November 2022 arXiv papers — page 121

Yufeng Lu

We establish the sharp conditions for the embedding between Wiener amalgam spaces $W_{p,q}^s$ and some classical spaces, including Sobolev spaces $L^{s,r}$, local Hardy spaces $h_{r}$, Besov spaces $B_{p,q}^s$, which partially improve and extend the main result obtained by Guo et al. in J. Funct. Anal., 273(1):404-443, 2017. In addition, we give the full cha

Mehrnaz Sabet, Praveen Palanisamy, Sakshi Mishra

One major barrier to advancing aerial autonomy has been collecting large-scale aerial datasets for training machine learning models. Due to costly and time-consuming real-world data collection through deploying drones, there has been an increasing shift towards using synthetic data for training models in drone applications. However, to increase widespread ge

Yi-Zhi Huang, Christopher Sadowski

Given a weight-one element $u$ of a vertex operator algebra $V$, we construct an automorphism of the category of generalized $g$-twisted modules for automorphisms $g$ of $V$ fixing $u$. We apply this construction to the case that $V$ is an affine vertex operator algebra to obtain explicit results on these automorphisms of categories. In particular, we give e

Vanessa Polito, Graham S. Kerr, Yan Xu, Viacheslav M. Sadykov

Lower atmospheric lines show peculiar profiles at the leading edge of ribbons during solar flares. In particular, increased absorption of the BBSO/GST \hei~10830~\AA\ line \citep[e.g.][]{Xu2016}, as well as broad and centrally reversed profiles in the spectra of the \mgii~and \cii~lines observed by the \iris~satellite \citep[e.g.][]{Panos2018,Panos2021a} hav

Gaoxiao Jiang, Zhihong You, Rui Ma, Chen-Xu Wu

In nature, active matter, such as worms or dogs, tend to spontaneously form a stable rotational cluster when they flock to the same food source on an unregulated and unconfined surface. {In this paper we present an $n$-node flexible active matter model to study the collective motion due to the flocking of individual agents on a two-dimensional surface, and c

L. Gehrig, T. Steindl, E. I. Vorobyov, R. Guadarrama

The effects of an accretion disk are crucial to understanding the evolution of young stars. During the combined evolution, stellar and disk parameters influence each other, motivating a combined stellar and disk model. This makes a combined numerical model, evolving the disk alongside the star, the next logical step in the progress of studying early stellar

Debasish Das

A strongly interacting Quark-Gluon Plasma (sQGP) is created in the high energy heavy ion collisions at RHIC and LHC. Our present understanding of sQGP as a very good liquid with astonishingly low viscosity is reviewed. With the arrival of the interesting results from LHC in high-energy p+p and p+A, a new endeavour to characterize the transition from these sm

Yufeng Lu

We study the Cauchy problem for the generalized KdV and one-dimensional fourth-order derivative nonlinear Schr\"odinger equations, for which the global well-posedness of solutions with the small rough data in certain scaling limit of modulation spaces is shown, which contain some data with infinite $L^{2}$ norm.

Kaidong Peng, Rick Poore, Philip Krantz, David E. Root

We present an efficient, accurate, and comprehensive analysis framework for generic, multi-port nonlinear parametric circuits, in the presence of dissipation from lossy circuit components, based on "quantum-adapted" X-parameters. We apply this method to Josephson traveling-wave parametric amplifiers (JTWPAs) - a key component in superconducting and spin qubi

Ronny Ko, Chuan Xiao, Makoto Onizuka, Yihe Huang

Existing what-if analysis systems are predominantly tailored to operate on either only the application layer or only the database layer of software. This isolated approach limits their effectiveness in scenarios where intensive interaction between applications and database systems occurs. To address this gap, we introduce Ultraverse, a what-if analysis frame

Declan S. Jagt, Matthew M. Peet

Partial Integral Equations (PIEs) have been used to represent both systems with delay and systems of Partial Differential Equations (PDEs) in one or two spatial dimensions. In this paper, we show that these results can be combined to obtain a PIE representation of any suitably well-posed 1D PDE model with constant delay. In particular, we represent these del

Michael J. Bremner, Zhengfeng Ji, Xingjian Li, Luke Mathieson

We study a parameterized version of the local Hamiltonian problem, called the weighted local Hamiltonian problem, where the relevant quantum states are superpositions of computational basis states of Hamming weight $k$. The Hamming weight constraint can have a physical interpretation as a constraint on the number of excitations allowed or particle number in

Naichung Conan Leung, Dan Wang

Let $(M, \omega, J)$ be a K\"ahler manifold, equipped with an effective Hamiltonian torus action $\rho: T \rightarrow \mathrm{Diff}(M, \omega, J)$ by isometries with moment map $\mu: M \rightarrow \mathfrak{t}^{*}$. We first construct a singular mixed polarization $\mathcal{P}_{\mathrm{mix}}$ on $M$. Second, we construct a one-parameter family of complex str

Fan Zhang, Weiwei Gao, Greis J. Cruz, Yi-yang Sun

Using first-principles GW plus Bethe-Salpeter equation calculations, we identify anomalously strong excitonic effects in several vacancy-ordered double perovskites Cs2MX6 (M = Ti, Zr; X = I, Br). Giant exciton binding energies about 1 eV are found in these moderate-gap, inorganic bulk semiconductors, pushing the limit of our understanding of electron-hole (e

Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li

We study a novel and important communication pattern in large-scale model-parallel deep learning (DL), which we call cross-mesh resharding. This pattern emerges when the two paradigms of model parallelism - intra-operator and inter-operator parallelism - are combined to support large models on large clusters. In cross-mesh resharding, a sharded tensor needs

Vien Ngoc Dang, Anna Cascarano, Rosa H. Mulder, Charlotte Cecil

A significant level of stigma and inequality exists in mental healthcare, especially in under-served populations. Inequalities are reflected in the data collected for scientific purposes. When not properly accounted for, machine learning (ML) models leart from data can reinforce these structural inequalities or biases. Here, we present a systematic study of

Peter Olamide Olanipekun, Yann Bernard

A four dimensional conformally invariant energy is studied. This energy generalises the well known two-dimensional Willmore energy. Although not positive definite, it includes minimal hypersurfaces as critical points. We compute its first variation and by applying the Noether theorem to the invariances, we derive some conservation laws which are satisfied by

Ning Ding, Yulin Chen, Ganqu Cui, Xiaobin Wang

Metric-based meta-learning is one of the de facto standards in few-shot learning. It composes of representation learning and metrics calculation designs. Previous works construct class representations in different ways, varying from mean output embedding to covariance and distributions. However, using embeddings in space lacks expressivity and cannot capture

Joseph Feneuil, Linhan Li, Svitlana Mayboroda

In the present paper, we show that for an optimal class of elliptic operators with non-smooth coefficients on a 1-sided Chord-Arc domain, the boundary of the domain is uniformly rectifiable if and only if the Green function $G$ behaves like a distance function to the boundary, in the sense that $\Big|\frac{\nabla G(X)}{G(X)}-\frac{\nabla D(X)}{D(X)}\Big|^2D(

Ashley M. Cook, Joel E. Moore

Symmetry-protected topological phases of matter have challenged our understanding of condensed matter systems and harbour exotic phenomena promising to address major technological challenges. Considerable understanding of these phases of matter has been gained recently by considering additional protecting symmetries, different types of quasiparticles, and sy

Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy, Jennifer Merickel

The current paper implements a methodology for automatically detecting vehicle maneuvers from vehicle telemetry data under naturalistic driving settings. Previous approaches have treated vehicle maneuver detection as a classification problem, although both time series segmentation and classification are required since input telemetry data is continuous. Our

Mikhail Zhitlukhin

We propose a multi-agent model of an asset market and study conditions that guarantee that the strategy of an individual agent cannot outperform the market. The model assumes a mean-field approximation of the market by considering an infinite number of infinitesimal agents who use the same strategy and another infinitesimal agent with a different strategy wh

Jun Okabayashi, Kazuya Z. Suzuki, Shigemi Mizukami

The magnetic atom diffusion at the interface between CoMn alloy and MnGa layer with annealing is studied using x-ray magnetic circular dichroism (XMCD) analysis. We found that the spins in bcc CoMn are coupled parallel to those in perpendicularly magnetized MnGa layer under the as-grown conditions, while the post-annealing modulates the interfacial magnetic

Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe

Selecting subsets of features that differentiate between two conditions is a key task in a broad range of scientific domains. In many applications, the features of interest form clusters with similar effects on the data at hand. To recover such clusters we develop DiSC, a data-driven approach for detecting groups of features that differentiate between condit

C. A. Holliman, M. Fan, A. M. Jayich

Optical clocks are the apotheosis of precision measurement, but they require frequent maintenance by scientists. The supporting laser systems are a particularly demanding component of these instruments. To reduce complexity and increase robustness we propose an optical clock with trapped alkali-like ions that use the $S_{1/2}\rightarrow D_{3/2}$ electric qua

Tomotsugu Wakasa, Shingo Tagami, Masanobu Yahiro

The PREX and the CREX group reported their skin values. Using the Love-Franey (LF) $t$-matrix folding model with the neutron and proton densities scaled to the neutron radius $r_{\rm n}^{208}({\rm PREX2})$ and the proton radius of the electron scattering, we found that the model reproduces $\sigma_R$ for p+ $^{208}$Pb scattering at $E_{\rm lab} = 534.1, 549,

Andrea Zanette

Model-free algorithms for reinforcement learning typically require a condition called Bellman completeness in order to successfully operate off-policy with function approximation, unless additional conditions are met. However, Bellman completeness is a requirement that is much stronger than realizability and that is deemed to be too strong to hold in practic

Zilai Li, Hao Liu, Huaqiao Wang

We consider the two-phase flow model with slip boundary condition in a 3D exterior domains whose boundary is smooth. We establish the global existence of classical solutions of this system provided that the initial energy is suitably small. Moreover, the pressure has large oscillations and contains vacuum states when the initial pressure allows large oscilla

Zhidong Tang, Zewei Wang, Yumeng Yuan, Chang He

This paper outlines the establishment of a generic cryogenic CMOS database in which key electrical parameters and transfer characteristics of the MOSFETs are quantified as functions of device size, temperature/frequency responses. Meanwhile, comprehensive device statistical study is conducted to evaluate the influence of variation and mismatch effects at low

Chi-en Amy Tai, Hayden Gunraj, Nedim Hodzic, Nic Flanagan

Breast cancer is the second most common type of cancer in women in Canada and the United States, representing over 25\% of all new female cancer cases. As such, there has been immense research and progress on improving screening and clinical support for breast cancer. In this paper, we investigate enhancing clinical support for breast cancer with deep learni

Tesshu Hanaka, Hironori Kiya, Hirotaka Ono, Kanae Yoshiwatari

Cram, Domineering, and Arc Kayles are well-studied combinatorial games. They are interpreted as edge-selecting-type games on graphs, and the selected edges during a game form a matching. In this paper, we define a generalized game called Colored Arc Kayles, which includes these games. Colored Arc Kayles is played on a graph whose edges are colored in black,

Hiroki Matsui, Shinji Mukohyama, Atsushi Naruko

In minisuperspace quantum cosmology, the Lorentzian path integral formulations of the no-boundary and tunneling proposals have recently been analyzed. But it has been pointed out that the wave function of linearized perturbations around a homogeneous and isotropic background is of an inverse Gaussian form and thus that their correlation functions are diverge

Jazmín Aragón Sánchez, María Lourdes Amigó, Cristian Horacio Belussi, María Victoria Ale Crivillero

The electronic properties of Fe-based superconductors are drastically affected by deformations on their crystal structure introduced by doping and pressure. Here we study single crystals of FeSe$_{1-x}$S$_{x}$ and reveal that local crystal deformations such as atomic-scale defects impact the spectral shape of the electronic core level states of the material.

Nico Lingg, Miguel Sarabia, Luca Zappella, Barry-John Theobald

Human skeleton point clouds are commonly used to automatically classify and predict the behaviour of others. In this paper, we use a contrastive self-supervised learning method, SimCLR, to learn representations that capture the semantics of skeleton point clouds. This work focuses on systematically evaluating the effects that different algorithmic decisions

Toshihiro Nishimura, Yosuke Suzuki, Tokuo Tsuji, Tetsuyou Watanabe

This study proposed a novel robotic gripper that can achieve grasping and infinite wrist twisting motions using a single actuator. The gripper is equipped with a differential gear mechanism that allows switching between the grasping and twisting motions according to the magnitude of the tip force applied to the finger. The grasping motion is activated when t

Yueqiang Zhu, Kaige Wang, Jintao Bai, Wei Zhao

The crucial zeroth-order light due to the pixelation effect of spatial light modulator (SLM) has been a serious issue in the field of light modulation, especially in applications with a high numerical aperture optical system. In this investigation, we report that by properly adjusting the high-level and low-level pixel voltages of an SLM, the zeroth-order li

Karthik Venkataramani, Scott M. Bailey, Srimoyee Samaddar, Justin Yonker

The Atmospheric Chemistry and Energetics (ACE) 1D model is a first principles based model that generates a globally averaged thermosphere and ionosphere in terms of constituent major, minor, and charged species, as well as associated temperatures. The model solves the 1D continuity and energy equations representing relevant physical processes, and is support

Run-Hong He, Xu-Sheng Xu, Mark S. Byrd, Zhao-Ming Wang

Any quantum program on a realistic quantum device must be compiled into an executable form while taking into account the underlying hardware constraints. Stringent restrictions on architecture and control imposed by physical platforms make this very challenging. In this paper, based on the quantum variational algorithm, we propose a novel scheme to train an

Yifan Liu, Youbao Tang, Ning Zhang, Ruei-Sung Lin

Temporal action localization (TAL) aims to detect the boundary and identify the class of each action instance in a long untrimmed video. Current approaches treat video frames homogeneously, and tend to give background and key objects excessive attention. This limits their sensitivity to localize action boundaries. To this end, we propose a prior-enhanced tem

Changying Ding, Srivatsav Kunnawalkam Elayavalli

Using computations in the bidual of $\mathbb{B}(L^2M)$ we develop a new technique at the von Neumann algebra level to upgrade relative proper proximality to full proper proximality. This is used to structurally classify subalgebras of $L\Gamma$ where $\Gamma$ is an infinite group that is biexact relative to a finite family of subgroups $\{\Lambda_i\}_{i\in I

Jiawei Zhang, Shen Li, Li Li

Connected and automated vehicles (CAVs) are viewed as a special kind of robots that have the potential to significantly improve the safety and efficiency of traffic. In contrast to many swarm robotics studies that are demonstrated in labs by employing a small number of robots, CAV studies aims to achieve cooperative driving of unceasing robot swarm flows. Ho

Tingyu Wang, Zhedong Zheng, Zunjie Zhu, Yuhan Gao

Cross-view geo-localization aims to spot images of the same location shot from two platforms, e.g., the drone platform and the satellite platform. Existing methods usually focus on optimizing the distance between one embedding with others in the feature space, while neglecting the redundancy of the embedding itself. In this paper, we argue that the low redun

Jianye Yi, Xiaopin Zhong, Weixiang Liu, Zongze Wu

The continuous development of the photovoltaic (PV) industry has raised high requirements for the quality of monocrystalline of PV module cells. When learning to segment defect regions in PV module cell images, Tiny Hidden Cracks (THC) lead to extremely-imbalanced samples. The ratio of defect pixels to normal pixels can be as low as 1:2000. This extreme imba

Yao Li, Caleb Meredith

Stochastic differential equations play an important role in various applications when modeling systems that have either random perturbations or chaotic dynamics at faster time scales. The time evolution of the probability distribution of a stochastic differential equation is described by the Fokker-Planck equation, which is a second order parabolic partial d

Xiaoyu Chen, Shaofeng H. -C. Jiang, Robert Krauthgamer

Max-Cut is a fundamental problem that has been studied extensively in various settings. We design an algorithm for Euclidean Max-Cut, where the input is a set of points in $\mathbb{R}^d$, in the model of dynamic geometric streams, where the input $X\subseteq [\Delta]^d$ is presented as a sequence of point insertions and deletions. Previously, Frahling and So

Xuerao He, Zhihao Sun, Mengqi Zhang

We study numerically a sequence of eddies in two-dimensional electrohydrodynamic (EHD) flows of a dielectric liquid, driven by an electric potential difference between a hyperbolic blade electrode and a flat plate electrode (or the blade-plate configuration). The electrically-driven flow impinges on the plate to generate vortices, which resemble Moffatt eddi

Ying Hu, Xiaomin Shi, Zuo Quan Xu

This paper studies finite-time optimal consumption-investment problems with power, logarithmic and exponential utilities, in a regime switching market with random coefficients, subject to coupled constraints on the consumption and investment strategies. We provide explicit optimal consumption-investment strategies and optimal values for the problems in terms

Peilin Zhou, Jingqi Gao, Yueqi Xie, Qichen Ye

Contrastive learning (CL) benefits the training of sequential recommendation models with informative self-supervision signals. Existing solutions apply general sequential data augmentation strategies to generate positive pairs and encourage their representations to be invariant. However, due to the inherent properties of user behavior sequences, some augment

Canyu Chen, Haoran Wang, Matthew Shapiro, Yunyu Xiao

Social media has been one of the main information consumption sources for the public, allowing people to seek and spread information more quickly and easily. However, the rise of various social media platforms also enables the proliferation of online misinformation. In particular, misinformation in the health domain has significant impacts on our society suc

Ahmed Medhat, Shankar Iyer

The friendship paradox implies that a person will, on average, have fewer friends than their friends do. Prior work has shown how the friendship paradox can lead to perception biases regarding behaviors that correlate with the number of friends: for example, people tend to perceive their friends as being more socially engaged than they are. Here, we investig

Hongning Wang, Xuning Zhang, Selina Zhang, Michelle Chen

Let $G$ be a finite group and $\chi\in \irr(G)$. The codegree of $\chi$ is defined as $\cod(\chi)=\frac{|G:\ker(\chi)|}{\chi(1)}$ and $\cod(G)=\{\cod(\chi) \ |\ \chi\in \irr(G)\}$ is called the set of codegrees of $G$. In this paper, we show that the set of codegrees of $\Sy_4(4), \U_4(2)$, $\Sy_4(q)\ (q \geq 4)$, $\U_4(3)$, ${}^2\F_4(2)'$, $\J_3$, $\G_2(3)$

Ya-long Ren, Sheng-li Ma, Fu-li Li

Chiral coupling at the single-quantum level promises to be a remarkable potential for quantum information processing. Here we propose to achieve a chiral interaction between a magnon mode in a ferromagnetic sphere and a superconducting qubit mediated by a one-dimensional coupled-cavity array. When the qubit is coupled to two lattice sites of the array and ea

Yijia Shao, Mengyu Zhou, Yifan Zhong, Tao Wu

Online forms are widely used to collect data from human and have a multi-billion market. Many software products provide online services for creating semi-structured forms where questions and descriptions are organized by pre-defined structures. However, the design and creation process of forms is still tedious and requires expert knowledge. To assist form de

Chen Xinghao, Ding Xu, Cheng Liantao, Zhang Xiaobin

Based on 2-minute cadence TESS data from sectors 1-50, we report the results of the systematic extraction of $\delta$ Scuti-type pulsations in the 6431 eclipsing binaries with orbital periods shorter than 13 days. A total number of 242 pulsators were found in those systems, including 143 new discoveries. We examined their pulsation properties based on the H-

Kevin Lin

In the setting of global geometric Langlands, we show that miraculous duality on the stack of principal bundles on a curve intertwines the functor of Poincare series with the dual functor to Whittaker coefficients. We construct, for arbitrary parabolic subgroups, Jacquet functors controlling constant terms of Poincare series and Whittaker coefficients of Eis

Hadley Black, Deeparnab Chakrabarty, C. Seshadhri

The problem of testing monotonicity for Boolean functions on the hypergrid, $f:[n]^d \to \{0,1\}$ is a classic topic in property testing. When $n=2$, the domain is the hypercube. For the hypercube case, a breakthrough result of Khot-Minzer-Safra (FOCS 2015) gave a non-adaptive, one-sided tester making $\widetilde{O}(\varepsilon^{-2}\sqrt{d})$ queries. Up to

Aaron Pollack

Quaternionic modular forms on the split exceptional group $G_2 = G_2^s$ were defined by Gan-Gross-Savin. A remarkable property of these automorphic functions is that they have a robust notion of Fourier expansion and Fourier coefficients, similar to the classical holomorphic modular forms on Shimura varieties. In this paper we prove that in even weight $\ell

Daciberg Lima Gonçalves, Jesús González

For finite connected graphs $\Gamma$ and $G$, with $\Gamma$ admitting a free involution $\tau$, we characterize the based homotopy classes $\alpha\in[\Gamma,G]$ for which the Borsuk-Ulam property holds in the sense of Gon\c{c}alves, Guaschi and Casteluber-Laass, i.e., the homotopy classes $\alpha$ so that each of its representatives $f\in\alpha$ satisfies $f

Praveen Kumar

Users may already have some perception of provided security based on experience with earlier generations. To maintain the stability and coherent integration of 5G services, it is imperative that security and privacy features prevalent in earlier generations are also present in 5G. However, it is not sufficient just to provide the same security features as in

Peng Meng, Yaze Wu, Renji Bian, Er Pan

When the atomic layers in a non-centrosymmetric van der Waals structure slide against each other, the interfacial charge transfer results in a reversal of the structures spontaneous polarization. This phenomenon is known as sliding ferroelectricity and it is markedly different from conventional ferroelectric switching mechanisms relying on ion displacement.

Shurui Li, Hangbo Yang, Chee Wei Wong, Volker J. Sorger

The last few years have seen a lot of work to address the challenge of low-latency and high-throughput convolutional neural network inference. Integrated photonics has the potential to dramatically accelerate neural networks because of its low-latency nature. Combined with the concept of Joint Transform Correlator (JTC), the computationally expensive convolu

Ray S. Sharma, Alyson M. Brooks, Michael Tremmel, Jillian Bellovary

We examine the quenching characteristics of $328$ isolated dwarf galaxies $\left(10^{8} < M_{\rm star}/M_\odot < 10^{10} \right)$ within the \Rom{} cosmological hydrodynamic simulation. Using mock observation methods, we identify isolated dwarf galaxies with quenched star formation and make direct comparisons to the quenched fraction in the NASA Sloan Atlas

Patrick dos Anjos, Lucas A. Quaresma, Marcelo L. P. Machado

This work aimed to mathematically model the glass transition temperature (Tg), one of the most important parameters regarding the behavior of slag, responsible for the sudden change in thermomechanical properties of non-crystalline materials, by the chemical composition of the SiO2-Na2O-CaO system, widely applicable in the production of glasses and constitue

Alexander S. Wein

Suppose we are given an $n$-dimensional order-3 symmetric tensor $T \in (\mathbb{R}^n)^{\otimes 3}$ that is the sum of $r$ random rank-1 terms. The problem of recovering the rank-1 components is possible in principle when $r \lesssim n^2$ but polynomial-time algorithms are only known in the regime $r \ll n^{3/2}$. Similar "statistical-computational gaps" occ

Hendri Murfi, Syamsyuriani, Theresia Gowandi, Gianinna Ardaneswari

Sentiment analysis is the computational study of opinions and emotions ex-pressed in text. Deep learning is a model that is currently producing state-of-the-art in various application domains, including sentiment analysis. Many researchers are using a hybrid approach that combines different deep learning models and has been shown to improve model performance

Haoran Geng, Helin Xu, Chengyang Zhao, Chao Xu

For years, researchers have been devoted to generalizable object perception and manipulation, where cross-category generalizability is highly desired yet underexplored. In this work, we propose to learn such cross-category skills via Generalizable and Actionable Parts (GAParts). By identifying and defining 9 GAPart classes (lids, handles, etc.) in 27 object

Ugo Nzongani, Julien Zylberman, Carlo-Elia Doncecchi, Armando Pérez

The aim of this paper is to build quantum circuits that implement discrete-time quantum walks having an arbitrary position-dependent coin operator. The position of the walker is encoded in base 2: with $n$ wires, each corresponding to one qubit, we encode $2^n$ position states. The data necessary to define an arbitrary position-dependent coin operator is the

K. Hori, A. Nilsson, S. M. Tobias

This Special Topic focuses on magnetohydrodynamic (MHD) processes in deep interiors of planets, in which their fluid dynamos are in operation. The dynamo-generated, global, magnetic fields provide a background for our solar-terrestrial environment. Probing the processes within the dynamos is a significant theoretical and computational challenge and any windo

Jay J. Yoo, Khashayar Namdar, Matthias W. Wagner, Liana Nobre

Segmentation of regions of interest (ROIs) for identifying abnormalities is a leading problem in medical imaging. Using machine learning for this problem generally requires manually annotated ground-truth segmentations, demanding extensive time and resources from radiologists. This work presents a weakly supervised approach that utilizes binary image-level l

Fatemeh Khayashi, Behnaz Jamasb, Reza Akbari, Pirooz Shamsinejadbabaki

Requirement engineering (RE) is the first and the most important step in software production and development. The RE is aimed to specify software requirements. One of the tasks in RE is the categorization of software requirements as functional and non-functional requirements. The functional requirements (FR) show the responsibilities of the system while non-

Francesco Fournier-Facio, Yash Lodha, Matthew C. B. Zaremsky

A left orderable monster is a finitely generated left orderable group all of whose fixpoint-free actions on the line are proximal: the action is semiconjugate to a minimal action so that for every bounded interval $I$ and open interval $J$, there is a group element that sends $I$ into $J$. In his 2018 ICM address, Navas asked about the existence of left orde

Chen Lin, Safoora Yousefi, Elvis Kahoro, Payam Karisani

Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural networks (ANNs). Most of the prior work relied on modeling pollutant concentrations collected from ground-based monitors and me

Jin-San Cheng, Junyi Wen

Using the local geometrical properties of a given zero-dimensional square multivariate nonlinear system inside a box, we provide a simple but effective and new criterion for the uniqueness and the existence of a real simple zero of the system inside the box. Based on the result, we design an algorithm based on subdivision and interval arithmetics to isolate

Pu-Xin Lin, Hai-Long Huang, Jun Zhang, Yun-Song Piao

How the spacetime evolved non-perturbatively in a landscape with multiple anti-de Sitter (AdS) vacua, which is theoretically well-motivated, has always been a matter of concern. As a step towards this issue, we perform (3+1)D numerical relativity simulations for the inhomogeneous universe in an AdS landscape, and find that large inhomogeneity of scalar field

Y. S. Dimant, M. M Oppenheim, S. Evans, J. Martinez-Sykora

This paper develops a unified linear theory of local cross-field plasma instabilities, such as the Farley-Buneman, electron thermal, and ion thermal instabilities, in collisional plasmas with fully or partially unmagnetized multi-species ions. Collisional lasma instabilities in low-ionized, highly dissipative, weakly magnetized plasmas play an important role

Seita Nojiri, Akihiko Yamaguchi, Yosuke Suzuki, Tokuo Tsuji

Robotic hands with soft surfaces can perform stable grasping, but the high friction of the soft surfaces makes it difficult to release objects, or to perform operations that require sliding. To solve this issue, we previously developed a contact area variable surface (CAVS), whose friction changed according to the load. However, only our fundamental results

Alexander Wikner, Joseph Harvey, Michelle Girvan, Brian R. Hunt

Recent work has shown that machine learning (ML) models can be trained to accurately forecast the dynamics of unknown chaotic dynamical systems. Short-term predictions of the state evolution and long-term predictions of the statistical patterns of the dynamics (``climate'') can be produced by employing a feedback loop, whereby the model is trained to predict

Justin C. Feng, Sumanta Chakraborty, Vitor Cardoso

We describe a shielding mechanism for a charged black hole immersed in a background involving charged matter fields, solely arising from the Einstein-Maxwell field equations. In particular, we consider a charged generalization of the Einstein cluster, that is a charged black hole surrounded by an effective fluid model for a partially charged dust cloud. We s

Jacopo Garofali

In the present work we define and study the classifying (or "quotient") site $[X/\Sigma]$ for any small site $X$ with (countable) coproducts endowed with an action of a (countable) semigroup $\Sigma$. A simple case (the most relevant to our applications) is the case $\Sigma=\mathbb{N}$, on which, therefore we concentrate. Our main result consists in establis

Santiago Cifuentes, Francisco J. Soulignac, Pablo Terlisky

Fishburn developed an algorithm to solve a system of $m$ difference constraints whose $n$ unknowns must take values from a set with $k$ real numbers [Solving a system of difference constraints with variables restricted to a finite set, Inform Process Lett 82 (3) (2002) 143--144]. We provide an implementation of Fishburn's algorithm that runs in $O(n+km)$ tim

Chinmay Sahu, Blaine Ayotte, Mahesh K. Banavar

In this innovative practice work-in-progress paper, we compare two different methods to teach machine learning concepts to undergraduate students in Electrical Engineering. While machine learning is now being offered as a senior-level elective in several curricula, this does not mean all students are exposed to it. Exposure to the concepts and practical appl

Mark Popinchalk, Jacqueline K. Faherty, Jason L. Curtis, Jonathan Gagné

The Tucana-Horologium Association (Tuc-Hor) is a 40 Myr old moving group in the southern sky. In this work, we measure the rotation periods of 313 Tuc-Hor objects with TESS light curves derived from TESS full frame images and membership lists driven by Gaia EDR3 kinematics and known youth indicators. We recover a period for 81.4% of the sample and report 255

Toshihiro Nishimura, Tsubasa Muryoe, Yoshitatsu Asama, Hiroki Ikeuchi

This letter proposes a novel single-fingered reconfigurable robotic gripper for grasping objects in narrow working spaces. The finger of the developed gripper realizes two configurations, namely, the insertion and grasping modes, using only a single motor. In the insertion mode, the finger assumes a thin shape such that it can insert its tip into a narrow sp

Daniel Wines, Kamal Choudhary, Adam J. Biacchi, Kevin F. Garrity

High-throughput density functional theory (DFT) calculations allow for a systematic search for conventional superconductors. With the recent interest in two-dimensional (2D) superconductors, we used a high-throughput workflow to screen over 1,000 2D materials in the JARVIS-DFT database and performed electron-phonon coupling calculations, using the McMillan-A

Julianne I. Moses, Zarah L. Brown, Tommi T. Koskinen, Leigh N. Fletcher

During the Grand Finale stage of the Cassini mission, organic-rich ring material was discovered to be flowing into Saturn's equatorial upper atmosphere at a surprisingly large rate. Through a series of photochemical models, we have examined the consequences of this ring material on the chemistry of Saturn's neutral and ionized atmosphere. We find that if a s

Nadir Murru, Giuliano Romeo

Continued fractions in the field of $p$--adic numbers have been recently studied by several authors. It is known that the real continued fraction of a positive quadratic irrational is eventually periodic (Lagrange's Theorem). It is still not known if a $p$--adic continued fraction algorithm exists that shares a similar property. In this paper we modify and i

Logan E. Beaver, Roberto Tron, Christos G. Cassandras

As robotic systems continue to address emerging issues in areas such as logistics, mobility, manufacturing, and disaster response, it is increasingly important to rapidly generate safe and energy-efficient trajectories. In this article, we present a new approach to plan energy-optimal trajectories through cluttered environments containing polygonal obstacles

Alexander W. Criswell, Jesse Miller, Noah Woldemariam, Theodoros Soultanis

Binary neutron star (BNS) post-merger gravitational-wave emission can occur in the aftermath of a BNS merger -- provided the system avoids prompt collapse to a black hole -- as a quasistable hypermassive remnant experiences quadrupolar oscillations and non-axisymmetric deformations. The post-merger gravitational-wave spectrum possesses a characteristic peak

Ana-Maria Cretu, Florimond Houssiau, Antoine Cully, Yves-Alexandre de Montjoye

Although query-based systems (QBS) have become one of the main solutions to share data anonymously, building QBSes that robustly protect the privacy of individuals contributing to the dataset is a hard problem. Theoretical solutions relying on differential privacy guarantees are difficult to implement correctly with reasonable accuracy, while ad-hoc solution

Pin-Hua Huang, Ryan Coffee, Leora Dresselhaus-Marais

Mechanical properties in crystals are strongly correlated to the arrangement of 1D line defects, termed dislocations. Recently, Dark field X-ray Microscopy (DFXM) has emerged as a new tool to image and interpret dislocations within crystals using multidimensional scans. However, the methods required to reconstruct meaningful dislocation information from high

Dong An, Jin-Peng Liu, Daochen Wang, Qi Zhao

We study the limitations and fast-forwarding of quantum algorithms for linear ordinary differential equation (ODE) systems with a particular focus on non-quantum dynamics, where the coefficient matrix in the ODE is not anti-Hermitian or the ODE is inhomogeneous. On the one hand, for generic linear ODEs, by proving worst-case lower bounds, we show that quantu

Salvador Barraza-Lopez, Gerardo G. Naumis

A two-dimensional topological crystalline insulator (TCI) with a single unit cell (u.c.) thickness is demonstrated here. To that end, one first shows that tetragonal ($C_4$ in-plane) symmetry is not a necessary condition for the creation of zero-energy metallic surface states on TCI slabs of finite-thicknesses, because zero-energy states persist even as all

Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charu C. Aggarwal

Time series anomaly detection has applications in a wide range of research fields and applications, including manufacturing and healthcare. The presence of anomalies can indicate novel or unexpected events, such as production faults, system defects, or heart fluttering, and is therefore of particular interest. The large size and complex patterns of time seri

Paul Blum, Peter Crowley, George Lykotrafitis

Development of navigation algorithms is essential for the successful deployment of robots in rapidly changing hazardous environments for which prior knowledge of configuration is often limited or unavailable. Use of traditional path-planning algorithms, which are based on localization and require detailed obstacle maps with goal locations, is not possible. I

Maxime Quesnel, Gilles Orban de Xivry, Olivier Absil, Gilles Louppe

Instrumental aberrations strongly limit high-contrast imaging of exoplanets, especially when they produce quasistatic speckles in the science images. With the help of recent advances in deep learning, we have developed in previous works an approach that applies convolutional neural networks (CNN) to estimate pupil-plane phase aberrations from point spread fu

Darryl E. Wright, Cole Cook, Jason Klug, Panagiotis Korfiatis

The de facto standard of dynamic histogram binning for radiomic feature extraction leads to an elevated sensitivity to fluctuations in annotated regions. This may impact the majority of radiomic studies published recently and contribute to issues regarding poor reproducibility of radiomic-based machine learning that has led to significant efforts for data ha

Dawei Fu, Alim Ruzi, Meng Lu, Qiang Li

We propose methods to produce energetic meson beams such as charged and neutral Kaons, which are boosted to be collimated and with relatively long life time. The first type of methods is based on asymmetric electron positron collisions with a center of mass energy of, e.g., 1020 MeV, and Kaons can be produced at a rate of $10^{4-5}/s$. The electron and posit

Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala

Representation learning for proteins has primarily focused on the global understanding of protein sequences regardless of their length. However, shorter proteins (known as peptides) take on distinct structures and functions compared to their longer counterparts. Unfortunately, there are not as many naturally occurring peptides available to be sequenced and t

Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani

We present RecD (Recommendation Deduplication), a suite of end-to-end infrastructure optimizations across the Deep Learning Recommendation Model (DLRM) training pipeline. RecD addresses immense storage, preprocessing, and training overheads caused by feature duplication inherent in industry-scale DLRM training datasets. Feature duplication arises because DLR

Oisín A. P. Mac Conamhna

A historical record of a seismic tsunami is identified in the Irish annals for October 720 (all dates herein CE). It is contained in the earliest stratum of the annals, which survives in the form of a handful of iterated scribal copies of the foundational text of the tradition. This was compiled by the contemporary observation of noteworthy events for the ye