May 2023 arXiv papers — page 170

Misha Urooj Khan, Maham Misbah, Zeeshan Kaleem, Yansha Deng

The usage of drones has tremendously increased in different sectors spanning from military to industrial applications. Despite all the benefits they offer, their misuse can lead to mishaps, and tackling them becomes more challenging particularly at night due to their small size and low visibility conditions. To overcome those limitations and improve the dete

Rami Oueslati

The present phenomenological study investigates a multi-channel model of high-energy hadron interactions by considering a full parton configurations space and the $U$-matrix unitarisation scheme of the elastic amplitude, comparing it to the two-channel model, and examining the consequences of up-to-date high-energy collider data on the best fits to various h

Yanqi Xiong, Xiaoquan Yu

We develop a neutral vortex fluid theory on closed surfaces with zero genus. The theory describes collective dynamics of many well-separated quantum vortices in a superfluid confined on a closed surface. Comparing to the case on a plane, the covariant vortex fluid equation on a curved surface contains an additional term proportional to Gaussian curvature mul

Ralph Peeters, Christian Bizer

Entity Matching is the task of deciding if two entity descriptions refer to the same real-world entity. State-of-the-art entity matching methods often rely on fine-tuning Transformer models such as BERT or RoBERTa. Two major drawbacks of using these models for entity matching are that (i) the models require significant amounts of fine-tuning data for reachin

Chao Yun, Zhongyu Liang, Aleš Hrabec, Zhentao Liu

Two-dimensional arrays of magnetically coupled nanomagnets provide a mesoscopic platform for exploring collective phenomena as well as realizing a broad range of spintronic devices. In particular, the magnetic coupling plays a critical role in determining the nature of the cooperative behaviour and providing new functionalities in nanomagnet-based devices. H

Juho Halonen, Risto Korhonen, Galina Filipuk

A generalization of the second main theorem of tropical Nevanlinna theory is presented for noncontinuous piecewise linear functions and for tropical hypersurfaces without requiring a growth condition. The method of proof is novel and significantly more straightforward than previously known proofs. The tropical analogue of the Nevanlinna inverse problem is fo

Ruben Van Belle

In this paper we will give a categorical proof of the Radon-Nikodym theorem. We will do this by describing the trivial version of the result on finite probability spaces as a natural isomorphism. We then proceed to Kan extend this isomorphism to obtain the result for general probability spaces. Moreover, we observe that conditional expectation naturally appe

Yahya Saleh

For this final year project, the goal is to add to the published works within data synthesis for health care. The end product of this project is a trained model that generates synthesized images that can be used to expand a medical dataset (Pierre, 2021). The chosen domain for this project is the Covid-19 cough recording which is have been proven to be a via

Alexey Golovnev, A. N. Semenova, V. P. Vandeev

We give a pedagogical introduction to static spherically symmetric solutions in models of New GR, both explaining the basics and showing how all such vacuum solutions can be obtained in elementary functions. In doing so, we coherently introduce the full landscape of these modified teleparallel spacetimes, and find a few special cases. The equations of motion

Yanxiang Jia, Xuyang Wang, Xiao Hu, Xin Hua

We designed and experimentally demonstrated a silicon photonics-integrated time-domain balanced homodyne detector (TBHD), whose optical part has dimensions of 1.5 mm * 0.4 mm. To automatically and accurately balance the detector, new variable optical attenuators were used, and a common mode rejection ratio of 86.9 dB could be achieved. In the quantum tomogra

Jose D. Bermúdez-Perez, Edwin Herrera-Vasco, Javier Casas-Salgado, Hector A. Castelblanco

We present the design, fabrication and discuss the performance of a new combined high-resolution Scanning Tunneling and thermopower Microscope (STM/SThEM). We also describe the development of the electronic control, the user interface, the vacuum system, and arrangements to reduce acoustical noise and vibrations. We demonstrate the microscope performance wit

Cecile Engrand, Jérémie Lasue, Diane H. Wooden, Mike E. Zolensky

Cometary dust particles are best preserved remnants of the matter present at the onset of the formation of the Solar System. Space missions, telescopic observations and laboratory analyses advanced the knowledge on the properties of cometary dust. Cometary samples were returned from comet 81P/Wild2 by the Stardust mission. The chondritic (porous) anhydrous i

Ousmane Youme, Jean Marie Dembele, Eugene C. Ezin, Christophe Cambier

In recent years, the CNN architectures designed by evolution algorithms have proven to be competitive with handcrafted architectures designed by experts. However, these algorithms need a lot of computational power, which is beyond the capabilities of most researchers and engineers. To overcome this problem, we propose an evolution architecture under length c

Abhishek Kushwaha, Amitesh Roy, Ianko Chterev, Isaac Boxx

In this paper, we present a framework to study the synchronization of flow velocity with acoustic pressure and heat-release rate in technically-premixed swirl flames. The framework uses the extended proper orthogonal decomposition to identify regions of the velocity field where velocity and heat release fluctuations are highly correlated. We apply this frame

Lai Wei, Zhengwei Chen, Jun Yin, Changming Zhu

Spectral-type subspace clustering algorithms have shown excellent performance in many subspace clustering applications. The existing spectral-type subspace clustering algorithms either focus on designing constraints for the reconstruction coefficient matrix or feature extraction methods for finding latent features of original data samples. In this paper, ins

Henry F. J. Tregidgo, Sonja Soskic, Mark D. Olchanyi, Juri Althonayan

The human thalamus is a highly connected subcortical grey-matter structure within the brain. It comprises dozens of nuclei with different function and connectivity, which are affected differently by disease. For this reason, there is growing interest in studying the thalamic nuclei in vivo with MRI. Tools are available to segment the thalamus from 1 mm T1 sc

Dániel Garamvölgyi, Tibor Jordán

A $d$-dimensional framework is a pair $(G,p)$, where $G$ is a graph and $p$ maps the vertices of $G$ to points in $\mathbb{R}^d$. The edges of $G$ are mapped to the corresponding line segments. A graph $G$ is said to be globally rigid in $\mathbb{R}^d$ if every generic $d$-dimensional framework $(G,p)$ is determined, up to congruence, by its edge lengths. A

Gregory Chance, Dhaminda B. Abeywickrama, Beckett LeClair, Owen Kerr

As Autonomous Systems (AS) become more ubiquitous in society, more responsible for our safety and our interaction with them more frequent, it is essential that they are trustworthy. Assessing the trustworthiness of AS is a mandatory challenge for the verification and development community. This will require appropriate standards and suitable metrics that may

E. Kleisioti, D. Dirkx, M. Rovira-Navarro, M. A. Kenworthy

Exomoons are expected to orbit gas giant exoplanets just as moons orbit solar system planets. Tidal heating is present in solar system satellites and it can heat up their interior depending on their orbital and interior properties. We aim to identify a Tidally Heated Exomoon's (THEM) orbital parameter space that would make it observable in infrared wavelengt

Joana Fraxanet, Alexandre Dauphin, Maciej Lewenstein, Luca Barbiero

In this work, we investigate a two-dimensional system of ultracold bosonic atoms inside an optical cavity, and show how photon-mediated interactions give rise to a plaquette-ordered bond pattern in the atomic ground state. The latter corresponds to a 2D Peierls transition, generalizing the spontaneous bond dimmerization driven by phonon-electron interactions

Hyowon Kim, Angel F. García-Fernández, Yu Ge, Yuxuan Xia

Belief propagation (BP) is a useful probabilistic inference algorithm for efficiently computing approximate marginal probability densities of random variables. However, in its standard form, BP is only applicable to the vector-type random variables with a fixed and known number of vector elements, while certain applications rely on RFSs with an unknown numbe

Lei Lei, Lei Zu, Guan-Wen Yuan, Zhao-Qiang Shen

Studies have proposed that there is evidence for cosmological coupling of black holes (BHs) with an index of $k\approx 3$; hence, BHs serve as the astrophysical source of dark energy. However, the data sample is limited for the redshifts of $\leq 2.5$. In recent years, the James Webb Space Telescope (JWST) has detected many high-redshift active galactic nucl

G. C. M. Silvestre, F. Balado, O. Akinremi, M. Ramo

The Transformer architecture is shown to provide a powerful machine transduction framework for online handwritten gestures corresponding to glyph strokes of natural language sentences. The attention mechanism is successfully used to create latent representations of an end-to-end encoder-decoder model, solving multi-level segmentation while also learning some

Pascal Scholl, Adam L. Shaw, Richard Bing-Shiun Tsai, Ran Finkelstein

Minimizing and understanding errors is critical for quantum science, both in noisy intermediate scale quantum (NISQ) devices and for the quest towards fault-tolerant quantum computation. Rydberg arrays have emerged as a prominent platform in this context with impressive system sizes and proposals suggesting how error-correction thresholds could be significan

Anthony Frion, Lucas Drumetz, Guillaume Tochon, Mauro Dalla Mura

Over the last few years, massive amounts of satellite multispectral and hyperspectral images covering the Earth's surface have been made publicly available for scientific purpose, for example through the European Copernicus project. Simultaneously, the development of self-supervised learning (SSL) methods has sparked great interest in the remote sensing comm

Benedikt Preis

In this thesis we give two applications of Ayoub's motivic nearby cycles functor: First we give a generalization of Grothendieck's classical local monodromy theorem. In the classical setup we show that the inertia group acts quasi-unipotently on the \'etale cohomology of sheaves 'coming from motives'. Second we study the notion of universal local acyclicity

Giulia Venditti, Sergio Caprara

Increasing experimental evidence suggests the occurrence of filamentary superconductivity in different (quasi) two-dimensional physical systems. In this piece of work, we discuss the proposal that under certain circumstances, this occurrence may be related to the competition with a phase characterized by charge ordering in the form of charge-density waves. W

Noah Hollmann, Samuel Müller, Frank Hutter

As the field of automated machine learning (AutoML) advances, it becomes increasingly important to incorporate domain knowledge into these systems. We present an approach for doing so by harnessing the power of large language models (LLMs). Specifically, we introduce Context-Aware Automated Feature Engineering (CAAFE), a feature engineering method for tabula

Michael Hinze, Christian Kahle, Michael Stahl

We propose a least squares formulation for abstract parabolic equations in the natural $L^2(0,T;V^\star)\times H$ norm which only relies on natural regularity assumptions on the data of the problem. The resulting bilinear form then is symmetric, coercive and continuous. We provide two space-time Galerkin frameworks for the numerical approximation. The first

ATLAS Collaboration

This paper describes a search for the single production of an up-type vector-like quark ($T$) decaying as $T \rightarrow Ht$ or $T \rightarrow Zt$. The search utilises a dataset of $pp$ collisions at $\sqrt{s}=13$ TeV collected with the ATLAS detector during the 2015-2018 data-taking period of the Large Hadron Collider, corresponding to an integrated luminos

Anuja Sahasrabudhe, Mikhail A. Prosnikov, Thomas C. Koethe, Philipp Stein

In the Kitaev magnet $\alpha$-RuCl$_3$, the existence of a magnetic-field-induced quantum spin liquid phase and of anyonic excitations are discussed controversially. We address this elusive, exotic phase via helicity-dependent Raman scattering and analyze the Raman optical activity of excitations as a function of magnetic field and temperature. The hotly deb

Satya Prakash Nayak, Lucas Neves Egidio, Matteo Della Rossa, Anne-Kathrin Schmuck

We consider the problem of automatically synthesizing a hybrid controller for non-linear dynamical systems which ensures that the closed-loop fulfills an arbitrary \emph{Linear Temporal Logic} specification. Moreover, the specification may take into account logical context switches induced by an external environment or the system itself. Finally, we want to

Sreejith Chulliparambil, Hua-Chen Zhang, Hong-Hao Tu

We introduce a family of SO($n$)-symmetric spin chains which generalize the transverse-field Ising chain for $n=1$. These spin chains are defined with Gamma matrices and can be exactly solved by mapping to $n$ species of itinerant Majorana fermions coupled to a static $\mathbb{Z}_2$ gauge field. Their phase diagrams include a critical point described by the

T. G. de Jong, G. Prokert, A. E. Sterk

We investigate a nonlinear parabolic reaction-diffusion equation describing the oxygen concentration in encapsulated pancreatic cells with a general core-shell geometry. This geometry introduces a discontinuous diffusion coefficient as the material properties of the core and shell differ. We apply monotone operator theory to show well-posedness of the proble

Lukas Mauth

We obtain an exact formula for the cubic partition function and prove a conjecture by Banerjee, Paule, Radu and Zeng.

Lars Skaaret-Lund, Geir Storvik, Aliaksandr Hubin

Artificial neural networks (ANNs) are powerful machine learning methods used in many modern applications such as facial recognition, machine translation, and cancer diagnostics. A common issue with ANNs is that they usually have millions or billions of trainable parameters, and therefore tend to overfit to the training data. This is especially problematic in

Zheyu Wu, Remmy Zen, Heitor P. Casagrande, Stéphane Bressan

Different neural network architectures can be unsupervisedly or supervisedly trained to represent quantum states. We explore and compare different strategies for the supervised training of feed forward neural network quantum states. We empirically and comparatively evaluate the performance of feed forward neural network quantum states in different phases of

Maksym Lysak, Ahmed Nassar, Nikolaos Livathinos, Christoph Auer

Extracting tables from documents is a crucial task in any document conversion pipeline. Recently, transformer-based models have demonstrated that table-structure can be recognized with impressive accuracy using Image-to-Markup-Sequence (Im2Seq) approaches. Taking only the image of a table, such models predict a sequence of tokens (e.g. in HTML, LaTeX) which

Sergei Nayakshin, James E. Owen, Vardan Elbakyan

Disc accretion rate onto low mass protostar FU Ori suddenly increased hundreds of times 85 years ago and remains elevated to this day. We show that the sum of historic and recent observations challenges existing FU Ori models. We build a theory of a new process, Extreme Evaporation (EE) of young gas giant planets in discs with midplane temperatures exceeding

James A King, Arshdeep Singh, Mark D. Plumbley

Convolutional neural networks (CNNs) are commonplace in high-performing solutions to many real-world problems, such as audio classification. CNNs have many parameters and filters, with some having a larger impact on the performance than others. This means that networks may contain many unnecessary filters, increasing a CNN's computation and memory requiremen

Jonas Stein, Farbod Chamanian, Maximilian Zorn, Jonas Nüßlein

Quantum computing provides powerful algorithmic tools that have been shown to outperform established classical solvers in specific optimization tasks. A core step in solving optimization problems with known quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) is the problem formulation. While quantum optimization has historically

Victor Gayral, Valentin Marie

Given a locally compact group $G=Q\ltimes V$ such that $V$ is Abelian and such that the action of $Q$ on the Pontryagin dual $\hat V$ has a free orbit of full measure, we construct a family of unitary dual $2$-cocycles $\Omega_\omega$ (aka non-formal Drinfel'd twists) whose equivalence classes $[\Omega_\omega]\in H^2(\hat G,\mathbb T)$ are parametrized by co

Hongjie Ye, Zhaohao Wang

Three-terminal magnetic tunnel junction (MTJ), where non-volatile magnetization state can be switched via spin orbit torque (SOT), is attracting massive research interests since it is featured by high speed, low power, nearly unlimited endurance, etc. The threshold switching current is a key parameter for MTJ as it determines the energy efficiency. Here, wit

Jiaming Guo, Xueyi Zou, Yuyi Chen, Yi Liu

In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD) resolution have become more popular for display devices such as TVs, mobile phones and VR. However, these high resolution images cannot achieve the expected visual effect due to the limitation of the internet bandwidth, and bring a great challenge for super-resolution networks to achie

Vikas Saini, Souvik Sasmal, Vikash Sharma, Suman Nandi

Chalcopyrite compounds are extensively explored for their exotic topological phases and associated phenomena in a variety of experiments. Here, we discuss the electrical transport properties of a direct energy gap semiconductor CdGeAs$_{2}$. The observed transverse magnetoresistance (MR) is found to be around 136% at a temperature of 1.8 K and a magnetic fie

Marco Spanghero, Panos Papadimitratos

Civilian Global Navigation Satellite Systems (GNSS) vulnerabilities are a threat to a wide gamut of critical systems. GNSS receivers, as part of the encompassing platform, can leverage external information to detect GNSS attacks. Specifically, cross-checking the time produced by the GNSS receiver against multiple trusted time sources can provide robust and a

Jiankang Shi, Minghua Chen

Anomalous diffusion is often modelled in terms of the subdiffusion equation, which can involve a weakly singular source term. For this case, many predominant time stepping methods, including the correction of high-order BDF schemes [{\sc Jin, Li, and Zhou}, SIAM J. Sci. Comput., 39 (2017), A3129--A3152], may suffer from a severe order reduction. To fill in t

Zahra Tabatabaei, Yuandou Wang, Adrián Colomer, Javier Oliver Moll

The paper proposes a Federated Content-Based Medical Image Retrieval (FedCBMIR) platform that utilizes Federated Learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. CBMIR assists pathologists in diagnosing breast cancer more rapidly by identifying similar medical images and relevant patches in prior case

Jiafeng Mao, Xueting Wang, Kiyoharu Aizawa

Diffusion models have the ability to generate high quality images by denoising pure Gaussian noise images. While previous research has primarily focused on improving the control of image generation through adjusting the denoising process, we propose a novel direction of manipulating the initial noise to control the generated image. Through experiments on sta

Josefine Foos, Stephan Held, Yannik Kyle Dustin Spitzley

Uniform cost-distance Steiner trees minimize the sum of the total length and weighted path lengths from a dedicated root to the other terminals. They are applied when the tree is intended for signal transmission, e.g. in chip design or telecommunication networks. They are a special case of general cost-distance Steiner trees, where different distance functio

Nisheeth Joshi, Pragya Katyayan

People who are visually impaired face a lot of difficulties while studying. One of the major causes to this is lack of available text in Bharti Braille script. In this paper, we have suggested a scheme to convert text in major Indian languages into Bharti Braille. The system uses a hybrid approach where at first the text in Indian language is given to a rule

Hans-Georg Fill, Fabian Muff

Large Language Models (LLMs) have revolutionized natural language processing by generating human-like text and images from textual input. However, their potential to generate complex 2D/3D visualizations has been largely unexplored. We report initial experiments showing that LLMs can generate 2D/3D visualizations that may be used for legal visualization. Fur

Kwara Nantomah

By using some tools of analysis, we establish some analytical properties such as monotonicity and inequalities involving the hyperbolic sine integral function. As applications of some of the established properties, we obtain some rational bounds for the hyperbolic tangent function.

Zhengzhuo Xu, Zenghao Chai, Chengyin Xu, Chun Yuan

Real-world data usually suffers from severe class imbalance and long-tailed distributions, where minority classes are significantly underrepresented compared to the majority ones. Recent research prefers to utilize multi-expert architectures to mitigate the model uncertainty on the minority, where collaborative learning is employed to aggregate the knowledge

Anett Kocsis, Dávid Matolcsi, Csaba Sándor, György Tőtős

In this paper we prove that if $A$ and $B$ are infinite subsets of positive integers such that every positive integer $n$ can be written as $n=ab$, $a\in A$, $b\in B$, then $\displaystyle \lim_{x\to \infty}\frac{A(x)B(x)}{x}=\infty $. We also prove many other results about sets like this.

Goda Klumbyte, Hannah Piehl, Claude Draude

Contemporary automation through AI entails a substantial amount of behind-the-scenes human labour, which is often both invisibilised and underpaid. Since invisible labour, including labelling and maintenance work, is an integral part of contemporary AI systems, it remains important to sensitise users to its role. We suggest that this could be done through ex

Goda Klumbyte, Hannah Piehl, Claude Draude

This paper follows calls for critical approaches to computing and conceptualisations of intersectional, feminist, decolonial HCI and AI design and asks what a feminist intersectional perspective in HCXAI research and design might look like. Sketching out initial research directions and implications for explainable AI design, it suggests that explainability f

Hong Chen, Yipeng Zhang, Simin Wu, Xin Wang

Subject-driven text-to-image generation aims to generate customized images of the given subject based on the text descriptions, which has drawn increasing attention. Existing methods mainly resort to finetuning a pretrained generative model, where the identity-relevant information (e.g., the boy) and the identity-irrelevant information (e.g., the background

Kim Chol-jun

We checked that the distribution of words in text should uniform, which gives Heaps' law as natural result, that is, the number of types of words can be expressed as a power law of the number of tokens within text. We developed a ``superposition'' model, which leads to an asymptotic power-law distribution of the number of occurrences (or frequency) of words,

Eugenio Bellini, Ugo Boscain

We consider surfaces embedded in a 3D contact sub-Riemannian manifold and the problem of the finiteness of the induced distance (i.e., the infimum of the length of horizontal curves that belong to the surface). Recently it has been proved that for a surface having the topology of a sphere embedded in a tight co-orientable structure, the distance is always fi

Marco Benini, Alexander Schenkel

This chapter provides a non-technical overview and motivation for the recent interactions between algebraic quantum field theory (AQFT) and rather abstract mathematical disciplines such as operads, model categories and higher categories.

Nisheeth Joshi, Pragya Katyayan

In this paper, we have shown the improvement of English to Bharti Braille machine translation system. We have shown how we can improve a baseline NMT model by adding some linguistic knowledge to it. This was done for five language pairs where English sentences were translated into five Indian languages and then subsequently to corresponding Bharti Braille. T

Anagha Sasikumar, Céline Merlet

Characterizing ion adsorption and diffusion in porous carbons is essential to understand the performance of such materials in a range of key technologies such as energy storage and capacitive deionisation. Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful technique to get insights in these systems thanks to its ability to distinguish between bulk a

Stefano De Marchi, Giacomo Elefante, Francesco Marchetti, Jean-Zacharie Mariethoz

Recently, $(\beta,\gamma)$-Chebyshev functions, as well as the corresponding zeros, have been introduced as a generalization of classical Chebyshev polynomials of the first kind and related roots. They consist of a family of orthogonal functions on a subset of $[-1,1]$, which indeed satisfies a three-term recurrence formula. In this paper we present further

Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan

The MuSe 2023 is a set of shared tasks addressing three different contemporary multimodal affect and sentiment analysis problems: In the Mimicked Emotions Sub-Challenge (MuSe-Mimic), participants predict three continuous emotion targets. This sub-challenge utilises the Hume-Vidmimic dataset comprising of user-generated videos. For the Cross-Cultural Humour D

Yannic Behovits, Alexander L. Chekhov, Stanislav Yu. Bodnar, Oliver Gueckstock

Antiferromagnets have large potential for ultrafast coherent switching of magnetic order with minimum heat dissipation. In novel materials such as Mn$_2$Au and CuMnAs, electric rather than magnetic fields may control antiferromagnetic order by N\'eel spin-orbit torques (NSOTs), which have, however, not been observed on ultrafast time scales yet. Here, we exc

Stefan Wagner

This article focuses on a system of sticky Brownian motions, also known as Howitt-Warren martingale problem, and correlated Brownian motions and shows that infinite-dimensional orthogonal polynomials intertwine the dynamics of infinitely many particles and their $n$-particle evolution. The proof is based on two assumptions about the model: information about

Archishman Raju, Eric D. Siggia

Cell fate decisions emerge as a consequence of a complex set of gene regulatory networks. Models of these networks are known to have more parameters than data can determine. Recent work, inspired by Waddington's metaphor of a landscape, has instead tried to understand the geometry of gene regulatory networks. Here, we describe recent results on the appropria

Zhen Liang, Taoran Wu, Changyuan Zhao, Wanwei Liu

The increasing use of deep neural networks (DNNs) in safety-critical systems has raised concerns about their potential for exhibiting ill-behaviors. While DNN verification and testing provide post hoc conclusions regarding unexpected behaviors, they do not prevent the erroneous behaviors from occurring. To address this issue, DNN repair/patch aims to elimina

Aashay Singhal, Kamalakar Karlapalem

In order to advance academic research, it is important to assess and evaluate the academic influence of researchers and the findings they produce. Citation metrics are universally used methods to evaluate researchers. Amongst the several variations of citation metrics, the h-index proposed by Hirsch has become the leading measure. Recent work shows that h-in

Takashi J. Moriya, Paolo A. Mazzali, Chris Ashall, Elena Pian

The effects of the interaction between Type Ia supernova ejecta and their circumstellar wind on the photometric properties of Type Ia supernovae are investigated. We assume that a hydrogen-rich, dense, and extended circumstellar matter (CSM) is formed by the steady mass loss of their progenitor systems. The CSM density is assumed to be proportional to r^{-2}

Moreshwar Tayde, Sayantan Ghosh, P. K. Sahoo

In this study, we have conducted an analysis of traversable wormhole solutions within the framework of linear $f(Q, T) = \alpha Q + \beta T$ gravity, ensuring that all the energy conditions hold for the entire spacetime. The solutions presented in this study were derived through a comprehensive analytical examination of the parameter space associated with th

Hugo Lourenço, João Costa Seco, Carla Ferreira, Tiago Simões

In model-driven engineering, the bidirectional transformation of models plays a crucial role in facilitating the use of editors that operate at different levels of abstraction. This is particularly important in the context of industrial-grade low-code platforms like OutSystems, which feature a comprehensive ecosystem of tools that complement the standard int

Hamdy Mubarak, Samir Abdaljalil, Azza Nassar, Firoj Alam

Social media platforms empower us in several ways, from information dissemination to consumption. While these platforms are useful in promoting citizen journalism, public awareness etc., they have misuse potentials. Malicious users use them to disseminate hate-speech, offensive content, rumor etc. to gain social and political agendas or to harm individuals,

Seiga Ochi, Kouta Ozaki, Kohei Noda, Heeyoung Lee

The spatial resolution of direct-modulation Brillouin optical correlation-domain reflectometry is studied with respect to modulation amplitude and frequency. Results suggest that optimal resolution improvement is achieved by increasing modulation amplitude first, followed by frequency.

Haoyang He

Model-based approaches are becoming increasingly popular in the field of offline reinforcement learning, with high potential in real-world applications due to the model's capability of thoroughly utilizing the large historical datasets available with supervised learning techniques. This paper presents a literature review of recent work in offline model-based

N. A. Melnikova, M. N. Achasov, A. A. Botov, V. P. Druzhinin

The SND is a non-magnetic detector at the VEPP-2000 $e^{+} e^{-}$ collider (BINP, Novosibirsk) designed for hadronic cross-section measurements in the center-of-mass energy range up to $2$ GeV. The important part of the detector is a hodoscopic electromagnetic calorimeter (EMC) with three layers of NaI(Tl) counters. The EMC signal shaping and digitizing elec

Halil Mutuk

We study the $S$-wave mass spectra of flavor exotic triply-heavy tetraquark states $cc\bar{c}\bar{q}$, $cc\bar{b}\bar{q}$, $bb\bar{c}\bar{q}$ and $bb\bar{b}\bar{q}$. We adopt a diquark-antidiquark scheme to solve Schr\"{o}dinger equation. The calculations are carried out in a nonrelativistic quark model with a color interaction described by a potential compu

Cameron Calk, Eric Goubault, Philippe Malbos

In this work, we explore links between natural homology and persistent homology for the classification of directed spaces. The former is an algebraic invariant of directed spaces, a semantic model of concurrent programs. The latter was developed in the context of topological data analysis, in which topological properties of point-cloud data sets are extracte

Wangzhen Guo, Linyin Luo, Hanjiang Lai, Jian Yin

Parsing questions into executable logical forms has showed impressive results for knowledge-base question answering (KBQA). However, complex KBQA is a more challenging task that requires to perform complex multi-step reasoning. Recently, a new semantic parser called KoPL has been proposed to explicitly model the reasoning processes, which achieved the state-

Zongxiong Chen, Jiahui Geng, Derui Zhu, Herbert Woisetschlaeger

The aim of dataset distillation is to encode the rich features of an original dataset into a tiny dataset. It is a promising approach to accelerate neural network training and related studies. Different approaches have been proposed to improve the informativeness and generalization performance of distilled images. However, no work has comprehensively analyze

Haowen Liu, Fengxian Wu, Bin Zhong, Yijun Zhao

Cane-type robots have been utilized to assist and supervise the mobility-impaired population. One essential technique for cane-type robots is human following control, which allows the robot to follow the user. However, the limited perceptible information of humans by sensors at close range, combined with the occlusion caused by lower limb swing during normal

Damien Sileo, Antoine Lernould

Theory of Mind (ToM) is a critical component of intelligence but its assessment remains the subject of heated debates. Prior research applied human ToM assessments to natural language processing models using either human-created standardized tests or rule-based templates. However, these methods primarily focus on simplistic reasoning and require further vali

Taoyong Cui, Yuhan Dong

Image/video denoising in low-light scenes is an extremely challenging problem due to limited photon count and high noise. In this paper, we propose a novel approach with contrastive learning to address this issue. Inspired by the success of contrastive learning used in some high-level computer vision tasks, we bring in this idea to the low-level denoising ta

Yiyi Zhang, Zhiwen Ying, Ying Zheng, Cuiling Wu

Plant leaf identification is crucial for biodiversity protection and conservation and has gradually attracted the attention of academia in recent years. Due to the high similarity among different varieties, leaf cultivar recognition is also considered to be an ultra-fine-grained visual classification (UFGVC) task, which is facing a huge challenge. In practic

Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi

Reconstructing samples from the training set of trained neural networks is a major privacy concern. Haim et al. (2022) recently showed that it is possible to reconstruct training samples from neural network binary classifiers, based on theoretical results about the implicit bias of gradient methods. In this work, we present several improvements and new insig

Chang-Lin Xiang, Gao-Feng Zheng

This paper is a continuation of the recent work of Guo-Xiang-Zheng \cite{Guo-Xiang-Zheng-2021-CV}. We deduce sharp Morrey regularity theory for weak solutions to the fourth order nonhomogeneous Lamm-Rivi\`ere equation \begin{equation*} \Delta^{2}u=\Delta(V\nabla u)+div(w\nabla u)+(\nabla\omega+F)\cdot\nabla u+f\qquad\text{in }B^{4},\end{equation*} under smal

Vipul Harsh, Tong Meng, Kapil Agrawal, P. Brighten Godfrey

Inferring the root cause of failures among thousands of components in a data center network is challenging, especially for "gray" failures that are not reported directly by switches. Faults can be localized through end-to-end measurements, but past localization schemes are either too slow for large-scale networks or sacrifice accuracy. We describe Flock, a n

Weijia Wu, Yuzhong Zhao, Zhuang Li, Jiahong Li

Most existing cross-modal language-to-video retrieval (VR) research focuses on single-modal input from video, i.e., visual representation, while the text is omnipresent in human environments and frequently critical to understand video. To study how to retrieve video with both modal inputs, i.e., visual and text semantic representations, we first introduce a

Giusy Monzillo, Tim Penttila, Alessandro Siciliano

Brown et al. provide a representation of a spread of the Tits quadrangle $T_2(\mathcal O)$, $\mathcal O$ an oval of $\mathrm PG(2,q)$, $q$ even, in terms of a certain family of $q$ ovals of $\mathrm PG(2,q)$. By combining this representation with the Vandendriessche classification of hyperovals in $\mathrm PG(2,64)$ and the classification of flocks of the qu

Jean-Marie Malherbe, Thierry Roudier

We summarize in this paper the spectro-polarimetric methods used at the Pic du Midi Turret Dome in spectroscopic or imagery mode. The polarimeters and spectrograph allow the cartography of solar magnetic fields at high spatial resolution through the Zeeman effect or measurements of the unresolved turbulent magnetic fields in the quiet Sun through the Hanle e

Julian Sester

A convex duality result for martingale optimal transport problems with two marginals was established in Beiglb\"ock et al. (2013). In this paper we provide a generalization of this result to the multi-period setting.

Fuyan Ma, Bin Sun, Shutao Li

Previous methods for dynamic facial expression recognition (DFER) in the wild are mainly based on Convolutional Neural Networks (CNNs), whose local operations ignore the long-range dependencies in videos. Transformer-based methods for DFER can achieve better performances but result in higher FLOPs and computational costs. To solve these problems, the local-g

Vladislav Chertenkov, Evgeni Burovski, Lev Shchur

We analyze the problem of supervised learning of ferromagnetic phase transitions from the statistical physics perspective. We consider two systems in two universality classes, the two-dimensional Ising model and two-dimensional Baxter-Wu model, and perform careful finite-size analysis of the results of the supervised learning of the phases of each model. We

Pablo M. Candela, Valentina De Romeri, Dimitrios K. Papoulias

We consider the possible production of a new MeV-scale fermion at the COHERENT experiment. The new fermion, belonging to a dark sector, can be produced through the up-scattering process of neutrinos off the nuclei and the electrons of the detector material, via the exchange of a light vector or scalar mediator. We perform a detailed statistical analysis of t

Bryce Allen Bagley, Navin Khoshnan, Claudia K Petritsch

As Evolutionary Dynamics moves from the realm of theory into application, algorithms are needed to move beyond simple models. Yet few such methods exist in the literature. Ecological and physiological factors are known to be central to evolution in realistic contexts, but accounting for them generally renders problems intractable to existing methods. We intr

Philippe Carvalho, Alexandre Durupt, Yves Grandvalet

The field of industrial defect detection using machine learning and deep learning is a subject of active research. Datasets, also called benchmarks, are used to compare and assess research results. There is a number of datasets in industrial visual inspection, of varying quality. Thus, it is a difficult task to determine which dataset to use. Generally speak

Xueao Li, Fan Zhang, Xuefei Wang, Weiwei Gao

The recent experimental fabrication of monolayer and few-layer C60 polymers paves the way for synthesizing two-dimensional cluster-assembled materials. Compared to atoms with the SO(3) symmetry, clusters as superatoms (e.g., C60) have an additional rotational degree of freedom, greatly enriching the phase spaces of superatom-assembled materials. Using first-

Cécile Huez, Séverine Renaudineau, Florence Volatron, Anna Proust

Polyoxometalates are nanoscale molecular oxides with promising properties that are currently explored for molecule-based memory devices. In this work, we synthesize a series of Preyssler polyoxometalates (POMs), (Na-P5W30O110)14-,stabilized with four different counterions, H+, K+, NH4+ and tetrabutylammonium (TBA+), and we study the electron transport proper

Hamid R. Bakhtiarizadeh, Hanif Golchin

In this paper, we investigate the asymptotically Anti de Sitter solutions of rotating black strings coupled to Born-Infeld and Modified Maxwell non-linear electrodynamics in the context of Einsteinian, Einsteinian cubic and Einsteinian quartic gravity. By studying the near-horizon behavior of solutions, we find the mass parameter, surface gravity and accordi