March 2023 arXiv papers — page 37

Guy Boistel

The present study collects 456 new times of maximum light of the classical Cepheid RT Aur, covering the period from 1897 to 2022. The O-C diagram resulting from these observations shows that the period given by the GCVS has to be corrected. It results that no strong period variation is found. However, the observed O-C residuals show a long term periodic tren

Javier Correa, Hellen de Paula

We show a flexibility result in the context of generalized entropy. The space of dynamical systems we work with is, homeomorphisms on the sphere whose non-wandering set consist in only one fixed point.

Cheng Wang, Fengwei Guo, Ruilin Yu, Luyao Wang

Driver models play a vital role in developing and verifying autonomous vehicles (AVs). Previously, they are mainly applied in traffic flow simulation to model driver behavior. With the development of AVs, driver models attract much attention again due to their potential contributions to AV safety assessment. The simulation-based testing method is an effectiv

Yabin Zhu, Chenglong Li, Xiao Wang, Jin Tang

Existing Transformer-based RGBT tracking methods either use cross-attention to fuse the two modalities, or use self-attention and cross-attention to model both modality-specific and modality-sharing information. However, the significant appearance gap between modalities limits the feature representation ability of certain modalities during the fusion process

Weihua Sun, Run-An Wang, Zhaonian Zou

Many problems in database systems, such as cardinality estimation, database testing and optimizer tuning, require a large query load as data. However, it is often difficult to obtain a large number of real queries from users due to user privacy restrictions or low frequency of database access. Query generation is one of the approaches to solve this problem.

Dan Segal

Finitely generated (non-abelian) free metabelian pro-p groups, and wreath products of f.g. free abelian pro-p groups, are all finitely axiomatizable in the class of all profinite groups.

Yi Liu

Surface bundles arising from periodic mapping classes may sometimes have non-isomorphic, but profinitely isomorphic fundamental groups. Pairs of this kind have been discovered by Hempel. This paper exhibits examples of nontrivial Hempel pairs where the mapping tori can be distinguished by some Turaev--Viro invariants, and also examples where they cannot be d

Farman Mamedov, Jasarat Gasimov

In this paper, we study a solvability result for the nonlinear problem $$ \mbox {div } \left ( \vert \nabla_\omega u\vert^{p-2}\nabla_\omega u \right )+v(x) u^{q-1}+\mu u^{\gamma-1}=0, \quad z\in \Omega, \quad u \Big \vert_{\partial \Omega}=0. $$ assuming for the weight functions $ v \in A_\infty, \, \omega \in A_p $ to belong the Muckenhoupt class and a bal

Changdae Oh, Hyeji Hwang, Hee-young Lee, YongTaek Lim

With the surge of large-scale pre-trained models (PTMs), fine-tuning these models to numerous downstream tasks becomes a crucial problem. Consequently, parameter efficient transfer learning (PETL) of large models has grasped huge attention. While recent PETL methods showcase impressive performance, they rely on optimistic assumptions: 1) the entire parameter

Chaitanya Devaguptapu, Samarth Sinha, K J Joseph, Vineeth N Balasubramanian

Models pre-trained on large-scale datasets are often fine-tuned to support newer tasks and datasets that arrive over time. This process necessitates storing copies of the model over time for each task that the pre-trained model is fine-tuned to. Building on top of recent model patching work, we propose $\Delta$-Patching for fine-tuning neural network models

Nader Asadi, MohammadReza Davari, Sudhir Mudur, Rahaf Aljundi

In Continual learning (CL) balancing effective adaptation while combating catastrophic forgetting is a central challenge. Many of the recent best-performing methods utilize various forms of prior task data, e.g. a replay buffer, to tackle the catastrophic forgetting problem. Having access to previous task data can be restrictive in many real-world scenarios,

Thuy-Trang Vu, Xuanli He, Gholamreza Haffari, Ehsan Shareghi

In very recent years more attention has been placed on probing the role of pre-training data in Large Language Models (LLMs) downstream behaviour. Despite the importance, there is no public tool that supports such analysis of pre-training corpora at large scale. To help research in this space, we launch Koala, a searchable index over large pre-training corpo

Yusong Shi, Weidong Liu

The concept of extension-based proofs models the idea of a valency argument, which is widely used in distributed computing. Extension-based proofs are limited in power: it has been shown that there is no extension-based proof of the impossibility of a wait-free protocol for $(n,k)$-set agreement among $n > k \geq 2$ processes. There are only a few tasks that

Aaron Pache, Mark CW van Rossum

When training neural networks for classification tasks with backpropagation, parameters are updated on every trial, even if the sample is classified correctly. In contrast, humans concentrate their learning effort on errors. Inspired by human learning, we introduce lazy learning, which only learns on incorrect samples. Lazy learning can be implemented in a f

Bei Gan, Xiujun Shu, Ruizhi Qiao, Haoqian Wu

Movie highlights stand out of the screenplay for efficient browsing and play a crucial role on social media platforms. Based on existing efforts, this work has two observations: (1) For different annotators, labeling highlight has uncertainty, which leads to inaccurate and time-consuming annotations. (2) Besides previous supervised or unsupervised settings,

Tianyi Zhang, Yongquan Xue

We present a routinized and reliable method to obtain source catalogs from the $\textit{Nuclear Spectroscopic Telescope Array}$ ($\textit{NuSTAR}$) extragalactic surveys of the Extended $\textit{Chandra}$ Deep Field-South (E-CDF-S) and $\textit{Chandra}$ Deep Field-North (CDF-N). The $\textit{NuSTAR}$ E-CDF-S survey covers a sky area of $\approx30'\times30'$

Carson Ezell, Abraham Loeb

The previous decade saw the discovery of the first four known interstellar objects due to advances in astronomical viewing equipment. Future sky surveys with greater sensitivity will allow for more frequent detections of such objects, including increasingly small objects. We consider the capabilities of the Legacy Survey of Space and Time (LSST) of the Vera

Zheng Lin, Guangyu Zhu, Yiqin Deng, Xianhao Chen

The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices. To overcome this challenge, in this paper, we advocate the integration of edge computing paradigm and parallel split learning (PSL), allowing multiple client devices to offload substan

Benjamin Kenwright

Over the past few years, the applications of dual-quaternions have not only developed in many different directions but has also evolved in exciting ways in several areas. As dual-quaternions offer an efficient and compact symbolic form with unique mathematical properties. While dual-quaternions are now common place in many aspects of research and implementat

Wenxing Zhang, Tianjun Li, Xiangwei Yin

We consider the generic scalar potential with CP-violation, and study the $Z$ resonance and inelastic dark matter in the Simple Extension of the Standard Model (SESM), which can explain the dark matter as well as new physics anomalies such as the B physics anomalies and muon anomalous magnetic moment, etc. With the new scalar potential terms, we obtain the m

Tsuyoshi Miyatsu, Myung-Ki Cheoun, Kyungsik Kim, Koichi Saito

We construct new effective interactions using the relativistic mean-field models with the isoscalar- and isovector-meson mixing, $\sigma^{2}\bm{\delta}^{2}$ and $\omega_{\mu}\omega^{\mu}\bm{\rho}_{\nu}\bm{\rho}^{\nu}$. Taking into account the particle flow data in heavy-ion collisions, the observed mass of PSR J0740$+$6620, and the tidal deformability of a n

Denys Gobov, Olga Solovei

Selecting techniques is a crucial element of the business analysis approach planning in IT projects. Particular attention is paid to the choice of techniques for requirements elicitation. One of the promising methods for selecting techniques is using machine learning algorithms trained on the practitioners' experience considering different projects' contexts

Karol Kampf, Jiri Novotny, Jaroslav Trnka, Petr Vasko

In this paper, we study celestial amplitudes of Goldstone bosons and conformal soft theorems. Motivated by the success of soft bootstrap in momentum space and the important role of the soft limit behavior of tree-level amplitudes, our goal is to extend some of the methods to the celestial sphere. The crucial ingredient of the calculation is the Mellin transf

Daniel T. Speckhard, Christian Carbogno, Luca Ghiringhelli, Sven Lubeck

The numerical precision of density-functional-theory (DFT) calculations depends on a variety of computational parameters, one of the most critical being the basis-set size. The ultimate precision is reached with an infinitely large basis set, i.e., in the limit of a complete basis set (CBS). Our aim in this work is to find a machine-learning model that extra

Max Reinhold Jahnke

In this work, we prove that, under a topological condition, the cohomology associated with left-invariant elliptic structures on compact semisimple Lie groups can be computed using only left-invariant forms. This reduces the analytical problem to a purely algebraic one, while also providing a generalization of the classic works of Chevalley and Eilenberg [CE

Asma Jodeiri Akbarfam, Sina Barazandeh, Hoda Maleki, Deepti Gupta

In general, deep learning models use to make informed decisions immensely. Developed models are mainly based on centralized servers, which face several issues, including transparency, traceability, reliability, security, and privacy. In this research, we identify a research gap in a distributed nature-based access control that can solve those issues. The inn

D. V. Artamonov

A model of representations of a Lie algebra is a representation which a direct sum of all irreducible finite dimensional representations taken with multiplicity $1$. In the paper an explicit construction of a model of representation for all series of classical Lie algebras is given. The construction does not differ much for different series. The space of the

Valentin Deliyski, Galin Gyulchev, Petya Nedkova, Stoytcho Yazadjiev

We study the linear polarization from the accretion disk around weakly and strongly naked Janis-Newman-Winicour singularities. We consider an analytical toy model of thin magnetized fluid ring orbiting in the equatorial plane and emitting synchrotron radiation. The observable polarized images are calculated and compared to the Schwarzschild black hole for ph

J. G. Cardoso

It is assumed that the non-singular big-bang birth of the Universe as set forth by Einstein-Cartan's theory particularly brought about the appearance of the cosmic microwave and dark energy backgrounds, dark matter, gravitons as well as of Dirac particles. On account of this assumption, a two-component description of the motion of quarks and leptons prior to

Iosif Petrakis

We present an abstract, categorical formulation of dependent functions in a fundamental manner and independently from the Sigma-construction. For that, we define first the notion of a category with family-arrows, or a $\f$-category. A $(\f, \Sigma)$-category is a $\f$-category with Sigma-objects, where a $(\f, \Sigma)$-category with a terminal object is exac

Andreas Kirsch

The paper 'Deep Learning on a Data Diet' by Paul et al. (2021) introduces two innovative metrics for pruning datasets during the training of neural networks. While we are able to replicate the results for the EL2N score at epoch 20, the same cannot be said for the GraNd score at initialization. The GraNd scores later in training provide useful pruning signal

Victor de la Pena, Henryk Gzyl, Silvia Mayoral, Haolin Zou

In this paper we propose an optimal predictor of a random variable that has either an infinite mean or an infinite variance. The method consists of transforming the random variable such that the transformed variable has a finite mean and finite variance. The proposed predictor is a generalized arithmetic mean which is similar to the notion of certainty price

Minh Hoang Trinh, Hoang Huy Vu, Nhat-Minh Le-Phan, Quyen Ngoc Nguyen

In this paper, we propose matrix-scaled consensus algorithms for linear dynamical agents interacting over an undirected network. Under the proposed algorithms, the state vectors of all agents to asymptotically agree up to some matrix scaling weights. First, the algebraic properties of the matrix-scaled Laplacian and the geometry of the matrix-scaled consensu

Nelson Rosa, Bassel Katamish, Maximilian Raff, C. David Remy

For a class of biped robots with impulsive dynamics and a non-empty set of passive gaits (unactuated, periodic motions of the biped model), we present a method for computing continuous families of locally optimal gaits with respect to a class of commonly used energetic cost functions (e.g., the integral of torque-squared). We compute these families using onl

Pasha Zusmanovich

We provide a variant of Baer's theorem about isomorphism of endomorphism rings of vector spaces over division rings, where the full endomorphism rings are replaced by some subrings of finitary maps.

Xiaojie Wang, Yuying Zhao, Zhongqiang Zhang

We present an error analysis of weak convergence of one-step numerical schemes for stochastic differential equations (SDEs) with super-linearly growing coefficients. Following Milstein's weak error analysis on the one-step approximation of SDEs, we prove a general conclusion on weak convergence of the one-step discretization of the SDEs mentioned above. As a

Xiaolong Shen, Zongxin Yang, Xiaohan Wang, Jianxin Ma

Video-based 3D human pose and shape estimations are evaluated by intra-frame accuracy and inter-frame smoothness. Although these two metrics are responsible for different ranges of temporal consistency, existing state-of-the-art methods treat them as a unified problem and use monotonous modeling structures (e.g., RNN or attention-based block) to design their

Xian-Li Yin, Jie-Qiao Liao

We study the generation of quantum entanglement between two giant atoms coupled to a common one-dimensional waveguide. Here each giant atom interacts with the waveguide at two separate coupling points. Within the Wigner-Weisskopf framework for single coupling points, we obtain the time-delayed quantum master equations governing the evolution of the two giant

Una Pale, Tomas Teijeiro, David Atienza

Epilepsy is a chronic neurological disorder with a significant prevalence. However, there is still no adequate technological support to enable epilepsy detection and continuous outpatient monitoring in everyday life. Hyperdimensional (HD) computing is an interesting alternative for wearable devices, characterized by a much simpler learning process and also l

Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Rogerio Feris

Building object detectors that are robust to domain shifts is critical for real-world applications. Prior approaches fine-tune a pre-trained backbone and risk overfitting it to in-distribution (ID) data and distorting features useful for out-of-distribution (OOD) generalization. We propose to use Relative Gradient Norm (RGN) as a way to measure the vulnerabi

Luisa Beghin, Lorenzo Cristofaro, Roberto Garrappa

We introduce and study here a renewal process defined by means of a time-fractional relaxation equation with derivative order $\alpha(t)$ varying with time $t\geq0$. In particular, we use the operator introduced by Scarpi in the Seventies and later reformulated in the regularized Caputo sense in Garrappa et al. (2021), inside the framework of the so-called g

Yunjie Ji, Yong Deng, Yan Gong, Yiping Peng

The success of ChatGPT has recently attracted numerous efforts to replicate it, with instruction-tuning strategies being a key factor in achieving remarkable results. Instruction-tuning not only significantly enhances the model's performance and generalization but also makes the model's generated results more consistent with human speech patterns. However cu

Jürg Fröhlich

This paper begins with a summary of a powerful formalism for the study of electronic states in condensed matter physics called "Gauge Theory of States/Phases of Matter." The chiral anomaly, which plays quite a prominent role in that formalism, is recalled. I then sketch an application of the chiral anomaly in 1+1 dimensions to quantum wires. Subsequently, so

Saikat Das, Suparna Roychowdhury

In this paper, we implement a generalised pseudo-Newtonian potential to study the off-equatorial orbits inclined at a certain angle with the equatorial plane around Schwarzschild and Kerr-like compact object primaries surrounded by a dipolar halo of matter. The chaotic dynamics of the orbits are detailed for both non-relativistic and special-relativistic tes

Kai Wang, Michael Z. Q. Chen, Fei Liu

This paper investigates the circuit synthesis problem for a certain positive-real bicubic (third-order) admittance with a simple pole at the origin (s = 0) to be realizable as a one-port series-parallel damper-spring-inerter circuit consisting of at most six elements, where the results can be directly applied to the design and physical realization of inerter

Zhentao Liu, Yu Fang, Changjian Li, Han Wu

Cone Beam Computed Tomography (CBCT) plays a vital role in clinical imaging. Traditional methods typically require hundreds of 2D X-ray projections to reconstruct a high-quality 3D CBCT image, leading to considerable radiation exposure. This has led to a growing interest in sparse-view CBCT reconstruction to reduce radiation doses. While recent advances, inc

Inoj Neupane, Belal Alsinglawi, Khaled Rabie

Humans and robots working together in an environment to enhance human performance is the aim of Industry 5.0. Although significant progress in outdoor positioning has been seen, indoor positioning remains a challenge. In this paper, we introduce a new research concept by exploiting the potential of indoor positioning for Industry 5.0. We use Wi-Fi Received S

Mark Petersen, Russ Tedrake

One of the most difficult parts of motion planning in configuration space is ensuring a trajectory does not collide with task-space obstacles in the environment. Generating regions that are convex and collision free in configuration space can separate the computational burden of collision checking from motion planning. To that end, we propose an extension to

Gang Dai, Yifan Zhang, Qingfeng Wang, Qing Du

Training machines to synthesize diverse handwritings is an intriguing task. Recently, RNN-based methods have been proposed to generate stylized online Chinese characters. However, these methods mainly focus on capturing a person's overall writing style, neglecting subtle style inconsistencies between characters written by the same person. For example, while

Matthias Ehrhardt, Thomas Kruse, Antoine Tordeux

The collective motion of self-driven agents is a phenomenon of great interest in interacting particle systems. In this paper, we develop and analyze a model of agent motion in one dimension with periodic boundaries using a stochastic port-Hamiltonian system (PHS). The interaction model is symmetric and based on nearest neighbors. The distance-based terms and

Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli

One of the central issues of several machine learning applications on real data is the choice of the input features. Ideally, the designer should select only the relevant, non-redundant features to preserve the complete information contained in the original dataset, with little collinearity among features and a smaller dimension. This procedure helps mitigat

Nhat-Minh Le-Phan, Minh Hoang Trinh, Phuoc Doan Nguyen

In this paper, randomized gossip-type matrix-weighted consensus algorithms are proposed for both leaderless and leader-follower topologies. First, we introduce the notion of expected matrix-weighted network, which captures the multi-dimensional interactions between any two agents in a probabilistic sense. Under some mild assumptions on the distribution of th

Minsu Park, Suman Kalyan Maity, Stefan Wuchty, Dashun Wang

Interdisciplinary research has emerged as a hotbed for innovation and a key approach to addressing complex societal challenges. The increasing dominance of grant-supported research in shaping scientific advances, coupled with growing interest in funding interdisciplinary work, raises fundamental questions about the effectiveness of interdisciplinary grants i

Amit Priyadarshi, Mrinal K. Roychowdhury, Manuj Verma

Let $\nu$ be a Borel probability measure on a $d$-dimensional Euclidean space $\mathbb{R}^d$, $d\geq 1$, with a compact support, and let $(p_0, p_1, p_2, \ldots, p_N)$ be a probability vector with $p_j>0$ for $0\leq j\leq N$. Let $\{S_j: 1\leq j\leq N\}$ be a set of contractive mappings on $\mathbb{R}^d$. Then, a Borel probability measure $\mu$ on $\mathbb R

Xuelin Qian, Yikai Wang, Yanwei Fu, Xinwei Sun

The connection between brain activity and corresponding visual stimuli is crucial in comprehending the human brain. While deep generative models have exhibited advancement in recovering brain recordings by generating images conditioned on fMRI signals, accomplishing high-quality generation with consistent semantics continues to pose challenges. Moreover, the

XENON Collaboration, E. Aprile, K. Abe, F. Agostini

We report on the first search for nuclear recoils from dark matter in the form of weakly interacting massive particles (WIMPs) with the XENONnT experiment which is based on a two-phase time projection chamber with a sensitive liquid xenon mass of $5.9$ t. During the approximately 1.1 tonne-year exposure used for this search, the intrinsic $^{85}$Kr and $^{22

Hangjie Ji, Thomas P. Witelski

A lubrication model can be used to describe the dynamics of a weakly volatile viscous fluid layer on a hydrophobic substrate. Thin layers of the fluid are unstable to perturbations and break up into slowly evolving interacting droplets. A reduced-order dynamical system is derived from the lubrication model based on the nearest-neighbor droplet interactions i

Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu

3D scene understanding, e.g., point cloud semantic and instance segmentation, often requires large-scale annotated training data, but clearly, point-wise labels are too tedious to prepare. While some recent methods propose to train a 3D network with small percentages of point labels, we take the approach to an extreme and propose ``One Thing One Click,'' mea

Xiaoming Li, Wangmeng Zuo, Chen Change Loy

Blind text image super-resolution (SR) is challenging as one needs to cope with diverse font styles and unknown degradation. To address the problem, existing methods perform character recognition in parallel to regularize the SR task, either through a loss constraint or intermediate feature condition. Nonetheless, the high-level prior could still fail when e

Fei Yu, Hongbo Zhang, Prayag Tiwari, Benyou Wang

This survey paper proposes a clearer view of natural language reasoning in the field of Natural Language Processing (NLP), both conceptually and practically. Conceptually, we provide a distinct definition for natural language reasoning in NLP, based on both philosophy and NLP scenarios, discuss what types of tasks require reasoning, and introduce a taxonomy

V. K. Oikonomou, Konstantinos-Rafail Revis, Ilias C. Papadimitriou, Maria-Myrto Pegioudi

In this paper, we worked in the framework of an inflationary $f(R,T)$ theory, in the presence of a canonical scalar field. More specifically, the $f(R,T)=\gamma R+2\kappa\alpha T$ gravity. The values of the dimensionless parameters $\alpha$ and $\gamma$ are taken to be $\alpha \geq 0$ and $0 < \gamma \leq 1$. The motivation for that study was the striking si

Zongsheng Zhou, Weinan Ye, Hong-Gang Luo, Jize Zhao

The Hubbard and related models serve as a fundamental starting point in understanding the novel experimental phenomena in correlated electron materials, such as superconductivity, Mott insulator, magnetism and stripe phases. Recent numerical simulations indicate that the emergence of superconductivity is connected with the next nearest-neighbor hopping $t^\p

Jaan Parts

In the mysterious and colorful world of chromatic numbers, where there are a lot of unknown, there is an amazing thing. It turns out that for some intervals of forbidden distances on the plane, one can specify the exact value of the chromatic number $\chi$. Two sets of such intervals have been found, for $\chi=7$ and 9. We call them islands of certainty. Her

Claudius Heyer

The Geometrical Lemma is a classical result in the theory of (complex) smooth representations of $p$-adic reductive groups, which helps to analyze the parabolic restriction of a parabolically induced representation by providing a filtration whose graded pieces are (smaller) parabolic inductions of parabolic restrictions. In this article, we establish the Geo

Nermin Caber, Bashar I. Ahmad, Jiaming Liang, Simon Godsill

Monitoring drivers' mental workload facilitates initiating and maintaining safe interactions with in-vehicle information systems, and thus delivers adaptive human machine interaction with reduced impact on the primary task of driving. In this paper, we tackle the problem of workload estimation from driving performance data. First, we present a novel on-road

Victor Shirandami

A dense forest is a set $F \subset \mathbb{R}^n$ with the property that for all $\varepsilon > 0$ there exists a number $V(\varepsilon) > 0$ such that all line segments of length $V(\varepsilon)$ are $\varepsilon$-close to a point in $F$. The function $V$ is called a visibility function of $F$. In this paper we study dense forests constructed from finite uni

Kazuki Sugihara, Moju Zhao, Takuzumi Nishio, Tasuku Makabe

Humanoids are versatile robotic platforms owing to their limbs with multiple degrees of freedom. Although humanoids can walk like humans, they are relatively slow, and cannot run over large barriers. To address these limitations, we aim to achieve rapid terrestrial locomotion ability and simultaneously expand the locomotion domain to the air by utilizing thr

Jianhui Yu, Hao Zhu, Liming Jiang, Chen Change Loy

Text-driven generation models are flourishing in video generation and editing. However, face-centric text-to-video generation remains a challenge due to the lack of a suitable dataset containing high-quality videos and highly relevant texts. This paper presents CelebV-Text, a large-scale, diverse, and high-quality dataset of facial text-video pairs, to facil

Alex Beeson, Giovanni Montana

Offline reinforcement learning agents seek optimal policies from fixed data sets. With environmental interaction prohibited, agents face significant challenges in preventing errors in value estimates from compounding and subsequently causing the learning process to collapse. Uncertainty estimation using ensembles compensates for this by penalising high-varia

Federico Corberi, Manoj Kumar, Eugenio Lippiello, Paolo Politi

After a zero temperature quench, we study the kinetics of the one-dimensional Ising model with long-range interactions between spins at distance $r$ decaying as $r^{-\alpha}$, with $\alpha \le 1$. As shown in our recent study [SciPost Phys 10, 109 (2021)] that only a fraction of the non-equilibrium trajectories is characterized by the presence of coarsening

Aubrey D. N. J. de Grey, Jaan Parts

Here we give refined numerical values for the minimum number of vertices of $k$-chromatic unit distance graphs in the Euclidean plane.

Aakash Ahmad, Muhammad Waseem, Peng Liang, Mahdi Fehmideh

Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics - to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum

Surya Giri, S. Sivaprasad Kumar

In this study, we deal with the sharp bounds of certain Toeplitz determinants whose entries are the logarithmic coefficients of analytic univalent functions $f$ such that the quantity $z f'(z)/f(z)$ takes values in a specific domain lying in the right half plane. The established results provide the bounds for the classes of starlike and convex functions, as

Marcel Reimann, Jungeun Won, Hiroyuki Takahashi, Antonio Yaghy

Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases. Newly visible features are, for example, small hyperreflective specks in age-related macular degeneration. Identifying these new markers is

Martin Pépin, Alfredo Viola

Directed acyclic graphs (DAGs) are directed graphs in which there is no path from a vertex to itself. DAGs are an omnipresent data structure in computer science and the problem of counting the DAGs of given number of vertices and to sample them uniformly at random has been solved respectively in the 70's and the 00's. In this paper, we propose to explore a n

Jordanka Kovaceva, Nikolce Murgovski, Balázs Kulcsár, Henk Wymeersch

This paper provides a general framework for efficiently obtaining the appropriate intervention time for collision avoidance systems to just avoid a rear-end crash. The proposed framework incorporates a driver comfort model and a vehicle model. We show that there is a relationship between driver steering manoeuvres based on acceleration and jerk, and steering

Huiru Wang, Xiuhong Li, Zenyu Ren, Dan Yang

Because multimodal data contains more modal information, multimodal sentiment analysis has become a recent research hotspot. However, redundant information is easily involved in feature fusion after feature extraction, which has a certain impact on the feature representation after fusion. Therefore, in this papaer, we propose a new multimodal sentiment analy

Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang

While Neural Radiance Fields (NeRFs) had achieved unprecedented novel view synthesis results, they have been struggling in dealing with large-scale cluttered scenes with sparse input views and highly view-dependent appearances. Specifically, existing NeRF-based models tend to produce blurry rendering with the volumetric reconstruction often inaccurate, where

Qian Wang, Yiqun Wang, Michael Birsak, Peter Wonka

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images in the multi-object scenario still remains a challenge. Recently, a 2D GAN termed BlobGAN has demonstrated great multi-object editing capabilities on real-world indoor scene datase

Mohammad Modiri

The brain can learn to execute a wide variety of tasks quickly and efficiently. Nevertheless, most of the mechanisms that enable us to learn are unclear or incredibly complicated. Recently, considerable efforts have been made in neuroscience and artificial intelligence to understand and model the structure and mechanisms behind the amazing learning capabilit

Guorun Wang, Jun Yang, Yaoru Sun

The Outstanding performance and growing size of Large Language Models has led to increased attention in parameter efficient learning. The two predominant approaches are Adapters and Pruning. Adapters are to freeze the model and give it a new weight matrix on the side, which can significantly reduce the time and memory of training, but the cost is that the ev

Hadar Hezi, Daniel Shats, Daniel Gurevich, Yosef E. Maruvka

Molecular subtypes of colorectal cancer (CRC) significantly influence treatment decisions. While convolutional neural networks (CNNs) have recently been introduced for automated CRC subtype identification using H&E stained histopathological images, the correlation between CRC subtype genomic variants and their corresponding cellular morphology expressed by t

Fabio Calefato, Luigi Quaranta, Filippo Lanubile

Context. GitHub has introduced a new gamification element through personal achievements, whereby badges are unlocked and displayed on developers' personal profile pages in recognition of their development activities. Objective. In this paper, we present an exploratory analysis using mixed methods to study the diffusion of personal badges in GitHub, in additi

Guangming Shi, Dahua Gao, Shuai Ma, Minxi Yang

Shannon information theory is established based on probability and bits, and the communication technology based on this theory realizes the information age. The original goal of Shannon's information theory is to describe and transmit information content. However, due to information is related to cognition, and cognition is considered to be subjective, Shann

Simian Luo, Xuelin Qian, Yanwei Fu, Yinda Zhang

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space. While this approach has been extended to the 3D domain for powerful shape generation, it still has two limitations: expensive computations on volumetric grids and ambiguous auto-regressive order along grid dimensions. To over

Peter B Marschik, Amanda KL Kwong, Nelson Silva, Joy E Olsen

The Prechtl General Movements Assessment (GMA) has become a clinician and researcher tool-box for evaluating neurodevelopment in early infancy. Given it involves observation of infant movements from video recordings, utilising smartphone applications to obtain these recordings seems like the natural progression for the field. In this review, we look back on

Poulami Bag, Shubhadip Nayak, Tanwi Debnath, Pulak K. Ghosh

Self-propelled Janus particles exhibit autonomous motion thanks to engines of their own. However, due to randomly changing direction of such motion they are of little use for emerging nano-technological and bio-medical applications. Here, we numerically show that the motion of chiral active Janus can be directed subjecting them to a linear array of convectio

Mallika Roy, Enric Ventura, Pascal Weil

We study the average case complexity of the uniform membership problem for subgroups of free groups, and we show that it is orders of magnitude smaller than the worst case complexity of the best known algorithms. This applies to subgroups given by a fixed number of generators as well as to subgroups given by an exponential number of generators. The main idea

Stefanie Kieninger, Simon Ghysbrecht, Bettina G. Keller

The critical step in a molecular process is often a rare-event and has to be simulated by an enhanced sampling protocol. Recovering accurate dynamical estimates from such biased simulation is challenging. Girsanov reweighting is a method to reweight dynamic properties formulated as path expected values. The path probability is calculated at the time-step res

Zi-Liang Zhang, Yun-Wei Yu, Xiao-Feng Cao

A large number of fast radio bursts (FRBs) detected with the CHIME telescope have enabled investigations of their energy distributions in different redshift intervals, incorporating the consideration of the selection effects of CHIME. As a result, we obtained a non-evolving energy function (EF) for the high-energy FRBs (HEFRBs) of energies $E\gtrsim2\times0^

Eveline Drijver, Rodrigo Pérez-Dattari, Jens Kober, Cosimo Della Santina

Intelligent manufacturing is becoming increasingly important due to the growing demand for maximizing productivity and flexibility while minimizing waste and lead times. This work investigates automated secondary robotic food packaging solutions that transfer food products from the conveyor belt into containers. A major problem in these solutions is varying

Xin-long Luo, Hang Xiao, Sen Zhang

This paper considers the regularization continuation method and the trust-region updating strategy for the nonlinearly equality-constrained optimization problem. Namely, it uses the inverse of the regularization quasi-Newton matrix as the pre-conditioner to improve its computational efficiency in the well-posed phase, and it adopts the inverse of the regular

Anton Matthijs Berghuis, Gabriel W. Castellanos, Shunsuke Murai, Jose Luis Pura

We show the first experimental demonstration of room-temperature exciton-polariton (EP) condensation from a bound state in the continuum (BIC). This demonstration is achieved by strongly coupling stable excitons in an organic perylene dye with the extremely long-lived BIC in a dielectric metasurface of silicon nanoparticles. The long lifetime of the BIC, mai

Prabhat Kumar

In a topology optimization setting, design-dependent fluidic pressure loads pose several challenges as their direction, magnitude, and location alter with topology evolution. This paper offers a compact 100-line MATLAB code, TOPress, for topology optimization of structures subjected to fluidic pressure loads using the method of moving asymptotes. The code is

Yuzhou Gu, Yury Polyanskiy

We study the weak recovery problem on the $r$-uniform hypergraph stochastic block model ($r$-HSBM) with two balanced communities. In HSBM a random graph is constructed by placing hyperedges with higher density if all vertices of a hyperedge share the same binary label, and weak recovery asks to recover a non-trivial fraction of the labels. We introduce a mul

Yuzhou Gu, Yury Polyanskiy

In the study of sparse stochastic block models (SBMs) one often needs to analyze a distributional recursion, known as the belief propagation (BP) recursion. Uniqueness of the fixed point of this recursion implies several results about the SBM, including optimal recovery algorithms for SBM (Mossel et al. (2016)) and SBM with side information (Mossel and Xu (2

Taiki Shibata, Kenichi Shimizu

Given a tensor functor between tensor categories $\mathcal{C}$ and $\mathcal{D}$, we give criteria that, under certain assumptions, the Frobeniusness of $\mathcal{C}$ or $\mathcal{D}$ implies the Frobeniusness of the other one. We also give an affirmative answer to Natale's question asking if the class of Frobenius tensor categories is closed under exact seq

Sakil Ahamed, Subrata Majumdar

In this paper, we study the control properties of the linearized compressible Navier-Stokes system with Maxwell's law around a constant steady state $(\rho_s, u_s, 0), \rho_s>0, u_s>0$ in the interval $(0, 2\pi)$ with periodic boundary data. We explore the exact controllability of the coupled system by means of a localized interior control acting in any of t

Yadong Jiang, Huan Wang, Kejie Bao, Zhaochen Liu

We theoretically propose that the van der Waals layered ternary transition metal chalcogenide V$_2 MX_4$ ($M=$ W, Mo; $X=$ S, Se) is a new family of quantum anomalous Hall insulators with sizable bulk gap and Chern number $\mathcal{C}=-1$. The large topological gap originates from the \emph{deep} band inversion between spin up bands contributed by $d_{xz},d_

M. Chaudhuri, L. C. J. Heijmans, M. van de Kerkhof, P. Krainov

The nanoparticle charging processes along with background spatial-temporal plasma profile have been investigated with 3DPIC simulation in a pulsed EUV exposure environment. It is found that the particle charge polarity (positive or negative) strongly depends on its size, location and background transient plasma conditions. The particle (100 nm diameter) char