arXiv papers from February 2021

J. Menezes

When faced with an imminent risk of predation, many animals react to escape consumption. Antipredator strategies are performed by individuals acting as a group to intimidate predators and minimize the damage when attacked. We study the antipredator prey response in spatial tritrophic systems with cyclic species dominance using the rock-paper-scissors game. T

Yifei Guo, Yuxuan Yuan, Zhaoyu Wang

The knowledge of distribution grid models, including topologies and line impedances, is essential to grid monitoring, control and protection. However, this information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to address this issue. This paper proposes a two-stage data-driven f

Sudhir Malik, Samuel Meehan, Kilian Lieret, Meirin Oan Evans

Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and adva

Aasma Aslam, Babar Hussian

Emotion recognition using digital image processing is a multifarious task because facial emotions depend on warped facial features as well as on gender, age, and culture. Furthermore, there are several factors such as varied illumination and intricate settings that increase complexity in facial emotion recognition. In this paper, we used four salient facial

E. Pryzant, Q. Deng, B. Mei, E. Shrestha

With the renaissance of neural networks, object detection has slowly shifted from a bottom-up recognition problem to a top-down approach. Best in class algorithms enumerate a near-complete list of objects and classify each into object/not object. In this paper, we show that strong performance can still be achieved using a bottom-up approach for vision-based

Shibo Shu, Nikita Klimovich, Byeong Ho Eom, Andrew Beyer

The nonlinear response associated with the current dependence of the superconducting kinetic inductance was studied in capacitively shunted NbTiN microstrip transmission lines. It was found that the inductance per unit length of one microstrip line could be changed by up to 20% by applying a DC current, corresponding to a single pass time delay of 0.7 ns. To

Cristiana de Farias, Naresh Marturi, Rustam Stolkin, Yasemin Bekiroglu

This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement to optimise grasp stability. In many situations, a robot will have only a partial camera view of the near side of an observed object, for which the far side remains occluded. We sho

Gregory Canal, Matthieu Bloch, Christopher Rozell

The iterative selection of examples for labeling in active machine learning is conceptually similar to feedback channel coding in information theory: in both tasks, the objective is to seek a minimal sequence of actions to encode information in the presence of noise. While this high-level overlap has been previously noted, there remain open questions on how

Wilson Yanez, Yongxi Ou, Run Xiao, Jahyun Koo

We report spin-to-charge and charge-to-spin conversion at room temperature in heterostructure devices that interface an archetypal Dirac semimetal, Cd3As2, with a metallic ferromagnet, Ni0.80Fe0.20 (permalloy). The spin-charge interconversion is detected by both spin torque ferromagnetic resonance and ferromagnetic resonance driven spin pumping. Analysis of

Jonathan Zhao, Matthew Westerham, Mark Lakatos-Toth, Zhikang Zhang

We present OpenICS, an image compressive sensing toolbox that includes multiple image compressive sensing and reconstruction algorithms proposed in the past decade. Due to the lack of standardization in the implementation and evaluation of the proposed algorithms, the application of image compressive sensing in the real-world is limited. We believe this tool

Dimitrios Katselis, Xiaotian Xie, Carolyn L. Beck, R. Srikant

We derive two upper bounds for the probability of deviation of a vector-valued Lipschitz function of a collection of random variables from its expected value. The resulting upper bounds can be tighter than bounds obtained by a direct application of a classical theorem due to Bobkov and G\"{o}tze.

Erick Schmidt, Junhwan Lee, Nikolaos Gatsis, David Akopian

This paper presents a novel time synchronization attack (TSA) model for the Global Positioning System (GPS) based on clock data behavior changes in a higher-order derivative domain. Further, the time synchronization attack rejection and mitigation based on sparse domain (TSARM-S) is presented. TSAs affect stationary GPS receivers in applications where precis

Noah Taylor

For a prime level $N$, we compute the index of the anemic Hecke algebra of weight 2 level $\Gamma_0(N)$ forms inside the full Hecke algebra. We prove that the index is fully described by the presence of weight 1 Katz forms of the same level.

Zhong Guan

Maximum likelihood estimators are proposed for the parameters and the densities in a semiparametric density ratio model in which the nonparametric baseline density is approximated by the Bernstein polynomial model. The EM algorithm is used to obtain the maximum approximate Bernstein likelihood estimates. Simulation study shows that the performance of the pro

Leslie Hogben, Carolyn Reinhart

Distance matrices of graphs were introduced by Graham and Pollack in 1971 to study a problem in communications. Since then, there has been extensive research on the distance matrices of graphs -- a 2014 survey by Aouchiche and Hansen on spectra of distance matrices of graphs lists more than 150 references. In the last ten years, variants such as the distance

Marco Buratti, Dieter Jungnickel

Two years ago, we alarmed the scientific community about the large number of bad papers in the literature on {\it zero difference balanced functions}, where direct proofs of seemingly new results are presented in an unnecessarily lengthy and convoluted way. Indeed, these results had been proved long before and very easily in terms of difference families. In

Nicolai Haydn, Matthew Nicol

Erdos-Renyi limit laws give the length scale of a time-window over which time-averages in Birkhoff sums have a non-trivial almost-sure limit. We establish Erdos-Renyi type limit laws for Holder observables on dynamical systems modeled by Young Towers with exponential and polynomial tails. This extends earlier results on Erdos-Renyi limit laws to a broad clas

Hassan Jafarzadeh, Cody Fleming

This work presents DMPC (Data-and Model-Driven Predictive Control) to solve control problems in which some of the constraints or parts of the objective function are known, while others are entirely unknown to the controller. It is assumed that there is an exogenous ``black box'' system, e.g. a machine learning technique, that predicts the value of the unknow

Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi, Mohit Sewak

Since Google unveiled Android OS for smartphones, malware are thriving with 3Vs, i.e. volume, velocity, and variety. A recent report indicates that one out of every five business/industry mobile application leaks sensitive personal data. Traditional signature/heuristic-based malware detection systems are unable to cope up with current malware challenges and

Zhou Rui, Ya Li, Hsiang-nan Li

We investigate the four-body decays $B_{(s)} \rightarrow (K\pi)_{S/P} (K\pi)_{S/P}$ in the $K\pi$-pair invariant mass region around the $K^*(892)$ resonance in the perturbative QCD (PQCD) approach, where $(K\pi)_{S/P}$ denotes a $S$- or $P$-wave $K\pi$ configuration. The contributions from the $P$-wave resonance $K^*(892)$ and from possible $S$-wave componen

Dragos Ghioca, Igor Shparlinski

Let $q$ be a power of the prime number $p$, let $K={\mathbb F}_q(t)$, and let $r\ge 2$ be an integer. For points ${\mathbf a}, {\mathbf b}\in K$ which are $\mathbb{F}_q$-linearly independent, we show that there exist positive constants $N_0$ and $c_0$ such that for each integer $\ell\ge N_0$ and for each generator $\tau$ of ${\mathbb F}_{q^\ell}/{\mathbb F}_

Martin G. Frasch, Bernd Walter, Christoph Anders, Reinhard Bauer

We expand from a spontaneous to an evoked potentials (EP) data set of brain electrical activities as electrocorticogram (ECoG) and electrothalamogram (EThG) in juvenile pig under various sedation, ischemia and recovery states. This EP data set includes three stimulation paradigms: auditory (AEP, 40 and 2000 Hz), sensory (SEP, left and right maxillary nerve)

Youssef El Azhari, Sa{ī}d Tagmouti

We use coherence theory to explain why it is necessary to modify the conventional setup of a Michelson interferometer to obtain Haidinger rings with an extended source of white light. The modification consists of introducing a glass slide into one of the two arms of the interferometer. This insertion circumvents the drastic restriction imposed by the low tem

Adel Khalfallah, Fathi Haggui, Miodrag Mateljević

In this paper, we prove the Khavinson conjecture for hyperbolic harmonic functions on the unit ball. This conjecture was partially solved in \cite{JKM2020}.

Hemant Rathore, Sanjay K. Sahay, Shivin Thukral, Mohit Sewak

Today anti-malware community is facing challenges due to the ever-increasing sophistication and volume of malware attacks developed by adversaries. Traditional malware detection mechanisms are not able to cope-up with next-generation malware attacks. Therefore in this paper, we propose effective and efficient Android malware detection models based on machine

Bangming Deng, Jiuzhao Hua

This paper presents analogous results of Hua [7][8] on numbers of representations of quivers over finite fields which respect nilpotent relations under certain assumptions. A closed formula which counts isomorphism classes of absolutely indecomposable representations with given dimension vectors is given and a $q$-deformation of Weyl-Kac denominator identity

Giulio Burgio, Benjamin Steinegger, Giacomo Rapisardi, Alex Arenas

We study how homophily of human physical interactions affects the efficacy of digital proximity tracing. Analytical results show a non monotonous dependence of the reproduction number with respect to the mixing rate between individuals that adopt the contact tracing app and the ones that do not. Furthermore, we find regimes in which the attack rate has local

Zhicheng Zhang, Lequan Yu, Xiaokun Liang, Wei Zhao

Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radiation to patients. However, the noise caused by low X-ray exposure degrades the CT image quality and then affects clinical diagnosis accuracy. In this paper, we train a transformer-

Neeraj Kumar Rajak, Neha Kondedan, Husna Jan, Muhammed Dilshah U

We present high resolution thermal expansion measurement data obtained with high relative sensitivity of $\Delta$L$/$L = 10$^{-9}$ and accuracy of $\pm$2$\%$ using closed cycle refrigerators employing two different dilatometers. The data quality is in excellent agreement with those obtained using wet liquid helium based systems, demonstrating great technolog

Giuseppe Carere, Maria Strazzullo, Francesco Ballarin, Gianluigi Rozza

Reduced basis approximations of Optimal Control Problems (OCPs) governed by steady partial differential equations (PDEs) with random parametric inputs are analyzed and constructed. Such approximations are based on a Reduced Order Model, which in this work is constructed using the method of weighted Proper Orthogonal Decomposition. This Reduced Order Model th

Tao Zou, Xian Li, Xuan Liang, Hansheng Wang

This article introduces subbagging (subsample aggregating) estimation approaches for big data analysis with memory constraints of computers. Specifically, for the whole dataset with size $N$, $m_N$ subsamples are randomly drawn, and each subsample with a subsample size $k_N\ll N$ to meet the memory constraint is sampled uniformly without replacement. Aggrega

Yagiz Savas, Abolfazl Hashemi, Abraham P. Vinod, Brian M. Sadler

We study the problem of securely communicating a sequence of information bits with a client in the presence of multiple adversaries at unknown locations in the environment. We assume that the client and the adversaries are located in the far-field region, and all possible directions for each adversary can be expressed as a continuous interval of directions.

Sarah Samorodnitsky, Katherine A. Hoadley, Eric F. Lock

Pan-omics, pan-cancer analysis has advanced our understanding of the molecular heterogeneity of cancer, expanding what was known from single-cancer or single-omics studies. However, pan-cancer, pan-omics analyses have been limited in their ability to use information from multiple sources of data (e.g., omics platforms) and multiple sample sets (e.g., cancer

Mohammad Akil, Haidar Badawi

In this paper, we investigate the stabilization of a linear Bresse system with one singular local frictional damping acting in the longitudinal displacement, under fully Dirichlet boundary conditions. First, we prove the strong stability of our system. Next, using a frequency domain approach combined with the multiplier method, we establish the exponential s

Aldo Solari, Vera Djordjilović

Split conformal prediction is a computationally efficient method for performing distribution-free predictive inference in regression. It involves, however, a one-time random split of the data, and the result depends on the particular split. To address this problem, we propose multi split conformal prediction, a simple method based on Markov's inequality to a

Mariana Dutra, Odilon Lourenço, Xavier Viñas, C. Mondal

In this work we have analyzed several features of symmetric nuclear matter (SNM) at finite temperature described by different zero- and finite-range nonrelativistic families of models, namely, Skyrme, Gogny, Momentum-dependent interaction (MDI), Michigan three-range Yukawa (M3Y) and Simple Effective Interaction (SEI). We have calculated the critical paramete

Matthias Schulte, J. E. Yukich

We employ stabilization methods and second order Poincar\'e inequalities to establish rates of multivariate normal convergence for a large class of vectors $(H_s^{(1)},...,H_s^{(m)})$, $s \geq 1$, of statistics of marked Poisson processes on $\mathbb{R}^d$, $d \geq 2$, as the intensity parameter $s$ tends to infinity. Our results are applicable whenever the

Donniell E. Fishkind, Felix Parker, Hamilton Sawczuk, Lingyao Meng

The alignment strength of a graph matching is a quantity that gives the practitioner a measure of the correlation of the two graphs, and it can also give the practitioner a sense for whether the graph matching algorithm found the true matching. Unfortunately, when a graph matching algorithm fails to find the truth because of weak signal, there may be "phanto

Julien Perolat, Sarah Perrin, Romuald Elie, Mathieu Laurière

We address scaling up equilibrium computation in Mean Field Games (MFGs) using Online Mirror Descent (OMD). We show that continuous-time OMD provably converges to a Nash equilibrium under a natural and well-motivated set of monotonicity assumptions. This theoretical result nicely extends to multi-population games and to settings involving common noise. A tho

Bedřich Sousedík, Howard C. Elman, Kookjin Lee, Randy Price

We study linear stability of solutions to the Navier\textendash Stokes equations with stochastic viscosity. Specifically, we assume that the viscosity is given in the form of a~stochastic expansion. Stability analysis requires a solution of the steady-state Navier-Stokes equation and then leads to a generalized eigenvalue problem, from which we wish to chara

Moritz E. Beber, Mattia G. Gollub, Dana Mozaffari, Kevin M. Shebek

eQuilibrator (equilibrator.weizmann.ac.il) is a calculator for biochemical equilibrium constants and Gibbs free energies, originally designed as a web-based interface. While the website now counts ${\sim}1000$ distinct monthly users, its design could not accommodate larger compound databases and it lacked an application programming interface (API) for integr

Moritz Lang

A system is invariant with respect to an input transformation if we can transform any dynamic input by this function and obtain the same output dynamics after adjusting the initial conditions appropriately. Often, the set of all such input transformations forms a Lie group, the most prominent examples being scale-invariant ($u\mapsto e^pu$, $p\in\mathbb{R}$)

Zeynab Khoshyari-morad, Reza Jahangir, Hashem Miri-Hakimabad, Najmeh Mohammadi

SPECT imaging is one of the common modalities used to examine kidney disease. The radiopharmaceuticals such as 99mTc-MAG3, 99mTc-DTPA, and 99mTc-DMSA are commonly employed for pediatric patients. It is generally accepted that children organs are more sensitive to radiation than adults, due to their growth rate. Therefore, evaluating the absorbed dose in chil

Daniel A. Jaume, Adrián Pastine, Victor Schvöllner

In the present work we prove that given any two unicycle graphs (pseudoforests) that share the same degree sequence there is a finite sequence of 2-switches transforming one into the other such that all the graphs in the sequence are also unicyclic graphs (pseudoforests).

Boris Botvinnik, Jonathan Rosenberg

It is well-known that spin structures and Dirac operators play a crucial role in the study of positive scalar curvature metrics (psc-metrics) on compact manifolds. Here we consider a class of non-spin manifolds with "almost spin" structure, namely those with spin$^c$ or pin$^\pm$-structures. It turns out that in those cases (under natural assumptions on such

Vignesh Prasad, Ruth Stock-Homburg, Jan Peters

One of the first and foremost non-verbal interactions that humans perform is a handshake. It has an impact on first impressions as touch can convey complex emotions. This makes handshaking an important skill for the repertoire of a social robot. In this paper, we present a novel framework for learning reaching behaviours for human-robot handshaking behaviour

H. Dausy, L. Nulens, B. Raes, M. J. Van Bael

In this work, we study the current phase relation ($C\Phi R$) of lithographically fabricated molybdenum germanium (MoGe) nanobridges, which is intimately linked to the nanobridge kinetic inductance. We do this by imbedding the nanobridges in a SQUID. We observe that for temperatures far below $T_c$, the $C\Phi R$ is linear as long as the condensate is not we

M. A. Hobosyan, K. S. Martirosyan

There is a growing interest on novel energetic materials called Nanoenergetic Gas-Generators (NGGs) which are potential alternatives to traditional energetic materials including pyrotechnics, propellants, primers and solid rocket fuels. NGGs are formulations that utilize metal powders as a fuel and oxides or hydroxides as oxidizers that can rapidly release l

F. Gautier, A. Greeley, S. G. Kanekal, T. Isidori

The AGILE (Advanced enerGetic Ion eLectron tElescope) project focuses on the development of a compact low-cost space-based instrument to measure the intensities of charged particles and ions in space. Using multiple layers of fast silicon sensors and custom front-end electronics, the instrument is designed for real-time particle identification of a large var

Sephora Ruppert, Amia Ross, Joost Vlassak, Martin Elvis

The lunar South pole likely contains significant amounts of water in the permanently shadowed craters there. Extracting this water for life support at a lunar base or to make rocket fuel would take large amounts of power, of order Gigawatts. A natural place to obtain this power are the "Peaks of Eternal Light", that lie a few kilometers away on the crater ri

I. Korover, R. G. Milner

We report on a Rosenbluth separation using previously published data by the CLAS collaboration in Hall B, Jefferson Lab for exclusive $\pi^{0}$ deeply virtual electroproduction (DVEP) from the proton at a mean $Q^{2}$ of $\approx$ 2 (GeV/c)$^{2}$. The central question we address is the applicability of factorization in $\pi^0$ DVEP at these kinematics. The r

Pieter David

With the LHC continuing to collect more data and experimental analyses becoming increasingly complex, tools to efficiently develop and execute these analyses are essential. The bamboo framework defines a domain-specific language, embedded in python, that allows to concisely express the analysis logic in a functional style. The implementation based on ROOT's

J. D. M. de Lima, E. Gomes, F. F. da Silva Filho, F. Moraes

Since electrons in a ballistic regime perceive a carbon nanotube or a graphene layer structure as a continuous medium, we can use the study of the quantum dynamics of one electron constrained to a curve or surface to obtain a qualitative description of the conduction electrons' behavior. The confinement process of a quantum particle to a curve or surface lea

L. Moriconi

Multifractal systems usually have singularity spectra defined on bounded sets of H\"older exponents. As a consequence, their associated multifractal scaling exponents are expected to depend linearly upon statistical moment orders at high enough orders -- a phenomenon referred to as the {\it{linearization effect}}. Motivated by general ideas taken from models

Khandaker Mohammad Mohi Uddin, Samrat Kumar Dey, Gias Uddin Parvez, Ayesha Siddika Mukta

We are living in the era of the fourth industrial revolution, which also treated as 4IR or Industry 4.0. Generally, 4IR considered as the mixture of robotics, artificial intelligence (AI), quantum computing, the Internet of Things (IoT) and other frontier technologies. It is obvious that nowadays a plethora of smart devices is providing services to make the

Rui Xin, Edirisuriya M. D. Siriwardane, Yuqi Song, Yong Zhao

Active learning has been increasingly applied to screening functional materials from existing materials databases with desired properties. However, the number of known materials deposited in the popular materials databases such as ICSD and Materials Project is extremely limited and consists of just a tiny portion of the vast chemical design space. Herein we

Mohsen Jannesari

For a set W of vertices and a vertex v in a graph G, the k-vector r2(v|W) = (aG(v,w1),...,aG(v,wk)) is the adjacency representation of v with respect to W, where W = {w1,...,wk} and aG(x,y) is the minimum of 2 and the distance between the vertices x and y. The set W is an adjacency resolving set for G if distinct vertices of G have distinct adjacency represe

Bingzhao Zhu, Mahsa Shoaran

Modern machine learning tools have shown promise in detecting symptoms of neurological disorders. However, current approaches typically train a unique classifier for each subject. This subject-specific training scheme requires long labeled recordings from each patient, thus failing to detect symptoms in new patients with limited recordings. This paper introd

Shuxi Zeng, Fan Li, Liangyuan Hu, Fan Li

Survival outcomes are common in comparative effectiveness studies and require unique handling because they are usually incompletely observed due to right-censoring. A ``once for all'' approach for causal inference with survival outcomes constructs pseudo-observations and allows standard methods such as propensity score weighting to proceed as if the outcomes

Yunchou Xing, Theodore S. Rappaport

This paper demonstrates how spectrum up to 1 THz will support mobile communications beyond 5G in the coming decades. Results of rooftop surrogate satellite/tower base station measurements at 140 GHz show the natural isolation between terrestrial networks and surrogate satellite systems, as well as between terrestrial mobile users and co-channel fixed backhau

Manoj Mandal, Sabyasachi Pal

We study the timing and spectral properties of the X-ray pulsar 2S 1553--542 using the NuSTAR, and NICER during the outburst in January--February 2021. During the outburst, the spin period of the neutron star was 9.2822 s based on NuSTAR data. The pulse profiles are studied using different NICER observations, which implies that the profile is more or less si

David Noever, Samantha E. Miller Noever

The short note presents an image classification dataset consisting of 10 executable code varieties and approximately 50,000 virus examples. The malicious classes include 9 families of computer viruses and one benign set. The image formatting for the first 1024 bytes of the Portable Executable (PE) mirrors the familiar MNIST handwriting dataset, such that mos

Anastasiia Svanidze, Tianyi Guo, Xiaoyu Zheng, Peter Palffy-Muhoray

Increasingly important photomechanical materials produce stress and mechanical work when illuminated. We propose experimentally accessible performance metrics for photostress and photowork, enabling comparison of materials performance. We relate these metrics to material properties, providing a framework for the design and optimization of photomechanical mat

Henry Hanifan, Ben Watson, John Cartlidge, Dave Cliff

We consider issues of time in automated trading strategies in simulated financial markets containing a single exchange with public limit order book and continuous double auction matching. In particular, we explore two effects: (i) reaction speed - the time taken for trading strategies to calculate a response to market events; and (ii) trading urgency - the s

Gareth Jones, Jim Parr, Perumal Nithiarasu, Sanjay Pant

This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease -- carotid artery stenosis (CAS), subclavian artery stenosis (SAC), peripheral arterial disease (PAD), and abdominal aortic aneurysms (AAA) -- are considered. The ML method

Luis Adrián Lizama-Pérez

We introduce a new approach for circuit anonymous communication based on Lizama's non-invertible Key Exchange Protocol (ni-KEP) which has been conceived to work in the quantum era. Lizama's protocol has the smallest key size when compared to main post-quantum schemes thus it becomes a promising alternative for the quantum era. Circuit-based communication can

Jean Marie Tshimula, Belkacem Chikhaoui, Shengrui Wang

The new coronavirus outbreak has been officially declared a global pandemic by the World Health Organization. To grapple with the rapid spread of this ongoing pandemic, most countries have banned indoor and outdoor gatherings and ordered their residents to stay home. Given the developing situation with coronavirus, mental health is an important challenge in

J. D. Franson

We consider an approach in which the usual wave function in the quadrature representation of mode j of the electromagnetic field is further quantized to produce a field operator. Since the electromagnetic field is already second quantized, this corresponds to an additional or third quantization. The third-quantization approach can be used to perform certain

Guanqun Cao, Jiaqi Jiang, Chen Lu, Daniel Fernandes Gomes

Tactile sensing is important for robots to perceive the world as it captures the texture and hardness of the object in contact and is robust to illumination and colour variances. However, due to the limited sensing area and the resistance of the fixed surface, current tactile sensors have to tap the tactile sensor on target object many times when assessing a

Camila Lorenz, Patricia Marques Moralejo Bermudi, Marcelo Antunes Failla, Breno Souza de Aguiar

Understanding differences in hospital case-fatality rates (HCFRs) of coronavirus disease (COVID-19) may help evaluate its severity and the capacity of the healthcare system to reduce mortality. We examined the variability in HCFRs of COVID-19 in relation to spatial inequalities in socioeconomic factors across the city of Sao Paulo, Brazil. We found that HCFR

Nilesh Goel, J. K. Freericks

We examine the detailed scenario for implementing n-control-qubit Toffoli gates and select gates on ion-trap quantum computers, especially those that shuttle ions into interaction zones. We determine expected performance of these gates with realistic parameters for an ion-trap quantum computer and taking into account the time variation of the exchange integr

S. Gerasimova, A. Belov, D. Korolev, D. Guseinov

The dynamics of memristive device in response to neuron-like signals and coupling electronic neurons via memristive device has been investigated theoretically and experimentally. The simplest experimental system consists of electronic circuit based on the FitzHugh-Nagumo model and metal-oxide memristive device. The hardware-software complex based on commerci

Satoshi Fukuda, Nenad Kos, Christoph Wolf

We study equilibrium distancing during epidemics. Distancing reduces the individual's probability of getting infected but comes at a cost. It creates a single-peaked epidemic, flattens the curve and decreases the size of the epidemic. We examine more closely the effects of distancing on the outset, the peak and the final size of the epidemic. First, we defin

Antonin Durey, Pierre Laperdrix, Walter Rudametkin, Romain Rouvoy

Browser fingerprinting is a stateless identification technique based on browser properties. Together, they form an identifier that can be collected without users' notice and has been studied to be unique and stable. As this technique relies on browser properties that serve legitimate purposes, the detection of this technique is challenging. While several stu

Tom Silver, Rohan Chitnis, Joshua Tenenbaum, Leslie Pack Kaelbling

Robotic planning problems in hybrid state and action spaces can be solved by integrated task and motion planners (TAMP) that handle the complex interaction between motion-level decisions and task-level plan feasibility. TAMP approaches rely on domain-specific symbolic operators to guide the task-level search, making planning efficient. In this work, we forma

Pernille Hansen, Benjamin Eltzner, Stefan Sommer

We introduce diffusion means as location statistics on manifold data spaces. A diffusion mean is defined as the starting point of an isotropic diffusion with a given diffusivity. They can therefore be defined on all spaces on which a Brownian motion can be defined and numerical calculation of sample diffusion means is possible on a variety of spaces using th

Vitalis Salis, Thodoris Sotiropoulos, Panos Louridas, Diomidis Spinellis

Call graphs play an important role in different contexts, such as profiling and vulnerability propagation analysis. Generating call graphs in an efficient manner can be a challenging task when it comes to high-level languages that are modular and incorporate dynamic features and higher-order functions. Despite the language's popularity, there have been very

Martin Formanek, Andrew Steinmetz, Johann Rafelski

We study the motion of a charged particle with magnetic moment in external electromagnetic fields utilizing covariant unification of Gilbertian and Amperian descriptions of particle magnetic dipole moment. Considering the case of a current loop, our approach is verified by comparing classical dynamics with the classical limit of relativistic quantum dynamics

Luca Sestini, Benoit Rosa, Elena De Momi, Giancarlo Ferrigno

3-D pose estimation of instruments is a crucial step towards automatic scene understanding in robotic minimally invasive surgery. Although robotic systems can potentially directly provide joint values, this information is not commonly exploited inside the operating room, due to its possible unreliability, limited access and the time-consuming calibration req

Hao Ren, Ratnesh Kumar, Matthew Clark

The paper presents our research on quantifier elimination (QE) for compositional reasoning and verification. For compositional reasoning, QE provides the foundation of our approach, serving as the calculus for composition to derive the strongest system-property in a single step, from the given component atomic-properties and their interconnection relation. W

Melih Is, Ismet Karaca

In this study, we improve the topological complexity computations on digital images with introducing the digital topological complexity computations of a surjective and digitally continuous map between digital images. We also reveal differences in topological complexity computations of maps between digital images and topological spaces. Moreover, we emphasiz

Anna Ijjas, Andrew P. Sullivan, Frans Pretorius, Paul J. Steinhardt

We study the detailed process by which slow contraction smooths and flattens the universe using an improved numerical relativity code that accepts initial conditions with non-perturbative deviations from homogeneity and isotropy along two independent spatial directions. Contrary to common descriptions of the early universe, we find that the geometry first ra

Nigora Gafur, Gajanan Kanagalingam, Martin Ruskowski

A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm i

Justin Bui, Robert J. Marks

Neural networks are largely black boxes. A neural network trained to classify fruit may classify a picture of a giraffe as a banana. A neural network watchdog's job is to identify such inputs, allowing a classifier to disregard such data. We investigate whether the watchdog should be separate from the neural network or symbiotically attached. We present empi

K. Monroe, Y. Yao, A. Lattanzi, V. Raghav

Expiratory events, such as coughs, are often pulsatile in nature and result in vortical flow structures that transport respiratory particles. In this work, direct numerical simulation (DNS) of turbulent pulsatile jets, coupled with Lagrangian particle tracking of micron-sized droplets, is performed to investigate the role of secondary and tertiary expulsions

Wenkai Xu, Gesine Reinert

We propose and analyse a novel nonparametric goodness of fit testing procedure for exchangeable exponential random graph models (ERGMs) when a single network realisation is observed. The test determines how likely it is that the observation is generated from a target unnormalised ERGM density. Our test statistics are derived from a kernel Stein discrepancy,

S. R. Uglov, A. V. Vukolov

Currently, most of the Cherenkov phenomenon researches for the X-ray region are theoretical studies; there are only a few experiments in this area. Here the new experimental results on observation of X-ray Cherenkov radiation generated by 5.7 MeV electrons in the thin Be and Si foils are presented. The Cherenkov effect from Be was observed for the first time

Daniel Morcuende, Jaime Rosado

Cosmic-ray observatories necessarily rely on Monte Carlo simulations for their design, calibration and analysis of their data. Detailed simulations are very demanding computationally. We present a python-based package called ShowerModel to model cosmic-ray showers, their light production and their detection by an array of telescopes. It is based on parameter

Maxim Mai, Michael Döring, Akaki Rusetsky

The extraction of two- and three-body hadronic scattering amplitudes and the properties of the low-lying hadronic resonances from the finite-volume energy levels in lattice QCD represents a rapidly developing field of research. The use of various modifications of the L\"uscher finite-volume method has opened a path to calculate infinite-volume scattering amp

Aurélien Drezet, Benjamin Stock

The aim of this article is reproduce and analyze an original article of David Bohm sent to Louis de Broglie in 1951. This article is the older document of David Bohm about his well known hidden variable theory based on the pilot wave interpretation of Louis de Broglie. We analyse the chronology and the history of this fascinating document.

Nathan Hayford, Fudong Wang

We give an in-depth analysis of a 1-parameter family of electrified droplets first described in D. Khavinson et. al. (2005). We also investigate a technique for searching for new solutions to the droplet equation, and rederive via this technique a 1-parameter family of physical droplets, which were first discovered by D. Crowdy (1999). We speculate on extens

Hanne Kekkonen, Matti Lassas, Eero Saksman, Samuli Siltanen

We propose alternatives to Bayesian a priori distributions that are frequently used in the study of inverse problems. Our aim is to construct priors that have similar good edge-preserving properties as total variation or Mumford-Shah priors but correspond to well defined infinite-dimensional random variables, and can be approximated by finite-dimensional ran

Vladislav Mikhailov, Ekaterina Taktasheva, Elina Sigdel, Ekaterina Artemova

The success of pre-trained transformer language models has brought a great deal of interest on how these models work, and what they learn about language. However, prior research in the field is mainly devoted to English, and little is known regarding other languages. To this end, we introduce RuSentEval, an enhanced set of 14 probing tasks for Russian, inclu

Malin Prematilake, Younghyun Kim, Vijay Raghunathan, Anand Raghunathan

Implantable and wearable medical devices (IWMDs) are widely used for the monitoring and therapy of an increasing range of medical conditions. Improvements in medical devices, enabled by advances in low-power processors, more complex firmware, and wireless connectivity, have greatly improved therapeutic outcomes and patients' quality-of-life. However, securit

Hannu Siikonen, T. Mäkelä, M. Voutilainen

We review the possible effects of the miscalibration of the flavor-dependent Jet Energy Corrections ($F_{\mathrm{Corr}}$) on the D{\O} lepton+jets top mass measurement. The work is based on a previous study, where the D{\O} $F_{\mathrm{Corr}}$ calibration procedure was repeated based on the release of the internal D{\O} notes after a 5-year moratorium. The c

Jesmin Jahan Tithi, Fabio Checconi, Douglas Doerfler, Fabrizio Petrini

SU3\_Bench is a microbenchmark developed to explore performance portability across multiple programming models/methodologies using a simple, but nontrivial, mathematical kernel. This kernel has been derived from the MILC lattice quantum chromodynamics (LQCD) code. SU3\_Bench is bandwidth bound and generates regular compute and data access patterns. Therefore

Theresa Trummler, Daniel Rahn, Steffen J. Schmidt, Nikolaus A. Adams

We present results of large eddy simulations of a cavitating nozzle flow and injection into gas, investigating the interactions of cavitation in the nozzle, primary jet breakup, mass-flow rates, and gas entrainment. During strong cavitation, detached vapor structures can reach the nozzle outlet, leading to partial entrainment of gas from the outflow region i

Shuoyang Wang, Zuofeng Shang, Guanqun Cao, Jun Liu

A central topic in functional data analysis is how to design an optimaldecision rule, based on training samples, to classify a data function. We exploit the optimal classification problem when data functions are Gaussian processes. Sharp nonasymptotic convergence rates for minimax excess mis-classification risk are derived in both settings that data function

Attila Moór, Péter Ábrahám, Gyula Szabó, Krisztián Vida

Extreme debris disks (EDDs) are rare systems with peculiarly large amounts of warm dust that may stem from recent giant impacts between planetary embryos during the final phases of terrestrial planet growth. Here we report on the identification and characterization of six new EDDs. These disks surround F5-G9 type main-sequence stars with ages >100 Myr, have

Hui Xu, Guillaume Basse

Group-formation experiments, in which experimental units are randomly assigned to groups, are a powerful tool for studying peer effects in the social sciences. Existing design and analysis approaches allow researchers to draw inference from such experiments without relying on parametric assumptions. In practice, however, group-formation experiments are often