity in shooting range, angle, and location of remote sensors, there is an increasing demand for methods to address these issues and improve retrieval performanc

Patrick Lee Orman, Ryoichi Kawai

A standard theory of thermodynamics states that a quantum system in contact with a thermal environment relaxes to the equilibrium state known as the Gibbs state wherein decoherence occurs in the system&#39;s energy eigenbasis. When the interaction between the system and environment is strong, a different equilibrium state can be reached that is not diagonal

Sheng-Yuan Liu, Yu-Nung Su, Igor Zinchenko, Kuo-Song Wang

The massive young stellar object S255IR NIRS3 embedded in the star forming core SMA1 has been recently observed with a luminosity burst, which is conjectured as a disc-mediated variable accretion event. In this context, it is imperative to characterize the gas properties around the massive young stellar object. With this in mind, we carried out high angular

Bao-Zong Wang, Peng-Cheng Hou, Youjin Deng, Kristjan Haule

The sign cancellation between scattering amplitudes makes fermions different from bosons. We systematically investigate Feynman diagrams&#39; fermionic sign structure in a representative many-fermion system---a uniform Fermi gas with Yukawa interaction. We analyze the role of the crossing symmetry and the global gauge symmetry in the fermionic sign cancellat

Shihao Yan, Stephen V. Hanly, Iain B. Collings

This paper jointly optimizes the flying location and wireless communication transmit power for an unmanned aerial vehicle (UAV) conducting covert operations. This is motivated by application scenarios such as military ground surveillance from airborne platforms, where it is vital for a UAV&#39;s signal transmission to be undetectable by those within the surv

Masahiko Hayashi, Hideo Yoshioka, Hikari Tomori, Akinobu Kanda

Strain engineering is one of the key technologies for using graphene as an electronic device: the strain-induced pseudo-gauge field reflects Dirac electrons, thus opening the so-called conduction gap. Since strain accumulates in constrictions, graphene nanoconstrictions can be a good platform for this technology. On the other hand, in the graphene nanoconstr

Jiaxin Ju, Ming Liu, Longxiang Gao, Shirui Pan

The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task. It contains three shared tasks and we participate in the LongSumm shared task. In this paper, we describe our text summarization system, SciSummPip, inspired by SummPip (Zhao et al., 2020) that is an unsupervised text summarizat

Ye Liu, Sheng Zhang, Rui Song, Suo Feng

Open attribute value extraction for emerging entities is an important but challenging task. A lot of previous works formulate the problem as a \textit{question-answering} (QA) task. While the collections of articles from web corpus provide updated information about the emerging entities, the retrieved texts can be noisy, irrelevant, thus leading to inaccurat

Vinit Sarode, Animesh Dhagat, Rangaprasad Arun Srivatsan, Nicolas Zevallos

Point clouds have grown in importance in the way computers perceive the world. From LIDAR sensors in autonomous cars and drones to the time of flight and stereo vision systems in our phones, point clouds are everywhere. Despite their ubiquity, point clouds in the real world are often missing points because of sensor limitations or occlusions, or contain extr

Shinji Mukohyama, Ryo Namba

The $k$-essence theory is a prototypical class of scalar-field models that already gives rich phenomenology and has been a target of extensive studies in cosmology. General forms of shift-symmetric $k$-essence are known to suffer from formation of caustics in a planar-symmetric configuration, with the only exceptions of canonical and DBI-/cuscuton-type kinet

Alexandre Lourdeaux

On revoit explicitement la construction ainsi que certaines propriétés des complexes de faisceaux étales $\mathbb{Q}/\mathbb{Z}(j)$ sur certains schémas. Le but de ces notes est d&#39;avoir une référence précise pour la conjecture de Gersten pour les faisceaux $\mathbb{Q}/\mathbb{Z}(j)$ sur un corps imparfait ainsi que pour la comparaison entre les groupes d

Haiming Yu, Jiang Xiao, Helmut Schultheiss

The spontaneous magnetic orders arising in ferro-, ferri- and antiferromagnets stem from various magnetic interactions. Depending on the interplay and competition among the Heisenberg exchange interaction, Dzyaloshinskii-Moriya exchange interaction, magnetic dipolar interaction and crystal anisotropies, a great variety of magnetic textures may be stabilized,

Ling Pan, Qingpeng Cai, Longbo Huang

A widely-used actor-critic reinforcement learning algorithm for continuous control, Deep Deterministic Policy Gradients (DDPG), suffers from the overestimation problem, which can negatively affect the performance. Although the state-of-the-art Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm mitigates the overestimation issue, it can lead to a