April 2020 arXiv papers — page 48

Ying Liu, Zhi-Ming Yu, Cong Xiao, Shengyuan A. Yang

A particle beam may undergo an anomalous spatial shift when it is reflected at an interface. The shift forms a vector field defined in the two-dimensional interface momentum space. We show that, although the shift vector at individual momentum is typically sensitive to the system details, its integral along a close loop, i.e., its circulation, could yield a

Jihong Guo, Yunpeng Liu

The Euler-Maclaurin summation formula is generalized to a modified form by expanding the periodic Bernoulli polynomials as its Fourier series and taking cuts, which includes both the Euler-Maclaurin summation formula and the Poission summation formula as special cases. By making use of the modified formula, a numerical summation method is obtained and the er

Chandan Joishi, Zhanbo Xia, John S. Jamison, Shahadat H. Sohel

We introduce a deep-recessed gate architecture in $\beta$-Ga$_2$O$_3$ delta-doped field effect transistors for improvement in DC-RF dispersion and breakdown properties. The device design incorporates an unintentionally doped $\beta$-Ga$_2$O$_3$ layer as the passivation dielectric. To fabricate the device, the deep-recess geometry was developed using BCl$_3$

Carl-Johan Hoel, Krister Wolff, Leo Laine

Reinforcement learning (RL) can be used to create a tactical decision-making agent for autonomous driving. However, previous approaches only output decisions and do not provide information about the agent's confidence in the recommended actions. This paper investigates how a Bayesian RL technique, based on an ensemble of neural networks with additional rando

Aurelie Nakamura, Fabienne El-Khoury, Anne-Laure Sutter-Dallay, Jeanna-Eve Franck

Background An advantaged socioeconomic position (SEP) and satisfying social support during pregnancy (SSP) have been found to be protective factors of maternal postpartum depression (PDD). An advantaged SEP is also associated with satisfying SSP, making SSP a potential mediator of social inequalities in PPD. SEP, SSP and PPD are associated with migrant statu

Charlotte F. Petersen, Lukas Schrack, Thomas Franosch

Confined fluids display complex behavior due to layering and local packing. Here, we disentangle these effects by confining a hard-sphere fluid to the surface of a cylinder, such the circumference extends only over a few particle diameters. We compare the static structure factor and the pressure measured in computer simulations to the Percus-Yevick closure i

Claire Voreiter, Jean-Christophe Burnel, Pierre Lassalle, Marc Spigai

In the field of remote sensing and more specifically in Earth Observation, new data are available every day, coming from different sensors. Leveraging on those data in classification tasks comes at the price of intense labelling tasks that are not realistic in operational settings. While domain adaptation could be useful to counterbalance this problem, most

Pian Yu, Dimos V. Dimarogonas

This paper investigates the online motion coordination problem for a group of mobile robots moving in a shared workspace. Based on the realistic assumptions that each robot is subject to both velocity and input constraints and can have only local view and local information, a fully distributed multi-robot motion coordination strategy is proposed. Building on

Juri Grossi, Ziad H. Musslimani, Michael Seidl, Paola Gori-Giorgi

We re-adapt a spectral renormalization method, introduced in nonlinear optics, to solve the Kohn-Sham (KS) equations of density functional theory (DFT), with a focus on functionals based on the strictly-correlated electrons (SCE) regime, which are particularly challenging to converge. Important aspects of the method are: (i) the eigenvalues and the density a

Sabah Suhail, Rasheed Hussain, Abid Khan, Choong Seon Hong

The Internet of Things (IoT) is gaining ground as a pervasive presence around us by enabling miniaturized things with computation and communication capabilities to collect, process, analyze, and interpret information. Consequently, trustworthy data act as fuel for applications that rely on the data generated by these things, for critical decision-making proc

Roman Cherniha, Mykola Serov, Yulia Prystavka

A class of nonlinear reaction-diffusion-convection equations describing various processes in physics, biology, chemistry etc. is under study in the case of time and two space variables. The group of equivalence transformations is constructed, which is applied for deriving a Lie symmetry classification for the class of such equations by the well-known algorit

Jurek Leonhardt, Avishek Anand, Megha Khosla

The extraction of main content from web pages is an important task for numerous applications, ranging from usability aspects, like reader views for news articles in web browsers, to information retrieval or natural language processing. Existing approaches are lacking as they rely on large amounts of hand-crafted features for classification. This results in m

Fabio Benatti, Roberto Floreanini, Laleh Memarzadeh

Within the standard weak-coupling limit, the reduced dynamics of open quantum spin chains with their two end spins coupled to two distinct heat baths at different temperatures are mainly derived using the so-called \textit{global} and \textit{local} approaches, in which, respectively, the spin self-interaction is and is not taken into account. In order to co

Wei Ye, Ying Guo, Yun Mao, Hai Zhong

The discrete modulation can make up for the shortage of transmission distance in measurement-device-independent continuous-variable quantum key distribution (MDI-CVQKD) that has an unique advantage against all side-channel attacks but also challenging for the further performance improvement. Here we suggest a quantum catalysis (QC) approach for enhancing the

Noel Carroll, Kieran Conboy

Given the prevalence and effectiveness of agile methods at a team level, large organizations are now attempting to mimic this success at large scale by adopting large-scale methods such as Scaled Agile Framework (SAFe), Spotify, and Large Scale Scrum (LeSS). However, compared to insights on traditionally small scale methods, the extant literature provides sp

Jie Chen, Wenjun Xu

With reinforcement learning, an agent could learn complex behaviors from high-level abstractions of the task. However, exploration and reward shaping remained challenging for existing methods, especially in scenarios where the extrinsic feedback was sparse. Expert demonstrations have been investigated to solve these difficulties, but a tremendous number of h

E. V. Mikheeva, S. V. Repin, V. N. Lukash

We consider the black hole (BH) shadow images which can be restored by data processing and image recovery procedures in future space Very Large Baseline Interferometry (VLBI) missions. For Kerr BHs with masses and coordinates of SgrA*, M87* and M31*, illuminated by light source behind them, we consider three kinds of observation: the ground-based interferome

Arjun Srinivasan, Bongshin Lee, John Stasko

Multimodal interfaces that combine direct manipulation and natural language have shown great promise for data visualization. Such multimodal interfaces allow people to stay in the flow of their visual exploration by leveraging the strengths of one modality to complement the weaknesses of others. In this work, we introduce an approach that interweaves multimo

Roberta Fantoni, Luisa Caneve, Francesco Colao, Luca Fiorani

Laser induced fluorescence (LIF) is a powerful remote and non-invasive analysis technique that has been successfully applied to the real-time diagnosis of historical artworks. Hyperspectral images collection on fresco' s and their false colours processing allowed to reveal features invisible to the naked eye and to obtain specific information on pigments com

Niels M. P. Neumann

Quantum computing has great potential for advancing machine learning algorithms beyond classical reach. Even though full-fledged universal quantum computers do not exist yet, its expected benefits for machine learning can already be shown using simulators and already available quantum hardware. In this work, we focus on distance-based classification using ac

T. Shang, M. Smidman, A. Wang, L. -J. Chang

By employing a series of experimental techniques, we provide clear evidence that CaPtAs represents a rare example of a noncentrosymmetric superconductor which simultaneously exhibits nodes in the superconducting gap and broken time-reversal symmetry (TRS) in its superconducting state (below $T_c$ $\approx$ 1.5 K). Unlike in fully-gapped superconductors, the

Vahid Roostapour, Jakob Bossek, Frank Neumann

Evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more knowledge about the structure of optimal solutions is given, which can be leveraged by means of biased search operators. We consider the Minimu

Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert

Counterfactual reasoning from logged data has become increasingly important for many applications such as web advertising or healthcare. In this paper, we address the problem of learning stochastic policies with continuous actions from the viewpoint of counterfactual risk minimization (CRM). While the CRM framework is appealing and well studied for discrete

Sunseng Pyon, Daisuke Miyawaki, Tsuyoshi Tamegai, Satoshi Awaji

We fabricated (Ba,Na)Fe2As2 superconducting wires using the powder-in-tube method and hot isostatic pressing. By improving powder synthesis processes compared with previous studies, highly pure raw materials for the wire fabrication were obtained. The largest transport critical current density (Jc) reached 40 kAcm-2 at T = 4.2 K under a magnetic field of 100

Abbas Nasrollah Nejad, Ali Akbar Yazdan Pour

In this paper, we focus on the initial degree and the vanishing of the Valabrega-Valla module of a pair of monomials ideals $J\subseteq I$ in a polynomials ring over a field $\mathbb{K}$. We prove that the initial degree of this module is bounded above by the maximum degree of a minimal generators of $J$. For edge ideals of graphs, a complete characterizatio

K. Krasikov, V. Glushkov, S. Demishev, A. Khoroshilov

Precise angle-resolved magnetoresistance (ARM) measurements are applied to reveal the origin for the lowering of symmetry in electron transport and the emergence of a huge number of magnetic phases in the ground state of antiferromagnetic metal HoB12 with fcc crystal structure. By analyzing of the polar H-theta-phi magnetic phase diagrams of this compound re

Deng-Ping Fan, Tao Zhou, Ge-Peng Ji, Yi Zhou

Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT slices faces several

M. Kieburg, M. Lauritzen, B. T. Søgaard, K. Splittorff

A random matrix model for lattice QCD which takes into account the positive definite nature of the Wilson term is introduced. The corresponding effective theory for fixed index of the Wilson Dirac operator is derived to next to leading order. It reveals a new term proportional to the topological index of the Wilson Dirac operator and the lattice spacing. The

Tianyi Ren

We prove resolvent estimates in the Euclidean setting for Schr\"{o}dinger operators with potentials in Lebesgue spaces: $-\Delta+V$. The $(L^{2}, L^{p})$ estimates were already obtained by Blair-Sire-Sogge, but we extend their result to other $(L^{p}, L^{q})$ estimates using their idea and the result and method of Kwon-Lee on non-uniform resolvent estimates

Yufeng Zhang, Xueli Yu, Zeyu Cui, Shu Wu

Text classification is fundamental in natural language processing (NLP), and Graph Neural Networks (GNN) are recently applied in this task. However, the existing graph-based works can neither capture the contextual word relationships within each document nor fulfil the inductive learning of new words. In this work, to overcome such problems, we propose TextI

Krzysztof Frączek, Adam Kanigowski, Mariusz Lemańczyk

We prove that neither a prime nor {an l-almost prime} number theorem hold in the class of regular Toeplitz subshifts. But, {when a quantitative strengthening of the regularity with respect to the periodic structure involving Euler's totient function is assumed}, then the two theorems hold.

Jiebo Li, Zhen Chi, Ruzhan Qin, Li Yan

There are emerging applications for photothermal conversion utilizing MXene, but the mechanism under these applications related interfacial energy migration from MXene to the attached surface layer is still unknown. In this paper, with comprehensive ultrafast studies, we reported the energy migration pathway from MXene (Ti3C2Tx) to local environment under pl

Sarita Agrawal, Swadesh Kumar Sahoo

In this paper we study sharp estimates of pre-Schwarzian derivatives of functions belonging to the Nehari-type classes by using techniques from differential equations. In the sequel, we also see that a solution of a complex differential equation has a special form in terms of ratio of hypergeometric functions resulting to an integral representation. Finally,

H. Yamaguchi, T. Okita, Y. Iwasaki, Y. Kono

We present a mixed spin-(1/2, 5/2) chain composed of a charge-transfer salt (4-Br-$o$-MePy-V)FeCl$_4$. We observe the entire magnetization curve up to saturation, which exhibits a clear Lieb-Mattis magnetization plateau and subsequent quantum phase transition towards the gapless Luttinger-liquid phase. The observed magnetic behavior is quantitatively explain

Yu. A. Markov, M. A. Markova, N. Yu. Markov, D. M. Gitman

We have developed the Hamiltonian theory for collective longitudinally polarized colorless excitations (plasmons) in a high-temperature gluon plasma using the general formalism for constructing the wave theory in nonlinear media with dispersion, which was developed by V.E. Zakharov. In this approach, we have explicitly obtained a special canonical transforma

Antroy Roy Chowdhury, Shovan Maity, Shreyas Sen

In this paper, we present a theoretical analysis of different integrating front-ends employed in broad-band communications through \textit{lossy} channels. Time-domain receivers for broad-band communication typically deal with large integrated noise due to its high bandwidth of operation. However, unlike traditional wireline systems that are typically not no

Jesko Hecking-Harbusch, Niklas O. Metzger

The manual implementation of distributed systems is an error-prone task because of the asynchronous interplay of components and the environment. Bounded synthesis automatically generates an implementation for the specification of the distributed system if one exists. So far, bounded synthesis for distributed systems does not utilize their asynchronous nature

Shankey Kumar, Swadesh Kumar Sahoo

In this article, we study preserving properties of certain nonlinear integral transforms in some classical families of normalized analytic univalent functions defined in the unit disk. Also, we find sharp pre-Schwarzian norm estimates of such integrals.

George Drivas, Argyro Chatzopoulou, Leandros Maglaras, Costas Lambrinoudakis

The NIS Directive introduces obligations for the security of the network and information systems of operators of essential services and of digital service providers and require from the national competent authorities to assess their compliance to these obligations. This paper describes a novel cybersecurity maturity assessment framework (CMAF) that is tailor

Mark Grennan, Joeran Beel

Citation parsing, particularly with deep neural networks, suffers from a lack of training data as available datasets typically contain only a few thousand training instances. Manually labelling citation strings is very time-consuming, hence synthetically created training data could be a solution. However, as of now, it is unknown if synthetically created ref

Katsuhiro Tanaka, Chisa Hotta

We study numerically the thermodynamic properties of the spin nematic phases in a magnetic field in the spin-1 bilinear-biquadratic model. When the field is applied, the phase transition temperature once goes up and then decreases rapidly toward zero, which is detected by the peak-shift in the specific heat. The underlying mechanism of the reentrant behavior

Muhammad Subkhi Sadullah, Gaby Launay, Jayne Parle, Rodrigo Ledesma-Aguilar

We demonstrate spontaneous bidirectional motion of droplets on liquid infused surfaces in the presence of a topographical gradient, in which the droplets can move either toward the denser or the sparser solid fraction area. Our analytical theory explains the origin of this bidirectional motion. Furthermore, using both lattice Boltzmann simulations and experi

V. Andreoli, U. Munari

LAMOST J202629.80+423652.0 has been recently classified as a new symbiotic star containing a long-period Mira, surrounded by dust (D-type) and displaying in the optical spectra high ionization emission lines, including the Raman-scattered OVI at 6825 Ang. We have observed LAMOST J202629.80+423652.0 photometrically in the BVRI bands and spectroscopically over

A. Y. Q. Ho, S. R. Kulkarni, D. A. Perley, S. B. Cenko

We present optical, radio, and X-ray observations of SN2020bvc (=ASASSN20bs; ZTF20aalxlis), a nearby ($z=0.0252$; $d$=114 Mpc) broad-lined (BL) Type Ic supernova (SN). Our observations show that SN2020bvc shares several properties in common with the Ic-BL SN2006aj, which was associated with the low-luminosity gamma-ray burst (LLGRB) 060218. First, the 10 GHz

Nidhi Pandey, Mukul Gupta, Jochen Stahn

Nickel nitride (Ni-N) thin film samples were deposited using reactive magnetron sputtering process utilizing different partial flow of N2 (RN2). They were characterized using x-ray reflectivity (XRR), x-ray diffraction (XRD) and x-ray absorption near edge spectroscopy (XANES) taken at N K-edge and Ni L-edges. From XRR measurements, we find that the depositio

Wenhu Chen, Jianshu Chen, Yu Su, Zhiyu Chen

Neural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence. However, existing studies on neural NLG are primarily focused on surface-level realizations with limited emphasis on logical inference, an important aspect of human thinking and language. In this paper, we suggest a new NLG task where a model is

M. Nakad, T. Witelski, J. C. Domec, S. Sevanto

Sucrose is among the main products of photosynthesis that are deemed necessary for plant growth and survival. It is produced in the mesophyll cells of leaves and translocated to different parts of the plant through the phloem. Progress in understanding this transport mechanism remains fraught with experimental difficulties thereby prompting interest in theor

Jianhua Sun, Qinhong Jiang, Cewu Lu

Social interaction is an important topic in human trajectory prediction to generate plausible paths. In this paper, we present a novel insight of group-based social interaction model to explore relationships among pedestrians. We recursively extract social representations supervised by group-based annotations and formulate them into a social behavior graph,

Chen Liang, Linqi Guo, Alessandro Zocca, Shuyue Yu

The transmission grid is often comprised of several control areas that are connected by multiple tie lines in a mesh structure for reliability. It is also well-known that line failures can propagate non-locally and redundancy can exacerbate cascading. In this paper, we propose an integrated approach to grid reliability that (i) judiciously switches off a sma

Kayvan Kousha, Mike Thelwall

The COVID-19 pandemic requires a fast response from researchers to help address biological, medical and public health issues to minimize its impact. In this rapidly evolving context, scholars, professionals and the public may need to quickly identify important new studies. In response, this paper assesses the coverage of scholarly databases and impact indica

Yuwei Chuai, Jichang Zhao

Fake news that manipulates political elections, strikes financial systems, and even incites riots is more viral than real news online, resulting in unstable societies and buffeted democracy. The easier contagion of fake news online can be causally explained by the greater anger it carries. The same results in Twitter and Weibo indicate that this mechanism is

Min-hwan Oh, Garud Iyengar

One of the most interesting application scenarios in anomaly detection is when sequential data are targeted. For example, in a safety-critical environment, it is crucial to have an automatic detection system to screen the streaming data gathered by monitoring sensors and to report abnormal observations if detected in real-time. Oftentimes, stakes are much hi

Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow

Federated learning (FL) is an emerging distributed machine learning framework for collaborative model training with a network of clients (edge devices). FL offers default client privacy by allowing clients to keep their sensitive data on local devices and to only share local training parameter updates with the federated server. However, recent studies have s

Michael Small, David Cavanagh

We show that precise knowledge of epidemic transmission parameters is not required to build an informative model of the spread of disease. We propose a detailed model of the topology of the contact network under various external control regimes and demonstrate that this is sufficient to capture the salient dynamical characteristics and to inform decisions. C

Derek Fujimoto

Used to store the results of $\mu$SR measurements at TRIUMF, the Muon Data (MUD) file format serves as a useful and flexible scheme that is both lightweight and self-describing. The application programming interface (API) for these files is written in C and FORTRAN, languages not known for their ease of use. In contrast, Python is a language which emphasizes

Pietro Tedeschi, Savio Sciancalepore, Roberto Di Pietro

The recent advancements in hardware miniaturization capabilities have boosted the diffusion of systems based on Energy Harvesting (EH) technologies, as a means to power embedded wireless devices in a sustainable and low-cost fashion. Despite the undeniable management advantages, the intermittent availability of the energy source and the limited power supply

Y. Ben-Aryeh

The free electron model with Boltzmann statistics for spherical low-density plasmas (Scientific Reports 9. 20384, 2019) is developed further by numerical calculations with asymptotic relations obtaining the density of electrons, mass densities and the potentials of such plasmas. Solutions are developed as function of a pure number x proportional to the dista

M. Kh. Hamad, M. H. A. Mhareb, Y. S. Alajeramid, M. I. Sayyed

In this work, we investigate the effect of Ni concentration on several shielding properties of $Nd_{0.6}Sr_{0.4}Mn_{1-y}Ni_{y}O_{3}$ (0.00 $\leq$ y $\leq$ 0.20) perovskite ceramic for possible use as radiation shielding materials. X-ray diffraction (XRD) analysis revealed that these ceramics have the orthorhombic structure with group space Pnma over a wide r

Qiang Dong, Quan Yuan, Yang-Bo Shi

The primary goal of a recommender system is often known as "helping users find relevant items", and a lot of recommendation algorithms are proposed accordingly. However, these accuracy-oriented methods usually suffer the problem of recommendation bias on popular items, which is not welcome to not only users but also item providers. To alleviate the recommend

Remy Adderton, Murray T. Batchelor, Paul Wedrich

The hamiltonian of the $N$-state superintegrable chiral Potts (SICP) model is written in terms of a coupled algebra defined by $N-1$ types of Temperley-Lieb generators. This generalises a previous result for $N=3$ obtained by J. F. Fjelstad and T. M\r{a}nsson [J. Phys. A {\bf 45} (2012) 155208]. A pictorial representation of a related coupled algebra is give

Sophie N. Parragh, Fabien Tricoire, Walter Gutjahr

In many real-world optimization problems, more than one objective plays a role and input parameters are subject to uncertainty. In this paper, motivated by applications in disaster relief and public facility location, we model and solve a bi-objective stochastic facility location problem. The considered objectives are cost and uncovered demand, whereas the d

TJ Tsai

This paper investigates the problem of matching a MIDI file against a large database of piano sheet music images. Previous sheet-audio and sheet-MIDI alignment approaches have primarily focused on a 1-to-1 alignment task, which is not a scalable solution for retrieval from large databases. We propose a method for scalable cross-modal retrieval that might be

Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang

We consider representation learning (hypothesis class $\mathcal{H} = \mathcal{F}\circ\mathcal{G}$) where training and test distributions can be different. Recent studies provide hints and failure examples for domain invariant representation learning, a common approach for this problem, but the explanations provided are somewhat different and do not provide a

Alan A. Kaptanoglu, Kyle D. Morgan, Chris J. Hansen, Steven L. Brunton

Plasmas are highly nonlinear and multi-scale, motivating a hierarchy of models to understand and describe their behavior. However, there is a scarcity of plasma models of lower fidelity than magnetohydrodynamics (MHD), although these reduced models hold promise for understanding key physical mechanisms, efficient computation, and real-time optimization and c

F. A. Aliev, N. A. Aliev, N. A. Ismailov

A mathematical model of oscillatory systems control with liquid dampers is considered which differs from the classical ones by replacing the first derivative of such a fractional derivative that is between numbers 0 and 2 other than unity. Using the methods of constructing Letov controllers, a control law is constructed that ensures the asymptotic stability

Bulat N. Khabibullin

Let $u\not\equiv -\infty$ be a subharmonic function on the complex plane $\mathbb C$. In 2016, we obtained a result on the existence of an entire function $f\neq 0$ satisfying the estimate $\log|f|\leq {\sf B}_u$ on $\mathbb C$, where functions ${\sf B}_u$ are integral averages of $u$ for rapidly shrinking disks as it approaches infinity. We give another equ

Qing Han, Shusen Yang, Xuebin Ren, Cong Zhao

Distributed machine learning (ML) at network edge is a promising paradigm that can preserve both network bandwidth and privacy of data providers. However, heterogeneous and limited computation and communication resources on edge servers (or edges) pose great challenges on distributed ML and formulate a new paradigm of Edge Learning (i.e. edge-cloud collabora

A. Pérez-Romero, R. Franco, J. Silva-Valencia

We explore the zero-temperature phase diagram of a one-dimensional gas composed of three-color fermions, which interact locally and with their next neighbors. Using the density matrix renormalization group method and considering one-third filling, we characterize the ground state for several values of the parameters, finding diverse phases, namely: phase sep

Jingfeng Zhang, Cheng Li, Antonio Robles-Kelly, Mohan Kankanhalli

When the federated learning is adopted among competitive agents with siloed datasets, agents are self-interested and participate only if they are fairly rewarded. To encourage the application of federated learning, this paper employs a management strategy, i.e., more contributions should lead to more rewards. We propose a novel hierarchically fair federated

Liemao Cao, Guanghui Zhou, Qingyun Wu, Shengyuan A. Yang

Ultrathin films of topological Dirac semimetal, Na$_3$Bi, has recently been revealed as an unusual electronic materials with field-tunable topological phases. Here we investigate the electronic and transport properties of ultrathin Na$_3$Bi as an electrical contact to two-dimensional (2D) metal, i.e. graphene, and 2D semiconductor, i.e. MoS$_2$ and WS$_2$ mo

Jianhai Bao, Jian Wang

In this paper, by invoking the coupling approach, we establish exponential ergodicity under the $L^1 $-Wasserstein distance for two-factor affine processes. The method employed herein is universal in a certain sense so that it is applicable to general two-factor affine processes, which allow that the first component solves a general CIR process, and that the

Mingyi Liu, Zhiying Tu, Xiaofei Xu, Zhongjie Wang

Services are flourishing drastically both on the Internet and in the real world. Additionally, services have become much more interconnected to facilitate transboundary business collaboration to create and deliver distinct new values to customers. Various service ecosystems have become a focus in both research and practice. However, due to the lack of widely

J. Wilkins, M. V. Nguyen, B. Rahmani

Lawn area measurement is an application of image processing and deep learning. Researchers have been used hierarchical networks, segmented images and many other methods to measure lawn area. Methods effectiveness and accuracy varies. In this project Image processing and deep learning methods has been compared to find the best way to measure the lawn area. Th

Wei Niu, Pu Zhao, Zheng Zhan, Xue Lin

High-end mobile platforms rapidly serve as primary computing devices for a wide range of Deep Neural Network (DNN) applications. However, the constrained computation and storage resources on these devices still pose significant challenges for real-time DNN inference executions. To address this problem, we propose a set of hardware-friendly structured model p

Zhe Wang, Pradeep Subedi, Shaohua Duan, Yubo Qin

In order to achieve near-time insights, scientific workflows tend to be organized in a flexible and dynamic way. Data-driven triggering of tasks has been explored as a way to support workflows that evolve based on the data. However, the overhead introduced by such dynamic triggering of tasks is an under-studied topic. This paper discusses different facets of

Colin M. Chow, Hongyi Yu, John R. Schaibley, Pasqual Rivera

Auger recombination in semiconductors is a many-body phenomenon in which recombination of electrons and holes is accompanied by excitation of other charge carriers. Being nonradiative, it is detrimental to light emission. The excess energy of the excited carriers is normally rapidly converted to heat, making Auger processes difficult to probe directly. Here,

X. Xu, Y. W. Li, S. R. Duan, S. L. Zhang

The van der Waals ferromagnet Fe$_3$GeTe$_2$ has recently attracted extensive research attention due to its intertwined magnetic, electronic and topological properties. Here, using high-resolution angle-resolved photoemission spectroscopy, we systematically investigate the temperature evolution of the electronic structure of bulk Fe$_3$GeTe$_2$. We observe l

Artem Chernikov, Kyle Gannon

We initiate a systematic study of the convolution operation on Keisler measures, generalizing the work of Newelski in the case of types. Adapting results of Glicksberg, we show that the supports of generically stable (or just definable, assuming NIP) measures are nice semigroups, and classify idempotent measures in stable groups as invariant measures on type

Zequn Sun, Jiacheng Huang, Wei Hu, Muchao Chen

Learning knowledge graph (KG) embeddings has received increasing attention in recent years. Most embedding models in literature interpret relations as linear or bilinear mapping functions to operate on entity embeddings. However, we find that such relation-level modeling cannot capture the diverse relational structures of KGs well. In this paper, we propose

Daniel Mas Montserrat, Carlos Bustamante, Alexander Ioannidis

Local-ancestry inference (LAI), also referred to as ancestry deconvolution, provides high-resolution ancestry estimation along the human genome. In both research and industry, LAI is emerging as a critical step in DNA sequence analysis with applications extending from polygenic risk scores (used to predict traits in embryos and disease risk in adults) to gen

Nicholas Soures, David Chambers, Zachariah Carmichael, Anurag Daram

The SARS-CoV-2 infectious outbreak has rapidly spread across the globe and precipitated varying policies to effectuate physical distancing to ameliorate its impact. In this study, we propose a new hybrid machine learning model, SIRNet, for forecasting the spread of the COVID-19 pandemic that couples with the epidemiological models. We use categorized spatiot

Wanhua Li, Yingqiang Zhang, Kangchen Lv, Jiwen Lu

In this paper, we propose a graph-based kinship reasoning (GKR) network for kinship verification, which aims to effectively perform relational reasoning on the extracted features of an image pair. Unlike most existing methods which mainly focus on how to learn discriminative features, our method considers how to compare and fuse the extracted feature pair to

Dong-Liang Fang, Amand Faessler

With partially restored isospin symmetry, we calculate the nuclear matrix element for a special decay mode of $2\nu\beta\beta$ (two neutrino double beta decay) -- the decay to the first $2^+$ excited states. With the realistic CD-Bonn nuclear force, we analyze the dependence of the nuclear matrix elements on the iso-vector and iso-scalar parts of proton-neut

Layne B. Frechette, Christoph Dellago, Phillip L. Geissler

Simple elastic models of spin-crossover compounds are known empirically to exhibit classical critical behavior. We demonstrate how the long-ranged interactions responsible for this behavior arise naturally upon integrating out mechanical fluctuations of such a model. A mean field theory applied to the resulting effective Hamiltonian quantitatively accounts f

Jun Xu, Mouyuan Sun, Yongquan Xue, Junyao Li

The dusty torus plays a vital role in unifying active galactic nuclei (AGNs). However, the physical structure of the torus remains largely unclear. Here we present a systematical investigation of the torus mid-infrared (MIR) spectroscopic feature, i.e., the 9.7 um silicate line, of $175$ AGNs selected from the Swift/BAT Spectroscopic Survey (BASS). Our sampl

Wei Li, Alexey Ovchinnikov, Gleb Pogudin, Thomas Scanlon

Consider an algorithm computing in a differential field with several commuting derivations such that the only operations it performs with the elements of the field are arithmetic operations, differentiation, and zero testing. We show that, if the algorithm is guaranteed to terminate on every input, then there is a computable upper bound for the size of the o

H. G. Zhang, D. Angelaszek, M. Copley, J. H. Han

The Cosmic Ray Energetics And Mass experiment for the International Space Station (ISS-CREAM) was installed on the ISS to measure high-energy cosmic-ray elemental spectra for the charge range $\rm Z=1$ to 26. The ISS-CREAM instrument includes a tungsten scintillating-fiber calorimeter preceded by a carbon target for energy measurements. The carbon target ind

Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li

Recent studies have shown that graph convolution networks (GCNs) are vulnerable to carefully designed attacks, which aim to cause misclassification of a specific node on the graph with unnoticeable perturbations. However, a vast majority of existing works cannot handle large-scale graphs because of their high time complexity. Additionally, existing works mai

Shusuke Takada, Kenichiro Tateishi, Yasuo Wakabayashi, Yoshimasa Ikeda

For the polarization of neutrons with an energy level of \textcolor{black}{$>0.1$ eV}, we developed a novel polarized proton spin filter based on dynamic nuclear polarization using photo-excited triplet electron spins. The spin filter consists of a single crystal of naphthalene doped with deuterated pentacene and has a size of $\phi15\times4$ ${\rm mm}^3$, a

Juan Kalemkerian

We extend the theoretical results for any FOU(p) processes for the case in which the Hurst parameter is less than 1/2 and we show theoretically and by simulations that under some conditions on T and the sample size n it is possible to obtain consistent estimators of the parameters when the process is observed in a discretized and equispaced interval [0, T ].

Edinah K. Gnang, Fan Tian

We propose a new hypermatrix singular value decomposition based upon the spectral decomposition of the symmetric products of transposes.

Sergey Norin, Luke Postle

In 1943, Hadwiger conjectured that every graph with no $K_t$ minor is $(t-1)$-colorable for every $t\ge 1$. While Hadwiger's conjecture does not hold for list-coloring, the linear weakening is conjectured to be true. In the 1980s, Kostochka and Thomason independently proved that every graph with no $K_t$ minor has average degree $O(t\sqrt{\log t})$ and thus

Chi Hong Chow, Naichung Conan Leung

Let $(X,\omega)$ be a compact symplectic manifold whose first Chern class $c_1(X)$ is divisible by a positive integer $n$. We construct a $\mathbb{Z}_{2n}$-action on its Fukaya category $Fuk(X)$ and a $\mathbb{Z}_n$-action on the local models of its moduli of Lagrangian branes. We show that this action is compatible with the gluing functions for different lo

Ying Da Wang, Traiwit Chung, Ryan T. Armstrong, Peyman Mostaghimi

Simulation of fluid flow in porous media has many applications, from the micro-scale (cell membranes, filters, rocks) to macro-scale (groundwater, hydrocarbon reservoirs, and geothermal) and beyond. Direct simulation of flow in porous media requires significant computational resources to solve within reasonable timeframes. An integrated method combining pred

Reza Pourreza, Nasser Kehtarnavaz

High-dynamic-range (HDR) photography involves fusing a bracket of images taken at different exposure settings in order to compensate for the low dynamic range of digital cameras such as the ones used in smartphones. In this paper, a method for automatically selecting the exposure settings of such images is introduced based on the camera characteristic functi

Zhikun Han, Yuqian Dong, Baojie Liu, Xiaopei Yang

Based on the geometrical nature of quantum phases, non-adiabatic holonomic quantum control (NHQC) has become a standard technique for enhancing robustness in constructing quantum gates. However, the conventional approach of NHQC is sensitive to control instability, as it requires the driving pulses to cover a fixed pulse area. Furthermore, even for small-ang

P. Myles Eugenio, Ceren B. Dağ

Strong interactions between electrons occupying bands of opposite (or like) topological quantum numbers (Chern$=\pm1$), and with flat dispersion, are studied by using lowest Landau level (LLL) wavefunctions. More precisely, we determine the ground states for two scenarios at half-filling: (i) LLL's with opposite sign of magnetic field, and therefore opposite

Manisha Verma, Sudhakar Kumawat, Yuta Nakashima, Shanmuganathan Raman

Human pose estimation is a well-known problem in computer vision to locate joint positions. Existing datasets for the learning of poses are observed to be not challenging enough in terms of pose diversity, object occlusion, and viewpoints. This makes the pose annotation process relatively simple and restricts the application of the models that have been trai

Pinjia He, Clara Meister, Zhendong Su

Machine translation software has seen rapid progress in recent years due to the advancement of deep neural networks. People routinely use machine translation software in their daily lives, such as ordering food in a foreign restaurant, receiving medical diagnosis and treatment from foreign doctors, and reading international political news online. However, du

Chen Luo, Michael J. Carey

Log-Structured Merge-trees (LSM-trees) have been widely used in modern NoSQL systems. Due to their out-of-place update design, LSM-trees have introduced memory walls among the memory components of multiple LSM-trees and between the write memory and the buffer cache. Optimal memory allocation among these regions is non-trivial because it is highly workload-de