May 2022 arXiv papers — page 79

Carlos Peña-Monferrer, Carmen Díaz-Marín

We present in this technical note an open-source web framework for the generation and visualization of parametric OpenFOAM simulations from surrogate models. It consists of a JavaScript module (rom.js) and a web app (cfd.xyz) to explore fluid dynamics problems efficiently and easily for a wide range of parameters. rom.js is a JavaScript port of a set of open

O. Ellegaard, S. B. F. Dorch

For decades, perhaps even centuries, the exchange of publications between observatories was the most important source of information on new astronomical results, either in the form of observational data or new scientific theories. In particular, small observatories or institutions used this method. The exchange of physical material between observatories has

Lijie Xie, Jiawei Shen, Andrea Mifsud, Chaohan Wang

The memristor, because of its controllability over a wide dynamic range of resistance, has emerged as a promising device for data storage and analog computation. A major challenge is the accurate measurement of memristance over a wide dynamic range. In this paper, a novel read-out circuit with feedback adjustment is proposed to measure and digitise input cur

Mesfin Taye

The nonequilibrium thermodynamics feature of a Brownian motor is investigated by obtaining exact time-dependent solutions. This in turn enables us to investigate not only the long time property (steady-state) but also the short time the behavior of the system. The general expressions for the free energy, entropy production ${\dot e}_{p}(t)$ as well as entrop

Bo-Qiang Lu, Cheng-Wei Chiang, Da Huang

Although searches for dark matter have lasted for decades, no convincing signal has been found without ambiguity in underground detections, cosmic ray observations, and collider experiments. We show by example that gravitational wave (GW) observations can be a supplement to dark matter detections if the production of dark matter follows a strong first-order

Andrea Mifsud, Jiawei Shen, Peilong Feng, Lijie Xie

Mass characterisation of emerging memory devices is an essential step in modelling their behaviour for integration within a standard design flow for existing integrated circuit designers. This work develops a novel characterisation platform for emerging resistive devices with a capacity of up to 1 million devices on-chip. Split into four independent sub-arra

Musa Furkan Keskin, Henk Wymeersch, Visa Koivunen

We consider the problem of monostatic radar sensing with orthogonal frequency-division multiplexing (OFDM) joint radar-communications (JRC) systems in the presence of phase noise (PN) caused by oscillator imperfections. We begin by providing a rigorous statistical characterization of PN in the radar receiver over multiple OFDM symbols for free-running oscill

Riccardo Taiello, Melek Önen, Francesco Capano, Olivier Humbert

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current approaches to image registration are generally based on the assumption that the content of the images is usually accessible in clear form, from which the spatial transformation is subsequently estimated. This com

Carmelo Cisto, Francesco Navarra, Rosanna Utano

Let $\mathcal{P}$ be a closed path having no zig-zag walks, a kind of non-simple thin polyomino. In this paper we give a combinatorial interpretation of the $h$-polynomial of $K[\mathcal{P}]$, showing that it is the rook polynomial of $\mathcal{P}$. It is known by Rinaldo and Romeo (2021), that if $\mathcal{P}$ is a simple thin polyomino then the $h$-polynom

Lucas Rovige, Joséphine Monzac, Julius Huijts, Igor A. Andriyash

In laser-wakefield acceleration, an ultra-intense laser pulse is focused into an underdense plasma in order to accelerate electrons to relativistic velocities. In most cases, the pulses consist of multiple optical cycles and the interaction is well described in the framework of the ponderomotive force where only the envelope of the laser has to be considered

Arash Abizadeh, Adrian Vetta

A proposed measure of voting power should satisfy two conditions to be plausible: first, it must be conceptually justified, capturing the intuitive meaning of what voting power is; second, it must satisfy reasonable postulates. This paper studies a set of postulates, appropriate for a priori voting power, concerning blockers (or vetoers) in a binary voting g

Emanuele Costa, Giuseppe Scriva, Rosario Fazio, Sebastiano Pilati

Machine-learned regression models represent a promising tool to implement accurate and computationally affordable energy-density functionals to solve quantum many-body problems via density functional theory. However, while they can easily be trained to accurately map ground-state density profiles to the corresponding energies, their functional derivatives of

Kamal Choudhary, Bobby G. Sumpter

The presence of point defects such as vacancies plays an important role in material design. Here, we demonstrate that a graph neural network (GNN) model trained only on perfect materials can also be used to predict vacancy formation energies ($E_{vac}$) of defect structures without the need for additional training data. Such GNN-based predictions are conside

Francesco Bonacci, Brato Chakrabarti, David Saintillan, Olivia du Roure

The fluid-structure interactions between flexible fibers and viscous flows play an essential role in various biological phenomena, medical problems, and industrial processes. Of particular interest is the case of particles freely transported in time-dependent flows. This work elucidates the dynamics and morphologies of actin filaments under oscillatory shear

Arno Förster, Lucas Visscher

The $GW$-Bethe-Salpeter Equation (BSE) method is promising for calculating the low-lying excited states of molecular systems. So far, it has only been applied to rather small molecules, and in the commonly implemented diagonal approximations to the electronic self-energy it depends on a mean-field starting point. We describe here an implementation of the sel

Iryna Raievska, Maryna Raievska

Lower bounds for the number of local nearrings on groups of order $p^3$ are obtained. On each non-metacyclic non-abelian or metacyclic abelian groups of order $p^3$ there exist at least $p+1$ non-isomorphic local nearrings

Manar Samad, Sakib Abrar

Fully connected deep neural networks (DNN) often include redundant weights leading to overfitting and high memory requirements. Additionally, the performance of DNN is often challenged by traditional machine learning models in tabular data classification. In this paper, we propose periodical perturbations (prune and regrow) of DNN weights, especially at the

Hans Ulrich Simon

A tournament is said to have the $S_k$-property if, for any set of $k$ players, there is another player who beats them all. Minimum tournaments having this property have been explored very well in the 1960's and the early 1970's. In this paper, we define a strengthening of the $S_k$-property that we name "strong $S_k$-property". We show, first, that several

Arash Abizadeh, Adrian Vetta

If a measure of voting power assigns players greater voting power because they no longer effectively cooperate, then it displays the quarrelling paradox and violates the quarrel postulate. However, we prove that certain types of quarrel increase some quarrellers' voting power on any proposed measure. On the one hand, such quarrels are politically significant

Arkaprabha Sarangi, Jonathan Slavin

In supernovae (SNe), where the light curves show evidence of strong and early interaction between the ejecta and the circumstellar matter (CSM), the formation of new dust is estimated to take place in a dense shell of gas between the forward (FS) and the reverse shock (RS). For the first time, in this study, the mechanism of dust formation in this dense shel

D. Aleja, G. Contreras-Aso, K. Alfaro-Bittner, E. Primo

In our more and more interconnected world, a specific risk is that of a cyber-epidemic (or cyber-pandemic), produced either accidentally or intentionally, where a cyber virus propagates from device to device up to undermining the global Internet system with devastating consequences in terms of economic costs and societal harms related to the shutdown of esse

Marcelo V. Flamarion, Roberto Ribeiro-Jr

While several articles have been written on water waves on flows with constant vorticity, little is known about the extent to which a nonconstant vorticity affects the flow structure, such as the appearance of stagnation points. In order to shed light on this topic, we investigate in detail the flow beneath solitary waves propagating on an exponentially deca

Arthur Câmara, Claudia Hauff

When training neural rankers using Large Language Models, it's expected that a practitioner would make use of multiple GPUs to accelerate the training time. By using more devices, deep learning frameworks, like PyTorch, allow the user to drastically increase the available VRAM pool, making larger batches possible when training, therefore shrinking training t

Kiryl Asheichyk, Matthias Krüger

Radiative heat transfer between two far-field-separated nanoparticles placed close to a perfectly conducting nanowire decays logarithmically slow with the interparticle distance. This makes a cylinder an excellent waveguide which can transfer thermal electromagnetic energy to arbitrary large distances with almost no loss. It leads to a dramatic increase of t

K. Abdaoui, R. Gharbi, S. Mabrouk, A. Makhlouf

The aim of this paper is to provide a cohomology of $n$-Hom-Lie color algebras governing one parameter formal deformations. Then, we study formal deformations of a $n$-Hom-Lie color algebra and introduce the notion of Nijenhuis operator on an $n$-Hom-Lie color algebra, which could give rise to infinitesimally trivial $(n-1)$-order deformations. Furthermore,

Felipe Maia Polo, Rafael Izbicki, Evanildo Gomes Lacerda, Juan Pablo Ibieta-Jimenez

Supervised learning techniques typically assume training data originates from the target population. Yet, in reality, dataset shift frequently arises, which, if not adequately taken into account, may decrease the performance of their predictors. In this work, we propose a novel and flexible framework called DetectShift that quantifies and tests for multiple

Yangyang Wang, Jeffrey P. Gill, Hillel J. Chiel, Peter J. Thomas

Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system pro

Ling-Jun Kong, Weixuan Zhang, Peng, Li

Optical knots and links have attracted great attention because of their exotic topological characteristics. Recent investigations have shown that the information encoding based on optical knots could possess robust features against external perturbations. However, as a superior coding scheme, it is also necessary to achieve a high capacity, which is hard to

Deyou Chen, Chuanhong Gao

In this paper, we investigate influences of the charge and angular momentum of a particle around a charged Einstein-Euler-Heisenberg AdS black hole on a Lyapunov exponent, and find spatial regions where the chaos bound is violated. Positions of circular orbits are gotten by fixing the charge and angular momentum of the particle, respectively. The positions g

Lirong Cui, Xiangchen Li, Narayanaswamy Balakrishnan

Uncertainty is an important feature of dynamic systems, and entropy has been widely used to measure this attribute. In this Letter, we prove that state aggregation and decomposition can decrease and increase the entropy, respectively, of dynamic systems. More than 20 popular entropies in the literature are summarized and analyzed, and it is noted that none o

Songqi Li, Wenpeng Li, Bernd R. Noack

We propose the first machine-learned control-oriented flow estimation for multiple-input multiple-output plants. Starting point is constant actuation with open-loop actuation commands leading to a database with simultaneously recorded actuation commands, sensor signals and flow fields. A key enabler is an estimator input vector comprising sensor signals and

Francesco Tarantelli, Ettore Vicari

We address the out-of-equilibrium dynamics of many-body systems subject to slow time-dependent round-trip protocols across quantum and classical (thermal) phase transitions. We consider protocols where one relevant parameter w is slowly changed across its critical point wc = 0, linearly in time with a large time scale ts, from wi < 0 to wf > 0 and then back

Xinkai Chen, Jing Wang, Xu Kong

We use 789 disk-like, star-forming galaxies (with 596 HI detections) from HI follow-up observations for the SDSS-IV MaNGA survey to study the possible role of inner HI gas in causing secondary dependences in the mass-gas-phase metallicity relation. We use the gas-phase metallicity derived at the effective radii of the galaxies. We derive the inner HI mass wi

Affaf Junaid Ahamad Momin, Gabriele Nava, Giuseppe LErario, Hosameldin Awadalla Omer Mohamed

Jet-powered vertical takeoff and landing (VTOL) drones require precise thrust estimation to ensure adequate stability margins and robust maneuvering. Small-scale turbojets have become good candidates for powering heavy aerial drones. However, due to limited instrumentation available in these turbojets, estimating the precise thrust using classical techniques

Sandra Lagén, Xavier Gelabert, Andreas Hansson, Manuel Requena

There is a widely held belief that future Radio Access Network (RAN) architectures will be characterized by increased levels of virtualization, whereby base station functionalities, traditionally residing at a single location, will be scattered across different logical entities while being interfaced via high-speed fronthaul (FH) links. For the deployment of

Muhammad Farooq, Tung Thanh Vu, Hien Quoc Ngo, Le-Nam Tran

With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated that future wireless networks will jointly serve both FL and downlink non-FL user groups in the same time-frequency resource. While in the downlink of each FL iteration, both grou

Anamul Md. Hoque, Bing Zhao, Dmitrii Khokhriakov, Prasanta Muduli

Quantum materials with a large charge current-induced spin polarization are promising for next-generation all-electrical spintronic science and technology. Van der Waals metals with high spin-orbit coupling and novel spin textures have attracted significant attention for an efficient charge to spin conversion process. Here, we demonstrate the electrical gene

Zachary Seymour, Niluthpol Chowdhury Mithun, Han-Pang Chiu, Supun Samarasekera

Understanding the geometric relationships between objects in a scene is a core capability in enabling both humans and autonomous agents to navigate in new environments. A sparse, unified representation of the scene topology will allow agents to act efficiently to move through their environment, communicate the environment state with others, and utilize the r

Dinghao Yang, Bin Wang, Weijia Li, Yiqi Lin

Recent image matting studies are developing towards proposing trimap-free or interactive methods for complete complex image matting tasks. Although avoiding the extensive labors of trimap annotation, existing methods still suffer from two limitations: (1) For the single image with multiple objects, it is essential to provide extra interaction information to

Jan Gregorovič, Lenka Zalabová

We study first BGG operators and their solutions on homogeneous conformal geometries. We focus on conformal Killing tensors, conformal Killing--Yano forms and twistor spinors in particular. We develop an invariant calculus that allows us to find solutions explicitly using only algebraic computations. We also discuss applications to holonomy reductions and co

Ralph C. Bohlin, Jessica E. Krick, Karl D. Gordon, Ivan Hubeny

An accurate tabulation of stellar brightness in physical units is essential for a multitude of scientific endeavors. The HST/CALSPEC database of flux standards contains many stars with spectral coverage in the 0.115--1 \micron\ range with some extensions to longer wavelengths of 1.7 or 2.5 \micron. Modeled flux distributions to 32 \micron\ for calibration of

Rishith Ellath Meethal, Birgit Obst, Mohamed Khalil, Aditya Ghantasala

We introduce a novel hybrid methodology combining classical finite element methods (FEM) with neural networks to create a well-performing and generalizable surrogate model for forward and inverse problems. The residual from finite element methods and custom loss functions from neural networks are merged to form the algorithm. The Finite Element Method-enhanc

Fırat Duruşan, Ali Hürriyetoğlu, Erdem Yörük, Osman Mutlu

The database creation utilized automated text processing tools that detect if a news article contains a protest event, locate protest information within the article, and extract pieces of information regarding the detected protest events. The basis of training and testing the automated tools is the GLOCON Gold Standard Corpus (GSC), which contains news artic

Pisin Chen, Misao Sasaki, Dong-han Yeom, Junggi Yoon

The information loss paradox remains unresolved ever since Hawking's seminal discovery of black hole evaporation. In this essay, we revisit the entanglement entropy via Euclidean path integral (EPI) and allow for the branching of semi-classical histories during the Lorentzian evolution. We posit that there exist two histories that contribute to EPI, where on

Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, Abhinav Valada

In recent years, policy learning methods using either reinforcement or imitation have made significant progress. However, both techniques still suffer from being computationally expensive and requiring large amounts of training data. This problem is especially prevalent in real-world robotic manipulation tasks, where access to ground truth scene features is

Kowsar. Al Mousavitaha, Özgür E. Müstecaplıoglu, Esfandyar Faizi

The micromaser is an archetype experimental setting where a beam of excited two-level atoms is injected into a high-finesse cavity. It has played a pivotal role as a testbed for predictions of quantum optics. We consider a generalized micromaser setting consisting of high-quality cavity pumped by a beam of three-level atoms. The atoms are assumed to be prepa

Yepeng Ding, Hiroyuki Sato

Self-sovereign identity (SSI) has gained a large amount of interest. It enables physical entities to retain ownership and control of their digital identities, which naturally forms a conceptual decentralized architecture. With the support of the distributed ledger technology (DLT), it is possible to implement this conceptual decentralized architecture in pra

Sergio Giardino

Using the complex Klein-Gordon field as a model, we quantize the quaternionic scalar field in the real Hilbert space. The lagrangian formulation has accordingly been obtained, as well as the hamiltonian formulation, and the energy and charge operators. Conversely to the complex case, the quaternionic quantization admits two quantization schemes, concerning e

Taro Kimura

We study the $qq$-character of quantum affine and toroidal algebra modules, with a focus on the role of spectral parameters. In particular, we revisit how their specialization affects the irreducibility of these modules.

Cezar Augusto Bellezi, Liang-Yee Cheng, Rubens Augusto Amaro Junior, Marcio Michiharu Tsukamoto

A novel multi-resolution technique called border mapping multi-resolution (BMMR) is proposed for projection-based particle methods. The BMMR aims to obtain background equivalent particle distributions in the two sides of a border between sub-domains with a 2:1 resolution ratio so that a single resolution framework is adopted to near-border particles calculat

Muhammad Farooq, Tung T. Vu, Hien Quoc Ngo, Le-Nam Tran

Federated learning (FL) with its data privacy protection and communication efficiency has been considered as a promising learning framework for beyond-5G/6G systems. We consider a scenario where a group of downlink non-FL users are jointly served with a group of FL users using massive multiple-input multiple-output technology. The main challenge is how to ut

Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner

Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical calculations, being practically limited to short timescales and few atoms. For larger systems, efficient, but much less reliable empirical force fields are used. Recently, machine le

Deblina Bhattacharjee, Tong Zhang, Sabine Süsstrunk, Mathieu Salzmann

We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, surface normal estimation, 2D keypoint detection, and edge detection. Based on the Swin transformer model, our framework encodes the input image into a shared re

Felipe Espreafico

In mirror symmetry, after the work by J. Walcher, the number of holomorphic disks with boundary on the real quintic lagrangian in a general quintic threefold is related to the periods of the mirror quintic family with boundary on two homologous rational curves. Following the ideias of H.Movasati, we construct a quasi-affine space parametrizing such objects e

Tong Hui, Antonello Paolino, Gabriele Nava, Giuseppe L'Erario

This paper presents a modeling and control framework for multibody flying robots subject to non-negligible aerodynamic forces acting on the centroidal dynamics. First, aerodynamic forces are calculated during robot flight in different operating conditions by means of Computational Fluid Dynamics (CFD) analysis. Then, analytical models of the aerodynamics coe

Thom S. Badings, Nils Jansen, Sebastian Junges, Marielle Stoelinga

We employ uncertain parametric CTMCs with parametric transition rates and a prior on the parameter values. The prior encodes uncertainty about the actual transition rates, while the parameters allow dependencies between transition rates. Sampling the parameter values from the prior distribution then yields a standard CTMC, for which we may compute relevant r

Xin Li, Wang Gao, Qing Jiang

The control of solute segregation at grain boundaries (GBs) is essential in engineering alloy properties, however the structure-activity relationship of the key parameter-the segregation energies-still remains elusive. Here we propose the electronic and geometric descriptors of GB segregation based on the valence, electronegativity and size of solutes and th

Maik Gaerner, Robin Silber, Tobias Peters, Jaroslav Hamrle

In most studies utilizing the magneto-optic Kerr effect (MOKE), the detected change of polarized light upon reflection from a magnetized sample is supposed to be proportional to the magnetization $\boldsymbol{M}$. However, MOKE signatures quadratic in $\boldsymbol{M}$ have also been identified and utilized, e.g., to sense the structural order in Heusler comp

Hendrik Leidinger, Christoph Weidenbach

We propose a new calculus SCL(EQ) for first-order logic with equality that only learns non-redundant clauses. Following the idea of CDCL (Conflict Driven Clause Learning) and SCL (Clause Learning from Simple Models) a ground literal model assumption is used to guide inferences that are then guaranteed to be non-redundant. Redundancy is defined with respect t

S. Q. Zhou, E. Gügercinoğlu, J. P. Yuan, M. Y. Ge

The close correlation observed between emission state and spin-down rate change of pulsars has many implications both for the magnetospheric physics and the neutron star interior. The middle-aged pulsar PSR J0738$-$4042, which had been observed to display variations in the pulse profile associated with its spin-down rate change due to external effects, is a

Young-Geun Choi, Gi-Soo Kim, Seunghoon Paik, Myunghee Cho Paik

Non-stationarity is ubiquitous in human behavior and addressing it in the contextual bandits is challenging. Several works have addressed the problem by investigating semi-parametric contextual bandits and warned that ignoring non-stationarity could harm performances. Another prevalent human behavior is social interaction which has become available in a form

Risto Raitio

A previous supersymmetric preon scenario for visible matter particles is extended to the dark sector. In addition, the scenario is reformulated as a Double Field Theory (DFT) with four extra dimensions, to avoid a singular Big Bang in cosmology. T-duality and doubled local Lorentz symmetry of the model are genuine stringy properties. It is proposed that DFT

Arnaud Marsiglietti, James Melbourne

We investigate quantitative implications of the notion of log-concavity through a probabilistic interpretation. In particular, we derive concentration inequalities, moment and entropy bounds for random variables satisfying a precise degree of log-concavity. Along the way, we recover, improve, and simplify several results existing in the literature. Our appro

Wei Dong, Baogang Xu, Yian Xu

Let $F_1$ and $F_2$ be two disjoint graphs. The union $F_1\cup F_2$ is a graph with vertex set $V(F_1)\cup V(F_2)$ and edge set $E(F_1)\cup E(F_2)$, and the join $F_1+F_2$ is a graph with vertex set $V(F_1)\cup V(F_2)$ and edge set $E(F_1)\cup E(F_2)\cup \{xy\;|\; x\in V(F_1)\mbox{ and } y\in V(F_2)\}$. In this paper, we present a characterization to $(P_5,

Young-Min Baek, Esther Cho, Donghwan Shin, Doo-Hwan Bae

Over recent decades, scenarios and scenario-based software/system engineering have been actively employed as essential tools to handle intricate problems, validate requirements, and support stakeholders' communication. However, despite the widespread use of scenarios, there have been several challenges for engineers to more willingly utilize scenario-based e

Hossein A. Rahmani, Mohammadmehdi Naghiaei, Mahdi Dehghan, Mohammad Aliannejadi

Recent work in recommender systems mainly focuses on fairness in recommendations as an important aspect of measuring recommendations quality. A fairness-aware recommender system aims to treat different user groups similarly. Relevant work on user-oriented fairness highlights the discriminative behavior of fairness-unaware recommendation algorithms towards a

Davide Locatelli, Ariadna Quattoni

Prior to deep learning the semantic parsing community has been interested in understanding and modeling the range of possible word alignments between natural language sentences and their corresponding meaning representations. Sequence-to-sequence models changed the research landscape suggesting that we no longer need to worry about alignments since they can

Trisha Chakraborty, Abir Islam, Valerie King, Daniel Rayborn

Can we make a denial-of-service attacker pay more than the server and honest clients? Consider a model where a server sees a stream of jobs sent by either honest clients or an adversary. The server sets a price for servicing each job with the aid of an estimator, which provides approximate statistical information about the distribution of previously occurrin

Fabian Germ, István Gyöngy

This paper is the first part of a series of papers on filtering for partially observed jump diffusions satisfying a stochastic differential equation driven by Wiener processes and Poisson martingale measures. The coefficients of the equation only satisfy appropriate growth conditions. Some results in filtering theory of diffusion processes are extended to ju

Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou

Knowledge representation learning has been commonly adopted to incorporate knowledge graph (KG) into various online services. Although existing knowledge representation learning methods have achieved considerable performance improvement, they ignore high-order structure and abundant attribute information, resulting unsatisfactory performance on semantics-ric

Alan S. Cornell, Anele Ncube, Gerhard Harmsen

In recent years there has been an increased interest in neural networks, particularly with regard to their ability to approximate partial differential equations. In this regard, research has begun on so-called physics-informed neural networks (PINNs) which incorporate into their loss function the boundary conditions of the functions they are attempting to ap

François Smekens, Nicolas Freud, Bruno Sixou, Guillaume Beslon

The dose delivered to the planning target volume by proton beams is highly conformal, sparing organs at risk and normal tissues. New treatment planning systems adapted to spot scanning techniques have been recently proposed to simultaneously optimize several fields and thus improve dose delivery. In this paper, we investigate a new optimization framework bas

Sylwia Bazak, Stanislaw Mrowczynski

A system of chromodynamic fields, which can be treated as classical, is generated at the earliest stage of relativistic heavy-ion collisions. Numerical simulations show that the system is unstable but the nature of the instability is not well understood. We study the problem systematically. In the first paper, we have performed a linear stability analysis of

Aleksandr Yu. Konovalov

Let V be a set of number-theoretical functions. We define a notion of V -realizability for predicate formulas in such a way that the indices of functions in V are used for interpreting the implication and the universal quantifier. In this paper we prove that Intuitionistic Predicate Calculus is sound with respect to the semantics of V -realizability if and o

R. J. F. Ypma, P. A. Maaskant-van Wijk, R. D. Gill, M. Sjerps

Messenger RNA (mRNA) profiling can identify body fluids present in a stain, yielding information on what activities could have taken place at a crime scene. To account for uncertainty in such identifications, recent work has focused on devising statistical models to allow for probabilistic statements on the presence of body fluids. A major hurdle for practic

Ailisi Li, Xueyao Jiang, Bang Liu, Jiaqing Liang

Math Word Problems (MWP) is an important task that requires the ability of understanding and reasoning over mathematical text. Existing approaches mostly formalize it as a generation task by adopting Seq2Seq or Seq2Tree models to encode an input math problem in natural language as a global representation and generate the output mathematical expression. Such

Stanisław Kasjan, Mariusz Lemańczyk, Sebastian Zuniga Alterman

We study the complexity of $\mathscr{B}$-free subshifts which are proximal and of zero entropy. Such subshifts are generated by Behrend sets. The complexity is shown to achieve any subexponential growth and is estimated for some classical subshifts (prime and semiprime subshifts). We also show that $\mathscr{B}$-admissible subshifts are transitive only for c

Zhaolin Wang, Xidong Mu, Yuanwei Liu, Xiaodong Xu

A non-orthogonal multiple access (NOMA)-aided joint communication, sensing, and multi-tier computing (JCSMC) framework is proposed. In this framework, a multi-functional base station (BS) carries out target sensing, while providing edge computing services to the nearby users. To enhance the computation efficiency, the multi-tier computing structure is exploi

Liang-Jun Zhai, Guang-Yao Huang, Shuai Yin

In this paper, we investigate the driven dynamics of the localization transition in the non-Hermitian Aubry-Andr\'{e} model with the periodic boundary condition. Depending on the strength of the quasi-periodic potential $\lambda$, this model undergoes a localization-delocalization phase transition. We find that the localization length $\xi$ satisfies $\xi\si

Rose Bohrer

Safety-critical chemical processes are the backbone of multi-billion-dollar industries, thus society deserves the strongest possible guarantees that they are safe. To that end, models of chemical processes are well-studied in the formal methods literature, including hybrid systems models which combine discrete and continuous dynamics. This paper is the first

Dong Woo Kang, Jongkuk Kim, Takaaki Nomura, Hiroshi Okada

It is clear that matter is dominant in the Universe compared to antimatter. We call this problem baryon asymmetry. The baryon asymmetry is experimentally determined by both cosmic microwave background and big bang nucleosynthesis measurements. To resolve the baryon number asymmetry of the Universe as well as neutrino oscillations, we study a radiative seesaw

Gen Chiaki, John H. Wise

The multiplicity of metal-free (Population III) stars may influence their feedback efficiency within their host dark matter halos, affecting subsequent metal enrichment and the transition to galaxy formation. Radiative feedback from massive stars can trigger nearby star formation in dense self-shielded clouds. In model radiation self-shielding, the H$_2$ col

Pierre Bouvier, Alireza Sasani, Eric Bousquet, Mael Guennou

Lead vanadate PbVO3 is a polar crystal with a P4mm space group at ambient conditions. It is isostructural with the model soft-mode driven ferroelectric PbTiO3, but differs from it by the so-called 'supertetragonal' elongation of its unit cell. In this paper, we report a combined study of the lattice dynamics of PbVO3 by Raman spectroscopy at room temperature

Yang Liu, Xin Zhong

The mathematical analysis on the behavior of the entropy for viscous, compressible, and heat conducting magnetohydrodynamic flows near the vacuum region is a challenging problem as the governing equation for entropy is highly degenerate and singular in the vacuum region. In particular, it is unknown whether the entropy remains its boundedness. In the present

Nadia Daoudi, Kevin Allix, Tegawendé F. Bissyandé, Jacques Klein

The popularity of Android OS has made it an appealing target to malware developers. To evade detection, including by ML-based techniques, attackers invest in creating malware that closely resemble legitimate apps. In this paper, we propose GUIDED RETRAINING, a supervised representation learning-based method that boosts the performance of a malware detector.

Lachlan Urquhart, Alex Laffer, Diana Miranda

This paper explores public perceptions around the role of affective computing in the workplace. It uses a series of design fictions with 46 UK based participants, unpacking their perspectives on the advantages and disadvantages of tracking the emotional state of workers. The scenario focuses on mundane uses of biometric sensing in a sales environment, and ho

Ali Kariminezhad, Soheil Gherekhloo, Aydin Sezgin

The utilization of RF signals to probe material properties of objects is of huge interest both in academia as well as industry. To this end, a setup is investigated, in which a transmitter equipped with a two-dimensional multi-antenna array dispatches a signal, which hits objects in the environment and the reflections from the objects are captured by distrib

Deheng Yuan, Tao Guo, Bo Bai, Wei Han

We consider a problem of coding for computing, where the decoder wishes to estimate a function of its local message and the source message at the encoder within a given distortion. We show that the rate-distortion function can be characterized through a characteristic multi-hypergraph, which simplifies the evaluation of the rate-distortion function.

Tekin Dereli, Ozay Gurtug, Mustafa Halilsoy, Yorgo Senikoglu

Sandwich gravitational waves are given globally in terms of step functions at the boundaries. Linearized Einstein-Weyl equations are solved exactly in this background in Rosen coordinates. Depending on the geometry and composition of the sandwich wave, the neutrino's energy-momentum redistributes itself. At the test field level, since the background will not

Ankur Kumar, Mayank Goswami

An in-house developed 2D ultrasound computerized Tomography system is fully automated. Performance analysis of instrument and software interfacing soft tools, namely the LabVIEW, MATLAB, C, and Python, is presented. The instrument interfacing algorithms, hardware control algorithms, signal processing, and analysis codes are written using above mentioned soft

Yunjing Gao, Jiahao Yang, Zhenyu Zhu, Yosuke Mizuno

Based on the GW dispersion relation raised in [1], we investigate the possible reflection of gravitational wave (GW) by superfluidity (SF) in the neutron star, provided its high density and dissipationless properties. Following this scenario, an experimental proposal is raised to probe the expected SF in neutron star by means of GW detection. Two types of bi

Monu Nath Baitha, Kyoungsik Kim

In plasmonic systems, the enhanced photonic spin Hall effect (PSHE) was previously possible only for horizontal polarization. By employing the wave-guiding surface plasmon resonance (WG-SPR) effect, we report a giant photonic spin Hall effect (G-PSHE) of reflected light for both horizontal and vertical polarization waves. We investigated the polarization-man

Daniel Rotman, Ophir Azulai, Inbar Shapira, Yevgeny Burshtein

Optical Character Recognition (OCR), the task of extracting textual information from scanned documents is a vital and broadly used technology for digitizing and indexing physical documents. Existing technologies perform well for clean documents, but when the document is visually degraded, or when there are non-textual elements, OCR quality can be greatly imp

Sidsel Boldsen, Patrizia Paggio

While a great deal of work has been done on NLP approaches to lexical semantic change detection, other aspects of language change have received less attention from the NLP community. In this paper, we address the detection of sound change through historical spelling. We propose that a sound change can be captured by comparing the relative distance through ti

Saber Salehkaleybar, Sadegh Khorasani, Negar Kiyavash, Niao He

Variance-reduced gradient estimators for policy gradient methods have been one of the main focus of research in the reinforcement learning in recent years as they allow acceleration of the estimation process. We propose a variance-reduced policy-gradient method, called SHARP, which incorporates second-order information into stochastic gradient descent (SGD)

Nazar Waheed, Muhammad Ikram, Saad Sajid Hashmi, Xiangjian He

Web-based chatbots provide website owners with the benefits of increased sales, immediate response to their customers, and insight into customer behaviour. While Web-based chatbots are getting popular, they have not received much scrutiny from security researchers. The benefits to owners come at the cost of users' privacy and security. Vulnerabilities, such

Carmelo Cisto, Francesco Navarra, Rosanna Utano

In this paper we introduce some monomial orders for the class of closed path polyominoes and we prove that the set of the generators of the polyomino ideal attached to a closed path forms the reduced Gr\"obner basis with respect to these monomial orders. It is known that the polyomino ideal attached to a closed path containing an L-configuration or a ladder

Georgios Daskalopoulos, Karen Uhlenbeck

In a 1998 preprint, Bill Thurston outlined a Teichmuller theory for hyperbolic surfaces based on maps between surfaces which minimize the Lipschitz constant (minimum stretch or best Lipschitz maps). In this paper we continue the analytic investigation which we began in our previous paper. In the spirit of the construction of infinity-harmonic functions, we p

Daniel Rotman, Yevgeny Yaroker, Elad Amrani, Udi Barzelay

Video scene detection is the task of dividing videos into temporal semantic chapters. This is an important preliminary step before attempting to analyze heterogeneous video content. Recently, Optimal Sequential Grouping (OSG) was proposed as a powerful unsupervised solution to solve a formulation of the video scene detection problem. In this work, we extend

Natalia Martín Sabanés, Faruk Krecinic, Takashi Kumagai, Fabian Schulz

Efficient operation of electronic nanodevices at ultrafast speeds requires understanding and control of the currents generated by femtosecond bursts of light. Ultrafast laser-induced currents in metallic nanojunctions can originate from photo-assisted hot electron tunneling or lightwave-induced tunneling. Both processes can drive localized photocurrents insi