May 2023 arXiv papers — page 177

Sorin G. Gal

In this paper we obtain several extension properties for monotone and sublinear operators. The results obtained generalize those known for positive and linear operators.

Christopher P. J. O'Connor, Sebastian Wieczorek, Andreas Amann

We introduce a formalism to efficiently calculate lasing modes and optical power flow in multi-section lasers with open boundaries. The formalism is underpinned by a projection of the complex-valued electric field and its spatial derivative onto a suitably extended complex $\mathcal{Z}$-plane, to reduce the order of the problem and simplify analysis. In a si

Jakob Bæk Tejs Houen, Mikkel Thorup

The \emph{Sparse Johnson-Lindenstrauss Transform} of Kane and Nelson (SODA 2012) provides a linear dimensionality-reducing map $A \in \mathbb{R}^{m \times u}$ in $\ell_2$ that preserves distances up to distortion of $1 + \varepsilon$ with probability $1 - δ$, where $m = O(\varepsilon^{-2} \log 1/δ)$ and each column of $A$ has $O(\varepsilon m)$ non-zero entr

Ludger O. Suarez-Burgoa

The saltbox-roof parametric probability distribution is a special case of the triangular distribution, where only one side is truncated. Here it is presented as a single and independent distribution, where the explicit equations are defined for its probability density--, the cumulative distribution--, and the inverse of the cumulative distribution (quantile-

Delia Garijo, Andrew Goodall, Lluís Vena

We extend the notion of graph homomorphism to cellularly embedded graphs (maps) by designing operations on vertices and edges that respect the surface topology; we thus obtain the first definition of map homomorphism that preserves both the combinatorial structure (as a graph homomorphism) and the topological structure of the surface (in particular, orientab

Thea H. Faridani, Smadar Naoz, Gongjie Li, Nicholas Inzunza

Short and ultra-short planets are a peculiar type of exoplanets with periods as short as a few days or less. Although it is challenging to detect them, already several are observed with many additional candidates. If these planets have formation pathways to their longer period counterparts, they are predicted to reside in multi-planet systems. Thus, gravitat

Friedrich Menhorn, Gianluca Geraci, D. Thomas Seidl, Youssef M. Marzouk

Optimization is a key tool for scientific and engineering applications, however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several desi

Akitaka Ariga, Reuven Balkin, Iftah Galon, Enrique Kajomovitz

Only two types of Standard Model particles are able to propagate the $480\,$meters separating the ATLAS interaction point and FASER: neutrinos and muons. Furthermore, muons are copiously produced in proton collisions. We propose to use FASER$ν$ as a muon fixed target experiment in order to search for new bosonic degrees of freedom coupled predominantly to mu

Yun Tang, Anna Y. Sun, Hirofumi Inaguma, Xinyue Chen

Transducer and Attention based Encoder-Decoder (AED) are two widely used frameworks for speech-to-text tasks. They are designed for different purposes and each has its own benefits and drawbacks for speech-to-text tasks. In order to leverage strengths of both modeling methods, we propose a solution by combining Transducer and Attention based Encoder-Decoder

Michael A Kouritzin, Stephen Styles, Beatrice-Helen Vritsiou

Training a neural network (NN) typically relies on some type of curve-following method, such as gradient descent (GD) (and stochastic gradient descent (SGD)), ADADELTA, ADAM or limited memory algorithms. Convergence for these algorithms usually relies on having access to a large quantity of observations in order to achieve a high level of accuracy and, with

Bastián Espinoza

An idea that became unavoidable to study zero entropy symbolic dynamics is that the dynamical properties of a system induce in it a combinatorial structure. An old problem addressing this intuition is finding a structure theorem for linear-growth complexity subshifts using the S-adic formalism. It is known as the S-adic conjecture and motivated several influ

Víctor Hernández-Santamaría, Alberto Peña-García

The shadow limit is a versatile tool used to study the reduction of reaction-diffusion systems into simpler PDE-ODE models by letting one of the diffusion coefficients tend to infinity. This reduction has been used to understand different qualitative properties and their interplay between the original model and its reduced version. The aim of this work is to

Shuvankar Gupta, Sudip Chakraborty, Santanu Pakhira, Anis Biswas

The realization of spin-glass (S-G) state in Heusler alloys is very rare despite the presence of inherent structural and elemental disorder in those compounds. Although a few half and full Heusler alloys are known to exhibit S-G state, there is hardly any manifestation of the same in cases of quaternary Heusler compounds. Here we report the observation of S-

Breandan Considine, Nicholas Albion, Xujie Si

This paper presents Idiolect, an open source (https://github.com/OpenASR/idiolect) IDE plugin for voice coding and a novel approach to building bots that allows for users to define custom commands on-the-fly. Unlike traditional chatbots, Idiolect does not pretend to be an omniscient virtual assistant but rather a reconfigurable voice programming system that

Xuan Long Do, Bowei Zou, Shafiq Joty, Anh Tai Tran

Conversational Question Generation (CQG) is a critical task for machines to assist humans in fulfilling their information needs through conversations. The task is generally cast into two different settings: answer-aware and answer-unaware. While the former facilitates the models by exposing the expected answer, the latter is more realistic and receiving grow

Jeremy Sakstein, Ippocratis D. Saltas

It has been hypothesized that dark matter is comprised of ultra-light bosons whose collective phenomena can be described as a scalar field undergoing coherent oscillations. Examples include axion and fuzzy dark matter models. In this ultra-light dark matter scenario, the harmonic variation in the field's energy-momentum tensor sources an oscillating comp

E. Karagoz, N. Alan, S. Bilir, S. Ak

We perform extensive spectroscopy of the supernova remnant N63A in the Large Magellanic Cloud, using $\sim 43$ ks {\it Chandra} archival data. By analysing the spectra of the entire remnant, we determine the abundance distributions for O, Ne, Mg, Si, and Fe. We detect evidence of enhanced O and possibly Ne and Mg in some of the central regions which might in

Vitaly V. Chaban

The concentration of carbon dioxide (CO2) in the Earth atmosphere is linked to the acute problem of global warming. For the first time, we herein introduce trialkylsulfonium aprotic ionic liquids (ILs) as a group of seemingly highly capacitive CO2 scavengers. We advocate the viability of the new sorbents by the reaction profiles recorded by means of hybrid d

Tiina Liimets, Michaela Kraus, Lydia Cidale, Sergey Karpov

Z Canis Majoris is a fascinating early-type binary with a Herbig Be primary and a FU Orionis-type secondary. Both of the stars exhibit sub-arcsecond jet-like ejecta. In addition, the primary is associated with the extended jet as well as with the large-scale outflow. In this study, we investigate further the nature of the large-scale outflow, which has not b

Uri Zvi, Denis R. Candido, Adam Weiss, Aidan R. Jones

Diamond nanocrystals can harbor spin qubit sensors capable of probing the physical properties of biological systems with nanoscale spatial resolution. These diamond nanosensors can readily be delivered into intact cells and even living organisms. However, applications beyond current proof-of-principle experiments require a substantial increase in sensitivity

Ludger O. Suarez-Burgoa

This note presents the definition of a proposed generalization of the conchoid at the plane. Known conchoids, such as the Nicomedes and the Limaçon of Pascal are part of this set. Following the definition, one can generate other conchoids. Examples are generated using of a computer code that is available openly for download. In addition, two step-by-step exa

Adam Hibberd

In preceding papers, Project Lyra has covered many possible trajectory options available to a spacecraft bound for 1I/Oumuamua, including Solar Oberth manoeuvres, Passive Jupiter encounters, Jupiter Oberths, Double Jupiter Gravitational Assists, etc. Because feasibility was the key driver for this analysis, the important question of which launcher to exploit

Christopher Scherb, Luc Bryan Heitz, Frank Grimberg, Hermann Grieder

With the rising number of cyberattacks, such as ransomware attacks and cyber espionage, educating non-cybersecurity professionals to recognize threats has become more important than ever before. However, traditional training methods, such as phishing awareness campaigns, training videos and assessments have proven to be less effective over time. Therefore, i

Xiaozhao Liu, Mianxin Liu, Lang Mei, Yuyao Zhang

To characterize atypical brain dynamics under diseases, prevalent studies investigate functional magnetic resonance imaging (fMRI). However, most of the existing analyses compress rich spatial-temporal information as the brain functional networks (BFNs) and directly investigate the whole-brain network without neurological priors about functional subnetworks.

Wei Gong, Le Liu

The aim of this paper is to study the shape optimization method for solving the Bernoulli free boundary problem, a well-known ill-posed problem that seeks the unknown free boundary through Cauchy data. Different formulations have been proposed in the literature that differ in the choice of the objective functional. Specifically, it was shown respectively in

Basile Van Hoorick, Pavel Tokmakov, Simon Stent, Jie Li

Tracking objects with persistence in cluttered and dynamic environments remains a difficult challenge for computer vision systems. In this paper, we introduce $\textbf{TCOW}$, a new benchmark and model for visual tracking through heavy occlusion and containment. We set up a task where the goal is to, given a video sequence, segment both the projected extent

Ruihan Gao, Wenzhen Yuan, Jun-Yan Zhu

Deep generative models have various content creation applications such as graphic design, e-commerce, and virtual Try-on. However, current works mainly focus on synthesizing realistic visual outputs, often ignoring other sensory modalities, such as touch, which limits physical interaction with users. In this work, we leverage deep generative models to create

Kazunori Asakura, Kiyoshi Hayashida, Tomoki Kawabata, Yoneyama Tomokage

We propose a novel x-ray imaging system, Multi-Image X-ray Interferometer Module (MIXIM), with which a very high angular resolution can be achieved even with a small system size. MIXIM is composed of equally-spaced multiple slits and an x-ray detector, and its angular resolution is inversely proportional to the distance between them. Here we report our evalu

Jun-Kun Chen, Jipeng Lyu, Yu-Xiong Wang

This paper proposes NeuralEditor that enables neural radiance fields (NeRFs) natively editable for general shape editing tasks. Despite their impressive results on novel-view synthesis, it remains a fundamental challenge for NeRFs to edit the shape of the scene. Our key insight is to exploit the explicit point cloud representation as the underlying structure

Louis Hainaut, Dan Petersen

We show that a certain locus inside the moduli space $M_g$ of hyperbolic surfaces, given by surfaces with "sufficiently many" short geodesics, is a classifying space of the handlebody mapping class group. A consequence of the construction is that the top weight cohomology of $M_g$, studied by Chan-Galatius-Payne, maps injectively into the cohomology

Connor Z. Lin, Koki Nagano, Jan Kautz, Eric R. Chan

There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for editing and animation, and robustness for single-view face reconstruction, they cannot easily capture geometric and appearance details. Methods based on neural implicit representatio

Hagen Muenkler, Hubert Misztela, Michal Pikusa, Marwin Segler

Many contemporary generative models of molecules are variational auto-encoders of molecular graphs. One term in their training loss pertains to reconstructing the input, yet reconstruction capabilities of state-of-the-art models have not yet been thoroughly compared on a large and chemically diverse dataset. In this work, we show that when several state-of-t

Qimiao Si, Nigel E. Hussey

The advent of iron-based superconductors in 2008 came as a complete surprise to the condensed matter community. Now 15 years later, they are beginning to impart some of their new-found wisdom on a slew of emerging superconductors that boast similar traits.

Shengcao Cao, Dhiraj Joshi, Liang-Yan Gui, Yu-Xiong Wang

Object detectors often suffer from the domain gap between training (source domain) and real-world applications (target domain). Mean-teacher self-training is a powerful paradigm in unsupervised domain adaptation for object detection, but it struggles with low-quality pseudo-labels. In this work, we identify the intriguing alignment and synergy between mean-t

Pasquale Di Bari

A solution to the problem of the origin of matter in the universe can be reasonably searched within extensions of the standard model that also explain neutrino masses and mixing. Models embedding the minimal seesaw mechanism can explain the observed matter-antimatter asymmetry of the universe via leptogenesis and dark matter via active-sterile neutrino mixin

Shirantha Welikala, Hai Lin, Panos J. Antsaklis

In this paper, we consider networked systems comprised of interconnected sets of linear subsystems and propose a decentralized and compositional approach to stabilize or dissipativate such linear networked systems via optimally modifying some existing interconnections and/or creating entirely new interconnections. We also extend this interconnection topology

Jonne Sälevä, Constantine Lignos

We introduce three simple randomized variants of byte pair encoding (BPE) and explore whether randomizing the selection of merge operations substantially affects a downstream machine translation task. We focus on translation into morphologically rich languages, hypothesizing that this task may show sensitivity to the method of choosing subwords. Analysis usi

Richard D. Gill

Kupczynski (2023) claims that Gill and Lambare (2022a, 2022b) misrepresent several of his published papers. This paper shows that the latest version of his "contextuality by default" model of a Bell experiment places no constraints whatsoever on the statistics of observed results in Bell type experiments. It thereby effectively allows arbitrary non-l

Fangkai Jiao, Bosheng Ding, Tianze Luo, Zhanfeng Mo

This project focuses on enhancing open-source large language models through instruction-tuning and providing comprehensive evaluations of their performance. We explore how various training data factors, such as quantity, quality, and linguistic distribution, influence the performance of instruction-tuned models trained on publicly accessible high-quality ins

Michael DeMarco, Ethan Lake, Xiao-Gang Wen

Chiral field theories describe large classes of matter, from the edges of Quantum Hall systems to the electroweak sector of the Standard Model, but defining them on the lattice has been an ongoing challenge due to a no-go theorem precluding free local models, the potential of symmetry anomalies, and sign problems. Some approaches define a $1+1$d chiral field

Vivek Sridhar, Keyvan Shahin, Michael Breuß, Marc Reichenbach

In this paper we consider the fundamental operations dilation and erosion of mathematical morphology. Many powerful image filtering operations are based on their combinations. We establish homomorphism between max-plus semi-ring of integers and subset of polynomials over the field of real numbers. This enables to reformulate the task of computing morphologic

Davi Castro-Silva

We study the interplay between notions of quasirandomness for additive sets and for hypergraphs. In particular, we show a strong connection between the notions of Gowers uniformity in the additive setting and discrepancy-type measures of quasirandomness in the hypergraph setting. Exploiting this connection, we provide a long list of disparate quasirandom pro

Cansu Özdemir, Ilmar Gahramanov

We review the Yang-Baxterization process of braid group representations. We discuss the corresponding $n$-CB algebras in the Yang-Baxterization process. We present diagrams of the relations for the $4$-CB algebras. These relations are illustrated using the isomorphism between the general free algebra generated by $\{1\}$, $\{E_i\}$, and $\{G_i\}$ and Kauffma

Haoran Li, Mingshi Xu, Yangqiu Song

Sentence-level representations are beneficial for various natural language processing tasks. It is commonly believed that vector representations can capture rich linguistic properties. Currently, large language models (LMs) achieve state-of-the-art performance on sentence embedding. However, some recent works suggest that vector representations from LMs can

James Gung, Emily Moeng, Wesley Rose, Arshit Gupta

Despite growing interest in applications based on natural customer support conversations, there exist remarkably few publicly available datasets that reflect the expected characteristics of conversations in these settings. Existing task-oriented dialogue datasets, which were collected to benchmark dialogue systems mainly in written human-to-bot settings, are

José Pereira Amorim, Pedro Henriques Abreu, João Santos, Henning Müller

Despite Convolutional Neural Networks having reached human-level performance in some medical tasks, their clinical use has been hindered by their lack of interpretability. Two major interpretability strategies have been proposed to tackle this problem: post-hoc methods and intrinsic methods. Although there are several post-hoc methods to interpret DL models,

François Brunault

We prove a conjecture of Boyd and Rodriguez Villegas relating the Mahler measure of the polynomial $(1+x)(1+y)+z$ and the value at $s=3$ of the $L$-function of an elliptic curve of conductor $15$. The proof makes use of the computation by Zudilin and the author of the regulator of certain $K_4$ classes on modular curves.

Michael Wessel

I recently consulted for a very big Common Lisp project having more than one million lines of code (including comments). Let's call it "System X" in the following. System X suffered from extremely long compilation times; i.e., a full recompile took about 33:17 minutes on a 3.1 GHz MacBook Pro Intel Core i7 with SSD and 16 GBs of RAM, using ACL 10

Ankush Goswami, Timothy Huber

An infinite class of relations between modular forms is constructed that generalizes evaluations of the Dirichlet beta function at odd positive integers. The work is motivated by a base case appearing in Ramanujan's Notebooks and a parallel construction for the Riemann zeta function. The identities are shown to be strong $q$-analogues by virtue of their

Elfarouk Harb, Kent Quanrud, Chandra Chekuri

Boob et al. [1] described an iterative peeling algorithm called Greedy++ for the Densest Subgraph Problem (DSG) and conjectured that it converges to an optimum solution. Chekuri, Quanrud, and Torres [2] extended the algorithm to general supermodular density problems (of which DSG is a special case) and proved that the resulting algorithm Super-Greedy++ (and

Piotr Krylov, Askar Tuganbaev

We study automorphisms, isomorphisms, and derivations of the incidence algebra $I(X,R)$, where $X$ is preordered set and $R$ is an algebra over some commutative ring $T$.

Jae-Woo Lee

We present a multiple stellar population study of the metal-poor globular cluster (GC) M92 (NGC 6341), which is long known for the substantial metallicity dispersion, using our own photometric system. We find two groups with slightly different mean metallicities, the metal-poor (MP) stars with [Fe/H] = $-$2.412$\pm$0.03, while the metal-rich (MR) ones with $

Cristina Gena, Rossana Damiano, Claudio Mattutino, Alessandro Mazzei

This extended abtract describes the preliminary qualitative results coming from a therapeutic laboratory focused on the use of the Pepper robot to promote autonomies and functional acquisitions in highly functioning (Asperger) children with autism. The field lab, ideated and led by a multidisciplinary team, involved 4 children, aged 11-13, who attended the l

Anna Beliakova, Matthew Hogancamp, Krzysztof Karol Putyra, Stephan Martin Wehrli

We show that the Khovanov and Cooper-Krushkal models for colored sl(2) homology are equivalent in the case of the unknot, when formulated in the quantum annular Bar-Natan category. Again for the unknot, these two theories are shown to be equivalent to a third colored homology theory, defined using the action of Jones-Wenzl projectors on the quantum annular h

Okan Köksal, L. L. Li, Rossitza Pentcheva

The dice lattice, containing a stack of three triangular lattices, has been proposed to exhibit nontrivial flat bands with nonzero Chern numbers, but unlike the honeycomb lattice it is much less studied. By employing density-functional theory (DFT) calculations with an on-site Coulomb repulsion term, we explore systematically the electronic and topological p

Minoh Jeong, Alex Dytso, Martina Cardone

This paper explores the Ziv-Zakai bound (ZZB), which is a well-known Bayesian lower bound on the Minimum Mean Squared Error (MMSE). First, it is shown that the ZZB holds without any assumption on the distribution of the estimand, that is, the estimand does not necessarily need to have a probability density function. The ZZB is then further analyzed in the hi

Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin

We introduce Masked Trajectory Models (MTM) as a generic abstraction for sequential decision making. MTM takes a trajectory, such as a state-action sequence, and aims to reconstruct the trajectory conditioned on random subsets of the same trajectory. By training with a highly randomized masking pattern, MTM learns versatile networks that can take on differen

Antonis Klironomos, Baifan Zhou, Zhipeng Tan, Zhuoxun Zheng

Many machine learning (ML) libraries are accessible online for ML practitioners. Typical ML pipelines are complex and consist of a series of steps, each of them invoking several ML libraries. In this demo paper, we present ExeKGLib, a Python library that allows users with coding skills and minimal ML knowledge to build ML pipelines. ExeKGLib relies on knowle

Adnan A. E. Hajomer, Huy Q. Nguyen, Melis Pahalı, Ulrik L. Andersen

We report the first coexistence experiment of 1550 nm single-mode squeezed states of light with a 1310 nm classical telecom channel over a 10 km fiber channel while measuring squeezing using a locally generated local oscillator. This is achieved using real-time optical heterodyne phase locking, allowing us to measure up to 0.5 dB of squeezing with a phase no

Tahir Shamsher, Mir Riyaz ul Rashid, S. Pirzada

A signed graph $S=(G, σ)$ is a pair in which $G$ is an underlying graph and $σ$ is a function from the edge set to $\{\pm1\}$. For signed graphs $S_{1}$ and $S_{2}$ on $n_{1}$ and $n_{2}$ vertices, respectively, the signed neighbourhood corona $S_{1} \star_s S_{2}$ (in short s-neighbourhood corona) of $S_{1}$ and $S_{2}$ is the signed graph obtained by takin

Weihang Ding, Mohammad Shikh-Bahaei

In wireless communication networks, relays are required when the quality of the direct link between the source and the destination is not high enough to support reliable transmission because of long distances or obstacles. Selecting the proper relay node (RN) to support hybrid automatic repeat request (HARQ) is of great importance in such a relay-assisted ne

Dhruv Malik, Conor Igoe, Yuanzhi Li, Aarti Singh

In recommender system or crowdsourcing applications of online learning, a human's preferences or abilities are often a function of the algorithm's recent actions. Motivated by this, a significant line of work has formalized settings where an action's loss is a function of the number of times that action was recently played in the prior $m$ timest

Abdul Zalloum

This is an expository survey with two goals. 1) The primary goal is to discuss and highlight the impact of two recent influential ideas in geometric group theory. The first of which is the notion of an injective metric space which is a rich class of spaces that was imported to geometric group theory by Lang and have shown to be of a great effect. The second

Bowen Zheng, Ran Cheng

While off-policy reinforcement learning (RL) algorithms are sample efficient due to gradient-based updates and data reuse in the replay buffer, they struggle with convergence to local optima due to limited exploration. On the other hand, population-based algorithms offer a natural exploration strategy, but their heuristic black-box operators are inefficient.

Weihang Ding, Mohammad Shikh-Bahaei

5G new radio (NR) technology is introduced to satisfy more demanding services. Ultra-Reliable Low Latency Communication (URLLC) requires very low delay compared with the previous techniques. This is hard to achieve when hybrid automatic repeat request (HARQ) is applied and especially when the feedback channel is erroneous. In this work, we consider various d

Alan Bregazzi, Etienne Batori, Ben Lewis, Christoph Affolderbach

We demonstrate a Ramsey-type microwave clock interrogating the 6.835~GHz ground-state transition in cold \textsuperscript{87}Rb atoms loaded from a grating magneto-optical trap (GMOT) enclosed in an additively manufactured loop-gap resonator microwave cavity. A short-term stability of $1.5 \times10^{-11} $~$τ^{-1/2}$ is demonstrated, in reasonable agreement

Kevin Ivan Piterman

For a symplectic space $V$ of dimension $2n$ over $\mathbb{F}_{q}$, we compute the eigenvalues of its orthogonality graph. This is the simple graph with vertices the $2$-dimensional non-degenerate subspaces of $V$ and edges between orthogonal vertices. As a consequence of Garland's method, we obtain vanishing results on the homology groups of the frame c

Ji Liu, Ed Younis, Mathias Weiden, Paul Hovland

We propose a novel hierarchical qubit mapping and routing algorithm. First, a circuit is decomposed into blocks that span an identical number of qubits. In the second stage permutation-aware synthesis (PAS), each block is optimized and synthesized in isolation. In the third stage a permutation-aware mapping (PAM) algorithm maps the blocks to the target devic

Joseph Moyalan, Andrew Zheng, Sriram S. K. S Narayanan, Umesh Vaidya

This paper presents the implementation of off-road navigation on legged robots using convex optimization through linear transfer operators. Given a traversability measure that captures the off-road environment, we lift the navigation problem into the density space using the Perron-Frobenius (P-F) operator. This allows the problem formulation to be represente

V. A. Frolova, E. E. Nokhrina, I. N. Pashchenko

We examine the effect of a jet transversal structure from magnetohydrodynamic semi-analytical modelling on the total intensity profiles of relativistic jets from active galactic nuclei. In order to determine the conditions for forming double- and triple-peaked transverse intensity profiles, we calculate the radiative transfer for synchrotron emission with se

Kathrin Bringmann, Siu Hang Man, Larry Rolen, Matthias Storzer

For a random partition, one of the most basic questions is: what can one expect about the parts which arise? For example, what is the distribution of the parts of random partitions modulo $N$? Since most partitions contain a $1$, and indeed many $1$s arise as parts of a random partition, it is natural to expect a skew towards $1\pmod{N}$. This is indeed the

Md. Atik Ahamed, Jin Chen, Abdullah-Al-Zubaer Imran

Medical image classification is one of the most important tasks for computer-aided diagnosis. Deep learning models, particularly convolutional neural networks, have been successfully used for disease classification from medical images, facilitated by automated feature learning. However, the diverse imaging modalities and clinical pathology make it challengin

Mohammad Rowshan, Vlad-Florin Drăgoi, Jinhong Yuan

The weight distribution of error correction codes is a critical determinant of their error-correcting performance, making enumeration of utmost importance. In the case of polar codes, the minimum weight $\wm$ (which is equal to minimum distance $d$) is the only weight for which an explicit enumerator formula is currently available. Having closed-form weight

Emanuel Indrei

The non-transversal intersection of the free boundary with the fixed boundary is obtained for nonlinear uniformly elliptic operators when $Ω= \{\nabla u \neq 0\} \cap \{x_n>0\}$ thereby solving a problem in elliptic theory that in the case of the Laplacian is completely understood but has remained arcane in the nonlinear setting in higher dimension. Also, a

Luke McHale, Paul V Gratz, Alex Sprintson

Switching, routing, and security functions are the backbone of packet processing networks. Fast and efficient processing of packets requires maintaining the state of a large number of transient network connections. In particular, modern stateful firewalls, security monitoring devices, and software-defined networking (SDN) programmable dataplanes require main

Addis S. Fuhr, Panchapakesan Ganesh, Rama K. Vasudevan, Bobby G. Sumpter

Developing methods to understand and control defect formation in nanomaterials offers a promising route for materials discovery. Monolayer MX2 phases represent a particularly compelling case for defect engineering of nanomaterials due to the large variability in their physical properties as different defects are introduced into their structure. However, effe

Mao-Rui Cai, Chong Ye, Yong Li, Hui Dong

Developing effective methods to measure the enantiomeric excess of the chiral mixture is one of the major topics in chiral molecular researches, yet remains challenging. Enantiodetection method via two-dimensional (2D) spectroscopy based on a four level model, containing a cyclic three-level system (CTLS), of chiral molecules was recently proposed and demons

Shashank Gupta, Philipp Hager, Jin Huang, Ali Vardasbi

Since its inception, the field of unbiased learning to rank (ULTR) has remained very active and has seen several impactful advancements in recent years. This tutorial provides both an introduction to the core concepts of the field and an overview of recent advancements in its foundations along with several applications of its methods. The tutorial is divided

Ziad Sakr

Models of dark energy or modified gravity that tries to alleviate the tensions on the Hubble constant ($H_0$) and the matter fluctuation parameter ($σ_8$) are usually parameterized as function of either late or early time cosmic evolution. In this work we rather focus on one that could privilege extensions to $Λ$CDM on intermediate redshifts by mean of a Gau

Keaton Coletti, Pawel Kalczynski, Zvi Drezner

The inverse-square law states that the effect a source has on its surroundings is inversely proportional to the square of the Euclidean distance from that source. Its applicability spans multiple fields including physics, engineering, and computer science. We study the combined effect of multiple point sources surrounding a closed region in multidimensional

Chuanbo Hu, Shan Jia, Fan Zhang, Changjiang Xiao

Urban Physical Disorder (UPD), such as old or abandoned buildings, broken sidewalks, litter, and graffiti, has a negative impact on residents' quality of life. They can also increase crime rates, cause social disorder, and pose a public health risk. Currently, there is a lack of efficient and reliable methods for detecting and understanding UPD. To bridg

Minh-Quan Dao, Vincent Frémont, Elwan Héry

Low-resolution point clouds are challenging for object detection methods due to their sparsity. Densifying the present point cloud by concatenating it with its predecessors is a popular solution to this challenge. Such concatenation is possible thanks to the removal of ego vehicle motion using its odometry. This method is called Ego Motion Compensation (EMC)

Chengyun Hua, Claire E. Marvinney, Seongjin Hong, Matthew Feldman

Magneto-optical microscopies, including optical measurements of magnetic circular dichroism, are increasingly ubiquitous tools for probing spin-orbit coupling, charge-carrier g-factors, and chiral excitations in matter, but the minimum detectable signal in classical magnetic circular dichroism measurements is fundamentally limited by the shot-noise limit of

Dayuan Chen, Jian Zhang, Yuqian Lv, Jinhuan Wang

Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbations. Previous adversaries primarily focus on graph modifications or node injections to existing graphs, yielding promising results but with notable limitations. Graph modification

Elnatan Kadar, Jonathan Brokman, Guy Gilboa

We present a new model, training procedure and architecture to create precise maps of distinction between two classes of images. The objective is to comprehend, in pixel-wise resolution, the unique characteristics of a class. These maps can facilitate self-supervised segmentation and objectdetection in addition to new capabilities in explainable AI (XAI). Ou

Etienne Batori, Alan Bregazzi, Ben Lewis, Paul Griffin

We present an additive-manufactured microwave cavity for a Ramsey-type, double resonance, compact cold-atom clock. Atoms can be laser cooled inside the cavity using a grating magneto-optic trap (GMOT) with the cavity providing an excellent TE011-like mode while maintaining sufficient optical access for atomic detection. The cavity features a low Q-factor of

Elias Nin-Ruiz, Jairo Diaz-Rodriguez

This paper proposes two practical implementations of Four-Dimensional Variational (4D-Var) Ensemble Kalman Filter (4D-EnKF) methods for non-linear data assimilation. Our formulations' main idea is to avoid the intrinsic need for adjoint models in the context of 4D-Var optimization and, even more, to handle non-linear observation operators during the assi

Yi-Yu Lin

Within the framework of holographic duality, CMI (conditional mutual information) is often understood as a correlation between ``region pairs" and is closely related to the concept of partial entanglement entropy (PEE). The main theme of this paper is to try to understand the rigorous physical meaning of such a region-pair correlation. This relies on the

Jose A. Carrillo, Nicolas Garcia Trillos, Sixu Li, Yuhua Zhu

Federated learning is an important framework in modern machine learning that seeks to integrate the training of learning models from multiple users, each user having their own local data set, in a way that is sensitive to data privacy and to communication loss constraints. In clustered federated learning, one assumes an additional unknown group structure amo

Xavier Bekaert, Nicolas Boulanger, Maxim Grigoriev, Yegor Goncharov

We propose a systematic generating procedure to construct free Lagrangians for massive, massless and partially massless, totally-symmetric tensor fields on $AdS_{d+1}$ starting from the BRST Lagrangian description of massless fields in the flat ambient space $\mathbb{R}^{d,2}$. A novelty is that the Lagrangian is described by a $d+1$ form on $\mathbb{R}^{d,2

Jesse Koivu, Danka Lučić, Tapio Rajala

We show that every bounded domain in a metric measure space can be approximated in measure from inside by closed $BV$-extension sets. The extension sets are obtained by minimizing the sum of the perimeter and the measure of the difference between the domain and the set. By earlier results, in PI-spaces the minimizers have open representatives with locally qu

Paul Kielty, Mehdi Sefidgar Dilmaghani, Cian Ryan, Joe Lemley

Driver monitoring systems (DMS) are a key component of vehicular safety and essential for the transition from semiautonomous to fully autonomous driving. A key task for DMS is to ascertain the cognitive state of a driver and to determine their level of tiredness. Neuromorphic vision systems, based on event camera technology, provide advanced sensing of facia

Lorenzo Vorabbi, Davide Maltoni, Stefano Santi

Binary Neural Networks (BNNs) use 1-bit weights and activations to efficiently execute deep convolutional neural networks on edge devices. Nevertheless, the binarization of the first layer is conventionally excluded, as it leads to a large accuracy loss. The few works addressing the first layer binarization, typically increase the number of input channels to

Raad Khraishi, Ramin Okhrati

Data augmentation is a widely used technique for improving model performance in machine learning, particularly in computer vision and natural language processing. Recently, there has been increasing interest in applying augmentation techniques to reinforcement learning (RL) problems, with a focus on image-based augmentation. In this paper, we explore a set o

Cecilia Ka Yuk Chan, Katherine K. W. Lee

This study aimed to explore the experiences, perceptions, knowledge, concerns, and intentions of Gen Z students with Gen X and Gen Y teachers regarding the use of generative AI (GenAI) in higher education. A sample of students and teachers were recruited to investigate the above using a survey consisting of both open and closed questions. The findings showed

Ahmad Reza Motezakker, Andrés Córdoba, Tomas Rosén, Fredrik Lundell

Semi-flexible polymers in crowded environments exhibit complex dynamics that play a crucial role in various biological and material design processes. Based on the classic reptation theory, it is generally believed that semiflexible polymers are trapped within static confinements. Here we demonstrate that semi-flexible polymers are indeed trapped in short-liv

Ivan Cavlek, Sonja Grgic

In this paper synchronization techniques using cyclic prefix (CP) are analyzed to remove the influence of symbol time offset (STO) for correct synchronization in Orthogonal Frequency Division Multiplex (OFDM) system. For correct detection of STO using CP two techniques are used. The first one is based on finding the maximum correlation between two blocks and

Zidong Wu, Linglong Dai

Millimeter-wave (mmWave) and terahertz (THz) communications with hybrid precoding architectures have been regarded as energy-efficient solutions to fulfill the vision of high-speed transmissions for 6G communications. Benefiting from the advantages of providing a wide scan range and flat array gain, the uniform circular array (UCA) has attracted much attenti

James O'Quinn

We prove that finitary isomorphisms with finite expectation exist between Bernoulli shifts over the same free group only if the shifts have the same distribution. This generalizes the integer case result of Schmidt. We provide new proofs of some of the technical results of Parry and Schmidt which avoid the assumption of amenability.

Manuel Santos Gutiérrez, Kalli Furtado

The supersaturation equation for a vertically moving adiabatic cloud parcel is analysed. The effects of turbulent updrafts are incorporated in the shape of a stochastic Lagrangian model, with spatial and time correlations expressed in terms of turbulent kinetic energy. Using the Fokker-Planck equation, the steady-state probability distributions of supersatur