August 2022 arXiv papers — page 12

Mohammadreza Doostmohammadian, Wei Jiang, Themistoklis Charalambous

Latency is inherent in almost all real-world networked applications. In this paper, we propose a distributed allocation strategy over multi-agent networks with delayed communications. The state of each agent (or node) represents its share of assigned resources out of a fixed amount (equal to overall demand). Every node locally updates its state toward optimi

Ioannis Contopoulos, Athanasios C. Tzemos, Foivos Zanias, George Contopoulos

We develop a classical picture of interference for non-interacting individual classical massive free particles. As long as they remain undetected, particles carry the information of a phase equal to an action integral along their trajectory. At the point of their detection, a special type of detector collects the phases from all individual particles reaching

Ibuki Terashima, Tetsuo Hyodo

The quark-antiquark potentials are known to be confining in the absence of the $\bar{q}q$ pair creation. On the other hand, the inter-hadron potentials vanish at large distance, because the interaction range is limited by the inverse pion mass. When the $\bar{q}q$ pair creation and annihilation are switched on, the channel coupling occurs between the quark a

Pihe Hu, Ling Pan, Yu Chen, Zhixuan Fang

Multi-user delay constrained scheduling is important in many real-world applications including wireless communication, live streaming, and cloud computing. Yet, it poses a critical challenge since the scheduler needs to make real-time decisions to guarantee the delay and resource constraints simultaneously without prior information of system dynamics, which

Li Sun, Junda Ye, Hao Peng, Philip S. Yu

Representation learning on temporal graphs has drawn considerable research attention owing to its fundamental importance in a wide spectrum of real-world applications. Though a number of studies succeed in obtaining time-dependent representations, it still faces significant challenges. On the one hand, most of the existing methods restrict the embedding spac

Jesper C. Provoost, Andreas Kamilaris, Gyözö Gidófalvi, Geert J. Heijenk

In ridepooling systems with electric fleets, charging is a complex decision-making process. Most electric vehicle (EV) taxi services require drivers to make egoistic decisions, leading to decentralized ad-hoc charging strategies. The current state of the mobility system is often lacking or not shared between vehicles, making it impossible to make a system-op

Vladimir Pislyakov

One of the most useful and correct methodological approaches in bibliometrics is ranking. In the context of highly skewed bibliometric distributions and severe distortions caused by outliers, it is often the preferable way of analysis. Ranking methodology strictly implies that "oranges should be compared with oranges, apples with apples". We should make a "l

Luca Frittoli, Diego Carrera, Beatrice Rossi, Pasqualina Fragneto

The chips contained in any electronic device are manufactured over circular silicon wafers, which are monitored by inspection machines at different production stages. Inspection machines detect and locate any defect within the wafer and return a Wafer Defect Map (WDM), i.e., a list of the coordinates where defects lie, which can be considered a huge, sparse,

Kazutaka Takahashi, Yasuhiro Utsumi

We extend the speed limit of a distance between two states evolving by different generators for quantum systems [K. Suzuki and K. Takahashi, Phys. Rev. Res. 2, 032016(R) (2020)] to the classical stochastic processes described by the master equation. We demonstrate that the trace distance between arbitrary evolving states is bounded from above by using a geom

Xian-Jun Long, Yue-Hong He, Nan-Jing Huang

The main purpose of this paper is to propose a variance-based Bregman extragradient algorithm with line search for solving stochastic variational inequalities, which is robust with respect an unknown Lipschitz constant. We prove the almost sure convergence of the algorithm by a more concise and effective method instead of using the supermartingale convergenc

Nikolaj Winther Hansen, James Luke Webb, Luca Troise, Christoffer Olsson

An important tool in the investigation of the early stages of neurodegenerative disease is the study of dissected living tissue from the brain of an animal model. Such investigations allow the physical structure of individual neurons and neural circuits to be probed alongside neuronal electrical activity, disruption of which can shed light on the mechanisms

Gennaro Coppola, Arthur E. P. Veldman

The spatial discretization of convective terms in compressible flow equations is studied from an abstract viewpoint, for finite-difference methods and finite-volume type formulations with cell-centered numerical fluxes. General conditions are sought for the local and global conservation of primary (mass and momentum) and secondary (kinetic energy) invariants

Stefano Della Fiore, Marco Dalai, Ugo Vaccaro

In this paper, we study bounds on the minimum length of $(k,n,d)$-superimposed codes introduced by Agarwal et al. [1], in the context of Non-Adaptive Group Testing algorithms with runlength constraints. A $(k,n,d)$-superimposed code of length $t$ is a $t \times n$ binary matrix such that any two 1's in each column are separated by a run of at least $d$ 0's,

Veronica Phan

A perfect graph is a graph which every induced subgraph has clique number equal to chromatic number. In this paper, I will introduce a new family of graphs, the quasiperfect graphs which generalizes the perfect graphs.

Ivan Gnusov, Stella Harrison, Sergey Alyatkin, Kirill Sitnik

The appearance of quantised vortices in the classical ``rotating bucket'' experiments of liquid helium and ultracold dilute gases provides the means for fundamental and comparative studies of different superfluids. Here, we realize the ``rotating bucket'' experiment for optically trapped quantum fluid of light based on exciton-polariton Bose-Einstein condens

Shinichi. W. Kinoshita, Fumitaka Nakamura

We investigated the effect of magnetic fields on the collision process between dense molecular cores. We performed three-dimensional magnetohydrodynamic simulations of collisions between two self-gravitating cores using the Enzo adaptive mesh refinement code. The core was modeled as a stable isothermal Bonnor-Ebert (BE) sphere immersed in uniform magnetic fi

Xinxing Tang, Shing-Tung Yau

In this paper, firstly, we will study the structure of the path complex $(\Omega_*(G;\Z),\partial)$ of a digraph $G$ via the $\Z$-generators of $\Omega_*(G,\Z)$ under strongly regular condition, which is called the minimal path in \cite{HY}. In particular, we will study various examples of the minimal $3$-paths. Secondly, we will show that the supporting sub

Zhongkai Tong, Ziyuan Zhu, Yusha Zhang, Yuxin Liu

To improve the overall performance of processors, computer architects use various performance optimization techniques in modern processors, such as speculative execution, branch prediction, and chaotic execution. Both now and in the future, these optimization techniques are critical for improving the execution speed of processor instructions. However, resear

Suzanne Lancaster, Iciar Arnay, Ruben Guerrero, Adrían Gudín

Direct integration of ferroelectric Hf0.5Zr0.5O2 (HZO) on the inert surface of graphene is challenging. Here, using nucleation layers to promote atomic layer deposition of HZO was investigated. Different metals were deposited as nucleation layers via dc sputtering. Ta, which oxidizes in air to form a sub-stoichiometric oxide, was compared to Pt, which offers

Pierrick Pochelu, Clara Erard, Philippe Cordier, Serge G. Petiton

Camera traps have revolutionized the animal research of many species that were previously nearly impossible to observe due to their habitat or behavior. They are cameras generally fixed to a tree that take a short sequence of images when triggered. Deep learning has the potential to overcome the workload to automate image classification according to taxon or

Mohammadreza Doostmohammadian, Alireza Aghasi, Apostolos I. Rikos, Andreas Grammenos

This paper considers a network of collaborating agents for local resource allocation subject to nonlinear model constraints. In many applications, it is required (or desirable) that the solution be anytime feasible in terms of satisfying the sum-preserving global constraint. Motivated by this, sufficient conditions on the nonlinear mapping for anytime feasib

Xuhua He, Sian Nie, Qingchao Yu

In this paper, we study affine Deligne--Lusztig varieties $X_w(b)$ when the finite part of the element $w$ in the Iwahori--Weyl group is a partial $\sigma$-Coxeter element. We show that such $w$ is a cordial element and $X_w(b) \neq \emptyset$ if and only if $b$ satisfies a certain Hodge--Newton indecomposability condition. The main result of this paper is t

Xinbiao Wang, Junyu Liu, Tongliang Liu, Yong Luo

Many fundamental properties of a quantum system are captured by its Hamiltonian and ground state. Despite the significance of ground states preparation (GSP), this task is classically intractable for large-scale Hamiltonians. Quantum neural networks (QNNs), which exert the power of modern quantum machines, have emerged as a leading protocol to conquer this i

Yan-Qi Wang, Chunxiao Liu, Joel E. Moore

The chiral spin liquid is one of the canonical examples of a topological state of quantum spins coexisting with symmetry-breaking chiral order; its experimental realization has been actively discussed in the past few years. Here, motivated by the interplay between topology and symmetry breaking, we examine the physics of the interface between two chiral spin

Jagadish Rajpoot, Ravneet Paul, Shivam Verma

Ensuring high performance, while meeting the power budget is a challenging task as the world is moving towards next-generation computing. Researchers and designers are in search of new solutions for efficient computation. Spintronics devices have been viewed as a promising way to deal with the escalating difficulties of CMOS downscaling, explicitly, the Magn

Moataz M. Alghamdi, Daniele Boffi, Francesca Bonizzoni

In this paper we introduce an algorithm based on a sparse grid adaptive refinement, for the approximation of the eigensolutions to parametric problems arising from elliptic partial differential equations. In particular, we are interested in detecting the crossing of the hypersurfaces describing the eigenvalues as a function of the parameters. The a priori ma

Chol Jong, Shin-Hyok Jon, Son-Il Jo, Namchol Choe

The uncertainty principle is the most important for the foundations of quantum mechanics but it still remains failed to reach a consensus of its interpretation, which gives rise to debates upon its physical nature. In this work, we address the problem of its foundation from a different aspect to present an alternative formulation for proving the uncertainty

Songbin Chen

With the development of autonomous driving, the improvement of autonomous driving technology for individual vehicles has reached the bottleneck. The advancement of vehicle-road cooperation autonomous driving technology can expand the vehicle's perception range, supplement the perception blind area and improve the perception accuracy, to promote the developme

Apurba Tiwari, Sudhir Kumar Gupta

We explore $\mathcal CP$-violation effects of Higgs-top interactions in the associated production of a Higgs boson with top-pair in the dileptonic decay modes of top-quark originating from proton proton collisions $pp \to t\bar{t}H \to (l^+ \nu_l b)(l^{-} \bar{\nu_l} \bar{b})H$ at NLO in QCD matched to parton shower via T-odd observables using momenta of var

Narayan Kundu, Vikrant Kumar, Dhananjay Nandi

We have studied electron-induced ion-pair dissociation dynamics of CO using the state-of-art velocity map imaging technique in combination with a time-of-flight-based two-field mass spectrometer. Extracting the characteristics for O$^-$/CO nascent atomic anionic fragments from the low energy (25 - 45 eV) electron-molecule scattering, first-time, we have dire

Pierrick Pochelu, Serge G. Petiton, Bruno Conche

Ensembles of Deep Neural Networks (DNNs) have achieved qualitative predictions but they are computing and memory intensive. Therefore, the demand is growing to make them answer a heavy workload of requests with available computational resources. Unlike recent initiatives on inference servers and inference frameworks, which focus on the prediction of single D

Yang Cao, Pan Wang, Kang Zheng, Xianghu Liang

Downlink coherent multiuser transmission is an essential technique for cell-free massive multiple-input multiple output (MIMO) systems, and the availability of channel state information (CSI) at the transmitter is a basic requirement. To avoid CSI feedback in a time-division duplex system, the uplink channel parameters should be calibrated to obtain the down

Bing-Sui Lu, Khatee Zathul Arifa, Martial Ducloy

We consider the resonant Casimir-Polder interaction of an excited alkali-type atom which has a single (electric dipole) transition with a Chern insulator. The Chern insulator has a nonzero, time reversal symmetry breaking Hall conductance, leading to an additional contribution to the resonant Casimir-Polder interaction which depends on the coupling between t

Pierrick Pochelu, Serge G. Petiton, Bruno Conche

Automated Machine Learning with ensembling (or AutoML with ensembling) seeks to automatically build ensembles of Deep Neural Networks (DNNs) to achieve qualitative predictions. Ensemble of DNNs are well known to avoid over-fitting but they are memory and time consuming approaches. Therefore, an ideal AutoML would produce in one single run time different ense

Andrea Bionda, Luca Frittoli, Giacomo Boracchi

Detecting anomalous regions in images is a frequently encountered problem in industrial monitoring. A relevant example is the analysis of tissues and other products that in normal conditions conform to a specific texture, while defects introduce changes in the normal pattern. We address the anomaly detection problem by training a deep autoencoder, and we sho

Aristide Doussot, Benoit Semelin

The bubble size distribution is a summary statistics that can be computed from the observed 21-cm signal from the Epoch of Reionization. As it depends only on the ionization field and is not limited to gaussian information, it is an interesting probe, complementary to the power spectrum of the full 21-cm signal. Devising a flexible and reliable theoretical m

Zhifang Li, Xiaojie Chen, Han-Xin Yang, Attila Szolnoki

Opinion dynamics on social networks have been received considerable attentions in recent years. Nevertheless, just a few works have theoretically analyzed the condition in which a certain opinion can spread in the whole structured population. In this paper, we propose an evolutionary game approach for a binary opinion model to explore the conditions for an o

Bing-Dong Wan, Cong-Feng Qiao

In this work, we investigate the spectra of the prospective tetracharm and tetrabottom baryonium, viz. the baryon-antibaryon states, in the framework of QCD sum rules. The non-perturbative contributions up to dimension 10 are taken into account. Numerical results indicate that there might exist 4 possible tetracharm baryonium states with masses $(7.33\pm0.12

Surajit Basak, Przemysław Piekarz, Andrzej Ptok

$A$B$_{2}$ ($A=$K, Rb, Cs) compounds crystallize in the cubic Laves phase (symmetry Fd$\bar{3}$m). The geometry of the crystal structure allows the realization of chiral phonons, which are associated with the circulation of atoms around their equilibrium positions. Due to the inversion symmetry and time reversal symmetry, total pseudo-angular momentum (PAM)

Mehrdad Nasernejad, Ayesha Asloob Qureshi

In this paper, we unfold balanced and totally balanced neighborhood hypergraphs to discover new classes of normally torsion-free monomial ideals. As a consequence, we establish that the closed neighborhood ideals and the dominating ideals of strongly chordal graphs are normally torsion-free. We discuss the stable sets of associated primes of the dominating i

Woon-Ha Yeo, Wang-Taek Oh, Kyung-Su Kang, Young-Il Kim

Image restoration is an important and challenging task in computer vision. Reverting a filtered image to its original image is helpful in various computer vision tasks. We employ a nonlinear activation function free network (NAFNet) for a fast and lightweight model and add a color attention module that extracts useful color information for better accuracy. W

Hongzhi Hua, Guixuan Wen, Kaigui Wu

The research of extending deep reinforcement learning (drl) to multi-agent field has solved many complicated problems and made great achievements. However, almost all these studies only focus on discrete or continuous action space and there are few works having ever used multi-agent deep reinforcement learning to real-world environment problems which mostly

Sándor Kunsági-Máté, Gábor Fáth, István Csabai, Gábor Molnár-Sáska

Recent studies have demonstrated the efficiency of Variational Autoencoders (VAE) to compress high-dimensional implied volatility surfaces into a low dimensional representation. Although this method can be effectively used for pricing vanilla options, it does not provide any explicit information about the dynamics of the underlying asset. In our work we pres

Ajay Vishwanath, Einar Duenger Bøhn, Ole-Christoffer Granmo, Charl Maree

Machine ethics has received increasing attention over the past few years because of the need to ensure safe and reliable artificial intelligence (AI). The two dominantly used theories in machine ethics are deontological and utilitarian ethics. Virtue ethics, on the other hand, has often been mentioned as an alternative ethical theory. While this interesting

Leandro S. M. Cardoso, Jean Michel Gomes, Polychronis Papaderos, Ciro Pappalardo

Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions into the main luminosity contributors (e.g. stellar populations or ionised gas). However, the impact nebular emission has on the inferred properties of star-forming (SF) galaxies has been largely overlooked over the ye

Matthew J Tudball, George Davey Smith, Qingyuan Zhao

Mendelian randomization (MR) is a natural experimental design based on the random transmission of genes from parents to offspring. However, this inferential basis is typically only implicit or used as an informal justification. As parent-offspring data becomes more widely available, we advocate a different approach to MR that is exactly based on this natural

Hanya Pan, Tingyu Gou, Rui Liu

A well-known precursor of an imminent solar eruption is the appearance of a hot S-shaped loop, also known as sigmoid, in an active region (AR). Classically, the formation of such an S-shaped loop is envisaged to be implemented by magnetic reconnection of two oppositely oriented J-shaped loops. However, the details of reconnection are elusive due to weak emis

Jun-Sik Sin

In this paper, we study electrostatic and structural properties between pH-responsive polyelectrolyte brushes by using a strong stretching theory accounting for excluded volume interactions, the density of polyelectrolyte chargeable sites and the Born energy difference between the inside and outside of the brush layer. In a free energy framework, we obtain s

Yury Kochetkov

A Latin square of order $n$ with symbols $a_1,\ldots,a_n$ can be considered as a multiplication table for binary operation in the set $A=\{a_1,\ldots,a_n\}$. We prove that, if this operation is associative, then $A$ is a group.

So Matsuura, Kazutoshi Ohta

In this paper, we consider an extended Kazakov-Migdal model defined on an arbitrary graph. The partition function of the model, which is expressed as the summation of all Wilson loops on the graph, turns out to be represented by the Bartholdi zeta function weighted by unitary matrices on the edges of the graph. The partition function on the cycle graph at fi

Davide Fioravanti, Daniele Gregori, Hongfei Shu

We show that previous correspondence between some (integrable) statistical field theory quantities and periods of $SU(2)$ $\mathcal{N}=2$ deformed gauge theory still holds if we add $N_f=1,2$ flavours of matter. Moreover, the correspondence entails a new non-perturbative solution to the theory. Eventually, we use this solution to give exact results on quasin

Luca Frittoli, Diego Carrera, Giacomo Boracchi

We address the problem of online change detection in multivariate datastreams, and we introduce QuantTree Exponentially Weighted Moving Average (QT-EWMA), a nonparametric change-detection algorithm that can control the expected time before a false alarm, yielding a desired Average Run Length (ARL$_0$). Controlling false alarms is crucial in many applications

Xiang Liu, Hongyuan Wang, Zhiqiang Yan, Yu Chen

Perceiving the three-dimensional (3D) structure of the spacecraft is a prerequisite for successfully executing many on-orbit space missions, and it can provide critical input for many downstream vision algorithms. In this paper, we propose to sense the 3D structure of spacecraft using light detection and ranging sensor (LIDAR) and a monocular camera. To this

Vadim Bobylev, Anisa Bajkova

We have studied the kinematics of Galactic masers and radio stars with measured VLBI trigonometric parallaxes and proper motions. We have considered masers with relative trigonometric parallax errors less than 10\% and determined the Galactic rotation parameters from them. In particular, the linear rotation velocity of the Galaxy at the solar distance $R_0$

Bohuan Lin, Jian Gao

We discuss a specific circumstance in which the topology of the communication network of a robotic swarm has to change during the movement. The variation is caused by a topological obstruction which emerges from certain geometric restrictions on both the environment and the swarm.

Shuai Ma, Yunqi Zhang, Haihong Sheng, Hang Li

In this paper, we investigate the optimal probabilistic constellation shaping design for covert communication systems from a practical view. Different from conventional covert communications with equiprobable constellations modulation, we propose nonequiprobable constellations modulation schemes to further enhance the covert rate. Specifically, we derive cov

S. Rosswog, O. Korobkin

Compact binary mergers involving neutron stars can eject a fraction of their mass to space. Being extremely neutron rich, this material undergoes rapid neutron capture nucleosynthesis, and the resulting radioactivity powers fast, short-lived electromagnetic transients known as kilonova or macronova. Such transients are exciting probes of the most extreme phy

Xiong Yao, Alessandro R. Mazza, Myung-Geun Han, Hee Taek Yi

Epitaxial Fe(Te,Se) thin films have been grown on various substrates but never been realized on magnetic layers. Here we report the epitaxial growth of four-fold Fe(Te,Se) film on a six-fold antiferromagnetic insulator, MnTe. The Fe(Te,Se)/MnTe heterostructure shows a clear superconducting transition at around 11 K and the critical magnetic field measurement

Robert Schmier, Ullrich Köthe, Christoph-Nikolas Straehle

Detecting test data deviating from training data is a central problem for safe and robust machine learning. Likelihoods learned by a generative model, e.g., a normalizing flow via standard log-likelihood training, perform poorly as an outlier score. We propose to use an unlabelled auxiliary dataset and a probabilistic outlier score for outlier detection. We

Edward Vendrow, Satyajit Kumar, Ehsan Adeli, Hamid Rezatofighi

Human pose forecasting is a challenging problem involving complex human body motion and posture dynamics. In cases that there are multiple people in the environment, one's motion may also be influenced by the motion and dynamic movements of others. Although there are several previous works targeting the problem of multi-person dynamic pose forecasting, they

Ruizhou Liu, Qiang Ma, Zhiwei Cheng, Yuanyuan Lyu

Fluoroscopy is an imaging technique that uses X-ray to obtain a real-time 2D video of the interior of a 3D object, helping surgeons to observe pathological structures and tissue functions especially during intervention. However, it suffers from heavy noise that mainly arises from the clinical use of a low dose X-ray, thereby necessitating the technology of f

M. E. Tunalioglu, H. O. Cildiroglu, A. U. Yilmazer

Correlation relations for the spin measurements on a pair of entangled particles scattered by the two separate arms of interferometers in hybrid setups of different types are investigated. Concurrence, entanglement of formation, quantum fidelity, Bures distance are used to clarify how the geometric phase affects the initial bipartite state. This affect cause

P. Bergamini, C. Grillo, P. Rosati, E. Vanzella

The combination of multi-band imaging from HST with MUSE integral field spectroscopy, obtained at the VLT, has recently driven remarkable progress in strong lensing (SL) modeling of galaxy clusters. From a few tens of multiple images with photometric redshifts per cluster, a new generation of high-precision SL models have recently been developed, by exploiti

Rui Wang, Chao Ding

In this paper, we propose a Robbins-Monro augmented Lagrangian method (RMALM) to solve a class of constrained stochastic convex optimization, which can be regarded as a hybrid of the Robbins-Monro type stochastic approximation method and the augmented Lagrangian method of convex optimizations. Under mild conditions, we show that the proposed algorithm exhibi

Peter Huston, Fiona Burnell, Corey Jones, David Penneys

Topological domain walls separating 2+1 dimensional topologically ordered phases can be understood in terms of Witt equivalences between the UMTCs describing anyons in the bulk topological orders. However, this picture does not provide a framework for decomposing stacks of multiple domain walls into superselection sectors - i.e., into fundamental domain wall

Tom Sprunck, Yannick Privat, Cédric Foy, Antoine Deleforge

Given a sound field generated by a sparse distribution of impulse image sources, can the continuous 3D positions and amplitudes of these sources be recovered from discrete, bandlimited measurements of the field at a finite set of locations, e.g., a multichannel room impulse response? Borrowing from recent advances in super-resolution imaging, it is shown tha

S. V. Bolokhov, K. A. Bronnikov, M. V. Skvortsova

We consider the gravity assist maneuver, that is, a correction of spacecraft motion at its passing near a planet, as a tool for evaluating the Eddington post-Newtonian parameters $\beta$ and $\gamma$, characterizing vacuum spherically symmetric gravitation fields in metric theories of gravity. We estimate the effect of variation in $\beta$ and $\gamma$ on a

Lucia Clarotto, Denis Allard, Thomas Romary, Nicolas Desassis

In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest. Large space-time datasets call for new numerical methods to efficiently process them. The Stochastic Partial Differential

Nicolas Vanspranghe, Francesco Ferrante, Christophe Prieur

This paper deals with a one-dimensional wave equation with a nonlinear dynamic boundary condition and a Neumann-type boundary control acting on the other extremity. We consider a class of nonlinear stabilizing feedbacks that only depend on the velocity at the controlled extremity. The uncontrolled boundary is subject to a nonlinear first-order term, which ma

S. P. Järvinen, S. Hubrig, R. Jayaraman, I. Ilyin

Previous observations suggested that Ap and Bp stars exhibit a bimodal distribution of surface magnetic field strengths and that actually only few or no stars exist with magnetic dipole field strengths below 300 G down to a few Gauss. As the number of Ap and Bp stars currently known to possess weak magnetic fields is not large, it is necessary to carry out a

François Renaville, Fabienne Prosmans, Isabelle Gilles

LibStaffer is a staff scheduling tool for libraries provided by Springshare. In this article, we present the analysis that we implemented to determine the potential of LibStaffer in order to simplify staff scheduling in library branches with various configurations, as well as in transversal units with a focus on public services. As a starting point, we focus

Hadi Ghasemi, Tayebe Lal Shateri

The paper is devoted to continuous frames and Riesz bases in Hilbert C*-modules. we define a continuous Riesz basis for Hilbert C*-modules and give some results about them.

Arijit Pyne, Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu

In real life, we frequently come across data sets that involve some independent explanatory variable(s) generating a set of ordinal responses. These ordinal responses may correspond to an underlying continuous latent variable, which is linearly related to the covariate(s), and takes a particular (ordinal) label depending on whether this latent variable takes

Jun-Sik Sin, Il-Chon Choe, Chol-Song Im

In this paper, we study the electrostatics of pH-responsive polyelectrolyte-grafted spherical particles by using a strong stretching theory that takes into account the excluded volume interaction and the density of chargeable sites on the polyelectrolyte molecules. Based on the free energy formalism, we obtain self-consistent field equations for determining

Arnab Bhattacharjee, Angshuman Bhattacharya

In this article we study analogues of the weak expectation property of discrete group C*-algebras and their crossed products, in the discrete quantum group setting, i.e., discrete quantum group C*-algebras and crossed products of C*-algebras with amenable discrete quantum groups.

S. Di, Y. Yang

As an alcoholic beverage, wine has remained prevalent for thousands of years, and the quality assessment of wines has been significant in wine production and trade. Scholars have proposed various deep learning and machine learning algorithms for wine quality prediction, such as Support vector machine (SVM), Random Forest (RF), K-nearest neighbors (KNN), Deep

Yuan Yue, Dirk De Ridder, Patrick Manning, Samantha Ross

Obesity is a serious issue in the modern society and is often associated to significantly reduced quality of life. Current research conducted to explore obesity-related neurological evidences using electroencephalography (EEG) data are limited to traditional approaches. In this study, we developed a novel machine learning model to identify brain networks of

Niharika Bhootna, Arun Kumar

In this article, we introduce a Gegenbauer autoregressive tempered fractionally integrated moving average (GARTFIMA) process. We work on the spectral density and autocovariance function for the introduced process. The parameter estimation is done using the empirical spectral density with the help of the nonlinear least square technique and the Whittle likeli

Max Tory, Evgeni Grishin, Ilya Mandel

The three-body problem is famously chaotic, with no closed-form analytical solutions. However, hierarchical systems of three or more bodies can be stable over indefinite timescales. A system is considered hierarchical if the bodies can be divided into separate two-body orbits with distinct time- and length-scales, such that one orbit is only mildly affected

Bitao Wang

Environment plays a critical role in the star formation history of galaxies. Tidal and hydrodynamical stripping, prominent in cluster environment, can remove the peripheral gas of galaxies and star formation may thus be environmentally suppressed from the outside-in. We revisit the environmental dependence of the radial gradient of specific star formation ra

Masoud Mokhtari, Teresa Tsang, Purang Abolmaesumi, Renjie Liao

Ejection fraction (EF) is a key indicator of cardiac function, allowing identification of patients prone to heart dysfunctions such as heart failure. EF is estimated from cardiac ultrasound videos known as echocardiograms (echo) by manually tracing the left ventricle and estimating its volume on certain frames. These estimations exhibit high inter-observer v

Kenny Kiriu, Jason Kumar, Jack Runburg

We consider the angular distribution of the photon signal which could arise from velocity-dependent dark matter annihilation within the Galactic bulge. We find that, for the case of Sommerfeld-enhanced annihilation, dark matter annihilation within the bulge is dominated by slow speed particles which never leave the bulge, allowing one to find a simple analyt

Hao Wang, Yangguang Li, Zhen Huang, Yong Dou

With the rapid development of automatic fake news detection technology, fact extraction and verification (FEVER) has been attracting more attention. The task aims to extract the most related fact evidences from millions of open-domain Wikipedia documents and then verify the credibility of corresponding claims. Although several strong models have been propose

Tomona Kinugawa, Tetsuo Hyodo

The compositeness $X$ is defined as the probability to observe the composite structure such as the hadronic molecule component in a bound state. One of the model-independent approaches to calculate $X$ is the weak-binding relation. However, when the scattering length $a_{0}$ is larger than the radius of the bound state $R$, the central value of the composite

Matteo Califano, Ivan de Martino, Daniele Vernieri, Salvatore Capozziello

We probe four cosmological models which, potentially, can solve the Hubble tension according to the dark energy equation of state. In this context, we demonstrate that the Einstein Telescope is capable of achieving a relative accuracy below $1\%$ on the Hubble constant independently of the specific dark energy model. We firstly build mock catalogs containing

Mikhail I. Gomoyunov

In this paper, a finite-horizon optimal control problem involving a dynamical system described by a linear Caputo fractional differential equation and a quadratic cost functional is considered. An explicit formula for the value functional is given, which includes a solution of a certain Fredholm integral equation. A step-by-step feedback control procedure fo

Nikhel Gupta, Minh Huynh, Ray P. Norris, Rosalind Wang

We present a set of peculiar radio sources detected using an unsupervised machine learning method. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope to train a self-organizing map (SOM). The radio maps from three ASKAP surveys, Evolutionary Map of Universe pilot survey (EMU-PS), Deep Investigation of Neutral Gas Origins pilo

Ram Krishna Patra, Sahil Gopalkrishna Naik, Edwin Peter Lobo, Samrat Sen

Principle of information causality, proposed as a generalization of no signaling principle, has efficiently been applied to outcast beyond quantum correlations as unphysical. In this letter we show that this principle when utilized properly can provide physical rationale towards structural derivation of multipartite quantum systems. In accordance with no sig

Wanfang Chen, Changhong Lu, Long-Tu Yuan

The Erd\H{o}s-Simonovits stability theorem is one of the most widely used theorems in extremal graph theory. We obtain an Erd\H{o}s-Simonovits type stability theorem in multi-partite graphs. Different from the Erd\H{o}s-Simonovits stability theorem, our stability theorem in multi-partite graphs says that if the number of edges of an $H$-free graph $G$ is clo

Weimin Zhu, Yi Zhang, DuanCheng Zhao, Jianrong Xu

Elucidating and accurately predicting the druggability and bioactivities of molecules plays a pivotal role in drug design and discovery and remains an open challenge. Recently, graph neural networks (GNN) have made remarkable advancements in graph-based molecular property prediction. However, current graph-based deep learning methods neglect the hierarchical

Shivam Tyagi, Shubham Yadav, Vaibhav Wani, Shivam Singh

Tin Selenide (SnSe) thin films were grown onto glass and alumina substrates by Chemical Vapor Deposition (CVD) method. The structural, micro-structural and morphological characterizations of the as grown thin films were investigated using XRD, SEM and Raman spectroscopy which reveals that the films on glass are phase pure oriented SnSe while those on Alumina

Jianfeng Chen, Sha Liu, Yong Wang, Congshan Zhuo

The rarefied flow and multi-scale flow are crucial for the aerodynamic design of spacecraft, ultra-low orbital vehicles and plumes. By introducing a discrete velocity space, the discrete velocity method (DVM) and unified methods can capture complex and non-equilibrium distribution functions and describe flow behaviors exactly. The unified methods predict flo

Xiao Luo, Yoshinobu Kuramashi

We apply the tensor renormalization group method to the (1+1)-dimensional SU(2) principal chiral model at finite chemical potential with the use of the Gauss-Legendre quadrature to discretize the SU(2) Lie group. The internal energy at vanishing chemical potential $\mu=0$ shows good consistency with the prediction of the strong and weak coupling expansions.

Daniel Alpay, Palle Jorgensen, Izchak Lewkowicz

We present a general setting where wavelet filters and multiresolution decompositions can be defined, beyond the classical $\mathbf L^2(\mathbb R,dx)$ setting. This is done in a framework of {\em iterated function system} (IFS) measures; these include all cases studied so far, and in particular the Julia set/measure cases. Every IFS has a fixed order, say $N

M. Kirchbach, J. A. Vallejo

We construct the integral transform passing from the space representation to the momentum representation for the Hydrogen atom using polar spherical coordinates. The resulting radial wave functions are explicitly given in terms of complex finite expansions of Gegenbauer functions of the first and second kind, or in terms of (elementary) trigonometric functio

Shu-Guang Wu, Yang Zhang

Applying functional differentiation to the density field with Newtonian gravity, we obtain the static, nonlinear equation of the three-point correlation function $\zeta$ of galaxies, to the third order density perturbations. We make the equation closed and perform renormalization of the mass and the Jeans wavenumber. Using the boundary condition inferred fro

Yuri Sato, Kaori Obayashi, B. Theodre Zhang, Shuta J. Tanaka

Gamma-ray bursts (GRBs) are intense bursts of high-energy photons (prompt emissions) caused by relativistic jets. After the emissions, multi-wavelength afterglows, from radio to very-high-energy (VHE) gamma-ray, last for more than a few days. In the past three years, the VHE gamma-ray photons from four GRBs (GRBs 180720B, 190114C, 190829A and 201216C) were d

Jiangbo Pei, Zhuqing Jiang, Aidong Men, Liang Chen

Source-free unsupervised domain adaptation (SFUDA) aims to learn a target domain model using unlabeled target data and the knowledge of a well-trained source domain model. Most previous SFUDA works focus on inferring semantics of target data based on the source knowledge. Without measuring the transferability of the source knowledge, these methods insufficie

Rohail Asim, Muhammad Khan, Luis Diez, Shiva Iyer

As global cellular networks converge to 5G, one question lingers: Are we ready for the 5G challenge? A growing concern surrounds how well do existing congestion control algorithms perform in diverse 5G networks. Given that 5G networks are not yet widely deployed, assessing the performance of existing congestion control algorithms in realistic 5G settings pre

Juan Martinez-Sykora, Viggo H. Hansteen, Bart De Pontieu, Enrico Landi

The magnetic field governs the corona; hence it is a crucial parameter to measure. Unfortunately, existing techniques for estimating its strength are limited by strong assumptions and limitations. These techniques include photospheric or chromospheric field extrapolation using potential or non-linear-force-free methods, estimates based on coronal seismology,