April 2024 arXiv papers — page 78

Jan Niklas Kolf, Naser Damer, Fadi Boutros

Face Image Quality Assessment (FIQA) estimates the utility of face images for automated face recognition (FR) systems. We propose in this work a novel approach to assess the quality of face images based on inspecting the required changes in the pre-trained FR model weights to minimize differences between testing samples and the distribution of the FR trainin

Karen Luz Burgoa Rosso, José Alberto Casto Nogales Vera, Ana Eliza Ferreira Alvim Silva

In this paper, we propose the replication of scientific experiments, with the participation of the general public, as one of the possible strategies to confront science deniers. Using the social media of the Federal University of Lavras (UFLA), the project entitled : The Magic of Physics and the Universe, invited the public to reproduce the experiment carrie

Ioannis Kousek, Tristán Radić

For a set $A \subset \mathbb{N}$ we characterize in terms of its density when there exists an infinite set $B \subset \mathbb{N}$ and $t \in \{0,1\}$ such that $B+B \subset A-t$, where $B+B : =\{b_1+b_2\colon b_1,b_2 \in B\}$. Specifically, when the lower density $\underline{d}(A) >1/2$ or the upper density $\overline{d}(A)> 3/4$, the existence of such a set

Maryam Ghahremani, Carlos J. Zapata-Rodriguez

This study presents a novel approach to activate a narrowband transparency line within a reflecting broadband window in all-dielectric metasurfaces, in analogy to the electromagnetically-induced transparency effect, by means of a quasi-bound state in the continuum (qBIC). We demonstrate that the resonance overlapping of a bright mode and a qBIC-based nearly-

Mohammad Aghaie, Giovanni Armando, Angela Conaci, Alessandro Dondarini

We propose simple scenarios where the observed dark matter abundance arises from decays and scatterings of heavy quarks through freeze-in of an axion-like particle with mass in the $10 {\rm \, keV} - 1 {\rm \, MeV}$ range. These models can be tested by future X-ray telescopes, and in some cases will be almost entirely probed by searches for two-body decays $

Elena Beretta, Cecilia Cavaterra, Matteo Fornoni, Guillermo Lorenzo

The availability of cancer measurements over time enables the personalised assessment of tumour growth and therapeutic response dynamics. However, many tumours are treated after diagnosis without collecting longitudinal data, and cancer monitoring protocols may include infrequent measurements. To facilitate the estimation of disease dynamics and better guide

Allan Freitas, Felippe Guimarães

We prove a codimension reduction and congruence theorem for compact $n$-dimensional submanifolds of $\mathbb{S}^{n+p}$ that admit a mean convex isometric embedding into $\mathbb{S}^{n+1}_+$ using a Reilly type formula for space forms.

G. Dallabona, P. G. de Oliveira, O. A. Battistel

We present a detailed investigation of the anomalous gravitational amplitude in a simple two-dimensional model with Weyl fermions. We employ a mathematical strategy that completely avoids any regularization prescription for handling divergent perturbative amplitudes. This strategy relies solely on the validity of the linearity of the integration operation an

Chandeepa Dissanayake, Lahiru Lowe, Sachith Gunasekara, Yasiru Ratnayake

Instruction fine-tuning pretrained LLMs for diverse downstream tasks has demonstrated remarkable success and has captured the interest of both academics and practitioners. To ensure such fine-tuned LLMs align with human preferences, techniques such as RLHF and DPO have emerged. At the same time, there is increasing interest in smaller parameter counts for mo

José Barrientos, Adolfo Cisterna, Mokhtar Hassaine, Julio Oliva

This paper investigates Buchdahl transformations within the framework of Einstein and Einstein-Scalar theories. Specifically, we establish that the recently proposed Schwarzschild-Levi-Civita spacetime can be obtained by means of a Buchdahl transformation of the Schwarschild metric along the spacelike Killing vector. The study extends Buchdahl's original the

Sergio A. De Raco, Viktoriya Semeshenko

In this paper we compare Skill-Relatedness Networks (SRNs) for selected countries, that is to say statistically significant inter-industrial interactions representing latent skills exchanges derived from observed labor flows, a kind of industry spaces. Using data from Argentina (ARG), Germany (DEU) and Sweden (SWE), we compare their SRNs utilizing an informa

Radu Chivereanu, Adrian Cosma, Andy Catruna, Razvan Rughinis

Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, including data augmentation and synthetic data generation. This work explores the use of LLMs to generate rich textual descriptions for motion sequences, encompassing both actions and walking patterns. We leverage the expressive power of LLMs to align motion representa

Leandro Benatto, Omar Mesquita, Kaike R. M. Pachecoand Lucimara S. Roman, Marlus Koehler

The Transfer Matrix Method (TMM) has become a prominent tool for the optical simulation of thin$-$film solar cells, particularly among researchers specializing in organic semiconductors and perovskite materials. As the commercial viability of these solar cells continues to advance, driven by rapid developments in materials and production processes, the impor

Jingwei Kang, Maarten de Rijke, Harrie Oosterhuis

Stochastic learning to rank (LTR) is a recent branch in the LTR field that concerns the optimization of probabilistic ranking models. Their probabilistic behavior enables certain ranking qualities that are impossible with deterministic models. For example, they can increase the diversity of displayed documents, increase fairness of exposure over documents, a

R. Mitra, F. Stefani, V. Galindo, S. Eckert

In this paper, we present numerical and experimental results on helicity oscillations in a liquid-metal Rayleigh-B\'enard (RB) convection cell, with an aspect ratio of 0.5. We find that helicity oscillations occur during transitions of flow states that are characterised by significant changes in the Reynolds number. Moreover, we also observe helicity oscilla

Nepomuk Krenn, Peter Gangl

We consider the topology optimization problem of a 2d permanent magnet synchronous machine in magnetostatic operation with demagnetization. This amounts to a PDE-constrained multi-material design optimization problem with an additional pointwise state constraint. Using a generic framework we can incorporate this additional constraint and compute the correspo

Sebastian Hirt, Maik Pfefferkorn, Ali Mesbah, Rolf Findeisen

Designing predictive controllers towards optimal closed-loop performance while maintaining safety and stability is challenging. This work explores closed-loop learning for predictive control parameters under imperfect information while considering closed-loop stability. We employ constrained Bayesian optimization to learn a model predictive controller's (MPC

Xikun Jiang, He Lyu, Chenhao Ying, Yibin Xu

With the increasingly widespread application of machine learning, how to strike a balance between protecting the privacy of data and algorithm parameters and ensuring the verifiability of machine learning has always been a challenge. This study explores the intersection of reinforcement learning and data privacy, specifically addressing the Multi-Armed Bandi

Bestoun S. Ahmed

The rapidly changing landscapes of modern optimization problems require algorithms that can be adapted in real-time. This paper introduces an Adaptive Metaheuristic Framework (AMF) designed for dynamic environments. It is capable of intelligently adapting to changes in the problem parameters. The AMF combines a dynamic representation of problems, a real-time

Tian-Fu Chen, Jie-Hong R. Jiang

Boolean matching is an important problem in logic synthesis and verification. Despite being well-studied for conventional Boolean circuits, its treatment for reversible logic circuits remains largely, if not completely, missing. This work provides the first such study. Given two (black-box) reversible logic circuits that are promised to be matchable, we chec

Andrei Niculae, Andy Catruna, Adrian Cosma, Daniel Rosner

Surveillance footage represents a valuable resource and opportunities for conducting gait analysis. However, the typical low quality and high noise levels in such footage can severely impact the accuracy of pose estimation algorithms, which are foundational for reliable gait analysis. Existing literature suggests a direct correlation between the efficacy of

Jaume Carbonell1, Vladimir Karmanov, Ekaterina Kupriyanova, Hagop Sazdjian

We summarize the main properties of the so called ''abnormal solutions'' of the Wick--Cutkosky model, i.e. two massive scalar particles interacting via massless scalar exchange ("photons"), within the Bethe--Salpeter equation. These solutions do not exist in the non-relativistic limit, in spite of having very small binding energies. They present a genuine ma

Raphaël Maillet, Grégoire Szymanski

We introduce a new approach for estimating the invariant density of a multidimensional diffusion when dealing with high-frequency observations blurred by independent noises. We consider the intermediate regime, where observations occur at discrete time instances $k\Delta_n$ for $k=0,\dots,n$, under the conditions $\Delta_n\to 0$ and $n\Delta_n\to\infty$. Our

Bang Liu, Li-Hua Zhang, Yu Ma, Tian-Yu Han

The criticality enhanced correlations and susceptibility allow weak periodic driving to induce collective synchronization due to critical slowing down, providing a unique platform to study non-equilibrium order emergence. This establishes a powerful paradigm for investigating non-equilibrium order formation, yet the fundamental mechanisms of critical-point s

Saud Čindrak, Adrian Paschke, Lina Jaurigue, Kathy Lüdge

In this work, we propose a quantum-mechanically measurable basis for the computation of spread complexity. Current literature focuses on computing different powers of the Hamiltonian to construct a basis for the Krylov state space and the computation of the spread complexity. We show, through a series of proofs, that time-evolved states with different evolut

Ebbe Kyhl Gøtske, Gorm Bruun Andresen, Fabian Neumann, Marta Victoria

As energy systems transform to rely on renewable energy and electrification, they encounter stronger year-to-year variability in energy supply and demand. However, most infrastructure planning is based on a single weather year, resulting in a lack of robustness. In this paper, we optimize energy infrastructure for a European energy system designed for net-ze

Aitor García-Pablos, Naiara Perez, Montse Cuadros, Jaione Bengoetxea

The widespread availability of Question Answering (QA) datasets in English has greatly facilitated the advancement of the Natural Language Processing (NLP) field. However, the scarcity of such resources for minority languages, such as Basque, poses a substantial challenge for these communities. In this context, the translation and alignment of existing QA da

Lin Ling, Wei Lin, Zhaoheng Liang, Minjie Pan

Dual-comb spectroscopy (DCS) with few-GHz tooth spacing that provides the optimal trade-off between spectral resolution and refresh rate is a powerful tool for measuring and analyzing rapidly evolving transient events. Despite such an exciting opportunity, existing technologies compromise either the spectral resolution or refresh rate, leaving few-GHz DCS wi

Jerome Lloyd, Alexios Michailidis, Xiao Mi, Vadim Smelyanskiy

Probing correlated states of many-body systems is one of the central tasks for quantum simulators and processors. A promising approach to state preparation is to realize desired correlated states as steady states of engineered dissipative evolution. A recent experiment with a Google superconducting quantum processor [X. Mi et al., Science 383, 1332 (2024)] d

Laura Majer, Jan Šnajder

The increasing threat of disinformation calls for automating parts of the fact-checking pipeline. Identifying text segments requiring fact-checking is known as claim detection (CD) and claim check-worthiness detection (CW), the latter incorporating complex domain-specific criteria of worthiness and often framed as a ranking task. Zero- and few-shot LLM promp

Saran Shaju, Dmitriy Sholokhov, Simon B. Jäger, Jürgen Eschner

We experimentally and theoretically study the formation of dressed states emerging from strong collective coupling of the narrow intercombination line of Yb atoms to a single mode of a high-finesse optical cavity. By permanently trapping and cooling the Yb atoms during their interaction with the cavity, we gain continuous experimental access to the dressed s

Tommie Kerssies, Daan de Geus, Gijs Dubbelman

Recent vision foundation models (VFMs) have demonstrated proficiency in various tasks but require supervised fine-tuning to perform the task of semantic segmentation effectively. Benchmarking their performance is essential for selecting current models and guiding future model developments for this task. The lack of a standardized benchmark complicates compar

İlker Gül, Rémi Lebret, Karl Aberer

Stance detection, a key task in natural language processing, determines an author's viewpoint based on textual analysis. This study evaluates the evolution of stance detection methods, transitioning from early machine learning approaches to the groundbreaking BERT model, and eventually to modern Large Language Models (LLMs) such as ChatGPT, LLaMa-2, and Mist

Zhijuan He, Kai Jiang, Liwei Tan, Xin Wang

Self-consistent field theory (SCFT) is one of the most widely-used framework in studying the equilibrium phase behaviors of inhomogenous polymers. For liquid crystalline polymeric systems, the main numerical challenges of solving SCFT encompass efficiently solving plenty of six dimensional partial differential equations (PDEs), precisely determining the subt

Shunpu Tang, Chen Liu, Qianqian Yang, Shibo He

Semantic communication (SemCom) has emerged as a key technology for the forthcoming sixth-generation (6G) network, attributed to its enhanced communication efficiency and robustness against channel noise. However, the open nature of wireless channels renders them vulnerable to eavesdropping, posing a serious threat to privacy. To address this issue, we propo

Leslie Wong

With the rapid growth of information technology, users are exposed to a massive amount of data online, including image, music, and video. This has led to strong needs to provide effective corresponsive search services such as image, music, and video search services. Most of them are operated based on keywords, namely using keywords to find related image, mus

Insoo Kim, Jae Seok Choi, Geonseok Seo, Kinam Kwon

As recent advances in mobile camera technology have enabled the capability to capture high-resolution images, such as 4K images, the demand for an efficient deblurring model handling large motion has increased. In this paper, we discover that the image residual errors, i.e., blur-sharp pixel differences, can be grouped into some categories according to their

Tatiana Vovk, Hannes Pichler

The cost of classical simulations of quantum many-body dynamics is often determined by the amount of entanglement in the system. In this paper, we study entanglement in stochastic quantum trajectory approaches that solve master equations describing open quantum system dynamics. First, we introduce and compare adaptive trajectory unravelings of master equatio

Philippe Laurençot, Ariane Trescases

Convergence to spatially homogeneous steady states is shown for a chemotaxis model with local sensing and possibly nonlinear diffusion when the intrinsic diffusion rate $\phi$ dominates the inverse of the chemotactic motility function $\gamma$, in the sense that $(\phi\gamma)'\ge 0$. This result encompasses and complies with the analysis and numerical simula

Sophie Hall, Giuseppe Belgioioso, Florian Dörfler, Dominic Liao-McPherson

Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion. This control paradigm has recently received increasing attention in various application fields, including robotics, autonomous driving, traf

Edin Husidic, Nicolas Wijsen, Tinatin Baratashvili, Stefaan Poedts

With the rise of satellites and mankind's growing dependence on technology, there is an increasing awareness of space weather phenomena related to high-energy particles. Shock waves driven by coronal mass ejections (CMEs) and corotating interaction regions (CIRs) occasionally act as potent particle accelerators, generating hazardous solar energetic particles

Stefanie Zbinden

Given a geodesic metric space $X$, we construct a corresponding hyperbolic space, which we call the contraction space, that detects all strongly contracting directions in the following sense; a geodesic in $X$ is strongly contracting if and only if its parametrized image in the contraction space is a quasi-geodesic. If a finitely generated group $G$ acts geo

Ningyue Fan, Songyu Li, Rui Zhan, Honghui Liu

We present an analysis of the whole 2018 outburst of the black hole X-ray binary MAXI J1820+070 with Insight-HXMT data. We focus our study on the temporal evolution of the parameters of the source. We employ two different models to fit the disk's thermal spectrum: the Newtonian model DISKBB and the relativistic model NKBB. These two models provide different

Juan Zhang, Wenlu Xun

We have introduced the generalized alternating direction implicit iteration (GADI) method for solving large sparse complex symmetric linear systems and proved its convergence properties. Additionally, some numerical results have demonstrated the effectiveness of this algorithm. Furthermore, as an application of the GADI method in solving complex symmetric li

Michele Giusfredi, Stefano Iubini, Paolo Politi

Several systems display an equilibrium condensation transition, where a finite fraction of a conserved quantity is spatially localized. The presence of two conservation laws may induce the emergence of such transition in an out-of-equilibrium setup, where boundaries are attached to different and subcritical heat baths. We study this phenomenon in a class of

Emil Mathew, Indrakshi Raychowdhury

Quantum simulation of the dynamics of a lattice gauge theory demands imposing on-site constraints. Ideally, the dynamics remain confined within the physical Hilbert space, where all the states satisfy those constraints. For non-Abelian gauge theories, implementing local constraints is non-trivial, as is keeping the dynamics confined in the physical Hilbert s

Euclid Collaboration, F. Dournac, A. Blanchard, S. Ilić

Future data provided by the Euclid mission will allow us to better understand the cosmic history of the Universe. A metric of its performance is the figure-of-merit (FoM) of dark energy, usually estimated with Fisher forecasts. The expected FoM has previously been estimated taking into account the two main probes of Euclid, namely the three-dimensional clust

Roberto Lalli, Paolo Politi

In spring 1949 about 70 physicists from eight countries met in Florence to discuss recent trends in statistical mechanics. This scientific gathering, co-organized by the Commission on Thermodynamics and Statistical Mechanics of the International Union of Pure and Applied Physics (IUPAP) and the Italian Physical Society (SIF), initiated a tradition of IUPAP-s

Michele Farisco, Kathinka Evers, Jean-Pierre Changeux

We here analyse the question of developing artificial consciousness from an evolutionary perspective, taking the evolution of the human brain and its relation with consciousness as a reference model. This kind of analysis reveals several structural and functional features of the human brain that appear to be key for reaching human-like complex conscious expe

Juan Zhang, Wenlu Xun

This paper proposes an effective low-rank alternating direction doubling algorithm (R-ADDA) for computing numerical low-rank solutions to large-scale sparse continuous-time algebraic Riccati matrix equations. The method is based on the alternating direction doubling algorithm (ADDA), utilizing the low-rank property of matrices and employing Cholesky factoriz

Zhen Han, Chaojie Mao, Zeyinzi Jiang, Yulin Pan

Given an original image, image editing aims to generate an image that align with the provided instruction. The challenges are to accept multimodal inputs as instructions and a scarcity of high-quality training data, including crucial triplets of source/target image pairs and multimodal (text and image) instructions. In this paper, we focus on image style edi

Zunran Wang, Zhonghua Li, Wei Shen, Qi Ye

Lexicon-based retrieval has gained siginificant popularity in text retrieval due to its efficient and robust performance. To further enhance performance of lexicon-based retrieval, researchers have been diligently incorporating state-of-the-art methodologies like Neural retrieval and text-level contrastive learning approaches. Nonetheless, despite the promis

Elina Zhakina, Luke Turnbull, Weijie Xu, Markus König

When materials are patterned in three dimensions, there exist opportunities to tailor and create functionalities associated with an increase in complexity, the breaking of symmetries, and the introduction of curvature and non-trivial topologies. For superconducting nanostructures, the extension to the third dimension may trigger the emergence of new physical

Tomasz Korbak

Language models (LMs) trained on vast quantities of text data can acquire sophisticated skills such as generating summaries, answering questions or generating code. However, they also manifest behaviors that violate human preferences, e.g., they can generate offensive content, falsehoods or perpetuate social biases. In this thesis, I explore several approach

Yihua Shao, Yeling Xu, Xinwei Long, Siyu Chen

In complex transportation systems, accurately sensing the surrounding environment and predicting the risk of potential accidents is crucial. Most existing accident prediction methods are based on temporal neural networks, such as RNN and LSTM. Recent multimodal fusion approaches improve vehicle localization through 3D target detection and assess potential ri

Mahmoud Zaher, Emil Björnson, Marina Petrova

Co-channel interference poses a challenge in any wireless communication network where the time-frequency resources are reused over different geographical areas. The interference is particularly diverse in cell-free massive multiple-input multiple-output (MIMO) networks, where a large number of user equipments (UEs) are multiplexed by a multitude of access po

Cella Florescu, Marc Kaufmann, Johannes Lengler, Ulysse Schaller

The compact Genetic Algorithm (cGA), parameterized by its hypothetical population size $K$, offers a low-memory alternative to evolving a large offspring population of solutions. It evolves a probability distribution, biasing it towards promising samples. For the classical benchmark OneMax, the cGA has to two different modes of operation: a conservative one

Xiu-Wu Wang, Zhi-Gang Wang

In the present work, the strong decays of the newly observed $P_{cs}(4338)$ as well as its high isospin cousin $P_{cs}(4460)$ are studied via the QCD sum rules. According to conservation of isospin, spin and parity, the hadronic coupling constants in four decay channels are obtained, then the partial decay widths are obtained. The total width of the $P_{cs}(

Xenia Ohmer, Elia Bruni, Dieuwke Hupkes

The staggering pace with which the capabilities of large language models (LLMs) are increasing, as measured by a range of commonly used natural language understanding (NLU) benchmarks, raises many questions regarding what "understanding" means for a language model and how it compares to human understanding. This is especially true since many LLMs are exclusi

Hilde Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen

Various metrics and interventions have been developed to identify and mitigate unfair outputs of machine learning systems. While individuals and organizations have an obligation to avoid discrimination, the use of fairness-aware machine learning interventions has also been described as amounting to 'algorithmic positive action' under European Union (EU) non-

Yanru Qu, Keyue Qiu, Yuxuan Song, Jingjing Gong

Generative models for structure-based drug design (SBDD) have shown promising results in recent years. Existing works mainly focus on how to generate molecules with higher binding affinity, ignoring the feasibility prerequisites for generated 3D poses and resulting in false positives. We conduct thorough studies on key factors of ill-conformational problems

Yuhang Yang, Xin Ren, Bo Wang, Yi-Fu Cai

We employ Hubble data and Gaussian Processes in order to reconstruct the dynamical connection function in $f(Q)$ cosmology beyond the coincident gauge. In particular, there exist three branches of connections that satisfy the torsionless and curvatureless conditions, parameterized by a new dynamical function $\gamma$. We express the redshift dependence of $\

Shouwei Ruan, Yinpeng Dong, Hanqing Liu, Yao Huang

Vision-Language Pre-training (VLP) models like CLIP have achieved remarkable success in computer vision and particularly demonstrated superior robustness to distribution shifts of 2D images. However, their robustness under 3D viewpoint variations is still limited, which can hinder the development for real-world applications. This paper successfully addresses

Rui Xu, Xintao Wang, Jiangjie Chen, Siyu Yuan

Can Large Language Models (LLMs) simulate humans in making important decisions? Recent research has unveiled the potential of using LLMs to develop role-playing language agents (RPLAs), mimicking mainly the knowledge and tones of various characters. However, imitative decision-making necessitates a more nuanced understanding of personas. In this paper, we be

Yacouba Boubacar Mainassara, Landy Rabehasaina

We consider an observed subcritical Galton Watson process $\{Y_n,\ n\in \mathbb{Z} \}$ with correlated stationary immigration process $\{\epsilon_n,\ n\in \mathbb{Z} \}$. Two situations are presented. The first one is when $\mbox{Cov}(\epsilon_0,\epsilon_k)=0$ for $k$ larger than some $k_0$: a consistent estimator for the reproduction and mean immigration ra

Wei Zhang, Hongcheng Guo, Jian Yang, Zhoujin Tian

Root cause analysis (RCA) in Micro-services architecture (MSA) with escalating complexity encounters complex challenges in maintaining system stability and efficiency due to fault propagation and circular dependencies among nodes. Diverse root cause analysis faults require multi-agents with diverse expertise. To mitigate the hallucination problem of large la

Charlotte Lacoquelle, Xavier Pucel, Louise Travé-Massuyès, Axel Reymonet

This paper addresses the problem of detecting time series outliers, focusing on systems with repetitive behavior, such as industrial robots operating on production lines.Notable challenges arise from the fact that a task performed multiple times may exhibit different duration in each repetition and that the time series reported by the sensors are irregularly

Julia Vinogradova, Gabor Fodor

Recent works on joint communication and sensing (JCAS) cellular networks have proposed to use time division mode (TDM) and concurrent mode (CM), as alternative methods for sharing the resources between communication and sensing signals. While the performance of these JCAS schemes for object tracking and parameter estimation has been studied in previous works

Shahin Amiriparian, Maurice Gerczuk, Justina Lutz, Wolfgang Strube

The delayed access to specialized psychiatric assessments and care for patients at risk of suicidal tendencies in emergency departments creates a notable gap in timely intervention, hindering the provision of adequate mental health support during critical situations. To address this, we present a non-invasive, speech-based approach for automatic suicide risk

Alan D. Sokal, James Walrad

We give a continued-fraction characterization of Stieltjes moment sequences for which there exists a representing measure with support in $[\xi, \infty)$. The proof is elementary.

Naibo Wang, Yuchen Deng, Wenjie Feng, Shichen Fan

Traditional federated learning mainly focuses on parallel settings (PFL), which can suffer significant communication and computation costs. In contrast, one-shot and sequential federated learning (SFL) have emerged as innovative paradigms to alleviate these costs. However, the issue of non-IID (Independent and Identically Distributed) data persists as a sign

Guangchen Wang, Zhuangzhuang Xing

This investigation is dedicated to a two-player zero-sum stochastic differential game (SDG), where a cost function is characterized by a backward stochastic differential equation (BSDE) with a continuous and monotonic generator regarding the first unknown variable, which possesses immense applicability in financial engineering. A verification theorem by virt

Mokhtar Ben Henda, Henri Hudrisier

The future of e-Learning is on the way to be constructed within ICT standardization international instances. The sub-committee 36 of ISO, which is responsible for standardizing educational technologies, is certainly the most prominent of all. The authors of this paper, who are official delegates of the Agency of French Speaking Universities (AUF) with this s

Ionut-Alex Moise, Alexandra Băicoianu

Web caching is essential for the World Wide Web, saving processing power, bandwidth, and reducing latency. Many proxy caching solutions focus on buffering data from the main server, neglecting cacheable information meant for server writes. Existing systems addressing this issue are often intrusive, requiring modifications to the main application for integrat

Shanshan Wang, Ying Hu, Xun Yang, Zhongzhou Zhang

Knowledge Tracing (KT) aims to trace changes in students' knowledge states throughout their entire learning process by analyzing their historical learning data and predicting their future learning performance. Existing forgetting curve theory based knowledge tracing models only consider the general forgetting caused by time intervals, ignoring the individual

Tamanna Jain, Michalis Agathos

The gravitational-wave signal GW170817 is a result of a binary neutron star coalescence event. The observations of electromagnetic counterparts suggest that the event didn't led to the prompt formation of a black-hole. In this work, we first classify the GW170817 LIGO-Virgo data sample into prompt collapse to a black-hole using the $q$-dependent threshold ma

Lars Berger, Uwe M. Borghoff, Gerhard Conrad, Stefan Pickl

Global conflicts and trouble spots have thrown the world into turmoil. Intelligence services have never been as necessary as they are today when it comes to providing political decision-makers with concrete, accurate, and up-to-date decision-making knowledge. This requires a common co-operation, a common working language and a common understanding of each ot

Vitória Cássia Gabriela de Oliveira, José Alberto Casto Nogales Vera

Introduction and Objective. Assuming the need to rethink Education and its function as an element of social transformation and generator of a profound ethical change and promoter of other ways of being on planet Earth, this study seeks to understand the possible dialogues between Earth Pedagogy and Astrobiology in the construction and proposition of continui

Wang Jia, Hang Xu

The present study applies a Deep Reinforcement Learning (DRL) algorithm to Active Flow Control (AFC) of a two-dimensional flow around a confined square cylinder. Specifically, the Soft Actor-Critic (SAC) algorithm is employed to modulate the flow of a pair of synthetic jets placed on the upper and lower surfaces of the confined squared cylinder in flow confi

Sebastian Baader, Masaharu Ishikawa

We construct efficient topological cobordisms between torus links and large connected sums of trefoil knots. As an application, we show that the signature invariant $\sigma_\omega$ at $\omega=\zeta_6$ takes essentially minimal values on torus links among all concordance homomorphisms with the same normalisation on the trefoil knot.

Britta Peis, Niklas Rieken

We give a simpler analysis of the ascending auction of Bikhchandani, de Vries, Schummer, and Vohra to sell a welfare-maximizing base of a matroid at Vickrey prices. The new proofs for economic efficiency and the charge of Vickrey prices only require a few matroid folklore theorems, therefore shortening the analysis of the design goals of the auction signific

Raz Lapid, Almog Dubin, Moshe Sipper

This paper presents RADAR-Robust Adversarial Detection via Adversarial Retraining-an approach designed to enhance the robustness of adversarial detectors against adaptive attacks, while maintaining classifier performance. An adaptive attack is one where the attacker is aware of the defenses and adapts their strategy accordingly. Our proposed method leverages

Sang-Eun Lee, Yoav William Windsor, Daniela Zahn, Alexej Kraiker

Optical manipulation of magnetism holds promise for future ultrafast spintronics, especially with lanthanides and their huge, localized 4f magnetic moments. These moments interact indirectly via the conduction electrons (RKKY exchange), influenced by interatomic orbital overlap, and the conduction electron susceptibility. Here, we study this influence in a s

Salvatore Gatto, Alessandra Colla, Heinz-Peter Breuer, Michael Thoss

A recently developed approach to the thermodynamics of open quantum systems, on the basis of the principle of minimal dissipation, is applied to the spin-boson model. Employing a numerically exact quantum dynamical treatment based on the hierarchical equations of motion (HEOM) method, we investigate the influence of the environment on quantities such as work

Alexander P. Mangerel

Let $\lambda$ denote the Liouville function. We show that for all sufficiently large integers $N$, the (non-trivial) convolution sum bound $$ \left|\sum_{1 \leq n < N} \lambda(n) \lambda(N-n)\right| < N-1 $$ holds. This (essentially) answers a question posed at the 2018 AIM workshop on Sarnak's conjecture.

V. V. Bavula

The aim of the papers is to describe the left regular left quotient ring ${}'Q(R)$ and the right regular right quotient ring $Q'(R)$ for the following algebras $R$: $\mS_n=\mS_1^{\t n}$ is the algebra of one-sided inverses, where $\mS_1=K\langle x,y\, | \, yx=1\rangle$, $\CI_n=K\langle \der_1, \ldots, \der_n,\int_1,\ldots, \int_n\rangle$ is the algebra of sc

Yifei Dong, Xianyi Cheng, Florian T. Pokorny

To develop robust manipulation policies, quantifying robustness is essential. Evaluating robustness in general manipulation, nonetheless, poses significant challenges due to complex hybrid dynamics, combinatorial explosion of possible contact interactions, global geometry, etc. This paper introduces an approach for evaluating manipulation robustness through

J. Cunha, P. Freitas

We develop a unified method to study spectral determinants for several different manifolds, including spheres and hemispheres, and projective spaces. This is a direct consequence of an approach based on deriving recursion relations for the corresponding zeta functions, which we are then able to solve explicitly. Apart from new applications such as hemisphere

Maurizio Grasselli, Luca Scarpa, Andrea Signori

We consider local and nonlocal Cahn-Hilliard equations with constant mobility and singular potentials including, e.g., the Flory-Huggins potential, subject to no-flux (or periodic) boundary conditions. The main goal is to show that the presence of a suitable class of reaction terms allows to establish the existence of a weak solution to the corresponding ini

Nil Mansuroglu, Bouzid Mosbahi

In this note, our goal is to describe the concept of generalized derivations in the context of BiHom-supertrialgebras. We provide a comprehensive analysis of the properties and applications of these generalized derivations, including their relationship with other algebraic structures. We also explore various examples and applications of BiHom-supertrialgebra

J. Ebad-Allah, M. -C. Jiang, R. Borkenhagen, F. Meggle

Antiferromagnetic FeSn is considered to be a close realization of the ideal two-dimensional (2D) kagome lattice, hosting Dirac cones, van Hove singularities, and flat bands, as it comprises Fe$_3$Sn kagome layers well separated by Sn buffer layers. We observe a pronounced optical anisotropy, with the low-energy optical conductivity being surprisingly higher

A. Sladkov, C. Fegan, W. Yao, A. F. A. Bott

Interactions between magnetic fields advected by matter play a fundamental role in the Universe at a diverse range of scales. A crucial role these interactions play is in making turbulent fields highly anisotropic, leading to observed ordered fields. These in turn, are important evolutionary factors for all the systems within and around. Despite scant eviden

Qingxuan Fu, Song He, Li Li, Zhibin Li

To quantitatively provide reliable predictions for the hot and dense QCD matter, a holographic model should be adjusted to describe first-principles lattice results available at vanishing baryon chemical potential. The equation of state from two well-known lattice groups, the HotQCD collaboration and the Wuppertal-Budapest (WB) collaboration, shows visible d

Salman Fariz Navas, Sabine H. L. Klapp

Non-reciprocal (NR) effective interactions violating Newton's third law occur in many biological systems, but can also be engineered in synthetic, colloidal systems. Recent research has shown that such NR interactions can have tremendous effects on the overall collective behaviour and pattern formation, but can also influence aggregation processes on the par

Angshuman Robin Goswami

In this paper, we primarily deal with approximately monotone and convex sequences. We start by showing that any sequence can be expressed as the difference between two nondecreasing sequences. One of these two monotone sequences act as the majorant of the original sequence, while the other possesses non-negativity. Another result establishes that an approxim

Taige Zhao, Jianxin Li, Ningning Cui, Wei Luo

Community search over heterogeneous information networks has been applied to wide domains, such as activity organization and team formation. From these scenarios, the members of a group with the same treatment often have different levels of activity and workloads, which causes unfairness in the treatment between active members and inactive members (called in

Alvise Bastianello, Žiga Krajnik, Enej Ilievski

The classical Landau--Lifshitz equation -- the simplest model of a ferromagnet -- provides an archetypal example for studying transport phenomena. In one-spatial dimension, integrability enables the classification of the spectrum of linear and nonlinear modes. An exact characterization of finite-temperature thermodynamics and transport has nonetheless remain

Jago Edyvean, Tulasi N. Parashar, Tom Simpson, James Juno

Understanding plasma turbulence requires a synthesis of experiments, observations, theory, and simulations. In the case of kinetic plasmas such as the solar wind, the lack of collisions renders the fluid closures such as viscosity meaningless and one needs to resort to higher order fluid models or kinetic models. Typically, the computational expense in such

Yuzhu Cai, Sheng Yin, Yuxi Wei, Chenxin Xu

The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors. However, these advancements bring forth critical ethical concerns, particularly with the misuse of open-source models to generate content that violates societal norms. Addressing this, we int

Nikolina Kubiak, Armin Mustafa, Graeme Phillipson, Stephen Jolly

In this paper we present S3R-Net, the Self-Supervised Shadow Removal Network. The two-branch WGAN model achieves self-supervision relying on the unify-and-adaptphenomenon - it unifies the style of the output data and infers its characteristics from a database of unaligned shadow-free reference images. This approach stands in contrast to the large body of sup