March 2023 arXiv papers — page 148

Tin-Han Chi, Kai-Chun Liu, Chia-Yeh Hsieh, Yu Tsao

Fall accidents are critical issues in an aging and aged society. Recently, many researchers developed pre-impact fall detection systems using deep learning to support wearable-based fall protection systems for preventing severe injuries. However, most works only employed simple neural network models instead of complex models considering the usability in reso

Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno

The amount of medical images stored in hospitals is increasing faster than ever; however, utilizing the accumulated medical images has been limited. This is because existing content-based medical image retrieval (CBMIR) systems usually require example images to construct query vectors; nevertheless, example images cannot always be prepared. Besides, there ca

Xiumin Wang, Zhong Huang, Xiangqian Zhou, Ralf Klasing

In 1982, Harary introduced the concept of Ramsey achievement game on graphs. Given a graph $F$ with no isolated vertices. Consider the following game played on the complete graph $K_n$ by two players Alice and Bob. First, Alice colors one of the edges of $K_n$ blue, then Bob colors a different edge red, and so on. The first player who can complete the format

Maxence Hussonnois, Thommen George Karimpanal, Santu Rana

Autonomously learning diverse behaviors without an extrinsic reward signal has been a problem of interest in reinforcement learning. However, the nature of learning in such mechanisms is unconstrained, often resulting in the accumulation of several unusable, unsafe or misaligned skills. In order to avoid such issues and ensure the discovery of safe and human

Qi Yang, Jesus G. Cruz-Garza, Saleh Kalantari

MindSculpt enables users to generate a wide range of hybrid geometries in Grasshopper in real time simply by thinking about those geometries. This design tool combines a brain-computer interface (BCI) with the parametric design platform Grasshopper, creating an intuitive design workflow that shortens the latency between ideation and implementation compared t

Kaveh Rahbardar Mojaver, Bokun Zhao, Edward Leung, S. Mohammad Reza Safaee

We demonstrate a novel mesh of Mach-Zehnder interferometers (MZIs) for programmable optical processors. The proposed mesh, referred to as Bokun mesh, is an architecture that merges the attributes of the prior topologies Diamond and Clements. Similar to Diamond, Bokun provides diagonal paths passing through every individual MZI enabling direct phase monitorin

Hajime Sotani, Tomoya Naito

We derive the empirical formulae expressing the mass and gravitational redshift of a neutron star, whose central density is less than threefold the nuclear saturation density, as a function of the neutron-skin thickness or the dipole polarizability of $ {}^{208} \mathrm{Pb} $ or $ {}^{132} \mathrm{Sn} $, especially focusing on the 8 Skyrme-type effective int

Yingxiao Du, Jianxin Wu

Unlike the case when using a balanced training dataset, the per-class recall (i.e., accuracy) of neural networks trained with an imbalanced dataset are known to vary a lot from category to category. The convention in long-tailed recognition is to manually split all categories into three subsets and report the average accuracy within each subset. We argue tha

Nijiati Yalikun, Xiang-Kun Dong, Bing-Song Zou

The possible hadronic molecules in $D_s^{(*)+}\Xi_c^{(',*)}$ systems with $J^P=1/2^-,3/2^-$ and $5/2^-$ are investigated with interactions described by light meson exchanges. By varying the cutoff in a phenomenologically reasonable range of $1\sim2.5$ GeV, we find ten near-threshold (bound or virtual) states in the single-channel case. After introducing the

Seungone Kim, Se June Joo, Yul Jang, Hyungjoo Chae

Chain-of-thought (CoT) prompting enables large language models (LLMs) to solve complex reasoning tasks by generating an explanation before the final prediction. Despite it's promising ability, a critical downside of CoT prompting is that the performance is greatly affected by the factuality of the generated explanation. To improve the correctness of the expl

Matthias Schötz

Consider a commutative monoid $(M,+,0)$ and a biadditive binary operation $\mu \colon M \times M \to M$. We will show that under some additional general assumptions, the operation $\mu$ is automatically both associative and commutative. The main additional assumption is localizability of $\mu$, which essentially means that a certain canonical order on $M$ is

Emily Kuang, Ruihuan Chen, Mingming Fan

Older adults increasingly adopt small-screen devices, but limited motor dexterity hinders their ability to type effectively. While a 9-key (T9) keyboard allocates larger space to each key, it is shared by multiple consecutive letters. Consequently, users must interrupt their gestures when typing consecutive letters, leading to inefficiencies and poor user ex

Rui Xu, Zhi Liu, Yong Luo, Han Hu

Lung cancer is the leading cause of cancer death worldwide. The best solution for lung cancer is to diagnose the pulmonary nodules in the early stage, which is usually accomplished with the aid of thoracic computed tomography (CT). As deep learning thrives, convolutional neural networks (CNNs) have been introduced into pulmonary nodule detection to help doct

Pengcheng Hou, Xiansheng Cai, Tao Wang, Youjin Deng

Superconductivity at low temperature -- observed in lithium and bismuth, as well as in various low-density superconductors -- calls for developing reliable theoretical and experimental tools for predicting ultralow critical temperatures, $T_c$, of Cooper instability in a system demonstrating nothing but normal Fermi liquid behavior in a broad range of temper

Alexandre Paiva Barreto, Fernando Gasparotto

In this article we fully classify regular tubular surfaces in Euclidean, Lorentzian and hyperbolic 3-spaces whose Gaussian and mean curvatures $K$ and $H$ verify a polynomial relation. More precisely, we determine the set $S(Q)$ of all regular tubular surfaces whose curvatures verify a given polynomial relation $Q(K,H)=0$, and the set $Q(S)$ of all polynomia

Chang Liu, Andrey Lvovskiy, Carlos Paz-Soldan, Stephen C. Jardin

Alfv\'enic modes in the current quench (CQ) stage of the tokamak disruption have been observed in experiments. In DIII-D the excitation of these modes is associated with the presence of high-energy runaway electrons, and a strong mode excitation is often associated with the failure of RE plateau formation. In this work we present results of self-consistent k

Tong Fang, Hui Zhang, Shangfei Liu, Beibei Liu

In the core accretion model, planetesimals grow by mutual collisions and engulfing millimeter-to-centimeter particles, i.e., pebbles. Pebble accretion can significantly increase the accretion efficiency and help explain the presence of planets on wide orbits. However, the pebble supply is typically parameterized as a coherent pebble mass flux, sometimes bein

Shaui Yao, Patricio Peralta-Braz, Mehri Makki Alamdari, Rafael O. Ruiz

Piezoelectric energy harvesters (PEHs) can be used as an additional power supply for a Structural Health Monitoring (SHM) system. Its design can be optimised for the best performance; however, the optimal design depends on the input vibration, e.g. acceleration of a bridge due to wind loads and passing traffic. In previous studies, we have shown that optimal

Banerjee, Anuvab, Sharma, Ajay

Study of quasi-periodic oscillations (QPO) in blazars is one of the crucial methods for gaining insights into the workings of the central engines of active galactic nuclei. QPOs with various characteristic time scales have been observed in the multi-wavelength emission of blazars, ranging from the radio to gamma-ray frequency bands. In this study, we carry o

Tina Li, Suho Oh, Edward Richmond, Grace Yan

The Demazure product (also goes by the name of 0-Hecke product or the greedy product) is an associative operation on Coxeter groups with interesting properties and important applications. In this note, we study permutations and present an efficient way to compute the Demazure product of two permutations starting from their usual product and then applying a n

Zhiqiang Liu, Wenjian Yu

Effective resistance, which originates from the field of circuits analysis, is an important graph distance in spectral graph theory. It has found numerous applications in various areas, such as graph data mining, spectral graph sparsification, circuits simulation, etc. However, computing effective resistances accurately can be intractable and we still lack e

Van-Thach Do, Quang-Cuong Pham

This paper presents a new approach to obtaining nearly complete coverage paths (CP) with low overlapping on 3D general surfaces using mesh models. The CP is obtained by segmenting the mesh model into a given number of clusters using constrained centroidal Voronoi tessellation (CCVT) and finding the shortest path from cluster centroids using the geodesic metr

Bivas Mallick, Saheli Mukherjee, Ananda G. Maity, A. S. Majumdar

Non-Markovian effects in open quantum system dynamics usually manifest backflow of information from the environment to the system, indicating complete-positive divisibility breaking of the dynamics. We provide a criterion for witnessing such non-Markovian dynamics exhibiting information backflow, based on the moments of Choi-matrices. The moment condition de

Zengyang Gong, Yuxiang Zeng, Lei Chen

Ridesharing has become a promising travel mode recently due to the economic and social benefits. As an essential operator, "insertion operator" has been extensively studied over static road networks. When a new request appears, the insertion operator is used to find the optimal positions of a worker's current route to insert the origin and destination of thi

Golchehr Amirkhani, Anna Goodridge, Mojtaba Esfandiari, Henry Phalen

Continuum dexterous manipulators (CDMs) are suitable for performing tasks in a constrained environment due to their high dexterity and maneuverability. Despite the inherent advantages of CDMs in minimally invasive surgery, real-time control of CDMs' shape during non-constant curvature bending is still challenging. This study presents a novel approach for the

Wenxing Zhang, Hao-Lin Li, Kun Liu, Michael J. Ramsey-Musolf

We investigate the prospects for resonant di-Higgs and heavy Higgs production searches at the 14 TeV HL-LHC in the combination of $bb\gamma\gamma$ and $4l$ channels, as a probe of a possible first order electroweak phase transition in real singlet scalar extension of the Standard Model. Event selection follows those utilized in the $bb\gamma\gamma$ and $4l$

Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin

Monitoring and detecting abnormal events in cyber-physical systems is crucial to industrial production. With the prevalent deployment of the Industrial Internet of Things (IIoT), an enormous amount of time series data is collected to facilitate machine learning models for anomaly detection, and it is of the utmost importance to directly deploy the trained mo

Napaporn A-thano, Supachai Awiphan, Ing-Guey Jiang, Eamonn Kerins

We present the transit timing variation (TTV) and planetary atmosphere analysis of the Neptune-mass planet HAT-P-26~b. We present a new set of 13 transit light curves from optical ground-based observations and combine them with light curves from the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope (HST), Transiting Exoplanet Survey Satellite (TESS),

Rin Suyama, Yoshiki Miyauchi, Atsuo Maki

Among ship maneuvers, berthing/unberthing maneuvers are one of the most challenging and stressful phases for captains. Concerning burden reduction on ship operators and preventing accidents, several researches have been conducted on trajectory planning to automate berthing/unberthing. However, few studies have aimed at assisting captains in berthing/unberthi

Yixin Liu, Alexander R. Fabbri, Yilun Zhao, Pengfei Liu

Interpretability and efficiency are two important considerations for the adoption of neural automatic metrics. In this work, we develop strong-performing automatic metrics for reference-based summarization evaluation, based on a two-stage evaluation pipeline that first extracts basic information units from one text sequence and then checks the extracted unit

Seyed Hassan Alavi

Let $G$ be a finite group and ${\rm cd}(G)$ denote the set of complex irreducible character degrees of $G$. In this paper, we prove that if $G$ is a finite group and $H$ is an almost simple group with socle $H_{0}= \, ^{2}{\rm G}_{2}(q)$, where $q=3^{f}$ with $f\geq 3$ odd such that ${\rm cd}(G)={\rm cd}(H)$, then $G$ is non-solvable and the chief factor $G'

Gage Bonner

Let $\{U(n)\}_{n \geq 0}$ be a sequence of independent random variables such that $U(n)$ is distributed uniformly on $\{0, 1, 2 \dots n\}$. The Ulam-Kac adder is the history-dependent random sequence defined by $X_{n + 1} = X_{n} + X_{U(n)}$ with the initial condition $X_0 = 1$. We show that for each $m \geq 1$, it holds that $\log E[X_n^m]/\sqrt{n}$ approac

Zhang Weilin, Yuan Pingzhi

In this note, we prove an irreducibility criterion for the polynomial of the form $f(x) = a_{n}x^{n} + a_{n-1}x^{n-1} + \cdots + a_{m}x^{m} + p^{u} \in \mathbb{Z}[x]$, where $p$ is a prime number, $u \geqslant 1$, $\gcd(u, m) = 1$, $p \nmid a_{m}$ and $p^{u} > |a_{n}| + |a_{n-1}| + \cdots + |a_{m}|$. In particular, we show that the conjecture of Koley and Re

David Moss

As a derivative of graphene, graphene oxide (GO) was initially developed by chemists to emulate some of the key properties of graphene, but it was soon recognized as a unique material in its own right, addressing an application space that is not accessible to chemical vapor deposition based materials. Over the past decade, GO has emerged as a new frontier ma

Wang Jin-Chuan, Li Cui-Hong, Zhu Shao-Chong, He Chao-Xiong

The accurate measurement of the net charge on a nanoparticle is critical in both the research and application of nanoparticles. Particularly, in the field of precision sensing based on optically levitated nanoparticles, the precise measurement of the net charge on a nanoparticle is prerequisite for stable levitation before electric control process and for th

Oguzhan Akcin, Po-han Li, Shubhankar Agarwal, Sandeep Chinchali

Fleets of networked autonomous vehicles (AVs) collect terabytes of sensory data, which is often transmitted to central servers (the ''cloud'') for training machine learning (ML) models. Ideally, these fleets should upload all their data, especially from rare operating contexts, in order to train robust ML models. However, this is infeasible due to prohibitiv

Hong Tao, Yuguo Su, Xingyu Zhang, Jing Liu

The distribution of Lee-Yang zeros not only matters in thermodynamics and quantum mechanics, but also in mathematics. Hereby we propose a nonlinear quantum toy model and discuss the distribution of corresponding Lee-Yang zeros. Utilizing the coupling between a probe qubit and the nonlinear system, all Lee-Yang zeros can be detected in the dynamics of the pro

Jinjie Ni, Yukun Ma, Wen Wang, Qian Chen

Learning on a massive amount of speech corpus leads to the recent success of many self-supervised speech models. With knowledge distillation, these models may also benefit from the knowledge encoded by language models that are pre-trained on rich sources of texts. The distillation process, however, is challenging due to the modal disparity between textual an

Kaiyuan Hu, Yili Jin, Haowen Yang, Junhua Liu

Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space. Volumetric videos, as an emerging representative 3D video paradigm that empowers extended reality, stand out to provide unprecedented immersive and interactive video watching experience. Despite the tremendous potential, the

Yuanjiang Cao, Lina Yao, Le Pan, Quan Z. Sheng

The goal of Image-to-image (I2I) translation is to transfer an image from a source domain to a target domain, which has recently drawn increasing attention. One major branch of this research is to formulate I2I translation based on Generative Adversarial Network (GAN). As a zero-sum game, GAN can be reformulated as a Partially-observed Markov Decision Proces

Pritha Dey, Tejendra Dixit, Vikash Mishra, Anubhab Sahoo

Low-dimensional transition metal dichalcogenide, TMDC, materials are heralding a new era in optoelectronics and valleytronics owing to their unique properties. Photo-induced dynamics in these systems has mostly been studied from the perspective of individual quasi-particles, including excitons, bi-excitons or, even, trions. Their formation, evolution and dec

F. Portillo, R. Longland, A. L. Cooper, S. Hunt

The $^{18}$F(p, $\alpha$)$^{15}$O reaction is key to determining the $^{18}$F abundance in classical novae. However, the cross section for this reaction has large uncertainties at low energies largely caused by interference effects. Here, we resolve a longstanding issue with unknown spin-parities of sub-threshold states in $^{19}$Ne that reduces these uncert

Xin Li, Tao Ma, Yuenan Hou, Botian Shi

LiDAR-camera fusion methods have shown impressive performance in 3D object detection. Recent advanced multi-modal methods mainly perform global fusion, where image features and point cloud features are fused across the whole scene. Such practice lacks fine-grained region-level information, yielding suboptimal fusion performance. In this paper, we present the

Yuka Oshima, Hiroki Fujimoto, Jun'ya Kume, Soichiro Morisaki

Axions are one of the well-motivated candidates for dark matter, originally proposed to solve the strong CP problem in particle physics. Dark matter Axion search with riNg Cavity Experiment (DANCE) is a new experimental project to broadly search for axion dark matter in the mass range of $10^{-17}~\mathrm{eV} < m_a < 10^{-11}~\mathrm{eV}$. We aim to detect t

Linyuan Gong, Jiayi Wang, Alvin Cheung

We propose the Adversarial DEep Learning Transpiler (ADELT), a novel approach to source-to-source transpilation between deep learning frameworks. ADELT uniquely decouples code skeleton transpilation and API keyword mapping. For code skeleton transpilation, it uses few-shot prompting on large language models (LLMs), while for API keyword mapping, it uses cont

Yiwei Lu, Gautam Kamath, Yaoliang Yu

Indiscriminate data poisoning attacks aim to decrease a model's test accuracy by injecting a small amount of corrupted training data. Despite significant interest, existing attacks remain relatively ineffective against modern machine learning (ML) architectures. In this work, we introduce the notion of model poisoning reachability as a technical tool to expl

Ankit Shah, Shuyi Chen, Kejun Zhou, Yue Chen

General-purpose embedding is highly desirable for few-shot even zero-shot learning in many application scenarios, including audio tasks. In order to understand representations better, we conducted a thorough error analysis and visualization of HEAR 2021 submission results. Inspired by the analysis, this work experiments with different front-end audio preproc

Jiang Xie, Qiao Deng, Shuyin Xia, Yangzhou Zhao

In recent years, the problem of fuzzy clustering has been widely concerned. The membership iteration of existing methods is mostly considered globally, which has considerable problems in noisy environments, and iterative calculations for clusters with a large number of different sample sizes are not accurate and efficient. In this paper, starting from the st

Alireza Mousavi-Hosseini, Tyler Farghly, Ye He, Krishnakumar Balasubramanian

Langevin diffusions are rapidly convergent under appropriate functional inequality assumptions. Hence, it is natural to expect that with additional smoothness conditions to handle the discretization errors, their discretizations like the Langevin Monte Carlo (LMC) converge in a similar fashion. This research program was initiated by Vempala and Wibisono (201

Dongkeun Lee, Kyunghyun Baek, Joonsuk Huh, Daniel K. Park

Quantum state discrimination (QSD) is a fundamental task in quantum information processing with numerous applications. We present a variational quantum algorithm that performs the minimum-error QSD, called the variational quantum state discriminator (VQSD). The VQSD uses a parameterized quantum circuit that is trained by minimizing a cost function derived fr

Akhtar A. Khan, Jinlu Li

This note conducts a comparative study of some approximating properties of the metric projection, generalized projection, and generalized metric projection in uniformly convex and uniformly smooth Banach spaces. We prove that the inverse images of the metric projections are closed and convex cones, but they are not necessarily convex. In contrast, inverse im

Hui Bai, Ran Cheng, Yaochu Jin

Reinforcement learning (RL) is a machine learning approach that trains agents to maximize cumulative rewards through interactions with environments. The integration of RL with deep learning has recently resulted in impressive achievements in a wide range of challenging tasks, including board games, arcade games, and robot control. Despite these successes, th

Elio G. Champenois, Nanna H. List, Matthew Ware, Mathew Britton

Directly imaging structural dynamics involving hydrogen atoms by ultrafast diffraction methods is complicated by their low scattering cross-sections. Here we demonstrate that megaelectronvolt ultrafast electron diffraction is sufficiently sensitive to follow hydrogen dynamics in isolated molecules. In a study of the photodissociation of gas phase ammonia, we

Ling Tang, Chao Zhang, Yang Sun, Kai-Ming Ho

Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of Fe90Si3O7 liquid close to the Earth's liquid core conditions. The simulation results reveal that the short-range structural order (SRO) in the Fe90Si3O7 liquid is very strong. About 80% of the atom

Carolina Neira Jiménez

This article presents a survey of recent developments on pseudodifferential operators on noncommutative tori. We describe currently available constructions of those operators: by means of a $C^*$--dynamical system, by using an analogue of the Fourier series representation of a function in the (commutative) torus $C^\infty(\mathbb{T}^n)$, as Rieffel deformati

Siqi Fan, Zhe Wang, Xiaoliang Huo, Yan Wang

Effective BEV object detection on infrastructure can greatly improve traffic scenes understanding and vehicle-toinfrastructure (V2I) cooperative perception. However, cameras installed on infrastructure have various postures, and previous BEV detection methods rely on accurate calibration, which is difficult for practical applications due to inevitable natura

Jinyuan Chang, Jing He, Jian Kang, Mingcong Wu

Statistical analysis of multimodal imaging data is a challenging task, since the data involves high-dimensionality, strong spatial correlations and complex data structures. In this paper, we propose rigorous statistical testing procedures for making inferences on the complex dependence of multimodal imaging data. Motivated by the analysis of multi-task fMRI

Kewei Cheng, Nesreen K. Ahmed, Yizhou Sun

Learning logical rules is critical to improving reasoning in KGs. This is due to their ability to provide logical and interpretable explanations when used for predictions, as well as their ability to generalize to other tasks, domains, and data. While recent methods have been proposed to learn logical rules, the majority of these methods are either restricte

Nen Saito, Shuji Ishihara

Cell deformability is an essential determinant for tissue-scale mechanical nature, such as fluidity and rigidity, and is thus crucial for understanding tissue homeostasis and stable developmental processes. However, numerical simulations for the collective dynamics of cells with arbitral cell deformations akin to mesenchymal, ameboid, and epithelial cells in

YuanDong Wang, Zhen-Gang Zhu, Gang Su

We propose the linear and nonlinear planar Hall effect (PHE) in tilted Weyl semimetals in the presence of an in-plane magnetic and electric field, where the field-induced Berry connection (FBC) plays a key role. We show that the PHE is ascribed to the quantum metric, distinct from the well-known chiral anomaly-induced PHE arising from the Berry curvature. Us

Peter Washington

Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be both a gift and a curse, as the propensity toward overfitting is magnifie

Peter Washington, Dennis P. Wall

Autism Spectrum Disorder (autism) is a neurodevelopmental delay which affects at least 1 in 44 children. Like many neurological disorder phenotypes, the diagnostic features are observable, can be tracked over time, and can be managed or even eliminated through proper therapy and treatments. Yet, there are major bottlenecks in the diagnostic, therapeutic, and

Admi Nazra

In this paper, we proved that there exist four distinct diffeomorphism classes of three-dimensional real Bott tower $M(A)=(S^1)^3/(\mathbb{Z}_2)^3$, and 12 distinct diffeomorphism classes of four-dimensional real Bott tower $M(A)=(S^1)^4/(\mathbb{Z}_2)^4$, where matrix $A$ corresponds to the action of $(\mathbb{Z}_2)^n$ on $(S^1)^n$ for n=3,4.

Yujie Zhao, Xiaoming Huo

In statistics, the least absolute shrinkage and selection operator (Lasso) is a regression method that performs both variable selection and regularization. There is a lot of literature available, discussing the statistical properties of the regression coefficients estimated by the Lasso method. However, there lacks a comprehensive review discussing the algor

Xiongwen Ke, Houying Zhu, Kai Yi, Gaoning He

In this paper, we propose an efficient simulation method based on adaptive importance sampling, which can automatically find the optimal proposal within the Gaussian family based on previous samples, to evaluate the probability of bit error rate (BER) or word error rate (WER). These two measures, which involve high-dimensional black-box integration and rare-

Hao Liu, Saipraneeth Devunuri, Lewis Lehe, Vikash V. Gayah

Ridesplitting -- a type of ride-hailing in which riders share vehicles with other riders -- has become a common travel mode in some major cities. This type of shared ride option is currently provided by transportation network companies (TNCs) such as Uber, Lyft, and Via and has attracted increasing numbers of users, particularly before the COVID-19 pandemic.

Karen Grigorian, Robert A. Jarrow

In this paper we provide an exhaustive survey of the current state of the mathematics of filtration enlargement and an interpretation of the key results of the literature from the viewpoint of mathematical finance. The emphasis is on providing a well-structured compendium of known mathematical results that can be used by researchers in mathematical finance.

Zahra Dasht Bozorgi, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy

Increasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain actions (a.k.a. treatments) that workers may execute to lift the probability that a case ends in a positive outcome. For example, in a loan origination process, a possible treatmen

Dan Barbasch, Jia-Jun Ma, Binyong Sun, Chen-Bo Zhu

We determine all genuine special unipotent representations of real spin groups and quaternionic spin groups, and show in particular that all of them are unitarizable. We also show that there are no genuine special unipotent representations of complex spin groups.

Maninderjeet Singh, Priyanka Das, Pabitra Narayan Samanta, Sumit Bera

Dielectric capacitors are critical components in electronics and energy storage devices. The polymer based dielectric capacitors have advantages of flexibility, fast charge and discharge, low loss, and graceful failure. Elevating the use of polymeric dielectric capacitors for advanced energy applications such as electric vehicles (EVs) however requires signi

Robin Ming Chen, Samuel Walsh, Miles H. Wheeler

A hollow vortex is a region of constant pressure bounded by a vortex sheet and suspended inside a perfect fluid; it can therefore be interpreted as a spinning bubble of air in water. This paper gives a general method for desingularizing non-degenerate steady point vortex configurations into collections of steady hollow vortices. Our machinery simultaneously

Koichi Miyamoto, Naoki Yamamoto, Yasubumi Sakakibara

We propose two quantum algorithms for a problem in bioinformatics, position weight matrix (PWM) matching, which aims to find segments (sequence motifs) in a biological sequence such as DNA and protein that have high scores defined by the PWM and are thus of informational importance related to biological function. The two proposed algorithms, the naive iterat

Mengyang Gu, Xinyi Fang, Yimin Luo

The dynamics of cellular pattern formation is crucial for understanding embryonic development and tissue morphogenesis. Recent studies have shown that human dermal fibroblasts cultured on liquid crystal elastomers can exhibit an increase in orientational alignment over time, accompanied by cell proliferation, under the influence of the weak guidance of a mol

Malabika Pramanik, K S Senthil Raani

The distance set $\Delta(E)$ of a set $E$ consists of all non-negative numbers that represent distances between pairs of points in $E$. This paper studies sparse (less than full-dimensional) Borel sets in $\mathbb R^d$, $d \geq 2$ with a focus on properties of their distance sets. Our results are of four types. First, we generalize a classical result of Stei

Jialin Lin, Xiaoqing Guo, Wen Fan, Wei Li

Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures such as small blood vessels, nerves, etc., under a microscope. To address the limitation of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However

Jingyu Liu, Wenhan Xiong, Ian Jones, Yixin Nie

Indoor scene synthesis involves automatically picking and placing furniture appropriately on a floor plan, so that the scene looks realistic and is functionally plausible. Such scenes can serve as homes for immersive 3D experiences, or be used to train embodied agents. Existing methods for this task rely on labeled categories of furniture, e.g. bed, chair or

Yuki Okoda, Yoko Oya, Logan Francis, Doug Johnstone

We have observed the low-mass protostellar source, IRAS 15398$-$3359, at a resolution of 0.$''$2-0.$''$3, as part of the Atacama Large Millimeter/Submillimeter Array Large Program FAUST, to examine the presence of a hot corino in the vicinity of the protostar. We detect nine CH$_3$OH lines including the high excitation lines with upper state energies up to 5

Sahin Buyukdagli

The requirement to boost the resolution of nanopore-based biosequencing devices necessitates the integration of novel biosensing techniques with reduced sensitivity to background noise. In this article, we probe the signatures of translocating polymers in magnetic fields induced by ionic currents through membrane nanopores. Within the framework of a previous

Tyler McMaken

The construction of black hole spacetimes that are regular (singularity-free) is plagued by the "mass inflation" instability, a classical perturbation instability induced by the surface gravity at the inner horizon and characterized by exponentially diverging stress-energy there. Recently, a class of "inner-extremal" regular black holes was proposed that pos

Antonio Joia Neto, Ivan de Oliveira Nunes

The wide adoption of IoT gadgets and Cyber-Physical Systems (CPS) makes embedded devices increasingly important. While some of these devices perform mission-critical tasks, they are usually implemented using Micro-Controller Units (MCUs) that lack security mechanisms on par with those available to general-purpose computers, making them more susceptible to re

Dandan Zhang, Jin Zheng, Jialin Lin

The accelerating aging population has led to an increasing demand for domestic robotics to ease caregivers' burden. The integration of Internet of Things (IoT), robotics, and human-robot interaction (HRI) technologies is essential for home-care applications. Although the concept of the Internet of Robotic Things (IoRT) has been utilized in various fields, mo

Kyosuke Nishibiro

Recently, Kaneko and Tsumura introduced multiple $\widetilde{T}$-values, another kind of poly-Euler numbers and the related Arakawa-Kaneko type zeta function. It is shown that each of them satisfies similar formulas to those of multiple zeta values, poly-Bernoulli numbers and the related Arakawa-Kaneko type zeta function. In this paper, we show some explicit

Marino Gran, Aline Michel

We prove that the category of preordered groups contains two full reflective subcategories that give rise to some interesting Galois theories. The first one is the category of the so-called commutative objects, which are precisely the preordered groups whose group law is commutative. The second one is the category of abelian objects, that turns out to be the

Luna Morrigan, Simon P. Neville, Margaret Gregory, Andrey E. Boguslavskiy

We develop and experimentally demonstrate a methodology for a full molecular frame quantum tomography (MFQT) of dynamical polyatomic systems. We exemplify this approach through the complete characterization of an electronically non-adiabatic wavepacket in ammonia (NH$_3$). The method exploits both energy and time-domain spectroscopic data, and yields the lab

Chintan Jansari, Stéphane P. A. Bordas, Elena Atroshchenko

We exploit level set topology optimization to find the optimal material distribution for metamaterial-based heat manipulators. The level set function, geometry, and solution field are parameterized using the non-uniform rational B-spline (NURBS) basis functions in order to take advantage of easy control of smoothness and continuity. In addition, NURBS approx

Brenda L. Frye, Massimo Pascale, Nicholas Foo, Reagen Leimbach

The massive galaxy cluster El Gordo (z=0.87) imprints multitudes of gravitationally lensed arcs onto James Webb Space Telescope (JWST) Near-Infrared Camera (NIRCam) images. Eight bands of NIRCam imaging were obtained in the ``Prime Extragalactic Areas for Reionization and Lensing Science'' (``PEARLS'') program. PSF-matched photometry across Hubble Space Tele

Sunny Howard, Jannik Esslinger, Robin H. W. Wang, Peter Norreys

Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm is utilised for the snapshot compressive imaging reconstruction due to its parameter efficiency and superior speed relative to other method

V. Santiago-Vargas, E. O. Velasco-Páez

In this work, we study the Hochschild-Mitchell Cohomology of triangular matrix categories. Given a triangular matrix category $\Lambda=\left[ \begin{smallmatrix} \mathcal{T} & 0 \\ M & \mathcal{U} \end{smallmatrix}\right]$, we investigate the relationship of the Hochschild-Mitchell cohomologies $H^{i}(\Lambda)$ and $H^{i}(\mathcal{U})$ of $\Lambda$ and $\mat

Qingsong Wen, Linxiao Yang, Liang Sun

Periodicity detection is an important task in time series analysis, but still a challenging problem due to the diverse characteristics of time series data like abrupt trend change, outlier, noise, and especially block missing data. In this paper, we propose a robust and effective periodicity detection algorithm for time series with block missing data. We fir

Trent Lucas

Given a finite group $G$ acting on a surface $S$, the centralizer of G in the mapping class group $\textrm{Mod}(S)$ has a natural representation given by its action on the homology $H_1(S; \mathbb{Q})$. We consider the question of whether this representation has arithmetic image. Several authors have given positive and negative answers to this question. We g

Renato Spacek, Gabriel Stoltz

Transport coefficients, such as the mobility, thermal conductivity and shear viscosity, are quantities of prime interest in statistical physics. At the macroscopic level, transport coefficients relate an external forcing of magnitude $\eta$, with $\eta \ll 1$, acting on the system to an average response expressed through some steady-state flux. In practice,

Owen Bradley, Yutan Zhang, Jaan Oitmaa, Rajiv R. P. Singh

We use strong coupling expansions to calculate the entropy function $S(T,h)$, the magnetization $M(T,h)$, and the double occupancy factor $D(T,h)$ for the half-filled triangular lattice Hubbard model as a function of temperature $T$ and Zeeman field $h$, for various values of the Hubbard parameter ratio $U/t$. These calculations converge well for temperature

Fabian Baumann, Daniel Halpern, Ariel D. Procaccia, Iyad Rahwan

Social media platforms are known to optimize user engagement with the help of algorithms. It is widely understood that this practice gives rise to echo chambers\emdash users are mainly exposed to opinions that are similar to their own. In this paper, we ask whether echo chambers are an inevitable result of high engagement; we address this question in a novel

Bowen Zhang, Harold Soh

Human models play a crucial role in human-robot interaction (HRI), enabling robots to consider the impact of their actions on people and plan their behavior accordingly. However, crafting good human models is challenging; capturing context-dependent human behavior requires significant prior knowledge and/or large amounts of interaction data, both of which ar

Christos Boutsikas, Petros Drineas, Ilse C. F. Ipsen

We perturb a real matrix $A$ of full column rank, and derive lower bounds for the smallest singular values of the perturbed matrix, in terms of normwise absolute perturbations. Our bounds, which extend existing lower-order expressions, demonstrate the potential increase in the smallest singular values, and represent a qualitative model for the increase in th

STAR Collaboration, M. I. Abdulhamid, B. E. Aboona, J. Adam

We report on new measurements of elliptic flow ($v_2$) of electrons from heavy-flavor hadron decays at mid-rapidity ($|y|<0.8$) in Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 27 and 54.4 GeV from the STAR experiment. Heavy-flavor decay electrons ($e^{\rm HF}$) in Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 54.4 GeV exhibit a non-zero $v_2$ in the transvers

Tim M. Fuchs, Dennis G. Uitenbroek, Jaimy Plugge, Noud van Halteren

Gravity differs from all other known fundamental forces since it is best described as a curvature of spacetime. For that reason it remains resistant to unifications with quantum theory. Gravitational interaction is fundamentally weak and becomes prominent only at macroscopic scales. This means, we do not know what happens to gravity in the microscopic regime

Itai Shapira

This study explores the number of neurons required for a Rectified Linear Unit (ReLU) neural network to approximate multivariate monomials. We establish an exponential lower bound on the complexity of any shallow network approximating the product function over a general compact domain. We also demonstrate this lower bound doesn't apply to normalized Lipschit

Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su

Rich data and powerful machine learning models allow us to design drugs for a specific protein target \textit{in silico}. Recently, the inclusion of 3D structures during targeted drug design shows superior performance to other target-free models as the atomic interaction in the 3D space is explicitly modeled. However, current 3D target-aware models either re

Peyman Jalali, Nengfeng Zhou, Yufei Yu

Developing explainability methods for Natural Language Processing (NLP) models is a challenging task, for two main reasons. First, the high dimensionality of the data (large number of tokens) results in low coverage and in turn small contributions for the top tokens, compared to the overall model performance. Second, owing to their textual nature, the input