November 2022 arXiv papers — page 100

Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad

Fine-scale covariate rasters are routinely used in geostatistical models for mapping demographic and health indicators based on household surveys from the Demographic and Health Surveys (DHS) program. However, the geostatistical analyses ignore the fact that GPS coordinates in DHS surveys are jittered for privacy purposes. We demonstrate the need to account

Min-Hsuan Yeh, Vicent Chen, Ting-Hao 'Kenneth' Haung, Lun-Wei Ku

Generating engaging content has drawn much recent attention in the NLP community. Asking questions is a natural way to respond to photos and promote awareness. However, most answers to questions in traditional question-answering (QA) datasets are factoids, which reduce individuals' willingness to answer. Furthermore, traditional visual question generation (V

Sergio Romero-Tapiador, Ruben Tolosana, Aythami Morales, Julian Fierrez

Maintaining a healthy lifestyle has become increasingly challenging in today's sedentary society marked by poor eating habits. To address this issue, both national and international organisations have made numerous efforts to promote healthier diets and increased physical activity. However, implementing these recommendations in daily life can be difficult, a

André Hernandes Alves Malavazi

In this thesis, we focus on the energetic analysis within autonomous quantum systems. To this aim, we propose a novel and general formalism for a dynamic description of the energy exchanges between interacting subsystems. From the Schmidt decomposition approach, we identify effective Hamiltonians as the representative operators for characterizing the local i

Pooja Devi, Ramesh Chandra, Arun Kumar Awasthi, Brigitte Schmieder

We present the observations of an extreme-ultraviolet (EUV) wave, which originated from the active region (AR) NOAA 12887 on 28 October 2021 and its impact on neighbouring loops. The event was observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) satellite at various wavebands and by the Solar TErrestrial RElations

Ralfy Kenaz, Saptarshi Ghosh, Pradheesh Ramachandran, Kenji Watanabe

As properties of mono- to few layers of exfoliated van der Waals heterostructures are heavily dependent on their thicknesses, accurate thickness measurement becomes imperative in their study. Commonly used atomic force microscopy and Raman spectroscopy techniques may be invasive and produce inconclusive results. Alternatively, spectroscopic ellipsometry is l

William F. Godoy, Ritu Arora, Keith Beattie, David E. Bernholdt

The Better Scientific Software Fellowship (BSSwF) was launched in 2018 to foster and promote practices, processes, and tools to improve developer productivity and software sustainability of scientific codes. BSSwF's vision is to grow the community with practitioners, leaders, mentors, and consultants to increase the visibility of scientific software producti

Torgeir Dingsøyr, Magne Jørgensen, Frode Odde Carlsen, Lena Carlström

In this article, we give advice on transitioning to a more agile delivery model for large-scale agile development projects based on experience from the Parental Benefit Project of the Norwegian Labour and Welfare Administration. The project modernized a central part of the organizations IT portfolio and included up to ten development teams working in paralle

Omar S. Alolayan, Abdullah O. Alomar, John R. Williams

Reformulating the history matching problem from a least-square mathematical optimization problem into a Markov Decision Process introduces a method in which reinforcement learning can be utilized to solve the problem. This method provides a mechanism where an artificial deep neural network agent can interact with the reservoir simulator and find multiple dif

Pranay Bhardwaj, Eesha Santosh Karnawat, S. M. Zafaruddin

The $\alpha$-$\eta$-$\kappa$-$\mu$ is one of the most generalized and flexible channel models having an excellent fit to experimental data from diverse propagation environments. The existing statistical results on the envelope of $\alpha$-$\eta$-$\kappa$-$\mu$ model contain an infinite series involving regularized hypergeometric function and generalized Lagu

Adrien Bourgoin, Etienne Savalle, Christophe Le Poncin-Lafitte, Stéphane Mathis

The LISA (Laser Interferometer Space Antenna) mission will observe in the low frequency band from 0.1 mHz to 1 Hz. In this regime, we expect the galactic binaries to be the dominant (by number) sources of gravitational waves signal. Considering that galactic binaries are composed of the most magnetized astrophysical objects in the universe (i.e., the white d

Ioanna Bouri, Manu Lahariya, Omer Nivron, Enrique Portales Julia

Reliable prediction of river floods in the first 72 hours can reduce harm because emergency agencies have sufficient time to prepare and deploy for help at the scene. Such river flood prediction models already exist and perform relatively well in most high-income countries. But, due to the limited availability of data, these models are lacking in low-income

David A. Bloore, Romane Gauriau, Anna L. Decker, Jacob Oppenheim

Electronic health records (EHR) are widely believed to hold a profusion of actionable insights, encrypted in an irregular, semi-structured format, amidst a loud noise background. To simplify learning patterns of health and disease, medical codes in EHR can be decomposed into semantic units connected by hierarchical graphs. Building on earlier synergy between

Rafal Madonski, Gernot Herbst, Momir Stankovic

In this work, we investigate two specific linear ADRC structures, namely output- and error-based. The former is considered a 'standard' version of ADRC, a title obtained primarily thanks to its simplicity and effectiveness, which have spurred its adoption across multiple industries. The latter is found to be especially appealing to practitioners as its feedb

E. A. Schneidmiller, I. J. Bermudez Macias, M. Beye, M. Braune

FLASH is the first soft X-ray FEL user facility, routinely providing brilliant photon beams for users since 2005. The second undulator branch of this facility, FLASH2, is gap-tunable which allows to test and use advanced lasing concepts. In particular, we developed a two-color operation mode based on the alternatingly tuned undulator segments (every other se

Eduard Chelebian, Francesco Ciompi, Carolina Wählby

Annotations are necessary to develop computer vision algorithms for histopathology, but dense annotations at a high resolution are often time-consuming to make. Deep learning models for segmentation are a way to alleviate the process, but require large amounts of training data, training times and computing power. To address these issues, we present seeded it

Susana J. Landau, Micol Benetti, Alejandro Perez, Daniel Sudarsky

A discrete space-time structure lying at about the Planck scale may become manifest in the form of very small violations of the conservation of the matter energy-momentum tensor. In order to include such kind of violations, forbidden within the General Relativity framework, the theory of unimodular gravity seems as the simplest option to describe the gravita

Mercè Roig, Astrid T. Rømer, P. J. Hirschfeld, Brian M. Andersen

The leading superconducting instabilities of the two-dimensional extended repulsive one-band Hubbard model within spin-fluctuation pairing theory depend sensitively on electron density, band and interaction parameters. We map out the phase diagrams within a random phase approximation (RPA) spin- and charge-fluctuation approach, and find that while $B_{1g}$ (

Corentin Salaün, Adrien Gruson, Binh-Son Hua, Toshiya Hachisuka

Monte Carlo integration is typically interpreted as an estimator of the expected value using stochastic samples. There exists an alternative interpretation in calculus where Monte Carlo integration can be seen as estimating a \emph{constant} function -- from the stochastic evaluations of the integrand -- that integrates to the original integral. The integral

Tomoki Nakanishi, Takahiro Nishinaka

We study the compactification of 4D $\mathcal{N}=3$ superconformal field theories (SCFTs) on $S^1$, focusing on the relation between the 4D superconformal index and 3D partition function on the squashed sphere $S^3_b$. Since the center $\mathfrak{u}(1)$ of the $\mathfrak{u}(3)$ R-symmetry of the 4D theory can mix with an $\mathcal{N}=6$ abelian flavor symmet

Aruane M. Pineda, Caroline L. Alves, Colm Connaughton, Francisco A. Rodrigues

The inference of outcomes in dynamic processes from structural features of systems is a crucial endeavor in network science. Recent research has suggested a machine learning-based approach for the interpretation of dynamic patterns emerging in complex network systems. The hypothesis is applied in this study towards showing opinions can be classified in the v

Zeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster

We study the problem of Reinforcement Learning (RL) with linear function approximation, i.e. assuming the optimal action-value function is linear in a known $d$-dimensional feature mapping. Unfortunately, however, based on only this assumption, the worst case sample complexity has been shown to be exponential, even under a generative model. Instead of making

José Carlos Neves de Araujo, Hemily Gomes Marciano Fortes

The mass of compact objects in General Relativity (GR), which as is well known, is obtained via the Tolman - Oppenheimer - Volkov (TOV) equations, is a well defined quantity. However, in alternative gravity, this is not in general the case. In the particular case of $f(T)$ gravity, where $T$ is the scalar torsion, some authors consider that this is still an

Pedro Dal Bianco, Gastón Ríos, Franco Ronchetti, Facundo Quiroga

Sign language translation (SLT) is an active field of study that encompasses human-computer interaction, computer vision, natural language processing and machine learning. Progress on this field could lead to higher levels of integration of deaf people. This paper presents, to the best of our knowledge, the first continuous Argentinian Sign Language (LSA) da

Jacco Vink, Aya Bamba

Shocks of supernova remnants (SNRs) accelerate charged particles up to 100 TeV range via diffusive shock acceleration (DSA) mechanism. It is believed that shocks of SNRs are the main contributors to the pool of Galactic cosmic rays, although it is still under debate whether they can accelerate particles up to the "knee" energy (10^15.5 eV) or not. In this ch

Simon Weber

In this paper, I develop an integrated approach to collective models and matching models of the marriage market. In the collective framework, both household formation and the intra-household allocation of bargaining power are taken as given. This is no longer the case in the present contribution, where both are endogenous to the determination of equilibrium

Valentina Vadori, Jean-Marie Graïc, Livio Finos, Livio Corain

In comparative neuroanatomy, the characterization of brain cytoarchitecture is critical to a better understanding of brain structure and function, as it helps to distill information on the development, evolution, and distinctive features of different populations. The automatic segmentation of individual brain cells is a primary prerequisite and yet remains c

Andreas Baer, Paolo Malgaretti, Malte Kaspereit, Jens Harting

Accurate modeling of diffusive transport of nanoparticles across nanopores is a particularly challenging problem. The reason is that for such narrow pores the large surface-to-volume ratio amplifies the relevance of the nanoscopic details and of the effective interactions at the interface with pore walls. Close to the pore wall, there is no clear separation

Onur Poyraz, Mohamad R. A. Sater, Loren G. Miller, James A. Mckinnell

MRSA colonization is a critical public health concern. Decolonization protocols have been designed for the clearance of MRSA. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Here, we formulate a machine learning mo

Andrea Civilini, Vito Latora

We propose a dynamical model of price formation on a spatial market where sellers and buyers are placed on the nodes of a graph, and the distribution of the buyers depends on the positions and prices of the sellers. We find that, depending on the positions of the sellers and on the level of information available, the price dynamics of our model can either co

Aren Karapetyan, Anastasios Tsiamis, Efe C. Balta, Andrea Iannelli

The setting of an agent making decisions under uncertainty and under dynamic constraints is common for the fields of optimal control, reinforcement learning, and recently also for online learning. In the online learning setting, the quality of an agent's decision is often quantified by the concept of regret, comparing the performance of the chosen decisions

N. Narayanan, Sagar S. Sawant

The $B$-polynomial defined by J. Awan and O. Bernardi is a generalization of Tutte Polynomial to digraphs. In this paper, we solve an open question raised by J. Awan and O. Bernardi regarding the expansion of $B$-polynomial in elementary symmetric polynomials. We show that the quasisymmetric generalization of the $B$-polynomial distinguishes a class of orien

Steven Tomsovic, Juan Diego Urbina, Klaus Richter

One of the principal goals of controlling classical chaotic dynamical systems is known as targeting, which is the very weakly perturbative process of using the system's extreme sensitivity to initial conditions in order to arrive at a predetermined target state. It is shown that a generalization to chaotic quantum systems is possible in the semiclassical reg

Pascal Koiran, Subhayan Saha

We study symmetric tensor decompositions, i.e. decompositions of the input symmetric tensor T of order 3 as sum of r 3rd-order tensor powers of u_i where u_i are vectors in \C^n. In order to obtain efficient decomposition algorithms, it is necessary to require additional properties from the u_i. In this paper we assume that the u_i are linearly independent.

Ying-Ming Xie, K. T. Law

In this work, we study superconducting moir\'e homobilayer transition metal dichalcogenides where the Ising spin-orbit coupling (SOC) is much larger than the moir\'e bandwidth. We call such noncentrosymmetric superconductors, moir\'e Ising superconductors. Due to the large Ising SOC, the depairing effect caused by the Zeeman field is negligible and the in-pl

Evgeny Derishev

For an expanding spherical relativistic shock, we derive relations between the parameters of downstream emitting zone and the quantities measured by a distant observer. These relations are formulated in terms of dimensionless effective coefficients combined with self-evident dimensional estimates. Our calculations take into account evolution of the shock's L

David O. Zisselman

Over the course of the last 50 years, many questions in the field of computability were left surprisingly unanswered. One example is the question of $P$ vs $NP\cap co-NP$. It could be phrased in loose terms as "If a person has the ability to verify a proof and a disproof to a problem, does this person know a solution to that problem?". When talking about peo

Jiří Wollmann, Petr Heinzel, Petr Kabáth

Stellar flares are energetic events occurring in stellar atmospheres. They have been observed on various stars using photometric light curves and spectra. On some cool stars, flares tend to release substantially more energy compared to solar flares. Spectroscopic observations have revealed that some spectral lines, aside from an enhancement and broadening, e

Komlan Payne

A low-profile, modified Complementary Frequency Selective Surface (CFSS) with dual band-pass characteristic is presented. This technique adds independent control of the operation bands, which was a limitation from previous FSSs design based on CFSS concept. The FSS structure utilizes resonant elements and interaction between the layers to deliverer the first

Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante

Learning anatomical segmentation from heterogeneous labels in multi-center datasets is a common situation encountered in clinical scenarios, where certain anatomical structures are only annotated in images coming from particular medical centers, but not in the full database. Here we first show how state-of-the-art pixel-level segmentation models fail in naiv

Yiyang Chen, Zhedong Zheng, Wei Ji, Leigang Qu

We investigate composed image retrieval with text feedback. Users gradually look for the target of interest by moving from coarse to fine-grained feedback. However, existing methods merely focus on the latter, i.e., fine-grained search, by harnessing positive and negative pairs during training. This pair-based paradigm only considers the one-to-one distance

Isabella Degen, Zahraa S. Abdallah

Type 1 Diabetes (T1D) is a chronic condition where the body produces little or no insulin, a hormone required for the cells to use blood glucose (BG) for energy and to regulate BG levels in the body. Finding the right insulin dose and time remains a complex, challenging and as yet unsolved control task. In this study, we use the OpenAPS Data Commons dataset,

Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros

We consider control of dynamical systems through the lens of competitive analysis. Most prior work in this area focuses on minimizing regret, that is, the loss relative to an ideal clairvoyant policy that has noncausal access to past, present, and future disturbances. Motivated by the observation that the optimal cost only provides coarse information about t

Stephen McWade, Mark F. Flanagan, Arman Farhang

Orthogonal time frequency space (OTFS) modulation has recently emerged as a potential 6G candidate waveform which provides improved performance in high-mobility scenarios. In this paper we investigate the combination of OTFS with non-orthogonal multiple access (NOMA). Existing equalization and detection methods for OTFS-NOMA, such as minimum-mean-squared err

Steven Bilaj, Sofien Dhouib, Setareh Maghsudi

We consider the problem of contextual multi-armed bandits in the setting of hypothesis transfer learning. That is, we assume having access to a previously learned model on an unobserved set of contexts, and we leverage it in order to accelerate exploration on a new bandit problem. Our transfer strategy is based on a re-weighting scheme for which we show a re

Marek Wodzinski, Artur Jurgas, Niccolo Marini, Manfredo Atzori

Registration of brain scans with pathologies is difficult, yet important research area. The importance of this task motivated researchers to organize the BraTS-Reg challenge, jointly with IEEE ISBI 2022 and MICCAI 2022 conferences. The organizers introduced the task of aligning pre-operative to follow-up magnetic resonance images of glioma. The main difficul

Ricardo Ortiz, Geza Giedke, Thomas Frederiksen

Poly(indenoindenes) are {\pi}-conjugated ladder carbon polymers with alternating hexagons and pentagons hosting one unpaired electron for each five-membered ring in the open-shell limit. Here we study the main magnetic interactions that are present in finite oligo(indenoindenes) (OInIn), classifying the six possible isomers in two different classes of three

Juan I. Pisula, Katarzyna Bozek

In digital pathology, Whole Slide Image (WSI) analysis is usually formulated as a Multiple Instance Learning (MIL) problem. Although transformer-based architectures have been used for WSI classification, these methods require modifications to adapt them to specific challenges of this type of image data. Among these challenges is the amount of memory and comp

M. Ibsen, C. Rathgeb, F. Brechtel, R. Klepp

Face recognition systems are widely deployed for biometric authentication. Despite this, it is well-known that, without any safeguards, face recognition systems are highly vulnerable to presentation attacks. In response to this security issue, several promising methods for detecting presentation attacks have been proposed which show high performance on exist

Donghyeong Kim, Chaewon Park, Suhwan Cho, Sangyoun Lee

Feature embedding-based methods have shown exceptional performance in detecting industrial anomalies by comparing features of target images with normal images. However, some methods do not meet the speed requirements of real-time inference, which is crucial for real-world applications. To address this issue, we propose a new method called Fast Adaptive Patch

Yuqi Xue

In this paper, we propose a novel strategy for text-independent speaker identification system: Multi-Label Training (MLT). Instead of the commonly used one-to-one correspondence between the speech and the speaker label, we divide all the speeches of each speaker into several subgroups, with each subgroup assigned a different set of labels. During the identif

Anton Gladyshev, Thomas C. Pekin, Marcel Schloz, Benedikt Haas

Ptychography is a computational imaging technique that has risen in popularity in the x-ray and electron microscopy communities in the past half decade. One of the reasons for this success is the development of new high performance electron detectors with increased dynamic range and readout speed, both of which are necessary for a successful application of t

Fadi Boutros, Marcel Klemt, Meiling Fang, Arjan Kuijper

Over the past years, the main research innovations in face recognition focused on training deep neural networks on large-scale identity-labeled datasets using variations of multi-class classification losses. However, many of these datasets are retreated by their creators due to increased privacy and ethical concerns. Very recently, privacy-friendly synthetic

Hércules Santana, E. V. L. de Mello

At the beginning of cuprate superconductors, the interlayer tunneling (ILT) and Lawrence-Doniach (L-D) models, which connect the CuO planes by Josephson coupling were considered the leading theoretical proposals for these materials. However, measurements of the interlayer magnetic penetration depth $\lambda_{c}$ yielded larger values than required by the ILT

Eren Arkangil, Mehmet Yildirimoglu, Jiwon Kim, Carlo Prato

Census and Household Travel Survey datasets are regularly collected from households and individuals and provide information on their daily travel behavior with demographic and economic characteristics. These datasets have important applications ranging from travel demand estimation to agent-based modeling. However, they often represent a limited sample of th

J. P. Carlomagno, S. A. Ferraris, D. Gómez Dumm, A. G. Grunfeld

We study the phase diagram in the $T-\mu$ plane for quark matter under the influence of a strong uniform magnetic field $\vec{B}$, in the framework of a non-local extension of the two-flavor Polyakov Nambu-Jona-Lasinio model. We analyze the deconfinement and chiral symmetry restoration transitions in the mean field approximation. For the considered parameter

George Macgregor, Barbara S. Lancho-Barrantes, Diane Rasmussen Pennington

The increasing centrality of persistent identifiers (PIDs) to scholarly ecosystems and the contribution they can make to the burgeoning 'PID graph' has the potential to transform scholarship. Despite their importance as originators of PID data, little is known about researchers' awareness and understanding of PIDs, or their efficacy in using them. In this ar

Matthew Wheeler, Suleiman Saka, Sanchari Das

A website browser cookie is a small file created by a web server upon visitation, which is placed in the user's browser directory to enhance the user's experience. However, first and third-party cookies have become a significant threat to users' privacy due to their data collection methods. To understand the users' perception of the risk of cookies and targe

Huai Yu, Hao Li, Wen Yang, Lei Yu

Making line segment detectors more reliable under motion blurs is one of the most important challenges for practical applications, such as visual SLAM and 3D reconstruction. Existing line segment detection methods face severe performance degradation for accurately detecting and locating line segments when motion blur occurs. While event data shows strong com

Yi Liu, Song Guo, Jie Zhang, Qihua Zhou

To eliminate the requirement of fully-labeled data for supervised model training in traditional Federated Learning (FL), extensive attention has been paid to the application of Self-supervised Learning (SSL) approaches on FL to tackle the label scarcity problem. Previous works on Federated SSL generally fall into two categories: parameter-based model aggrega

Kaiwei Zhang, Xi Weng, Xienan Cheng

A monopoly platform sells either a risky product (with unknown utility) or a safe product (with known utility) to agents who sequentially arrive and learn the utility of the risky product by the reporting of previous agents. It is costly for agents to report utility; hence the platform has to design both the prices and the reporting bonus to motivate the age

Marc Brachet, Georges Sadaka, Zhentong Zhang, Victor Kalt

Numerical methods for solving the Navier-Stokes equations for classical (or normal) viscous fluids are well established. This is also the case for the Gross-Pitaevskii equation, governing quantum inviscid flows (or superfluids) in the zero temperature limit. In quantum flows, like liquid helium II at intermediate temperatures between zero and 2.17 K, a norma

Gideon Uchehara, Tor M. Aamodt, Olivia Di Matteo

Recent works have demonstrated that large quantum circuits can be cut and decomposed into smaller clusters of quantum circuits with fewer qubits that can be executed independently on a small quantum computer. Classical post-processing then combines the results from each cluster to reconstruct the output of the original quantum circuit. However, the runtime f

Valentina Guglielmi

In high-energy particle physics, complex Monte Carlo (MC) simulations are needed to compare theory predictions to measurable quantities. Many and large MC samples are needed to be generated to take into account all the systematics. Therefore, the MC statistics (and hence the MC modeling uncertainties) become a limiting factor for most measurements. Moreover,

Nicholas Defilippis, Shari Moskow, John C. Schotland

We consider the Born and inverse Born series for scalar waves with a cubic nonlinearity of Kerr type. We find a recursive formula for the operators in the Born series and prove their boundedness. This result gives conditions which guarantee convergence of the Born series, and subsequently yields conditions which guarantee convergence of the inverse Born seri

Yiran Liu, Xiao Liu, Haotian Chen, Yang Yu

Gender bias in language models has attracted sufficient attention because it threatens social justice. However, most of the current debiasing methods degraded the model's performance on other tasks while the degradation mechanism is still mysterious. We propose a theoretical framework explaining the three candidate mechanisms of the language model's gender b

Xiaozhi Wang, Kaiyue Wen, Zhengyan Zhang, Lei Hou

Transformer-based pre-trained language models have demonstrated superior performance on various natural language processing tasks. However, it remains unclear how the skills required to handle these tasks distribute among model parameters. In this paper, we find that after prompt tuning for specific tasks, the activations of some neurons within pre-trained T

Margarita Chasapi, Pablo Antolin, Annalisa Buffa

This contribution explores the combined capabilities of reduced basis methods and IsoGeometric Analysis (IGA) in the context of parameterized partial differential equations. The introduction of IGA enables a unified simulation framework based on a single geometry representation for both design and analysis. The coupling of reduced basis methods with IGA has

Claudia Bongiovanni, Nikolas Geroliminis, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theory, aims at finding minimal user ride time schedules in polynomial time. The algorithm can either return

Bofeng Wu

The multipole expansions for massive vector and symmetric tensor fields in the region outside spatially compact stationary sources are obtained by using the symmetric and trace-free formalism in terms of the irreducible Cartesian tensors, and the closed-form expressions for the source multipole moments are provided. The expansions show a Yukawa-like dependen

Afra Amini, Ryan Cotterell

There have been many proposals to reduce constituency parsing to tagging in the literature. To better understand what these approaches have in common, we cast several existing proposals into a unifying pipeline consisting of three steps: linearization, learning, and decoding. In particular, we show how to reduce tetratagging, a state-of-the-art constituency

Pengyu Cheng, Ruineng Li

We introduce replacing language model (RLM), a sequence-to-sequence language modeling framework for text style transfer (TST). Our method autoregressively replaces each token of the source sentence with a text span that has a similar meaning but in the target style. The new span is generated via a non-autoregressive masked language model, which can better pr

Jiaxin Ye, Xin-cheng Wen, Yujie Wei, Yong Xu

Speech emotion recognition (SER) plays a vital role in improving the interactions between humans and machines by inferring human emotion and affective states from speech signals. Whereas recent works primarily focus on mining spatiotemporal information from hand-crafted features, we explore how to model the temporal patterns of speech emotions from dynamic t

Xiaozhi Wang, Yulin Chen, Ning Ding, Hao Peng

The diverse relationships among real-world events, including coreference, temporal, causal, and subevent relations, are fundamental to understanding natural languages. However, two drawbacks of existing datasets limit event relation extraction (ERE) tasks: (1) Small scale. Due to the annotation complexity, the data scale of existing datasets is limited, whic

Giuseppe Belgioioso, Dominic Liao-McPherson, Mathias Hudoba de Badyn, Nicolas Pelzmann

In distributed model predictive control (MPC), the control input at each sampling time is computed by solving a large-scale optimal control problem (OCP) over a finite horizon using distributed algorithms. Typically, such algorithms require several (virtually, infinite) communication rounds between the subsystems to converge, which is a major drawback both c

O. I. Piskounova

The positive hyperon production asymmetries that have been measured at LHC are real demonstrations of string junction role in the baryon charge transfer at baryon production in HE proton-proton interactions. In order to invent the neutral heavy particle with zero baryon charge as a candidate for Dark Matter, it is necessary to turn back to the times of dual

Po Jui Shih, Hassaan Saadat, Sri Parameswaran, Hasindu Gamaarachchi

Third-generation nanopore sequencers offer a feature called selective sequencing or 'Read Until' that allows genomic reads to be analyzed in real-time and abandoned halfway, if not belonging to a genomic region of 'interest'. This selective sequencing opens the door to important applications such as rapid and low-cost genetic tests. The latency in analyzing

Vishal Parmar, H. C. Das, M. K. Sharma, S. K. Patra

Even though the crystallize nature of the neutron star crust plays a pivotal role in describing various fascinating astrophysical observations, its microscopic structure is not fully understood in the presence of a colossal magnetic field. In the present work, we study the crustal properties of a neutron star within an effective relativistic mean field frame

Mahmood Zeheiry

In this paper, firstly considering that in separable states, the measurement of one particle has no effect on the measurement of the second particle, we show that Alice and Bob can find directions in which the results of their measurements on the spin of the particle are always maximized. In other words, the state of the particle is an eigenstate for the ope

Philipp Dominic Siedler

We approach autonomous drone-based reforestation with a collaborative multi-agent reinforcement learning (MARL) setup. Agents can communicate as part of a dynamically changing network. We explore collaboration and communication on the back of a high-impact problem. Forests are the main resource to control rising CO2 conditions. Unfortunately, the global fore

H. Krásná, L. Baldreich, J. Böhm, S. Böhm

Context: We introduce the computation of global reference frames from Very Long Baseline Interferometry (VLBI) observations at the Vienna International VLBI Service for Geodesy and Astrometry (IVS) Analysis Center (VIE) in detail. We focus on the celestial and terrestrial frames from our two latest solutions VIE2020 and VIE2022b. Aims: The current Internatio

Ion Santra, Urna Basu, Sanjib Sabhapandit

We study the long-time asymptotic behavior of the position distribution of a run-and-tumble particle (RTP) in two dimensions and show that the distribution at a time $t$ can be expressed as a perturbative series in $(\gamma t)^{-1}$, where $\gamma^{-1}$ is the persistence time of the RTP. We show that the higher order corrections to the leading order Gaussia

Mohamed Amine Kerkouri, Marouane Tliba, Aladine Chetouani, Alessandro Bruno

The visual scanpath is a sequence of points through which the human gaze moves while exploring a scene. It represents the fundamental concepts upon which visual attention research is based. As a result, the ability to predict them has emerged as an important task in recent years. In this paper, we propose an inter-observer consistent adversarial training app

Tongzhou Zhao, Ajit C. Balram, J. K. Jain

Pairing of composite fermions provides a possible mechanism for fractional quantum Hall effect at even denominator fractions and is believed to serve as a platform for realizing quasiparticles with non-Abelian braiding statistics. We present results from fixed-phase diffusion Monte Carlo calculations which predict that substantial Landau level mixing can ind

Lukasz Wolanski, Wojciech Grochala

In 2000, a remarkably simple relationship was introduced, which connected the calculated geometries of isomolecular states of three different multiplicities. These encompass a ground singlet state, the first excited triplet state, as well as related radical anion and radical cation. The rule allows prediction of geometry of one of the species if the three re

N. Deg, K. Spekkens, T. Westmeier, T. N. Reynolds

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I HI kinematic models. This first data release consists of HI observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic mode

Jian-Peng Wang, Qin Qin, Fu-Sheng Yu

In this letter, we propose a novel approach to concurrently measure the complementary $CP$ violation observables induced by $T$-odd correlations and their corresponding $T$-even counterparts, where $T$ represents time reversal. Our analysis demonstrates that $T$-odd and -even correlations, when satisfying specific conditions, result in cosine and sine strong

Chia-Ying Shih, Chi-Han Peng

Computational methods to compute similarities between floor plans can help architects explore floor plans in large datasets to avoid duplication of designs and to search for existing plans that satisfy their needs. Recently, LayoutGMN delivered state-of-the-art performance for computing similarity scores between floor plans. However, the high computational c

Mayar Elfares, Zhiming Hu, Pascal Reisert, Andreas Bulling

Gaze estimation methods have significantly matured in recent years, but the large number of eye images required to train deep learning models poses significant privacy risks. In addition, the heterogeneous data distribution across different users can significantly hinder the training process. In this work, we propose the first federated learning approach for

Prasenjit Ghosh

We introduce the notion of a generalized fusion frame in quaternionic Hilbert space. A characterization of generalized fusion frame in quaternionic Hilbert space with the help of frame operator is being discussed. Finally, we construct g-fusion frame in quaternionic Hilbert space using invertible bounded right Q-linear operator on quaternionic Hilbert space.

Mohamed Abdalmoaty, Sribalaji C. Anand, André M. H. Teixeira

In this paper, we propose a new architecture to enhance the privacy and security of networked control systems against malicious adversaries. We consider an adversary which first learns the system dynamics (privacy) using system identification techniques, and then performs a data injection attack (security). In particular, we consider an adversary conducting

Tommaso d'Orsi, Rajai Nasser, Gleb Novikov, David Steurer

We consider estimation models of the form $Y=X^*+N$, where $X^*$ is some $m$-dimensional signal we wish to recover, and $N$ is symmetrically distributed noise that may be unbounded in all but a small $\alpha$ fraction of the entries. We introduce a family of algorithms that under mild assumptions recover the signal $X^*$ in all estimation problems for which

Sarah Wettermann, Ranajay Datta, Peter Virnau

We investigate knotting probabilities of long double-stranded DNA strands in a coarse-grained Kratky-Porod model for DNA with Monte Carlo simulations. Various ionic conditions are implemented by adjusting the effective diameter of monomers. We find that the occurrence of knots in DNA can be reinforced considerably by high salt conditions and confinement betw

Tomasz Kociumaka, Adam Polak

This paper is about the problem of finding a shortest $s$-$t$ path using at most $h$ edges in edge-weighted graphs. The Bellman--Ford algorithm solves this problem in $O(hm)$ time, where $m$ is the number of edges. We show that this running time is optimal, up to subpolynomial factors, under popular fine-grained complexity assumptions. More specifically, we

Alice Eltvedt, T. Shanks, N. Metcalfe, B. Ansarinejad

We present the VST ATLAS Quasar Survey, consisting of $\sim1,229,000$ quasar (QSO) candidates with $16<g<22.5$ over $\sim4700$ deg$^2$. The catalogue is based on VST ATLAS$+$NEOWISE imaging surveys and aims to reach a QSO sky density of $130$ deg$^{-2}$ for $z<2.2$ and $\sim30$ deg$^{-2}$ for $z>2.2$. One of the aims of this catalogue is to select QSO target

Matthijs Borst

For a simple graph $\Gamma$ and for unital $C^*$-algebras with GNS-faithful states $(\mathbf{A}_v,\varphi_v)$ for $v\in V\Gamma$, we consider the reduced graph product $(\mathcal{A},\varphi)=*_{v,\Gamma}(\mathbf{A}_{v},\varphi_v)$ , and show that if every $C^*$-algebra $\mathbf{A}_{v}$ has the completely contractive approximation property (CCAP) and satisfie

Liqin Ding, Gonzalo Seco-Granados, Hyowon Kim, Russ Whiton

Bayesian receiver autonomous integrity monitoring (RAIM) algorithms are developed for the snapshot cellular positioning problem in a simplified one-dimensional (1D) linear Gaussian setting. Position estimation, multi-fault detection and exclusion, and protection level (PL) computation are enabled by the efficient and exact computation of the position posteri

Ziyang Ma, Zhisheng Zheng, Changli Tang, Yujin Wang

In this paper, we provide a new perspective on self-supervised speech models from how the training targets are obtained. We generalize the targets extractor into Offline Targets Extractor (Off-TE) and Online Targets Extractor (On-TE). Based on this, we propose a new multi-tasking learning framework for self-supervised learning, MT4SSL, which stands for Boost

Christophe H. Valahu, Vanessa C. Olaya-Agudelo, Ryan J. MacDonell, Tomas Navickas

Conical intersections are ubiquitous in chemistry and physics, often governing processes such as light harvesting, vision, photocatalysis, and chemical reactivity. They act as funnels between electronic states of molecules, allowing rapid and efficient relaxation during chemical dynamics. In addition, when a reaction path encircles a conical intersection, th

Jacob Whitlow, Zhubing Jia, Ye Wang, Chao Fang

Conical intersections are common in molecular physics and photochemistry, and are often invoked to explain observed reaction products. A conical intersection can occur when an excited electronic potential energy surface intersects with the ground electronic potential energy surface in the coordinate space of the nuclear positions. Theory predicts that the co