October 2022 arXiv papers — page 17

Yiming Dong, Lijing Shao, Zexin Hu, Xueli Miao

The discovery of radio pulsars (PSRs) around the supermassive black hole (SMBH) in our Galactic Center (GC), Sagittarius A* (Sgr A*), will have significant implications for tests of gravity. In this paper, we predict restrictions on the parameters of the Yukawa gravity by timing a pulsar around Sgr A* with a variety of orbital parameters. Based on a realisti

R. Srinivas, C. M. Löschnauer, M. Malinowski, A. C. Hughes

We present a new method for coherent control of trapped ion qubits in separate interaction regions of a multi-zone trap by simultaneously applying an electric field and a spin-dependent gradient. Both the phase and amplitude of the effective single-qubit rotation depend on the electric field, which can be localised to each zone. We demonstrate this interacti

Federico Faedo, Alessio Fontanarossa, Dario Martelli

We construct new supersymmetric $\mathrm{AdS}_2\times \mathbb{M}_4$ solutions of $D=6$ gauged supergravity, where $\mathbb{M}_4$ are certain four-dimensional orbifolds. After uplifting to massive type IIA supergravity these correspond to the near-horizon limit of a system of $N$ D4-branes and $N_f$ D8-branes wrapped on $\mathbb{M}_4$. In one class of solutio

Ming Cheng, Weiqing Wang, Yucong Zhang, Xiaoyi Qin

Target-speaker voice activity detection is currently a promising approach for speaker diarization in complex acoustic environments. This paper presents a novel Sequence-to-Sequence Target-Speaker Voice Activity Detection (Seq2Seq-TSVAD) method that can efficiently address the joint modeling of large-scale speakers and predict high-resolution voice activities

Fadri Grünenfelder, Alberto Boaron, Matthieu Perrenoud, Giovanni V. Resta

Quantum Key Distribution has made continuous progress over the last 20 years and is now commercially available. However, the secret key rates (SKR) are still limited to a few Mbps. Here, we present a custom multipixel superconducting nanowire single-photon detectors and fast acquisition and real-time key distillation electronics, removing two roadblocks and

John D. Osborne, Tobias O'Leary, Akhil Nadimpalli, Salma M. Aly.

Objective: Implement and assess personal health identifying information (PHI) substitution strategies and quantify their privacy preserving benefits. Materials and Methods: We implement and assess 3 different `Hiding in Plain Sight` (HIPS) strategies for PHI replacement including a standard Consistent replacement strategy, a Random replacement strategy and a

Lucille Calmon, Sanjukta Krishnagopal, Ginestra Bianconi

We propose Local Dirac Synchronization which uses the Dirac operator to capture the dynamics of coupled nodes and link signals on an arbitrary network. In Local Dirac Synchronization, the harmonic modes of the dynamics oscillate freely while the other modes are interacting non-linearly, leading to a collectively synchronized state when the coupling constant

Carl-Fredrik Nyberg-Brodda

We give an infinite family of monoids $\Pi_N$ (for $N=2, 3, \dots$), each with a single defining relation of the form $bUa = a$, such that the Dehn function of $\Pi_N$ is at least exponential. More precisely, we prove that the Dehn function $\partial_N(n)$ of $\Pi_N$ satisfies $\partial_N(n) \succeq N^{n/4}$. This answers negatively a question posed by Cain

Pierre Degond, Amic Frouvelle, Sara Merino-Aceituno, Ariane Trescases

In this paper, we study a nonlinear system of first order partial differential equations describing the macroscopic behavior of an ensemble of interacting self-propelled rigid bodies. Such system may be relevant for the modelling of bird flocks, fish schools or fleets of drones. We show that the system is hyperbolic and can be approximated by a conservative

Qing Zeng, Yuefeng Yang, Kaishun Wang

A weakly distance-regular digraph is $P$-polynomial if its attached scheme is $P$-polynomial. In this paper, we characterize all $P$-polynomial weakly distance-regular digraphs.

Asselya G. Smadiyeva, Berikbol T. Torebek

In this paper, the initial-boundary value problems for the time-fractional degenerate evolution equations are considered. Firstly, in the linear case, we obtain the optimal rates of decay estimates of the solutions. The decay estimates are also established for the time-fractional evolution equations with nonlinear operators such as: p-Laplacian, the porous m

Giulia Ceriotti, Giovanni M Porta, Claudio Geloni, Matilde Dalla Rosa

We develop a methodological framework and mathematical formulation which yields estimates of the uncertainty associated with the amounts of CO2 generated by carbonate-clays reactions (CCR) in large-scale subsurface systems to assist characterization of the main features of this geochemical process. Our approach couples a one-dimensional compaction model, pro

Yong Xiao, Zijian Sun, Guangming Shi, Dusit Niyato

Semantic communication has recently attracted significant interest from both industry and academia due to its potential to transform the existing data-focused communication architecture towards a more generally intelligent and goal-oriented semantic-aware networking system. Despite its promising potential, semantic communications and semantic-aware networkin

Fengfan Zhou, Hefei Ling, Yuxuan Shi, Jiazhong Chen

Face recognition (FR) models can be easily fooled by adversarial examples, which are crafted by adding imperceptible perturbations on benign face images. The existence of adversarial face examples poses a great threat to the security of society. In order to build a more sustainable digital nation, in this paper, we improve the transferability of adversarial

Pierre Nazé

The objective of this work is to show that adiabatic processes can be very similar to isothermal ones. First, we show that the criteria for the compatibility of linear-response theory with the Second Law of Thermodynamics for thermally isolated systems are the same as those for systems performing isothermal processes. Motivated by such a result, we explore t

Jie Fan, Quansen Jiu

This paper is to derive a new blow-up criterion for the 2D full compressible Navier-Stokes equations without heat conduction in terms of the density $\rho$ and the pressure $P$. More precisely, it indicates that in a bounded domain the strong solution exists globally if the norm $\|\rho||_{{L^\infty(0,t;L^{\infty})}}+||P||_{L^{p_0}(0,t;L^\infty)}<\infty$ for

Chuqin Geng, Nham Le, Xiaojie Xu, Zhaoyue Wang

Having reliable specifications is an unavoidable challenge in achieving verifiable correctness, robustness, and interpretability of AI systems. Existing specifications for neural networks are in the paradigm of data as specification. That is, the local neighborhood centering around a reference input is considered to be correct (or robust). While existing spe

Maxime Poli, Emmanuel Dupoux, Rachid Riad

Parts of the brain that carry sensory tasks are organized topographically: nearby neurons are responsive to the same properties of input signals. Thus, in this work, inspired by the neuroscience literature, we proposed a new topographic inductive bias in Convolutional Neural Networks (CNNs). To achieve this, we introduced a new topographic loss and an effici

Kazuo Sano

Trade is one of the essential feature of human intelligence. The securities market is the ultimate expression of it. The fundamental indicators of stocks include information as well as the effects of noise and bias on the stock prices; however, identifying the effects of noise and bias is generally difficult. In this article, I present the true fundamentals

Pankaj C. Bhambhani, Ivan. K. Baldry, Sarah Brough, Alexander D. Hill

Galaxy populations are known to exhibit a strong colour bimodality, corresponding to blue star-forming and red quiescent subpopulations. The relative abundance of the two populations has been found to vary with stellar mass and environment. In this paper, we explore the effect of environment considering different types of measurements. We choose a sample of

Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao

In this paper, deep learning (DL) methods are evaluated in the context of turbulent flows. Various generative adversarial networks (GANs) are discussed with respect to their suitability for understanding and modeling turbulence. Wasserstein GANs (WGANs) are then chosen to generate small-scale turbulence. Highly resolved direct numerical simulation (DNS) turb

Maciej Fidrysiak

We carry out a systematic study of collective spin- and charge excitations for the canonical single-band Hubbard, $t$-$J$-$U$, and $t$-$J$ models of high-temperature copper-oxide superconductors, both on electron- and hole-doped side of the phase diagram. Recently developed variational wave function approach, combined with the expansion in inverse number of

Chengyuan Li, Zhifang Qiu, Yugao Ma, Meifu Li

Prognosis of the reactor accident is a crucial way to ensure appropriate strategies are adopted to avoid radioactive releases. However, there is very limited research in the field of nuclear industry. In this paper, we propose a method for accident prognosis based on the Temporal Fusion Transformer (TFT) model with multi-headed self-attention and gating mech

Loïc Philoxene, Vu Hung Dao, Raymond Frésard

We introduce and analyze an extended Hubbard model, in which intersite Coulomb interaction as well as a staggered local potential (SLP) are considered, on the square lattice at half band filling, in the thermodynamic limit. Using both Hartree-Fock approximation and Kotliar and Ruckenstein slave boson formalism, we show that the model harbors charge order (CO

Marvin Becker, Johannes Köhler, Sami Haddadin, Matthias A. Müller

Recently, many reactive trajectory planning approaches were suggested in the literature because of their inherent immediate adaption in the ever more demanding cluttered and unpredictable environments of robotic systems. However, typically those approaches are only locally reactive without considering global path planning and no guarantees for simultaneous c

Chen Dun, Mirian Hipolito, Chris Jermaine, Dimitrios Dimitriadis

Asynchronous learning protocols have regained attention lately, especially in the Federated Learning (FL) setup, where slower clients can severely impede the learning process. Herein, we propose \texttt{AsyncDrop}, a novel asynchronous FL framework that utilizes dropout regularization to handle device heterogeneity in distributed settings. Overall, \texttt{A

Bo Li, Mingzhe Guo, Hui Yu, Shao-Xia Chen

Impulsively excited wave trains are of considerable interest in solar coronal seismology. To our knowledge, however, it remains to examine the three-dimensional (3D) dispersive propagation of impulsive kink waves in straight, field-aligned, symmetric, low-beta, slab equilibria that are structured only in one transverse direction. We offer a study here, start

E. Kefala, V. Bosch-Ramon

High-mass gamma-ray binaries are powerful nonthermal galactic sources, some of them hosting a pulsar whose relativistic wind interacts with a likely inhomogeneous stellar wind. So far, modeling these sources including stellar wind inhomogeneities has been done using either simple analytical approaches or heavy numerical simulations, none of which allow for a

Haojie Pan, Zepeng Zhai, Yuzhou Zhang, Ruiji Fu

Online encyclopedias, such as Wikipedia, have been well-developed and researched in the last two decades. One can find any attributes or other information of a wiki item on a wiki page edited by a community of volunteers. However, the traditional text, images and tables can hardly express some aspects of an wiki item. For example, when we talk about ``Shiba

José Agustin Barrachina, Chengfang Ren, Christèle Morisseau, Gilles Vieillard

In this paper, we investigated the semantic segmentation of Polarimetric Synthetic Aperture Radar (PolSAR) using Complex-Valued Neural Network (CVNN). Although the coherency matrix is more widely used as the input of CVNN, the Pauli vector has recently been shown to be a valid alternative. We exhaustively compare both methods for six model architectures, thr

Jacob van den Berg, Henk Don

The OSSS inequality [O'Donnell, Saks, Schramm and Servedio, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), Pittsburgh (2005)] gives an upper bound for the variance of a function f of independent 0-1 valued random variables, in terms of the influences of these random variables and the computational complexity of a (randomised) algori

Jiahao Lu, Chong Yin, Kenny Erleben, Michael Bachmann Nielsen

Recently, attempts have been made to reduce annotation requirements in feature-based self-explanatory models for lung nodule diagnosis. As a representative, cRedAnno achieves competitive performance with considerably reduced annotation needs by introducing self-supervised contrastive learning to do unsupervised feature extraction. However, it exhibits unstab

Marcel Risch

Electrocatalysts for the oxygen evolution reaction (OER) are an important component for the transition from fossil to sustainable energy. Commercialization of cost-effective earth-abundant electrocatalysts is in large parts hindered by their degradation. In this short review, I identify common processes leading to a decrease in electrocatalyst activity, foll

Andrea Gallo Rosso, Sara Algeri, Jan Conrad

The goal of this paper is to introduce a novel likelihood-based inferential framework for axion haloscopes which is valid under the commonly applied "rescanning" protocol. The proposed method enjoys short data acquisition times and a simple tuning of the detector configuration. Local statistical significance and power are computed analytically, avoiding the

Lang Liu, Zhi-Qiang You, You Wu, Zu-Cheng Chen

Primordial black holes (PBHs) can be not only cold dark matter candidates but also progenitors of binary black holes observed by LIGO-Virgo-KAGRA (LVK) Collaboration. The PBH mass can be shifted to the heavy distribution if multi-merger processes occur. In this work, we constrain the merger history of PBH binaries using the gravitational wave events from the

Dishant Padalia, Abhishek Mazumdar, Bharati Singh

According to multiple authoritative authorities, including the World Health Organization, vision-related impairments and disorders are becoming a significant issue. According to a recent report, one of the leading causes of irreversible blindness in persons over the age of 50 is delayed cataract treatment. A cataract is a cloudy spot in the eye's lens that c

Miles D. Blanchet, Bethany E. Matthews, Steven R. Spurgeon, Steve M. Heald

Transition metal spinel oxides comprised of Earth-abundant Mn and Co have long been explored for their use in catalytic reactions and energy storage. However, understanding of functional properties can be challenging due to differences in sample preparation and the ultimate structural properties of the materials. Epitaxial thin film synthesis provides a nove

Shao-Xia Chen, Bo Li, Mingzhe Guo, Mijie Shi

There has been considerable interest in magnetoacoustic waves in static, straight, field-aligned, one-dimensional equilibria where the exteriors of a magnetic slab are different between the two sides. We focus on trapped, transverse fundamental, oblique quasi-kink modes in pressureless setups where the density varies continuously from a uniform interior (wit

David Biesner, Thore Gerlach, Christian Bauckhage, Bernd Kliem

Many applications in automated auditing and the analysis and consistency check of financial documents can be formulated in part as the subset sum problem: Given a set of numbers and a target sum, find the subset of numbers that sums up to the target. The problem is NP-hard and classical solving algorithms are therefore not practical to use in many real appli

Károly Seller

The super-weak model is a U(1) extension of the Standard Model. In addition to a mediator $Z'$, a singlet scalar field $\chi$ is added to deal with the meta-stability of the SM vacuum, and right-handed neutrinos are introduced to account for the non-vanishing neutrino masses. We demonstrate that the lightest right-handed neutrino is a possible dark matter ca

Sayan Goswami

In a recent work \cite{key-11}, A. Fish proved that if $E_{1}$ and $E_{2}$ are two subsets of $\mathbb{Z}$ of positive upper Banach density, then there exists $k\in\mathbb{Z}$ such that $k\cdot\mathbb{Z}\subset\left(E_{1}-E_{1}\right)\cdot\left(E_{2}-E_{2}\right).$ In this article we will show that a similar result is true for the set of primes $\mathbb{P}$

Eduardo Santana de Almeida, Iftekhar Ahmed, Andre van der Hoek

The whiteboard plays a crucial role in the day-to-day lives of software architects, as they frequently will organize meetings at the whiteboard to discuss a new architecture, some proposed changes to the architecture, a mismatch between the architecture and the code, and more. While much has been studied about software architects, the architectures they prod

Gonzalo Camacho, Christoph Karrasch, Roman Rausch

We investigate the nonequilibrium dynamics of the $S=1$ quantum spin chain subjected to a time-dependent external drive, where the driving frequency is adiabatically decreased as a function of time (``Floquet adiabatic evolution''). We show that when driving the rhombic anisotropy term (known as the ``two-axis countertwisting'' in the context of squeezed spi

Poula Tadros, Iiro Vilja

We study Calabi-Yau compactifications of non relativistic string theory and show that it can be derived from the corresponding relativistic Calabi-Yau compactifications by taking the non relativistic limit of the resulting 4D theory without changing the internal part.

Ning Hao, Fenghua He, Chungeng Tian, Yu Yao

In this paper, we revisit the inconsistency problem of EKF-based cooperative localization (CL) from the perspective of system decomposition. By transforming the linearized system used by the standard EKF into its Kalman observable canonical form, the observable and unobservable components of the system are separated. Consequently, the factors causing the dim

Qianyu Yang, Anna Guerra, Francesco Guidi, Nir Shlezinger

Sixth generation (6G) cellular communications are expected to support enhanced wireless localization capabilities. The widespread deployment of large arrays and high-frequency bandwidths give rise to new considerations for localization applications. First, emerging antenna architectures, such as dynamic metasurface antennas (DMAs), are expected to be frequen

Tomoki Goda, Krzysztof Kutak, Sebastian Sapeta

In this study we incorporate the Sudakov form factor into the dipole factorization formula, where the hard scale of the former is provided by the photon virtuality $Q^2$. We obtain a general formula which we then apply to the well-known GBW and BGK saturation models. Parameters of the above Sudakov-improved models are successfully fitted to the $F_2$ data fr

JunKyu Lee, Blesson Varghese, Hans Vandierendonck

This paper analyzes the effects of dynamically varying video contents and detection latency on the real-time detection accuracy of a detector and proposes a new run-time accuracy variation model, ROMA, based on the findings from the analysis. ROMA is designed to select an optimal detector out of a set of detectors in real time without label information to ma

Gang Bao, Yixuan Zhang

This work establishes a framework for solving inverse boundary problems with the geodesic based quadratic Wasserstein distance ($W_{2}$). A general form of the Fr\'echet gradient is systematically derived by optimal transportation (OT) theory. In addition, a fast algorithm based on the new formulation of OT on $\mathbb{S}^{1}$ is developed to solve the corre

Mariona Caros, Ariadna Just, Santi Segui, Jordi Vitria

Airborne topographic LiDAR is an active remote sensing technology that emits near-infrared light to map objects on the Earth's surface. Derived products of LiDAR are suitable to service a wide range of applications because of their rich three-dimensional spatial information and their capacity to obtain multiple returns. However, processing point cloud data s

Yanyan Shen, Lifan Zhao, Weiyu Cheng, Zibin Zhang

Click-Through Rate (CTR) prediction on cold users is a challenging task in recommender systems. Recent researches have resorted to meta-learning to tackle the cold-user challenge, which either perform few-shot user representation learning or adopt optimization-based meta-learning. However, existing methods suffer from information loss or inefficient optimiza

Johannes Mario Meissner, Saku Sugawara, Akiko Aizawa

Debiasing language models from unwanted behaviors in Natural Language Understanding tasks is a topic with rapidly increasing interest in the NLP community. Spurious statistical correlations in the data allow models to perform shortcuts and avoid uncovering more advanced and desirable linguistic features. A multitude of effective debiasing approaches has been

Konstantinos Georgiadis, Albert Saà-Garriga, Mehmet Kerim Yucel, Anastasios Drosou

Bokeh effect highlights an object (or any part of the image) while blurring the rest of the image, and creates a visually pleasant artistic effect. Due to the sensor-based limitations on mobile devices, machine learning (ML) based bokeh rendering has gained attention as a reliable alternative. In this paper, we focus on several improvements in ML-based bokeh

D. C. Moreira, F. A Brito, J. C. Mota-Silva

We study classical scalar fields in asymptotically Lifshitz spacetimes. By evading Derrick's theorem requiring the scalar potential to explicitly depend on the background coordinates, we induce a diffeomorphism invariance breaking and settle a first-order formalism to find spatially localized solutions in the probe field limit. By inserting a backreaction eq

Hollis Williams

We present a number of exact solutions to the linearised Grad equations for non-equilibrium rarefied gas flows and heat flows. The solutions include the flow and pressure fields associated to a point force placed in a rarefied gas flow close to a no-slip boundary and the temperature field for a point heat source placed in a heat flow close to a temperature j

Meng Xu, Bo Jiang, Wenqiang Pu, Ya-Feng Liu

Fair principal component analysis (FPCA), a ubiquitous dimensionality reduction technique in signal processing and machine learning, aims to find a low-dimensional representation for a high-dimensional dataset in view of fairness. The FPCA problem involves optimizing a non-convex and non-smooth function over the Stiefel manifold. The state-of-the-art methods

David Biesner, Maren Pielka, Rajkumar Ramamurthy, Tim Dilmaghani

Natural language processing methods have several applications in automated auditing, including document or passage classification, information retrieval, and question answering. However, training such models requires a large amount of annotated data which is scarce in industrial settings. At the same time, techniques like zero-shot and unsupervised learning

Anjiao Gu, Yajuan Sun

In high-temperature plasma physics, a strong magnetic field is usually used to confine charged particles. Therefore, for studying the classical mathematical models of the physical problems it is needed to consider the effect of external magnetic fields. One of the important model equations in plasma is the Vlasov-Poisson equation with an external magnetic fi

David Biesner, Helen Schneider, Benjamin Wulff, Ulrike Attenberger

Chest X-Ray imaging is one of the most common radiological tools for detection of various pathologies related to the chest area and lung function. In a clinical setting, automated assessment of chest radiographs has the potential of assisting physicians in their decision making process and optimize clinical workflows, for example by prioritizing emergency pa

Sayan Goswami

W. T. Gower generalized Hindman's Finite sum theorem over $X_{k}=\left\{ \left(n_{1},n_{2},\ldots,n_{k}\right):n_{1}\neq0\right\} $ by showing that for any finite coloring of $X_{k}$ there exists a sequence such that the Gower subspace generated by that sequence is monochromatic. For $k=1,$ this immediately gives the finite sum theorem. In this article we wi

Benjamin Knorr, Chris Ripken, Frank Saueressig

Asymptotic Safety implies that observables including scattering amplitudes remain finite at the highest energy scales. Traditionally, this feature is connected to an interacting fixed point of the Wilsonian renormalization group that provides the high-energy completion of the theory. In this article, we discuss a different facet of Asymptotic Safety, reviewi

Tim Moser, Boris Lohmann

We present a new structure-preserving model order reduction (MOR) framework for large-scale port-Hamiltonian descriptor systems (pH-DAEs). Our method exploits the structural properties of the Rosenbrock system matrix for this system class and utilizes condensed forms which often arise in applications and reveal the solution behaviour of a system. Provided th

Ulysse Pavloff, Yackolley Amoussou-Guenou, Sara Tucci-Piergiovanni

Ethereum has undergone a recent change called \textit{the Merge}, which made Ethereum a Proof-of-Stake blockchain, shifting closer to BFT consensus. Ethereum, which wished to keep the best of the two protocol designs (BFT and Nakomoto-style), now has a convoluted consensus protocol as its core. The result is a blockchain being possibly produced in a tree-lik

Andrea Boido, Jerome P. Gauntlett, Dario Martelli, James Sparks

We introduce an entropy function for supersymmetric accelerating black holes in $AdS_4$, that uplift on general Sasaki-Einstein manifolds $X_7$ to solutions of M-theory. This allows one to compute the black hole entropy without knowing the explicit solutions. A dual holographic microstate counting would follow from computing certain supersymmetric partition

Samaneh Manavi Roodsari, Antal Huck-Horvath, Sara Freund, Azhar Zam

Continuum robots in robot-assisted minimally invasive surgeries provide adequate access to target anatomies that are not directly reachable through small incisions. Achieving precise and reliable motion control of such snake-like manipulators necessitates an accurate navigation system that requires no line-of-sight and is immune to electromagnetic noises. Fi

Dennis Bonatsos, K. E. Karakatsanis, Andriana Martinou, T. J. Mertzimekis

Using covariant density functional theory with the DDME2 functional and labeling single-particle energy orbitals by Nilsson quantum numbers, a search for particle-hole (p-h) excitations connected to the appearance of shape coexistence is performed for Z=38 to 84. Islands of shape coexistence are found near the magic numbers Z=82 and Z=50, restricted in regio

S. N. Mayburov

Analysis of Bell-EPR nonlocal correlations in microscopic measurement theory framework indicates that novel quantum nonlocality effects can exist. In particular, it can result in distant correlations between the systems of elementary quantum objects or particles. Doebner-Goldin nonlinear quantum formalism applied for nonlocal correlation description, compari

Yassine El Ouahidi, Lucas Drumetz, Giulia Lioi, Nicolas Farrugia

BCI Motor Imagery datasets usually are small and have different electrodes setups. When training a Deep Neural Network, one may want to capitalize on all these datasets to increase the amount of data available and hence obtain good generalization results. To this end, we introduce a spatial graph signal interpolation technique, that allows to interpolate eff

Harshad Khadilkar, Hardik Meisheri

A significant challenge in reinforcement learning is quantifying the complex relationship between actions and long-term rewards. The effects may manifest themselves over a long sequence of state-action pairs, making them hard to pinpoint. In this paper, we propose a method to link transitions with significant deviations in state with unusually large variatio

A. Bensberg, S. Wolf

Aims. We present an implementation of an algorithm for 3D time-dependent Monte Carlo radiative transfer. It allows one to simulate temperature distributions as well as images and spectral energy distributions of the scattered light and thermal reemission radiation for variable illuminating and heating sources embedded in dust distributions, such as circumste

Puyu Yang, Giovanni Colavizza

Wikipedia is the largest online encyclopedia: its open contribution policy allows everyone to edit and share their knowledge. A challenge of radical openness is that it facilitates introducing biased contents or perspectives in Wikipedia. Wikipedia relies on numerous external sources such as journal articles, books, news media, and more. News media sources,

Qipeng Guo, Yuqing Yang, Hang Yan, Xipeng Qiu

In recent years, there is a surge of generation-based information extraction work, which allows a more direct use of pre-trained language models and efficiently captures output dependencies. However, previous generative methods using lexical representation do not naturally fit document-level relation extraction (DocRE) where there are multiple entities and r

Roee M. Francos, Alfred M. Bruckstein

The goal of this research is to devise guaranteed defense policies that allow to protect a given region from the entrance of smart mobile invaders by detecting them using a team of defending agents equipped with identical line sensors. By designing cooperative defense strategies that ensure all invaders are detected, conditions on the defenders' speed are de

Paul Stoewer, Achim Schilling, Andreas Maier, Patrick Krauss

The hippocampal-entorhinal complex plays a major role in the organization of memory and thought. The formation of and navigation in cognitive maps of arbitrary mental spaces via place and grid cells can serve as a representation of memories and experiences and their relations to each other. The multi-scale successor representation is proposed to be the mathe

N. M. Rosário, S. C. C. Barros, O. D. S. Demangeon, N. C. Santos

A tidal interaction between a star and a close-in exoplanet leads to shrinkage of the planetary orbit and eventual tidal disruption of the planet. Measuring the shrinkage of the orbits will allow for the tidal quality parameter of the star ($Q'_\star$) to be measured, which is an important parameter to obtain information about stellar interiors. We analyse d

Amir Aghabiglou, Matthieu Terris, Adrian Jackson, Yves Wiaux

We propose a new approach for large-scale high-dynamic range computational imaging. Deep Neural Networks (DNNs) trained end-to-end can solve linear inverse imaging problems almost instantaneously. While unfolded architectures provide robustness to measurement setting variations, embedding large-scale measurement operators in DNN architectures is impractical.

Fan Ouyang, Weiqi Xu, Mutlu Cukurova

Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance to examine the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical research examining t

Lisheng Wu, Ke Chen

Reinforcement learning (RL) often struggles to accomplish a sparse-reward long-horizon task in a complex environment. Goal-conditioned reinforcement learning (GCRL) has been employed to tackle this difficult problem via a curriculum of easy-to-reach sub-goals. In GCRL, exploring novel sub-goals is essential for the agent to ultimately find the pathway to the

Ming Tong, Yongzhen Wang, Peng Cui, Xuefeng Yan

Image dehazing is fundamental yet not well-solved in computer vision. Most cutting-edge models are trained in synthetic data, leading to the poor performance on real-world hazy scenarios. Besides, they commonly give deterministic dehazed images while neglecting to mine their uncertainty. To bridge the domain gap and enhance the dehazing performance, we propo

Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

Have you ever imagined what a corgi-alike coffee machine or a tiger-alike rabbit would look like? In this work, we attempt to answer these questions by exploring a new task called semantic mixing, aiming at blending two different semantics to create a new concept (e.g., corgi + coffee machine -- > corgi-alike coffee machine). Unlike style transfer, where an

Ayesha Tasnim, Md. Mahamudujjaman, Md. Asif Afzal, R. S. Islam

Density functional theory based study of the pressure dependent physical properties of binary SnS compound has been carried out. The computed elastic constants reveal that SnS is mechanically stable and brittle under ambient conditions. With increasing pressure, the compound becomes ductile. The Poisson's ratio also indicates brittle-ductile transition with

S. D. Balika

The work discusses the problem of measurement of the zeta-potential for electrolyte-based suspensions of nanoparticle. A theory is presented for the effect of the diffuse electric double layer, including the interphase (stagnant) layer, on the effective conductivity of such suspensions. The theory is based on the method of compact groups of inhomogeneities a

Linus Kreitner, Ivan Ezhov, Daniel Rueckert, Johannes C. Paetzold

Recent studies suggest that early stages of diabetic retinopathy (DR) can be diagnosed by monitoring vascular changes in the deep vascular complex. In this work, we investigate a novel method for automated DR grading based on optical coherence tomography angiography (OCTA) images. Our work combines OCTA scans with their vessel segmentations, which then serve

Federico Gasparotto, Andreas Rapakoulias, Stefan Weinzierl

We show that methods developed in the context of perturbative calculations can be transferred to non-perturbative calculations. We demonstrate that correlation functions on the lattice can be computed with the method of differential equations, supplemented with techniques from twisted cohomology. We derive differential equations for the variation with the co

Nnamdi Uzoukwu, Acep Purqon

A fuzzy inference system was developed for predicting the heat index from temperature and relative humidity data. The effectiveness of fuzzy logic in using imprecise mapping of input to output to encode interconnectedness of system variables was exploited to uncover a linguistic model of how the temperature and humidity conditions impact the heat index in a

Jiantao Wu, Fabrizio Orlandi, Declan O'Sullivan, Soumyabrata Dev

Climate science has become more ambitious in recent years as global awareness about the environment has grown. To better understand climate, historical climate (e.g. archived meteorological variables such as temperature, wind, water, etc.) and climate-related data (e.g. geographical features and human activities) are widely used by today's climate research t

Ibai Laña, Ignacio, Olabarrieta, Javier Del Ser

The estimation of the amount of uncertainty featured by predictive machine learning models has acquired a great momentum in recent years. Uncertainty estimation provides the user with augmented information about the model's confidence in its predicted outcome. Despite the inherent utility of this information for the trustworthiness of the user, there is a th

Kari J. Eskola, Christopher A. Flett, Vadim Guzey, Topi Löytäinen

We present predictions for the cross sections of coherent $J/\psi$ photoproduction in lead-lead and oxygen-oxygen ultraperipheral collisions (UPCs) as a function of the $J/\psi$ rapidity at the LHC in the framework of collinear factorization at next-to-leading order (NLO) in perturbative QCD. Taking generalized parton distribution functions in their forward

Kevin Fiederling, Mostafa Abasifard, Martin Richter, Volker Deckert

Tip-enhanced Raman spectroscopy (TERS) is a valuable method for surface analysis with nanometer to angstrom-scale resolution, however, the accurate simulation of particular TERS signals remains a computational challenge. We present a unique approach to this challenge by combining the two main contributors to plasmon-enhanced Raman spectroscopy and to the hig

Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi

Image recognition models that work in challenging environments (e.g., extremely dark, blurry, or high dynamic range conditions) must be useful. However, creating training datasets for such environments is expensive and hard due to the difficulties of data collection and annotation. It is desirable if we could get a robust model without the need for hard-to-o

Jason Fong, Yun Wang, Prabhav Agrawal, Vimal Manohar

Text-based voice editing (TBVE) uses synthetic output from text-to-speech (TTS) systems to replace words in an original recording. Recent work has used neural models to produce edited speech that is similar to the original speech in terms of clarity, speaker identity, and prosody. However, one limitation of prior work is the usage of finetuning to optimise p

Chunlin Liu, Kesong Yan

We study the sequence entropy for amenable group actions and investigate systematically spectrum and several mixing concepts via sequence entropy both in measure-theoretic dynamical systems and topological dynamical systems. Moreover, we use sequence entropy pairs to characterize weakly mixing and null systems.

Ramon Sanabria, Hao Tang, Sharon Goldwater

Given the strong results of self-supervised models on various tasks, there have been surprisingly few studies exploring self-supervised representations for acoustic word embeddings (AWE), fixed-dimensional vectors representing variable-length spoken word segments. In this work, we study several pre-trained models and pooling methods for constructing AWEs wit

Alain-Philippe Fortin, Patrick Gagliardini, Olivier Scaillet

This paper studies new tests for the number of latent factors in a large cross-sectional factor model with small time dimension. These tests are based on the eigenvalues of variance-covariance matrices of (possibly weighted) asset returns, and rely on either the assumption of spherical errors, or instrumental variables for factor betas. We establish the asym

Yiping Liu, Jiamou Liu, Bakhadyr Khoussaino, Miao Qiao

This paper aims to provide a new perspective on the interplay between decentralization -- a prevalent character of multi-agent systems -- and centralization, i.e., the task of imposing central control to meet system-level goals. In particular, in the context of networked opinion dynamic model, the paper proposes and discusses a framework for centralization.

Talha Iqbal, Adnan Elahi, Atif Shahzad, William Wijns

Cardiovascular activities are directly related to the response of a body in a stressed condition. Stress, based on its intensity, can be divided into two types i.e. Acute stress (short-term stress) and Chronic stress (long-term stress). Repeated acute stress and continuous chronic stress may play a vital role in inflammation in the circulatory system and thu

Paul Blochas, Aric Wheeler

For the ZND model, we show also singularity formation on the downstream side for arbitrary exponentially-growing weighted norms. For the Majda model on the other hand, we establish for appropriate such weighted norms a set of energy estimates implying not only non-formation of singularities near waves of arbitrary amplitude but also full asymptotic orbital s

Max Muzeau, Chengfang Ren, Sébastien Angelliaume, Mihai Datcu

In this paper, we proposed to investigate unsupervised anomaly detection in Synthetic Aperture Radar (SAR) images. Our approach considers anomalies as abnormal patterns that deviate from their surroundings but without any prior knowledge of their characteristics. In the literature, most model-based algorithms face three main issues. First, the speckle noise

Krishna Nandipati, Oriol Vendrell

We investigate Jahn-Teller (JT) polaritons, which emerge from the interaction of the two normal-incidence electromagnetic modes with perpendicular polarizations in a Fabry-Perot cavity resonator with JT active systems. These JT polaritons are characterized by a mixed $(+/-)$--circular electromagnetic polarization that originates from the molecular JT vibroni

Jaskirat Brar, Saurabh Singh, Kentaro Kuga, Priyamedha Sharma

We investigate the unusual phase transitions in SrRuO$_{3}$ and Sr$_{0.5}$Ca$_{0.5}$Ru$_{1-x}$Cr$_{x}$O$_{3}$ (x=0,0.05 and 0.1) employing x-ray diffraction, resistivity, magnetic studies and x-ray photoemission spectroscopy. Our results show the compounds undergo crossover from $itinerant$ ferromagnetism to $localised$ ferromagnetism. The combined studies s