November 2024 arXiv papers — page 171

Thomas Kahle, Seth Sullivant

For the distributions of finitely many binary random variables, we study the interaction of restrictions of the supports with conditional independence constraints. We prove a generalization of the Hammersley-Clifford theorem for distributions whose support is a natural distributive lattice: that is, any distribution which has natural lattice support and sati

Rui Xie, Yue Chen, Pierre Pinson

The growing uncertainty from renewable power and electricity demand brings significant challenges to unit commitment (UC). While various advanced forecasting and optimization methods have been developed to predict better and address this uncertainty, most previous studies treat forecasting and optimization as separate tasks. This separation can lead to subop

Alicia Guo, Shreya Sathyanarayanan, Leijie Wang, Jeffrey Heer

Creative writing is a deeply human craft, yet AI systems using large language models (LLMs) offer the automation of significant parts of the writing process. So why do some creative writers choose to use AI? Through interviews and observed writing sessions with 18 creative writers who already use AI regularly in their writing practice, we find that creative

Mahendra K. Verma, Rodion Stepanov, Alexandre Delache

In this paper, using \textit{hydrodynamic entropy} we quantify the multiscale disorder in Euler and hydrodynamic turbulence. These examples illustrate that the hydrodynamic entropy is not extensive because it is not proportional to the system size. Consequently, we cannot add hydrodynamic and thermodynamic entropies, which measure disorder at macroscopic and

J. R. Pardo, C. De Breuck, D. Muders, J. González

Due to the importance of a reference atmospheric radiative transfer model for both planning and calibrating ground-based observations at millimetre and submillimetre wavelengths, we have undertaken a validation campaign consisting of acquiring atmospheric spectra under different weather conditions, in different diurnal moments and seasons, with the Atacama P

Anthony E. Pizzimenti, Umarkhon Rakhimov

The Harary reconstruction conjecture states that any graph with more than four edges can be uniquely reconstructed from its set of maximal edge-deleted subgraphs. In 1977, M\"uller verified the conjecture for graphs with $n$ vertices and $n \log_2(n)$ edges, improving on Lov\'as's bound of $\log(n^2-n)/4$. Here, we show that the reconstruction conjecture hol

Lin Htoo Zaw, Valerio Scarani

Tsirelson's precession protocol is a nonclassicality witness that can be defined for both discrete and continuous variable systems. Its original version involves measuring a precessing observable, like the quadrature of a harmonic oscillator or a component of angular momentum, along three equally-spaced angles. In this work, we characterise all three-angle v

Bárbara L. Miranda Marques, Alberto Rodríguez-Ardila, Marcos A. Fonseca-Faria, Swayamtrupta Panda

Gigahertz Peaked Spectrum (GPS) and Compact Steep Spectrum (CSS) sources are compact radio galaxies (RGs), with jets extending up to 20 kpc and ages <10^3 years. They are considered to evolve to Fanaroff-Riley RGs, but the real scenario to explain the compact sources remains unsolved. The young compact jets make GPS/CSS ideal for studying feedback in the nuc

Yiqun Liu, Ke Zhang, Yin Zhu

Ground reaction force (GRF) is the force exerted by the ground on a body in contact with it. GRF-based automatic disease detection (ADD) has become an emerging medical diagnosis method, which aims to learn and identify disease patterns corresponding to different gait pressures based on deep learning methods. Although existing ADD methods can save doctors tim

I. Doran, M. Beyer, F. Merkt

The structure of the low-lying rotational levels of the X$^+$ $ ^2 \Sigma_g ^+$ ($v^+=0$) vibronic ground state of para-H$_2^+$ has been determined by combining frequency-comb calibrated continuous-wave high-resolution laser spectroscopy of $n$f Rydberg series in the range of principal quantum number $n$ between 28 and 115 and Rydberg-series extrapolation us

Xunze Liu, Yifei Sun, Zhaorui Wang, Lizhao You

This paper investigates semantic communications between a transmitter and a receiver, where original data, such as videos of interest to the receiver, is stored at the transmitter. Although significant process has been made in semantic communications, a fundamental design problem is that the semantic information is extracted based on certain criteria at the

Ji-Guo Zhang, Yi-Fan Jiang, Ze-Wei Zhao, Jing-Zhao Qi

The Macquart relation and time-delay cosmography are now two promising ways to fast radio burst (FRB) cosmology. In this work, we propose a joint method that combines strongly lensed and unlensed FRBs for improving cosmological parameter estimation by using simulated FRB data from the future sensitive coherent all-sky monitor survey, which is expected to det

Kavin Kabilan, Swapnil Sen, Arun K Saha

The present study numerically investigates the two-dimensional mixed convective flow of air past a square cylinder placed at an angle of incidence $\alpha = 45^{\circ}$ to the free-stream. We perform direct numerical simulations (DNS) for a Reynolds number (Re) of 100, a range of Richardson numbers (Ri) between 0.0 and 1.0, and a Prandtl number (Pr) of 0.7.

Pablo Ochoa, Analía Silva, Federico Valverde

In this paper, we consider Dirichlet boundary value problem involving the anisotropic $p(x)$-Laplacian, where $p(x)= (p_1(x), ..., p_n(x))$, with $p_i(x)> 1$ in $\overline{\Omega}$. Using the topological degree constructed by Berkovits, we prove, under appropriate assumptions on the data, the existence of weak solutions for the given problem. An important co

Carlo Giunti, Konstantin Kouzakov, Yu-Feng Li, Alexander Studenikin

Neutrinos are neutral in the Standard Model, but they have tiny charge radii generated by radiative corrections. In theories Beyond the Standard Model, neutrinos can also have magnetic and electric moments and small electric charges (millicharges). We review the general theory of neutrino electromagnetic form factors, which reduce, for ultrarelativistic neut

Sayan Bhattacharya, Martín Costa, Ermiya Farokhnejad

In metric $k$-clustering, we are given as input a set of $n$ points in a general metric space, and we have to pick $k$ centers and cluster the input points around these chosen centers, so as to minimize an appropriate objective function. In recent years, significant effort has been devoted to the study of metric $k$-clustering problems in a dynamic setting,

Yiran Li, Dongming Liu

An in-house numerical model has been developed to study the temperature destratification induced by bubble plumes in reservoirs. The mean flow of the mixed fluid phase is solved using the Reynolds-Averaged Navier-Stokes Equations, while the bubble phase is calculated by employing the advection-diffusion equation of air concentration. The change of water temp

Yin Huang, Xurong Chen

Considering that the experimentally observed molecular states are significantly fewer than those predicted theoretically, and that these states are traditionally classified as lying below thresholds while several candidates are found above them, we propose to broaden the definition of molecular states to include those that exist just above the thresholds. Id

Mohammadreza Mohajer

In this thesis, we aim to develop p-adic analogs of known results for classical periods, focusing specifically on 1-motives. We establish an integration theory for 1-motives with good reductions, which generalizes the Colmez-Fontaine-Messing p-adic integration for abelian varieties with good reductions. We also compare the integration pairing with other pair

Sankar V, Anand Babu K, Deepak M, Poojitha Mallapu

Objective: To assess the antioxidant, wound healing, anti-ulcer, and anti-inflammatory properties of Jatropha maheshwari. Methods: Jatropha maheshwari was collected from Kanyakumari district and authenticated. Ethanol was used for continuous hot percolation extraction of the plant. Antioxidant activity was evaluated using DPPH and ABTS assays. The wound heal

James Bono, Justin Grana, Alec Xu

We measure the association between generative AI (GAI) tool adoption and security operations center productivity. We find that GAI adoption is associated with a 30.13% reduction in security incident mean time to resolution. This result is robust to several modeling decisions. While unobserved confounders inhibit causal identification, this result is among th

Ting-Chun Lin, Hsin-Po Wang, Min-Hsiu Hsieh

A self-correcting quantum memory is a type of quantum error correcting code that can correct errors passively through cooling. A major open question in the field is whether self-correcting quantum memories can exist in 3D. In this work, we propose two candidate constructions for 3D self-correcting quantum memories. The first construction is an extension of H

Mads Svanborg Peters, Mads Juul Ahlebæk, Mads Toudal Frandsen, Bjarke Jørgensen

In this paper, a recently developed snapshot hyperspectral imaging (HSI) system based on Computed Tomography Imaging Spectroscopy (CTIS) is utilized to determine Brix and pH values in Sheegene 20 table grapes through Partial Least Squares Regression (PLSR) modeling. The performance of the CTIS system is compared with that of a state-of-the-art line scan HSI

Enrico Marco Zucchelli, Erwin Mooij

Aerocapture leverages atmospheric drag to convert a spacecraft's hyperbolic trajectory into a bound orbit. For some aerocapture missions, heating due to the radiation of high temperature gases in the shock-layer can be much larger than the heat due to convection. This paper provides analytical proof and numerical validation that radiative heat load is minimi

Hongsong Feng, Jeffrey Y. Zhao, Guo-Wei Wei

Protein flexibility is crucial for understanding protein structures, functions, and dynamics, and it can be measured through experimental methods such as X-ray crystallography. Theoretical approaches have also been developed to predict B-factor values, which reflect protein flexibility. Previous models have made significant strides in analyzing B-factors by

Adrián Pérez-Salinas, Patrick Emonts, Jordi Tura, Vedran Dunjko

Classical simulation of quantum physics is a central approach to investigating physical phenomena. Quantum computers enhance computational capabilities beyond those of classical resources, but it remains unclear to what extent existing limited quantum computers can contribute to this enhancement. In this work, we explore a new hybrid, efficient quantum-class

Lingxi Li, Yue Yu, Joanna Borowiec, Francisco V Ramirez-Cuevas

Photon transport through a diffusing slab can be described by the radiative transfer equation (RTE). When the slab is highly scattering and weakly absorbing, the RTE simplifies to the diffusion equation. In this paper, an inverse diffusion approximation (IDA) method is numerically developed to determine the optical properties (reduced scattering $\mu'_s$ and

Ziyang Jiang, Jiahe Lei, Xueyan Chen, Yifan Zhang

Target Speaker Extraction (TSE) aims to extract the clean speech of the target speaker in an audio mixture, eliminating irrelevant background noise and speech. While prior work has explored various auxiliary cues including pre-recorded speech, visual information, and spatial information, the acquisition and selection of such strong cues are infeasible in man

Veronika Krauß, Mark McGill, Thomas Kosch, Yolanda Thiel

With the recent advancements in Large Language Models (LLMs), web developers increasingly apply their code-generation capabilities to website design. However, since these models are trained on existing designerly knowledge, they may inadvertently replicate bad or even illegal practices, especially deceptive designs (DD). This paper examines whether users can

Long-Fei Li, Peng Zhao, Zhi-Hua Zhou

We study episodic linear mixture MDPs with the unknown transition and adversarial rewards under full-information feedback, employing dynamic regret as the performance measure. We start with in-depth analyses of the strengths and limitations of the two most popular methods: occupancy-measure-based and policy-based methods. We observe that while the occupancy-

ALICE Collaboration

The ALICE Collaboration presents a new suite of jet substructure measurements in Pb-Pb and pp collisions at a center-of-mass energy per nucleon pair $\sqrt{s}_{\rm NN} = 5.02$ TeV. These measurements provide access to the internal structure of jets via the momentum and angle of their constituents, probing how the quark--gluon plasma modifies jets, an effect

Christel Sirocchi, Muhammad Suffian, Federico Sabbatini, Alessandro Bogliolo

In clinical practice, decision-making relies heavily on established protocols, often formalised as rules. Concurrently, Machine Learning (ML) models, trained on clinical data, aspire to integrate into medical decision-making processes. However, despite the growing number of ML applications, their adoption into clinical practice remains limited. Two critical

Xing Huang, Xiaochen Ma

By using coupling by change of conditional probability measure, the log-Harnack inequality for path dependent McKean-Vlasov SDEs with distribution dependent diffusion coefficients is established, which together with the exponential contractivity in $L^2$-Wasserstein distance yields the exponential contractivity in entropy-cost under the uniformly dissipative

Faniriana Rakoto Endor, Irène Waldspurger

We consider MaxCut-type semidefinite programs (SDP) which admit a low rank solution. To numerically leverage the low rank hypothesis, a standard algorithmic approach is the Burer-Monteiro factorization, which allows to significantly reduce the dimensionality of the problem at the cost of its convexity. We give a sharp condition on the conditioning of the Lap

Jyotishman Bhowmick, Bappa Ghosh, Andrey O. Krutov, Réamonn Ó Buachalla

We classify covariant metrics (in the sense of Beggs and Majid) on a class of quantum homogeneous spaces. In particular, our classification implies the existence of a unique (up to scalar) quantum symmetric covariant metric on the Heckenberger--Kolb calculi for the quantized irreducible flag manifolds. Moreover, we prove the existence and uniqueness of Levi-

M. Vrard, M. H. Pinsonneault, Y. Elsworth, M. Hon

Evolved cool stars have three distinct evolutionary status: shell Hydrogen-burning (RGB), core Helium and shell Hydrogen burning (RC), and double shell burning (AGB). Asteroseismology can distinguish between the RC and the other status, but distinguishing RGB and AGB has been difficult seismically and spectroscopically. The precise boundaries of different st

Andressa Cerqueira, Laila L. S. Costa

Community detection methods have been extensively studied to recover communities structures in network data. While many models and methods focus on binary data, real-world networks also present the strength of connections, which could be considered in the network analysis. We propose a probabilistic model for generating weighted networks that allows us to co

Chang He, Yue Xin, Longfei Yang, Zewei Wang

We report the design-technology co-optimization (DTCO) scheme to develop a 28-nm cryogenic CMOS (Cryo-CMOS) technology for high-performance computing (HPC). The precise adjustment of halo implants manages to compensate the threshold voltage (VTH) shift at low temperatures. The optimized NMOS and PMOS transistors, featured by VTH<0.2V, sub-threshold swing (SS

Pasi Fränti

Hunt for predatory journals is based on binary division of the publishing world to legitime and predatory journals. This leads to difficulties in labeling publishers like MDPI with questionable practices. However, the root cause is not the publisher itself but the problems in the peer review system. These problems have created markets for the for-profit publ

Adrian B. Chłopowiec, Adam R. Chłopowiec, Krzysztof Galus, Wojciech Cebula

Limited medical imaging datasets challenge deep learning models by increasing risks of overfitting and reduced generalization, particularly in Generative Adversarial Networks (GANs), where discriminators may overfit, leading to training divergence. This constraint also impairs classification models trained on small datasets. Generative Data Augmentation (GDA

Ella S. C. Orme, Marina Evangelou, Ulrich Paquet

Multi-view data from the same source often exhibit correlation. This is mirrored in correlation between the latent spaces of separate variational autoencoders (VAEs) trained on each data-view. A multi-view VAE approach is proposed that incorporates a joint prior with a non-zero correlation structure between the latent spaces of the VAEs. By enforcing such co

Jonas Kamminga, Dorian Rudolph

In this work we investigate the computational complexity of the pure consistency of local density matrices (PureCLDM) and pure N-representability (Pure-N-Representability; analog of PureCLDM for bosonic or fermionic systems) problems. In these problems the input is a set of reduced density matrices and the task is to determine whether there exists a global p

Ya-Ze Cheng, Yan Cao, Yong Tang

Extreme mass-ratio hyperbolic encounters (EMRHEs) around the supermassive black holes will be observable at the future gravitational-wave (GW) detectors in space, such as LISA and Taiji. Here we consider such EMRHEs in the presence of surrounding matter distribution including baryonic accretion disk and dark matter (DM) spike, and estimate their effects on t

Long Cui, Xin Hao, Liu Zhao

We consider the linear response of a near-equilibrium charged relativistic gas in the presence of electromagnetic and gravitational field in a generic stationary spacetime up to the second order of relaxation time and calculate the tensorial kinetic coefficients introduced by the presence of the strong electromagnetic and/or gravitational field. Using the co

Hannes Rox, Fabian Ränke, Jonathan Mädler, Mateusz M. Marzec

Laser-structuring techniques like Direct Laser Interference Patterning show great potential for optimizing electrodes for water electrolysis. Therefore, a systematic experimental study based on statistical design of experiments is performed to analyze the influence of the spatial period and the aspect ratio between spatial period and structure depth on the e

Romain Meriot, Benoit Semelin, David Cornu

While the observation of the 21 cm signal from the Cosmic Dawn and Epoch of Reionization is an instrumental challenge, the interpretation of a prospective detection is still open to questions regarding the modelling of the signal and the Bayesian inference techniques that bridge the gap between theory and observations. To address some of these questions, we

Takumi Otani

For a generalized root system of affine ADE type, we introduce a twist automorphism. We prove that the Dubrovin-Zhang extended affine Weyl group is isomorphic to our (modified) extended affine Weyl group, which is an extension of the affine Weyl group by the twist automorphism. We also show that the number of root bases with a Coxeter transformation modulo t

Wen-Wei Li

Let $\mathrm{Mp}(2n)$ be the metaplectic group of rank $n$ over a local field $F$ of characteristic zero. In this note, we determine the behavior of endoscopic transfer for $\mathrm{Mp}(2n)$ under variation of additive characters of $F$. The arguments are based on properties of transfer factor, requiring no deeper results from representation theory. Combined

Yuta Tanabe, Kentaro Yaji, Kuniharu Ushijima

This paper proposes a topology optimization method for non-thermal and thermal fluid problems using the Lattice Kinetic Scheme (LKS).LKS, which is derived from the Lattice Boltzmann Method (LBM), requires only macroscopic values, such as fluid velocity and pressure, whereas LBM requires velocity distribution functions, thereby reducing memory requirements. T

S. Zhang, S. Seidelin, R. Le Targat, P. Goldner

The possibility of generating an narrow spectral hole in a rare-earth doped crystal opens the gateway to a variety of applications, one of which is the realization of an ultrastable laser. As this is achieved by locking in a pre-stabilized laser to the narrow hole, a prerequisite is the elimination of frequency fluctuations of the spectral hole. One potentia

J. -F. Donati, P. I. Cristofari, S. H. P. Alencar, Á. Kóspál

This paper presents near-infrared spectropolarimetric and velocimetric observations of the young planet-hosting T Tauri star PDS 70, collected with SPIRou at the 3.6m Canada-France-Hawaii Telescope from 2020 to 2024. Clear Zeeman signatures from magnetic fields at the surface of PDS 70 are detected in our data set of 40 circularly polarized spectra. Longitud

Jiaqi Chen, Bo Feng, Yi-Xiao Tao

In this paper, we give the analytic expression for the homogeneous part of solutions of arbitrary tree-level cosmological correlators, including massive propagators and time-derivative interaction cases. The solutions are given in the form of multivariate hypergeometric functions. It is achieved by two steps. Firstly, we indicate the factorization of the hom

Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer

We introduce efficient differentially private (DP) algorithms for several linear algebraic tasks, including solving linear equalities over arbitrary fields, linear inequalities over the reals, and computing affine spans and convex hulls. As an application, we obtain efficient DP algorithms for learning halfspaces and affine subspaces. Our algorithms addressi

Arnab Dey, Cheng-You Lu, Andrew I. Comport, Srinath Sridhar

Recent advancements in radiance field rendering show promising results in 3D scene representation, where Gaussian splatting-based techniques emerge as state-of-the-art due to their quality and efficiency. Gaussian splatting is widely used for various applications, including 3D human representation. However, previous 3D Gaussian splatting methods either use p

Wupeng Wang, Zexu Pan, Xinke Li, Shuai Wang

Speech separation seeks to separate individual speech signals from a speech mixture. Typically, most separation models are trained on synthetic data due to the unavailability of target reference in real-world cocktail party scenarios. As a result, there exists a domain gap between real and synthetic data when deploying speech separation models in real-world

Ferhad Askerbeyli, Wen Xu, Josef A. Nossek

Feeding power amplifiers (PAs) with constant envelope (CE) signals is an effective way to reduce the power consumption in massive multiple-input-multiple-output (MIMO) systems. The nonlinear distortion caused by CE signaling must be mitigated by means of signal processing to improve the achievable sum rates. To this purpose, many linear and nonlinear precodi

Xiao-yu Chen

Multipartite entanglement detection is crucial for the develop of quantum information science and quantum computation, communication, simulation and metrology tasks. In contrast to experiments, where several handreds of qubits have been entangled to build a quantum computer or a quantum simulator, theoretically only for lower dimensional quantum system such

Irum Mehboob, Li Sun, Alireza Astegarpanah, Rustam Stolkin

This paper shows how an uncertainty-aware, deep neural network can be trained to detect, recognise and localise objects in 2D RGB images, in applications lacking annotated train-ng datasets. We propose a self-supervising teacher-student pipeline, in which a relatively simple teacher classifier, trained with only a few labelled 2D thumbnails, automatically pr

Ruizhi Gong, Deng-Shan Wang

For the KdV equation with well-type initial value, the interaction between the trial soliton and the mean field is studied. The well initial value will lead to the appearance of rarefaction wave and dispersion shock wave, and there will be a linear wave region after a long time. The interaction between trial soliton and mean field is described within the fra

Jonathan Lindell, Lleonard Rubio y Degrassi

In this paper we investigate the Lie algebra structure of the first relative Hochschild cohomology and its relation with the relative notion of fundamental group. Let $A,B$ be finite-dimensional basic $k$-algebras over an algebraically closed field of characteristic zero, such that $Q_B$ is a subquiver of $Q_A$. We show that if the complement of $Q_A$ by the

Jinbao Chen, Hongjing Xiang, Zuohong Zhao, Luhao Li

Static Application Security Testing (SAST) tools are critical to software quality, identifying potential code issues early in development. However, they often produce false positive warnings that require manual review, slowing down development. Thus, automating false positive mitigation (FPM) is essential. The advent of Large Language Models (LLMs), with the

Penghua Ying, Xiang Gao, Amir Natan, Michael Urbakh

The mechanisms underlying chemifriction, i.e. the contribution of interfacial bonding to friction in defected twisted graphene interfaces are revealed using fully atomistic machine-learning molecular dynamics simulations. This involves stochastic events of consecutive bond formation and rupture, that are spatially separated but not necessarily independent. A

Aidan Carlson, Brian Hopkins, James A. Sellers

In 2014, as part of a larger study of overpartitions with restrictions of the overlined parts based on residue classes, Munagi and Sellers defined $d_2(n)$ as the number of overpartitions of weight $n$ wherein only even parts can be overlined. As part of that work, they used a generating function approach to prove a parity characterization for $d_2(n)$. In t

Dan Yang, Yu-Ting Rong, Rong An, Rui-Xiang Shi

Shell quenching phenomena in nuclear charge radii are typically observed at the well-established neutron magic numbers. However, the recent discovery of potential new magic numbers at the neutron numbers $N = 32$ and $N = 34$ has sparked renewed interest in this mass region. This work further inspects into the charge radii of nuclei around the $N = 28$ shell

Marceau Limousin

Parametric strong lensing studies of galaxy clusters often display misleading features: group/cluster scale dark matter components without any stellar counterpart, offsets between both components larger than what might be allowed by neither Cold Dark Matter nor self interacting Dark Matter models, or significant unexplained external shear components. I am re

Gavin Buxton

A model of lightning that captures the propagation of lightning channels on an irregular lattice is developed. The irregular lattice allows us to capture large two-dimensional systems (2 km x 2 km), while allowing grid refinement (on the order of cm) near areas of interest. Furthermore, the direction of lightning propagation is not biased in the orthogonal o

Wouter van Doorn

Let $\displaystyle \sum_{i=a}^b \frac{1}{i} = \frac{u_{a,b}}{v_{a,b}}$ with $u_{a,b}$ and $v_{a,b}$ coprime. Erd\H{o}s and Graham asked the following: Does there, for every fixed $a$, exist a $b$ such that $v_{a,b} < v_{a,b-1}$? If so, what is the least such $b = b(a)$? In this paper we will investigate these problems in a more general setting, answer the fi

Huaping Li, Ekrem Mert Bahçeci, Mehmet Sayar, Alkan Kabakçıoğlu

We investigate the denaturation dynamics of nucleic acids through extensive molecular dynamics simulations of a coarse-grained RNA hairpin model. In apparent contradiction with Arrhenius' law, our findings reveal that the denaturation time of RNA hairpins is a non-monotonous function of temperature for molecules longer than few persistence lengths, with an o

Dingyu Wang

The celebrated Morris counter uses $\log_2\log_2 n + O(\log_2 \sigma^{-1})$ bits to count up to $n$ with a relative error $\sigma$, where if $\hat{\lambda}$ is the estimate of the current count $\lambda$, then $\mathbb{E}|\hat{\lambda}-\lambda|^2 <\sigma^2\lambda^2$. A natural generalization is \emph{multi-dimensional} approximate counting. Let $d\geq 1$ be

Jasper Nalbach, Gereon Kremer

The cylindrical algebraic covering method was originally proposed to decide the satisfiability of a set of non-linear real arithmetic constraints. We reformulate and extend the cylindrical algebraic covering method to allow for checking the truth of arbitrary non-linear arithmetic formulas, adding support for both quantifiers and Boolean structure. Furthermo

Jonas Forster, Lutz Schröder, Paul Wild

Game-theoretic characterizations of process equivalences traditionally form a central topic in concurrency; for example, most equivalences on the classical linear-time / branching-time spectrum come with such characterizations. Recent work on so-called graded semantics has led to a generic behavioural equivalence game that covers the mentioned games on the l

Jing Li, Yinghua Yao, Yuangang Pan, Xuanqian Wang

Worst-case fairness with off-the-shelf demographics achieves group parity by maximizing the model utility of the worst-off group. Nevertheless, demographic information is often unavailable in practical scenarios, which impedes the use of such a direct max-min formulation. Recent advances have reframed this learning problem by introducing the lower bound of m

Anastasiia Plotnikova, Lorenzo Spina, Bridget Ratcliffe, Giada Casali

In this study we address whether the age--metallicity relation (AMR) deviates from the expected trend of metallicity increasing smoothly with age. We also show the presence (or absence) of two populations, as recently claimed using a relatively small dataset. Moreover, we studied the Milky Way thin disk's chemical evolution using solar twins, including the e

Prince Mathew, Vincent Penelle, Prakash Saivasan, A. V. Sreejith

This paper introduces deterministic weighted real-time one-counter automaton (DWROCA). A DWROCA is a deterministic real-time one-counter automaton whose transitions are assigned a weight from a field. Two DWROCAs are equivalent if every word accepted by one is accepted by the other with the same weight. DWROCA is a sub-class of weighted one-counter automata

William Fleurat

We show that given a log-concave offspring distribution, the corresponding sequence of Bienaym\'e-Galton-Watson trees conditioned to have $n\geq 1$ vertices admits a realization as a Markov process $(T_n)_{n\geq1}$ which adds a new "right-leaning" leaf at each step. This applies for instance to offspring distributions which are Poisson, binomial, geometric,

Gabriel Bellon de Carvalho, Jurandy Almeida

Segment Anything Model (SAM), a new AI model from Meta AI released in April 2023, is an ambitious tool designed to identify and separate individual objects within a given image through semantic interpretation. The advanced capabilities of SAM are the result of its training with millions of images and masks, and a few days after its release, several researche

Xueyan Bai, Haixiang Zhang

The use of mediation analysis has become increasingly popular in various research fields in recent years. The primary objective of mediation analysis is to examine the indirect effects along the pathways from exposure to outcome. Meanwhile, the advent of data collection technology has sparked a surge of interest in the burgeoning field of big data analysis,

Ivan Novak

We determine all possible degrees of cyclic isogenies of non-CM elliptic curves with rational $j$-invariant over number fields of degree $p$, where $p$ is an odd prime. The question had been answered for $p=2$, so this paper completes the classification in case when the degree of the number field is prime.

J. Torre-Cruz, D. Martinez-Munoz, N. Ruiz-Reyes, A. J. Munoz-Montoro

The proposed system consists of a two-stage cascade. The first stage performs a rough heartbeat detection while the second stage refines the previous one, improving the temporal localization and also classifying the heartbeats into types S1 and S2. The first contribution is a novel approach that combines the dissimilarity matrix with the frame-level spectral

Himanshu Chaudhary, Lehel Csillag, Tiberiu Harko

We present a review of the Semi-Symmetric Metric Gravity (SSMG) theory, representing a geometric extension of standard general relativity, based on a connection introduced by Friedmann and Schouten in 1924. The semi-symmetric connection is a connection that generalizes the Levi-Civita one, by allowing for the presence of a simple form of the torsion, describ

Tao Huang, Qingyu Huang, Xin Shi, Jiayang Meng

In the domain of deep learning, the challenge of protecting sensitive data while maintaining model utility is significant. Traditional Differential Privacy (DP) techniques such as Differentially Private Stochastic Gradient Descent (DP-SGD) typically employ strategies like direct or per-sample adaptive gradient clipping. These methods, however, compromise mod

Joan Elias, Maria Evelina Rossi

The purpose of this paper is to characterize one-dimensional local domains, or more in general reduced, in terms of its Macaulay's inverse system. This leads to study almost finitely generated modules in the divided power ring. We specialize the results to a numerical semigroup ring by computing explicitly its inverse system. In the graded case we characteri

Taeuk Nam

Drinfeld and Gaitsgory proved that $\mathrm{D}-\mathrm{mod}(\mathrm{Bun}_G)$ is compactly generated. Let $\mathrm{Bun}_G^{\mathrm{I}}$ be the algebraic stack of principal $G$-bundles on $X$ together with Iwahori level structure at a fixed point $x \in X$. More generally, for a finite collection of points $x_1, ..., x_k \in X$, let $\mathrm{Bun}_G^{(\mathrm{I

Somita Dhal, Koustav Konar, R. K. Paul

This paper presents a novel approach to constrain the $\mu$- and y- distortions in the Cosmic Microwave Background (CMB) using the COBE/FIRAS data. The analysis draws from the concept of blackbody radiation inversion (BRI), a mathematical technique typically used to determine the temperature distribution from a radiated power spectrum. We study the deviation

Luca Zhou, Daniele Solombrino, Donato Crisostomi, Maria Sofia Bucarelli

Model merging has emerged as a cost-efficient approximation to multitask learning. Among merging strategies, task arithmetic is notable for its simplicity and effectiveness. In this work, we provide a theoretical motivation for task vectors by highlighting that, under single-epoch full-batch gradient descent, they are equivalent to multitask gradients. This

Ram Zamir, Kenneth Rose

The inherent trade-off in on-line learning is between exploration and exploitation. A good balance between these two (conflicting) goals can achieve a better long-term performance. Can we define an optimal balance? We propose to study this question through a backward-adaptive lossy compression system, which exhibits a "natural" trade-off between exploration

Tao Huang, Jiayang Meng, Hong Chen, Guolong Zheng

We investigate the construction of gradient-guided conditional diffusion models for reconstructing private images, focusing on the adversarial interplay between differential privacy noise and the denoising capabilities of diffusion models. While current gradient-based reconstruction methods struggle with high-resolution images due to computational complexity

Jennifer Volk, George Tzimpragos, Oleg Mukhanov

ERSFQ circuits eliminate the dominant portion of static power consumption in RSFQ circuits by using current-limiting Josephson junctions and inductors instead of bias resistors. In practice, these junctions still contribute to static power consumption through switching required to correct phase imbalances across the circuit, with their contributions sometime

Yuyang Huang, Michael Herty, Dante Kalise, Nikolas Kantas

We propose a variant of consensus-based optimization (CBO) algorithms, controlled-CBO, which introduces a feedback control term to improve convergence towards global minimizers of non-convex functions in multiple dimensions. The feedback law is a gradient of a numerical approximation to the Hamilton-Jacobi-Bellman (HJB) equation, which serves as a proxy of t

Margarita Hernanz, Marco Feroci, Yuri Evangelista, Aline Meuris

The eXTP mission is a major project of the Chinese Academy of Sciences (CAS), with a large involvement of Europe. Its scientific payload includes four instruments: SFA, PFA, LAD and WFM. They offer an unprecedented simultaneous wide-band Xray timing and polarimetry sensitivity. A large European consortium is contributing to the eXTP study, both for the scien

Arijit Manna, Sabyasachi Pal, Sekhar Sinha, Sushanta Kumar Mondal

The atomic and molecular compounds of cometary ices serve as valuable knowledge into the chemical and physical properties of the outer solar nebula, where comets are formed. From the cometary atmospheres, the atoms and gas-phase molecules arise mainly in three ways: (i) the outgassing from the nucleus, (ii) the photochemical process, and (iii) the sublimatio

Zhongjin Luo, Haolin Liu, Chenghong Li, Wanghao Du

Neural implicit functions have brought impressive advances to the state-of-the-art of clothed human digitization from multiple or even single images. However, despite the progress, current arts still have difficulty generalizing to unseen images with complex cloth deformation and body poses. In this work, we present GarVerseLOD, a new dataset and framework t

Ying Chen, Chuangchuang Kang, Jiafeng Lü

The $\lambda$-differential operators and modified $\lambda$-differential operators are generalizations of classical differential operators. This paper introduces the notions of $\lambda$-differential Poisson ($\lambda$-DP for short) algebras and modified $\lambda$-differential Poisson ($\lambda$-mDP for short) algebras as generalizations of differential Pois

Andraž Gnidovec, Emanuele Locatelli, Simon Čopar, Anže Božič

The behaviour and stability of soft and biological matter depend significantly on electrostatic interactions, as particles such as proteins and colloids acquire a charge when dispersed in an electrolytic solution. A typical simplification used to understand bulk phenomena involving electrostatic interactions is the isotropy of the charge on the particles. Ho

Peter Drotár, Jiří Mekyska, Irena Rektorová, Lucia Masarová

Objective: We present the PaHaW Parkinson's disease handwriting database, consisting of handwriting samples from Parkinson's disease (PD) patients and healthy controls. Our goal is to show that kinematic features and pressure features in handwriting can be used for the differential diagnosis of PD. Methods and Material: The database contains records from 37

Konstantin Kovalyov

In this paper we introduce an axiomatization of B\"uchi arithmetic, i.e., of the elementary theory of natural numbers in the language with addition and function $V_p(a) = p^k$ such that $p^k | a$ and $p^{k + 1} \nmid a$.

Bei Li, Tong Zheng, Rui Wang, Jiahao Liu

Residual networks, as discrete approximations of Ordinary Differential Equations (ODEs), have inspired significant advancements in neural network design, including multistep methods, high-order methods, and multi-particle dynamical systems. The precision of the solution to ODEs significantly affects parameter optimization, thereby impacting model performance

Zhang Qixiang, Yang Yuxiang, Zu Chen, Zhang Jianjia

Semi-supervised learning (SSL) is a popular solution to alleviate the high annotation cost in medical image classification. As a main branch of SSL, consistency regularization engages in imposing consensus between the predictions of a single sample from different views, termed as Absolute Location consistency (AL-c). However, only AL-c may be insufficient. J

Thomas Ceulemans, Frederik De Ceuster, Leen Decin, Jeremy Yates

Spectral line observations are an indispensable tool to remotely probe the physical and chemical conditions throughout the universe. Modelling their behaviour is a computational challenge that requires dedicated software. In this paper, we present the first long-term stable release of Magritte, an open-source software library for line radiative transfer. Fir

Mael Houbre, Florian Boudin, Beatrice Daille, Akiko Aizawa

State-of-the-art models for keyphrase generation require large amounts of training data to achieve good performance. However, obtaining keyphrase-labeled documents can be challenging and costly. To address this issue, we present a self-compositional data augmentation method. More specifically, we measure the relatedness of training documents based on their s