December 2023 arXiv papers — page 64

Qixiang Fang, Zhihan Zhou, Francesco Barbieri, Yozen Liu

Learning general-purpose user representations based on user behavioral logs is an increasingly popular user modeling approach. It benefits from easily available, privacy-friendly yet expressive data, and does not require extensive re-tuning of the upstream user model for different downstream tasks. While this approach has shown promise in search engines and

Athipatana Iamphongsai, Teeradej Kittipassorn

In this paper, we prove an isoperimetric inequality for the triangular grid graph which was conjectured by Adams, Gibson, and Pfaffinger, using the compression technique of Bollob\'as and Leader. Moreover, we apply the isoperimetric inequality to the Zero-Visibility Search game and Lions and Contamination game in order to obtain lower bounds for the inspecti

Elie Rasmussen Cueto, Anne Hutter, Pratika Dayal, Stefan Gottlöber

Observations with JWST have revealed an unexpected high abundance of bright z>10 galaxy candidates. We explore whether a stellar initial mass function (IMF) that becomes increasingly top-heavy towards higher redshifts and lower gas-phase metallicities results in a higher abundance of bright objects in the early universe and how it affects the evolution of ga

Xiangyu Liu, Yang Liu, Wei Hu

Knowledge graphs (KGs) often contain various errors. Previous works on detecting errors in KGs mainly rely on triplet embedding from graph structure. We conduct an empirical study and find that these works struggle to discriminate noise from semantically-similar correct triplets. In this paper, we propose a KG error detection model CCA to integrate both text

Tao He, Shuxian Hu, Longbin Lai, Dongze Li

Graph computing has become increasingly crucial in processing large-scale graph data, with numerous systems developed for this purpose. Two years ago, we introduced GraphScope as a system addressing a wide array of graph computing needs, including graph traversal, analytics, and learning in one system. Since its inception, GraphScope has achieved significant

Cara MacBride, Vinny Davies, Duncan Lee

In areal unit data with missing or suppressed data, it desirable to create models that are able to predict observations that are not available. Traditional statistical methods achieve this through Bayesian hierarchical models that can capture the unexplained residual spatial autocorrelation through conditional autoregressive (CAR) priors, such that they can

Valerio Goretti, Davide Basile, Luca Barbaro, Claudio Di Ciccio

Inter-organizational business processes involve multiple independent organizations collaborating to achieve mutual interests. Process mining techniques have the potential to allow these organizations to enhance operational efficiency, improve performance, and deepen the understanding of their business based on the recorded process event data. However, inter-

Andreas P. Braun, Richie Dadhley

We study the worldsheet CFTs of type II strings on compact $G_2$ orbifolds obtained as quotients of a product of a Calabi-Yau threefold and a circle. For such models, we argue that the Calabi-Yau mirror map implies a mirror map for the associated $G_2$ varieties by examining how anti-holomorphic involutions behave under Calabi-Yau mirror symmetry. The mirror

Minoru Wakimoto

In this paper, we study modular transformation properties of a certain class of functions with indefinite quadratic forms.

Yao Rong, Peizhu Qian, Vaibhav Unhelkar, Enkelejda Kasneci

Effectively explaining decisions of black-box machine learning models is critical to responsible deployment of AI systems that rely on them. Recognizing their importance, the field of explainable AI (XAI) provides several techniques to generate these explanations. Yet, there is relatively little emphasis on the user (the explainee) in this growing body of wo

Robson Christie, Jessica Eastman

We explore dissipative quantum tunnelling, a phenomenon central to various physical and chemical processes, using a double-well potential model. This paper aims to bridge gaps in understanding the crossover from thermal activation to quantum tunnelling, a domain still shrouded in mystery despite extensive research. We study a Caldeira-Leggett-derived model o

Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv

Graph Neural Networks (GNNs) show promising results for graph tasks. However, existing GNNs' generalization ability will degrade when there exist distribution shifts between testing and training graph data. The cardinal impetus underlying the severe degeneration is that the GNNs are architected predicated upon the I.I.D assumptions. In such a setting, GNNs a

Taeri Kim, Jiho Heo, Hongil Kim, Kijung Shin

We address the medication recommendation problem, which aims to recommend effective medications for a patient's current visit by utilizing information (e.g., diagnoses and procedures) given at the patient's current and past visits. While there exist a number of recommender systems designed for this problem, we point out that they are challenged in accurately

Amr Ali Abdulkader Al-Maktry

Let $n>1$ and let $R$ be a commutative ring with identity $1\ne 0$ and $R[x_1,\ldots,x_n]^n$ the set of all $n$-tuples of polynomials of the form $(f_1,\ldots,f_n),$ where $f_1,\ldots,f_n\in R[x_1,\ldots,x_n]$. We call these $n$-tuples vector-polynomials. We define composition on $R[x_1,\ldots,x_n]^n$ by $$\vec{g}\circ \vec{f}=(g_1(f_1, \ldots ,f_n), \ldots

Jaeyeul Kim, Jungwan Woo, Jeonghoon Kim, Sunghoon Im

In the realm of LiDAR-based perception, significant strides have been made, yet domain generalization remains a substantial challenge. The performance often deteriorates when models are applied to unfamiliar datasets with different LiDAR sensors or deployed in new environments, primarily due to variations in point cloud density distributions. To tackle this

Vincent Noculak, Johannes Reuther

The pseudo-fermion functional renormalization group is generalized to treat spin Hamiltonians with finite magnetic fields, enabling its application to arbitrary spin lattice models with linear and bilinear terms in the spin operators. We discuss in detail an efficient numerical implementation of this approach making use of the system's symmetries. Particular

Chunjie Luo, Fei Luo, Yusen Wang, Enxu Zhao

Reconstructing a dynamic human with loose clothing is an important but difficult task. To address this challenge, we propose a method named DLCA-Recon to create human avatars from monocular videos. The distance from loose clothing to the underlying body rapidly changes in every frame when the human freely moves and acts. Previous methods lack effective geome

Yanwen Ba, Xuan Liu, Xinning Chen, Hao Wang

While decentralized training is attractive in multi-agent reinforcement learning (MARL) for its excellent scalability and robustness, its inherent coordination challenges in collaborative tasks result in numerous interactions for agents to learn good policies. To alleviate this problem, action advising methods make experienced agents share their knowledge ab

Linglin Jing, Sheng Xu, Yifan Wang, Yuzhe Zhou

Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a single model that could ignore either the semantic context of the protein or the global 3D geometric information. Consequ

Ruchi Mahajan, T. Wheeler, E. Pollacco, C. Wrede

Background: The established GADGET detection system, designed for measuring weak, low-energy $\beta$-delayed proton decays, features a gaseous Proton Detector with MICROMEGAS readout for calorimetric particle detection, surrounded by a Segmented Germanium Array for high-resolution prompt $\gamma$-ray detection. Purpose: To upgrade GADGET's Proton Detector to

Soumitra Daptari, Fuad Kittaneh, Satyajit Sahoo

The main goal of this article is to establish several new $\mathbb{A}$-numerical radius equalities and inequalities for $n\times n$ cross-diagonal, left circulant, skew left circulant operator matrices, where $\mathbb{A}$ is the $n\times n$ diagonal operator matrix whose diagonal entries are positive bounded operator $A$. Also, we introduce two new matrices

Adrian Zahariuc

We prove that any number of general fat points of any multiplicities impose the expected number of conditions on a linear system on a smooth projective surface, in several cases including primitive linear systems on very general K3 and abelian surfaces, `Du Val' linear systems on blowups of ${\mathbb P}^2$ at $9$ very general points, and certain linear syste

Boyu Fan, Siyang Jiang, Xiang Su, Sasu Tarkoma

As privacy concerns continue to grow, federated learning (FL) has gained significant attention as a promising privacy-preserving technology, leading to considerable advancements in recent years. Unlike traditional machine learning, which requires central data collection, FL keeps data localized on user devices. However, conventional FL assumes that all clien

Haodong Yan, Zhiming Hu, Syn Schmitt, Andreas Bulling

Human motion prediction is important for many virtual and augmented reality (VR/AR) applications such as collision avoidance and realistic avatar generation. Existing methods have synthesised body motion only from observed past motion, despite the fact that human eye gaze is known to correlate strongly with body movements and is readily available in recent V

Min Li, Zhaoyang Yin

We consider the Cauchy problem of the Euler-Poincar\'e equations in $\mathbb{R}^d$ with a varying dispersion parameter $\alpha$. Based on the convex entropy structure and the modified commutator estimates, we have proved that the Euler-Poincar\'e equations have a uniform existence time with respect to $\alpha$ in Sobolev spaces $H^s.$ Combined with the Bona-

Liam Hughes

We observe that non-doubling metric spaces can be characterized as those that contain arbitrarily large sets of approximately equidistant points and use this to show that, for $\gamma \in (0,2]$, the $\gamma$-Liouville quantum gravity metric is almost surely not doubling and thus cannot be quasisymmetrically embedded into any finite-dimensional Euclidean spa

Maxime Ligonnière

This article is devoted to the study of products of random operators of the form $M_{0,n}=M_0\cdots M_{n-1}$, where $(M_{n})_{n\in\mathbb{N}}$ is an ergodic sequence of positive operators on the space of signed measures on a space $\mathbb{X}$. Under suitable conditions, in particular, a Doeblin-type minoration suited for non conservative operators, we obtai

Reza Saadati, Fatimah Shojai

We study the circular motion of massive and massless particles in a recently proposed quantum-corrected Schwarzschild black hole in loop quantum gravity. This solution is supposed to introduce small but non-zero quantum corrections in the low curvature limit. In this paper, we confine our attention to the shadow of the black hole and the geodetic precession

Meizhu Li, Qi Zhang

There is a consensus in science that information theory and statistical physics have a close relationship but the literary proofs of the equivalence between most of the conceptions in the two disciplines are still missing. In this work, according to the statistical ensembles' description of the information sequences that are generated by the i.i.d. single va

Jan Moser

In this paper we obtain number of new equivalents of the Fermat-Wiles theorem that are based on Jacob's ladders. The main of these is the $D$-equivalent that is generated by the Dirichlet's $D(x)$-function.

Debam Biswas

Differentiability of geometric and arithmetic volumes of Hermitian line-bundles leads to the proof of equidistribution results on projective varieties using the variational principle. In this article, we work in the setting of adelic divisors on quasi-projective varieties recently introduced by Xinyi Yuan and Shou-Wu Zhang to show that their geometric and ar

Edi Sutoyo, Andrea Capiluppi

Technical debt (TD) refers to the long-term costs associated with suboptimal design or code decisions in software development, often made to meet short-term delivery goals. Self-Admitted Technical Debt (SATD) occurs when developers explicitly acknowledge these trade-offs in the codebase, typically through comments or annotations. SATD detection has become an

Vyacheslav Grines, Olga Pochinka, Ekaterina Chilina

The present paper is devoted to a study of orientation-preserving homeomorphisms on three-dimensional manifolds with a non-wandering set consisting of a finite number of surface attractors and repellers. The main results of the paper relate to a class of homeomorphisms for which the restriction of the map to a connected component of the non-wandering set is

Antonio Flavio Donnarumma, Manuel Friedrich

We study stochastic homogenisation of free-discontinuity surface functionals defined on piecewise rigid functions which arise in the study of fracture in brittle materials. In particular, under standard assumptions on the density, we show that there exists a $\Gamma$-limit almost surely and that it can be represented by a surface integral. In addition, the e

Manuel Valle, Miguel A. Vazquez-Mozo

The general form of the linear torsional constitutive relations at finite temperature of the chiral current, energy-momentum tensor, and spin energy potential are computed for a chiral fermion fluid minimally coupled to geometric torsion and with nonzero chiral chemical potential. The corresponding transport coefficients are explicitly calculated in terms of

James Hong, Lu Yuan, Michaël Gharbi, Matthew Fisher

How to frame (or crop) a photo often depends on the image subject and its context; e.g., a human portrait. Recent works have defined the subject-aware image cropping task as a nuanced and practical version of image cropping. We propose a weakly-supervised approach (GenCrop) to learn what makes a high-quality, subject-aware crop from professional stock images

Tanisha Joshi, S. D Pathak

We proposed a generalized Lagrangian for three different classes of scalar fields namely quintessence($\alpha =-1$), phantom($\alpha =0$), and tachyonic ($\alpha =1$) parameterized by $\alpha$. These three scalar fields can be described by a common single Lagrangian called generalized scalar field Lagrangian and corresponding scalar field termed as generaliz

Yunfeng Jiang

Integrable quantum field theories can be regularized on the lattice while preserving integrability. The resulting theory on the lattice are integrable lattice models. A prototype of such a regularization is the correspondence between sine-Gordon model and 6-vertex model on a light-cone lattice. We propose an integrable deformation of the light-cone lattice m

Sylvain Carpentier, Alexander V. Mikhailov, Jing Ping Wang

This paper builds upon our recent work, published in Lett. Math. Phys., 112: 94, 2022, where we established that the integrable Volterra lattice on a free associative algebra and the whole hierarchy of its symmetries admits a quantisation dependent on a parameter $\omega$. We also uncovered an intriguing aspect: all odd-degree symmetries of the hierarchy adm

Yijie Liao, Edvin Olofsson, Jan Marcus Dahlström, Liang-Wen Pi

We utilize the reconstruction of attosecond beating by interference of two-photon transitions (RABBIT) technique to study the phase of a Rabi-cycling atom using circularly polarized extreme ultraviolet and infrared (IR) fields, where the IR field induces Rabi oscillations between the 2s and 2p states of lithium. Autler-Townes splittings are observed in sideb

Johannes Koppenwallner, Erich Schikuta

Outsourcing a relational database to the cloud offers several benefits, including scalability, availability, and cost-effectiveness. However, there are concerns about the security and confidentiality of the outsourced data. A general approach here would be to encrypt the data with a standardized encryption algorithm and then store the data only encrypted in

Alessandro Campa, Shamik Gupta

We consider a system of globally-coupled phase-only oscillators with distributed intrinsic frequencies and evolving in presence of distributed Gaussian, white noise, namely, a Gaussian, white noise whose strength for every oscillator is a specified function of its intrinsic frequency. In the absence of noise, the model reduces to the celebrated Kuramoto mode

Farzana Quayyum, Giske Naper Freberg

Cybersecurity challenges and the need for awareness are well-recognized in developed countries, but this still needs attention in less-developed countries. With the expansion of technology, security concerns are also becoming more prevalent worldwide. This paper presents a design and creation research study exploring which factors we should consider when des

Tatsuya Yamaguchi, Mizuki Furo, Yuki Sakai, Takumi Nishikubo

Perovskites with Bi or Pb on the A-site host a number of interesting and yet to be understood phenomena such as negative thermal expansion in BiNiO$_3$. We employ hard x-ray photoemission spectroscopy of Ni 2$p$ core-level as well as valence band to probe the electronic structure of BiNiO$_3$ and PbNiO$_3$. The experimental results supported by theoretical c

V. Gol'dshtein, R. Panenko

We study the procedure of regularization in the context of the Lipschitz version of de Rham calculus on metric simplicial complexes with bounded geometry. It provides us with the machinery to handle the de Rham homomorphism for $L_\pi$-cohomologies. In this respect, we obtain the condition resolving the question of triviality of the kernel for de Rham homomo

Yuxuan Chen, Mark Spivack, Orsola Rath Spivack

The paper develops a method for recovering a one-dimensional rough surface profile from scattered wave field, using a single receiver and repeated measurements when the surface is moving with respect to source and receiver. This extends a previously introduced marching method utilizing low grazing angles, and addresses the key issue of the requirement for ma

Hemanth Chandravamsi, Steven H. Frankel

In this paper, we propose a new set of midpoint-based high-order discretization schemes for computing straight and mixed nonlinear second derivative terms that appear in the compressible Navier-Stokes equations. Firstly, we detail a set of conventional fourth and sixth-order baseline schemes that utilize central midpoint derivatives for the calculation of se

Wengang Guo, Jiayi Yang, Huilin Yin, Qijun Chen

Convolutional Neural Networks (CNNs) have exhibited great performance in discriminative feature learning for complex visual tasks. Besides discrimination power, interpretability is another important yet under-explored property for CNNs. One difficulty in the CNN interpretability is that filters and image classes are entangled. In this paper, we introduce a n

Ioannis Anagnostides, Ioannis Panageas, Gabriele Farina, Tuomas Sandholm

Policy gradient methods enjoy strong practical performance in numerous tasks in reinforcement learning. Their theoretical understanding in multiagent settings, however, remains limited, especially beyond two-player competitive and potential Markov games. In this paper, we develop a new framework to characterize optimistic policy gradient methods in multi-pla

Songhan Ge, Haoyuan Tian, Wei Zhang, Rui Zheng

The loss of cervical lordosis is a common degenerative disorder known to be associated with abnormal spinal alignment. In recent years, ultrasound (US) imaging has been widely applied in the assessment of spine deformity and has shown promising results. The objectives of this study are to automatically segment bony structures from the 3D US cervical spine im

Nai-Chieh Huang, Ping-Chun Hsieh, Kuo-Hao Ho, I-Chen Wu

Proximal Policy Optimization algorithm employing a clipped surrogate objective (PPO-Clip) is a prominent exemplar of the policy optimization methods. However, despite its remarkable empirical success, PPO-Clip lacks theoretical substantiation to date. In this paper, we contribute to the field by establishing the first global convergence results of a PPO-Clip

Marian-Leontin Pop, Levente Tamas

Time-of-Flight (ToF) cameras are becoming popular in a wide span of areas ranging from consumer-grade electronic devices to safety-critical industrial robots. This is mainly due to their high frame rate, relative good precision and the lowered costs. Although ToF cameras are in continuous development, especially pulse-based variants, they still face differen

Bingkun Lai, Jinbo Wen, Jiawen Kang, Hongyang Du

As the next-generation wireless communication system, Sixth-Generation (6G) technologies are emerging, enabling various mobile edge networks that can revolutionize wireless communication and connectivity. By integrating Generative Artificial Intelligence (GAI) with mobile edge networks, generative mobile edge networks possess immense potential to enhance the

Binil Shyam T, Rati Sharma

mRNA translation is a crucial process that leads to protein synthesis in living cells. Therefore, it is a process that needs to work optimally for a cell to stay healthy and alive. With advancements in microscopy and novel experimental techniques, a lot of the intricate details about the translation mechanism are now known. However, the why and how of this m

Ping Wong Ng, Arindam Sutradhar, Cangyuan Wang

Spectral flow was first studied by Atiyah and Lusztig, and first appeared in print in the work of Atiyah-Patodi-Singer (APS). For a norm-continuous path of self-adjoint Fredholm operators in the multiplier algebra $\mathcal{M}(\mathcal{B})$ with $\mathcal{B}$ separable and stable, spectral flow roughly measures the ``net mass" of spectrum that passes through

Junpeng Wu, Riyi Zheng, Jialuo Liang, Manzhu Ke

As a distinctive feature unique to non-Hermitian systems, non-Hermitian skin effect displays fruitful exotic phenomena in one or higher dimensions, especially when conventional topological phases are involved. Among them, hybrid skin-topological effect is theoretically proposed recently, which exhibits anomalous localization of topological boundary states at

Giancarlo Esposito, Gaetano D'Avino, Massimiliano Maria Villone

The manipulation and control of microparticles through non-intrusive methods is pivotal in biomedical applications such as cell sorting and cell focusing. Although several experimental and numerical studies have been dedicated to single suspended particles or clusters of rigid spheres, analogous cases with deformable particles have not been as thoroughly stu

Holger Gies, Philip Heinzel, Johannes Laufkötter, Marta Picciau

We propose relativistic Luttinger fermions as a new ingredient for the construction of fundamental quantum field theories. We construct the corresponding Clifford algebra and the spin metric for relativistic invariance of the action using the spin-base invariant formalism. The corresponding minimal spinor has 32 complex components, matching with the degrees

Lev Sorokin, Ulrich Schoepp

When deploying mission-critical systems in the cloud, where deviations may have severe consequences, the assurance of critical decisions becomes essential. Typical cloud systems are operated by third parties and are built on complex software stacks consisting of e.g., Kubernetes, Istio, or Kafka, which due to their size are difficult to be verified. Neverthe

Xiaoyuan Xie, Shuo Jin, Songqiang Chen, Shing-Chi Cheung

With the wide application of machine translation, the testing of Machine Translation Systems (MTSs) has attracted much attention. Recent works apply Metamorphic Testing (MT) to address the oracle problem in MTS testing. Existing MT methods for MTS generally follow the workflow of input transformation and output relation comparison, which generates a follow-u

The NA62 collaboration

The NA62 experiment at CERN, configured in beam-dump mode, has searched for dark photon decays in flight to electron-positron pairs using a sample of $1.4\times 10^{17}$ protons on dump collected in 2021. No evidence for a dark photon signal is observed. The combined result for dark photon searches in lepton-antilepton final states is presented and a region

Mukesh Kumar Samal, Divya Mishra, Parvendra Kumar

Semiconductor quantum dots are among the best sources of on-demand entangled photon pairs. The degree of entanglement, however, is generally limited by the fine structure splitting of exciton states. In this paper, we theoretically investigate the generation of polarisation-entangled photon pairs under two-photon excitation and cavity-assisted two-photon emi

Guillaume Gbikpi-Benissan, Frédéric Magoulès

This paper introduces the multiplicative variant of the recently proposed asynchronous additive coarse-space correction method. Definition of an asynchronous extension of multiplicative correction is not straightforward, however, our analysis allows for usual asynchronous programming approaches. General asynchronous iterative models are explicitly devised bo

Leandro F. Aurichi, Maddalena Bonanzinga, Davide Giacopello

In these notes we introduce and investigate two new games called R-nw-selective game and the M-nw-selective game. These games naturally arise from the corresponding selection principles involving networks introduced in \cite{BG}.

Gabor B. Hollbeck, René Pilarczyk, Shanshan Wang, Michael Schreckenberg

The congestion of a motorway section is propagated to its neighbouring sections, leading to correlations. The resulting correlation matrix encodes the information on congestion. Here, we study symmetrized time-lagged correlations and show how their spectral properties reveal congestion durations. We carry out an empirical analysis and find a transition behav

Lena G. M. Bauer, Collin Leiber, Christian Böhm, Claudia Plant

Over the last decade, the Dip-test of unimodality has gained increasing interest in the data mining community as it is a parameter-free statistical test that reliably rates the modality in one-dimensional samples. It returns a so called Dip-value and a corresponding probability for the sample's unimodality (Dip-p-value). These two values share a sigmoidal re

Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai

In the rapidly growing digital economy, protecting intellectual property (IP) associated with digital products has become increasingly important. Within this context, machine learning (ML) models, being highly valuable digital assets, have gained significant attention for IP protection. This paper introduces a practical encryption-based framework called \tex

Andrew M. Steane

When gas molecules collide, they accelerate, and therefore encounter the Fulling-Davies-Unruh and Moore-DeWitt effects. The size of these effects is sufficient to randomize the motion of the gas molecules after about 1 nanosecond at standard temperature and pressure. Such observations show that quantum field theory modifies what is required to isolate a phys

Tekin Dereli, Ekin Sıla Yörük

We present a Jordan algebraic formulation of the non-commutative Landau problem coupled to a harmonic potential. To achieve this, an alternative formulation of the Hilbert space version of quantum mechanics is presented. Using this construction, the Hilbert space corresponding to the non-commutative Landau problem is obtained. Non-commutative parameters are

V. Hocdé, R. Smolec, P. Moskalik, R. Singh Rathour

Y~Ophiuchi (Y~Oph) is a classical Cepheid reported to be as dim as a Cepheid of about half its pulsation period, and exhibits a low radial velocity and light-curves amplitude. Our objective is to conduct hydrodynamical pulsation modeling of Y~Oph to derive its distance and provide physical insight to its low amplitude and luminosity, constrained by an extens

Armando Maria Monforte

This thesis explores the application of Plane Wave Discontinuous Galerkin (PWDG) methods for the numerical simulation of electromagnetic scattering by periodic structures. Periodic structures play a pivotal role in various engineering and scientific applications, including antenna design, metamaterial characterization, and photonic crystal analysis. Understa

Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov

Inspired by the diversity and depth of XLand and the simplicity and minimalism of MiniGrid, we present XLand-MiniGrid, a suite of tools and grid-world environments for meta-reinforcement learning research. Written in JAX, XLand-MiniGrid is designed to be highly scalable and can potentially run on GPU or TPU accelerators, democratizing large-scale experimenta

Ran Chen, Jing Zhao, Xiaomin Luo, Xinxue Yan

To improve the environment of the ecosystem, China has implemented the Green-forGrain Program for two decades, which has resulted in an imbalance among ecology.economy and food. This study focuses on the "ecology-food" imbalance problem.taking Sichuan-Chongqing Region as an example, to set up future scenarios topredicate the distribution of ESs. We first for

Stéphane Fischler, Tanguy Rivoal

We solve a long standing problem in the theory of Siegel's $E$-functions, initiated by Lang for Bessel's function $J_0$ in the 60's and considered in full generality by G. Chudnovsky in the 80's: we prove that irrational values taken at rational points by $E$-functions with rational Taylor coefficients have irrationality exponent equal to 2. This result had

Zhiming Hu, Jiahui Xu, Syn Schmitt, Andreas Bulling

Human eye gaze plays a significant role in many virtual and augmented reality (VR/AR) applications, such as gaze-contingent rendering, gaze-based interaction, or eye-based activity recognition. However, prior works on gaze analysis and prediction have only explored eye-head coordination and were limited to human-object interactions. We first report a compreh

Konstantin N. Lyashchenko, Oleg Yu. Andreev, Deyang Yu

We present a study of two-photon electron capture by H-like uranium ions. The energy of the incident electron was chosen to be in the region with the most significant contribution of the dielectric recombination. We studied the photon emission spectrum, including the main resonance groups corresponding to the cascade transition, and the low-energy photon reg

Lingyun Zuo, Keyu An, Shiliang Zhang, Zhijie Yan

In a speech recognition system, voice activity detection (VAD) is a crucial frontend module. Addressing the issues of poor noise robustness in traditional binary VAD systems based on DFSMN, the paper further proposes semantic VAD based on multi-task learning with improved models for real-time and offline systems, to meet specific application requirements. Ev

Prem Nigam Kar, Jitendra Prakash, David E Roberson

We study a class of nonlocal games, called transitive games, for which the set of perfect strategies forms a semigroup. We establish several interesting correspondences of bisynchronous transitive games with the theory of compact quantum groups. In particular, we associate a quantum permutation group with each bisynchronous transitive game and vice versa. We

Carles Martorell, Rubén Calvo, Alessia Annibale, Miguel A. Muñoz

Diverse equilibrium systems with heterogeneous interactions lie at the edge of stability. Such marginally stable states are dynamically selected as the most abundant ones or as those with the largest basins of attraction. On the other hand, systems with non-reciprocal (or asymmetric) interactions are inherently out of equilibrium, and exhibit a rich variety

Aakash Anand, A. Bhattacharyay

We analyse surface-fluctuations-driven fluid flow through nano-channels to investigate the interplay between boundary layer flow structures and the bulk flow of fluid under a pressure-head. Surface fluctuations of a wide range of frequencies (up to several thousands of Hertz) in a nano-channel keep the flow in the low Reynolds number regime. Using this advan

Sichao Xiong, Yigit Ihlamur

This research introduces an innovative evaluation method for the "founder-idea" fit in early-stage startups, utilizing advanced large language model techniques to assess founders' profiles against their startup ideas to enhance decision-making. Embeddings, self-play, tree-of-thought, and critique-based refinement techniques show early promising results that

Federico Ceola, Lorenzo Natale, Niko Sünderhauf, Krishan Rana

Instructing a robot to complete an everyday task within our homes has been a long-standing challenge for robotics. While recent progress in language-conditioned imitation learning and offline reinforcement learning has demonstrated impressive performance across a wide range of tasks, they are typically limited to short-horizon tasks -- not reflective of thos

Hadi Kharaghani, Sho Suda, Yash Shamsundar Khobragade

The existence of a projective plane of order $p\equiv3\pmod{4}$, where $p$ is a prime power, is shown to be equivalent to the existence of a balancedly multi-splittable embeddable $p^2\times p(p+1)$ partial Hadamard matrix.

Alba Crescente, Dario Ferraro, Maura Sassetti

The coherent energy transfer between two quantum devices (a quantum charger and a quantum battery) mediated by a photonic cavity is investigated, in presence of dissipative environments, with particular focus on the the ultrastrong coupling regime. Here, very short transfer times and high charging power can be achieved in comparison with the usually addresse

Alberto Carta, Anwesha Panda, Claude Ederer

We use a combination of density functional theory (DFT) and dynamical mean-field theory (DMFT) to investigate the potential emergence of a charge-disproportionated insulating phase in SrCrO$_{3}$, whereby the Cr cations disproportionate according to $3\text{Cr}^{4+} \rightarrow 2\text{Cr}^{3+} + \text{Cr}^{6+}$ and arrange in ordered planes perpendicular to

Pieter-Jan Hoedt, Günter Klambauer

Input-Convex Neural Networks (ICNNs) are networks that guarantee convexity in their input-output mapping. These networks have been successfully applied for energy-based modelling, optimal transport problems and learning invariances. The convexity of ICNNs is achieved by using non-decreasing convex activation functions and non-negative weights. Because of the

Bennet Gebken

Approximation of subdifferentials is one of the main tasks when computing descent directions for nonsmooth optimization problems. In this article, we propose a bisection method for weakly lower semismooth functions which is able to compute new subgradients that improve a given approximation in case a direction with insufficient descent was computed. Combined

Gilbert Moss, Justin Trias

Let $R$ be a commutative $\mathbb{Z}[1/p]$-algebra, let $m \leq n$ be positive integers, and let $G_n=\text{GL}_n(F)$ and $G_m=\text{GL}_m(F)$ where $F$ is a $p$-adic field. The Weil representation is the smooth $R[G_n\times G_m]$-module $C_c^{\infty}(\text{Mat}_{n\times m}(F),R)$ with the action induced by matrix multiplication. When $R=\mathbb{C}$ or is an

Olaya Álvarez-Tuñón, Yury Brodskiy, Erdal Kayacan

This paper overviews different pose representations and metric functions in visual odometry (VO) networks. The performance of VO networks heavily relies on how their architecture encodes the information. The choice of pose representation and loss function significantly impacts network convergence and generalization. We investigate these factors in the VO net

Jiachun Pan, Hanshu Yan, Jun Hao Liew, Jiashi Feng

Training-free guided sampling in diffusion models leverages off-the-shelf pre-trained networks, such as an aesthetic evaluation model, to guide the generation process. Current training-free guided sampling algorithms obtain the guidance energy function based on a one-step estimate of the clean image. However, since the off-the-shelf pre-trained networks are

Markus Q. Huber, Christian S. Fischer, Hèlios Sanchis-Alepuz

The quenched spectrum of glueballs with positive charge parity is calculated from two-body bound state equations. As input, a self-contained solution for the primitively divergent correlation functions from Dyson-Schwinger equations is used. It only has one parameter to be set which is the physical scale. An important feature of this setup is the consistent

Shengzhe Wang, Zhixin Meng, and Peiqiang Yan, Yuanxing Liu

We present a cold atomic beam source based on a two-dimensional (2D)+ magneto-optical trap (MOT), capable of generating a continuous cold beam of 87Rb atoms with a flux up to 4.3*10^9 atoms/s, a mean velocity of 10.96(2.20) m/s, and a transverse temperature of 16.90(1.56) uK. Investigating the influence of high cooling laser intensity, we observe a significa

Arijit Shaw, Brendan Juba, Kuldeep S. Meel

One approach to probabilistic inference involves counting the number of models of a given Boolean formula. Here, we are interested in inferences involving higher-order objects, i.e., functions. We study the following task: Given a Boolean specification between a set of inputs and outputs, count the number of functions of inputs such that the specification is

Tung Nguyen, Eric Nichols, Randy Gomez

Recently, research in human-robot interaction began to consider a robot's influence at the group level. Despite the recent growth in research investigating the effects of robots within groups of people, our overall understanding of what happens when robots are placed within groups or teams of people is still limited. This paper investigates several key probl

Fabio Saggese, Victor Croisfelt, Francesca Costanzo, Junya Shiraishi

This paper investigates the role and the impact of control operations for dynamic mobile edge computing (MEC) empowered by Reconfigurable Intelligent Surfaces (RISs), in which multiple devices offload their computation tasks to an access point (AP) equipped with an edge server (ES), with the help of the RIS. While usually ignored, the control aspects related

Hugh Dorward, David M. Knowles, Eralp Demir, Mahmoud Mostafavi

Crystal plasticity models are a powerful tool for predicting the deformation behaviour of polycrystalline materials accounting for the underlying grain morphology and texture. These models typically have a large number of parameters, an understanding of which is required to effectively calibrate and apply the model. This study presents a structured framework

Jiale Zhang, Wenfeng Huang, Xiangyun Liao, Qiong Wang

Laparoscopic surgery offers minimally invasive procedures with better patient outcomes, but smoke presence challenges visibility and safety. Existing learning-based methods demand large datasets and high computational resources. We propose the Progressive Frequency-Aware Network (PFAN), a lightweight GAN framework for laparoscopic image desmoking, combining

Tolga Çöplü, Marc Loedi, Arto Bendiken, Mykhailo Makohin

This paper explores the feasibility and performance of on-device large language model (LLM) inference on various Apple iPhone models. Amidst the rapid evolution of generative AI, on-device LLMs offer solutions to privacy, security, and connectivity challenges inherent in cloud-based models. Leveraging existing literature on running multi-billion parameter LL

Jing Nan, Yan Qin, Wei Dai, Chau Yuen

Data-driven soft sensors provide a potentially cost-effective and more accurate modeling approach to measure difficult-to-measure indices in industrial processes compared to mechanistic approaches. Artificial intelligence (AI) techniques, such as deep learning, have become a popular soft sensors modeling approach in the area of machine learning and big data.

Da Luo, Yanglei Gan, Rui Hou, Run Lin

Few-shot Relation Extraction (FSRE) aims to extract relational facts from a sparse set of labeled corpora. Recent studies have shown promising results in FSRE by employing Pre-trained Language Models (PLMs) within the framework of supervised contrastive learning, which considers both instances and label facts. However, how to effectively harness massive inst