March 2024 arXiv papers — page 150

Antonio Laface, Luca Ugaglia

We prove that the Cox ring of the blowing-up of a minimal toric surface of Picard rank two is finitely generated. As part of our proof of this result we provide a necessary and sufficient condition for finite generation of Cox rings of normal projective $\mathbb Q$-factorial surfaces.

Hoi Ping Luk

We classify the dihedral edge-to-edge tilings of the sphere by squares and rhombi.

Pan Du, Meet Hemant Parikh, Xiantao Fan, Xin-Yang Liu

This study introduces the Conditional Neural Field Latent Diffusion (CoNFiLD) model, a novel generative learning framework designed for rapid simulation of intricate spatiotemporal dynamics in chaotic and turbulent systems within three-dimensional irregular domains. Traditional eddy-resolved numerical simulations, despite offering detailed flow predictions,

Pouria Alikhanifard, Nikolaos Tsantalis

Software undergoes constant changes to support new requirements, address bugs, enhance performance, and ensure maintainability. Thus, developers spend a great portion of their workday trying to understand and review the code changes of their teammates. Abstract Syntax Tree (AST) diff tools were developed to overcome the limitations of line-based diff tools,

Hoi Ping Luk

We classify the dihedral edge-to-edge tilings of the sphere by regular polygons and quadrilaterals with equal opposite edges (edge configuration xyxy).

Andrew Douglas, Joe Repka

A subalgebra of a semisimple Lie algebra is wide if every simple module of the semisimple Lie algebra remains indecomposable when restricted to the subalgebra. A subalgebra is narrow if the restrictions of all non-trivial simple modules to the subalgebra have proper decompositions. A semisimple Lie algebra is regular extreme if any regular subalgebra of the

Cunhui Dong, Haichuan Ma, Haotian Zhang, Changsheng Gao

Neural network-based image coding has been developing rapidly since its birth. Until 2022, its performance has surpassed that of the best-performing traditional image coding framework -- H.266/VVC. Witnessing such success, the IEEE 1857.11 working subgroup initializes a neural network-based image coding standard project and issues a corresponding call for pr

Ketan Rikame, Biswajit Paul, Rahul Sharma, V. Jithesh

In eclipsing X-ray binary systems, the direct X-ray emission is blocked by the companion star during the eclipse. We observe only reprocessed emission that contains clues about the environment of the compact object and its chemical composition, ionization levels, etc. We have found flares in some X-ray binaries during their eclipses. The study of eclipse fla

Ruhui Jin, Qin Li, Anjali Nair, Samuel Stechmann

Theoretical inverse problems are often studied in an ideal infinite-dimensional setting. The well-posedness theory provides a unique reconstruction of the parameter function, when an infinite amount of data is given. Through the lens of PDE-constrained optimization, this means one attains the zero-loss property of the mismatch function in this setting. This

Andrew Douglas, Joe Repka

A subalgebra of a semisimple Lie algebra is wide if every simple module of the semisimple Lie algebra remains indecomposable when restricted to the subalgebra. From a finer viewpoint, a subalgebra is $\lambda$-wide if the simple module of a semisimple Lie algebra of highest weight $\lambda$ remains indecomposable when restricted to the subalgebra. A subalgeb

Corbinian Schlosser, Matteo Tacchi

Recently a moment-sum-of-squares hierarchy for exit location estimation of stochastic processes has been presented. When restricting to the special case of the unit ball, we show that the solutions approach the optimal value by a super-polynomial rate. To show this result we state a new effective Positivstellensatz on the sphere with quadratic degree bound b

Julian Fernandez Bonder, Ariel Salort

In this work we investigate the energy of minimizers of Rayleigh-type quotients of the form $$ \frac{\int_\Omega A(|\nabla u|)\, dx}{\int_\Omega A(|u|)\, dx}. $$ These minimizers are eigenfunctions of the generalized laplacian defined as $\Delta_a u = \text{div}\left(a(|\nabla u|)\frac{\nabla u}{|\nabla u|}\right)$ where $a(t)=A'(t)$ and the Rayleigh quotien

Roi Ronen, Ilan Koren, Aviad Levis, Eshkol Eytan

Significant uncertainty in climate prediction and cloud physics is tied to observational gaps relating to shallow scattered clouds. Addressing these challenges requires remote sensing of their three-dimensional (3D) heterogeneous volumetric scattering content. This calls for passive scattering computed tomography (CT). We design a learning-based model (ProbC

Kevin Joshua T, Arnav Agarwal, Shriya Sanjay, Yash Sarda

Conversational systems are crucial for human-computer interaction, managing complex dialogues by identifying threads and prioritising responses. This is especially vital in multi-party conversations, where precise identification of threads and strategic response prioritisation ensure efficient dialogue management. To address these challenges an end-to-end mo

Xinlei Shao, Hongruixuan Chen, Kirsty Magson, Jiaqi Wang

Since coral reef ecosystems face threats from human activities and climate change, coral conservation programs are implemented worldwide. Monitoring coral health provides references for guiding conservation activities. However, current labor-intensive methods result in a backlog of unsorted images, highlighting the need for automated classification. Few stud

M. Ashraf Bhat, G. Sankara Raju Kosuru

We establish trace inequalities for Riesz potentials on Herz-type spaces and discuss the optimality of conditions imposed on specific parameters. We also present some applications in the form of Sobolev-type inequalities, including the Gagliardo-Nirenberg-Sobolev inequality and the fractional integration theorem in the Herz space setting. In addition, we obt

Eugene Goldberg

Typically, a practical algorithm of hardware verification obtains a semantic result by being applied to a particular formula $F$. That is, although this algorithm uses the specifics of $F$ (sometimes inadvertently), its result holds for all formulas logically equivalent to $F$. We refer to computations that get a semantic result by intentionally exploiting t

Meysam Miralaei, Ali Mohammadian, Behruz Tayfeh-Rezaie

The $r$-edge bootstrap percolation on a graph is an activation process of the edges. The process starts with some initially activated edges and then, in each round, any inactive edge whose one of endpoints is incident to at least $r$ active edges becomes activated. A set of initially activated edges leading to the activation of all edges is said to be a perc

Benjamin Sambale

We call a finite group G ultrasolvable if it has a characteristic subgroup series whose factors are cyclic. It was shown by Durbin--McDonald that the automorphism group of an ultrasolvable group is supersolvable. The converse statement was established by Baartmans--Woeppel under the hypothesis that G has no direct factor isomorphic to the Klein four-group. W

Joshua Yancosek, Ali Baheri

The rigorous safety verification of control systems in critical applications is essential, given their increasing complexity and integration into everyday life. Simulation-based falsification approaches play a pivotal role in the safety verification of control systems, particularly within critical applications. These methods systematically explore the operat

Yanyi Zhang, Qi Jia, Xin Fan, Yu Liu

Attribute and object (A-O) disentanglement is a fundamental and critical problem for Compositional Zero-shot Learning (CZSL), whose aim is to recognize novel A-O compositions based on foregone knowledge. Existing methods based on disentangled representation learning lose sight of the contextual dependency between the A-O primitive pairs. Inspired by this, we

Dan Crisan, Oana Lang

For a class of evolution equations that possibly have only local solutions, we introduce a stochastic component that ensures that the solutions of the corresponding stochastically perturbed equations are global. The class of partial differential equations amenable for this type of treatment includes the 3D Navier-Stokes equation, the rotating shallow water e

Yiping Liu, Siqi Xu, Chandan Mondal, Xingbo Zhao

We obtain all the leading-twist quark generalized parton distributions (GPDs) inside the proton at nonzero skewness within the basis light-front quantization framework. We employ the light-front wave functions of the proton from a light-front quantized Hamiltonian in the valence Fock sector consisting of a three-dimensional confinement potential and a one-gl

Bohui Zhang, Valentina Anita Carriero, Katrin Schreiberhuber, Stefani Tsaneva

Ontology engineering (OE) in large projects poses a number of challenges arising from the heterogeneous backgrounds of the various stakeholders, domain experts, and their complex interactions with ontology designers. This multi-party interaction often creates systematic ambiguities and biases from the elicitation of ontology requirements, which directly affe

Syed I. Munzir, Daniel B. Hier, Michael D. Carrithers

Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic health records requires high throughput methods. Over the past thirty years, progress toward making high throughput phenotyping feasible. In this study, we demonstrate that a large lang

Hirotaka Wakuta

We study conditions that the semiquantised Riemannian metric $g_Q$ and Levi-Civita connection $\nabla_Q$ have the same form as classical one in semiclassical theory. Concrete examples of semiclassical theory have been computed by Majid et al. for upper half-planes, hemispheres and complex projective spaces. However, only in the example of the upper half-plan

Ming Zheng, Yang Yang, Zhi-Hang Zhao, Shan-Chao Gan

In the field of data mining and machine learning, commonly used classification models cannot effectively learn in unbalanced data. In order to balance the data distribution before model training, oversampling methods are often used to generate data for a small number of classes to solve the problem of classifying unbalanced data. Most of the classical oversa

Vivek Mishra, Ge Wang, P. J. Hirschfeld

There is considerable evidence that the heavy fermion material UTe$_2$ is a spin-triplet superconductor, possibly manifesting time-reversal symmetry breaking, as measured by Kerr effect and muon spin resonance experiments below the critical temperature, in some samples. Such signals can arise due to a chiral orbital state, or possible nonunitary pairing. Alt

Hao Lu, Xuesong Niu, Jiyao Wang, Yin Wang

Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in language understanding, it is critical to evaluate the performance of downstream tasks for better human-centric applications. This paper assesses the application of MLLMs with 5 cru

Fei Wang, Qi Liu, Enhong Chen, Chuanren Liu

Cognitive diagnosis models have been widely used in different areas, especially intelligent education, to measure users' proficiency levels on knowledge concepts, based on which users can get personalized instructions. As the measurement is not always reliable due to the weak links of the models and data, the uncertainty of measurement also offers important

Rocío Milagros Besana, Federico Elías, Joaquín Puig, Jazmín Aragón Sánchez

Novel hyperuniform materials are emerging as an active field of applied and basic research since they can be designed to have exceptional physical properties. This ubiquitous state of matter presents a hidden order that is characterized by the density of constituents of the system being uniform at large scales, as in a perfect crystal, although they can be i

Pietro Luigi Muzzeddu, Andrea Gambassi, Jens-Uwe Sommer, Abhinav Sharma

Polymer-like structures are ubiquitous in nature and synthetic materials. Their configurational and migration properties are often affected by crowded environments leading to non-thermal fluctuations. Here, we study an ideal Rouse chain in contact with a non-homogeneous active bath, characterized by the presence of active self-propelled agents which exert ti

Gergely Horvath

We experimentally study effort provision and network formation in the linear-quadratic game characterized by positive externality and complementarity of effort choices among network neighbors. We compare experimental outcomes to the equilibrium and efficient allocations and study the impact of group size and linking costs. We find that individuals overprovid

Hairong Shi, Songhao Han, Shaofei Huang, Yue Liao

Tumor lesion segmentation on CT or MRI images plays a critical role in cancer diagnosis and treatment planning. Considering the inherent differences in tumor lesion segmentation data across various medical imaging modalities and equipment, integrating medical knowledge into the Segment Anything Model (SAM) presents promising capability due to its versatility

Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Susan A. Murphy

Imagine if AI decision-support tools not only complemented our ability to make accurate decisions, but also improved our skills, boosted collaboration, and elevated the joy we derive from our tasks. Despite the potential to optimize a broad spectrum of such human-centric objectives, the design of current AI tools remains focused on decision accuracy alone. W

Jinlong Li, Shucheng Pan

We present a cross-architecture high-order heterogeneous Navier-Stokes simulation solver, XFluids, for compressible reacting multicomponent flows on different platforms. The multi-component reacting flows are ubiquitous in many scientific and engineering applications, while their numerical simulations are usually time-consuming to capture the underlying mult

Elise Grosjean, Alex Keilmann, Henry Jäger, Shimi Mohanan

We develop a model the dynamics of human mesenchymal stem cells (hMSCs) and chondrocytes evolving in a nonwoven polyethylene terephtalate (PET) scaffold impregnated with hyaluron and supplied with a differentiation medium. The scaffold and the cells are assumed to be contained in a bioreactor with fluid perfusion. The differentiation of hMSCs into chondrocyt

Sara Santos, Xinyu Song, Vincenzo Savona

The simulation of many-body open quantum systems is key to solving numerous outstanding problems in physics, chemistry, material science, and in the development of quantum technologies. Near-term quantum computers may bring considerable advantage for the efficient simulation of their static and dynamical properties, thanks to hybrid quantum-classical variati

Junyi Cao, Zhichao Li, Naiyan Wang, Chao Ma

Recent studies have highlighted the promising application of NeRF in autonomous driving contexts. However, the complexity of outdoor environments, combined with the restricted viewpoints in driving scenarios, complicates the task of precisely reconstructing scene geometry. Such challenges often lead to diminished quality in reconstructions and extended durat

Jingyun Xue, Tao Wang, Pengwen Dai, Kaihao Zhang

Under-Display Camera (UDC) is an emerging technology that achieves full-screen display via hiding the camera under the display panel. However, the current implementation of UDC causes serious degradation. The incident light required for camera imaging undergoes attenuation and diffraction when passing through the display panel, leading to various artifacts i

Heiko Dietrich, Willem A. de Graaf

We present a computational approach to determine the space of almost-inner derivations of a finite dimensional Lie algebra given by a structure constant table. We also present an example of a Lie algebra for which the quotient algebra of the almost-inner derivations modulo the inner derivations is non-abelian. This answers a question of Kunyavskii and Ostape

Jacob H. Rothschild

Assuming power travels instantaneously, can be steered by us, and is lost quadratically in each power line, the dynamic optimal power flow problem simplifies to a min-cost dynamic generalized flow with quadratic losses (MCDGFWQL) problem. As this is a special case of the min-cost concave dynamic generalized flow (MCCDGF) problem, we derive both general resul

Pratyush Kumar Mohanty, Akhilesh Kumar Sahu, Ram Prakash Bharti

In this study, the role of solvent viscosity ratio ($\beta$) on the creeping flow characteristics of Oldroyd-B fluid over a channel-confined circular cylinder has been explored numerically. The hydrodynamic model equations have been solved by RheoTool, an open-source toolbox based on OpenFOAM, employing the finite volume method for extensive ranges of Debora

Waseem Akbar, Andrzej Biborski, Louk Rademaker, Michał Zegrodnik

We investigate strong coupling topological superconductivity in twisted moir\'e bilayer WSe$_2$. Our approach is based on an effective $t$-$J$ model with displacement-field-dependent complex hoppings, which is treated with the variational Gutzwiller projection method. The calculated phase diagram contains domes of topologically nontrivial superconducting pha

Verena Blaschke, Barbara Kovačić, Siyao Peng, Barbara Plank

This document provides the annotation guidelines for MaiBaam, a Bavarian corpus manually annotated with part-of-speech (POS) tags, syntactic dependencies, and German lemmas. MaiBaam belongs to the Universal Dependencies (UD) project, and our annotations elaborate on the general and German UD version 2 guidelines. In this document, we detail how to preprocess

Garry Goldstein

In this work we re-examine the Wilson Fisher fixed point. We study Wilsonian momentum space renormalization group (RG) flow for various forms of the cutoff. We show that already at order $\left(4-d\right)^{1}$, where $d$ is the dimension of the $\phi^{4}$ theory, there are changes to the position of the fixed point and the direction of irrelevant coupling pa

Rassul Bairamkulov, Mingfei Yu, Giovanni De Micheli

Rapid single-flux quantum (RSFQ), a leading cryogenic superconductive electronics (SCE) technology, offers extremely low power dissipation and high speed. However, implementing RSFQ systems at VLSI complexity faces challenges, such as substantial area overhead from gate-level pipelining and path balancing, exacerbated by RSFQ's limited layout density. T1 fli

Alexander Ostermann, Nasrin Vaisi

The exponential trapezoidal rule is proposed and analyzed for the numerical integration of semilinear integro-differential equations. Although the method is implicit, the numerical solution is easily obtained by standard fixed-point iteration, making its implementation straightforward. Second-order convergence in time is shown in an abstract Hilbert space fr

Mohamed Abdalmoaty, Efe C. Balta, John Lygeros, Roy S. Smith

It is well known that ignoring the presence of stochastic disturbances in the identification of stochastic Wiener models leads to asymptotically biased estimators. On the other hand, optimal statistical identification, via likelihood-based methods, is sensitive to the assumptions on the data distribution and is usually based on relatively complex sequential

Ru-Kui Zhang, Jun Jiang, Chen-Zhong Dong, Yong-Bo Tang

The dynamic electric dipole polarizabilities of the $5s^2~^1S_0$, $5s5p~^3P_{0}$, and $5s5p~^3P_2$ states for Cd atoms are calculated using the relativistic configuration interaction plus many-body perturbation theory method. The magic wavelengths for the $5s^2~^1S_0\rightarrow 5s5p~^3P_{0}$ and $5s^2~^1S_0\rightarrow 5s5p~^3P_2$ transitions within a range o

Ximiao Zhang, Min Xu, Xiuzhuang Zhou

Self-supervised feature reconstruction methods have shown promising advances in industrial image anomaly detection and localization. Despite this progress, these methods still face challenges in synthesizing realistic and diverse anomaly samples, as well as addressing the feature redundancy and pre-training bias of pre-trained feature. In this work, we intro

Xueqian Li, Simon Lucey

In contrast to current state-of-the-art methods, such as NSFP [25], which employ deep implicit neural functions for modeling scene flow, we present a novel approach that utilizes classical kernel representations. This representation enables our approach to effectively handle dense lidar points while demonstrating exceptional computational efficiency -- compa

Xiuzhe Wu, Xiaoyang Lyu, Qihao Huang, Yong Liu

Although considerable advancements have been attained in self-supervised depth estimation from monocular videos, most existing methods often treat all objects in a video as static entities, which however violates the dynamic nature of real-world scenes and fails to model the geometry and motion of moving objects. In this paper, we propose a self-supervised m

Cuong Pham, Van-Anh Nguyen, Trung Le, Dinh Phung

Knowledge distillation is an attractive approach for learning compact deep neural networks, which learns a lightweight student model by distilling knowledge from a complex teacher model. Attention-based knowledge distillation is a specific form of intermediate feature-based knowledge distillation that uses attention mechanisms to encourage the student to bet

Shreyas Jain, V. Arvind Rameshwar, Navin Kashyap

This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a sampler that produces codewords according to a suitably defined Gibbs distribution. We apply our method to moderate-block

Shining Lin, Jiancheng An, Lu Gan, Mérouane Debbah

Low earth orbit (LEO) satellite communication systems have gained increasing attention as a crucial supplement to terrestrial wireless networks due to their extensive coverage area. This letter presents a novel system design for LEO satellite systems by leveraging stacked intelligent metasurface (SIM) technology. Specifically, the lightweight and energy-effi

Matthew J. Colbrook

Residual Dynamic Mode Decomposition (ResDMD) offers a method for accurately computing the spectral properties of Koopman operators. It achieves this by calculating an infinite-dimensional residual from snapshot data, thus overcoming issues associated with finite truncations of Koopman operators, such as spurious eigenvalues. These spectral properties include

Yichen Li, Qunwei Li, Haozhao Wang, Ruixuan Li

In Federated Learning (FL), the data in each client is typically assumed fixed or static. However, data often comes in an incremental manner in real-world applications, where the data domain may increase dynamically. In this work, we study catastrophic forgetting with data heterogeneity in Federated Incremental Learning (FIL) scenarios where edge clients may

Henri Alloul

We established that the morphology of the phase diagrams is mostly governed by disorder in the various cuprate families. In the minimally disordered YBCO substitutions of Zn or Li spinless impurities on the planar Cu sites control the extent of the spin glass phase and superconducting (SC) dome. NMR data establish that these defects induce in their vicinity

Yajie Zhang, Yanzun Meng, Zuoqiang Shi

In this paper, we propose a class of nonlocal models to approximate the Poisson model on manifolds with homogeneous Neumann boundary condition, where the manifolds are assumed to be embedded in high dimensional Euclid spaces. In comparison to the existing nonlocal approximation of Poisson models with Neumann boundary, we optimize the truncation error of mode

Hexin Liu, Xiangyu Zhang, Haoyang Zhang, Leibny Paola Garcia

Code-switching (CS) refers to the switching of languages within a speech signal and results in language confusion for automatic speech recognition (ASR). To address language confusion, we propose a language alignment loss (LAL) that aligns acoustic features to pseudo-language labels learned from the ASR decoder during ASR training. This approach enables fram

Shuang Du

While the precise mechanism of generating pulsed coherent radio emission from pulsars remains elusive, certain gap-invoking models (especially, the inner gap model) offer a comprehensive and plausible explanation for the genesis and termination of such emissions. However, the transition stage between the period of persistent radio emission and the period of

Runhua Jiang, Yahong Han

Existing image restoration models are typically designed for specific tasks and struggle to generalize to out-of-sample degradations not encountered during training. While zero-shot methods can address this limitation by fine-tuning model parameters on testing samples, their effectiveness relies on predefined natural priors and physical models of specific de

Jun Xia, Shaorong Chen, Jingbo Zhou, Tianze Ling

Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the analysis of protein composition in biological samples. Despite the development of various deep learning methods for identifying amino acid sequences (peptides) responsible for observed spectra, challenges persist in \emph{de novo} peptide sequencing. Firstly, prior metho

Santu Prasad Jana, Shivangi, Suraina Gupta, Anjan K. Gupta

Scalable methods for improving the performance and stability of a field-effect transistor (FET) based on two-dimensional materials are crucial for its real applications. A scalable method of encapsulating the exfoliated MoS$ _{2} $ on SiO$ _{2} $/Si substrate by hexamethyldisilazane (HMDS) is explored here for reducing the influence of interface traps and am

Rassul Bairamkulov, Giovanni De Micheli

Rapid single-flux quantum (RSFQ) is one of the most advanced superconductive electronics technologies. SFQ systems operate at tens of gigahertz with up to three orders of magnitude smaller power as compared to CMOS. In conventional SFQ systems, most gates require clock signal. Each gate should have the fanins with equal logic depth, necessitating insertion o

Z. J. Zheng, Q. Y. Peng, F. R. Lin, D. Li

Context. In Gaia era, atmospheric turbulence, which causes stochastic wander of a star image, is a fundamental limitation to the astrometric accuracy of ground-based optical imaging. However, the positional bias caused by turbulence (called turbulence error here) can be effectively reduced by measuring a target relative to another reference (a star or a fast

Prarabdh Shukla, Gagan Raj Gupta, Kunal Dutta

In this work, we propose a novel dimensionality reduction technique, DiffRed, which first projects the data matrix, A, along first $k_1$ principal components and the residual matrix $A^{*}$ (left after subtracting its $k_1$-rank approximation) along $k_2$ Gaussian random vectors. We evaluate M1, the distortion of mean-squared pair-wise distance, and Stress,

Rui Yang, Haoran Liu, Edison Marrese-Taylor, Qingcheng Zeng

Large language models (LLMs) have demonstrated impressive generative capabilities with the potential to innovate in medicine. However, the application of LLMs in real clinical settings remains challenging due to the lack of factual consistency in the generated content. In this work, we develop an augmented LLM framework, KG-Rank, which leverages a medical kn

Puneet Kumar, Alexander Vedernikov, Yuwei Chen, Wenming Zheng

Analysis of stress, depression and engagement is less common and more complex than that of frequently discussed emotions such as happiness, sadness, fear and anger. The importance of these psychological states has been increasingly recognized due to their implications for mental health and well-being. Stress and depression are interrelated and together they

Ramin Abolfath, Niayesh Afshordi, Sohrab Rahvar, Adri van Duin

We present a multi-scale formalism that accounts for the formation of nano-scale bubbles/cavities owing to a burst of water molecules after the passage of high energy charged particles that leads to the formation of hot non-ionizing excitations or thermal spikes (TS). We demonstrate the coexistence of a rapidly growing condensed state of water and a hot spot

Bangyu Lan, Momen Abayazid, Nico Verdonschot, Stefano Stramigioli

In Total Knee Replacement Arthroplasty (TKA), surgical robotics can provide image-guided navigation to fit implants with high precision. Its tracking approach highly relies on inserting bone pins into the bones tracked by the optical tracking system. This is normally done by invasive, radiative manners (implantable markers and CT scans), which introduce unne

Ghalib Ahmed Tahir, Murtaza Ashraf

Employee turnover remains a pressing issue within high-tech sectors such as IT firms and research centers, where organizational success heavily relies on the skills of their workforce. Intense competition and a scarcity of skilled professionals in the industry contribute to a perpetual demand for highly qualified employees, posing challenges for organization

Yorick Broens, Hans Butler, Roland Tóth

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-depe

Marco Baioletti, Valentino Santucci, Marco Tomassini

During the last decades many metaheuristics for global numerical optimization have been proposed. Among them, Basin Hopping is very simple and straightforward to implement, although rarely used outside its original Physical Chemistry community. In this work, our aim is to compare Basin Hopping, and two population variants of it, with readily available implem

Anna Mancini, Antonio Desiderio, Giovanni Palermo, Riccardo Di Clemente

Nowadays human interactions largely take place on social networks, with online users' behavior often falling into a few general typologies or "social roles". Among these, opinion leaders are of crucial importance as they have the ability to spread an idea or opinion on a large scale across the network, with possible tangible consequences in the real world. I

Song He, Pak Hang Chris Lau, Long Zhao

Quantum informatic quantities such as entanglement entropy are useful in detecting quantum phase transitions. Recently, a new entanglement measure called pseudo-entropy was proposed which is a generalization of the more well-known entanglement entropy. It has many nice properties and is useful in the study of post-selection measurements. In this paper, one o

Boshen Xu, Sipeng Zheng, Qin Jin

We introduce SPAFormer, an innovative model designed to overcome the combinatorial explosion challenge in the 3D Part Assembly (3D-PA) task. This task requires accurate prediction of each part's poses in sequential steps. As the number of parts increases, the possible assembly combinations increase exponentially, leading to a combinatorial explosion that sev

Yen-Trang Dang, Thanh-Le Cong, Phuc-Thanh Nguyen, Anh M. T. Bui

Open-source development has revolutionized the software industry by promoting collaboration, transparency, and community-driven innovation. Today, a vast amount of various kinds of open-source software, which form networks of repositories, is often hosted on GitHub - a popular software development platform. To enhance the discoverability of the repository ne

Bhuvaneswari R, Mandar M Deshmukh, Umesh V Waghmare

Magnetic field emerging from the geometric curvature of quantum structure of electrons in a crystal bends electronic trajectory causing anomalous linear and nonlinear electrical Hall effects that have been observed in low symmetry crystals with narrow electronic band gap. We present first-principles theoretical analysis to show that dynamical lowering of cry

Severin Diederichs, Carlo Benedetti, Angel Ferran Pousa, Alexander Sinn

Linear colliders rely on high-quality flat beams to achieve the desired event rate, while avoiding potentially deleterious beamstrahlung effects. Here, we show that flat beams in plasma accelerators can be subject to quality degradation due to emittance mixing. This effect occurs when the beam particles' betatron oscillations in a nonlinearly coupled wakefie

Xianghao Yao, Jiancheng An, Lu Gan, Marco Di Renzo

Emerging technologies, such as holographic multiple-input multiple-output (HMIMO) and stacked intelligent metasurface (SIM), are driving the development of wireless communication systems. Specifically, the SIM is physically constructed by stacking multiple layers of metasurfaces and has an architecture similar to an artificial neural network (ANN), which can

Huandong Chen, Shantanu Singh, Hongyan Mei, Guodong Ren

BaTiS3, a quasi-1D complex chalcogenide, has gathered considerable scientific and technological interest due to its giant optical anisotropy and electronic phase transitions. However, the synthesis of high-quality BaTiS3 crystals, particularly those featuring crystal sizes of millimeters or larger, remains a challenge. Here, we investigate the growth of BaTi

Zhicheng Wang, Wandi Wei, Ruiqi Yu, Jun Wu

Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots. However, there is a notable gap in analytical research concerning estimations. Therefore, we endeavor to further understand how various types of estimations influence the decision

Deepthi G., S. Chandankumar

Let $\overline{p}_o(n)$ denote the number of overpartitions of $n$ into odd parts. The partition function $\overline{p}_o(n)$ has been the subject of many recent studies where many explicit Ramanujan-like congruences were discovered. In this paper, we provide three linear recurrence relation for $\overline{p}_o(n)$. Several connections with partitions into p

Josue Knorst, Artur O. Lopes

Given a smooth potential $W:\mathrm{T}^{n} \to \mathbb{R}$ on the torus, the Quantum Guerra-Morato action functional is given by \smallskip $ \,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, \,\,\,\,\,\,\,\,\, I(\psi) = \int\,(\, \, \,\frac{D v\, D v^*}{2}(x) - W(x) \,) \,\,a(x)^2 dx,$ \smallskip \noindent where $\psi $ is described by $\psi = a\, e^{i\,\frac{ u }{h}}

Mojtaba Taherisadr, Salma Elmalaki

In the evolving landscape of human-centric systems, personalized privacy solutions are becoming increasingly crucial due to the dynamic nature of human interactions. Traditional static privacy models often fail to meet the diverse and changing privacy needs of users. This paper introduces PEaRL, a system designed to enhance privacy preservation by tailoring

Mrabet Becher, Maher Boudabra, Fathi Haggui

In this work, we introduce the Skorokhod energy of a simply connected domain. We show that among all domains solving the planar Skorokhod embedding problem, Gross solution generates the domain with the minimal Skorokhod energy.

Agelos Georgakopoulos, Matthias Hamann

Halin's well-known grid theorem states that a graph $G$ with a thick end must contain a subdivision of the hexagonal half-grid. We obtain the following strengthening when $G$ is vertex-transitive and locally finite. Either $G$ is quasi-isometric to a tree (and therefore has no thick end), or it contains a subdivision of the full hexagonal grid.

Yoochan Kim, Kihyun Kim, Yonghyeon Cho, Jinwoo Kim

Distributed Deep Learning (DDL), as a paradigm, dictates the use of GPU-based clusters as the optimal infrastructure for training large-scale Deep Neural Networks (DNNs). However, the high cost of such resources makes them inaccessible to many users. Public cloud services, particularly Spot Virtual Machines (VMs), offer a cost-effective alternative, but thei

Per Mattsson, Fabio Bonassi, Valentina Breschi, Thomas B. Schön

Recently, several direct Data-Driven Predictive Control (DDPC) methods have been proposed, advocating the possibility of designing predictive controllers from historical input-output trajectories without the need to identify a model. In this work, we show that these approaches are equivalent to an indirect approach. Reformulating the direct methods in terms

Florence Débarre, Michael Worobey

The centrality of Wuhan's Huanan market in maps of December 2019 COVID-19 case residential locations, established by Worobey et al. (2022a), has recently been challenged by Stoyan and Chiu (2024, SC2024). SC2024 proposed a statistical test based on the premise that the measure of central tendency (hereafter, "centre") of a sample of case locations must coinc

Pavel Osinenko, Stefan Streif

This paper investigates the possibility of constructive extraction of measurable selector from set-valued maps which may commonly arise in viability theory, optimal control, discontinuous systems etc. For instance, existence of solutions to certain differential inclusions, often requires iterative extraction of measurable selectors. Next, optimal controls ar

DengYu Shi

With the growing demand for energy and increased environmental awareness, Non-Intrusive Load Monitoring (NILM) has become an essential tool in smart grid and energy management. By analyzing total power load data, NILM infers the energy usage of individual appliances without the need for separate sensors, enabling real-time monitoring from a few locations. Th

Prasanna Kumar Billa, Tejaswi Josyula, Cameron Tropea, Pallab Sinha Mahapatra

In this study, we experimentally examine the behavior of a free-falling rigid sphere penetrating a quiescent liquid pool. Observations of the sphere trajectory in time are made using two orthogonally placed high-speed cameras, yielding the velocity and acceleration vector through repeated differentiation of the time-resolved trajectories. The novelty of this

Boshen Xu, Sipeng Zheng, Qin Jin

We humans are good at translating third-person observations of hand-object interactions (HOI) into an egocentric view. However, current methods struggle to replicate this ability of view adaptation from third-person to first-person. Although some approaches attempt to learn view-agnostic representation from large-scale video datasets, they ignore the relatio

Christopher Katins, Paweł W. Woźniak, Aodi Chen, Ihsan Tumay

Current research in Mixed Reality (MR) presents a wide range of novel use cases for blending virtual elements with the real world. This yet-to-be-ubiquitous technology challenges how users currently work and interact with digital content. While offering many potential advantages, MR technologies introduce new security, safety, and privacy challenges. Thus, i

Qihao Zhao, Yalun Dai, Hao Li, Wei Hu

Long-tail recognition is challenging because it requires the model to learn good representations from tail categories and address imbalances across all categories. In this paper, we propose a novel generative and fine-tuning framework, LTGC, to handle long-tail recognition via leveraging generated content. Firstly, inspired by the rich implicit knowledge in

Lei Niu, Yuheng Song

In this paper we study the permanence and impermanence for continuous-time competitive Kolmogorov systems via the carrying simplex. We first give an extension to attractors of V. Hutson's results on the existence of repellors in continuous-time dynamical systems that have found wide use in the study of permanence via average Liapunov functions. We then give

Hanzheng Wang, Wei Li, Xiang-Gen Xia, Qian Du

Hyperspectral video (HSV) offers valuable spatial, spectral, and temporal information simultaneously, making it highly suitable for handling challenges such as background clutter and visual similarity in object tracking. However, existing methods primarily focus on band regrouping and rely on RGB trackers for feature extraction, resulting in limited explorat