July 2023 arXiv papers — page 143

Kai-Bao Chen, Tianbo Liu, Yu-Kun Song, Shu-Yi Wei

The hadronization of a high-energy parton is described by fragmentation functions which are introduced through QCD factorizations. While the hadronization mechanism per se remains uknown, fragmentation functions can still be investigated qualitatively and quantitatively. The qualitative study mainly concentrates on extracting genuine features based on the op

Patrick Blumenberg, Arne Schmidt, Aaron T. Becker

We investigate motion planning algorithms for the assembly of shapes in the \emph{tilt model} in which unit-square tiles move in a grid world under the influence of uniform external forces and self-assemble according to certain rules. We provide several heuristics and experimental evaluation of their success rate, solution length, runtime, and memory consump

Sergio Leiva M., Jürgen Henk, Ingrid Mertig, Annika Johansson

The spin Edelstein effect has proven to be a promising phenomenon to generate spin polarization from a charge current in systems without inversion symmetry. In recent years, a current-induced orbital magnetization, called orbital Edelstein effect, has been predicted for various systems with broken inversion symmetry, using the atom-centered approximation and

Hanzhang Xue, Xiaochang Hu, Rui Xie, Hao Fu

Discriminating the traversability of terrains is a crucial task for autonomous driving in off-road environments. However, it is challenging due to the diverse, ambiguous, and platform-specific nature of off-road traversability. In this paper, we propose a novel self-supervised terrain traversability learning framework, utilizing a contrastive label disambigu

Johanna Naumann, Nicole Bohn, Oleg Birkholz, Matthias Neumann

The rising demand for high-performing batteries requires new technological concepts. To facilitate fast charge and discharge, hierarchically structured electrodes offer short diffusion paths in the active material. However, there are still gaps in understanding the influences on the cell performance of such electrodes. Here, we employed a cell model to demon

Pandeng Li, Chen-Wei Xie, Hongtao Xie, Liming Zhao

Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language description. To achieve this goal, we provide a generative diffusion-based framework called MomentDiff, which simulates a typical human retrieval process from random browsing to gradual

Yanqiang Guo, Zinan Hu, Jianchao Zhang, Chenyu Zhu

Precision experimental determination of photon correlation requires the massive amounts of data and extensive measurement time. We present a technique to monitor second-order photon correlation $g^{(2)}(0)$ of amplified quantum noise based on wideband balanced homodyne detection and deep-learning acceleration. The quantum noise is effectively amplified by an

Marc Zeller, Thomas Waschulzik, Reiner Schmid, Claus Bahlmann

Traditional automation technologies alone are not sufficient to enable driverless operation of trains (called Grade of Automation (GoA) 4) on non-restricted infrastructure. The required perception tasks are nowadays realized using Machine Learning (ML) and thus need to be developed and deployed reliably and efficiently. One important aspect to achieve this i

Camillo De Lellis, Ian Fleschler

We generalize a classical theorem of Besicovitch, showing that, for any positive integers $k<n$, if $E\subset \mathbb R^n$ is a Souslin set which is not $\mathcal{H}^k$-$\sigma$-finite, then $E$ contains a purely unrectifiable closed set $F$ with $0< \mathcal{H}^k (F) < \infty$. Therefore, if $E\subset \mathbb R^n$ is a Souslin set with the property that eve

Valerio Arnaboldi, Mattia Giovanni Campana, Franca Delmastro, Elena Pagani

In this paper, we propose a novel tag-based recommender system called PLIERS, which relies on the assumption that users are mainly interested in items and tags with similar popularity to those they already own. PLIERS is aimed at reaching a good tradeoff between algorithmic complexity and the level of personalization of recommended items. To evaluate PLIERS,

Tong Wang, Zhiming Pan, Keith Slevin, Tomi Ohtsuki

Disorder is ubiquitous in solid-state systems, and its crucial influence on transport properties was revealed by the discovery of Anderson localization. Generally speaking, all bulk states will be exponentially localized in the strong disorder limit, but whether an Anderson transition takes place depends on the dimension and symmetries of the system. The sca

Lukas Birkenmaier, Claudia Wagner, Clemens Lechner

Guidance on how to validate computational text-based measures of social constructs is fragmented. While researchers generally acknowledge the importance of validating text-based measures, they often lack a shared vocabulary and a unified framework to do so. This paper introduces ValiText, a new validation framework designed to assist scholars in validly meas

Shiqi Yang, Atsushi Hashimoto, Yoshitaka Ushiku

In recent years large model trained on huge amount of cross-modality data, which is usually be termed as foundation model, achieves conspicuous accomplishment in many fields, such as image recognition and generation. Though achieving great success in their original application case, it is still unclear whether those foundation models can be applied to other

Jiawei Wang, Jia Xu Brian Sia, Xiang Li, Xin Guo

The escalating need for expansive data bandwidth, and the resulting capacity constraints of the single mode fiber (SMF) have positioned the 2-${\mu}$m waveband as a prospective window for emerging applications in optical communication. This has initiated an ecosystem of silicon photonic components in the region driven by CMOS compatibility, low cost, high ef

Anh L. Mai, Pengyu Wang, Azza Abouzied, Matteo Brucato

A package query returns a package - a multiset of tuples - that maximizes or minimizes a linear objective function subject to linear constraints, thereby enabling in-database decision support. Prior work has established the equivalence of package queries to Integer Linear Programs (ILPs) and developed the SketchRefine algorithm for package query processing.

Chandan Kumar Vishwakarma, B. K. Mani

The multifunctional materials with prominent properties such as electrical, ferroelectric, magnetic, optical and magneto-optical are of keen interest to several practical implications. In the roadmap of designing such materials, in the present work, using density functional theory based first-principles calculations, we have investigated the functional prope

Usman Muhammad, Md Ziaul Hoque, Mourad Oussalah, Jorma Laaksonen

Face presentation attacks (PA), also known as spoofing attacks, pose a substantial threat to biometric systems that rely on facial recognition systems, such as access control systems, mobile payments, and identity verification systems. To mitigate the spoofing risk, several video-based methods have been presented in the literature that analyze facial motion

Michele Carriero, Simone Cito, Antonio Leaci

We look for minimizers of the buckling load problem with perimeter constraint in any dimension. In dimension 2, we show that the minimizing plates are convex; in higher dimension, by passing through a weaker formulation of the problem, we show that any optimal set is open and connected. For higher eigenvalues, we prove that minimizers exist among convex sets

Nandita Pattnaik, Jason R. C. Nurse, Sarah Turner, Gareth Mott

As cyber-attacks continue to increase in frequency and sophistication, organisations must be better prepared to face the reality of an incident. Any organisational plan that intends to be successful at managing security risks must clearly understand the harm (i.e., negative impact) and the various parties affected in the aftermath of an attack. To this end,

Iván Panadero, Hilario Espinós, Lucas Tsunaki, Kseniia Volkova

We model and experimentally demonstrate the full time-dependent counting statistics of photons emitted by a single nitrogen-vacancy (NV) center in diamond under non-resonant laser excitation and resonant microwave control. A generalization of the quantum jump formalism for the seven electronic states involved in the fast intrinsic dynamics of an NV center pr

Marek Sikora, Andrzej Zdziarski

We propose a model explaining the origin of transient/episodic jets in black-hole X-ray binaries, in which they are caused by transitions from a collimated, strongly magnetized, jet to a wide, un-collimated, outflow. The change occurs when the accretion flow leaves the magnetically-choked state due to an increase of the accretion rate for a weakly varying ma

Xuyang Zhao, Chengpu Yu, Erpei Xu, Yixuan Liu

Exploration systems are critical for enhancing the autonomy of robots. Due to the unpredictability of the future planning space, existing methods either adopt an inefficient greedy strategy or require a lot of resources to obtain a global solution. In this work, we address the challenge of obtaining global exploration routes with minimal computing resources.

Samir Suweis, Francesco Ferraro, Christian Grilletta, Sandro Azaele

In this work, we explore the dynamics of species abundances within ecological communities using the Generalized Lotka-Volterra (GLV) model. At variance with previous approaches, we present an analysis of stochastic GLV dynamics with temporal fluctuations in interaction strengths between species. We develop a dynamical mean field theory (DMFT) tailored for sc

Jonas Fritzsch, Marvin Wyrich, Justus Bogner, Stefan Wagner

Technology trends play an important role in the hiring process for software and IT professionals. In a recent study of 591 software professionals in both hiring (130) and technical (558) roles, we found empirical support for a tendency to overemphasize technology trends in r\'esum\'es and the application process. 60% of the hiring professionals agreed that s

Zi'ou Zheng, Xiaodan Zhu

Reasoning has been a central topic in artificial intelligence from the beginning. The recent progress made on distributed representation and neural networks continues to improve the state-of-the-art performance of natural language inference. However, it remains an open question whether the models perform real reasoning to reach their conclusions or rely on s

Yun Liu, Yu-Huan Wu, Shi-Chen Zhang, Li Liu

Tuberculosis (TB) is a major global health threat, causing millions of deaths annually. Although early diagnosis and treatment can greatly improve the chances of survival, it remains a major challenge, especially in developing countries. Recently, computer-aided tuberculosis diagnosis (CTD) using deep learning has shown promise, but progress is hindered by l

Jinyi Deng, Xinru Tang, Jiahao Zhang, Yuxuan Li

Spatial architecture is a high-performance architecture that uses control flow graphs and data flow graphs as the computational model and producer/consumer models as the execution models. However, existing spatial architectures suffer from control flow handling challenges. Upon categorizing their PE execution models, we find that they lack autonomous, peer-t

Roan Talbut, Daniele Tramontano, Yueqi Cao, Mathias Drton

The problem of comparing probability distributions is at the heart of many tasks in statistics and machine learning. Established comparison methods treat the standard setting that the distributions are supported in the same space. Recently, a new geometric solution has been proposed to address the more challenging problem of comparing measures in Euclidean s

Pablo Rosillo-Rodes, Maxi San Miguel, David Sanchez

In multilingual societies, it is common to encounter different language varieties. Various approaches have been proposed to discuss different mechanisms of language shift. However, current models exploring language shift in languages in contact often overlook the influence of language ideologies. Language ideologies play a crucial role in understanding langu

Roghayeh Maleki, Andriaherimanana Sarobidy Razafimahatratra

Given the symmetric group $G = \operatorname{Sym}(n)$ and a multiplicity-free subgroup $H\leq G$, the orbitals of the action of $G$ on $G/H$ by left multiplication induce a commutative association scheme. The irreducible constituents of the permutation character of $G$ acting on $G/H$ are indexed by partitions of $n$ and if $\lambda \vdash n$ is the second l

Thibault D. Décoppet, Hao Xu

Given an algebra in a monoidal 2-category, one can construct a 2-category of right modules. Given a braided algebra in a braided monoidal 2-category, it is possible to refine the notion of right module to that of a local module. Under mild assumptions, we prove that the 2-category of local modules admits a braided monoidal structure. In addition, if the brai

Yu Chen, Yihan Du, Pihe Hu, Siwei Wang

Risk-sensitive reinforcement learning (RL) aims to optimize policies that balance the expected reward and risk. In this paper, we present a novel risk-sensitive RL framework that employs an Iterated Conditional Value-at-Risk (CVaR) objective under both linear and general function approximations, enriched by human feedback. These new formulations provide a pr

A. Verbitskiy, A. Yulin

In this paper we theoretically study the nonlinear dynamics of Wannier-Stark states in the dissipative system consisting of interacting optical resonators, whose resonant frequencies depend linearly on their number. It is shown that the negative losses in some resonators can switch the system into a lasing regime with Wannier-Stark states serving as working

Federico Ghimenti, Ludovic Berthier, Grzegorz Szamel, Frédéric van Wijland

Sampling the Boltzmann distribution using forces that violate detailed balance can be faster than with the equilibrium evolution, but the acceleration depends on the nature of the nonequilibrium drive and the physical situation. Here, we study the efficiency of forces transverse to energy gradients in dense liquids through a combination of techniques: Browni

Le Xiao, Xiaolin Chen

News summary generation is an important task in the field of intelligence analysis, which can provide accurate and comprehensive information to help people better understand and respond to complex real-world events. However, traditional news summary generation methods face some challenges, which are limited by the model itself and the amount of training data

A. Sheikhhosseini, S. Malekinejad, M. Khosravi

In this paper, we obtain some new matrix inequalities involving Hadamard product. Also some Hadamard product inequalities for accretive matrices involving the matrix means, positive unital linear maps and matrix concave functions are investigated. Among other results, it is shown that if $A, B, C, D$ are $n\times n$ positive definite matrices, then \begin{eq

Elena Barcucci, Antonio Bernini, Stefano Bilotta, Renzo Pinzani

Dyck paths having height at most $h$ and without valleys at height $h-1$ are combinatorially interpreted by means of 312-avoding permutations with some restrictions on their \emph{left-to-right maxima}. The results are obtained by analyzing a restriction of a well-known bijection between the sets of Dyck paths and 312-avoding permutations. We also provide a

Shiqi Deng, Zhiyu Sun, Ruiyan Zhuang, Jun Gong

Anomaly detection has a wide range of applications and is especially important in industrial quality inspection. Currently, many top-performing anomaly-detection models rely on feature-embedding methods. However, these methods do not perform well on datasets with large variations in object locations. Reconstruction-based methods use reconstruction errors to

Rupchand Sutradhar, D C Dalal

Analysis of the cell population generally provides average information about viral infection in a host whereas the intracellular model captures the individual cellular responses. The primary goal of this study is to comprehensively analyze the intracellular dynamics of hepatitis B virus (HBV) infection and to identify the most influential factors. In this st

Ram Sagar, Gopal-Krishna

Devasthal observatory, established over a time span of about 5 decades, is located in central Himalayan region of Devabhumi in Nainital district of Uttarakhand state, India. Operated and maintained by the Aryabhatta Research Institute of observational sciencES (ARIES), its location was selected after an extensive site survey. The first measurements of atmosp

Zahra Sadeghibogar, Alessandro Berti, Marco Pegoraro, Wil M. P. van der Aalst

Computer-based scientific experiments are becoming increasingly data-intensive, necessitating the use of High-Performance Computing (HPC) clusters to handle large scientific workflows. These workflows result in complex data and control flows within the system, making analysis challenging. This paper focuses on the extraction of case IDs from SLURM-based HPC

Netta Madvil, Yonatan Bitton, Roy Schwartz

The prevalence of large-scale multimodal datasets presents unique challenges in assessing dataset quality. We propose a two-step method to analyze multimodal datasets, which leverages a small seed of human annotation to map each multimodal instance to the modalities required to process it. Our method sheds light on the importance of different modalities in d

David J. Beerling, Dimitar Z. Epihov, Ilsa B. Kantola, Michael D. Masters

Enhanced weathering (EW) with crushed basalt on farmlands is a promising scalable atmospheric carbon dioxide removal strategy that urgently requires performance assessment with commercial farming practices. Our large-scale replicated EW field trial in the heart of the U.S. Corn Belt shows cumulative time-integrated carbon sequestration of 15.4 +/- 4.1 t CO2

Hsuan-Wei Lee, Colin Cleveland, Attila Szolnoki

Introducing strategy complexity into the basic conflict of cooperation and defection is a natural response to avoid the tragedy of the common state. As an intermediate approach, quasi-cooperators were recently suggested to address the original problem. In this study, we test its vitality in structured populations where players have fixed partners. Naively, t

Jonathan P. Keating, Fei Wei

In a companion paper \cite{jon-fei}, we established asymptotic formulae for the joint moments of derivatives of the characteristic polynomials of CUE random matrices. The leading order coefficients of these asymptotic formulae are expressed as partition sums of derivatives of determinants of Hankel matrices involving I-Bessel functions, with column indices s

Xuefeng Li, Liwen Wang, Guanting Dong, Keqing He

Zero-shot cross-domain slot filling aims to transfer knowledge from the labeled source domain to the unlabeled target domain. Existing models either encode slot descriptions and examples or design handcrafted question templates using heuristic rules, suffering from poor generalization capability or robustness. In this paper, we propose a generative zero-shot

Jialei Huang, Zhaoheng Yin, Yingdong Hu, Yang Gao

Adversarial imitation learning (AIL) is a popular method that has recently achieved much success. However, the performance of AIL is still unsatisfactory on the more challenging tasks. We find that one of the major reasons is due to the low quality of AIL discriminator representation. Since the AIL discriminator is trained via binary classification that does

Xu Han, Anmin Liu, Chenxuan Yao, Yanbo Fan

Deep neural networks are known to be vulnerable to adversarial examples crafted by adding human-imperceptible perturbations to the benign input. After achieving nearly 100% attack success rates in white-box setting, more focus is shifted to black-box attacks, of which the transferability of adversarial examples has gained significant attention. In either cas

Zhilong Liu, Jiayi Zhang, Ziheng Liu, Hongyang Du

Cell-free massive multiple-input multiple-output (mMIMO) and extremely large-scale MIMO (XL-MIMO) are regarded as promising innovations for the forthcoming generation of wireless communication systems. Their significant advantages in augmenting the number of degrees of freedom have garnered considerable interest. In this article, we first review the essentia

Zi-Yuan Wang, Jie Qian, Yi-Pu Wang, Jie Li

We experimentally demonstrate the nonreciprocal microwave amplification using a cavity magnonic system, consisting of a passive cavity (i.e., the split-ring resonator), an active feedback circuit integrated with an amplifier, and a ferromagnetic spin ensemble (i.e., a yttrium-iron-garnet sphere). Combining the amplification provided by the active circuit and

Yuanjing Feng, Lei Xie, Jingqiang Wang, Qiyuan Tian

Tractography traces the peak directions extracted from fiber orientation distribution (FOD) suffering from ambiguous spatial correspondences between diffusion directions and fiber geometry, which is prone to producing erroneous tracks while missing true positive connections. The peaks-based tractography methods 'locally' reconstructed streamlines in 'single

Thomas Spanner, Thomas Mieling, Stefan Palenta

Laser-interferometric gravitational wave detectors are commonly modeled as being at rest in transverse-traceless coordinates (and thus geodesic). In this paper, we analyze what happens if the interferometer is mounted on a material that can undergo elastic oscillations caused by the gravitational wave. We thus compute the response of a two-dimensional elasti

Anthony Hastir, Riccardo Muolo

The classical Routh-Hurwitz criterion is one of the most popular methods to study the stability of polynomials with real coefficients, given its simplicity and ductility. However, when moving to polynomials with complex coefficients, a generalization exists but it is rather cumbersome and not as easy to apply. In this paper, we make such generalization clear

Carl Tipler

Kaneyama and Klyachko have shown that any torus equivariant vector bundle of rank $r$ over $\mathbb{CP}^n$ splits if $r < n$. In particular, any such bundle is not slope stable. In contrast, we provide explicit examples of stable equivariant reflexive sheaves of rank $r$ on any polarised toric variety $(X, L)$, for $2 \leq r < \mathrm{dim}(X) + \mathrm{rank}

Azmain A. Hossain, Haozhe Wang, David S. Catherall, Martin Leung

Microwave loss in superconducting titanium nitride (TiN) films is attributed to two-level systems in various interfaces arising in part from oxidation and microfabrication-induced damage. Atomic layer etching (ALE) is an emerging subtractive fabrication method which is capable of etching with Angstrom-scale etch depth control and potentially less damage. How

Zeynep Hilal Kilimci, Ulku Bayraktar, Ayhan Kucukmanisa

Speech emotion recognition is a challenging task in speech processing field. For this reason, feature extraction process has a crucial importance to demonstrate and process the speech signals. In this work, we represent a model, which feeds raw audio files directly into the deep neural networks without any feature extraction stage for the recognition of emot

Nathan Koome Murungi, Michael Vinh Pham, Xufeng Dai, Xiaodong Qu

This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in the context of Machine Learning. Our focus is on Electroencephalography (EEG) research, highlighting the latest trends as of 2023. The objective is to provide undergraduate researchers with an accessible overview of the BCI field, covering tasks, algorithms, and dataset

Sagnik Nandy, Bhaswar B. Bhattacharya

The $\boldsymbol{\beta}$-model for random graphs is commonly used for representing pairwise interactions in a network with degree heterogeneity. Going beyond pairwise interactions, Stasi et al. (2014) introduced the hypergraph $\boldsymbol{\beta}$-model for capturing degree heterogeneity in networks with higher-order (multi-way) interactions. In this paper w

Mayuko Kori, Flavio Ascari, Filippo Bonchi, Roberto Bruni

We formulate, in lattice-theoretic terms, two novel algorithms inspired by Bradley's property directed reachability algorithm. For finding safe invariants or counterexamples, the first algorithm exploits over-approximations of both forward and backward transition relations, expressed abstractly by the notion of adjoints. In the absence of adjoints, one can u

Thomas John, Lars Kaestner, Christian Wagner, Alexis Darras

Erythrocyte Sedimentation Rate (ESR) is a clinical parameter used as a non-specific marker for inflammation, and recent studies have shown that it is linked to the collapse of the gel formed by red blood cells (RBCs) at physiological hematocrits (i.e. RBC volume fraction). Previous research has suggested that the delay time before the sedimentation process i

Dwip Dalal, Gautam Vashishtha, Prajwal Singh, Shanmuganathan Raman

Digital imaging aims to replicate realistic scenes, but Low Dynamic Range (LDR) cameras cannot represent the wide dynamic range of real scenes, resulting in under-/overexposed images. This paper presents a deep learning-based approach for recovering intricate details from shadows and highlights while reconstructing High Dynamic Range (HDR) images. We formula

Yuanchen Bei, Hao Xu, Sheng Zhou, Huixuan Chi

Dynamic graph data mining has gained popularity in recent years due to the rich information contained in dynamic graphs and their widespread use in the real world. Despite the advances in dynamic graph neural networks (DGNNs), the rich information and diverse downstream tasks have posed significant difficulties for the practical application of DGNNs in indus

Ko-Yun Huang, Serena Viti

Multi-line molecular observations are an ideal tool for a systematic study of the physico-chemical processes in the Interstellar Medium (ISM), given the wide range of critical densities associated with different molecules and their transitions, and the dependencies of chemical reactions on the energy budget of the system. Recently high spatial resolution of

Bjorn Jasper R. Raquel, Tetsuya Hashimoto, Tomotsugu Goto, Bo Han Chen

Fast Radio Bursts (FRBs) are mysterious bursts in the millisecond timescale at radio wavelengths. Currently, there is little understanding about the classification of repeating FRBs, based on difference in physics, which is of great importance in understanding their origin. Recent works from the literature focus on using specific parameters to classify FRBs

Adérito Fins Carreira, Adam Wysocki, Christophe Ybert, Mathieu Leocmach

An important challenge in active matter lies in harnessing useful global work from entities that produce work locally, e.g., via self-propulsion. We investigate here the active matter version of a classical capillary rise effect, by considering a non-phase separated sediment of self-propelled Janus colloids in contact with a vertical wall. We provide experim

Liping Sun

We perform a complete study on the $J/\psi$ pair hadroproduction at next-to-leading order (NLO) in the nonrelativstic-QCD (NRQCD) framework with the pair of $c\bar{c}$ either in ${}^{3}S_1^{[1]}$ or ${}^{1}S_0^{[8]}$ fock state. It is found that the ${}^{1}S_0^{[8]}$ channel contribution at NLO is essential. Our results indicate that for the CMS, the NRQCD p

Zicheng Zhang, Wei Sun, Yingjie Zhou, Haoning Wu

Digital humans have witnessed extensive applications in various domains, necessitating related quality assessment studies. However, there is a lack of comprehensive digital human quality assessment (DHQA) databases. To address this gap, we propose SJTU-H3D, a subjective quality assessment database specifically designed for full-body digital humans. It compri

Kuiliang Wang, Hong Liang, Chong Zhao, Xin Bian

We employ a multi-phase smoothed particle hydrodynamics (SPH) method to study droplet dynamics in shear flow. With an extensive range of Reynolds number, capillary number, wall confinement, and density/viscosity ratio between the droplet and the matrix fluid, we are able to investigate systematically the droplet dynamics such as deformation and breakup. We c

Hanie Moghaddasi, Richard C. Hendriks, Borbala Hunyadi, Paul Knops

The severity of atrial fibrillation (AF) can be assessed from intra-operative epicardial measurements (high-resolution electrograms), using metrics such as conduction block (CB) and continuous conduction delay and block (cCDCB). These features capture differences in conduction velocity and wavefront propagation. However, they do not clearly differentiate pat

M. Rybakov, D. Shkatov

We discuss the modifications of the Kripke trick simulating binary predicate letters of classical first-order formulas with monadic modal first-order formulas and the situations where the trick does not work. As a result, we obtain results on algorithmic upper bounds for monadic fragments of some modal and superintuitionistic first-order logics.

Mohammad Abu-Shaira, Greg Speegle

Machine Learning requires a large amount of training data in order to build accurate models. Sometimes the data arrives over time, requiring significant storage space and recalculating the model to account for the new data. On-line learning addresses these issues by incrementally modifying the model as data is encountered, and then discarding the data. In th

Nirjan Biswas, Harsh Prasad

For $p \in (1, \infty)$ and $s \in (0,1)$, we consider the following mixed local-nonlocal equation $$ - \Delta_p u + (-\Delta_p)^s u = f \; \text{in} \; \Omega,$$ where $\Omega \subset \mathbb{R}^d$ is a bounded domain and the function $f \in L_{loc}^1(\Omega)$. Depending on the dimension $d$, we prove gradient potential estimates of weak solutions for the e

Belle II Collaboration, I. Adachi, K. Adamczyk, L. Aggarwal

We present a measurement of time-dependent rate asymmetries in $B^0\to \phi K^0_S$ decays to search for non-standard-model physics in $b\to q \overline{q}s$ transitions. The data sample is collected with the Belle II detector at the SuperKEKB asymmetric-energy $e^{+}e^{-}$ collider in 2019-2022 and contains $(387\pm 6)\times 10^6$ bottom-antibottom mesons fr

Yuqing Zhu, Yiwen Zhu, Aoyu Gong, Yan Lin

This paper considers an uplink Internet of Things system with synchronous periodic traffic, where multiple devices generate their status updates at the beginning of each global frame and attempt to send them to a common access point. To achieve a low network-wide age of information (AoI) in an easily implementable manner, we require each device to adopt an a

M. Rybakov, D. Shkatov

We prove that predicate modal logics QK4.3 and QS4.3 are undecidable in languages with two individual variables, one modandic predicate letter, and one proposition letter.

Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

This study proposes a few-shot personalized saliency prediction method that leverages interpersonal gaze patterns. Unlike general saliency maps, personalized saliency maps (PSMs) capture individual visual attention and provide insights into individual visual preferences. However, predicting PSMs is challenging because of the complexity of gaze patterns and t

Hritam Basak, Zhaozheng Yin

Although unsupervised domain adaptation (UDA) is a promising direction to alleviate domain shift, they fall short of their supervised counterparts. In this work, we investigate relatively less explored semi-supervised domain adaptation (SSDA) for medical image segmentation, where access to a few labeled target samples can improve the adaptation performance s

Mengyan Wang, Yuxuan Hu, Zihan Yuan, Chenting Jiang

In the realm of personalized recommendation systems, the increasing concern is the amplification of belief imbalance and user biases, a phenomenon primarily attributed to the filter bubble. Addressing this critical issue, we introduce an innovative intermediate agency (BHEISR) between users and existing recommendation systems to attenuate the negative reperc

Nan Tang, Chenyu Yang, Ju Fan, Lei Cao

Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as inaccurate decision-making, the spread of false information, privacy violations, legal liabilities, and more. Although efforts to address these risks are underway, including expla

Massimo Tessarotto, Claudio Cremaschini, Marco Tessarotto

In this paper the problem is posed of the formulation of the so-called "ab initio" approach to the statistical description of the Boltzmann-Sinai N-body classical dynamical system (CDS) formed by identical smooth hard spheres. This amounts to introducing a suitably-generalized version of the axioms of Classical Statistical Mechanics. The latter involve a pro

Ayush Kumar, David K. Yau

In this work, we propose a testbed environment to capture the attack strategies of an adversary carrying out a cyber-attack on an enterprise network. The testbed contains nodes with known security vulnerabilities which can be exploited by hackers. Participants can be invited to play the role of a hacker (e.g., black-hat, hacktivist) and attack the testbed. T

Gioia Carinci, Chiara Franceschini, Davide Gabrielli, Cristian Giardinà

We consider the one dimensional boundary driven harmonic model and its continuous version, both introduced in \cite{FGK}. By combining duality and integrability the authors of \cite{FG} obtained the invariant measures in a combinatorial representation. Here we give an integral representation of the invariant measures which turns out to be a convex combinatio

Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang

The rapid advances of large language models (LLMs), such as ChatGPT, are revolutionizing data science and statistics. These state-of-the-art tools can streamline complex processes. As a result, it reshapes the role of data scientists. We argue that LLMs are transforming the responsibilities of data scientists, shifting their focus from hands-on coding, data-

Charles Jones, Mélanie Roschewitz, Ben Glocker

We investigate performance disparities in deep classifiers. We find that the ability of classifiers to separate individuals into subgroups varies substantially across medical imaging modalities and protected characteristics; crucially, we show that this property is predictive of algorithmic bias. Through theoretical analysis and extensive empirical evaluatio

Bach Long Nguyen, Anh-Dzung Doan, Tat-Jun Chin, Christophe Guettier

Countries with access to large bodies of water often aim to protect their maritime transport by employing maritime surveillance systems. However, the number of available sensors (e.g., cameras) is typically small compared to the to-be-monitored targets, and their Field of View (FOV) and range are often limited. This makes improving the situational awareness

Jian-Ying Bai, Jing Wang, Hua-Li Li, Li-Ping Xin

We observed active M dwarf star AD Leo for 146 hr in photometry by GWAC-F30 and also analyzed 528-hr photometric data of the star from TESS. A total of 9 and 70 flares are detected from GWAC-F30 and TESS, respectively. Flare durations, amplitudes and energies are calculated. The distributions of the three properties and FFDs are given. Within the same energy

Sabine Bellstedt, Aaron S. G. Robotham, Simon P. Driver, Claudia del P. Lagos

We present the first look at star formation histories of galaxy components using ProFuse, a new technique to model the 2D distribution of light across multiple wavelengths using simultaneous spectral and spatial fitting of purely imaging data. We present a number of methods to classify galaxies structurally/morphologically, showing the similarities and discr

Tesshu Hanaka, Hirotaka Ono, Kunihiko Sadakane, Kosuke Sugiyama

Given a directed edge-weighted graph $G=(V, E)$ with beer vertices $B\subseteq V$, a beer path between two vertices $u$ and $v$ is a path between $u$ and $v$ that visits at least one beer vertex in $B$, and the beer distance between two vertices is the shortest length of beer paths. We consider \emph{indexing problems} on beer paths, that is, a graph is give

Vinod Kumar, Rituraj Sharma, Abhishek Bhatt, I. Csarnovics

The donor-acceptor interaction of a charge-coupled heterostructure encompassing a metal and an amorphous semiconductor subjected to a laser field has many potential applications in the realm of nonlinear optics. In this work, we fabricate an electron donor gold nanoparticle (AuNP) and acceptor amorphous Ge24Se76 heterostructure on a quartz substrate using a

Hirokazu Sasaki, Yuta Yamazaki, Toshitaka Kajino, Grant J. Mathews

The partcle-induced hadronic de-excitation of the Hoyle state in $^{12}$C induced by inelastic scattering in a hot and dense plasma can enhance the triple-alpha reaction rate. This prevents the production of heavy nuclei within the neutrino-driven winds of core-collapse supernovae and raises a question as to the contribution of proton-rich neutrino-driven wi

Nuwa Xi, Sendong Zhao, Haochun Wang, Chi Liu

Decoding text stimuli from cognitive signals (e.g. fMRI) enhances our understanding of the human language system, paving the way for building versatile Brain-Computer Interface. However, existing studies largely focus on decoding individual word-level fMRI volumes from a restricted vocabulary, which is far too idealized for real-world application. In this pa

Seyoung Ahn, Soohyeong Kim, Yongseok Kwon, Joohan Park

In this paper, we investigate the spatial-wideband effects in cell-free massive MIMO (CF-mMIMO) systems in mmWave bands. The utilization of mmWave frequencies brings challenges such as signal attenuation and the need for denser networks like ultra-dense networks (UDN) to maintain communication performance. CF-mMIMO is introduced as a solution, where distribu

Triet M. Thai, Anh T. Vo, Hao K. Tieu, Linh N. P. Bui

In recent years, artificial intelligence has played an important role in medicine and disease diagnosis, with many applications to be mentioned, one of which is Medical Visual Question Answering (MedVQA). By combining computer vision and natural language processing, MedVQA systems can assist experts in extracting relevant information from medical image based

M. Sánchez-Cruces, M. Rosado

We analysed the ionised gas kinematics of the dwarf galaxy NGC 4214 using high resolution Fabry-Perot interferometry observations and present a set of narrowband images in the H$\alpha$, [SII] $\lambda$6717 $\r{A}$, [NII] $\lambda$6584 $\r{A}$ and [OIII] $\lambda$5007 $\r{A}$ emission lines. The high-resolution Fabry-Perot observations of the H$\alpha$ emiss

Masahiro Morimoto

We prove that any polar action on a separable Hilbert space by a connected Hilbert Lie group does not have exceptional orbits. This generalizes a result of Berndt, Console and Olmos in the finite dimensional Euclidean case. As an application, we give a simple geometric proof of the fact that any hyperpolar action on a simply connected compact Riemannian symm

Jiachen Cai, Robert J. B. Goudie, Colin Starr, Brian D. M. Tom

The increasing availability of high-dimensional, longitudinal measures of gene expression can facilitate understanding of biological mechanisms, as required for precision medicine. Biological knowledge suggests that it may be best to describe complex diseases at the level of underlying pathways, which may interact with one another. We propose a Bayesian appr

Zahmeeth Sayed Sakkaff

New mental tasks were investigated for suitability in Brain-Computer Interface (BCI). Electroencephalography (EEG) signals were collected and analyzed to identify these mental tasks. MS Windows-based software was developed for investigating and classifying recorded EEG data with unnecessary frequencies filtered out with Bandpass filtering. To identify the be

Yifei Shen, Jiawei Shao, Xinjie Zhang, Zehong Lin

The evolution of wireless networks gravitates towards connected intelligence, a concept that envisions seamless interconnectivity among humans, objects, and intelligence in a hyper-connected cyber-physical world. Edge artificial intelligence (Edge AI) is a promising solution to achieve connected intelligence by delivering high-quality, low-latency, and priva

Mengfei Zhang, Miao Li

High-velocity atomic clouds in the Galactic center have attracted significant attention due to their enigmatic formation process, which is potentially linked to the starburst or supermassive black hole activities in the region. Further, the discovery of high-velocity molecular clouds (HVMCs) presents a greater puzzle, because they are much denser and more ma

Rui Chen, Songtao Tian, Dongming Huang, Qian Lin

In this paper, we prove that functional sliced inverse regression (FSIR) achieves the optimal (minimax) rate for estimating the central space in functional sufficient dimension reduction problems. First, we provide a concentration inequality for the FSIR estimator of the covariance of the conditional mean. Based on this inequality, we establish the root-$n$