May 2020 arXiv papers — page 44

ALICE Collaboration

Measurements of the inclusive J/$\psi$ yield as a function of charged-particle pseudorapidity density ${\rm d}N_{\rm ch}/\rm{d}\eta$ in pp collisions at $\sqrt{s}$ = 13 TeV with ALICE at the LHC are reported. The J/$\psi$ meson yield is measured at midrapidity ($|y|<0.9$) in the dielectron channel, for events selected based on the charged-particle multiplici

ALICE Collaboration

In this Letter, we report the first measurement of the inelastic cross section for antideuteron-nucleus interactions at low particle momenta, covering a range of $0.3 \leq p < 4$ GeV/$c$. The measurement is carried out using p-Pb collisions at a center-of-mass energy per nucleon-nucleon pair of $\sqrt{s_{\rm{NN}}}$ = 5.02 TeV, recorded with the ALICE detecto

Peter Kevei, Dalia Terhesiu

We obtain a strong renewal theorem with infinite mean beyond regular variation, when the underlying distribution belongs to the domain of geometric partial attraction a semistable law with index $\alpha\in (1/2,1]$. In the process we obtain local limit theorems for both finite and infinite mean, that is for the whole range $\alpha\in (0,2)$. We also derive t

ALICE Collaboration

The production of $\pi^{\pm}$, $\rm{K}^{\pm}$, $\rm{K}^{0}_{S}$, $\rm{K}^{*}(892)^{0}$, $\rm{p}$, $\phi(1020)$, $\Lambda$, $\Xi^{-}$, $\Omega^{-}$, and their antiparticles was measured in inelastic proton-proton (pp) collisions at a center-of-mass energy of $\sqrt{s}$ = 13 TeV at midrapidity ($|y|<0.5$) as a function of transverse momentum ($p_{\rm{T}}$) usi

Diana Vaclavkova, Alex Delhomme, Clément Faugeras, Marek Potemski

We report experimental and theoretical studies on the magnetoelastic interactions in MnPS$_3$. Raman scattering response measured as a function of temperature shows a blue shift of the Raman active modes at 120.2 and 155.1 cm$^{-1}$, when the temperature is raised across the antiferromagnetic-paramagnetic transition. Density functional theory (DFT) calculati

Yi Feng, Di Li, Zheng Zheng, Chao-Wei Tsai

Supermassive black holes are commonly found in the center of galaxies and evolve with their hosts. The supermassive binary black holes (SMBBH) are thus expected to exist in close galaxy pairs, however, none has been unequivocally detected. The square kilometre array (SKA) is a multi-purpose radio telescope with a collecting area approaching 1 million square

Bing Sun, Yao Ma, Liangyun Chen

The purpose of this paper is to determine skew-symmetric biderivations $\text{Bider}_{\text{s}}(L, V)$ and commuting linear maps $\text{Com}(L, V)$ on a Hom-Lie algebra $(L,\alpha)$ having their ranges in an $(L,\alpha)$-module $(V, \rho, \beta)$, which are both closely related to $\text{Cent} (L, V)$, the centroid of $(V, \rho, \beta)$. Specifically, under

Jacques Dark, Christian Konrad

In this paper, we give simple optimal lower bounds on the one-way two-party communication complexity of approximate Maximum Matching and Minimum Vertex Cover with deletions. In our model, Alice holds a set of edges and sends a single message to Bob. Bob holds a set of edge deletions, which form a subset of Alice's edges, and needs to report a large matching

Ansgar Steland

Supervised learning by extreme learning machines resp. neural networks with random weights is studied under a non-stationary spatial-temporal sampling design which especially addresses settings where an autonomous object moving in a non-stationary spatial environment collects and analyzes data. The stochastic model especially allows for spatial heterogeneity

Masahide Ito

This paper addresses a motion planning problem of the second-order chained form system. The author presents a novel control approach based on switching a state. The second-order chained form system is composed of three subsystems including two double integrators and a nonlinear system. Switching a single state of the double integrators can modify the nature

P. Giannakeas, Matthew T. Eiles, F. Robicheaux, Jan-Michael Rost

We predict the existence of a universal class of ultralong-range Rydberg molecular states whose vibrational spectra form trimmed Rydberg series. A dressed ion-pair model captures the physical origin of these exotic molecules, accurately predicts their properties, and reveals features of ultralong-range Rydberg molecules and heavy Rydberg states with a surpri

Johann Ostmeyer, Evan Berkowitz, Stefan Krieg, Timo A. Lähde

We take advantage of recent improvements in the grand canonical Hybrid Monte Carlo algorithm, to perform a precision study of the single-particle gap in the hexagonal Hubbard model, with on-site electron-electron interactions. After carefully controlled analyses of the Trotter error, the thermodynamic limit, and finite-size scaling with inverse temperature,

Lorenzo David

In this article, we give a formula for the generalization of the binomial coefficient to the complex numbers as a linear combination of $\sinc$ functions. We then give a general formula to compute the integral on the real line of the product of the binomial coefficient and a given function, which, in some cases, turns out to be equal to the series of their v

Farmer Schlutzenberg

We prove a weakened version of the reflection of Reinhardt cardinals by super Reinhardt cardinals: Let $M=(V^M,P)$ be a countable model of second order set theory $\mathsf{ZF}_2$ (with universe $V^M$ and classes $P$) which models "$\kappa$ is super Reinhardt". We show that there are unboundedly many $\mu<\kappa$ such that there is $j$ such that $(V^M,j)$ mod

Jakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch

Deep Gaussian Processes learn probabilistic data representations for supervised learning by cascading multiple Gaussian Processes. While this model family promises flexible predictive distributions, exact inference is not tractable. Approximate inference techniques trade off the ability to closely resemble the posterior distribution against speed of converge

S. Q. Zhong, Z. G. Dai, H. M. Zhang, C. M. Deng

Owing to the detection of an extremely bright fast radio burst (FRB) 200428 associated with a hard X-ray counterpart from the magnetar soft gamma-ray repeater (SGR) 1935+2154, the distance of SGR 1935+2154 potentially hosted in the supernova remnant (SNR) G57.2+0.8 can be revisited. Under the assumption that the SGR and the SNR are physically related, in thi

Juan Carlos Naranjo, Ángela Ortega

We prove that the ramified Prym map $\mathcal P_{g, r}$ which sends a covering $\pi:D\longrightarrow C$ ramified in $r$ points to the Prym variety $P(\pi):=\text{Ker}(\text{Nm}_{\pi})$ is an embedding for all $r\ge 6$ and for all $g(C)>0$. Moreover, by studying the restriction to the locus of coverings of hyperelliptic curves, we show that $\mathcal P_{g, 2}

Kisung You

Discovering patterns of the complex high-dimensional data is a long-standing problem. Dimension Reduction (DR) and Intrinsic Dimension Estimation (IDE) are two fundamental thematic programs that facilitate geometric understanding of the data. We present Rdimtools - an R package that supports 133 DR and 17 IDE algorithms whose extent makes multifaceted scruti

M. Kiani

In this paper, the generalized regression neural network is used to predict the GNSS position time series. Using the IGS 24-hour final solution data for Bad Hamburg permanent GNSS station in Germany, it is shown that the larger the training of the network, the higher the accuracy is, regardless of the time span of the time series. In order to analyze the per

Ömer Faruk Bağ, Vera Fischer

We show that generalized eventually narrow sequences on a strongly inaccessible cardinal $\kappa$ are preserved under the Cummings-Shaleh non-linear iterations of the higher Hechler forcing on $\kappa$. Moreover assuming GCH, $\kappa^{<\kappa}=\kappa$, we show that: (1) if $\kappa$ is strongly unfoldable, $\kappa^+\leq\beta=\hbox{cf}(\beta)\leq \hbox{cf}(\de

N Nandy, S Pradhan

Due to the widespread applicability of discrete-time queues in wireless networks or telecommunication systems, this paper analyzes an infinite-buffer batch-service queue with single and multiple vacation where customers/messages arrive according to the Bernoulii process and service time varies with the batch-size. The foremost focal point of this analysis is

Changjie Cheng, Bin Shu, Yang Zeng

Considering the general linear Lie superalgebra $\mathfrak{gl}(m|n)=\mathfrak{gl}(m|n)_{\bar{\bar 0}}\oplus \mathfrak{gl}(m|n)_{\bar{\bar 1}}$ over $\mathbb{C}$, we first formulate a super version of Vust theorem associated with a principal nilpotent element $e\in \mathfrak{gl}(m|n)_{\bar{\bar 0}}$. As an application of this theorem, we then obtain a Schur-S

Fariba Abbasi, Emanuele Viterbo

In this paper, we modify polar codes constructed with some 2^t x 2^t polarization kernels to reduce the time complexity of the window decoding. This modification is based on the permutation of the columns of the kernels. This method is applied to some of the kernels constructed in the literature of size 16 and 32, with different error exponents and scaling e

Javier Hernandez-Ortega, Julian Fierrez, Aythami Morales, David Diaz

This paper presents a comparative evaluation of methods for remote heart rate estimation using face videos, i.e., given a video sequence of the face as input, methods to process it to obtain a robust estimation of the subjects heart rate at each moment. Four alternatives from the literature are tested, three based in hand crafted approaches and one based on

Julien Bringer, Hervé Chabanne, Linda Guiga

Neural Networks (NNs) are today used for all our daily tasks; for instance, in mobile phones. We here want to show how to restrict their access to privileged users. Our solution relies on a degraded implementation which can be corrected thanks to a PIN. We explain how to select a few parameters in an NN so as to maximize the gap in the accuracy between the p

Robert Brandenberger, Bryce Cyr, Hao Jiao

We compute the energy spectrum of photons and neutrinos produced by the unwinding of a scaling distribution of cosmic textures, and discuss the implications for the spectrum of high energy cosmic rays, and for CMB spectral distortions. Textures lead to a contribution to the photon flux which scales as $E^3 F(E) \sim E^{3/2}$. Hence, the tightest constraints

Dufan Wu, Daniel Montes, Ziheng Duan, Yangsibo Huang

Purpose: To develop CADIA, a supervised deep learning model based on a region proposal network coupled with a false-positive reduction module for the detection and localization of intracranial aneurysms (IA) from computed tomography angiography (CTA), and to assess our model's performance to a similar detection network. Methods: In this retrospective study,

Ömer Faruk Bağ, Vera Fischer

Developing a system of parallel non-linear iterations, we establish the consistency of $\mathfrak{b}<\mathfrak{s}<\mathfrak{d}<\mathfrak{c}$ where $\mathfrak{b}, \mathfrak{d}, \mathfrak{c}$ are arbitrary subject to the known ZFC restrictions and $\mathfrak{s}$ is regular. By evaluating other invariants we achieve also the constellations $\mathfrak{b}<\mathfr

Reto Hofstetter, Klaus M. Miller, Harley Krohmer, Z. John Zhang

Knowledge of consumers' willingness to pay (WTP) is a prerequisite to profitable price-setting. To gauge consumers' WTP, practitioners often rely on a direct single question approach in which consumers are asked to explicitly state their WTP for a product. Despite its popularity among practitioners, this approach has been found to suffer from hypothetical bi

Yaniv Ganor, Shira Tanny

We study the Floer-theoretic interaction between disjointly supported Hamiltonians by comparing Floer-theoretic invariants of these Hamiltonians with the ones of their sum. These invariants include spectral invariants, boundary depth and Abbondandolo-Haug-Schlenk's action selector. Additionally, our method shows that in certain situations the spectral invari

Arindam Biswas, Jyoti Prakash Saha

Given two nonempty subsets $A, B$ of a group $G$, they are said to form a co-minimal pair if $A \cdot B = G$, and $A' \cdot B \subsetneq G$ for any $\emptyset \neq A' \subsetneq A$ and $A\cdot B' \subsetneq G$ for any $\emptyset \neq B' \subsetneq B$. In this article, we show several new results on co-minimal pairs in the integers and the integral lattices.

Francesco Verdoja, Ville Kyrki

The most common way for robots to handle environmental information is by using maps. At present, each kind of data is hosted on a separate map, which complicates planning because a robot attempting to perform a task needs to access and process information from many different maps. Also, most often correlation among the information contained in maps obtained

Yania Molina Souto, Rafael Pereira, Rocío Zorrilla, Anderson Chaves

In this paper, we present a cost-based approach for the automatic selection and allocation of a disjoint ensemble of black-box predictors to answer predictive spatio-temporal queries. Our approach is divided into two parts -- offline and online. During the offline part, we preprocess the predictive domain data -- transforming it into a regular grid -- and th

Yuanxin Ye, Chao Yang, Bai Zhu, Youquan He

Co-registering the Sentinel-1 SAR and Sentinel-2 optical data of European Space Agency (ESA) is of great importance for many remote sensing applications. However, we find that there are evident misregistration shifts between the Sentinel-1 SAR and Sentinel-2 optical images that are directly downloaded from the official website. To address that, this paper pr

Christian Brahms, Federico Belli, John C. Travers

Resonant dispersive wave (RDW) emission in gas-filled hollow waveguides is a powerful technique for the generation of bright few-femtosecond laser pulses from the vacuum ultraviolet to the near infrared. Here we investigate deep-ultraviolet RDW emission in a hollow capillary fibre filled with a longitudinal gas pressure gradient. We obtain broadly similar em

O. B. Zaslavskii

We consider collision of two particles 1 and 2 near the horizon of the extremal Reissner-Nordstr\"{o}m (RN) black hole that produce two other particles 3 and 4. There exists such a scenario that both new particles fall in a black hole. One of them emerges from the white hole horizon in the asymptotically flat region, the other one oscillates between turning

P. Harmanec, J. Lipták, P. Koubský, H. Božić

We confirmed the binary nature of the Be star 7~Vul, derived a~more accurate spectroscopic orbit with an orbital period of (69.4212+/-0.0034) d, and improved the knowledge of the basic physical elements of the system. Analyzing available photometry and the strength of the \ha emission, we also document the long-term spectral variations of the Be primary. In

Christian Schaaf, Holger Stark

Staggered and linear multi-particle trains constitute characteristic structures in inertial microfluidics. Using lattice-Boltzmann simulations, we investigate their properties and stability, when flowing through microfluidic channels. We confirm the stability of cross-streamline pairs by showing how they contract or expand to their equilibrium axial distance

David J. Skelton, Aoesha Alsobhe, Elisa Anastasi, Christian Atallah

Severe acute respiratory syndrome coronavirus two (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents an unprecedented global health challenge. Consequently, a large amount of research into the disease pathogenesis and potential treatments has been carried out in a short time frame. However, developing novel d

Paul K. Gorbow, Graham E. Leigh

We develop an untyped framework for the multiverse of set theory. $\mathsf{ZF}$ is extended with semantically motivated axioms utilizing the new symbols $\mathsf{Uni}(\mathcal{U})$ and $\mathsf{Mod}(\mathcal{U, \sigma})$, expressing that $\mathcal{U}$ is a universe and that $\sigma$ is true in the universe $\mathcal{U}$, respectively. Here $\sigma$ ranges ov

Murat Abdughani, Daohan Wang, Lei Wu, Jin Min Yang

Measuring the triple Higgs coupling is a crucial task in the LHC and future collider experiments. We apply the Message Passing Neural Network (MPNN) to the study of the non-resonant Higgs pair production process $pp \to hh$ in the final state with $2b + 2\ell + E_{\rm T}^{\rm miss}$ at the LHC. Although the MPNN can improve the signal significance, it is sti

Timoteo Carletti, Duccio Fanelli, Francesco Piazza

When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by the WHO in March 2020, the scientific community had already braced up in the effort of making sense of the fast-growing wealth of data gathered by national authorities all over the world. However, despite the diversity of novel theoretical approaches and the compreh

Rana Hanocka, Gal Metzer, Raja Giryes, Daniel Cohen-Or

In this paper, we introduce Point2Mesh, a technique for reconstructing a surface mesh from an input point cloud. Instead of explicitly specifying a prior that encodes the expected shape properties, the prior is defined automatically using the input point cloud, which we refer to as a self-prior. The self-prior encapsulates reoccurring geometric repetitions f

Murat Altunbas, Ramazan Simsek, Aydin Gezer

Let $(M_{2k},\varphi ,g)$ be an almost anti-paraHermitian manifold and $(TM,g_{BS})$ be its tangent bundle with a Berger type deformed Sasaki metric $g_{BS}$. In this paper, we deal with the harmonicity of the canonical projection $\pi :TM\rightarrow M$ and a vector field $\xi $ which is considered as a map $\xi :M\rightarrow TM$.

Andrei Kucharavy, El Mahdi El Mhamdi, Rachid Guerraoui

Generative adversarial networks (GANs) are pairs of artificial neural networks that are trained one against each other. The outputs from a generator are mixed with the real-world inputs to the discriminator and both networks are trained until an equilibrium is reached, where the discriminator cannot distinguish generated inputs from real ones. Since their in

Maxime Chamberland, Sila Genc, Erika P. Raven, Greg D. Parker

There is an urgent need for a paradigm shift from group-wise comparisons to individual diagnosis in diffusion MRI (dMRI) to enable the analysis of rare cases and clinically-heterogeneous groups. Deep autoencoders have shown great potential to detect anomalies in neuroimaging data. We present a framework that operates on the manifold of white matter (WM) path

Natalia Vesselinova, Rebecca Steinert, Daniel F. Perez-Ramirez, Magnus Boman

Existing approaches to solving combinatorial optimization problems on graphs suffer from the need to engineer each problem algorithmically, with practical problems recurring in many instances. The practical side of theoretical computer science, such as computational complexity, then needs to be addressed. Relevant developments in machine learning research on

Kimet Jusufi, Muhammed Amir, Md Sabir Ali, Sunil D. Maharaj

We study quasinormal modes (QNMs) in 5D electrically charged Bardeen black holes spacetime by considering the scalar and electromagnetic field perturbations. The black holes spacetime is an exact solution of Einstein gravity coupled to nonlinear electrodynamics in five dimensions, which has nonsingular behavior. To calculate QNMs, we use the WKB approximatio

Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han

We study the problem of semi-supervised learning on graphs, for which graph neural networks (GNNs) have been extensively explored. However, most existing GNNs inherently suffer from the limitations of over-smoothing, non-robustness, and weak-generalization when labeled nodes are scarce. In this paper, we propose a simple yet effective framework -- GRAPH RAND

Yuichi Harikane, Nicolas Laporte, Richard S. Ellis, Yoshiki Matsuoka

We examine the absorption line spectra of a sample of 31 luminous (M_UV=-23) Lyman break galaxies at redshift z~6 using data taken with the FOCAS and OSIRIS spectrographs on the Subaru and GTC telescopes. For two of these sources we present longer exposure data taken at higher spectral resolution from ESO's X-shooter spectrograph. Using these data, we demons

Donghao Xu, Zhezhang Ding, Chenfeng Tu, Huijing Zhao

Intra-driver and inter-driver heterogeneity has been confirmed to exist in human driving behaviors by many studies. In this study, a joint model of the two types of heterogeneity in car-following behavior is proposed as an approach of driver profiling and identification. It is assumed that all drivers share a pool of driver states; under each state a car-fol

Hui Tong, Mu-Xin Liu, Yi-Ming Hu, Man Leong Chan

The multi-messenger observation of compact binary coalescence promises great scientific treasure. However, a synthetic observation from both gravitational wave and electromagnetic channels remains challenging. Relying on the day-to-week long macronova emission, GW170817 remains the only event with successful electromagnetic followup. In this manuscript, we e

Hanchu Zhang, Leonhard Hennig, Christoph Alt, Changjian Hu

Named Entity Recognition (NER) in domains like e-commerce is an understudied problem due to the lack of annotated datasets. Recognizing novel entity types in this domain, such as products, components, and attributes, is challenging because of their linguistic complexity and the low coverage of existing knowledge resources. To address this problem, we present

George Kyriakides, Konstantinos Margaritis

Neural Architecture Search (NAS) is a research field concerned with utilizing optimization algorithms to design optimal neural network architectures. There are many approaches concerning the architectural search spaces, optimization algorithms, as well as candidate architecture evaluation methods. As the field is growing at a continuously increasing pace, it

O. Borisenko, V. Chelnokov, S. Voloshyn

Dual representations are constructed for non-abelian lattice spin models with U(N) and SU(N) symmetry groups, for all N and in any dimension. These models are usually related to the effective models describing the interaction between Polyakov loops in the strong coupled QCD. The original spin degrees of freedom are explicitly integrated out and a dual theory

Olivia J. Erdélyi, Judy Goldsmith

With increasing ubiquity of artificial intelligence (AI) in modern societies, individual countries and the international community are working hard to create an innovation-friendly, yet safe, regulatory environment. Adequate regulation is key to maximize the benefits and minimize the risks stemming from AI technologies. Developing regulatory frameworks is, h

C. K. Li, L. Lin, S. L. Xiong, M. Y. Ge

Fast radio bursts (FRBs) are short pulses observed in radio band from cosmological distances. One class of models invoke soft gamma-ray repeaters (SGRs), or magnetars, as the sources of FRBs. Some radio pulses have been observed from some magnetars, however, no FRB-like events had been detected in association any magnetar burst, including one giant flare. Re

Yuancai Gong, Yifan Zhang, Erin Jedlicka, Rajiv Giridharagopal

The limiting factor preventing kesterite (CZTSSe) thin film solar cell performance further improvement is the large open-circuit voltage deficit (Voc,def) issue, which is 0.345V for the current world record device with an efficiency of 12.6%. In this work, SnCl4 and SnCl2_2H2O are respectively used as tin precursor to investigate the Voc,def issue of dimethy

Lei-Hua Liu, Tomislav Prokopec

We investigate two-field inflationary models in which scalar cosmological pertubations are generated via a spectator field nonminimally coupled to gravity, with the particular emphasis on curvaton scenarios. The principal advantage of these models is in the possibility to tune the spectator spectral index via the nonminimal coupling. Our models naturally yie

Sugandha Maheshwary

The aim of this article is to draw attention towards various natural but unanswered questions related to the lower central series of the unit group of an integral group ring.

Agapitos N. Hatzinikitas

Asymptotic expansions as well as necessary and sufficient conditions are provided for the pointwise convergence of the spherical partial integrals of the associated Fourier transforms on the real hyperbolic space. The proposed method permits one to produce new results and opens a connection with already known ones utilizing a unified framework.

Diego Antognini, Claudiu Musat, Boi Faltings

Using personalized explanations to support recommendations has been shown to increase trust and perceived quality. However, to actually obtain better recommendations, there needs to be a means for users to modify the recommendation criteria by interacting with the explanation. We present a novel technique using aspect markers that learns to generate personal

C. Zhang, C. Wang, G. Hobbs, C. J. Russell

To investigate the use of saliency-map analysis to aid in searches for transient signals, such as fast radio bursts and individual pulses from radio pulsars. We aim to demonstrate that saliency maps provide the means to understand predictions from machine learning algorithms and can be implemented in piplines used to search for transient events. We have impl

Wenjie Huang, Jing Jiang, Xiao Liu

In this paper, novel gradient-based online learning algorithms are developed to investigate an important environmental application: real-time river pollution source identification, which aims at estimating the released mass, location, and time of a river pollution source based on downstream sensor data monitoring the pollution concentration. The pollution is

Peng Hang, Chen Lv, Yang Xing, Chao Huang

Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on roads in the future for a long time, how to merge AVs into human drivers traffic ecology and minimize the effect of AVs and their misfit with human drivers, are issues worthy of consideration. Moreover, different passengers have different needs for AVs, thus, how to provide

Anoop Mutneja, Smarajit Karmakar

Probing dynamic and static correlation in glass-forming supercooled liquids has been a challenge for decades in spite of extensive research. Dynamic correlation which manifests itself as Dynamic Heterogeneity is ubiquitous in a vast variety of systems starting from molecular glass-forming liquids, dense colloidal systems to collections of cells. On the other

Christina Büsing, Martin Comis, Eva Schmidt, Manuel Streicher

Mobile medical units (MMUs) are customized vehicles fitted with medical equipment that are used to provide primary care in rural environments. As MMUs can be easily relocated, they enable a demand-oriented, flexible, and local provision of health services. In this paper, we investigate the strategic planning of an MMU service by deciding where MMU operation

Hokuto Hirano, Kazuki Koga, Kazuhiro Takemoto

Under the epidemic of the novel coronavirus disease 2019 (COVID-19), chest X-ray computed tomography imaging is being used for effectively screening COVID-19 patients. The development of computer-aided systems based on deep neural networks (DNNs) has been advanced, to rapidly and accurately detect COVID-19 cases, because the need for expert radiologists, who

N. Shahabi, A. Phirouznia

The role of staggered potential on light-induced spin and pseudo-spin polarization has been investigated in silicene. It has been shown that non-equilibrium spin and pseudo-spin polarizations are emerged in silicene sheet by applying an external perpendicular electric field in the presence of circularly polarized light emission. This electric field results i

Peng Hang, Chen Lv, Chao Huang, Jiacheng Cai

This paper presents a novel integrated approach to deal with the decision making and motion planning for lane-change maneuvers of autonomous vehicle (AV) considering social behaviors of surrounding traffic occupants. Reflected by driving styles and intentions of surrounding vehicles, the social behaviors are taken into consideration during the modelling proc

Klaus Zollner, Martin Gmitra, Jaroslav Fabian

The concept of swapping the two most important spin interactions -- exchange and spin-orbit coupling -- is proposed based on two-dimensional multilayer van der Waals heterostructures. Specifically, we show by performing realistic ab initio simulations, that a single device consisting of a bilayer graphene sandwiched by a 2D ferromagnet Cr$_2$Ge$_2$Te$_6$ (CG

SM Zobaed, Mohsen Amini Salehi

Cloud-based enterprise search services (e.g., Amazon Kendra) are enchanting to big data owners by providing them with convenient search solutions over their enterprise big datasets. However, individuals and businesses that deal with confidential big data (eg, credential documents) are reluctant to fully embrace such services, due to valid concerns about data

Mark Briers, Marcos Charalambides, Chris Holmes

We consider how the NHS COVID-19 application will initially calculate a risk score for an individual based on their recent contact with people who report that they have coronavirus symptoms.

Z. -Y. Zhang, F. Ritterbusch, W. -K. Hu, X. -Z. Dong

We report an increase of up to 60% on the count rates of the rare $^{81}\mathrm{Kr}$ and $^{85}\mathrm{Kr}$ isotopes in the Atom Trap Trace Analysis method by enhancing the production of metastable atoms in the discharge source. Additional atoms in the metastable $ 1s_5 $ level (Paschen notation) are obtained via optically pumping the $1s_4-2p_6$ transition

Kushal Chauhan, Abhirut Gupta

Technical support problems are often long and complex. They typically contain user descriptions of the problem, the setup, and steps for attempted resolution. Often they also contain various non-natural language text elements like outputs of commands, snippets of code, error messages or stack traces. These elements contain potentially crucial information for

Song Hua, Shenbin Zhang, Bingfeng Pi, Jun Sun

Blockchain, as a distributed ledger technology, becomes more and more popular in both industry and academia. Each peer in blockchain system maintains a copy of ledger and makes sure of data consistency through consensus protocol. Blockchain system can provide many benefits such as immutability, transparency and security. Hyperledger Fabric is permissioned bl

D. Koroliouk, M. Zozyuk, Yu. I. Yakymenko

A method for creating metasurfaces using a standing wave, formed in a dielectric, is proposed. Such metasurfaces are formed from metal suspensions, deposited on a dielectric plate, placed in a metal frame-screen. A series of parameters for creating the standing waves is discussed. Here the method for creating Hladni figures using acoustic standing waves is t

Jun Zhang, Mina Henein, Robert Mahony, Viorela Ila

Combining Simultaneous Localisation and Mapping (SLAM) estimation and dynamic scene modelling can highly benefit robot autonomy in dynamic environments. Robot path planning and obstacle avoidance tasks rely on accurate estimations of the motion of dynamic objects in the scene. This paper presents VDO-SLAM, a robust visual dynamic object-aware SLAM system tha

Bill Jackson, Anthony Nixon, Shin-Ichi Tanigawa

We consider the problem of characterising the generic rigidity of bar-joint frameworks in $\mathbb{R}^d$ in which each vertex is constrained to lie in a given affine subspace. The special case when $d=2$ was previously solved by I. Streinu and L. Theran in 2010 and the case when each vertex is constrained to lie in an affine subspace of dimension $t$, and $d

Ali Mokhtari, Chavit Denninnart, Mohsen Amini Salehi

Robustness of a distributed computing system is defined as the ability to maintain its performance in the presence of uncertain parameters. Uncertainty is a key problem in heterogeneous (and even homogeneous) distributed computing systems that perturbs system robustness. Notably, the performance of these systems is perturbed by uncertainty in both task execu

M. A. Braun

In the QCD the small~$x$ evolution of the interacting pomerons and odderons is studied with all angular momenta $l$ taken into account. The resulting system of coupled nonlinear evolution equations is formulated in the momentum space and solved numerically. Excellent convergence in $l$ is observed. Also it is found that states with $l>1$ play an important ro

S. Fedotov

The main goal of the T2K long-baseline neutrino experiment is the precise measurement of the parameters of neutrino oscillation and the search for CP-violation in the lepton sector. In 2017, the T2K collaboration launched the Near Detector Upgrade project. This upgrade aims to reduce the systematic errors of the oscillation parameters from 6-7% to 3-4%. In o

Miguel Beneitez, Yohann Duguet, Dan S. Henningson

The transition to turbulence in many shear flows proceeds along two competing routes, one linked with finite-amplitude disturbances and the other one originating from a linear instability, as in e.g. boundary layer flows. The dynamical systems concept of edge manifold has been suggested in the subcritical case to explain the partition of the state space of t

M. Willsch, D. Willsch, K. Michielsen, F. Jin

We present a detailed analysis of the time series of time-stamped neutron counts obtained by single-neutron interferometry. The neutron counting statistics display the usual Poissonian behavior, but the variance of the neutron counts does not. Instead, the variance is found to exhibit a dependence on the phase-shifter setting which can be explained by a prob

Michaël Chirmeni Boujike, Jerry Lonlac, Norbert Tsopze, Engelbert Mephu Nguifo

The gradual patterns that model the complex co-variations of attributes of the form "The more/less X, The more/less Y" play a crucial role in many real world applications where the amount of numerical data to manage is important, this is the biological data. Recently, these types of patterns have caught the attention of the data mining community, where sever

Marc Blanchon, Olivier Morel, Fabrice Meriaudeau, Ralph Seulin

Robotics applications in urban environments are subject to obstacles that exhibit specular reflections hampering autonomous navigation. On the other hand, these reflections are highly polarized and this extra information can successfully be used to segment the specular areas. In nature, polarized light is obtained by reflection or scattering. Deep Convolutio

Hongyu Li, Xiaogang Huang, Zhihui Fu, Xiaolin Li

Preserving original noise residuals in images are critical to image fraud identification. Since the resizing operation during deep learning will damage the microstructures of image noise residuals, we propose a framework for directly training images of original input scales without resizing. Our arbitrary-sized image training method mainly depends on the pse

Jun Zheng, Guchuan Zhu

This paper presents a maximum principle-based approach in the establishment of input-to-state stability (ISS) for a class of nonlinear parabolic partial differential equations (PDEs) over higher dimensional domains with variable coefficients and different types of nonlinear boundary conditions. Technical development on ISS analysis of the considered systems

Fan Zhou, Xovee Xu, Goce Trajcevski, Kunpeng Zhang

The deluge of digital information in our daily life -- from user-generated content, such as microblogs and scientific papers, to online business, such as viral marketing and advertising -- offers unprecedented opportunities to explore and exploit the trajectories and structures of the evolution of information cascades. Abundant research efforts, both academi

Yuki Ueda, Takashi Ishio, Akinori Ihara, Kenichi Matsumoto

Static analysis tools, or linters, detect violation of source code conventions to maintain project readability. Those tools automatically fix specific violations while developers edit the source code. However, existing tools are designed for the general conventions of programming languages. These tools do not check the project/API-specific conventions. We pr

Alberto Baldi, Franco Bagnoli

The concept of intransitiveness for games, which is the condition for which there is no first-player winning strategy can arise surprisingly, as happens in the Penney game, an extension of the heads or tails. Since a game can be converted into a random walk on a graph, i.e., a Markov process, we extend the intransitiveness concept to such systems. The end of

Amit Mittal, Md Sanam Suraj, Rajiv Aggarwal

The present paper deals with the periodic orbits generated by Lagrangian solutions of the restricted three-body problem when both the primaries are oblate bodies. We have illustrated the periodic orbits for different values of $\mu, h,\sigma_1$ and $\sigma_2$ ($h$ is energy constant, $\mu$ mass ratio of the two primaries, $\sigma_1$ and $\sigma_2$ are oblate

Francisco Tello-Ortiz, M. Malaver, Angel Rincon, Y. Gomez-Leyton

In this work, a spherically symmetric and static relativistic anisotropic fluid sphere solution of the Einstein field equations is provided. To build this particular model, we have imposed metric potential $e^{2\lambda(r)}$ and an equation of state. Specifically, the so-called modified generalized Chaplygin equation of state with $\omega=1$ and depending on

Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen

Existing fully-supervised person re-identification (ReID) methods usually suffer from poor generalization capability caused by domain gaps. The key to solving this problem lies in filtering out identity-irrelevant interference and learning domain-invariant person representations. In this paper, we aim to design a generalizable person ReID framework which tra

Iwo Bialynicki-Birula, Zofia Bialynicka-Birula

Analytical solutions of the Dirac equation in an external electromagnetic field are found such that according to the field-theoretic interpretation electron-positron pairs are trapped for a period of time. The naive one-particle interpretation of the Dirac wave function fails in this case completely. Simple electromagnetic field which produces this effect wa

Jangho Kim, KiYoon Yoo, Nojun Kwak

We propose the position-based scaled gradient (PSG) that scales the gradient depending on the position of a weight vector to make it more compression-friendly. First, we theoretically show that applying PSG to the standard gradient descent (GD), which is called PSGD, is equivalent to the GD in the warped weight space, a space made by warping the original wei

Shijie Hao, Yuan Zhou, Yanrong Guo, Richang Hong

Nowadays, vision-based computing tasks play an important role in various real-world applications. However, many vision computing tasks, e.g. semantic segmentation, are usually computationally expensive, posing a challenge to the computing systems that are resource-constrained but require fast response speed. Therefore, it is valuable to develop accurate and

Bin Wang, Le Xie, Slava Maslennikov, Xiaochuan Luo

This paper proposes a novel approach to estimate the steady-state angle stability limit (SSASL) by using the nonlinear power system dynamic model in the modal space. Through two linear changes of coordinates and a simplification introduced by the steady-state condition, the nonlinear power system dynamic model is transformed into a number of single-machine-l

Ashwin Venkatraman, Uros Markovic, Dmitry Shchetinin, Evangelos Vrettos

An increasing penetration of renewable generation has led to reduced levels of rotational inertia and damping in the system. The consequences are higher vulnerability to disturbances and deterioration of the dynamic response of the system. To overcome these challenges, novel converter control schemes that provide virtual inertia and damping have been introdu

Giulia Cisotto, Martina Capuzzo, Anna V. Guglielmi, Andrea Zanella

Internet of Things is rapidly spreading across several fields, including healthcare, posing relevant questions related to communication capabilities, energy efficiency and sensors unobtrusiveness. Particularly, in the context of recognition of gestures, e.g., grasping of different objects, brain and muscular activity could be simultaneously recorded via EEG