April 2024 arXiv papers — page 77

Laurie Williams, Sammy Migues, Jamie Boote, Ben Hutchison

The Proactive Software Supply Chain Risk Management Framework (P SSCRM) described in this document is designed to help you understand and plan a secure software supply chain risk management initiative. P SSCRM was created through a process of understanding and analyzing real world data from nine industry leading software supply chain risk management initiati

Yusuke Sakai, Mana Makinae, Hidetaka Kamigaito, Taro Watanabe

In Simultaneous Machine Translation (SiMT) systems, training with a simultaneous interpretation (SI) corpus is an effective method for achieving high-quality yet low-latency systems. However, it is very challenging to curate such a corpus due to limitations in the abilities of annotators, and hence, existing SI corpora are limited. Therefore, we propose a me

Andrei Alexandru, Claudio Bonanno, Massimo D'Elia, Ivan Horváth

We compute the renormalized Dirac spectral density in $N_f = 2+1$ QCD at physical quark masses, temperature $T = 230$ MeV and system size $L_s = 3.4$ fm. To that end, we perform a point-wise continuum limit of the staggered density in lattice QCD with staggered quarks. We find, for the first time, that a clear infrared structure (IR peak) emerges in the dens

Aditi Chakrabarty, Sanjoy Datta

One of the most striking features of non-Hermitian quasiperiodic systems with arbitrarily small asymmetry in the hopping amplitudes and open boundaries is the accumulation of all the bulk eigenstates at one of the edges of the system, termed in literature as the skin effect, below a critical strength of the potential. In this Letter, we uncover that a time-p

Ryan Piansky, Georgia Stinchfield, Alyssa Kody, Daniel K. Molzahn

Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This paper considers sizing, siting, and operating batteries in a power grid to maximize their benefits, including price arbitrage and load shed mitigation, during both normal operatio

Tristan Piater, Niklas Penzel, Gideon Stein, Joachim Denzler

A substantial body of research has focused on developing systems that assist medical professionals during labor-intensive early screening processes, many based on convolutional deep-learning architectures. Recently, multiple studies explored the application of so-called self-attention mechanisms in the vision domain. These studies often report empirical impr

Rahul Srinivasan, Marco Crisostomi, Roberto Trotta, Enrico Barausse

We propose a novel method ($floZ$), based on normalizing flows, to estimate the Bayesian evidence (and its numerical uncertainty) from a pre-existing set of samples drawn from the unnormalized posterior distribution. We validate it on distributions whose evidence is known analytically, up to 15 parameter space dimensions, and compare with two state-of-the-ar

Anna Shalova, André Schlichting, Mark Peletier

We study the limiting dynamics of a large class of noisy gradient descent systems in the overparameterized regime. In this regime the set of global minimizers of the loss is large, and when initialized in a neighbourhood of this zero-loss set a noisy gradient descent algorithm slowly evolves along this set. In some cases this slow evolution has been related

Niklas Penzel, Gideon Stein, Joachim Denzler

Deep models trained on large amounts of data often incorporate implicit biases present during training time. If later such a bias is discovered during inference or deployment, it is often necessary to acquire new data and retrain the model. This behavior is especially problematic in critical areas such as autonomous driving or medical decision-making. In the

Yucheng Lin, Yuhan Xia, Yunfei Long

This study introduces a novel method for irony detection, applying Large Language Models (LLMs) with prompt-based learning to facilitate emotion-centric text augmentation. Traditional irony detection techniques typically fall short due to their reliance on static linguistic features and predefined knowledge bases, often overlooking the nuanced emotional dime

Lingxiao Li, Raaz Dwivedi, Lester Mackey

Modern compression methods can summarize a target distribution $\mathbb{P}$ more succinctly than i.i.d. sampling but require access to a low-bias input sequence like a Markov chain converging quickly to $\mathbb{P}$. We introduce a new suite of compression methods suitable for compression with biased input sequences. Given $n$ points targeting the wrong dist

Simeon Junker, Sina Zarrieß

Scene context is well known to facilitate humans' perception of visible objects. In this paper, we investigate the role of context in Referring Expression Generation (REG) for objects in images, where existing research has often focused on distractor contexts that exert pressure on the generator. We take a new perspective on scene context in REG and hypothes

Susan E. Johnston

Meiotic recombination is a fundamental feature of sexually reproducing species. It is often required for proper chromosome segregation and plays important role in adaptation and the maintenance of genetic diversity. The molecular mechanisms of recombination are remarkably conserved across eukaryotes, yet meiotic genes and proteins show substantial variation

Alexey Gorelov

In this paper, we study conditions for the existence of an embedding $\widetilde{f} \colon P \to Q \times \mathbb{R}$ such that $f = \mathrm{pr}_Q \circ \widetilde{f}$, where $f \colon P \to Q$ is a piecewise linear map between polyhedra. Our focus is on non-degenerate maps between graphs, where non-degeneracy means that the preimages of points are finite se

Fumio Hiroshima, Noriaki Teranishi

A conjugate operator $T$ of one-dimensional harmonic oscillator $N$ is defined by an operator satisfying canonical commutation relation $[N,T]=-i\one$ on some domain but not necessarily a dense one. Examples of conjugate operators include the angle operator $\TA$ and the Galapon operator $\TG$. Let $\sT$ denote a set of conjugate operators of $N$ of the form

Yona Falinie A. Gaus, Neelanjan Bhowmik, Brian K. S. Isaac-Medina, Toby P. Breckon

The Segment Anything Model (SAM) is a deep neural network foundational model designed to perform instance segmentation which has gained significant popularity given its zero-shot segmentation ability. SAM operates by generating masks based on various input prompts such as text, bounding boxes, points, or masks, introducing a novel methodology to overcome the

Doghonay Arjmand, Victor Martinez Calzada

The demagnetization field in micromagnetism is given as the gradient of a potential which solves a partial differential equation (PDE) posed in R^d. In its most general form, this PDE is supplied with continuity condition on the boundary of the magnetic domain and the equation includes a discontinuity in the gradient of the potential over the boundary. Typic

Nicholas Harris, Anand Butani, Syed Hashmy

Embedding models are crucial for various natural language processing tasks but can be limited by factors such as limited vocabulary, lack of context, and grammatical errors. This paper proposes a novel approach to improve embedding performance by leveraging large language models (LLMs) to enrich and rewrite input text before the embedding process. By utilizi

Jose Florido, He Wang, Amirul Khan, Peter K. Jimack

Physics-informed neural networks (PINNs) provide a means of obtaining approximate solutions of partial differential equations and systems through the minimisation of an objective function which includes the evaluation of a residual function at a set of collocation points within the domain. The quality of a PINNs solution depends upon numerous parameters, inc

Chenxi Wang, Hongjie Fang, Hao-Shu Fang, Cewu Lu

Precise robot manipulations require rich spatial information in imitation learning. Image-based policies model object positions from fixed cameras, which are sensitive to camera view changes. Policies utilizing 3D point clouds usually predict keyframes rather than continuous actions, posing difficulty in dynamic and contact-rich scenarios. To utilize 3D perc

Richard I. Anderson, Giordano Viviani, Shreeya S. Shetye, Nami Mowlavi

This first VELOCE data release comprises 18,225 high-precision RV measurements of 258 bona fide classical Cepheids on both hemispheres collected mainly between 2010 and 2022, alongside 1161 additional observations of 164 other stars. The median per-observation RV uncertainty is 0.037 km/s, and some reach 0.002 km/s. Non-variable standard stars characterize R

Mary Rees

Two conjectures are presented. The first, Conjecture 1, is that the pushforward of a geometric distribution on the integers under $n$ Collatz iterates, modulo $2^p$, is usefully close to uniform distribution on the integers modulo $2^p$, if $p/n$ is small enough. Conjecture 2 is that the density is bounded from zero for the incidence of both $0$ and $1$ for

David Restrepo, Chenwei Wu, Constanza Vásquez-Venegas, Luis Filipe Nakayama

In the big data era, integrating diverse data modalities poses significant challenges, particularly in complex fields like healthcare. This paper introduces a new process model for multimodal Data Fusion for Data Mining, integrating embeddings and the Cross-Industry Standard Process for Data Mining with the existing Data Fusion Information Group model. Our m

Thomas A. Courtade, Max Fathi

In a recent work, Klartag gave an improved version of Lichnerowicz' spectral gap bound for uniformly log-concave measures, which improves on the classical estimate by taking into account the covariance matrix. We analyze the equality cases in Klartag's bound, showing that it can be further improved whenever the measure has no Gaussian factor. Additionally, w

Jeongbhin Seo, Fan Guo, Xiaocan Li, Hui Li

Magnetic reconnection regions in space and astrophysics are known as active particle acceleration sites. There is ample evidence showing that energetic particles can take a substantial amount of converted energy during magnetic reconnection. However, there has been a lack of studies understanding the backreaction of energetic particles at magnetohydrodynamic

Arnab Bhattacharya, Mohammad Rezwan Habib, Afsar Ahmed, Biswarup Satpati

Realization of noncentrosymmetric magnetic Weyl metals is expected to exhibit anomalous transport properties stemming from the interplay of unusual bulk electronic topology and magnetism. Here, we present spin-valve-like magnetoresistance at room temperature in ferrimagneticWeyl metal Mn$_2$PdSn that crystallizes in the inverse Heusler structure. Anomalous m

Jiabao Ji, Bairu Hou, Zhen Zhang, Guanhua Zhang

Although large language models (LLMs) have achieved significant success, their vulnerability to adversarial perturbations, including recent jailbreak attacks, has raised considerable concerns. However, the increasing size of these models and their limited access make improving their robustness a challenging task. Among various defense strategies, randomized

Yuanqin He, Yan Kang, Lixin Fan, Qiang Yang

Federated Learning (FL) has emerged as a promising solution for collaborative training of large language models (LLMs). However, the integration of LLMs into FL introduces new challenges, particularly concerning the evaluation of LLMs. Traditional evaluation methods that rely on labeled test sets and similarity-based metrics cover only a subset of the accept

Shreya Shankar, J. D. Zamfirescu-Pereira, Björn Hartmann, Aditya G. Parameswaran

Due to the cumbersome nature of human evaluation and limitations of code-based evaluation, Large Language Models (LLMs) are increasingly being used to assist humans in evaluating LLM outputs. Yet LLM-generated evaluators simply inherit all the problems of the LLMs they evaluate, requiring further human validation. We present a mixed-initiative approach to ``

Jordan Hobbs, Calum J. Gibb, Richard. J. Mandle

Polar liquid crystals possess three dimensional orientational order coupled with unidirectional electric polarity, yielding fluid ferroelectrics. Such polar phases are generated by rod-like molecules with large electric dipole moments. 2,5-Disubstituted 1,3-dioxane is commonly employed as a polar motif in said systems, and here we show this to suffer from th

Wei-Bo Kao, Yanxia Zhang, Xue-Bing Wu

Broad Absorption Line Quasars (BALQSOs) displaying distinct blue-shifted broad absorption lines. These serve as invaluable probes for unraveling the intricate structure and evolution of quasars, shedding light on the profound influence exerted by supermassive black holes on galaxy formation. The proliferation of large-scale spectroscopic surveys such as LAMO

Victoria Gitman, Jonathan Osinski

Galeotti, Khomskii and V\"a\"an\"aanen recently introduced the notion of the upward L\"owenheim-Skolem-Tarski number for a logic, strengthening the classical notion of a Hanf number. A cardinal $\kappa$ is the \emph{upward L\"owenheim-Skolem-Tarski number} (ULST) of a logic $\mathcal L$ if it is the least cardinal with the property that whenever $M$ is a mod

Sacha Cerf, Johannes Lengler

Our theoretical understanding of crossover is limited by our ability to analyze how population diversity evolves. In this study, we provide one of the first rigorous analyses of population diversity and optimization time in a setting where large diversity and large population sizes are required to speed up progress. We give a formal and general criterion whi

Sheikh Waqas Akhtar

Physics-integrated generative modeling is a class of hybrid or grey-box modeling in which we augment the the data-driven model with the physics knowledge governing the data distribution. The use of physics knowledge allows the generative model to produce output in a controlled way, so that the output, by construction, complies with the physical laws. It impa

Shan-Zhong Li, Zhi Li

By Avila's global theory, we analytically reveal that the non-Hermitian mobility edge will take on a ring structure in the complex plane, which we name as "mobility ring". The universality of mobility ring has been checked and supported by the Hermitian limit, $PT$-symmetry protection and without $PT$-symmetry cases. Further, we study the evolution of mobili

Karim Adiprasito, Zuzana Patáková

We prove a generalization of Istvan F\'ary's celebrated theorem to higher dimension.

Olga Oshmarina, Andrei Vesnin

Let $K_n$ be a complete graph with $n$ vertices. An embedding of $K_n$ in $S^3$ is called a spatial $K_n$-graph. Knots in a spatial $K_n$-graph corresponding to simple cycles of $K_n$ are said to be constituent knots. We consider the case $n=4$. The boundary of an oriented band surface with zero Seifert form, constructed for a spatial $K_4$, is a four-compon

Mathis Fricke, Clara Bernklau, Elisabeth Diehl, Joël De Coninck

In this note, we revisit the problem of the pressure-driven transport of a meniscus through a narrow cylindrical capillary or pore. This generic process finds many applications in science and technology. As it is known that Direct Numerical Simulations of moving contact line problems are highly demanding in terms of computational costs, simplified models in

Diane Guignard, Olga Mula

This paper is concerned with model order reduction of parametric Partial Differential Equations (PDEs) using tree-based library approximations. Classical approaches are formulated for PDEs on Hilbert spaces and involve one single linear space to approximate the set of PDE solutions. Here, we develop reduced models relying on a collection of linear or nonline

Luca Ganassali

This thesis studies the graph alignment problem, the noisy version of the graph isomorphism problem, which aims to find a matching between the nodes of two graphs which preserves most of the edges. Focusing on the planted version where the graphs are random, we are interested in understanding the fundamental information-theoretical limits for this problem, a

Astik Srivastava, S. Indu, Richa Sharma

This paper presents the design, implementation, and flight test results of linear quadratic integral regulator (LQRi) based attitude control for a quadcopter UAV. We present the derivation of the mathematical model for the kinematics and dynamics of the UAV, along with the linearized state space representation of the system about hover conditions. LQR and LQ

Israel A. Laurensi, Alceu de Souza Britto, Jean Paul Barddal, Alessandro Lameiras Koerich

Facial expression recognition is a pivotal component in machine learning, facilitating various applications. However, convolutional neural networks (CNNs) are often plagued by catastrophic forgetting, impeding their adaptability. The proposed method, emotion-centered generative replay (ECgr), tackles this challenge by integrating synthetic images from genera

Michelle S. Lam, Janice Teoh, James Landay, Jeffrey Heer

Data analysts have long sought to turn unstructured text data into meaningful concepts. Though common, topic modeling and clustering focus on lower-level keywords and require significant interpretative work. We introduce concept induction, a computational process that instead produces high-level concepts, defined by explicit inclusion criteria, from unstruct

Mohammed Shaiqur Rahman, Ibne Farabi Shihab, Lynna Chu, Anuj Sharma

In this study, we introduce DeepLocalization, an innovative framework devised for the real-time localization of actions tailored explicitly for monitoring driver behavior. Utilizing the power of advanced deep learning methodologies, our objective is to tackle the critical issue of distracted driving-a significant factor contributing to road accidents. Our st

Gautham Vinod, Jiangpeng He, Zeman Shao, Fengqing Zhu

Image-based methods to analyze food images have alleviated the user burden and biases associated with traditional methods. However, accurate portion estimation remains a major challenge due to the loss of 3D information in the 2D representation of foods captured by smartphone cameras or wearable devices. In this paper, we propose a new framework to estimate

Jilan Samiuddin, Benoit Boulet, Di Wu

The autonomous driving industry is expected to grow by over 20 times in the coming decade and, thus, motivate researchers to delve into it. The primary focus of their research is to ensure safety, comfort, and efficiency. An autonomous vehicle has several modules responsible for one or more of the aforementioned items. Among these modules, the trajectory pla

Maryna Ishchenko, Dana A. Kovaleva, Peter Berczik, Nina V. Kharchenko

In a previous paper using Gaia DR2 data, we demonstrated that the two closely situated open clusters Collinder 135 and UBC 7 might have formed together about 50 Myr ago. In this work, we performed star-by-star dynamical modelling of the evolution of the open clusters Collinder 135 and UBC 7 from their supposed initial state to their present-day state, reprod

Hasan Emre Baysal, Tzu-Yi Yu, Viktor Naenen, Stijn De Smedt

The next generation of soft electronics will expand to the third dimension. This will require the integration of mechanically-compliant three-dimensional functional structures with stretchable materials. This study demonstrates omnidirectional direct ink writing (DIW) of Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) aerogels with tunable

Ye Tian, Baolin Peng, Linfeng Song, Lifeng Jin

Despite the impressive capabilities of Large Language Models (LLMs) on various tasks, they still struggle with scenarios that involves complex reasoning and planning. Recent work proposed advanced prompting techniques and the necessity of fine-tuning with high-quality data to augment LLMs' reasoning abilities. However, these approaches are inherently constra

Matthias Schwab, Agnes Mayr, Markus Haltmeier

The recent emergence of deep learning has led to a great deal of work on designing supervised deep semantic segmentation algorithms. As in many tasks sufficient pixel-level labels are very difficult to obtain, we propose a method which combines a Gaussian mixture model (GMM) with unsupervised deep learning techniques. In the standard GMM the pixel values wit

Luciana Trinkaus Menon, Luiz Carlos Ribeiro Neduziak, Jean Paul Barddal, Alessandro Lameiras Koerich

The study of human emotions, traditionally a cornerstone in fields like psychology and neuroscience, has been profoundly impacted by the advent of artificial intelligence (AI). Multiple channels, such as speech (voice) and facial expressions (image), are crucial in understanding human emotions. However, AI's journey in multimodal emotion recognition (MER) is

Sagnik Chatterjee, Tamaghna Chowdhury, Pablo Díaz Núñez, Nicholas Kay

Transition metal dichalcogenide (TMD) nanoscrolls (NS) exhibit significant photoluminescence (PL) signals despite their multilayer structure, which cannot be explained by the strained multilayer description of NS. Here, we investigate the interlayer interactions in NS to address this discrepancy. The reduction of interlayer interactions in NS is attributed t

Ronen Brilleslijper, Oliver Fabert

In $n$-dimensional classical field theory one studies maps from $n$-dimensional manifolds in such a way that classical mechanics is recovered for $n=1$. In previous papers we have shown that the standard polysymplectic framework in which field theory is described, is not suitable for variational techniques. In this paper, we introduce for $n=2$ a Lagrange-Ha

Vincent Lam, Daniele Oriti

We discuss the challenges that the standard (Humean and non-Humean) accounts of laws face within the framework of quantum gravity where space and time may not be fundamental. This paper identifies core (meta)physical features that cut across a number of quantum gravity approaches and formalisms and that provide seeds for articulating updated conceptions that

Alexander P. Fellows, Álvaro Díaz Duque, Vasileios Balos, Louis Lehmann

The air-water interface is a highly prevalent phase boundary with a far-reaching impact on natural and industrial processes. Water molecules behave differently at the interface compared to the bulk, exhibiting anisotropic orientational distributions, reduced intermolecular connectivity in the hydrogen bond network, and significantly slower dynamics. Despite

Andrei-Timotei Ardelean, Tim Weyrich

Anomaly detection and localization in images is a growing field in computer vision. In this area, a seemingly understudied problem is anomaly clustering, i.e., identifying and grouping different types of anomalies in a fully unsupervised manner. In this work, we propose a novel method for clustering anomalies in largely stationary images (textures) in a blin

Olga A. Ryazanova, Igor M. Voloshin, Igor Ya. Dubey, Larysa V. Dubey

The porphyrins are macrocyclic compounds widely used as photosensitizers in anticancer photodynamic therapy. The binding of a tricationic meso-tris(N-methylpyridinium)-porphyrin, $TMPyP^{3+}$, to poly(A)-poly(U) polynucleotide has been studied in neutral buffered solution, pH6.9, of low and near-physiological ionic strength in a wide range of molar phosphate

Khaish Singh Chadha, Prabhat Kumar

This paper introduces an adaptive convolutional neural network (CNN) architecture capable of automating various topology optimization (TO) problems with diverse underlying physics. The proposed architecture has an encoder-decoder-type structure with dense layers added at the bottleneck region to capture complex geometrical features. The network is trained us

Michał Bobula

We construct a (quantum mechanically) modified model for the Oppenheimer-Snyder collapse scenario where the exterior of the collapsing dust ball is a Hayward black hole spacetime and the interior is a dust Friedmann-Robertson-Walker cosmology. This interior cosmology is entirely determined by the junction conditions with the exterior black hole. It turns out

Mengna Zhu, Zijie Xu, Kaisheng Zeng, Kaiming Xiao

Extracting structured event knowledge, including event triggers and corresponding arguments, from military texts is fundamental to many applications, such as intelligence analysis and decision assistance. However, event extraction in the military field faces the data scarcity problem, which impedes the research of event extraction models in this domain. To a

Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use

Lukas Rottkamp, Matthias Schubert

Accurate spatio-temporal information about the current situation is crucial for smart city applications such as modern routing algorithms. Often, this information describes the state of stationary resources, e.g. the availability of parking bays, charging stations or the amount of people waiting for a vehicle to pick them up near a given location. To exploit

Alexander J. Mustill, Melvyn B. Davies, Matthew A. Kenworthy

Several stars show deep transits consistent with discs of roughly 1 Solar radius seen at moderate inclinations, likely surrounding planets on eccentric orbits. We show that this configuration arises naturally as a result of planet-planet scattering when the planets possess satellite systems. Planet-planet scattering explains the orbital eccentricities of the

Roger Pros, Jordi Vitrià

In recent years, there has been a growing interest in using machine learning techniques for the estimation of treatment effects. Most of the best-performing methods rely on representation learning strategies that encourage shared behavior among potential outcomes to increase the precision of treatment effect estimates. In this paper we discuss and classify t

Irene Gonzálvez, Alfredo Miranda, Julio D. Rossi

In this paper we study the two membranes problem for operators given in terms of a mean value formula on a regular tree. We show existence of solutions under adequate conditions on the boundary data and the involved source terms. We also show that, when the boundary data are strictly separated, the coincidence set is separated from the boundary and thus it c

Petru Neague, Marcel Gregoriadis, Johan Pouwelse

This study introduces De-DSI, a novel framework that fuses large language models (LLMs) with genuine decentralization for information retrieval, particularly employing the differentiable search index (DSI) concept in a decentralized setting. Focused on efficiently connecting novel user queries with document identifiers without direct document access, De-DSI

Ivo S. Mihov, Nikolay V. Vitanov

We present a study of the dynamics of a qubit driven by a pulsed field of finite duration. The pulse shape starts and ends linearly in time. The most typical example of such a shape is the sine function between two of its nodes, but several other pulse shapes are also studied. All of them present smooth alternatives to the commonly used rectangular pulse sha

Xianyu Chen, Ming Jiang, Qi Zhao

Understanding how attention varies across individuals has significant scientific and societal impacts. However, existing visual scanpath models treat attention uniformly, neglecting individual differences. To bridge this gap, this paper focuses on individualized scanpath prediction (ISP), a new attention modeling task that aims to accurately predict how diff

Tadahisa Funaki, Chenlin Gu, Han Wang

For the non-gradient exclusion process, we prove the quantitative homogenization of the diffusion matrix and the conductivity by local functions. The proof relies on the renormalization approach developed by Armstrong, Kuusi, Mourrat, and Smart, while the new challenge here is the hard core constraint of particle number on every site. Therefore, a coarse-gra

Jan Kalinowski, Wojciech Kotlarski

In view of lack of the direct experimental evidence for a Beyond the Standard Model (BSM) physics, accommodating a SM-like Higgs boson is on the most important constraints that a BSM model must fulfill. Already for some time the FlexibleSUSY spectrum generator generator allowed for a reliable prediction of masses and decay patterns of the BSM Higgs boson in

Felix Buchele, Patric Müller, Michael Blank, Thorsten Pöschel

We describe a method for modeling the geometry of porous materials. The approach enables the independent selection of crucial parameters, including porosity, pore size distribution, pore shape, and connectivity. Consequently, it can effectively model a wide range of porous systems. Due to the diverse and systematic variation possibilities, the method is suit

José Manuel Fernández Vilaboa, Ramón González Rodríguez, Brais Ramos Pérez, Ana Belén Rodríguez Raposo

This paper is devoted to the study of Hopf braces projections in a monoidal setting. Given a cocommutative Hopf brace ${\mathbb H}$ in a strict symmetric monoidal category ${\sf C}$, we define the braided monoidal category of left Yetter-Drinfeld modules over ${\mathbb H}$. For a Hopf brace ${\mathbb A}$ in this category, we introduce the concept of bosoniza

Sergey A. Matveev, Matvey Smirnov

In this work we provide theoretical estimates for the ranks of the power functions $f(k) = k^{-\alpha}$, $\alpha>1$ in the quantized tensor train (QTT) format for $k = 1, 2, 3, \ldots, 2^{d}$. Such functions and their several generalizations (e.~g. $f(k) = k^{-\alpha} \cdot e^{-\lambda k}, \lambda > 0$) play an important role in studies of the asymptotic sol

Jaume Baixeries, Amedeo Napoli

In this paper we revisit the problem of computing the closure of a set of attributes given a basis of dependencies or implications. This problem is of main interest in logics, in the relational database model, in lattice theory, and in Formal Concept Analysis as well. A basis of dependencies may have different characteristics, among which being ``minimal'',

Xiang Li, Shunpan Liang, Yu Lei, Chen Li

Medication recommendation systems are developed to recommend suitable medications tailored to specific patient. Previous researches primarily focus on learning medication representations, which have yielded notable advances. However, these methods are limited to capturing personalized patient representations due to the following primary limitations: (i) unab

C. E. Woodward, G. Shaw, S. Starrfield, A. Evans

A near-infrared spectrum of nova V1716 Scorpii (PNV J17224490-4137160), a recent bright (V_max = 7.3 mag), Fermi-LAT detected gamma-ray source, was modeled using the photoionization code CLOUDY. Abundances were estimated for He, C, N, O, Si, Al, Mg, Fe, Ne, S, Ca, and P. Notably, P (a factor of 120) and N (a factor of 248) are highly overabundant. It was nec

João Faccin, Ingrid Nunes, Abdelwahab Hamou-Lhadj

Many modern software systems are built as a set of autonomous software components (also called agents) that collaborate with each other and are situated in an environment. To keep these multiagent systems operational under abnormal circumstances, it is crucial to make them resilient. Existing solutions are often centralised and rely on information manually p

Gwyn Bellamy, Alastair Craw, Travis Schedler

We study GIT quotients $X_\theta=V\!/\!\!/\!_\theta G$ whose linearisation map defines an isomorphism between the group of characters of $G$ and the Picard group of $X_\theta$ modulo torsion. Our main result establishes that the Cox ring of $X_\theta$ is isomorphic to the semi-invariant ring of the $\theta$-stable locus in $V$. This applies to quiver flag va

Jie Wang, Tao Ji, Yuanbin Wu, Hang Yan

Generalizing to longer sentences is important for recent Transformer-based language models. Besides algorithms manipulating explicit position features, the success of Transformers without position encodings (NoPE) provides a new way to overcome the challenge. In this paper, we study the length generalization property of NoPE. We find that although NoPE can e

Zelin Zhang, Songbai Chen, Jiliang Jing

We adopt general relativistic ray-tracing (GRRT) schemes to study images of Kerr-MOG black holes surrounded by geometrically thick magnetized equilibrium tori, which belong to steady-state solutions of thick accretion disks within the framework of general relativistic magnetohydrodynamics (GRMHD). The black hole possesses an extra dimensionless MOG parameter

Sergey Mironov, Andrey Morozov

In this paper we discuss how to use arborescent knots to construct entangled multi-qubit states. We show that Bell-states, GHZ-states and cluster states can be constructed from such knots. The latter are particularly interesting since they form a base for the measurement-based quantum computers.

Damian Sercombe

Let $G$ be an affine algebraic group scheme over a field $k$. We show there exists a unipotent normal subgroup of $G$ which contains all other such subgroups; we call it the restricted unipotent radical $\mathrm{Rad}_u(G)$ of $G$. We investigate some properties of $\mathrm{Rad}_u(G)$, and study those $G$ for which $\mathrm{Rad}_u(G)$ is trivial. In particula

Wentao Zhang, Shaohang Xu, Gewei Zuo, Bolin Li

Inspired by sled-pulling dogs in transportation, we present a cable-trailer integrated with a quadruped robot system. The motion planning of this system faces challenges due to the interactions between the cable's state transitions, the trailer's nonholonomic constraints, and the system's underactuation. To address these challenges, we first develop a hybrid

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Saad Hamid

Parallelisation in Bayesian optimisation is a common strategy but faces several challenges: the need for flexibility in acquisition functions and kernel choices, flexibility dealing with discrete and continuous variables simultaneously, model misspecification, and lastly fast massive parallelisation. To address these challenges, we introduce a versatile and

Xichen Chao, Katherine Skipper, C. Patrick Royall, Silke Henkes

We study an intriguing new type of self-assembled active colloidal polymer system in 3D. It is obtained from a suspension of Janus particles in an electric field that induces parallel dipoles in the particles as well as self-propulsion in the plane perpendicular to the field. At low packing fractions, in experiment, the particles self-assemble into 3D column

Weiqiang Lyu, Huan Tian, Zhenwei Fu, Lingjie Zhang

Broadband microwave waveforms with programmable chirp shapes are captivating in numerous practical applications. Compared with electronic technology, photonic-assisted solutions exhibit excellent performance in bandwidth and flexibility, but still suffer from complex architecture and requirement of high-speed electronics. Besides, rapid manipulation of chirp

Abolfazl Jafari

We treat the Christoffel coefficients as operators and introduce new mappings for quaternionic products to connect with the theory of electrodynamics in general spacetime. By utilizing the directional operator of the covariant derivative, we generalize the quaternionic mechanism to the theory of electrodynamics. We demonstrate that the Einstein equation perm

Han Fang, Xianghao Zang, Chao Ban, Zerun Feng

Text-video retrieval aims to find the most relevant cross-modal samples for a given query. Recent methods focus on modeling the whole spatial-temporal relations. However, since video clips contain more diverse content than captions, the model aligning these asymmetric video-text pairs has a high risk of retrieving many false positive results. In this paper,

Paul Hofman, Yusuf Sale, Eyke Hüllermeier

Uncertainty representation and quantification are paramount in machine learning and constitute an important prerequisite for safety-critical applications. In this paper, we propose novel measures for the quantification of aleatoric and epistemic uncertainty based on proper scoring rules, which are loss functions with the meaningful property that they incenti

Edmund Crawley, Alexandros Theloudis

This article reviews the economics literature of, primarily, the last 20 years, that studies the link between income shocks and consumption fluctuations at the household level. We identify three broad approaches through which researchers estimate the consumption response to income shocks: 1.) structural methods in which a fully or partially specified model h

Hadrien Hendrikx

Mirror Descent is a popular algorithm, that extends Gradients Descent (GD) beyond the Euclidean geometry. One of its benefits is to enable strong convergence guarantees through smooth-like analyses, even for objectives with exploding or vanishing curvature. This is achieved through the introduction of the notion of relative smoothness, which holds in many of

Arijit Manna, Sabyasachi Pal

Amino acids are essential for the synthesis of protein. Amino acids contain both amine (R$-$NH$_{2}$) and carboxylic acid (R$-$COOH) functional groups, which help to understand the possible formation mechanism of life in the universe. Among the 20 types of amino acids, glycine (NH$_{2}$CH$_{2}$COOH) is known as the simplest non-essential amino acid. In the l

Vikash Pandey, Dhrubaditya Mitra

From the perspective of physical properties, the cell membrane is an exotic two-dimensional material that has a dual nature: it exhibits characteristics of fluids, i.e., lipid molecules show lateral diffusion, while also demonstrating properties of solids, evidenced by a non-zero shear modulus. We construct a model for such a $\textit{semi-solid}$ $\textit{m

Jin Gao, Shubo Lin, Shaoru Wang, Yutong Kou

Masked image modeling (MIM) pre-training for large-scale vision transformers (ViTs) has enabled promising downstream performance on top of the learned self-supervised ViT features. In this paper, we question if the \textit{extremely simple} lightweight ViTs' fine-tuning performance can also benefit from this pre-training paradigm, which is considerably less

Viktoria Ehm, Maolin Gao, Paul Roetzer, Marvin Eisenberger

Finding correspondences between 3D shapes is an important and long-standing problem in computer vision, graphics and beyond. A prominent challenge are partial-to-partial shape matching settings, which occur when the shapes to match are only observed incompletely (e.g. from 3D scanning). Although partial-to-partial matching is a highly relevant setting in pra

Yuying Man, Nian Li, Zhen Liu, Xiangyong Zeng

Substitution boxes (S-boxes) play a significant role in ensuring the resistance of block ciphers against various attacks. The Upper Boomerang Connectivity Table (UBCT), the Lower Boomerang Connectivity Table (LBCT) and the Double Boomerang Connectivity Table (DBCT) of a given S-box are crucial tools to analyze its security concerning specific attacks. Howeve

Virgil V. Baran, Jens Paaske

We theoretically explore the possibility of realizing the symmetry-protected topological Haldane phase of spin-1 chains in a tunable hybrid platform of superconducting islands (SIs) and quantum dots (QDs). Inspired by recent findings suggesting that an appropriately tuned QD-SI-QD block may behave as a robust spin-1 unit, we study the behavior of many such u

R. O. Kuzian, E. E. Krasovskii

Attosecond dynamics of electron reflection from a thin film is studied based on a one-dimensional jellium model. Following the Eisenbud-Wigner-Smith concept, the reflection time delay $\Delta\tau_{\rm R}$ is calculated as the energy derivative of the phase of the complex reflection amplitude $r$. For a purely elastic scattering by a jellium slab of a finite

Alessio Cesarano, Peter Gangl

In the context of the optimization of rotating electric machines, many different objective functions are of interest and considering this during the optimization is of crucial importance. While evolutionary algorithms can provide a Pareto front straightforwardly and are widely used in this context, derivative-based optimization algorithms can be computationa

Wen-Han Zhu, Rong-Xia Hao, Zhen He

Let $H$ be a fixed graph. A graph $G$ is called {\it $H$-saturated} if $H$ is not a subgraph of $G$ but the addition of any missing edge to $G$ results in an $H$-subgraph. The {\it saturation number} of $H$, denoted $sat(n,H)$, is the minimum number of edges over all $H$-saturated graphs of order $n$, and $Sat(n,H)$ denote the family of $H$-saturated graphs