August 2022 arXiv papers — page 116

Masaaki Harada

New $s$-extremal extremal unimodular lattices in dimensions $38$, $40$, $42$ and $44$ are constructed from self-dual codes over $\mathbb{F}_5$ by Construction A. In the process of constructing these codes, we obtain a self-dual $[44,22,14]$ code over $\mathbb{F}_5$. In addition, the code implies a $[43,22,13]$ code over $\mathbb{F}_5$. These codes have large

Shuang Gao, Peter E. Caines

This work connects models for virus spread on networks with their equivalent neural network representations. Based on this connection, we propose a new neural network architecture, called Transmission Neural Networks (TransNNs) where activation functions are primarily associated with links and are allowed to have different activation levels. Furthermore, thi

B. G. Palm, F. M. Bayer, R. J. Cintra

Two-dimensional (2-D) autoregressive moving average (ARMA) models are commonly applied to describe real-world image data, usually assuming Gaussian or symmetric noise. However, real-world data often present non-Gaussian signals, with asymmetrical distributions and strictly positive values. In particular, SAR images are known to be well characterized by the R

Aryeh Brill

Blazars exhibit stochastic flux variability across the electromagnetic spectrum, often exhibiting heavy-tailed flux distributions, commonly modeled as lognormal. However, Tavecchio et al. (2020) and Adams et al. (2022) found that the high-energy gamma-ray flux distributions of several of the brightest flaring Fermi-LAT flat spectrum radio quasars (FSRQs) are

Michael Maihöfer, Johannes Reiff, Jörg Main, Rigoberto Hernandez

Understanding the magnetization switching process in ferromagnetic thin films is essential for many technological applications. We investigate the effects of periodic driving via magnetic fields on a macrospin system under explicit consideration of inertial dynamics. This is usually achieved by extending the Landau-Lifshitz-Gilbert equation with a term inclu

Changfeng Gui, Qinfeng Li

In this paper, we prove that if $u$ is a solution to the Liouville equation \begin{align} \label{scalliouville} \Delta u+e^{2u} =0 \quad \mbox{in $\mathbb{R}^2$,} \end{align}then the diameter of $\mathbb{R}^2$ under the conformal metric $g=e^{2u}\delta$ is bounded below by $\pi$. Here $\delta$ is the Euclidean metric in $\mathbb{R}^2$. Moreover, we explicitl

B. G. Palm, F. M. Bayer, R. J. Cintra

The Rayleigh regression model was recently proposed for modeling amplitude values of synthetic aperture radar (SAR) image pixels. However, inferences from such model are based on the maximum likelihood estimators, which can be biased for small signal lengths. The Rayleigh regression model for SAR images often takes into account small pixel windows, which may

Zikui Cai, Chengyu Song, Srikanth Krishnamurthy, Amit Roy-Chowdhury

Blackbox adversarial attacks can be categorized into transfer- and query-based attacks. Transfer methods do not require any feedback from the victim model, but provide lower success rates compared to query-based methods. Query attacks often require a large number of queries for success. To achieve the best of both approaches, recent efforts have tried to com

Veena Kaustaban, Qinle Ba, Ipshita Bhattacharya, Nahil Sobh

Recent years have seen great advancements in the development of deep learning models for histopathology image analysis in digital pathology applications, evidenced by the increasingly common deployment of these models in both research and clinical settings. Although such models have shown unprecedented performance in solving fundamental computational tasks i

Quan Zheng, Ziwei Wang, Jie Zhou, Jiwen Lu

Explaining deep convolutional neural networks has been recently drawing increasing attention since it helps to understand the networks' internal operations and why they make certain decisions. Saliency maps, which emphasize salient regions largely connected to the network's decision-making, are one of the most common ways for visualizing and analyzing deep n

George Grispos, William R. Mahoney

Maritime shipping has become a trillion-dollar industry that now impacts the economy of virtually every country around the world. It is therefore no surprise that countries and companies have spent billions of dollars to modernize shipping vessels and ports with various technologies. However, the implementation of these technologies has also caught the atten

Gábor Czédli

Slim semimodular lattices (for short, SPS lattices) and slim rectangular lattices (for short, SR lattices) were introduced by G. Gr\"atzer and E. Knapp in 2007 and 2009. These lattices are necessarily finite and planar, and they have been studied in more then four dozen papers since 2007. They are best understood with the help of their $\mathcal C_1$-diagram

Ramchander Rao Bhaskara, Kookjin Sung, Manoranjan Majji

Interferometric Vision-Based Navigation (iVisNav) is a novel optoelectronic sensor for autonomous proximity operations. iVisNav employs laser emitting structured beacons and precisely characterizes six degrees of freedom relative motion rates by measuring changes in the phase of the transmitted laser pulses. iVisNav's embedded package must efficiently proces

Suman Satyal, Billy Quarles, Marialis Rosario-Franco

All 4 giant planets in the Solar System host systems of multiple moons, whereas the terrestrial planets only host up to 2 moons. The Earth can capture small asteroids as temporary satellites, which begs the question as to how many moons could stably orbit the Earth, or an Earth-mass exoplanet. We perform a series of N-body simulations of closely-spaced equal

Leonid A. Bunimovich, Yaofeng Su

We prove a maximal-type large deviation principle for dynamical systems with arbitrarily slow polynomial mixing rates. Also several applications, particularly to billiard systems, are presented.

Tan Gan

I study the optimal pricing process for selling a unit good to a buyer with prospect theory preferences. In the presence of probability weighting, the buyer is dynamically inconsistent and can be either sophisticated or naive about her own inconsistency. If the buyer is naive, the uniquely optimal mechanism is to sell a ``loot box'' that delivers the good wi

Romakanta Bhattarai, Kai Ni, Xiao Shen

The first two-dimensional (2D) polymorphs of antimony dioxide, namely, $\gamma$-Sb$_2$O$_4$ and $\delta$-Sb$_2$O$_4$, are predicted using the evolutionary algorithm combined with first-principles density functional theory (DFT) calculations. Out-of-plane ferroelectricity is found in $\gamma$-Sb$_2$O$_4$, while in-plane ferroelectricity is found in $\delta$-S

Teo Banica

This is an introduction to the algebras $A\subset B(H)$ that the linear operators $T:H\to H$ can form, once a complex Hilbert space $H$ is given. Motivated by quantum mechanics, we are mainly interested in the von Neumann algebras, which are stable under taking adjoints, $T\to T^*$, and are weakly closed. When the algebra has a trace $tr:A\to\mathbb C$, we c

Hui Hu, Jia Wang, Xia-Ji Liu

We present a microscopic many-body theory of the recently measured two-dimensional coherent spectroscopy (2DCS) of excitons and trions in monolayer MoSe$_{2}$ materials {[}K. Hao \textit{et al.}, Nano Lett. \textbf{16}, 5109 (2016){]}, where excitons and trions can be well interpreted as repulsive and attractive polarons, respectively, in the dilute limit of

Samuel Herschenfeld, Peter D. Hislop

We use the method of eigenvalue level spacing developed by Dietlein and Elgart (arXiv:1712.03925) to prove that the local eigenvalue statistics (LES) for the Anderson model on $Z^d$, with uniform higher-rank $m \geq 2$, single-site perturbations, is given by a Poisson point process with intensity measure $n(E_0)~ds$, where $n(E_0)$ is the density of states a

Paige Bright, Shengwen Gan

We prove two conjectures in this paper. The first conjecture is by Lund, Pham and Thu: Given a Borel set $A\subset \mathbb{R}^n$ such that $\dim A\in (k,k+1]$ for some $k\in\{1,\dots,n-1\}$. For $0<s<k$, we have \[ \text{dim}(\{y\in \mathbb{R}^n \setminus A\mid \text{dim} (\pi_y(A)) < s\})\leq \max\{k+s -\dim A,0\}. \] The second conjecture is by Liu: Given

Ralf Wehlitz, David L. Huber

The low energy resonance in the double photoionization of the aromatic hydrocarbons pyrene (C$_{16}$H$_{10}$) and coronene (C$_{24}$H$_{12}$) is investigated theoretically using an approach based on the one-dimension Hubbard model for $\pi$-conjugated systems with nearest-neighbor interactions. The Independent Subsystem Approximation, where the perimeter and

Tadahiro Miyao, Hayato Tominaga

The periodic Anderson model (PAM) is a fundamental model describing heavy fermion systems. In this paper, we examine the PAM with electron-phonon interactions. Introducing a new analytical method based on operator inequalities, we prove that the ground state at half-filling is unique and a singlet. We also prove that the ground state exhibits short-range ant

Lizhe Wan

We consider the $L^2$ well-posedness of third order Benjamin-Ono equation. We show that by means of a normal form and a gauge transformation, the equation can be changed into an Airy-type equation. A second goal of this work is to establish that the solutions to the nonlinear third order Benjamin-Ono equation problem exhibit a dispersive decay estimate analo

Md Umar Hashmi

In September 2018 EirGrid launched the new electricity market. These new market arrangements integrate the all island electricity market with European electricity markets, making optimal use of cross border transmission assets. Ireland operates three operational HVDC interconnectors: Moyle, East-West, and Greenlink and one in development Celtic interconnecto

Yipeng Peng, Rigelesaiyin Ji, Thanh Phan, Laurent Capolungo

In this paper, we perform concurrent atomistic-continuum (CAC) simulations to (i) characterize the internal stress induced by the microscale dislocation pileup at an atomically structured interface; (ii) decompose this stress into two parts, one of which is from the dislocations behind the pileup tip according to the Eshelby model and the other is from the d

Andrea Addazi, Salvatore Capozziello, Qingyu Gan, Antonino Marcianò

We show that the neutrino mass, the dark matter and the dark energy can be explained in a unified framework, postulating a new invisible Born-Infeld field, which we name "non-linear dark photon", undergoing a meV-scale dynamical transmutation and coupled to neutrinos. Dark energy genesis is dynamically explained as a byproduct of the dark photon condensation

Tomasz Klimsiak, Maurycy Rzymowski

We study Backward Stochastic Differential Equations on a probability space equipped with a Brownian filtration. We assume that the terminal value and the generator at zero are merely integrable. Moreover, the generator is assumed to be non-increasing with respect to the value variable (with no restrictions on the growth) and Lipschitz continuous, with sublin

Yongchun Li, Marcia Fampa, Jon Lee, Feng Qiu

We study the D-optimal Data Fusion (DDF) problem, which aims to select new data points, given an existing Fisher information matrix, so as to maximize the logarithm of the determinant of the overall Fisher information matrix. We show that the DDF problem is NP-hard and has no constant-factor polynomial-time approximation algorithm unless P $=$ NP. Therefore,

Chen Shen, Nicola Peserico, Jiawei Meng, Xiaoxuan Ma

Solving mathematical equations faster and more efficiently has been a Holy Grail for centuries for scientists and engineers across all disciplines. While electronic digital circuits have revolutionized equation solving in recent decades, it has become apparent that performance gains from brute-force approaches of compute-solvers are quickly saturating over t

Arthur Stephanovitch, Anqi Dong, Tryphon T. Georgiou

We address the problem of optimal transport with a quadratic cost functional and a constraint on the flux through a constriction along the path. The constriction, conceptually represented by a toll station, limits the flow rate across. We provide a precise formulation which, in addition, is amenable to generalization in higher dimensions. We work out in deta

Nadezhda Mukhaleva, Valentin Grigorev, George Chernishev

A window function is a generalization of the aggregation operation. Unlike aggregation, the cardinality of its output is always the same as the cardinality of input. That is, the semantics of this operator imply computing values for extra attributes for each row, depending on its context, either expressed by a sliding window or a previously evaluated row. Wi

Yuriko Baba, Mario Amado, Enrique Diez, Francisco Domínguez-Adame

A quantum anomalous Hall state with high Chern number has so far been realized in multiplayer structures consisting of alternating magnetic and undoped topological insulator layers. However, in previous proposals, the Chern number can be only tuned by varying the doping concentration or the width of the magnetic topological insulator layers. This drawback la

Ali Ahmad Malik

The thrust for increased rating capacity of wind turbines has resulted into larger generators, longer blades, and taller towers. Presently, up to 16 MW wind turbines are being offered by wind turbines manufacturers which is nearly a 60 percent increase in the design capacity over the last five years. Manufacturing of these turbines involves assembling of gig

Liang Li, She-Sheng Xue, Zi-Gao Dai

Despite decades of polarization observations and high-significance polarized $\gamma$-ray, X-ray, optical, and radio emissions in gamma-ray bursts (GRBs) have been accumulating in dozens of cases, people have yet to find a consistent scenario for understanding the globally observed timing properties of GRB polarization to date. Here, we report that the obser

Emre Arslan, Fatih Kilinc, Sultangali Arzykulov, Ali Tugberk Dogukan

Innovative reconfigurable intelligent surface (RIS) technologies are rising and recognized as promising candidates to enhance 6G and beyond wireless communication systems. RISs acquire the ability to manipulate electromagnetic signals, thus, offering a degree of control over the wireless channel and the potential for many more benefits. Furthermore, active R

Christiaan G. A. Viviers, Mark Ramaekers, Peter H. N. de With, Dimitrios Mavroeidis

Pancreatic cancer is one of the global leading causes of cancer-related deaths. Despite the success of Deep Learning in computer-aided diagnosis and detection (CAD) methods, little attention has been paid to the detection of Pancreatic Cancer. We propose a method for detecting pancreatic tumor that utilizes clinically-relevant features in the surrounding ana

David Schaich

Supersymmetry plays prominent roles in the study of quantum field theory and in many proposals for potential new physics beyond the standard model. Lattice field theory provides a non-perturbative regularization suitable for strongly interacting systems. This invited review briefly summarizes significant recent progress in lattice investigations of supersymm

Marek Balcerzak, Tomasz Kania

Let $\mathcal C$ be a concrete category. We prove that if $\mathcal{C}$ admits a universally free object $\mathsf F$, then there is a projectively universal morphism $u\colon \mathsf F\to \mathsf F$, i.e., a morphism $u$ such that for any $B\in \mathcal{C}$ and $\tau\in {\rm Mor}(B)$ there exists an epimorphism $\pi\in {\rm Mor}(\mathsf F, B)$ such that $\pi

Juanwu Lu, Wei Zhan, Masayoshi Tomizuka, Yeping Hu

Trajectory prediction is one of the essential tasks for autonomous vehicles. Recent progress in machine learning gave birth to a series of advanced trajectory prediction algorithms. Lately, the effectiveness of using graph neural networks (GNNs) with vectorized representations for trajectory prediction has been demonstrated by many researchers. Nonetheless,

Claudio Gorodski

These are the notes for a series of lectures at the Institute of Geometry and Topology of the University of Stuttgart, Germany, in July 13-15, 2022. We assume basic knowledge of isometric actions on Riemannian manifolds, including the normal slice theorem and the principal orbit type theorem. Lecture 1 introduces polar actions and culminates with Heintze, Li

Ashwin Tunga, Kexin Li, Nicholas C. Miller, Matt Grupen

Various simulations of a GaN HEMT are used to study the behaviors of two different energy-transport models: the Fermi kinetics transport model and a hydrodynamics transport model as it is implemented in the device simulator Sentaurus from Synopsys. The electron transport and heat flow equations of the respective solvers are described in detail. The differenc

Jamerson Bezerra, Pedro Duarte

We prove that if $\mu$ is a finitely supported measure on $\text{SL}_2(\mathbb{R})$ with positive Lyapunov exponent but not uniformly hyperbolic, then the Lyapunov exponent function is not $\alpha$-H\"older around $\mu$ for any $\alpha$ exceeding the Shannon entropy of $\mu$ over the Lyapunov exponent of $\mu$.

Andreas Bartel, Michael Günther, Birgit Jacob, Timo Reis

A dynamic iteration scheme for linear differential-algebraic port-Hamil\-tonian systems based on Lions-Mercier-type operator splitting methods is developed. The dynamic iteration is monotone in the sense that the error is decreasing and no stability conditions are required. The developed iteration scheme is even new for linear port-Hamiltonian systems. The o

Ralph Morrison, Lucas Tolley

In the theory of divisors on multigraphs, the $r^{th}$ divisorial gonality of a graph is the minimum degree of a rank $r$ divisor on that graph. It was proved by Gijswijt et al. that the first divisorial gonality of a finite graph is NP-hard to compute. We generalize their argument to prove that it is NP-hard to compute the $r^{th}$ divisorial gonality of a

Donato Bini, Stuart Kauffman, Sauro Succi, Pablo G. Tello

We compute the metric fluctuations induced by a turbulent energy-matter tensor within the first order Post-Minkowskian approximation. It is found that the turbulent energy cascade can in principle interfere with the process of black hole formation, leading to a potentially strong coupling between these two highly nonlinear phenomena. It is further found that

Athena Psalta, Vasileios Tsironis, Konstantinos Karantzalos

Data association is a crucial component for any multiple object tracking (MOT) method that follows the tracking-by-detection paradigm. To generate complete trajectories such methods employ a data association process to establish assignments between detections and existing targets during each timestep. Recent data association approaches try to solve either a

Haim Nakav, Ran Finkelstein, Lee Peleg, Nitzan Akerman

High fidelity single and multi-qubit operations compose the backbone of quantum information processing. This fidelity is based on the ability to couple single- or two-qubit levels in an extremely coherent and precise manner. A necessary condition for coherent quantum evolution is a highly stable local oscillator driving these transitions. Here we study the e

Vaanathi Sundaresan, Julia F. Lehman, Sean Fitzgibbon, Saad Jbabdi

Anatomic tracing data provides detailed information on brain circuitry essential for addressing some of the common errors in diffusion MRI tractography. However, automated detection of fiber bundles on tracing data is challenging due to sectioning distortions, presence of noise and artifacts and intensity/contrast variations. In this work, we propose a deep

F. Martín-Fernández, C. Caballero-Gil, P. Caballero-Gil, J. Molina-Gil

A vehicular ad-hoc network is a type of communication network where the nodes are vehicles. Their aim is to manage traffic efficiently in order to prevent unwanted events such as accidents, jams, etc. The research on this type of networks assumes the use of additional infrastructure installed on the roads, and special devices installed in vehicles. In this p

Kara Karpman, Sumanta Basu, David Easley

Financial networks are typically estimated by applying standard time series analyses to price-based economic variables collected at low-frequency (e.g., daily or monthly stock returns or realized volatility). These networks are used for risk monitoring and for studying information flows in financial markets. High-frequency intraday trade data sets may provid

Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini

Proof-of-Learning (PoL) proposes that a model owner logs training checkpoints to establish a proof of having expended the computation necessary for training. The authors of PoL forego cryptographic approaches and trade rigorous security guarantees for scalability to deep learning. They empirically argued the benefit of this approach by showing how spoofing--

Sèdjro Salomon Hotegni, Ernest Fokoué

Fatal diseases, as Critical Health Episodes (CHEs), represent real dangers for patients hospitalized in Intensive Care Units. These episodes can lead to irreversible organ damage and death. Nevertheless, diagnosing them in time would greatly reduce their inconvenience. This study therefore focused on building a highly effective early warning system for CHEs

Amparo Fúster-Sabater, Pino Caballero-Gil

The application of a nonlinear filtering function to a Linear Feedback Shift Register (LFSR) is a general technique for designing pseudorandom sequence generators with cryptographic application. In this paper, we investigate the equivalence between different nonlinear filtering functions applied to distinct LFSRs. It is a well known fact that given a binary

David Macêdo

Current deep learning solutions are well known for not informing whether they can reliably classify an example during inference. One of the most effective ways to build more reliable deep learning solutions is to improve their performance in the so-called out-of-distribution detection task, which essentially consists of "know that you do not know" or "know t

Debjani Goswami, Merim Dzaferagic, Harun Siljak, Suvra Sekhar Das

The evolution of fifth generation (5G) networks needs to support the latest use cases, which demand robust network connectivity for the collaborative performance of the network agents, like multi-robot systems and vehicle to anything (V2X) communication. Unfortunately, the user device's limited communication range and battery constraint confirm the unfitness

Daniel Levy, Avichai Snir

Recent studies in psychology and neuroscience offer systematic evidence that fictional works exert a surprisingly strong influence on readers and have the power to shape their opinions and worldviews. Building on these findings, we study what we term Potterian economics, the economic ideas, insights, and structure, found in Harry Potter books, to assess how

Pino Caballero-Gil, Francisco Martín-Fernández, Cándido Caballero-Gil

Revocation of dishonest users is not an easy problem. This paper proposes a new way to manage revocation of pseudonyms in vehicular ad-hoc networks when using identity-based authentication to increase efficiency and security through certificateless authentication. In order to improve the performance of revocation lists, this paper proposes the use of a data

Zeshun Zong, Xuan Li, Jianping Ye, Sian Wen

Contact-aware topology optimization faces challenges in robustness, accuracy, and applicability to internal structural surfaces under self-contact. This work builds on the recently proposed barrier-based Incremental Potential Contact (IPC) model and presents a new self-contact-aware topology optimization framework. A combination of SIMP, adjoint sensitivity

Xiao Liu, Spyridon Thermos, Pedro Sanchez, Alison Q. O'Neil

Learning disentangled representations requires either supervision or the introduction of specific model designs and learning constraints as biases. InfoGAN is a popular disentanglement framework that learns unsupervised disentangled representations by maximising the mutual information between latent representations and their corresponding generated images. M

Eman Yahia, Kannan Premnath

Convergence acceleration of flow simulations to their steady states at lower Mach numbers can be achieved via preconditioning the lattice Boltzmann (LB) schemes that alleviate the associated numerical stiffness, which have so far been constructed on square lattices. We present a new central moment LB method on rectangular lattice grids for efficient computat

Qiaomu Miao, Sinhwa Kang, Stacy Marsella, Steve DiPaola

There is strong interest in the generation of synthetic video imagery of people talking for various purposes, including entertainment, communication, training, and advertisement. With the development of deep fake generation models, synthetic video imagery will soon be visually indistinguishable to the naked eye from a naturally capture video. In addition, ma

Basma B. Hasanen, Mohammad I. Awad, Mohamed N. Boushaki, Zhenwei Niu

Loss of upper extremity motor control and function is an unremitting symptom in post-stroke patients. This would impose hardships on accomplishing their daily life activities. Supernumerary robotic limbs (SRLs) were introduced as a solution to regain the lost Degrees of Freedom (DoFs) by introducing an independent new limb. The actuation systems in SRL can b

Md. Khaledur Rahman, Ariful Azad

Graph Neural Networks (GNNs) are widely used to perform different machine learning tasks on graphs. As the size of the graphs grows, and the GNNs get deeper, training and inference time become costly in addition to the memory requirement. Thus, without sacrificing accuracy, graph sparsification, or model compression becomes a viable approach for graph learni

Rishav Pramanik, Sourodip Sarkar, Ram Sarkar

Pneumonia is one of the major reasons for child mortality especially in income-deprived regions of the world. Although it can be detected and treated with very less sophisticated instruments and medication, Pneumonia detection still remains a major concern in developing countries. Computer-aided based diagnosis (CAD) systems can be used in such countries due

Tushima Basak, Tista Basak, Alok Shukla

This work demonstrates the unique approach of introducing divacancy imperfections in topological Stone-Wales type defected graphene quantum dots for harvesting both singlet and triplet excitons, essential for fabricating fluorescent organic light-emitting diodes. Here, we first reveal that structural relaxation of these systems establishes the high-spin trip

Yu-Hsien Chiang, Kyle Frohna, Hayden Salway, Anna Abfalterer

Tandem perovskite solar cells beckon as lower cost alternatives to conventional single junction solar cells, with all-perovskite tandem photovoltaic architectures showing power conversion efficiencies up to 26.4%. Solution-processing approaches for the perovskite layers have enabled rapid 2optimization of perovskite solar technologies, but new deposition rou

Haruka Kogure, Taishi Kurahashi

We investigate modal logical aspects of provability predicates $\mathrm{Pr}_T(x)$ satisfying the following condition: $\mathbf{M}$: If $T \vdash \varphi \to \psi$, then $T \vdash \mathrm{Pr}_T(\ulcorner \varphi \urcorner) \to \mathrm{Pr}_T(\ulcorner \psi \urcorner)$. We prove the arithmetical completeness theorems for monotonic modal logics $\mathsf{MN}$, $\

Belle II Collaboration, F. Abudinén, I. Adachi, K. Adamczyk

We present a measurement of the branching fraction and longitudinal polarization of $B^0 \to \rho^+ \rho^-$ decays. SuperKEKB electron-positron collision data corresponding to 189~fb$^{-1}$ of integrated luminosity and containing $198 \times 10^6 B\bar{B}$ pairs collected with the Belle II detector are used. We obtain \begin{eqnarray*} \mathcal{B}(B^0\to\rho

Taishi Kurahashi

We prove that the provability logic of all provability predicates is exactly Fitting, Marek, and Truszczy\'nski's pure logic of necessitation $\mathsf{N}$. Moreover, we introduce three extensions $\mathsf{N4}$, $\mathsf{NR}$, and $\mathsf{NR4}$ of $\mathsf{N}$ and investigate the arithmetical semantics of these logics. In fact, we prove that $\mathsf{N4}$, $

Lingzhi Zhang, Connelly Barnes, Kevin Wampler, Sohrab Amirghodsi

Recently, deep models have established SOTA performance for low-resolution image inpainting, but they lack fidelity at resolutions associated with modern cameras such as 4K or more, and for large holes. We contribute an inpainting benchmark dataset of photos at 4K and above representative of modern sensors. We demonstrate a novel framework that combines deep

Pino Caballero-Gil, Cándido Caballero-Gil, Jezabel Molina-Gil

Continuous advances of Information Technologies (ITs), and in particular of the RFID technologies that allow the connection between the physical world objects and the IT infrastructure, have guaranteed the improvement and efficiency of industrial technologies in the last decades. This paper includes the proposal of two new schemes for RFID. On the one hand,

Byron Tasseff, Russell Bent, Carleton Coffrin, Clayton Barrows

The classic pump scheduling or Optimal Water Flow (OWF) problem for water distribution networks (WDNs) minimizes the cost of power consumption for a given WDN over a fixed time horizon. In its exact form, the OWF is a computationally challenging mixed-integer nonlinear program (MINLP). It is complicated by nonlinear equality constraints that model network ph

Ziyi Lin, Shijie Geng, Renrui Zhang, Peng Gao

Video recognition has been dominated by the end-to-end learning paradigm -- first initializing a video recognition model with weights of a pretrained image model and then conducting end-to-end training on videos. This enables the video network to benefit from the pretrained image model. However, this requires substantial computation and memory resources for

Szu-Pei Fu, Rolf Ryham, Bryan Quaife, Y. -N. Young

Active colloidal systems with non-equilibrium self-organization is a long-standing, challenging area in biology. To understand how hydrodynamic flow may be used to actively control self-assembly of Janus particles (JPs), we use a model recently developed for the many-body hydrodynamics of amphiphilic JPs suspended in a viscous background flow (JFM, 941, 2022

MC Hernández-Goya, Pino Caballero-Gil

Currently, special attention is being paid to scenarios where the interconnection of devices with heterogeneous computational and communication capabilities it is required. It is essential to integrate security services during the stages of design and deployment of these networks since many of these scenarios provide critical services such as medical health,

Hasnaa Hajji, Morad El Baz

Semi-quantum key distribution is traditionally based on two-level quantum systems. In this paper, an unconditional security of a semi quantum key distribution protocol based on higher-dimensional systems using various mutually unbiased bases is presented. We first consider the three dimensional case using three and four mutually unbiased bases and derive a l

M. Hunza, M. Asjad, T. Abbas, M. Qasymeh

We consider a hybrid atom-optomechanical system incorporating N identical $\Lambda$-type atoms. The system is subjected to dual optical and phononic drives. We show that by exploiting the optomechanical linear and quadratic interactions, multiple electromagnetic transparency windows are attained. Furthermore, owing to the incorporated mechanical pump, the tr

Jamil Chaker, Luis Silvestre

We prove a bound on the entropy dissipation for the Boltzmann collision operator from below by a weighted $L^p$-Norm. The estimate holds for a wide range of potentials including soft potentials as well as very soft potentials. As an application, we study weak solutions to the spatially homogeneous Boltzmann equation and prove a weighted $L^1_t(L^p_v)$ estima

Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen, Linh T. Le

Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical classification tasks. However, only a few studies addressed the localization of abnormal findings from CXR scans, which is essential in explaining the image-level classification to radiologists. We introduce in this paper an explainable deep learning

Milad Jangjan, Luis E. F. Foa Torres, Mir Vahid Hosseini

We report on the theoretical investigation of the topological properties of a periodically quenched one-dimensional dimerized lattice where a piece-wise constant Hamiltonian switches from $h_1$ to $h_2$ at a partition time $t_p$ within each driving period $T$. We examine different dimerization patterns for $h_1$ and $h_2$ and the interplay with the driving p

Chaoqiang Zhao, Youmin Zhang, Matteo Poggi, Fabio Tosi

Self-supervised monocular depth estimation is an attractive solution that does not require hard-to-source depth labels for training. Convolutional neural networks (CNNs) have recently achieved great success in this task. However, their limited receptive field constrains existing network architectures to reason only locally, dampening the effectiveness of the

Anupam Ghosh

In this paper, we study the applicability of an early warning index while studying the transitions to complete and generalized synchronizations in the coupled oscillator models using an unconventional system parameter and the coupling strength as the required control parameters. The coupled oscillator models are widely used and well-documented for studying v

Michael Philip Sitte, Nguyen Anh Khoa Doan

Pool fires are canonical representations of many accidental fires, which can exhibit an unstable unsteady behaviour, known as puffing, which involves a strong coupling between the temperature and velocity fields. Despite their practical relevance to fire research, their experimental study can be limited due to the complexity of measuring relevant quantities

V Mora-Afonso, Pino Caballero-Gil, Jezabel Molina-Gil

The rapid deployment of wireless technologies has given rise to the current situation where mobile phones and other wireless devices have become essential elements in all types of activities, including in the home. In particular, smartphones and laptops are used for wirelessly sharing photos and documents, playing games, browsing websites, and viewing multim

Swadesh Pal, Roderick Melnik

Alzheimer's disease (AD) is a common neurodegenerative disorder nowadays. Amyloid-beta (A$\beta$) and tau proteins are among the main contributors to the development or propagation of AD. In AD, A$\beta$ proteins clump together to form plaques and disrupt cell functions. On the other hand, the abnormal chemical change in the brain helps to build sticky tau t

Hélder Lima

The main objects of the investigation presented in this paper are branched-continued-fraction representations of ratios of contiguous hypergeometric series and type II multiple orthogonal polynomials on the step-line with respect to linear functionals or measures whose moments are ratios of products of Pochhammer symbols. This is an interesting case study of

Bruno Régaldo-Saint Blancard, Erwan Allys, Constant Auclair, François Boulanger

The quest for primordial $B$-modes in the cosmic microwave background has emphasized the need for refined models of the Galactic dust foreground. Here, we aim at building a realistic statistical model of the multi-frequency dust emission from a single example. We introduce a generic methodology relying on microcanonical gradient descent models conditioned by

Saverio E. Spagnolie, Patrick T. Underhill

We review the literature on swimming in complex fluids. A classification is proposed by comparing the length and time scales of a swimmer with those of nearby obstacles, interpreted broadly, extending from rigid or soft confining boundaries to molecules which confer the bulk fluid with complex stresses. A third dimension in the classification is the concentr

Fithanegest Kassa Dagnew, Nat Gopalswamy, Solomon Belay Tessema, Sachiko Akiyama

The culmination of solar cycle 24 by the end of 2019 has created the opportunity to compare the differing properties of coronal mass ejections (CMEs) between two whole solar cycles: Solar cycle 23 (SC 23) and Solar cycle 24 (SC 24). We report on the width evolution of limb CMEs in SC 23 and 24 in order to test the suggestion by Gopalswamy et al. (2015a) that

Justin Dombecki, James Golding, Mitchell Pleune, Nicholas Paul

We were able to complete the full integration of the Robotic Technology Kernel (RTK) into an electric vehicle by-wire system using lidar and GPS sensors. The solution included a mobile application to interface with the RTK-enabled autonomous vehicle. Altogether the system was designed to be modular, using the concepts of message-based software design that is

Guanzhou Wei, Xiao Liu, Russell Barton

A class of physics-informed spatio-temporal models has recently been proposed for modeling spatio-temporal processes governed by advection-diffusion equations. The central idea is to approximate the process by a truncated Fourier series and let the governing physics determine the dynamics of the spectral coefficients. However, because many spatio-temporal pr

Fabio Siringo, Giorgio Comitini

One-loop explicit expressions are derived for the gluon Nielsen identity in the formalism of the screened massive expansion for Yang-Mills theory. The gauge-parameter-independence of the poles and residues is discussed in a strict perturbative context and, more generally, in extended resummation schemes. No exact formal proof was reached by the approximate r

Swadesh Pal, Roderick Melnik, Malay Banerjee

Pattern formation is a visual understanding of the dynamics of complex systems. Patterns arise in many ways, such as the segmentation of animals, bacterial colonies during growth, vegetation, chemical reactions, etc. In most cases, the long-range diffusion occurs, and the usual reaction-diffusion (RD) model can not capture such phenomena. The nonlocal RD mod

Meysam Shahrbaf Motlagh, Subhajit Majhi, Patrick Mitran, Hideki Ochiai

We consider the downlink of a multi-cell massive MIMO system suffering from asymptotic rate saturation due to pilot contamination. As opposed to treating pilot contamination interference as noise (TIN), we study the performance of decoding the pilot contamination interference. We model pilot-sharing users as an interference channel (IC) and study the perform

Satyam Srivastav, Milan Sil, Prasanta Gorai, Amit Pathak

Straight-chain (normal-propyl cyanide, n - C3H7CN) and branched-chain (iso-propyl cyanide, i - C3H7CN) alkyl cyanides are recently identified in the massive star-forming regions (Sgr B2(N) and Orion). These branched-chain molecules indicate that the key amino acids (side-chain structures) may also be present in a similar region. The process by which this bra

Akash Kumar Saha, Priyank Parashari, Tarak Nath Maity, Abhishek Dubey

Recent observation of Sagittarius A$^*$ (Sgr A$^*$) by the Event Horizon Telescope (EHT) collaboration has uncovered various unanswered questions in black hole (BH) physics. Besides, it may also probe various beyond the Standard Model (BSM) scenarios. One of the most profound possibilities is the search for ultralight bosons (ULBs) using BH superradiance (SR

Siddharth H. Nair, Eric H. Tseng, Francesco Borrelli

We propose a Model Predictive Control (MPC) for collision avoidance between an autonomous agent and dynamic obstacles with uncertain predictions. The collision avoidance constraints are imposed by enforcing positive distance between convex sets representing the agent and the obstacles, and tractably reformulating them using Lagrange duality. This approach al

Zitai Chen, Sam L. Thomas, Flavio D. Garcia

In this paper we present MetaEmu, an architecture-agnostic emulator synthesizer geared towards rehosting and security analysis of automotive firmware. MetaEmu improves over existing rehosting environments in two ways: Firstly, it solves the hitherto open-problem of a lack of generic Virtual Execution Environments (VXEs) for rehosting by synthesizing processo

Shrawan Kumar

Following some work of Aluffi-Mihalcea-Sch\"{u}rmann-Su for the CSM classes of Schubert cells and some elaborate computer calculations by R. Rimanyi and L. Mihalcea, I conjecture that the CSM classes of the Richardson cells expressed in the Schubert basis have nonnegative coefficients. This conjecture was principally motivated by a new product $\square$ comi