May 2022 arXiv papers — page 147

SangMook Kim, Wonyoung Shin, Soohyuk Jang, Hwanjun Song

Robustness is becoming another important challenge of federated learning in that the data collection process in each client is naturally accompanied by noisy labels. However, it is far more complex and challenging owing to varying levels of data heterogeneity and noise over clients, which exacerbates the client-to-client performance discrepancy. In this work

Jean-Emile Bourgine

The notion of shifted quantum groups has recently played an important role in algebraic geometry. This subtle modification of the original definition brings more flexibility in the representation theory of quantum groups. The first part of this paper presents new mathematical results for the shifted quantum toroidal $\mathfrak{gl}(1)$ and quantum affine $\ma

Md Hasan Shahriar, Yang Xiao, Pablo Moriano, Wenjing Lou

Modern vehicles rely on a fleet of electronic control units (ECUs) connected through controller area network (CAN) buses for critical vehicular control. With the expansion of advanced connectivity features in automobiles and the elevated risks of internal system exposure, the CAN bus is increasingly prone to intrusions and injection attacks. As ordinary inje

Subhajit Barman, Bibhas Ranjan Majhi, L. Sriramkumar

We investigate the radiative processes involving two entangled Unruh-DeWitt detectors that are moving on circular trajectories in $(2+1)$-dimensional Minkowski spacetime. We assume that the detectors are coupled to a massless, quantum scalar field, and calculate the transition probability rates of the detectors in the Minkowski vacuum as well as in a thermal

Donghyeon Kim, Gwantae Kim, Bokyeung Lee, Jeong-gi Kwak

Unseen noise signal which is not considered in a model training process is difficult to anticipate and would lead to performance degradation. Various methods have been investigated to mitigate unseen noise. In our previous work, an Instance-level Dynamic Filter (IDF) and a Pixel Dynamic Filter (PDF) were proposed to extract noise-robust features. However, th

M. Vidyasagar

In this paper, we study the almost sure boundedness and the convergence of the stochastic approximation (SA) algorithm. At present, most available convergence proofs are based on the ODE method, and the almost sure boundedness of the iterations is an assumption and not a conclusion. In Borkar-Meyn (2000), it is shown that if the ODE has only one globally att

B. Tripathi, A. E. Fraser, P. W. Terry, E. G. Zweibel

Straining of magnetic fields by large-scale shear flow, generally assumed to lead to intensification and generation of small scales, is re-examined in light of the persistent observation of large-scale magnetic fields in astrophysics. It is shown that, in magnetohydrodynamic turbulence, unstable shear flows have the unexpected effect of sequestering magnetic

Boris Kovalerchuk, Răzvan Andonie, Nuno Datia, Kawa Nazemi

This volume is devoted to the emerging field of Integrated Visual Knowledge Discovery that combines advances in Artificial Intelligence/Machine Learning (AI/ML) and Visualization/Visual Analytics. Chapters included are extended versions of the selected AI and Visual Analytics papers and related symposia at the recent International Information Visualization C

Sarah Peluse

Fix a prime $p\geq 11$. We show that there exists a positive integer $m$ such that any subset of $\mathbb{F}_p^n\times\mathbb{F}_p^n$ containing no nontrivial configurations of the form $(x,y),(x,y+z),(x,y+2z),(x+z,y)$ must have density $\ll 1/\log_{m}{n}$, where $\log_{m}$ denotes the $m$-fold iterated logarithm. This gives the first reasonable bound in the

Niloufar Dousti Mousavi, Hani Aldirawi, Jie Yang

We introduce a newly developed R package AZIAD for analyzing zero-inflated or zero-altered data. Compared with existing R packages, AZIAD covers a much larger class of zero-inflated and hurdle models, including both discrete and continuous cases. It provides more accurate parameter estimates, along with the corresponding Fisher information matrix and confide

Pablo Yepiz-Graciano, Zeferino Ibarra-Borja, Roberto Ramírez Alarcón, Gerardo Gutiérrez-Torres

Quantum-optical coherence tomography (QOCT) is an optical sectioning modality based on the quantum interference of photon pairs, obtained from a spontaneous parametric downconversion (SPDC) source. The promise of QOCT derives from two quantum-conferred advantages when compared to equivalent classical optical coherence tomography (OCT) systems: a factor of 2

Siyu Gu, Xiangrong Sheng

Industrial ranking systems, such as advertising systems, rank items by aggregating multiple objectives into one final objective to satisfy user demand and commercial intent. Cascade architecture, composed of retrieval, pre-ranking, and ranking stages, is usually adopted to reduce the computational cost. Each stage may employ various models for different obje

Cheng Peng, Jia Tian, Yingyu Yang

We study "half-wormhole-like" saddle point contributions to spectral correlators in a variety of ensemble average models, including various statistical models, generalized 0d SYK models, 1d Brownian SYK models and an extension of it. In statistical ensemble models, where more general distributions of the random variables could be studied in great det

Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng

Recent studies show that pre-trained language models (LMs) are vulnerable to textual adversarial attacks. However, existing attack methods either suffer from low attack success rates or fail to search efficiently in the exponentially large perturbation space. We propose an efficient and effective framework SemAttack to generate natural adversarial text by co

Philippe Boileau, Nina Ting Qi, Mark J. van der Laan, Sandrine Dudoit

An endeavor central to precision medicine is predictive biomarker discovery; they define patient subpopulations which stand to benefit most, or least, from a given treatment. The identification of these biomarkers is often the byproduct of the related but fundamentally different task of treatment rule estimation. Using treatment rule estimation methods to id

Yuya Murakami

In this paper, we prove a conjecture by Gukov-Pei-Putrov-Vafa for a wide class of plumbed 3-manifolds. Their conjecture states that Witten-Reshetikhin-Turaev (WRT) invariants are radial limits of homological blocks, which are $ q $-series introduced by them for plumbed 3-manifolds with negative definite linking matrices. The most difficult point in our proof

Jiping Luo, Tingting Zhang, Rui Hao, Donglin Li

Cooperative coordination at unsignalized road intersections, which aims to improve the driving safety and traffic throughput for connected and automated vehicles, has attracted increasing interests in recent years. However, most existing investigations either suffer from computational complexity or cannot harness the full potential of the road infrastructure

Ryan A. DeCrescent, Zixuan Wang, Poolad Imany, Robert C. Boutelle

Surface acoustic waves (SAWs) coupled to quantum dots (QDs), trapped atoms and ions, and point defects have been proposed as quantum transduction platforms, yet the requisite coupling rates and cavity lifetimes have not been experimentally established. Although the interaction mechanism varies, small acoustic cavities with large zero-point motion are require

Fangzhou Mu, Sicheng Mo, Jiayong Peng, Xiaochun Liu

Computational approach to imaging around the corner, or non-line-of-sight (NLOS) imaging, is becoming a reality thanks to major advances in imaging hardware and reconstruction algorithms. A recent development towards practical NLOS imaging, Nam et al. demonstrated a high-speed non-confocal imaging system that operates at 5Hz, 100x faster than the prior art.

Asadollah Bafekry, Mehrdad Faraji, Mohamed M. Fadlallah, I. Abdolhosseini Sarsari

Recently, reported a comments on the our paper [Appl. Phys. Lett. 119, 142102 (2021)]. With our response, the APL journal rejected their non scientific comments. There are some ambiguities about their claim: 1-They can check the phonon dispersion of their structure to see ZA out-of-plane mode. 2-They report the uniaxial stress-strain responses in Fig 2., whi

D. Alina, J. -Ph. Bernard, K. H. Yuen, A. Lazarian

Polarization of interstellar dust emission is a powerful probe of dust properties and magnetic field structure. Yet studies of external galaxies are hampered by foreground dust contribution. The aim of this study is to separate the polarised signal from the Large Magellanic Cloud (LMC) from that of the Milky Way (MW) in order to construct a wide-field, spati

Cheng-Lung Chen, Eduardo Pasiliao, Vladimir Boginski

The least cost influence maximization problem aims to determine minimum cost of partial (e.g., monetary) incentives initially given to the influential spreaders on a social network, so that these early adopters exert influence toward their neighbors and prompt influence propagation to reach a desired penetration rate by the end of cascading processes. We fir

Yihan Wang, Muyang Li, Han Cai, Wei-Ming Chen

Pose estimation plays a critical role in human-centered vision applications. However, it is difficult to deploy state-of-the-art HRNet-based pose estimation models on resource-constrained edge devices due to the high computational cost (more than 150 GMACs per frame). In this paper, we study efficient architecture design for real-time multi-person pose estim

Lister Staveley-Smith, Emma Bond, Kenji Bekki, Tobias Westmeier

A plausible formation scenario for the Galactic globular clusters 47 Tuc and Omega Cen is that they are tidally stripped remnants of dwarf galaxies, in which case they are likely to have retained a fraction of their dark matter cores. In this study, we have used the ultra-wide band receiver on the Parkes telescope (Murriyang) to place upper limits on the ann

Dechao Li, Mengying He

As the two basic fuzzy inference models, fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) have the important application in artificial intelligence. In order to solve FMP and FMT problems, Zadeh proposed a compositional rule of inference (CRI) method. This paper aims mainly to investigate the validity of A-compositional rule of inference (ACRI) method,

Adish Singla, Nikitas Theodoropoulos

Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need several compone

Hanxiu 'Hazel' Zhu, Shelly Shiying Cheng, Eugene Wu

Captions help readers better understand visualizations. However, if the visualization is intended to communicate specific features, should the caption be statistical, and focus on specific values, or perceptual, and focus on general patterns? Prior work has shown that when captions mention visually salient features, readers tend to recall those features. Sti

Jarrett L. Lancaster, Nicholas M. Palladino

A recent experiment testing the necessity of complex numbers in the standard formulation of quantum theory is recreated using IBM quantum computers. To motivate the experiment, we present a basic construction for real-valued quantum theory. The real-valued description is shown to predict correlations identical to those of complex-valued quantum mechanics for

Tian-Yu Ye, Li-Zhen Jiang

A large payload quantum steganography protocol based on cavity quantum electrodynamics (QED) is presented in the paper, which effectively uses the evolution law of atom in cavity QED. The protocol builds up hidden channel to transmit secret messages using entanglement swapping between one GHZ state and one Bell state in cavity QED together with the Hadamard

Yunan Zhang, Po-An Tsai, Hung-Wei Tseng

Matrix-multiplication units (MXUs) are now prevalent in every computing platform. The key attribute that makes MXUs so successful is the semiring structure, which allows tiling for both parallelism and data reuse. Nonetheless, matrix-multiplication is not the only algorithm with such attributes. We find that many algorithms share the same structure and diffe

Cheng-Hsien Yang, Shu-Tong Chang

The transition-metal dichalcogenide (TMDC) in the family of $\mathrm{MX}_2$ ($\mathrm{M}=\mathrm{Mo},\mathrm{W}$; $\mathrm{X}=\mathrm{S},\mathrm{Se}$) and the graphene monolayer are atomically thin semiconductors and semimetal, respectively. The monolayer $\mathrm{MX}_2$ have been discovered as a new class of semiconductors for electronics and optoelectronic

Stephanie Brandl, Daniel Hershcovich, Anders Søgaard

We argue that we need to evaluate model interpretability methods 'in the wild', i.e., in situations where professionals make critical decisions, and models can potentially assist them. We present an in-the-wild evaluation of token attribution based on Deep Taylor Decomposition, with professional journalists performing reliability assessments. We find

Matías Tailanian, Pablo Musé, Álvaro Pardo

Anomalies can be defined as any non-random structure which deviates from normality. Anomaly detection methods reported in the literature are numerous and diverse, as what is considered anomalous usually varies depending on particular scenarios and applications. In this work we propose an a contrario framework to detect anomalies in images applying statistica

Dinuka Ravijaya Piyadigama, Guhanathan Poravi

Recommendations Systems have been identified to be one of the integral elements of driving sales in e-commerce sites. The utilization of opinion mining data extracted from trends has been attempted to improve the recommendations that can be provided by baseline methods in this research when user-click data is lacking or is difficult to be collected due to pr

Ryota Moriguchi, Satoshi Tsutsui, Shun Katakami, Kenji Nagata

Mössbauer spectroscopy, which provides knowledge related to electronic states in materials, has been applied to various fields such as condensed matter physics and material sciences. In conventional spectral analyses based on least-square fitting, hyperfine interactions in materials have been determined from the shape of observed spectra. In conventional spe

Manuel Hinojosa, Ivan Garcia, Ignacio Rey-Stolle, Carlos Algora

Zinc-diffusion can induce multiple failures in the electrical performance of a multijunction solar cell. In this work, we show an important Zn-diffusion from the AlGaInP back-surface-field layer to the emitter of the GaInP top cell of an inverted multijunction solar cell. Through the analysis of different doping profiles, we provide strong evidence that the

Jingxuan Men, Yun Hou

The use case of C-V2X for road safety requires real-time network connection and information exchanging between vehicles. In order to improve the reliability and safety of the system, intelligent networked vehicles need to move cooperatively to achieve network optimization. In this paper, we use the C-V2X sidelink mode 4 abstraction and the regression results

Kalaharsha Pagadala

Now-a-days, cyberattacks are increasing at an unprecedented rate. Phishing is a social engineering attack which has a massive global impact, destroying the financial and economic value of corporations, government sectors and individuals. In phishing, attackers steal users personal information such as username, passwords, debit card information and so on. In

Abey S. Kelil, Appanah R. Appadu, Sama Arjika

In this paper, monic polynomials orthogonal with deformation of the Freud-type weight function are considered. These polynomials fullfill linear differential equation with some polynomial coefficients in their holonomic form. The aim of this work is explore certain characterizing properties of perturbed Freud type polynomials such as nonlinear recursion rela

Adam Hamilton, Matthew Roughan, Giang T. Nguyen

Firewall policies are an important line of defence in cybersecurity, specifying which packets are allowed to pass through a network and which are not. These firewall policies are made up of a list of interacting rules. In practice, firewall can consist of hundreds or thousands of rules. This can be very difficult for a human to correctly configure. One propo

Yun Li, Zhe Liu, Lina Yao, Molly Lucas

With the development of digital technology, machine learning has paved the way for the next generation of tinnitus diagnoses. Although machine learning has been widely applied in EEG-based tinnitus analysis, most current models are dataset-specific. Each dataset may be limited to a specific range of symptoms, overall disease severity, and demographic attribu

Yuxiang Feng, Weilin Xie, Yinxia Meng, Jiang Yang

Coherent fading has been regarded as a critical issue in phase-sensitive optical frequency domain reflectometry (ϕ-OFDR) based distributed fiber-optic sensing. Here, we report on an approach for fading noise suppression in ϕ-OFDR with multi-core fiber. By exploiting the independent nature of the randomness in the distribution of reflective index in each of t

Asher Yahalom

In this paper we represent a different approach to the calculation of the perihelion shift than the one presented in common text books. We do not rely on the Schwarzschild metric and the Hamilton Jacobi technique to obtain our results. Instead we use a weak field approximation, with the advantage that we are not obliged to work with a definite static metric

Sunil Gundapu, Radhika Mamidi

The exponential rise of social media networks has allowed the production, distribution, and consumption of data at a phenomenal rate. Moreover, the social media revolution has brought a unique phenomenon to social media platforms called Internet memes. Internet memes are one of the most popular contents used on social media, and they can be in the form of im

Qiuyi Wu, Julie Bessac, Whitney Huang, Jiali Wang

This study develops a statistical conditional approach to evaluate climate model performance in wind speed and direction and to project their future changes under the representative concentration pathway 8.5 scenario over inland and offshore locations across the Continental United States. The proposed conditional approach extends the scope of existing studie

Mathieu Cura, Katarina Firdova, Céline Labart, Arthur Martel

In this paper we describe an approach for anomaly detection and its explainability in multivariate functional data. The anomaly detection procedure consists of transforming the series into a vector of features and using an Isolation forest algorithm. The explainable procedure is based on the computation of the SHAP coefficients and on the use of a supervised

Ruben Tolosana, Ruben Vera-Rodriguez, Julian Fierrez, Javier Ortega-Garcia

Architectures based on Recurrent Neural Networks (RNNs) have been successfully applied to many different tasks such as speech or handwriting recognition with state-of-the-art results. The main contribution of this work is to analyse the feasibility of RNNs for on-line signature verification in real practical scenarios. We have considered a system based on Lo

Jean-Pierre Magnot

The works prsented in this habilitation thesis can be gathered in six themes. Works on the implicit function theorem and the geometry of numerical schemes. On the existence of an exponential map on an infinite dimensioal Lie group. Holonomy and Ambrose-Singer theorem for connections on infinite dimensional principal bundles. Results on integration theory and

Alex Mendez, Mohammad Farazmand

Spotting refers to the transport of burning pieces of firebrand by wind which, at the time of landing, may ignite new fires beyond the direct ignition zone of the main fire. Spot fires that occur far from the original burn unit are rare but have consequential ramifications since their prediction and control remains challenging. To facilitate their prediction

Ling-Ze Bu, Wei Wang

To improve the computational efficiencies of the real-space orbital-free density functional theory, this work develops a new single-grid solver by directly providing the closed-form solution to the inner iteration and using an improved bisection method to accelerate the line search process in the outer iteration, and extended the single-grid solver to a mult

Wajiha Javed, Sibgha Riaz, Ali Övgün

In this paper, we examine the weak deflection angle and greybody bound for magnetized regular black hole.$~$ For this purpose, we apply the Gauss-Bonnet theorem on the black hole and obtain the deflection angle in plasma and non-plasma mediums.$~$ Moreover, we investigate graphically the effect of impact parameter on the deflection angle for regular black ho

Tongjun Liu, Jun-Yu Ou, Nikitas Papasimakis, Kevin F. MacDonald

Flexural oscillations of free-standing films, nano-membranes and nano-wires are attracting growing attention for their importance to the thermal, electrical and mechanical properties of 2D materials. Here we report on the observation of short-timescale ballistic motion in the flexural mode of a nano-membrane cantilever, driven by thermal fluctuation of flexu

Basil Duvernoy, Sarah McIntyre

The main objective of this study is to investigate whether one can use recordings of human-to-human touch, such as a caress, to improve tactile apparent motion interfaces to make them feel more natural. We report here preliminary recordings of natural and continuous human-to-human caresses. To do this, six accelerometers were positioned on the receiving hand

R. Balaji, Vinayak Gupta

Distance matrices of some star like graphs are investigated in \cite{JAK}. These graphs are trees which are stars, wheel graphs, helm graphs and gear graphs. Except for gear graphs in the above list of star like graphs, there are precise formulas available in the literature to compute the inverse/Moore-Penrose inverse of their distance matrices. These formul

Marita Kuhlmann

In practice, the value-at-risk (VaR) for a longer holding period is often scaled using the 'square root of time rule'. The VaR is determined for a shorter holding period and then scaled up according to the desired holding period. For example, the Basel rules allow banks to scale up the 1-day VaR by the square root of ten to determine the 10-day VaR.

Zhengyu Yue, Yuanzhi Yao, Weihai Li, Nenghai Yu

With the rapid development of general cloud services, more and more individuals or collectives use cloud platforms to store data. Assured data deletion deserves investigation in cloud storage. In time-sensitive data storage scenarios, it is necessary for cloud platforms to automatically destroy data after the data owner-specified expiration time. Therefore,

Yajing Feng, Qian Hu, Zhenzhou Tang

Vacant parking space (VPS) prediction is one of the key issues of intelligent parking guidance systems. Accurately predicting VPS information plays a crucial role in intelligent parking guidance systems, which can help drivers find parking space quickly, reducing unnecessary waste of time and excessive environmental pollution. Through the simple analysis of

Yufei Tian, Nanyun Peng

Poetry generation, and creative language generation in general, usually suffers from the lack of large training data. In this paper, we present a novel framework to generate sonnets that does not require training on poems. We design a hierarchical framework which plans the poem sketch before decoding. Specifically, a content planning module is trained on non

Colin G. West

A considerable share of the literature on physics education and on education more broadly focuses on the principles which should guide the design of courses and of classroom activities. In this short article I wish to place more attention on the unplanned aspects of teaching: specifically, the spontaneous interactions that occur between instructors and stude

Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor

The Covid-19 pandemic has led to infodemic of low quality information leading to poor health decisions. Combating the outcomes of this infodemic is not only a question of identifying false claims, but also reasoning about the decisions individuals make. In this work we propose a holistic analysis framework connecting stance and reason analysis, and fine-grai

Matthew Fong, Jiaxin Han, Jun Zhang, Xiaohu Yang

We use weak lensing observations to make the first measurement of the characteristic depletion radius, one of the three radii that characterize the region where matter is being depleted by growing haloes. The lenses are taken from the halo catalog produced by the extended halo-based group/cluster finder applied to DESI Legacy Imaging Surveys DR9, while the s

John Rodman, Petr Cagas, Ammar Hakim, Bhuvana Srinivasan

Rayleigh-Taylor (RT) instabilities are prevalent in many physical regimes ranging from astrophysical to laboratory plasmas and have primarily been studied using fluid models, the majority of which have been ideal fluid models. This work is the first of its kind to present a 5-dimensional (2 spatial dimensions, 3 velocity space dimensions) simulation using th

Kenichi Yoshida

Ground-state moments of inertia (MoI) are investigated for about 1700 even-even nuclei from the proton drip line to the neutron drip line up to $Z=120$ and $N=184$. The cranked Skyrme-Hartree-Fock-Bogoliubov equation is solved in the coordinate space. This model describes well the available experimental data of more than 300 nuclides possessing an appreciabl

Franz Klein, Shweta Mahajan, Stefan Roth

Stylized image captioning as presented in prior work aims to generate captions that reflect characteristics beyond a factual description of the scene composition, such as sentiments. Such prior work relies on given sentiment identifiers, which are used to express a certain global style in the caption, e.g. positive or negative, however without taking into ac

Athiya Deviyani

A biased dataset is a dataset that generally has attributes with an uneven class distribution. These biases have the tendency to propagate to the models that train on them, often leading to a poor performance in the minority class. In this project, we will explore the extent to which various data augmentation methods alleviate intrinsic biases within the dat

Helei Duan, Ashish Malik, Mohitvishnu S. Gadde, Jeremy Dao

In this work, we propose a learning approach for 3D dynamic bipedal walking when footsteps are constrained to stepping stones. While recent work has shown progress on this problem, real-world demonstrations have been limited to relatively simple open-loop, perception-free scenarios. Our main contribution is a more advanced learning approach that enables real

Emily R. Bartusiak, Edward J. Delp

Attackers may manipulate audio with the intent of presenting falsified reports, changing an opinion of a public figure, and winning influence and power. The prevalence of inauthentic multimedia continues to rise, so it is imperative to develop a set of tools that determines the legitimacy of media. We present a method that analyzes audio signals to determine

Emily R. Bartusiak, Sri Kalyan Yarlagadda, David Güera, Paolo Bestagini

The widespread availability of image editing tools and improvements in image processing techniques allow image manipulation to be very easy. Oftentimes, easy-to-use yet sophisticated image manipulation tools yields distortions/changes imperceptible to the human observer. Distribution of forged images can have drastic ramifications, especially when coupled wi

Michael W. Robbins, Sebastian Bauhoff, Lane Burgette

Policymakers often require information on programs' long-term impacts that is not available when decisions are made. We demonstrate how data fusion methods may be used address the problem of missing final outcomes and predict long-run impacts of interventions before the requisite data are available. We implement this method by concatenating data on an in

Dinuka Ravijaya Piyadigama, Guhanathan Poravi

Recommendations Systems allow users to identify trending items among a community while being timely and relevant to the user's expectations. When the purpose of various Recommendation Systems differs, the required type of recommendations also differs for each use case. While one Recommendation System may focus on recommending popular items, another may f

Nicholas Pischke

We provide quantitative information in the form of a rate of metastability in the sense of T. Tao and (under a metric regularity assumption) a rate of convergence for an algorithm approximating zeros of differences of maximally monotone operators due to A. Moudafi by using techniques from `proof mining', a subdiscipline of mathematical logic. For the rat

Emily R. Bartusiak, Edward J. Delp

Synthesized speech is common today due to the prevalence of virtual assistants, easy-to-use tools for generating and modifying speech signals, and remote work practices. Synthesized speech can also be used for nefarious purposes, including creating a purported speech signal and attributing it to someone who did not speak the content of the signal. We need me

Kathryn M. Zurek

This short review is intended as a colloquium-level summary, for the Snowmass 2021 process, on recent theoretical results on infrared observables in quantum gravity. We rely on simple physical arguments, most notably a random walk intuition, to show how effects of quantum gravity in the ultraviolet (at the Planck length $\ell_p \approx 10^{-35} \mbox{ m}$) m

Tea Temim, Patrick Slane, John C. Raymond, Daniel Patnaude

We present a study of the Galactic supernova remnant (SNR) G292.0+1.8, a classic example of a core-collapse SNR that contains oxygen-rich ejecta, circumstellar material, a rapidly moving pulsar, and a pulsar wind nebula (PWN). We use hydrodynamic simulations of the remnant evolution to show that the SNR reverse shock is interacting with the PWN and has most

Lei Yang, Yossi Gilad, Mohammad Alizadeh

High-throughput blockchains require efficient transaction broadcast mechanisms that can deliver transactions to most network nodes with low bandwidth overhead and latency. Existing schemes coordinate transmissions across peers to avoid sending redundant data, but they either incur a high latency or are not robust against adversarial network nodes. We present

Fran Herr, Legrand Jones

The jump graph $J(G)$ of a simple graph $G$ has vertices which represent edges in $G$ where two vertices in $J(G)$ are adjacent if and only if the corresponding edges in $G$ do not share an endpoint. In this paper, we examine sequences of graphs generated by iterating the jump graph operation and characterize the behavior of this sequence for all initial gra

Hyung Park, Danni Wu, Eva Petkova, Thaddeus Tarpey

The general idea of this article is to develop a Bayesian model with a flexible link function connecting an exponential family treatment response to a linear combination of covariates and a treatment indicator and the interaction between the two. Generalized linear models allowing data-driven link functions are often called "single-index models," and

Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry

This paper considers meta-cognitive radars in an adversarial setting. A cognitive radar optimally adapts its waveform (response) in response to maneuvers (probes) of a possibly adversarial moving target. A meta-cognitive radar is aware of the adversarial nature of the target and seeks to mitigate the adversarial target. How should the meta-cognitive radar ch

Rahnuma Rahman, Supriyo Bandyopadhyay

Binary stochastic neurons (BSNs) are excellent hardware accelerators for machine learning. A popular platform for implementing them are low- or zero-energy barrier nanomagnets possessing in-plane magnetic anisotropy (e.g. circular disks or quasi-elliptical disks with very small eccentricity). Unfortunately, small geometric variations in the lateral shapes of

Laurent Bartholdi, Volodymyr Nekrashevych, Tianyi Zheng

We introduce a new method of proving upper estimates of growth of finitely generated groups and constructing groups of intermediate growth using graphs of their actions. These estimates are of the form $\exp(n^α)$ for some $α<1$, and provide the first examples of such bounds for simple groups of intermediate growth.

Samuel Triest, Matthew Sivaprakasam, Sean J. Wang, Wenshan Wang

We present TartanDrive, a large scale dataset for learning dynamics models for off-road driving. We collected a dataset of roughly 200,000 off-road driving interactions on a modified Yamaha Viking ATV with seven unique sensing modalities in diverse terrains. To the authors&#39; knowledge, this is the largest real-world multi-modal off-road driving dataset, b

Zeric Tabekoueng Njitacke, Sishu Shankar Muni, Soumyajit Seth, Jan Awrejcewicz

In this contribution, we have considered the collective behavior of the two as well as the network of heterogeneous coupled Hindmarsh Rose (HR) neurons. The heterogeneous models were made of a memristive 2D (HR) and the traditional 3D HR neurons. Investigating a model of two coupled neurons through an electrical synapse reveals dissipative properties. When c

Rohan Srivastava

The purpose of this paper is to provide an introductory overview of the large cardinal hierarchy in set theory. By a large cardinal, we mean any cardinal $κ$ whose existence is strong enough of an assumption to prove the consistency of ZFC. We assume basic familiarity with set theory, model theory, and the ZFC axioms, though certain concepts will be reviewed

Laura D. Geulig, Lieselotte Obst-Huebl, Kei Nakamura, Jianhui Bin

Laser-driven ion beams have gained considerable attention for their potential use in multidisciplinary research and technology. Pre-clinical studies into their radiobiological effectiveness have established the prospect of using laser-driven ion beams for radiotherapy. In particular, research into the beneficial effects of ultra-high instantaneous dose rates

Charles J. Law, Sage Crystian, Richard Teague, Karin I. Öberg

High spatial resolution CO observations of mid-inclination (30-75°) protoplanetary disks offer an opportunity to study the vertical distribution of CO emission and temperature. The asymmetry of line emission relative to the disk major axis allows for a direct mapping of the emission height above the midplane, and for optically-thick, spatially-resolved emiss

Stefano Cipolla, Jacek Gondzio

In this work, in the context of Linear and Quadratic Programming, we interpret Primal Dual Regularized Interior Point Methods (PDR-IPMs) in the framework of the Proximal Point Method. The resulting Proximal Stabilized IPM (PS-IPM) is strongly supported by theoretical results concerning convergence and the rate of convergence, and can handle degenerate proble

Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

Let $X$ be a random vector valued in $\mathbb{R}^{m}$ such that $\|X\|_{2} \le 1$ almost surely. For every $k\ge 3$, we show that there exists a sigma algebra $\mathcal{F}$ generated by a partition of $\mathbb{R}^{m}$ into $k$ sets such that \[\|\operatorname{Cov}(X) - \operatorname{Cov}(\mathbb{E}[X\mid\mathcal{F}]) \|_{\mathrm{F}} \lesssim \frac{1}{\sqrt{\

İzzet Sakallı, Sara Kanzi

We give a pedagogical introduction to black holes (BHs) greybody factors (GFs) and quasinormal modes (QNMs) and share the recent developments on those subjects. In this study, our primary focus will be on the bosonic and fermionic GFs and QNMs of various BH and brane geometries and reveal the fingerprints of the invisibles with the radiation spectra to be ob

Zihao Chen, Yuhua Chen, Yibin Xie, Debiao Li

Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application. Data-consistent (DC) deep learning can accelerate reconstruction with good image quality, but has not been formulated for non-Cartesian subspace imaging. In this study, we propose a DC

Tianchen Ji, Roy Dong, Katherine Driggs-Campbell

The number of multi-robot systems deployed in field applications has increased dramatically over the years. Despite the recent advancement of navigation algorithms, autonomous robots often encounter challenging situations where the control policy fails and the human assistance is required to resume robot tasks. Human-robot collaboration can help achieve high

Adam R. Kobelski, Lucas A. Tarr, Sarah A. Jaeggli, Nicholas Luber

New instruments sensitive to chromospheric radiation at X-ray, UV, Visible, IR, and sub-mm wavelengths have become available that significantly enhance our ability to understand the bi-directional flow of energy through the chromosphere. We describe the calibration, co-alignment, initial results, and public release of a new data set combining a large number

Osvaldo Chandia, Brenno Carlini Vallilo

We study supersymmetry conditions for the heterotic pure superstring preserving and N=1 supersymmetry in four dimensions directly from the curved superspace defined by the Berkovits-Howe constraints.

Z. Y. Zhao, S. Calder, H. D. Zhou, Z. Z. He

In this work, a temperature-induced valence-state transition is studied in a narrow composition range of Ba$_{2-x}$Sr$_x$TbIrO$_6$. The valence-state transition involves an electron transfer between Tb and Ir leading to the valence-state change between Tb$^{3+}$/Ir$^{5+}$ and Tb$^{4+}$/Ir$^{4+}$ phases. This first-order transition has a dramatic effect on th

Shuo Zhang, Mu-Chun Wang, Krisztian Balog

User simulation has been a cost-effective technique for evaluating conversational recommender systems. However, building a human-like simulator is still an open challenge. In this work, we focus on how users reformulate their utterances when a conversational agent fails to understand them. First, we perform a user study, involving five conversational agents

E. C. Aschenauer, V. Batozskaya, S. Fazio, K. Gates

We present the EpIC Monte Carlo event generator for exclusive processes sensitive to generalised parton distributions. EpIC utilises the PARTONS framework, which provides a flexible software architecture and a variety of modelling options for the partonic description of the nucleon. The generator offers a comprehensive set of features, including multi-channe

Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin

We present a method for differentiable simulation of soft articulated bodies. Our work enables the integration of differentiable physical dynamics into gradient-based pipelines. We develop a top-down matrix assembly algorithm within Projective Dynamics and derive a generalized dry friction model for soft continuum using a new matrix splitting strategy. We de

Yuwei Cao, William Groves, Tanay Kumar Saha, Joel R. Tetreault

Temporal Expression Extraction (TEE) is essential for understanding time in natural language. It has applications in Natural Language Processing (NLP) tasks such as question answering, information retrieval, and causal inference. To date, work in this area has mostly focused on English as there is a scarcity of labeled data for other languages. We propose XL

Alarith Uhde, Mena Mesenhöller, Marc Hassenzahl

Studying how social contexts shape technology interactions and how we experience them is hard. One challenge is that social contexts are very dynamic and shaped by the situated practices of everyone involved. As a result, the same human-technology interaction can be experienced quite differently depending on what other people around us do. As a first step to

David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan

High-throughput virtual screening is an indispensable technique utilized in the discovery of small molecules. In cases where the library of molecules is exceedingly large, the cost of an exhaustive virtual screen may be prohibitive. Model-guided optimization has been employed to lower these costs through dramatic increases in sample efficiency compared to ra

Luca Di Persio, Yuri Kondratiev, Viktorya Vardanyan

We study stochastic differential equations(SDEs) with a small perturbation parameter. Under the dissipative condition on the drift coefficient and the local Lipschitz condition on the drift and diffusion coefficients we prove the existence and uniqueness result for the perturbed SDE, also the convergence result for the solution of the perturbed system to the