December 2023 arXiv papers — page 118

Daniel Gomes de Pinho Zanco, Leszek Szczecinski, Jacob Benesty

In this work, we consider the problem of regularization in the design of minimum mean square error (MMSE) linear filters. Using the relationship with statistical machine learning methods, using a Bayesian approach, the regularization parameter is found from the observed signals in a simple and automatic manner. The proposed approach is illustrated in system

Lucas Pinol, Sébastien Renaux-Petel, Denis Werth

The time evolution of primordial fluctuations conceals a wealth of insights into the high-energy physics at play during the earliest moments of our Universe, which is ultimately encoded in late-time spatial correlation functions. However, the conventional procedure to compute them is technically challenging, and a complete dictionary mapping the landscape of

Enrico Picco, Alessandro Lupo, Serge Massar

Speech recognition is a critical task in the field of artificial intelligence and has witnessed remarkable advancements thanks to large and complex neural networks, whose training process typically requires massive amounts of labeled data and computationally intensive operations. An alternative paradigm, reservoir computing, is energy efficient and is well a

Victor M. Tenorio, Samuel Rey, Antonio G. Marques

Graph Neural Networks (GNNs) have emerged as a notorious alternative to address learning problems dealing with non-Euclidean datasets. However, although most works assume that the graph is perfectly known, the observed topology is prone to errors stemming from observational noise, graph-learning limitations, or adversarial attacks. If ignored, these perturba

Pedro Dedin Neto, Irene Tamborra, Shashank Shalgar

In core-collapse supernovae and neutron star mergers, the neutrino density is so large that neutrino-neutrino refraction can lead to flavor conversion, if a zero-crossing is present in the neutrino flavor lepton number (FLN) angular distribution and the neutrino self-interaction strength $\mu=\sqrt{2} G_F n_\nu$ represents the characteristic timescale of the

Omer Melih Gul, Michel Kulhandjian, Burak Kantarci, Claude D'Amours

Cyber-physical systems have recently been used in several areas (such as connected and autonomous vehicles) due to their high maneuverability. On the other hand, they are susceptible to cyber-attacks. Radio frequency (RF) fingerprinting emerges as a promising approach. This work aims to analyze the impact of decoupling tapped delay line and clustered delay l

Byoung-jin Jeon, Matteo M. Guareschi, Jaimie M. Stewart, Emily Wu

The diversity and heterogeneity of biomarkers has made the development of general methods for single-step quantification of analytes difficult. For individual biomarkers, electrochemical methods that detect a conformational change in an affinity binder upon analyte binding have shown promise. However, because the conformational change must operate within a n

Xiaogang Peng, Yiming Xie, Zizhao Wu, Varun Jampani

We address the problem of generating realistic 3D human-object interactions (HOIs) driven by textual prompts. To this end, we take a modular design and decompose the complex task into simpler sub-tasks. We first develop a dual-branch diffusion model (HOI-DM) to generate both human and object motions conditioned on the input text, and encourage coherent motio

Moritz Weber, Luc Janecke, Hüseyin K. Çakmak, Veit Hagenmeyer

In the present paper, we introduce a new method for the automated generation of residential distribution grid models based on novel building load estimation methods and a two-stage optimization for the generation of the 20 kV and 400 V grid topologies. Using the introduced load estimation methods, various open or proprietary data sources can be utilized to e

Zijian Zhang, Jieao Zhu, Linglong Dai, Robert W. Heath

Fluid antenna systems (FASs) can reconfigure their antenna locations freely within a spatially continuous space. To keep favorable antenna positions, the channel state information (CSI) acquisition for FASs is essential. While some techniques have been proposed, most existing FAS channel estimators require several channel assumptions, such as slow variation

Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang

The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs have only released partial artifacts, such as the final model weights or inference code, and technical reports increasingly limit their scope to high-level design choices and surfa

Thiago Gomes Vidal de Mello, Matheus Schreiner Homrich da Silva, Gabriel Fonseca Silva, Soraia Raupp Musse

This paper proposes the simulation of structured behaviors in a crowd of virtual agents by extending the BioCrowds simulation model. Three behaviors were simulated and evaluated, a queue as a generic case and two specific behaviors observed at rock concerts. The extended model incorporates new parameters and modifications to replicate these behaviors accurat

Dmitry Gayfulin, Manuel Hauke

Given an irrational number $\alpha$, we study the asymptotic behaviour of the Sudler product denoted by $P_N(\alpha) = \prod_{r=1}^N 2\lvert \sin \pi r \alpha \rvert$. We show that $\liminf_{N \to \infty} P_N(\alpha) >0$ and $\limsup_{N \to \infty} P_N(\alpha)/N < \infty$ whenever the sequence of partial quotients in the continued fraction expansion of $\alp

Zina-Sabrina Duma, Jouni Susiluoto, Otto Lamminpää, Tuomas Sihvonen

Partial Least-Squares (PLS) Regression is a widely used tool in chemometrics for performing multivariate regression. PLS is a bi-linear method that has a limited capacity of modelling non-linear relations between the predictor variables and the response. Kernel PLS (K-PLS) has been introduced for modelling non-linear predictor-response relations. In K-PLS, t

Mohamed S. Halawa, Rebeca P. Díaz-Redondo, Ana Fernández-Vilas

Performance analysis is an essential task in High-Performance Computing (HPC) systems and it is applied for different purposes such as anomaly detection, optimal resource allocation, and budget planning. HPC monitoring tasks generate a huge number of Key Performance Indicators (KPIs) to supervise the status of the jobs running in these systems. KPIs give dat

Moritz F. Richter, Andrea Smirne, Walter T. Strunz, Dario Egloff

In classical stochastic theory, the joint probability distributions of a stochastic process obey by definition the Kolmogorov consistency conditions. Interpreting such a process as a sequence of physical measurements with probabilistic outcomes, these conditions reflect that the measurements do not alter the state of the underlying physical system. Prominent

Dominic Konrad, Zhihao Duan, Mertcan Cokbas, Prakash Ishwar

Knowing how many and where are people in various indoor spaces is critical for reducing HVAC energy waste, space management, spatial analytics and in emergency scenarios. While a range of technologies have been proposed to detect and track people in large indoor spaces, ceiling-mounted fisheye cameras have recently emerged as strong contenders. Currently, RA

Shirin Besati, Ali Mosallanejad, Madhav Manjrekar

The Virtual Synchronous Machine (VSM) concept stands as a strategy for the seamless integration of renewable energy sources into the grid. In scenarios where symmetrical and sinusoidal operating conditions are lacking, VSMs demonstrate multifaceted capabilities. They can operate as power sources especially in islanded-systems, adeptly address harmonic distor

Patrick Uftring

In the late 1980s, Abrusci, Girard and van de Wiele defined a variant of Goodstein sequences: the so-called inverse Goodstein sequence. In their work, they show that it terminates precisely at the Bachmann-Howard ordinal. This reveals that a proof of this fact requires substantial consistency strength. Moreover, the authors could show that sequences of this

Dominik Inauen, Govind Menon

This paper introduces a probabilistic formulation for the isometric embedding of a Riemannian manifold $(M^n,g)$ into Euclidean space $\mathbb{R}^q$. Given $\alpha \in ]\tfrac{1}{2},1]$, we show that a $C^{1,\alpha}$ embedding $u: M \to \mathbb{R}^q$ is isometric if and only if the intrinsic and extrinsic constructions of Brownian motion on $u(M)\subset \mat

Brecht Evens, Puya Latafat, Panagiotis Patrinos

The Chambolle-Pock algorithm (CPA), also known as the primal-dual hybrid gradient method, has gained popularity over the last decade due to its success in solving large-scale convex structured problems. This work extends its convergence analysis for problems with varying degrees of (non)monotonicity, quantified through a so-called oblique weak Minty conditio

Martin R. Bridson

Given an arbitrary, finitely presented, residually finite group $\Gamma$, one can construct a finitely generated, residually finite, free-by-free group $M_\Gamma = F_\infty\rtimes F_4$ and an embedding $M_\Gamma \hookrightarrow (F_4\ast \Gamma)\times F_4$ that induces an isomorphism of profinite completions. In particular, there is a free-by-free group whose

Nuno Reis, Vasco Costa, João M. Pereira

We present an algorithm for creating an n-level ray-space hierarchy (RSH) of coherent rays that runs on the GPU. Our algorithm uses rasterization to process the primary rays, then uses those results as the inputs for a RSH, that processes the secondary rays. The RSH algorithm generates bundles of rays; hashes them, according to their attributes; and sorts th

Stasis Chuchurka, Vladislav Sukharnikov, Andrei Benediktovitch, Nina Rohringer

We propose an approach based on stochastic differential equations to describe superfluorescence in compact ensembles of multi-level emitters in the presence of various incoherent processes. This approach has a numerical complexity that does not depend on the number of emitters. The stochastic differential equations are derived directly from the quantum maste

J. A. García-González, M. M. González

We present a comparison of the flux normalization of HAWC sources using 17 months of data that was processed using two different versions of the official data reconstruction used for HAWC analyses. Pass4 (P4) has been used so far for most of the results published by HAWC. The most recent reconstruction version, Pass5 (P5) will be used in future analyses and

Viviane Timmermann, Samuel T. Wall, Joakim Sundnes, Tarek Lawen

Heterogeneous mechanical dyskinesis during acute myocardial ischaemia is thought to contribute to arrhythmogenic alterations to cardiac electrophysiology. Various forms of mechano-electric coupling (MEC) mechanisms have been suggested to contribute to these changes, with two primary mechanisms being: (1) myofilament-dependent calcium release events, and (2)

Mohamed Soliman Halawa, Rebeca P. Díaz-Redondo, Ana Fernández-Vilas

High-Performance Computing (HPC) systems need to be constantly monitored to ensure their stability. The monitoring systems collect a tremendous amount of data about different parameters or Key Performance Indicators (KPIs), such as resource usage, IO waiting time, etc. A proper analysis of this data, usually stored as time series, can provide insight in choo

Samuel Lin, Ricardo A. E. Mendes, Marco Radeschi

We prove a version of Weyl's Law for the basic spectrum of a closed singular Riemannian foliation $(M,\mathcal{F})$ with basic mean curvature. In the special case of $M=\mathbb{S}^n$, this gives an explicit formula for the volume of the leaf space $\mathbb{S}^n/\mathcal{F}$ in terms of the algebra of basic polynomials. In particular, $\operatorname{Vol}(\mat

Rahul Vishwakarma, Rucha Bhalchandra Joshi, Subhankar Mishra

Indoor localization is the process of determining the location of a person or object inside a building. Potential usage of indoor localization includes navigation, personalization, safety and security, and asset tracking. Commonly used technologies for indoor localization include WiFi, Bluetooth, RFID, and Ultra-wideband. Among these, WiFi's Received Signal

Anders Hjort, Gudmund Horn Hermansen, Johan Pensar, Jonathan P. Williams

Non-parametric machine learning models, such as random forests and gradient boosted trees, are frequently used to estimate house prices due to their predictive accuracy, but a main drawback of such methods is their limited ability to quantify prediction uncertainty. Conformal prediction (CP) is a model-agnostic framework for constructing confidence sets arou

Camila Vicari Maccari, Gustavo Galle de Melo, Paulo Ricardo Knob, Soraia Raupp Musse

This paper studies the non-verbal behavior of a conversational agent named Arthur. We propose the development of body movements for this agent, which interacts solely through voice commands, chat, and videos with facial animations. This research aims to analyze users' perceptions regarding the gestures performed by Arthur. This study was conducted with parti

Alena Prudnikava, Yegor Tamashevich, Anna Makarova, Dmitry Smirnov

In the present work the chemical composition of niobium surface upon 200-400 {\deg}C baking similar to "medium-temperature baking" and "furnace baking" of cavities is explored in-situ by synchrotron X-ray photoelectron spectroscopy (XPS). Our findings imply that below the critical thickness of $Nb_2O_5$ layer (about 1 nm) niobium starts to interact actively

Xiang Cheng, Yuxin Chen, Suvrit Sra

Many neural network architectures are known to be Turing Complete, and can thus, in principle implement arbitrary algorithms. However, Transformers are unique in that they can implement gradient-based learning algorithms under simple parameter configurations. This paper provides theoretical and empirical evidence that (non-linear) Transformers naturally lear

Theodore Wolf, Nantas Nardelli, John Shawe-Taylor, Maria Perez-Ortiz

Governments around the world aspire to ground decision-making on evidence. Many of the foundations of policy making - e.g. sensing patterns that relate to societal needs, developing evidence-based programs, forecasting potential outcomes of policy changes, and monitoring effectiveness of policy programs - have the potential to benefit from the use of large-s

E. Musumeci, A. Irles, R. Perez-Ramos, I. Corredoira

Future $e^+e^-$ colliders are expected to play a fundamental role in measuring Standard Model (SM) parameters with unprecedented precision and in probing physics beyond the SM (BSM). This study investigates two-particle angular correlation distributions involving final-state SM charged hadrons. Unexpected correlation structures in these distributions is cons

Anish Giri, Robert J. Scherrer

We examine big bang nucleosynthesis (BBN) in models with a time-varying gravitational constant $G$, when this time variation is rapid on the scale of the expansion rate $H$, i.e, $\dot G/G \gg H$. Such models can arise naturally in the context of scalar-tensor theories of gravity and result in additional terms in the Friedman equation. We examine two represe

Simone Cristofori, Michela Zedda

In view of a better understanding of the geometry of scalar flat K\"ahler metrics, this paper studies two families of scalar flat K\"ahler metrics constructed in [10] by A. D. Hwang and M. A. Singer on $\mathbb C^{n+1}$ and on $\mathcal O(-k)$. For the metrics in both the families, we prove the existence of an asymptotic expansion for their $\epsilon$-functi

Peter Fulde

The dimension of the Hilbert space needed for the description of an interacting electron system increases exponentially with electron number $N$. As pointed out by W. Kohn this exponential wall problem (EWP) limits the concept of many-electron wavefunctions based on solutions of Schr\"odinger's equation to $N \leq N_0$, where $N_0 \approx 10^3$ \cite{Kohn199

Yijie Gao, Shijing Si, Hua Luo, Haixia Sun

Label smoothing is a widely used technique in various domains, such as text classification, image classification and speech recognition, known for effectively combating model overfitting. However, there is little fine-grained analysis on how label smoothing enhances text sentiment classification. To fill in the gap, this article performs a set of in-depth an

Giorgio Comitini, Tim De Meerleer, David Dudal, Silvio Paolo Sorella

We discuss the possibility to obtain a massive Landau gauge, based on the local composite operator (LCO) effective action framework combined with the Zimmerman reduction of couplings prescription. As a way to deal with the gauge ambiguity, we check that the ghost propagator remains positive, a necessary condition for gluon field configurations beyond the Gri

Jacob Grant, Hossein Mirinejad

Fluid resuscitation, also called fluid therapy, is commonly used in treatment of critical care patients. Of the variables inherent to fluid therapy treatment, fluid infusion types are well-studied, but volumetric optimization is not. Automated fluid resuscitation systems employ computational control algorithms along with physiological sensors and actuators t

Asif Newaz, Abdullah Taharat, Md Sakibul Islam, A. G. M. Fuad Hasan Akanda

Ovarian cancer (OC) is one of the most prevalent types of cancer in women. Early and accurate diagnosis is crucial for the survival of the patients. However, the majority of women are diagnosed in advanced stages due to the lack of effective biomarkers and accurate screening tools. While previous studies sought a common biomarker, our study suggests differen

Ramón González Rodríguez, Ana Belén Rodríguez Raposo

In this paper we introduce the notion of generalized invertible 1-cocycle in a strict braided monoidal category C, and we prove that the category of Hopf trusses is equivalent to the category of generalized invertible 1-cocycles. On the other hand, we also introduce the notions of module for a Hopf truss and for a generalized invertible 1-cocycle. We prove s

Hung-Chun Hsu, Bo-Jun Wu, Ming-Yi Hong, Che Lin

Graph neural networks (GNNs) face significant challenges with class imbalance, leading to biased inference results. To address this issue in heterogeneous graphs, we propose a novel framework that combines Graph Neural Network (GNN) and Generative Adversarial Network (GAN) to enhance classification for underrepresented node classes. The framework incorporate

Hongcai He, Anjie Zhu, Shuang Liang, Feiyu Chen

Offline meta-reinforcement learning (meta-RL) methods, which adapt to unseen target tasks with prior experience, are essential in robot control tasks. Current methods typically utilize task contexts and skills as prior experience, where task contexts are related to the information within each task and skills represent a set of temporally extended actions for

Dennis Buckmaster, Sami Basir, Hanae Sakata

As an on-ramp to databases, we offer several well-structured private database templates as open source resources for agriculturalists, particularly those with modest spreadsheet skills. These farmer-oriented Air table databases use simple data-validated forms, with the look and feel of a customized app, to yield operational data that is tidy, machine- and hu

Manuel Fernández-Veiga, M. E. Sousa-Vieira, Ana Fernández-Vilas, Rebeca P Díaz-Redondo

Irregular repetition slotted Aloha (IRSA) has shown significant advantages as a modern technique for uncoordinated random access with massive number of users due to its capability of achieving theoretically a throughput of $1$ packet per slot. When the receiver has also the multi-packet reception of multi-user (MUD) detection property, by applying successive

Anna Lena Duque Antón, Johannes Müller, Lucas Deutschmann, Mohammad Rahmani Fadiheh

The threat of hardware Trojans (HTs) in security-critical IPs like cryptographic accelerators poses severe security risks. The HT detection methods available today mostly rely on golden models and detailed circuit specifications. Often they are specific to certain HT payload types, making pre-silicon verification difficult and leading to security gaps. We pr

Craig M. Vineyard, William M. Severa, James B. Aimone

Co-design is a prominent topic presently in computing, speaking to the mutual benefit of coordinating design choices of several layers in the technology stack. For example, this may be designing algorithms which can most efficiently take advantage of the acceleration properties of a given architecture, while simultaneously designing the hardware to support t

Hongyuan Li, Ziyu Xiang, Aidan P. Reddy, Trithep Devakul

Semiconductor moir\'e superlattices provide a versatile platform to engineer new quantum solids composed of artificial atoms on moir\'e sites. Previous studies have mostly focused on the simplest correlated quantum solid - the Fermi-Hubbard model - where intra-atom interactions are simplified to a single onsite repulsion energy U. These studies have revealed

Soniya Vijayakumar, Tanja Bäumel, Simon Ostermann, Josef van Genabith

Pre-trained Language Models (PLMs) have shown to be consistently successful in a plethora of NLP tasks due to their ability to learn contextualized representations of words (Ethayarajh, 2019). BERT (Devlin et al., 2018), ELMo (Peters et al., 2018) and other PLMs encode word meaning via textual context, as opposed to static word embeddings, which encode all m

Gábor Hetyei

Combining Carver's variant of the Farkas' lemma with the Flow Decomposition Theorem we show that the regions of any deformation of a graphical arrangement may be bijectively labeled with a set of weighted digraphs containing directed cycles of negative weight only. Bounded regions correspond to strongly connected digraphs. The study of the resulting labeling

GVS Mothish, Karthik Rajgopal, Ravi Kola, Manan Tayal

This paper introduces the Stoch BiRo, a cost-effective bipedal robot designed with a modular mechanical structure having point feet to navigate uneven and unfamiliar terrains. The robot employs proprioceptive actuation in abduction, hips, and knees, leveraging a Raspberry Pi4 for control. Overcoming computational limitations, a Learning-based Linear Policy c

Matteo Crispino, Pablo Villar Arribi, Anmol Shukla, Frédéric Hardy

We define a general strategy for finding new heavy-fermionic materials without rare-earth elements: doping a Hund metal with pronounced orbital-selective correlations towards half-filling. We argue that in general band structures a possible orbital-selective Mott transition is frustrated by inter-orbital hopping into heavy-fermion behaviour - where d-orbital

Metin Lamby, Valentin Zieglmeier, Christian Ziegler

Smart contract access control mechanisms can introduce centralization into supposedly decentralized ecosystems. In our view, such centralization is an overlooked risk of smart contracts that underlies well-known smart contract security incidents. Critically, mitigating the known vulnerability of missing permission verification by implementing authorization p

Rubén Izquierdo, Javier Alonso, Ola Benderius, Miguel Ángel Sotelo

This study presents the outcomes of empirical investigations pertaining to human-vehicle interactions involving an autonomous vehicle equipped with both internal and external Human Machine Interfaces (HMIs) within a crosswalk scenario. The internal and external HMIs were integrated with implicit communication techniques, incorporating a combination of gentle

Brooke Polak, Mordecai-Mark Mac Low, Ralf S. Klessen, Jia Wei Teh

The mode of star formation that results in the formation of globular clusters and young massive clusters is difficult to constrain through observations. We present models of massive star cluster formation using the Torch framework, which uses AMUSE to couple distinct multi-physics codes that handle star formation, stellar evolution and dynamics, radiative tr

Tullio Basaglia, Zane W. Bell, Daniele DAgostino, Paul V. Dressendorfer

This paper summarizes Geant4 contribution to scientific research over the past 25 years through a scientometric analysis of the results with which it has been associated. The scientometric data collected from scholarly literature and databases are evaluated with methods pertaining to econometrics and ecology to quantify relevant traits, diversity and dispari

Xuyang Wu, Changxin Liu, Sindri Magnusson, Mikael Johansson

Existing asynchronous distributed optimization algorithms often use diminishing step-sizes that cause slow practical convergence, or use fixed step-sizes that depend on and decrease with an upper bound of the delays. Not only are such delay bounds hard to obtain in advance, but they also tend to be large and rarely attained, resulting in unnecessarily slow c

Shai Evra, Brooke Feigon, Kathrin Maurischat, Ori Parzanchevski

In their seminal paper, Lubotzky, Phillips and Sarnak (LPS) defined the notion of regular Ramanujan graphs and gave an explicit construction of infinite families of $(p+1)$-regular Ramanujan Cayley graphs, for infinitely many primes $p$. In this paper we extend the work of LPS and its successors to bigraphs (biregular bipartite graphs), in several aspects: w

Henning Basold, Peter Bruin, Dominique Lawson

Directed topology is an area of mathematics with applications in concurrency. It extends the concept of a topological space by adding a notion of directedness, which restricts how paths can evolve through a space and enables thereby a faithful representation of computation with their direction. In this paper, we present a Lean formalisation of directed space

Shangzhe Di, Weidi Xie

Existing approaches to video understanding, mainly designed for short videos from a third-person perspective, are limited in their applicability in certain fields, such as robotics. In this paper, we delve into open-ended question-answering (QA) in long, egocentric videos, which allows individuals or robots to inquire about their own past visual experiences.

Reza Dastbasteh, Josu Etxezarreta Martinez, Andrew Nemec, Antonio deMarti iOlius

We present a family of quantum stabilizer codes using the structure of duadic constacyclic codes over $\mathbb{F}_4$. Within this family, quantum codes can possess varying dimensions, and their minimum distances are lower bounded by a square root bound. For each fixed dimension, this allows us to construct an infinite sequence of binary quantum codes with a

ATLAS Collaboration

This Letter presents the first study of Higgs boson production in association with a vector boson (V = W or Z) in the fully hadronic $qqbb$ final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at $\sqrt{s}=13$ TeV and corresponding to an integrated luminosity of 137 fb$^{-1}$. The vector bosons and Higgs bosons are eac

J. Abad-Arredondo, A. I. Fernández-Domínguez

Thanks to their exceptional spatial, spectral and temporal resolution, highly-coherent free-electron beams have emerged as powerful probes for material excitations, enabling their characterization even in the quantum regime. Here, we investigate strong light-matter coupling through monochromatic and modulated electron wavepackets. In particular, we consider

Christian Mancas

Homogeneous binary function products are often encountered in the sub-universes modeled by databases, from genealogical trees to sports, from education to healthcare, etc. Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility. The (Elementary) Mathematical Data Model provides 18 dyadic-type

S. Mondal, K. Adamczyk, L. Aggarwal, H. Aihara

The silicon vertex detector (SVD) is installed at the heart of the Belle II experiment, taking data at the high-luminosity $B$-Factory SuperKEKB since 2019. The detector has shown a stable and above-99\% hit efficiency, with a large signal-to-noise in all sensors since the beginning of data taking. Cluster position and time resolution have been measured with

Rebeca P. Díaz-Redondo, Manuel Caeiro-Rodríguez, Juan José López-Escobar, Ana Fernández-Vilas

Lifelong learning requires appropriate solutions, especially for corporate training. Workers usually have difficulty combining training and their normal work. In this context, micro-learning emerges as a suitable solution, since it is based on breaking down new concepts into small fragments or pills of content, which can be consumed in short periods of time.

Fanny Jourdan, Louis Béthune, Agustin Picard, Laurent Risser

Ensuring fairness in NLP models is crucial, as they often encode sensitive attributes like gender and ethnicity, leading to biased outcomes. Current concept erasure methods attempt to mitigate this by modifying final latent representations to remove sensitive information without retraining the entire model. However, these methods typically rely on linear cla

Jihoon Chung, Nastaran Shahmansouri, Rhys Goldstein, James Stoddart

This paper explores the benefits of incorporating natural ventilation (NV) simulation into a generative process of designing residential buildings to improve energy efficiency and indoor thermal comfort. Our proposed workflow uses the Wave Function Collapse algorithm to generate a diverse set of plausible floor plans. It also includes post-COVID occupant pre

Pankaj Kumar, Heike Vogel, Julia Bruckert, Lisa Janina Muth

Aerosols influence weather and climate by interacting with radiation through absorption and scattering. These effects heavily rely on the optical properties of aerosols, which are mainly governed by attributes such as morphology, size distribution, and chemical composition. These attributes undergo continuous changes due to chemical reactions and aerosol mic

Simone Alioli, Guido Bell, Georgios Billis, Alessandro Broggio

We present the resummation of one-jettiness for the colour-singlet plus jet production process $p p \to ( \gamma^*/Z \to \ell^+ \ell^-) + {\text{jet}}$ at hadron colliders up to the fourth logarithmic order (N$^3$LL). This is the first resummation at this order for processes involving three coloured partons at the Born level. We match our resummation formula

Matheus Schreiner Homrich da Silva, Paulo Brossard de Souza Pinto Neto, Rodolfo Migon Favaretto, Soraia Raupp Musse

Security is an important topic in our contemporary world, and the ability to automate the detection of any events of interest that can take place in a crowd is of great interest to a population. We hypothesize that the detection of events in videos is correlated with significant changes in pedestrian behaviors. In this paper, we examine three different scena

Martin Gorbahn, Ulserik Moldanazarova, Kai Henryk Sieja, Emmanuel Stamou

The excellent experimental prospects to measure the invisible mass spectrum of the $K^+\to\pi^+\nu\bar\nu$ decay opens a new path to test generalised quark--neutrino interactions with flavour changing $s\to d$ transitions and as such to novel probes of Physics beyond the Standard Model. Such signals can be a consequence of new lepton-number violating or lept

Eeshwar Prasad Poudel, Pitambar Acharya, Jeevan Kafle, Shreeram Khadka

In this paper, we address a time-dependent one-dimensional linear advection-diffusion equation with Dirichlet homogeneous boundary conditions. The equation is solved both analytically, using separation of variables, and numerically, employing the finite difference method. The computational output includes three dimensional (3D) plots for solutions, focusing

Thies Jansen, Geert Brocks, Menno Bokdam

Perovskite oxides are known to exhibit many magnetic, electronic and structural phases as function of doping and temperature. These materials are theoretically frequently investigated by the DFT+U method, typically in their ground state structure at $T=0$. We show that by combining machine learning force fields (MLFFs) and DFT+U based molecular dynamics, it

Ruhul Amin Khalil, Muhammad Haris, Nasir Saeed

Beyond Line of Sight (BLOS) communication stands as an indispensable element within defense communication strategies, facilitating information exchange in scenarios where traditional Line of Sight (LOS) methodologies encounter obstruction. This article delves into the forefront of technologies driving BLOS communication, emphasizing advanced systems like pha

Alice Petrov, Christian Muise

This paper explores the application of automated planning to automated theorem proving, which is a branch of automated reasoning concerned with the development of algorithms and computer programs to construct mathematical proofs. In particular, we investigate the use of planning to construct elementary proofs in abstract algebra, which provides a rigorous an

Rajsekhar Bhattacharyya

In this paper, we show examples of local cohomology modules over ramified regular local ring, having finite set of associated primes. In doing so we consider our ramified regular local ring as Eisenstein extension of an unramified regular local ring sitting inside it. In ramified regular local ring for extended ideal (from the unramified one) set of associat

Na Zhao, Kejiang Chen, Weiming Zhang, Nenghai Yu

With the development of deep learning, high-value and high-cost models have become valuable assets, and related intellectual property protection technologies have become a hot topic. However, existing model watermarking work in black-box scenarios mainly originates from training-based backdoor methods, which probably degrade primary task performance. To addr

Miranda K. Zak, Jon M. Miller, Ehud Behar, William N. Brandt

Markarian 817 is a bright and variable Seyfert-1.2 active galactic nucleus (AGN). X-ray monitoring of Mrk 817 with the Neil Gehrels Swift Observatory in 2022 revealed that the source flux had declined to a lower level than recorded at any prior point in the then-19-year mission. We present an analysis of deep XMM-Newton and NuSTAR observations obtained in th

Xi Ye, Guillaume-Alexandre Bilodeau

Predicting future frames of a video is challenging because it is difficult to learn the uncertainty of the underlying factors influencing their contents. In this paper, we propose a novel video prediction model, which has infinite-dimensional latent variables over the spatio-temporal domain. Specifically, we first decompose the video motion and content infor

Eleanor Archer, Quirin Vogel

We consider critical percolation on a supercritical Galton-Watson tree. We show that, when the offspring distribution is in the domain of attraction of an $\alpha$-stable law for some $\alpha \in (1,2)$, or has finite variance, several annealed properties also hold in a quenched setting. In particular, the following properties hold for the critical root clus

Kari Heine

In modern days, the ability to carry out computations in parallel is key to efficient implementations of computationally intensive algorithms. This paper investigates the applicability of the previously proposed Augmented Island Resampling Particle Filter (AIRPF) -- an algorithm designed for parallel implementations -- to particle Markov Chain Monte Carlo (P

Osama A. Marzouk

Magnetohydrodynamics (MHD) is a subject concerned with the dynamics of electrically conducting fluids (plasma) and can be applied in electric power generation. As a unique technology for producing direct-current electricity without moving parts, it can be utilized within a high-temperature topping power cycle to be combined with a traditional bottoming power

R. K. S. Yadav, Arvind K. Dattatrey, Geeta Rangwal, Annapurni Subramaniam

We present the study of four FUV stars in the field of open cluster NGC 2420 using the Ultra Violet Imaging Telescope (UVIT) mounted on AstroSat. The three stars 525, 527, and 560 are members, while star 646 is a non-member of the cluster. To characterize and determine the parameters of these stars, multi-wavelength spectral energy distributions (SEDs) are a

William Giarè, Eleonora Di Valentino, Alessandro Melchiorri

We study the possibility of measuring the optical depth at reionization, $\tau$, without relying on large-scale Cosmic Microwave Background (CMB) polarization. Our analysis is driven by the need to obtain competitive measurements that can validate the state-of-the-art constraints on this parameter, widely based on E-mode polarization measurements at $\ell\le

Alessandra Sorrentino, Laura Fiorini, Carlo La Viola, Filippo Cavallo

Socially Assistive Robots represent a valid solution for improving the quality of life and the mood of older adults. In this context, this work presents the CloudIA robot, a non-human-like robot intended to promote sociality and well-being among older adults. The design of the robot and of the provided services were carried out by a multidisciplinary team of

Lijie Wang, Razan Nughays, Jun Yin, Chun-Hua Shih

Using ultrafast broad-band transient absorption (TA) spectroscopy of photo-excited MAPbBr3 thin films with probe continua in the visible and the mid-to-deep-UV ranges, we capture the ultrafast gap renormalization at the fundamental gap situated at the R symmetry point of the Brillouin Zone (BZ) and a higher energy gap at the M point. Global Lifetime analysis

Kyle Myers, Wei Yang Tham

The design of research grants has been hypothesized to be a useful tool for influencing researchers and their science. We test this by conducting two thought experiments in a nationally representative survey of academic researchers. First, we offer participants a hypothetical grant with randomized attributes and ask how the grant would influence their resear

Feng Gan, Wanfeng Liang, Changliang Zou

In modern data analysis, it is common to use machine learning methods to predict outcomes on unlabeled datasets and then use these pseudo-outcomes in subsequent statistical inference. Inference in this setting is often called post-prediction inference. We propose a novel assumption-lean framework for statistical inference under post-prediction setting, calle

Zhengwei Liu, Shuang Ming, Yilong Wang, Jinsong Wu

We introduce the 3-alterfold topological quantum field theory (TQFT) by extending the quantum invariant of 3-alterfolds. The bases of the TQFT are explicitly characterized and the Levin-Wen model is naturally interpreted in 3-alterfold TQFT bases. By naturally considering the RT TQFT and TV TQFT as sub-TQFTs within the 3-alterfold TQFT, we establish their eq

Balakrishnan Varadarajan, Bilge Soran, Forrest Iandola, Xiaoyu Xiang

The Segment Anything Model (SAM) has been a cornerstone in the field of interactive segmentation, propelling significant progress in generative AI, computational photography, and medical imaging. Despite its ability to process arbitrary user input and generate corresponding segmentation masks, SAM's 600 million parameter architecture, based on ViT-H, is not

Jean Gutt, Vinicius G. B. Ramos

It is a long-standing conjecture that all symplectic capacities which are equal to the Gromov width for ellipsoids coincide on a class of convex domains in $\mathbb{R}^{2n}$. It is known that they coincide for monotone toric domains in all dimensions. In this paper, we study whether requiring a capacity to be equal to the $k^{th}$ Ekeland-Hofer capacity for

Anestis Dalgkitsis, Christos Verikoukis

Robots are increasingly being used in a variety of applications, from manufacturing and healthcare to education and customer service. However, the mobility, power, and price points of these robots often dictate that they do not have sufficient computing power on board to run modern algorithms for personalization in human-robot interaction at desired rates. T

Xiaoyi Bao, Jie Qin, Siyang Sun, Yun Zheng

For few-shot semantic segmentation, the primary task is to extract class-specific intrinsic information from limited labeled data. However, the semantic ambiguity and inter-class similarity of previous methods limit the accuracy of pixel-level foreground-background classification. To alleviate these issues, we propose the Relevant Intrinsic Feature Enhanceme

Toyomu Matsuda, Avi Mayorcas

We show pathwise uniqueness of multiplicative SDEs, in arbitrary dimensions, driven by fractional Brownian motion with Hurst parameter $H\in (1/3,1)$ with volatility coefficient $\sigma$ that is at least $\gamma$-H\"older continuous for $\gamma > \frac{1}{2H} \vee \frac{1-H}{H}$. This improves upon the long-standing results of [Lyo94 , Lyo98 , Dav08] which c

Shirantha Welikala, Zihao Song, Panos J. Antsaklis, Hai Lin

Vehicular platoons provide an appealing option for future transportation systems. Most of the existing work on platoons separated the design of the controller and its communication topologies. However, it is beneficial to design both the platooning controller and the communication topology simultaneously, i.e., controller and topology co-design, especially i

Giorgio Cignarale, Roman Kuznets

Standard epistemic logic is concerned with describing agents' epistemic attitudes given the current set of alternatives the agents consider possible. While distributed systems can (and often are) discussed without mentioning epistemics, it has been well established that epistemic phenomena lie at the heart of what agents, or processes, can and cannot do. Dyn

Zhenze Yang, Weike Ye, Xiangyun Lei, Daniel Schweigert

Solid polymer electrolytes hold significant promise as materials for next-generation batteries due to their superior safety performance, enhanced specific energy, and extended lifespans compared to liquid electrolytes. However, the material's low ionic conductivity impedes its commercialization, and the vast polymer space poses significant challenges for the