March 2024 arXiv papers — page 93

Elisabeth Agoritsas, Peter K. Morse

Protocol-dependent states in structural glasses can encode a disordered, yet retrievable memory. While training such materials is typically done via a global drive, such as external shear, in dense active matter the driving is instead local and spatio-temporally correlated. Here we focus on the impact of such spatial correlation on memory formation. We inves

Juan Zhang, Jiahao Chen, Cheng Wang, Zhiwang Yu

With the widespread popularity of internet celebrity marketing all over the world, short video production has gradually become a popular way of presenting products information. However, the traditional video production industry usually includes series of procedures as script writing, video filming in a professional studio, video clipping, special effects ren

Zhengzheng Tu, Zigang Zhu, Yayang Duan, Bo Jiang

Ultrasound video-based breast lesion segmentation provides a valuable assistance in early breast lesion detection and treatment. However, existing works mainly focus on lesion segmentation based on ultrasound breast images which usually can not be adapted well to obtain desirable results on ultrasound videos. The main challenge for ultrasound video-based bre

Kohei Shibata, Makoto Naka, Harald O. Jeschke, Junya Otsuki

Akali superoxides AO2 (A=Na, K, Rb, Cs), due to an open p shell of the oxygen ion O2^- with degenerate pi orbitals, have spin and orbital degrees of freedom. The complex magnetic, orbital, and structural phase transitions observed experimentally in this family of materials are only partially understood. Based on density functional theory, we derive a strong-

Junge Zhang, Qihang Zhang, Li Zhang, Ramana Rao Kompella

Generating unbounded 3D scenes is crucial for large-scale scene understanding and simulation. Urban scenes, unlike natural landscapes, consist of various complex man-made objects and structures such as roads, traffic signs, vehicles, and buildings. To create a realistic and detailed urban scene, it is crucial to accurately represent the geometry and semantic

Maksim Velikanov, Maxim Panov, Dmitry Yarotsky

The asymptotically precise estimation of the generalization of kernel methods has recently received attention due to the parallels between neural networks and their associated kernels. However, prior works derive such estimates for training by kernel ridge regression (KRR), whereas neural networks are typically trained with gradient descent (GD). In the pres

Ali Asghar Sharifi, Ali Zoljodi, Masoud Daneshtalab

Autonomous driving systems are a rapidly evolving technology that enables driverless car production. Trajectory prediction is a critical component of autonomous driving systems, enabling cars to anticipate the movements of surrounding objects for safe navigation. Trajectory prediction using Lidar point-cloud data performs better than 2D images due to providi

Zhuoyuan Li, Zikun Yuan, Li Li, Dong Liu

In modern video coding standards, block-based inter prediction is widely adopted, which brings high compression efficiency. However, in natural videos, there are usually multiple moving objects of arbitrary shapes, resulting in complex motion fields that are difficult to represent compactly. This problem has been tackled by more flexible block partitioning m

Maojun Zhang, Guangxu Zhu, Richeng Jin, Xiaoming Chen

Semantic communication (SemCom) is emerging as a key technology for future sixth-generation (6G) systems. Unlike traditional bit-level communication (BitCom), SemCom directly optimizes performance at the semantic level, leading to superior communication efficiency. Nevertheless, the task-oriented nature of SemCom renders it challenging to completely replace

Shaun T. Brown, Azadeh Fattahi, Ian G. McCarthy, Andreea S. Font

We present the new ARTEMIS Emulator suite of high resolution (baryon mass of $2.23 \times 10^{4}$ $h^{-1}$M$_{\odot}$) zoom-in simulations of Milky Way mass systems. Here, three haloes from the original ARTEMIS sample have been rerun multiple times, systematically varying parameters for the stellar feedback model, the density threshold for star formation, th

Lisa Weijler, Muhammad Jehanzeb Mirza, Leon Sick, Can Ekkazan

Test-Time Training (TTT) proposes to adapt a pre-trained network to changing data distributions on-the-fly. In this work, we propose the first TTT method for 3D semantic segmentation, TTT-KD, which models Knowledge Distillation (KD) from foundation models (e.g. DINOv2) as a self-supervised objective for adaptation to distribution shifts at test-time. Given a

Chiara Gavioli, Leon Happ, Valerio Pagliari

Motivated by manifold-constrained homogenization problems, we construct suitable extensions for Sobolev functions defined on a perforated domain and taking values in a compact, connected $C^2$-manifold without boundary. The proof combines a by now classical extension result for the unconstrained case with a retraction argument that heavily relies on the topo

Haoyu Zhao, Wenhui Dong, Rui Yu, Zhou Zhao

The task of single-source domain generalization (SDG) in medical image segmentation is crucial due to frequent domain shifts in clinical image datasets. To address the challenge of poor generalization across different domains, we introduce a Plug-and-Play module for data augmentation called MoreStyle. MoreStyle diversifies image styles by relaxing low-freque

Xiao Zhang, Ning Mao, Oleg Janson, Jeroen van den Brink

The recently synthesized ternary quasi-2D material TaRhTe$_4$ is a bulk Weyl semimetal with an intrinsically layered structure, which poses the question how the topology of its electronic structure depends on layers separations. Experimentally these separations may be changed for instance by intercalation of the bulk, or by exfoliation to reach monolayer or

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo

We study the problem of efficiently computing the derivative of the fixed-point of a parametric nondifferentiable contraction map. This problem has wide applications in machine learning, including hyperparameter optimization, meta-learning and data poisoning attacks. We analyze two popular approaches: iterative differentiation (ITD) and approximate implicit

Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki, Naoya Chiba

Predicting physical properties of materials from their crystal structures is a fundamental problem in materials science. In peripheral areas such as the prediction of molecular properties, fully connected attention networks have been shown to be successful. However, unlike these finite atom arrangements, crystal structures are infinitely repeating, periodic

Meenakshi Sharma, Sergio Caprara, Andrea Perali, Surinder P. Singh

The Berezinskii-Kosterlitz-Thouless (BKT) transition in ultra-thin NbN films is investigated in the presence of weak perpendicular magnetic fields. A jump in the phase stiffness at the BKT transition is detected up to 5 G, while the BKT features are smeared between 5 G and 50 G, disappearing altogether at 100 G, where conventional current-voltage behaviour i

Aicha Kraria, Bachir Merikhi, Djamel Benterki

In this paper, we present an interior point algorithm with a full-Newton step for solving a linearly constrained convex optimization problem, in which we propose a generalization of the work of Kheirfam and Nasrollahi \cite{kheirfam2018full}, that consists in determining the descent directions through a parametric algebraic transformation. The work concludes

Miguel Barroso Varela, Orfeu Bertolami

The presently open problem of the Hubble tension is shown to be removed in the context of a modified theory of gravity with a non-minimal coupling between curvature and matter. By evolving the cosmological parameters that match the cosmic microwave background data until their values from direct late-time measurements, we obtain an agreement between different

Nicolas Zalot, Ekaterina Sokolova-Lapa, Jakob Stierhof, Ralf Ballhausen

Context. The High-Mass X-ray Binary (HMXB) system GX 301$-$2 is a persistent source with a well-known variable cyclotron line centered at 35 keV. Recently, a second cyclotron line at 50 keV has been reported with a presumably different behavior than the 35 keV line. Aims. We investigate the presence of the newly discovered cyclotron line in the phase-average

Guiyong Zheng, Jinqi Jiang, Chen Feng, Shaojie Shen

Surface prediction and completion have been widely studied in various applications. Recently, research in surface completion has evolved from small objects to complex large-scale scenes. As a result, researchers have begun increasing the volume of data and leveraging a greater variety of data modalities including rendered RGB images, descriptive texts, depth

Viktoras Kulionis, Andreas Froemelt, Stephan Pfister

In this study, we explore a range of options and outcomes associated with using different allocation approaches to operationalise the Planetary Boundaries (PB) framework at the country, sector, and city scales. We demonstrate: (i) how to translate the PB framework into various sub-global scales (countries, cities, industries); and (ii) how to take global/loc

Yiming Ji, Yang Liu, Guanghu Xie, Boyu Ma

We propose NEDS-SLAM, a dense semantic SLAM system based on 3D Gaussian representation, that enables robust 3D semantic mapping, accurate camera tracking, and high-quality rendering in real-time. In the system, we propose a Spatially Consistent Feature Fusion model to reduce the effect of erroneous estimates from pre-trained segmentation head on semantic rec

Ahmet Bingül, Zekeriya Uysal

The reconstruction of photon conversions is importantin order to improve the reconstruction efficiency of the physics measurements involving photons. However, there are significant number of conversions in which only one of the two tracks emitted electrons is reconstructed in the detector due to very asymmetric energy sharing between the electron-positron pa

Antoine Schnepf, Karim Kassab, Jean-Yves Franceschi, Laurent Caraffa

We present a method enabling the scaling of NeRFs to learn a large number of semantically-similar scenes. We combine two techniques to improve the required training time and memory cost per scene. First, we learn a 3D-aware latent space in which we train Tri-Plane scene representations, hence reducing the resolution at which scenes are learned. Moreover, we

Santiago González-Gaitán, Claudia P. Gutiérrez, Joseph P. Anderson, Antonia Morales-Garoffolo

Narrow absorption features in nearby supernova (SN) spectra are a powerful diagnostic of the slow-moving material in the line of sight: they are extensively used to infer dust extinction from the host galaxies, and they can also serve in the detection of circumstellar material originating from the SN progenitor and present in the vicinity of the explosion. D

Takeshi Tsuji

Similarly to the theory of crystalline cohomology, we give a local description of a prismatic crystal and its cohomology in terms of a $q$-Higgs module and the associated $q$-Higgs complex on the bounded prismatic envelope of an embedding into a framed smooth algebra, when the base bounded prism is defined over the $q$-crystalline prism. We also discuss its

François Porcher, Camille Couprie, Marc Szafraniec, Jakob Verbeek

Despite the availability of large datasets for tasks like image classification and image-text alignment, labeled data for more complex recognition tasks, such as detection and segmentation, is less abundant. In particular, for instance segmentation annotations are time-consuming to produce, and the distribution of instances is often highly skewed across clas

Chamuditha Jayanga Galappaththige, Sanoojan Baliah, Malitha Gunawardhana, Muhammad Haris Khan

We approach the challenge of addressing semi-supervised domain generalization (SSDG). Specifically, our aim is to obtain a model that learns domain-generalizable features by leveraging a limited subset of labelled data alongside a substantially larger pool of unlabeled data. Existing domain generalization (DG) methods which are unable to exploit unlabeled da

Suchitra Krishnaswamy, Fabian Schule, Laura Ares, Vladyslav Dyachuk

We utilize click-counting theory for the reconstruction of photon statistics. Our approach employs an analytic pseudo-inversion method to estimate photon counts from measured click counts. A reconfigurable time-bin multiplexing, click-counting detector is set up that renders it possible to alter the photon-number resolution as needed. A detector tomography i

Haoyu Zhao, Yuliang Gu, Zhou Zhao, Bo Du

In clinical examinations and diagnoses, low-dose computed tomography (LDCT) is crucial for minimizing health risks compared with normal-dose computed tomography (NDCT). However, reducing the radiation dose compromises the signal-to-noise ratio, leading to degraded quality of CT images. To address this, we analyze LDCT denoising task based on experimental res

Xufeng Yao, Haoyang Li, Tsz Ho Chan, Wenyi Xiao

In the domain of chip design, Hardware Description Languages (HDLs) play a pivotal role. However, due to the complex syntax of HDLs and the limited availability of online resources, debugging HDL codes remains a difficult and time-intensive task, even for seasoned engineers. Consequently, there is a pressing need to develop automated HDL code debugging model

Arif Ali Khan, Davide Taibi, Muhammad Azeem Akbar

This paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this mo

Peter Švec, Štefan Balogh, Martin Homola, Ján Kľuka

Ontologies are a standard tool for creating semantic schemata in many knowledge intensive domains of human interest. They are becoming increasingly important also in the areas that have been until very recently dominated by subsymbolic knowledge representation and machine-learning (ML) based data processing. One such area is information security, and specifi

Anne Sawhney, Emmanuel Shittu, Ben Morgan, Elizabeth Sackett

Electrodes in sodium-ion batteries endure mechanical stress during production and application, which can damage these fragile coatings, causing performance inefficiencies and early failure. Binder material provides elasticity in electrode composites to resist fracture, but evaluating the effectiveness of binder is complicated by substrate dependency of these

Julia Wolleb, Florentin Bieder, Paul Friedrich, Peter Zhang

The high performance of denoising diffusion models for image generation has paved the way for their application in unsupervised medical anomaly detection. As diffusion-based methods require a lot of GPU memory and have long sampling times, we present a novel and fast unsupervised anomaly detection approach based on latent Bernoulli diffusion models. We first

Aashish Chahal, Abhishek Sharma

Over the last two decades, non-trivial magnetic textures, especially the magnetic skyrmion family, have been extensively explored out of fundamental interest and for diverse possible applications. Given the possible technological and scientific ramifications of skyrmion-texture on magnetic tunnel junctions (Sk-MTJs), in this work, we present a non-equilibriu

Wolfgang Fuhl

We propose an improvement to the landmark validity loss. Landmark detection is widely used in head pose estimation, eyelid shape extraction, as well as pupil and iris segmentation. There are numerous additional applications where landmark detection is used to estimate the shape of complex objects. One part of this process is the accurate and fine-grained det

Josh Hunter, John McDermid, Simon Burton

As the railway industry increasingly seeks to introduce autonomy and machine learning (ML), several questions arise. How can safety be assured for such systems and technologies? What is the applicability of current safety standards within this new technological landscape? What are the key metrics to classify a system as safe? Currently, safety analysis for t

Monica Nonino, Davide Torlo

We propose a novel Model Order Reduction framework that is able to handle solutions of hyperbolic problems characterized by multiple travelling discontinuities. By means of an optimization based approach, we introduce suitable calibration maps that allow us to transform the original solution manifold into a lower dimensional one. The novelty of the methodolo

Krzysztof Pachucki

A general quantum electrodynamic method for derivation of nuclear recoil corrections in hydrogenic systems, which are exact in the nuclear charge parameter $Z\,\alpha$, is introduced. The exemplary derivation is presented for the $O(m/M)$ nuclear pure recoil correction to the hyperfine splitting. The obtained result is verified by comparison to the known $(Z

Xiangyuan Wang, Kuangyi Chen, Wen Yang, Lei Yu

Keypoint detection and tracking in traditional image frames are often compromised by image quality issues such as motion blur and extreme lighting conditions. Event cameras offer potential solutions to these challenges by virtue of their high temporal resolution and high dynamic range. However, they have limited performance in practical applications due to t

Lorenzo Lamberti, Georg Rutishauser, Francesco Conti, Luca Benini

A critical challenge in deploying unmanned aerial vehicles (UAVs) for autonomous tasks is their ability to navigate in an unknown environment. This paper introduces a novel vision-depth fusion approach for autonomous navigation on nano-UAVs. We combine the visual-based PULP-Dronet convolutional neural network for semantic information extraction, i.e., servin

Kamalesh Bera, Priyanka Mohan, Arijit Saha

Our theoretical study unfolds the topological phase transitions (within bands of the Moir\'e super-lattice) in small angle twisted double bilayer graphene (tDBLG) under the influence of external gate voltage and intrinsic spin-orbit coupling (SOC) for both AB-AB and AB-BA stacking configurations. Utilizing a low-energy continuum model, we investigate the ban

Benjamin A. Burton, Finn Thompson

The Heegaard genus is a fundamental invariant of 3-manifolds. However, computing the Heegaard genus of a triangulated 3-manifold is NP-hard, and while algorithms exist, little work has been done in making such an algorithm efficient and practical for implementation. Current algorithms use almost normal surfaces, which are an extension of the algorithm-friend

Koushik Dey, Bikash Das, Pabitra Kumar Hazra, Tanima Kundu

The study investigates the influence of negative capacitance on the transfer characteristics of vdW FETs on the heterophase of CIPS ferroelectric. Notably, a less pronounced NC resulting from the spatial distribution of the ferroelectric and paraelectric phases plays crucial role in stabilizing of n-channel-conductance. This results into the emergence of a n

Ravit Helled, David J. Stevenson

New interior models of Jupiter and Saturn suggest that both planets have "fuzzy cores". These cores should be viewed as central regions that are enriched with heavy elements but are not distinct from the rest of the deep interior. These cores may contain large amounts of hydrogen and helium though small pure-heavy element cores may also exist. New measuremen

Yuxin Cao, Jinghao Li, Xi Xiao, Derui Wang

Previous work has shown that well-crafted adversarial perturbations can threaten the security of video recognition systems. Attackers can invade such models with a low query budget when the perturbations are semantic-invariant, such as StyleFool. Despite the query efficiency, the naturalness of the minutia areas still requires amelioration, since StyleFool l

Masataka Kawano

Quasiparticle excitations in material solids often experience a fictitious gauge field, which can be a potential source of intriguing transport phenomena. Here, we show that low-energy excitations in insulating antiferromagnetic skyrmion crystals on the triangular lattice are effectively described by magnons with an SU(3) gauge field. The three-sublattice st

David Burguet

For a partially hyperbolic attractor with a center bundle splitting in a dominatedway into one-dimensional subbundles we show that for Lebesgue almost every point there is anempirical measure from $x$ with a SRB component. Moreover if the center exponents are nonzero, then $x$ lies in the basin of an ergodic hyperbolic SRB measure and there are only finitely

Santiago Forero

The Cartographic Assessment of Ecological Potential (CARPO) allows users to characterize the ecological context of a group of sites at several scales (its perimeter and surrounding area) and on the basis of 4 themes: biodiversity zonings, land use (major types of environment, natural character and degree of permeability of territories), ecological connectivi

Narendra Nath Patra, Nirupam Roy

Atomic Hydrogen-21 cm transition (HI) is an excellent tracer to study and understand the properties of the atomic gas in the Galaxy. Using the Westerbork Synthesis Radio Telescope (WSRT), we observed 12 quasar sightlines to detect galactic HI in absorption. We achieve an optical depth RMS of $\sim 1-2 \times 10^{-3}$, essential to detect the Warm Neutral Med

D. Nóbrega-Siverio, I. Cabello, S. Bose, L. H. M. Rouppe van der Voort

Advancements in instrumentation have revealed a multitude of small-scale EUV events in the solar atmosphere. Our aim is to employ high-resolution magnetograms to gain a detailed understanding of the magnetic origin of such phenomena. We have used coordinated observations from SST, IRIS, and SDO to analyze an ephemeral magnetic flux emergence episode and the

Théophile Blard, Théo Ladune, Pierrick Philippe, Gordon Clare

Overfitted image codecs offer compelling compression performance and low decoder complexity, through the overfitting of a lightweight decoder for each image. Such codecs include Cool-chic, which presents image coding performance on par with VVC while requiring around 2000 multiplications per decoded pixel. This paper proposes to decrease Cool-chic encoding a

Xinyu Sun, Lizhao Liu, Hongyan Zhi, Ronghe Qiu

We study zero-shot instance navigation, in which the agent navigates to a specific object without using object annotations for training. Previous object navigation approaches apply the image-goal navigation (ImageNav) task (go to the location of an image) for pretraining, and transfer the agent to achieve object goals using a vision-language model. However,

Kévin Polisano, Basile Dubois-Bonnaire, Sylvain Meignen

We present a new approach leveraging the Sliding Frank--Wolfe algorithm to address the challenge of line recovery in degraded images. Building upon advances in conditional gradient methods for sparse inverse problems with differentiable measurement models, we propose two distinct models tailored for line detection tasks within the realm of blurred line decon

Stephan Rhode, Fabian Jarmolowitz, Felix Berkel

In this paper, we follow the physics guided modeling approach and integrate a neural differential equation network into the physical structure of a vehicle single track model. By relying on the kinematic relations of the single track ordinary differential equations (ODE), a small neural network and few training samples are sufficient to substantially improve

Sajid Ali, Dibyendu Bala, Anthony Francis, Greg Jackson

Thermal photons produced in heavy-ion collision experiments are an important observable for understanding quark-gluon plasma (QGP). The thermal photon rate from the QGP at a given temperature can be calculated from the spectral function of the vector current correlator. Extraction of the spectral function from the lattice correlator is known to be an ill-con

Timothée Ly, Julien Ferry, Marie-José Huguet, Sébastien Gambs

Differentially-private (DP) mechanisms can be embedded into the design of a machine learning algorithm to protect the resulting model against privacy leakage. However, this often comes with a significant loss of accuracy due to the noise added to enforce DP. In this paper, we aim at improving this trade-off for a popular class of machine learning algorithms

Ibrahim Almakky, Santosh Sanjeev, Anees Ur Rehman Hashmi, Mohammad Areeb Qazi

Transfer learning has become a powerful tool to initialize deep learning models to achieve faster convergence and higher performance. This is especially useful in the medical imaging analysis domain, where data scarcity limits possible performance gains for deep learning models. Some advancements have been made in boosting the transfer learning performance g

Vincenzo Roberto Arezzo, Davide Rossini, Giulia Piccitto

We study the performances of an imperfect quantum many-body Otto engine based on free-fermion systems. Starting from the thermodynamic definitions of heat and work along ideal isothermal, adiabatic, and isochoric transformations, we generalize these expressions in the case when the hypotheses of ideality are relaxed (i.e., nonperfect thermalization with the

Océane Koska, Marc Baboulin, Arnaud Gazda

The Pauli matrices are 2-by-2 matrices that are very useful in quantum computing. They can be used as elementary gates in quantum circuits but also to decompose any matrix of $\mathbb{C}^{2^n \times 2^n}$ as a linear combination of tensor products of the Pauli matrices. However, the computational cost of this decomposition is potentially very expensive since

Theodor Westny, Björn Olofsson, Erik Frisk

The ability to predict the future trajectories of traffic participants is crucial for the safe and efficient operation of autonomous vehicles. In this paper, a diffusion-based generative model for multi-agent trajectory prediction is proposed. The model is capable of capturing the complex interactions between traffic participants and the environment, accurat

Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini, Ivan Donadello

Counterfactual explanations suggest what should be different in the input instance to change the outcome of an AI system. When dealing with counterfactual explanations in the field of Predictive Process Monitoring, however, control flow relationships among events have to be carefully considered. A counterfactual, indeed, should not violate control flow relat

Foivos Paraperas Papantoniou, Alexandros Lattas, Stylianos Moschoglou, Jiankang Deng

This paper presents Arc2Face, an identity-conditioned face foundation model, which, given the ArcFace embedding of a person, can generate diverse photo-realistic images with an unparalleled degree of face similarity than existing models. Despite previous attempts to decode face recognition features into detailed images, we find that common high-resolution da

Pierre Laclau, Stéphane Bonnet, Bertrand Ducourthial, Xiaoting Li

With the increasing demand for dynamic behaviors in automotive use cases, Software Defined Vehicles (SDVs) have emerged as a promising solution by bringing dynamic onboard service management capabilities. While users may request a wide range of services during vehicle operation, background tasks such as cooperative Vehicle-to-Everything (V2X) services can ac

Swapnil Nitin Shah

Gauge-gravity duality provides a robust mathematical framework for studying the behavior of strongly coupled non-abelian plasmas both near and far away from thermodynamic equilibrium. In particular, their near-equilibrium transport coefficients such as viscosity, conductivity, diffusion constants, etc. can be determined from poles of the retarded Green's fun

Zewen Xu, Yijia He, Hao Wei, Bo Xu

Line features are valid complements for point features in man-made environments. 3D-2D constraints provided by line features have been widely used in Visual Odometry (VO) and Structure-from-Motion (SfM) systems. However, how to accurately solve three-view relative motion only with 2D observations of points and lines in real time has not been fully explored.

Ravshan Ashurov, Oqila Muhiddinova

The work considers a system of fractional order partial differential equations. The existence and uniqueness theorems for the classical solution of initial-boundary value problems are proved in two cases: 1) the right-hand side of the equation does not depend on the solution of the problem and 2) it depends on the solution, but at the same time satisfies the

Nadav Merlis, Dorian Baudry, Vianney Perchet

In reinforcement learning (RL), agents sequentially interact with changing environments while aiming to maximize the obtained rewards. Usually, rewards are observed only after acting, and so the goal is to maximize the expected cumulative reward. Yet, in many practical settings, reward information is observed in advance -- prices are observed before performi

M. Saberi, A. Vogel

In this work, we propose an adaptive geometric multigrid method for the solution of large-scale finite cell flow problems. The finite cell method seeks to circumvent the need for a boundary-conforming mesh through the embedding of the physical domain in a regular background mesh. As a result of the intersection between the physical domain and the background

W. Q. Su, J. L. Han, Z. L. Yang, P. F. Wang

Double neutron star (DNS) systems offer excellent opportunities to test gravity theories. We report the timing results of PSR J1901+0658, the first pulsar discovered in the FAST Galactic Plane Pulsar Snapshot (GPPS) Survey. Based on timing observations by FAST over 5 yr, we obtain the phase-coherent timing solutions and derive the precise measurements of its

Tom Wehrbein, Bodo Rosenhahn, Iain Matthews, Carsten Stoll

Recently, regression-based methods have dominated the field of 3D human pose and shape estimation. Despite their promising results, a common issue is the misalignment between predictions and image observations, often caused by minor joint rotation errors that accumulate along the kinematic chain. To address this issue, we propose to construct dense correspon

Luis A. Guardiola, Behzad Hezarkhani, Ana Meca

International trade can be a profitable business for agri-food communities. However, access to international markets can be costly and thus unattainable for small and medium sized enterprises (SMEs). This problem is exacerbated under trade policies which require minimum quantity commitments (MQCs) on export volumes, e.g., licensing tariff rate quota (TRQ) me

Isabell Stucke, Deborah Morgenstern, Georg J. Mayr, Thorsten Simon

This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat, especially to wind turbines, as the long-duration current of UL can cause significant damage. Current risk assessment methods overlook the impact of meteorological conditions, po

M. Saberi, L. Zhao, A. Vogel

The weak imposition of essential boundary conditions is an integral aspect of unfitted finite element methods, where the physical boundary does not in general coincide with the computational domain. In this regard, the symmetric Nitsche's method is a powerful technique that preserves the symmetry and variational consistency of the unmodified weak formulation

Kun Ding, Xiaohui Li, Qiang Yu, Ying Wang

Context Optimization (CoOp) has emerged as a simple yet effective technique for adapting CLIP-like vision-language models to downstream image recognition tasks. Nevertheless, learning compact context with satisfactory base-to-new, domain and cross-task generalization ability while adapting to new tasks is still a challenge. To tackle such a challenge, we pro

Trambak Bhattacharyya, Md Hasanujjaman

We investigate the propagation of nonlinear energy density waves in a nonextensive quark-gluon plasma under the influence of a magnetic field using the reductive perturbation technique. For a nonextensive MIT bag equation of state, we obtain the governing equation for the first order perturbation of the energy density. We observe that an increase in the stre

Bernabé Cedrés, Simon B. De Daniloff, Ángel Bongiovanni, Miguel Sánchez-Portal

In this paper, we revisit the data for the galaxy cluster ZwCl 0024.0+1652 provided by the GLACE survey and study the mass--metallicity function and its relationship with the environment. Here we describe an alternative way to reduce the data from OSIRIS tunable filters. This method gives us better uncertainties in the fluxes of the emission lines and the de

V. Yu. Denisov

The evaluated nuclide yields, fragment mass and charge distributions, and averaged total kinetic energy of fission fragments for the neutron-induced fission of 30 actinide nuclei are well described in the new model, which considers the fissioning scission system consisting of two heavy fragments and an alpha-particle between them. The alpha-particle has its

Yang Yang, Wen Wang, Liang Peng, Chaotian Song

Customization generation techniques have significantly advanced the synthesis of specific concepts across varied contexts. Multi-concept customization emerges as the challenging task within this domain. Existing approaches often rely on training a fusion matrix of multiple Low-Rank Adaptations (LoRAs) to merge various concepts into a single image. However, w

Zhizhen Zhou, Yejing Huo, Guoheng Huang, An Zeng

The study of music-generated dance is a novel and challenging Image generation task. It aims to input a piece of music and seed motions, then generate natural dance movements for the subsequent music. Transformer-based methods face challenges in time series prediction tasks related to human movements and music due to their struggle in capturing the nonlinear

Xiaohan Lei, Min Wang, Wengang Zhou, Houqiang Li

In embodied vision, Instance ImageGoal Navigation (IIN) requires an agent to locate a specific object depicted in a goal image within an unexplored environment. The primary challenge of IIN arises from the need to recognize the target object across varying viewpoints while ignoring potential distractors. Existing map-based navigation methods typically use Bi

Xiang Li, Chaofan Fu, Zhongying Zhao, Guanjie Zheng

Effective recommender systems play a crucial role in accurately capturing user and item attributes that mirror individual preferences. Some existing recommendation techniques have started to shift their focus towards modeling various types of interactive relations between users and items in real-world recommendation scenarios, such as clicks, marking favorit

Arvid Fälldin, Tommy Löfstedt, Tobias Semberg, Erik Wallin

Multi-object grasping is a challenging task. It is important for energy and cost-efficient operation of industrial crane manipulators, such as those used to collect tree logs from the forest floor and on forest machines. In this work, we used synthetic data from physics simulations to explore how data-driven modeling can be used to infer multi-object grasp p

Michele Azzone, Emilio Barucci, Davide Stocco

We investigate the portfolio frontier and risk premia in equilibrium when institutional investors aim to minimize the tracking error variance under an ESG score mandate. If a negative ESG premium is priced in the market, this mandate can reduce portfolio inefficiency when the return over-performance target is limited. In equilibrium, with asset managers endo

Haoyun Xu, Runzhe Zhan, Derek F. Wong, Lidia S. Chao

Large Language Models (LLMs) are composed of neurons that exhibit various behaviors and roles, which become increasingly diversified as models scale. Recent studies have revealed that not all neurons are active across different datasets, and this sparsity correlates positively with the task-specific ability, leading to advancements in model pruning and train

Marc Rovirola, Héctor Briongos-Merino, Bruno Juliá-Díaz, Montserrat Guilleumas

We consider a ring-shaped triple-well potential with few polar bosons with in-plane dipole orientation. By diagonalizing the extended Bose-Hubbard Hamiltonian, we investigate the ground state properties of the system as we rotate the dipole angle and vary the on-site and dipole-dipole interaction strengths. We find that the anisotropic character of the dipol

Chrislene Lionel, Shubham Das, Diparnab Banik, S. Koley

Composite oxides have been indeed proved to be valuable materials in optoelectronic applications. The combination of indium oxide and gallium oxide and other materials can lead to enhanced optical and electronic properties, making them suitable for a variety of optoelectronic devices. Meticulous analysis of the various optical properties helped to draw concl

Takahiko Makiuchi, Naoki Kanazawa, Eiji Saitoh

Spin torque nano-oscillators realized by magnetization dynamics trapped in a current-induced potential are reported. We fabricated Ni$_{81}$Fe$_{19}$/Pt nanostructures and measured current-induced microwave emission from the structures. The result shows an increase in the magnitude and spectral narrowing of the microwave emission. We demonstrate that the cur

Mauro Tellaroli, Matteo Luperto, Michele Antonazzi, Nicola Basilico

Multi-robot rendezvous and exploration are fundamental challenges in the domain of mobile robotic systems. This paper addresses multi-robot rendezvous within an initially unknown environment where communication is only possible after the rendezvous. Traditionally, exploration has been focused on rapidly mapping the environment, often leading to suboptimal re

Jayarshi Bhattacharya, Sunandan Gangopadhyay, Gautam Gangopadhyay

This paper investigates the dynamics of current and quantum transport factor in a bosonic system consisting of a central system interacting with two reservoirs at different temperatures. We derive a master equation describing the time evolution of the density matrix of the system, accounting for the interactions and energy transfer between the components. We

Vijay John, Yasutomo Kawanishi

For training a video-based action recognition model that accepts multi-view video, annotating frame-level labels is tedious and difficult. However, it is relatively easy to annotate sequence-level labels. This kind of coarse annotations are called as weak labels. However, training a multi-view video-based action recognition model with weak labels for frame-l

W. J. Pearson, D. J. D. Santos, T. Goto, T. -C. Huang

Aims. In this work, we intend to examine how environment influences the merger fraction, from the low density field environment to higher density groups and clusters. We also aim to study how the properties of a group or cluster, as well as the position of a galaxy in the group or cluster, influences the merger fraction. Methods. We identified galaxy groups

S. Horikawa, S. Yang, T. Tanaka, T. Aoki

We present characterization and storage methods for a high-finesse nanofiber Fabry-P\'{e}rot resonator. Reflection spectroscopy from both ends of the resonator allows for evaluation of the mirror transmittances and optical loss inside the resonator. To maintain the quality of the nanofiber resonator after the fabrication, we have developed a portable storage

Datao Tang, Xiangyong Cao, Xingsong Hou, Zhongyuan Jiang

The emergence of generative models has revolutionized the field of remote sensing (RS) image generation. Despite generating high-quality images, existing methods are limited in relying mainly on text control conditions, and thus do not always generate images accurately and stably. In this paper, we propose CRS-Diff, a new RS generative framework specifically

Langlang Xiong, Xunya Jiang, Guangwei Hu

The exploration of topology in natural materials and metamaterials has garnered significant attention. Notably, the one-dimensional (1D) and two-dimensional (2D) Su-Schrieffer-Heeger (SSH) model, assessed through tight-binding approximations, has been extensively investigated in both quantum and classical systems, encompassing general and higher-order topolo

Atsushi Horikoshi

Symplectic integrators are widely implemented numerical integrators for Hamiltonian mechanics, which preserve the Hamiltonian structure (symplecticity) of the system. Although the symplectic integrator does not conserve the energy of the system, it is well known that there exists a conserving modified Hamiltonian, called the shadow Hamiltonian. For the Nambu

Min-Li Zeng, Martin Stoll

In this paper, we focus on efficient methods to solve discretized linear systems obtained from eddy current optimal control problems in an all-at-once approach. We construct a new low-rank matrix equation method based on a special splitting of the coefficient matrix and the Krylov-plus-inverted-Krylov (KPIK) algorithm. Firstly, we rewrite the resulting discr

Eduard Mychelkin, Maxim Makukov, Gulnara Suliyeva, Nosratollah Jafari

The triumph of general relativity under the banner "gravity is geometry" began with confirming the crucial effects within the Solar system and proceeded recently to the strong-field shadow effect for the compact object in the center of the Milky Way. Here, we examine some of those phenomena for the Einstein-scalar equations in the antiscalar regime to reveal