February 2021 arXiv papers — page 2

James Oxley, Jagdeep Singh

A graph in which every connected induced subgraph has a disconnected complement is called a cograph. Such graphs are precisely the graphs that do not have the 4-vertex path as an induced subgraph. We define a $2$-cograph to be a graph in which the complement of every $2$-connected induced subgraph is not $2$-connected. We show that, like cographs, $2$-cograp

Sheng Lü, Mao-Zhi Yang

We consider the renormalization-group evolution of the matrix element of $\langle 0| \bar{q}(z)_β[z,0]b(0)_α| \bar{B}\rangle$, which can be used to define the distribution amplitudes for $B$ meson and widely applied in studies of $B$ meson decays. The contribution to the renormalization constant of the non-local operator $\bar{q}(z)_β[z,0]b(0)_α$ is consider

Hao Li, Daniel Appelö, Xiangxiong Zhang

The spectral element method constructed by the $Q^k$ ($k\geq 2$) continuous finite element method with $(k+1)$-point Gauss-Lobatto quadrature on rectangular meshes is a popular high order scheme for solving wave equations in various applications. It can also be regarded as a finite difference scheme on all Gauss-Lobatto points. We prove that this finite diff

Indranil Biswas, A. J. Parameswaran

Let $F$ be a torsionfree semistable coherent sheaf on a polarized normal projective variety. We prove that $F$ has a unique maximal locally free subsheaf $V$ such that $F/V$ is torsionfree and $V$ admits a filtration of subbundles for which each successive quotient is stable whose slope is $μ(F)$. We also prove that $F$ has a unique maximal reflexive subshea

Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu

Training generative adversarial networks (GANs) with limited real image data generally results in deteriorated performance and collapsed models. To conquer this challenge, we are inspired by the latest observation, that one can discover independently trainable and highly sparse subnetworks (a.k.a., lottery tickets) from GANs. Treating this as an inductive pr

Junru Luo, Hong Qiao, Bo Zhang

Imbalanced classification tasks are widespread in many real-world applications. For such classification tasks, in comparison with the accuracy rate, it is usually much more appropriate to use non-decomposable performance measures such as the Area Under the receiver operating characteristic Curve (AUC) and the $F_β$ measure as the classification criterion sin

Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss

We examine the general problem of inter-domain Gaussian Processes (GPs): problems where the GP realization and the noisy observations of that realization lie on different domains. When the mapping between those domains is linear, such as integration or differentiation, inference is still closed form. However, many of the scaling and approximation techniques

Chaolong Jiang, Jin Cui, Xu Qian, Songhe Song

A novel class of high-order linearly implicit energy-preserving integrating factor Runge-Kutta methods are proposed for the nonlinear Schrödinger equation. Based on the idea of the scalar auxiliary variable approach, the original equation is first reformulated into an equivalent form which satisfies a quadratic energy. The spatial derivatives of the system a

Zhu Wang

A structure preserving proper orthogonal decomposition reduce-order modeling approach has been developed in [Gong et al. 2017] for the Hamiltonian system, which uses the traditional framework of Galerkin projection-based model reduction but modifies the reduced order model so that the appropriate Hamiltonian structure is preserved. However, its computational

Zhouchi Li, Luyao Niu, Andrew Clark

We investigate a linear quadratic Gaussian (LQG) tracking problem with safety and reachability constraints in the presence of an adversary who mounts an FDI attack on an unknown set of sensors. For each possible set of compromised sensors, we maintain a state estimator disregarding the sensors in that set, and calculate the optimal LQG control input at each

Zümrüt Akçam, Kimberly A. Cornell, Daniel S. Hono, Paliath Narendran

In this paper, we investigate problems which are dual to the unification problem, namely the Fixed Point (FP) problem, Common Term (CT) problem and the Common Equation (CE) problem for string rewriting systems. Our main motivation is computing fixed points in systems, such as loop invariants in programming languages. We show that the fixed point (FP) problem

Yunchou Xing, Theodore S. Rappaport, Amitava Ghosh

This letter provides a comparison of indoor radio propagation measurements and corresponding channel statistics at 28, 73, and 140 GHz, based on extensive measurements from 2014-2020 in an indoor office environment. Side-by-side comparisons of propagation characteristics (e.g., large-scale path loss and multipath time dispersion) across a wide range of frequ

Gautam Krishna, Mason Carnahan, Shilpa Shamapant, Yashitha Surendranath

In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded synchronously with aphasia, apraxia, and dysarthria speech. We demonstrate a significant decoding performance improvement by

Hanwool Bae, Chi Hong Chow, Naichung Conan Leung

We quantize the problem considered by Bott-Samelson who applied Morse theory to any compact symmetric space $G/K$ and the associated real flag manifold $G_{\mathbb{R}}/B$ which is a real locus of a complex partial flag variety $G_{\mathbb{C}}/P_σ$. We prove that the Pontryagin ring $H_{-*}(Ω(G/K))$ of the based loop space $Ω(G/K)$ is isomorphic to the Floer

Penglong Zhai, Shihua Zhang

The information bottleneck (IB) principle has been adopted to explain deep learning in terms of information compression and prediction, which are balanced by a trade-off hyperparameter. How to optimize the IB principle for better robustness and figure out the effects of compression through the trade-off hyperparameter are two challenging problems. Previous m

Abheesht Sharma, Harshit Pandey

Establishing a good information retrieval system in popular mediums of entertainment is a quickly growing area of investigation for companies and researchers alike. We delve into the domain of information retrieval for podcasts. In Spotify's Podcast Challenge, we are given a user's query with a description to find the most relevant short segment from

Zhicheng Feng, Zhenye Li, Jiping Zhang

The Alperin weight conjecture was reduced to simple groups by the work of Navarro, Tiep and Späth. To prove Alperin weight conjecture, it suffices to show that all finite non-abelian simple groups are BAW-good. We reduce the verification of the inductive conditons for groups of Lie type in non-defining characteristic to quasi-isolated blocks.

Chen Wang, Rui Wang, Ajay Mandlekar, Li Fei-Fei

Imitation Learning (IL) is an effective framework to learn visuomotor skills from offline demonstration data. However, IL methods often fail to generalize to new scene configurations not covered by training data. On the other hand, humans can manipulate objects in varying conditions. Key to such capability is hand-eye coordination, a cognitive ability that e

Fumihiro Ishikawa, Hidemaro Suwa, Synge Todo

Integrable systems have provided various insights into physical phenomena and mathematics. The way of constructing many-body integrable systems is limited to few ansatzes for the Lax pair, except for highly inventive findings of conserved quantities. Machine learning techniques have recently been applied to broad physics fields and proven powerful for buildi

Mark Hamilton, Scott Lundberg, Lei Zhang, Stephanie Fu

Visual search, recommendation, and contrastive similarity learning power technologies that impact billions of users worldwide. Modern model architectures can be complex and difficult to interpret, and there are several competing techniques one can use to explain a search engine's behavior. We show that the theory of fair credit assignment provides a $\te

Muhammad Umar Karim Khan

Although depth extraction with passive sensors has seen remarkable improvement with deep learning, these approaches may fail to obtain correct depth if they are exposed to environments not observed during training. Online adaptation, where the neural network trains while deployed, with self-supervised learning provides a convenient solution as the network ca

Yiling Jia, Huazheng Wang, Stephen Guo, Hongning Wang

Online Learning to Rank (OL2R) eliminates the need of explicit relevance annotation by directly optimizing the rankers from their interactions with users. However, the required exploration drives it away from successful practices in offline learning to rank, which limits OL2R's empirical performance and practical applicability. In this work, we propose t

Kristof Lommers, Ouns El Harzli, Jack Kim

This study aims to examine the challenges and applications of machine learning for financial research. Machine learning algorithms have been developed for certain data environments which substantially differ from the one we encounter in finance. Not only do difficulties arise due to some of the idiosyncrasies of financial markets, there is a fundamental tens

Guoyang Xie, Jinbao Wang, Guo Yu, Feng Zheng

Due to limited computational cost and energy consumption, most neural network models deployed in mobile devices are tiny. However, tiny neural networks are commonly very vulnerable to attacks. Current research has proved that larger model size can improve robustness, but little research focuses on how to enhance the robustness of tiny neural networks. Our wo

Jason A. Platt, Adrian S. Wong, Randall Clark, Stephen G. Penny

Reservoir computers (RC) are a form of recurrent neural network (RNN) used for forecasting timeseries data. As with all RNNs, selecting the hyperparameters presents a challenge when training onnew inputs. We present a method based on generalized synchronization (GS) that gives direction in designing and evaluating the architecture and hyperparameters of an R

Max Simchowitz, Aleksandrs Slivkins

How do you incentivize self-interested agents to $\textit{explore}$ when they prefer to $\textit{exploit}$? We consider complex exploration problems, where each agent faces the same (but unknown) MDP. In contrast with traditional formulations of reinforcement learning, agents control the choice of policies, whereas an algorithm can only issue recommendations

Sirish Srinivasan, Sebastian Nicolas Giles, Alexander Liniger

We present a holistically designed three layer control architecture capable of outperforming a professional driver racing the same car. Our approach focuses on the co-design of the motion planning and control layers, extracting the full potential of the connected system. First, a high-level planner computes an optimal trajectory around the track, then in rea

Hamed Amini, Erhan Bayraktar, Suman Chakraborty

We consider bootstrap percolation and diffusion in sparse random graphs with fixed degrees, constructed by configuration model. Every node has two states: it is either active or inactive. We assume that to each node is assigned a nonnegative (integer) threshold. The diffusion process is initiated by a subset of nodes with threshold zero which consists of ini

J. F. Ruiz-Robles, A. M. Longoria-Hernandez, N. A. Gerling-Cervantes, L. E. Sanches-Diaz

The effect of polyvalent molecular cations, such as spermine, on the condensation of DNA into very well-defined toroidal shapes have been well studied and understood. However, a great effort has been made trying to obtain similar condensed structures from either ssRNA or dsRNA, which the latter carries similar negative charge density as dsDNA, although it ad

Kevin Cahill

This paper reviews how a two-state, spin-one-half system transforms under rotations. It then uses that knowledge to explain how momentum-zero, spin-one-half annihilation and creation operators transform under rotations. The paper then explains how a spin-one-half field transforms under rotations. The momentum-zero spinors are found from the way spin-one-half

Henrik Wiechers, Benjamin Eltzner, Stephan F. Huckemann, Kanti V. Mardia

Molecular structures of RNA molecules reconstructed from X-ray crystallography frequently contain errors. Motivated by this problem we examine clustering on a torus since RNA shapes can be described by dihedral angles. A previously developed clustering method for torus data involves two tuning parameters and we assess clustering results for different paramet

Aissam Outchakoucht, Hamza Es-Samaali

Darija Open Dataset (DODa) is an open-source project for the Moroccan dialect. With more than 10,000 entries DODa is arguably the largest open-source collaborative project for Darija-English translation built for Natural Language Processing purposes. In fact, besides semantic categorization, DODa also adopts a syntactic one, presents words under different sp

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

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

Bolu Oluwalade, Sunil Neela, Judy Wawira, Tobiloba Adejumo

In recent years, human activity recognition has garnered considerable attention both in industrial and academic research because of the wide deployment of sensors, such as accelerometers and gyroscopes, in products such as smartphones and smartwatches. Activity recognition is currently applied in various fields where valuable information about an individual&

Hanzi Huang, Yetian Huang, Haoshuo Chen, Qianwu Zhang

We propose a digital interference mitigation scheme to reduce the impact of mode coupling in space division multiplexing self-homodyne coherent detection and experimentally verify its effectiveness in 240-Gbps mode-multiplexed transmission over 3-mode multimode fiber.

Robert Reynolds, Allan Stauffer

In 1826 Cauchy presented an Integral over the real line. Al and I thought a derivation would be mighty fine. So we packed our contour integral bags that day, and we now present an analytic continuation this time.

Mary V. Bastawrous, Mahmoud I. Hussein

Elastic metamaterials may exhibit band gaps at wavelengths far exceeding feature sizes. This is attributed to local resonances of embedded or branching substructures. In branched configurations, such as a pillared plate, waves propagating in the base medium-e.g., the plate portion-experience attenuation at band-gap frequencies. Considering a simplified lumpe

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, sec

Muhammad Mudassar Qureshi, Amjad Farooq, Muhammad Mazhar Qureshi

eHealth (Health Informatics/Medical Informatics) field is growing worldwide due to acknowledge of reputable Organizations such as World Health Organization, Institute of Medicine in USA and several others. This field is facing number of challenges and there is need to classify these challenges mentioned by different researchers of this area. The purpose of t

Matteo Turetta, Fabio Del Ben, Giulia Brisotto, Eva Biscontin

In the present review, we describe three hot topics in cancer research such as circulating tumor cells, exosomes, and 3D environment models. The first section is dedicated to microfluidic platforms for detecting circulating tumor cells, including both affinity based methods that take advantage of antibodies and aptamers, and label free approaches, exploiting

Prathamesh Muzumdar, George Kurian

This study tries to examine the influence of salesperson's customer orientation on customer loyalty. Customer orientation is the approach taken by a salesperson to improve customer relationship and increase sales. Many organizations prefer sales orientation as a strategic approach towards increasing sales. Though successful in its objective, sales orient

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

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

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

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 Götze.

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 $Γ_0(N)$ 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

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 th

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

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 $τ$ of ${\mathbb F}_{q^\ell}/{\mathbb F}_q$,

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

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

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

We present high resolution thermal expansion measurement data obtained with high relative sensitivity of $Δ$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 technological

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

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 Poincaré 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 co

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

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

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

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 $π^{0}$ 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 $π^0$ DVEP at these kinematics. The resul

L. Moriconi

Multifractal systems usually have singularity spectra defined on bounded sets of Hölder 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 o

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

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

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 communica

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

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 d

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

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 v

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

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

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,

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 Lüscher finite-volume method has opened a path to calculate infinite-volume scattering ampli