March 2024 arXiv papers — page 11

Jiani Fan, Lwin Khin Shar, Jiale Guo, Wenzhuo Yang

This paper aims to provide differentiated security protection for infotainment data communication in Internet-of-Vehicle (IoV) networks. The IoV is a network of vehicles that uses various sensors, software, built-in hardware, and communication technologies to enable information exchange between pedestrians, cars, and urban infrastructure. Negligence on the s

Philip Freese, Sebastian Götschel, Thibaut Lunet, Daniel Ruprecht

We investigate the parallel performance of Parallel Spectral Deferred corrections, a numerical approach that provides small-scale parallelism for the numerical solution of initial value problems. The scheme is applied to the shallow-water equation and uses an implicit-explicit splitting that, in order to be efficient, integrates fast modes implicitly and slo

Megan Su, Yuwei Bao

Interactive Artificial Intelligent(AI) assistant systems are designed to offer timely guidance to help human users to complete a variety tasks. One of the remaining challenges is to understand user's mental states during the task for more personalized guidance. In this work, we analyze users' mental states during task executions and investigate the capabilit

Laurent Doyen, Thomas Soullard

We consider two-player games with imperfect information and the synthesis of a randomized strategy for one player that ensures the objective is satisfied almost-surely (i.e., with probability 1), regardless of the strategy of the other player. Imperfect information is modeled by an indistinguishability relation describing the pairs of histories that the firs

Michael Färber

jq is a widely used tool that provides a programming language to manipulate JSON data. However, the jq language is currently only specified by its implementation, making it difficult to reason about its behaviour. To this end, we provide a formal syntax and denotational semantics for a large subset of the jq language. Our most significant contribution is to

Jianchao Zhang, Jun Suzuki

Quantum parameter estimation holds significant promise for achieving high precision through the utilization of the most informative measurements. While various lower bounds have been developed to assess the best accuracy for estimates, they are not tight, nor provide a construction of the optimal measurement in general. Thus, determining the explicit forms o

Dongzhe Zhang, Jianfeng Chen, Jisheng Bai, Mou Wang

Deep learning-based sound event localization and classification is an emerging research area within wireless acoustic sensor networks. However, current methods for sound event localization and classification typically rely on a single microphone array, making them susceptible to signal attenuation and environmental noise, which limits their monitoring range.

Sounak Sinha Biswas, Ghanasyam Remesh, Venu Gopal Achanta, Ayan Banerjee

Reflectionless potentials following the prescription of Kay and Moses allow for total transmission of incoming waves of any kinetic energy. The optical analogue of such potentials occur as dielectric stratified media that can offer null reflectivity and near total transmission over a large range of incidence angles and wavelengths. In a previous work (S. Dut

Ansei Yonezawa, Heisei Yonezawa, Itsuro Kajiwara

Inverse kinematics is an important and challenging problem in the operation of industrial manipulators. This study proposes a simple inverse kinematics calculation scheme for an industrial serial manipulator. The proposed technique can calculate appropriate values of the joint variables to realize the desired end-effector position and orientation while consi

Kaito Taguchi, Yujie Gu, Kouichi Sakurai

In recent years, there have been significant advancements in the development of Large Language Models (LLMs). While their practical applications are now widespread, their potential for misuse, such as generating fake news and committing plagiarism, has posed significant concerns. To address this issue, detectors have been developed to evaluate whether a give

Beomyoung Kim, Joonsang Yu, Sung Ju Hwang

Panoptic segmentation, combining semantic and instance segmentation, stands as a cutting-edge computer vision task. Despite recent progress with deep learning models, the dynamic nature of real-world applications necessitates continual learning, where models adapt to new classes (plasticity) over time without forgetting old ones (catastrophic forgetting). Cu

Razmik A. Hovhannisyan, Sergey Yu. Grebenchuk, Andrey G. Shishkin, Artem Grebenko

The presence of quantum vortices determines the electromagnetic response of superconducting materials and devices. Controlling the vortex motion, their pinning on intrinsic and artificial defects is therefore essential for superconducting electronics. Here we take advantage of the attractive force between a magnetic cantilever of the Magnetic Force Microscop

José Alberto Benítez-Andrades, Camino Prada-García, Rubén García-Fernández, María D. Ballesteros-Pomar

Objectives: Metabolic Bariatric Surgery (MBS) is a critical intervention for patients living with obesity and related health issues. Accurate classification and prediction of patient outcomes are vital for optimizing treatment strategies. This study presents a novel machine learning approach to classify patients in the context of metabolic bariatric surgery,

Guilherme D. da Fonseca, Yan Gerard

The 2024 edition of the CG:SHOP Challenge focused on the knapsack polygonal packing problem. Each instance consists of a convex polygon known as the container and a multiset of items, where each item is a simple polygon with an associated integer value. A feasible packing solution places a selection of the items inside the container without overlapping and u

Ting-Ting Zhu, Yuan-Hai Shao, Chun-Na Li, Tian Liu

Learning using statistical invariants (LUSI) is a new learning paradigm, which adopts weak convergence mechanism, and can be applied to a wider range of classification problems. However, the computation cost of invariant matrices in LUSI is high for large-scale datasets during training. To settle this issue, this paper introduces a granularity statistical in

Sameh M. Altanany, I. Zajcewa, T. Zajarniuk, A. Szewczyk

The evolution of the vortex glass (VG) phase transition and vortex creep with decreasing film thickness is studied in ultrathin, polycrystalline niobium films, with thickness in the range 7.4 nm to 44 nm, using current-voltage characteristics measurements in perpendicular magnetic field. Standard methods, including scaling laws, allow to identify VG transiti

Ayush Rastogi, Harsh Rastogi, Yash Rastogi, Divyansh Dubey

In this paper, we present a multidimensional, highly effective method for aggregating data for wireless sensor networks while maintaining privacy. The suggested system is resistant to data loss and secure against both active and passive privacy compromising attacks, such as the coalition attack from a rogue base station and kidnapped sensor nodes. With regar

F. Antola, A. Braggio, G. De Simoni, F. Giazotto

Efficient heat management at cryogenic temperatures is crucial for superconducting quantum technologies. This study demonstrates the controlled manipulation of the heat flow and heat rectification through an asymmetric superconducting tunnel junction. The system exhibits a non-reciprocal behavior, developing a thermoelectric regime exclusively when the elect

Qingqian Kang, Zekun Zhao, Teng Zhao, Cunjin Liu

Utilizing nonlinear elements, SU(1,1) interferometers demonstrate superior phase sensitivity compared to passive interferometers. However, the precision is significantly impacted by photon losses, particularly internal losses. We propose a theoretical scheme to improve the precision of phase measurement using homodyne detection by implementing number-conserv

Hiroto Yanagisawa, Masami Ouchi, Kimihiko Nakajima, Hidenobu Yajima

We investigate the physical origins of the Balmer decrement anomalies in GS-NDG-9422 (Cameron et al. 2023) and RXCJ2248-ID (Topping et al. 2024) galaxies at $z\sim 6$ whose $\mathrm{H}\alpha/\mathrm{H}\beta$ values are significantly smaller than $2.7$, the latter of which also shows anomalous $\mathrm{H}\gamma/\mathrm{H}\beta$ and $\mathrm{H}\delta/\mathrm{H

Rejin John Varghese, Matteo Pizzi, Aritra Kundu, Agnese Grison

The adoption of high-density electrode systems for human-machine interfaces in real-life applications has been impeded by practical and technical challenges, including noise interference, motion artifacts and the lack of compact electrode interfaces. To overcome some of these challenges, we introduce a wearable and stretchable electromyography (EMG) array, a

Pranjal Paul, Anant Garg, Tushar Choudhary, Arun Kumar Singh

Existing Vision-Language models (VLMs) estimate either long-term trajectory waypoints or a set of control actions as a reactive solution for closed-loop planning based on their rich scene comprehension. However, these estimations are coarse and are subjective to their "world understanding" which may generate sub-optimal decisions due to perception errors. In

G. V. Afonin, J. C. Qiao, A. S. Makarov, R. A. Konchakov

We performed calorimetric measurements on 30 bulk metallic glasses differing with their mixing entropies DSmix. On this basis, the excess entropies DS and excess enthalpies DH of glasses with respect to their maternal crystalline states are calculated. It is found that the excess entropy DS on the average decreases with increasing mixing entropy DSmix. This

Jesse Atuhurra, Iqra Ali, Tatsuya Hiraoka, Hidetaka Kamigaito

Large language models (LLMs) have increased interest in vision language models (VLMs), which process image-text pairs as input. Studies investigating the visual understanding ability of VLMs have been proposed, but such studies are still preliminary because existing datasets do not permit a comprehensive evaluation of the fine-grained visual linguistic abili

David Amblard, Xavier Blase, Ivan Duchemin

Continuum or discrete polarizable models for the study of optoelectronic processes in embedded subsystems rely mostly on the restriction of the surrounding electronic dielectric response to its low frequency limit. Such a description hinges on the assumption that the electrons in the surrounding medium react instantaneously to any excitation in the central s

Long Hu, Guillaume Olive

In this article we study the internal controllability of 1D linear hyperbolic balance laws when the number of controls is equal to the number of state variables. The controls are supported in space in an arbitrary open subset. Our main result is a complete characterization of the minimal control time for the exact controllability property.

David Vázquez-Lema, Eduardo Mosqueira-Rey, Elena Hernández-Pereira, Carlos Fernández-Lozano

This paper explores the application of Human-in-the-Loop (HITL) strategies in training machine learning models in the medical domain. In this case a doctor-in-the-loop approach is proposed to leverage human expertise in dealing with large and complex data. Specifically, the paper deals with the integration of genomic data and Whole Slide Imaging (WSI) analys

Alessandro Ilic Mezza, Riccardo Giampiccolo, Enzo De Sena, Alberto Bernardini

Over the past few decades, extensive research has been devoted to the design of artificial reverberation algorithms aimed at emulating the room acoustics of physical environments. Despite significant advancements, automatic parameter tuning of delay-network models remains an open challenge. We introduce a novel method for finding the parameters of a Feedback

Douglas Lind, Klaus Schmidt

Let $f$, $p$, and $q$ be Laurent polynomials with integer coefficients in one or several variables, and suppose that $f$ divides $p+q$. We establish sufficient conditions to guarantee that $f$ individually divides $p$ and $q$. These conditions involve a bound on coefficients, a separation between the supports of $p$ and $q$, and, surprisingly, a requirement

Miho Tanaka, Masahiro Sato

We theoretically study the inverse Faraday effect (IFE), i.e., photo-induced magnetization, in two-dimensional Rashba spin-orbit coupled electron systems irradiated by a circularly polarized light. The quantum master (Gorini-Kossakowski-Sudarshan-Lindblad) equation enables us to accurately compute the laser driven dynamics, taking inevitable dissipation effe

Jinyeong Park, Jaegyoon Ahn, Jonghwan Choi, Jibum Kim

Optimizing techniques for discovering molecular structures with desired properties is crucial in artificial intelligence(AI)-based drug discovery. Combining deep generative models with reinforcement learning has emerged as an effective strategy for generating molecules with specific properties. Despite its potential, this approach is ineffective in exploring

Jolanta Brodzicka

The discovery of CP violation in charm sector in 2019 was a milestone in searches performed over last decades. The $\Delta A_{CP}$ measured by LHCb is at the upper end of the Standard Model predictions. This triggers many interpretations involving New Physics origins, and calls for more experimental input to clarify the picture. Recent LHCb measurements of C

Wei Yuan, Chaoqun Yang, Liang Qu, Guanhua Ye

Federated Recommender Systems (FedRecs) have garnered increasing attention recently, thanks to their privacy-preserving benefits. However, the decentralized and open characteristics of current FedRecs present two dilemmas. First, the performance of FedRecs is compromised due to highly sparse on-device data for each client. Second, the system's robustness is

Hu Gao, Depeng Dang

Image deblurring aims to restore a high-quality image from its corresponding blurred. The emergence of CNNs and Transformers has enabled significant progress. However, these methods often face the dilemma between eliminating long-range degradation perturbations and maintaining computational efficiency. While the selective state space model (SSM) shows promis

Barbara Toniella Corradini, Mustafa Shukor, Paul Couairon, Guillaume Couairon

Foundation models have exhibited unprecedented capabilities in tackling many domains and tasks. Models such as CLIP are currently widely used to bridge cross-modal representations, and text-to-image diffusion models are arguably the leading models in terms of realistic image generation. Image generative models are trained on massive datasets that provide the

Emrah Öztürk, Kevin Kaspar, Timm Faulwasser, Karl Worthmann

The increasing penetration of volatile renewables combined with increasing demands poses a challenge to modern power grids. Furthermore, distributed energy resources and flexible devices (electric vehicles, PV generation, ...) are becoming more widespread, making their aggregate usage for ancillary services interesting. However, accurately quantifying the ag

Helena Bonaldi, Yi-Ling Chung, Gavin Abercrombie, Marco Guerini

In recent years, counterspeech has emerged as one of the most promising strategies to fight online hate. These non-escalatory responses tackle online abuse while preserving the freedom of speech of the users, and can have a tangible impact in reducing online and offline violence. Recently, there has been growing interest from the Natural Language Processing

Yan Liu, Hong-Da Lyu, Chuan-Yi Wang

We exploit holographic duality to study the system of a one-dimensional interface contacting two semi-infinite two-dimensional CFTs. Central to our investigation is the introduction of a dynamical scalar field located on the bulk interface brane which breaks the scaling symmetry of the dual interface field theory, along with its consequential backreaction on

Benjamin Townsend, Madison May, Katherine Mackowiak, Christopher Wells

We introduce RealKIE, a benchmark of five challenging datasets aimed at advancing key information extraction methods, with an emphasis on enterprise applications. The datasets include a diverse range of documents including SEC S1 Filings, US Non-disclosure Agreements, UK Charity Reports, FCC Invoices, and Resource Contracts. Each presents unique challenges:

Harish P. Jain, Axel Voigt, Luiza Angheluta

Within the context of epithelial monolayers, T1 transitions, also known as cell-intercalations, are topological rearrangements of cells that contribute to fluidity of the epithelial monolayers. We use a multi-phase field model to show that the ensemble-averaged flow profile of a T1 transition exhibits a saddle point structure, where large velocities are loca

A. Yung

It has been shown that non-Abelian solitonic vortex string supported in four-dimensional (4D) N=2 supersymmetric QCD (SQCD) with the U(2) gauge group and $N_f=4$ quark flavors becomes a critical superstring. This string propagates in the ten-dimensional space formed by a product of the flat 4D space and an internal space given by a Calabi-Yau noncompact thre

Miles Mountney, Zixu Wang, Florian Trost, Hannes Lindenblatt

We formulate a general hybrid quantum-classical technique to describe the interaction of diatomic molecules with XUV pulses. We demonstrate the accuracy of our model in the context of the interaction of the O$_2$ molecule with an XUV pulse with photon energy ranging from 20 eV to 42 eV. We account for the electronic structure and electron ionization quantum

Hanzhong Zhang, Jibin Yin, Haoyang Wang, Ziwei Xiang

Large Language Models (LLMs) still face challenges in tasks requiring understanding implicit instructions and applying common-sense knowledge. In such scenarios, LLMs may require multiple attempts to achieve human-level performance, potentially leading to inaccurate responses or inferences in practical environments, affecting their long-term consistency and

Catalin-Mihai Halati, Ameneh Sheikhan, Giovanna Morigi, Corinna Kollath

We analyze the relaxation dynamics in an open system, composed by a quantum gas of bosons in a lattice interacting via both contact and global interactions. We report the onset of periodic oscillations of the atomic coherences exhibiting hallmarks of synchronization after a quantum quench. The dynamical behavior exhibits the many-body collapse and revival of

Salvatore Bufi, Alberto Carlo Maria Mancino, Antonio Ferrara, Daniele Malitesta

The recent integration of Graph Neural Networks (GNNs) into recommendation has led to a novel family of Collaborative Filtering (CF) approaches, namely Graph Collaborative Filtering (GCF). Following the same GNNs wave, recommender systems exploiting Knowledge Graphs (KGs) have also been successfully empowered by the GCF rationale to combine the representatio

Tristan Benoist, Laurent Bruneau, Clément Pellegrini

The evolution of a quantum system undergoing repeated indirect measurements naturally leads to a Markov chain on the set of states which is called a quantum trajectory. In this paper we consider a specific model of such a quantum trajectory associated to the one-atom maser model. It describes the evolution of one mode of the quantized electromagnetic field i

Svyatoslav Trusov, Pauline Zarrouk, Shaun Cole

We present a Neural Network based emulator for the galaxy redshift-space power spectrum that enables several orders of magnitude acceleration in the galaxy clustering parameter inference, while preserving 3$\sigma$ accuracy better than 0.5\% up to $k_{\mathrm{max}}$=0.25$h^{-1}Mpc$ within $\Lambda$CDM and around 0.5\% $w_0$-$w_a$CDM. Our surrogate model only

Qi Bi, Shaodi You, Theo Gevers

Images from outdoor scenes may be taken under various weather conditions. It is well studied that weather impacts the performance of computer vision algorithms and needs to be handled properly. However, existing algorithms model weather condition as a discrete status and estimate it using multi-label classification. The fact is that, physically, specifically

Longhai Zhao, Yunchuan Yang, Qi Xiong, He Wang

Channel charting, an unsupervised learning method that learns a low-dimensional representation from channel information to preserve geometrical property of physical space of user equipments (UEs), has drawn many attentions from both academic and industrial communities, because it can facilitate many downstream tasks, such as indoor localization, UE handover,

Jon Fagerström, Sebastian J. Schlecht, Vesa Välimäki

Previous research on late-reverberation modeling has mainly focused on exponentially decaying room impulse responses, whereas methods for accurately modeling non-exponential reverberation remain challenging. This paper extends the previously proposed basic dark-velvet-noise reverberation algorithm and proposes a parametrization scheme for modeling late rever

Luca Deck, Jan-Laurin Müller, Conradin Braun, Domenique Zipperling

The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years. However, from a legal perspective, particularly from the perspective of European Union law, many open questions remain. Whereas algorithmic fairness aims to mitigate structural inequ

Fahim Faisal, Antonios Anastasopoulos

The capacity and effectiveness of pre-trained multilingual models (MLMs) for zero-shot cross-lingual transfer is well established. However, phenomena of positive or negative transfer, and the effect of language choice still need to be fully understood, especially in the complex setting of massively multilingual LMs. We propose an \textit{efficient} method to

Henrik Viitasaari, Oskari Färdig, Joona H. Siljander, A. Petrus Väisänen

The Arago spot is an intensity maximum at the center of a shadow created by constructive interference of diffracted waves around a spherical object. While the study of diffraction patterns usually concerns visible light, de Broglie's wave nature of matter makes diffraction theory applicable for particles, such as neutrinos, as well. During a solar eclipse, s

Giovanni Bellitto, Federica Proietto Salanitri, Matteo Pennisi, Matteo Boschini

We present SAM, a biologically-plausible selective attention-driven modulation approach to enhance classification models in a continual learning setting. Inspired by neurophysiological evidence that the primary visual cortex does not contribute to object manifold untangling for categorization and that primordial attention biases are still embedded in the mod

Peize Liu, Chen Feng, Yang Xu, Yan Ning

Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, which limits researchers from utilizing aeri

Kanij Fatema, Fazle Dawood Haider, Nirzona Ferdousi Turpa, Tanveer Azmal

The International Phonetic Alphabet (IPA) serves to systematize phonemes in language, enabling precise textual representation of pronunciation. In Bengali phonology and phonetics, ongoing scholarly deliberations persist concerning the IPA standard and core Bengali phonemes. This work examines prior research, identifies current and potential issues, and sugge

Yun-Zhi Du, Huai-Fan Li, Yu-Bo Ma, Qiang Gu

Since the spontaneously broken of the Lorentz symmetry in the gravity theory with the non-minimally coupling between the Kalb-Ramond (KR) field (that acquires a nonzero vacuum expectation value) and the Einstein gravity, there exists the exactly static and spherically symmetric black holes solutions related with the Lorentz violating parameter. Based on this

Sonia Mazzucchi, Fabio Nicola, S. Ivan Trapasso

The full characterization of the class of Fresnel integrable functions is an open problem in functional analysis, with significant applications to mathematical physics (Feynman path integrals) and the analysis of the Schr\"odinger equation. In finite dimension, we prove the Fresnel integrability of functions in the Sj\"ostrand class $M^{\infty,1}$ - a family

Ulrich Pennig, Taro Sogabe

KK-theory is a bivariant and homotopy-invariant functor on $C^*$-algebras that combines K-theory and K-homology. KK-groups form the morphisms in a triangulated category. Spanier-Whitehead K-Duality intertwines the homological with the cohomological side of KK-theory. Any extension of a unital $C^*$-algebra by the compacts has two natural exact triangles asso

Yuiko Sakuma, Masakazu Yoshimura, Junji Otsuka, Atsushi Irie

Compression of large and performant vision foundation models (VFMs) into arbitrary bit-wise operations (BitOPs) allows their deployment on various hardware. We propose to fine-tune a VFM to a mixed-precision quantized supernet. The supernet-based neural architecture search (NAS) can be adopted for this purpose, which trains a supernet, and then subnets withi

Zhongrui Yu, Haoran Wang, Jinze Yang, Hanzhang Wang

Novel View Synthesis (NVS) for street scenes play a critical role in the autonomous driving simulation. The current mainstream technique to achieve it is neural rendering, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). Although thrilling progress has been made, when handling street scenes, current methods struggle to maintain renderi

Xue Jiang, Feng Liu, Zhen Fang, Hong Chen

Out-of-distribution (OOD) detection aims at identifying samples from unknown classes, playing a crucial role in trustworthy models against errors on unexpected inputs. Extensive research has been dedicated to exploring OOD detection in the vision modality. Vision-language models (VLMs) can leverage both textual and visual information for various multi-modal

Rémi Barritault

Let G be a Roelcke-precompact non-archimedean Polish group, B(G) the algebra of matrix coefficients of G arising from its continuous unitary representations. The Gel'fand spectrum H(G) of the norm closure of B(G) is known as the Hilbert compactification of G. Let A be the dense subalgebra of B(G) generated by indicator maps of open cosets in G. We prove that

Henri Gouin

We present the principle of virtual action as a foundation of continuum mechanics. Used mainly in relativity, the method has a useful application in classical mechanics and places the notion of action as the basic concept of dynamics. The principle is an extension of virtual work to space-time. It extends the efforts made by d'Alembert and Lagrange. Unlike t

Zhigang Yan, Dong Li

In Federated Learning (FL), with parameter aggregated by a central node, the communication overhead is a substantial concern. To circumvent this limitation and alleviate the single point of failure within the FL framework, recent studies have introduced Decentralized Federated Learning (DFL) as a viable alternative. Considering the device heterogeneity, and

Tomohiro Itagaki, Kazunori Nakamoto, Takeshi Torii

Let ${\rm N}_m(R) = \{ (a_{ij}) \in {\rm M}_m(R) \mid a_{11} = a_{22} = \cdots = a_{mm} \mbox{ and } a_{ij} = 0 \mbox{ for any } i > j \}$ for a commutative ring $R$. Then ${\rm N}_m(R)$ is a quadratic monomial algebra over $R$. We calculate ${\rm HH}^{\ast}({\rm N}_m(R), {\rm M}_m(R)/{\rm N}_m(R))$ as $R$-modules. We also determine the $R$-algebra structure

John M. Campbell

The (Mahler-Popken) complexity $\| n \|$ of a natural number $n$ is the smallest number of ones that can be used via combinations of multiplication and addition to express $n$, with parentheses arranged in such a way so as to form legal nestings. We generalize $\| \cdot \|$ by defining $\| n \|_{m}$ as the smallest number of possibly repeated selections from

S. L. Gavrilyuk, H. Gouin

By dispersive models of fluid mechanics we are referring to the Euler-Lagrange equations for the constrained Hamilton action functional where the internal energy depends on high order derivatives of unknowns. The mass conservation law is considered as a constraint. The corresponding Euler-Lagrange equations include, in particular, the van der Waals--Korteweg

Timothy Peters, Josh Shelton, Hui Tang, Philippe Trinh

Ice crystal icing (ICI) in aircraft engines is a major threat to flight safety. Due to the complex thermodynamic and phase-change conditions involved in ICI, rigorous modelling of the accretion process remains limited. The present study proposes a novel modelling approach based on the physically-observed mixed-phase nature of the accretion layers. The mathem

Panagiotis Gianniotis

We study the existence and small scale behaviour of almost splitting maps along a Ricci flow satisfying Type I curvature bounds. These are special solutions of the heat equation that serve as parabolic analogues of harmonic almost splitting maps, which have proven to be an indespensable tool in the study of the structure of the singular set of non-collapsed

Pierre-Alexandre Bliman, Nga Nguyen, Nicolas Vauchelet

The Sterile Insect Technique (SIT) is one of the sustainable strategies for the control of disease vectors, which consists of releasing sterilized males that will mate with the wild females, resulting in a reduction and, eventually a local elimination, of the wild population. The implementation of the SIT in the field can become problematic when there are in

Perla Kfoury, Stefan Le Coz

Periodic waves are standing wave solutions of nonlinear Schr\''odinger equations whose profile is periodic in space dimension one. We consider general nonlinearities and provide variational characterizations for the periodic wave profiles. This involves minimizing energy while keeping mass and momentum constant, as well as minimizing the action over the Neha

Riccardo Riolo, Andrea Tomadin, Giacomo Mazza, Reza Asgari

The question of whether or not passive sub-wavelength cavities can alter the properties of quantum materials is currently attracting a great deal of attention. In this Article we show that the Fermi liquid parameters of a two-dimensional metal are modified by cavity polariton modes, and that these changes can be monitored by measuring a paradigmatic magneto-

N. P. Ikonnikova, M. A. Burlak, A. V. Dodin, S. Yu. Shugarov

We present the results of multicolour $UBVR_{\text{C}}I_{\text{C}}JHK$ photometry, spectroscopic analysis and spectral energy distribution (SED) modelling for the post-AGB candidate IRAS 02143+5852. We detected Cepheid-like light variations with the full peak-to-peak amplitude $\Delta V\sim0.9$ mag and the pulsation period of about 24.9 d. The phased light c

Huidong Tang, Chen Li, Sayaka Kamei, Yoshihiro Yamanishi

Deep generative models, such as generative adversarial networks (GANs), have been employed for $de~novo$ molecular generation in drug discovery. Most prior studies have utilized reinforcement learning (RL) algorithms, particularly Monte Carlo tree search (MCTS), to handle the discrete nature of molecular representations in GANs. However, due to the inherent

Vladimir Grinin, Tatiana Demidova

The paper proposes a model of deep and prolonged eclipses of young stars of the UX~Ori type. Some of these events continue for decades and existing models cannot explain them. Our paper shows that such eclipses can be caused by the falling of gas and dust clump from the remnants of the protostellar cloud onto the protoplanetary disk. The disturbance in the d

Zachary T. Draper, Stephen R. Sharpe

We generalize previous three-particle finite-volume formalisms to allow for multiple three-particle channels. For definiteness, we focus on the two-channel $\eta \pi \pi$ and $K \overline K \pi$ system in isosymmetric QCD, considering the positive $G$ parity sector of the latter channel, and neglecting the coupling to modes with four or more particles. The f

Genoveva Vargas-Solar, Jérôme Darmont, Alejandro Adorjan, Javier A. Espinosa-Oviedo

This vision paper introduces a pioneering data lake architecture designed to meet Life \& Earth sciences' burgeoning data management needs. As the data landscape evolves, the imperative to navigate and maximize scientific opportunities has never been greater. Our vision paper outlines a strategic approach to unify and integrate diverse datasets, aiming to cu

Masaki Okada, Yuji Tachikawa

Non-invertible symmetries of quantum field theories and many-body systems generalize the concept of symmetries by allowing non-invertible operations in addition to more ordinary invertible ones described by groups. The aim of this paper is to point out that these non-invertible symmetries act on local operators by quantum operations, i.e. completely positive

Vincent Lescarret

We give a counter part of Sommerfeld outging radiation condition for waves propagating in a 2d periodic medium under generical assumptions and provide a uniqueness theorem for outgoing solutions.

Merlin Füllgraf, Jochen Gemmer

Owning up to the authors' occasional mixed performances when playing darts we follow up on the ingenious work to determine the optimal aim to score high by Tibshirani et. al [JRS A 174, 213 (2011)] and expand on maximal expected reward lines assuming spread profiles beyond the standard case of an isotropic distribution by investigating situations in which a

Hyungjun Yoon, Jaehyun Kwak, Biniyam Aschalew Tolera, Gaole Dai

Self-supervised learning has emerged as a method for utilizing massive unlabeled data for pre-training models, providing an effective feature extractor for various mobile sensing applications. However, when deployed to end-users, these models encounter significant domain shifts attributed to user diversity. We investigate the performance degradation that occ

Marco Calderini, Roberto Civino, Riccardo Invernizzi

Civino et al. (2019) have shown how some diffusion layers can expose a Substitution-Permutation Network to vulnerability from differential cryptanalysis when employing alternative operations coming from groups isomorphic to the translation group on the message space. In this study, we present a classification of diffusion layers that exhibit linearity with r

Luoyu Wang, Yitian Tao, Qing Yang, Yan Liang

Simultaneous functional PET/MR (sf-PET/MR) presents a cutting-edge multimodal neuroimaging technique. It provides an unprecedented opportunity for concurrently monitoring and integrating multifaceted brain networks built by spatiotemporally covaried metabolic activity, neural activity, and cerebral blood flow (perfusion). Albeit high scientific/clinical valu

Antoine Roueff, Jérôme Pety, Maryvonne Gerin, Léontine Ségal

Robust radiative transfer techniques are requisite for efficiently extracting the physical and chemical information from molecular rotational lines.We study several hypotheses that enable robust estimations of the column densities and physical conditions when fitting one or two transitions per molecular species. We study the extent to which simplifying assum

Shadi Manafi, Nikhil Krishnaswamy

Multilingual Language Models (MLLMs) exhibit robust cross-lingual transfer capabilities, or the ability to leverage information acquired in a source language and apply it to a target language. These capabilities find practical applications in well-established Natural Language Processing (NLP) tasks such as Named Entity Recognition (NER). This study aims to i

Mohammad Ghebleh, Salem Al-Yakoob, Ali Kanso, Dragan Stevanović

We describe here how the recent Wagner's approach for applying reinforcement learning to construct examples in graph theory can be used in the search for critical graphs for small Ramsey numbers. We illustrate this application by providing lower bounds for the small Ramsey numbers $R(K_{2,5}, K_{3,5})$, $R(B_3, B_6)$ and $R(B_4, B_5)$ and by improving the lo

Mariusz Lemańczyk, Michal D. Lemańczyk, Thierry de La Rue

Basic properties of stationary processes called Sarnak processes are studied. As an application, a combinatorial reformulation of Sarnak's conjecture on M{\"o}bius orthogonality is provided.

Marco Fedele

Motivated by the recent theoretical and experimental developments in $b \to c \ell\nu$ transitions, the aim of these proceedings is to critically analyse the current situation in this sector. In particular, we will inspect the possibility of explaining the current anomalous pattern by means of New Physics effects coupled with light charged leptons, motivated

Sandra Bella

During the querelle des infiniment petits, Leibniz wrote several texts to justify using Differential calculus among Parisian savants. However, only three were published. Among these publications, ''Sentiment de Monsieur Leibnitz'' had a peculiar destiny. Although we are aware of the manuscript (Gotha FB A 448--449, Bl. 41--42), it is only recently that we ha

Heidemarie Schmidt

We like and need Information and Communications Technologies (ICT) for data processing. This is measureable in the exponential growth of data processed by ICT, e.g. ICT for cryptocurrency mining and search engines. So far, the energy demand for computing technology has increased by a factor of 1.38 every ten years due to the exponentially increasing use of I

Runxi Wang, Jun-Han Han, Mircea Stan, Xinfei Guo

Microfluidic cooling has been recognized as one of the most promising solutions to achieve efficient thermal management for three-dimensional integrated circuits (3DICs). It enables more opportunities to architect 3DICs with different die configurations. It becomes increasingly important to perform thermal analysis in the early design phases to validate the

Leen Droogendijk

Edge-girth-regular graphs (abbreviated as \emph{egr} graphs) are regular graphs in which every edge is contained in the same number of shortest cycles. We prove that there is no $3$-regular \emph{egr} graph with girth $7$ such that every edge is on exactly $6$ shortest cycles, and there is no $3$-regular \emph{egr} graph with girth $8$ such that every edge i

Monica La Barbiera, Roya Moghimipor

In this paper we study classes of monomial ideals for which all of its powers have a linear resolution. Let K[x_{1},x_{2}] be the polynomial ring in two variables over the field K, and let L be the generalized mixed product ideal induced by a monomial ideal I. It is shown that, if I\subset K[x_1,x_2] and the ideals substituting the monomials in I are Verones

Komal Prasad Sharma, Alok Bhargava, Omprakash Saini

Kinetic equations hold a very important place in physics and further their fractional generalization enhances the scope of their applicability and significance in describing the continuity of motion in materials. After the development of generalized form of fractional kinetic equations, many researchers proffered several new forms of these equations and foun

Bowen Lei, Dongkuan Xu, Ruqi Zhang, Bani Mallick

Sparse training has emerged as a promising method for resource-efficient deep neural networks (DNNs) in real-world applications. However, the reliability of sparse models remains a crucial concern, particularly in detecting unknown out-of-distribution (OOD) data. This study addresses the knowledge gap by investigating the reliability of sparse training from

Yongqi Tong, Dawei Li, Sizhe Wang, Yujia Wang

Recent works have shown the benefits to LLMs from fine-tuning golden-standard Chain-of-Thought (CoT) rationales or using them as correct examples in few-shot prompting. While humans can indeed imitate correct examples, learning from our mistakes is another vital aspect of human cognition. Hence, a question naturally arises: \textit{can LLMs learn and benefit

Tianqi Jiang, Haoxiang Luo, Kun Yang, Gang Sun

The energy market encompasses the behavior of energy supply and trading within a platform system. By utilizing centralized or distributed trading, energy can be effectively managed and distributed across different regions, thereby achieving market equilibrium and satisfying both producers and consumers. However, recent years have presented unprecedented chal

Sadhana Singh, Jeewan C. Pandey, Thiem Hoang, Neelam Panwar

Using starlight polarization, we present the properties of foreground dust towards cluster NGC 7380 embedded in H{\sc ii} region Sh 2-142. Observations of starlight polarization are carried out in four filters using an imaging polarimeter equipped with a 104-cm ARIES telescope. Polarization vectors of stars are aligned along the Galactic magnetic field. Towa

Fabio Vallejo

This paper considers the problem of surface waves in an isotropic elastic half-space endowed with impedance boundary conditions as first proposed by Godoy et al. [Wave Motion 49 (2012), 585-594]. These conditions are controlled by two impedance parameters, where the standard stress-free boundary condition is retrieved for zero impedance. While the existence