November 2022 arXiv papers — page 132

Jinpeng Zhang, Chuanqi Dong, Xiangyu Duan, Yuqi Zhang

Word alignment is to find translationally equivalent words between source and target sentences. Previous work has demonstrated that self-training can achieve competitive word alignment results. In this paper, we propose to use word alignments generated by a third-party word aligner to supervise the neural word alignment training. Specifically, source word an

Vinicius Beltram Tergolina, Enrico Calzavarini, Gilmar Mompean, Stefano Berti

Plankton dynamics depend in a complex manner on a variety of physical phenomena, according to both experimental and numerical data. In particular, experimental field studies have highlighted the relation between phytoplankton survival and turbulent upwelling and downwelling from thermal convection. Recent numerical works have also shown the importance of acc

Anirudha Menon, Banasri Basu

Fractals have been at the heart of geophysical and geospatial studies in the recent past. We examine the emergent fractal character of water vapor distributions above the surface of the Earth as a function of both image resolution (number of pixels) and moisture content percentile. We calculate physically relevant quantities such as fractal dimension, number

Lucas Hedström, Ludvig Lizana

The most common gene regulation mechanism is when a transcription factor protein binds to a regulatory sequence to increase or decrease RNA transcription. However, transcription factors face two main challenges when searching for these sequences. First, they are vanishingly short relative to the genome length. Second, many nearly identical sequences are scat

Omer Anjum, Alok Kamatar, Toby Liang, Jinjun Xiong

Assigning qualified, unbiased and interested reviewers to paper submissions is vital for maintaining the integrity and quality of the academic publishing system and providing valuable reviews to authors. However, matching thousands of submissions with thousands of potential reviewers within a limited time is a daunting challenge for a conference program comm

William Seymour, Xiao Zhan, Mark Cote, Jose Such

Since Siri's release in 2011 there have been a growing number of AI-driven domestic voice assistants that are increasingly being integrated into devices such as smartphones and TVs. But as their presence has expanded, a range of ethical concerns has been identified around the use of voice assistants, such as the privacy implications of having devices that ar

Ľubomír Baňas, Michael Röckner, André Wilke

We correct two errors in our paper [4]. First error concerns the definition of the SVI solution, where a boundary term which arises due to the Dirichlet boundary condition, was not included. The second error concerns the discrete estimate [4, Lemma 4.4], which involves the discrete Laplace operator. We provide an alternative proof of the estimate in spatial

Quentin Kral, James Pringle, Luca Matrà, Philippe Thébault

Context: Gas is now detected in many extrasolar systems around mature stars aged between 10 Myr to $\sim$ 1 Gyr with planetesimal belts. Gas in these mature disks is thought to be released from planetesimals and has been modelled using a viscous disk approach. At low densities, this may not be a good assumption as the gas could be blown out by the stellar wi

Shuo-Ying Yu, Xian-Wei Kang, V. O. Galkin

In the framework of the factorization approach we calculate the branching fractions of 100 two-body nonleptonic decay channels in total, including 44 channels of the charm meson decays and 56 channels of the bottom meson decays. For charm meson decays, we test and confirm the previous observation that taking the limit for the number of colors $N\to\infty$ si

The NUCLEUS collaboration, C. Goupy, H. Abele, G. Angloher

The NUCLEUS experiment aims to perform a high-precision measurement of Coherent Elastic Neutrino-Nucleus Scattering (CEvNS) at the EdF Chooz B nuclear power plant in France. CEvNS is a unique process to study neutrino properties and to search for physics beyond the Standard Model. The study of CEvNS is also important for light Dark-Matter searches. It could

Francesco Barbato, Giulia Rizzoli, Pietro Zanuttigh

Most approaches for semantic segmentation use only information from color cameras to parse the scenes, yet recent advancements show that using depth data allows to further improve performances. In this work, we focus on transformer-based deep learning architectures, that have achieved state-of-the-art performances on the segmentation task, and we propose to

Fien Apers

The DGKT vacua are a class of AdS$_4$ flux vacua showing full moduli stabilization, parametric control, and a parametric separation of scales. The particular masses of the moduli remarkably give rise to integer conformal dimensions in the light spectrum of the would-be holographic duals. In this note, we comment on two properties for AdS flux vacua with inte

Kazuyasu Shigemoto

In our previous paper, the logistic curve of the removed number was derived from SIR and SEIR models in the case of the small basic reproduction number. In this paper, we derive various logistic curves of the removed, unsusceptible and infectious numbers respectively from SIS and SIR models in the case of small and large basic reproduction numbers.

Xinyu Zhang, Yuanhao Huang, Kangyao Huang, Ziqi Zhao

A deformable land-air robot is introduced with excellent driving and flying capabilities, offering a smooth switching mechanism between the two modes. An elaborate coupled dynamics model is established for the robot, including rotors, chassis, suspension, and the deformable structure. In addition, a model-based controller is designed for landing and mode swi

Francis X. Diebold, Kamil Yilmaz

We offer retrospective and prospective assessments of the Diebold-Yilmaz connectedness research program, combined with personal recollections of its development. Its centerpiece in many respects is Diebold and Yilmaz (2014), around which our discussion is organized.

Maciej Dworak, Krzysztof Malarz

In this paper, the results of computer simulations based on Nowak--Szamrej--Latan\'e model with multiple (from two to five) opinions available in the system are presented. We introduce the noise discrimination level (which says how small the clusters of agents could be considered as negligible) as a quite useful quantity that allows qualitative characterizat

Alan C. Santos

In this work we study the role of parasitic interactions and microwave crosstalk in a system of two superconducting artificial atoms interacting via a single-mode coplanar waveguide. Through a general description of the effective dynamics of the atoms, beyond the two-level approximation, we show that the atom selectivity (ability to individually address an a

Yulia G. Polynskaya, Irina V. Lebedeva, Andrey A. Knizhnik, Andrey M. Popov

We investigate how parameters of the model of semi-infinite graphene based on a graphene nanoribbon under periodic boundary conditions affect the accuracy of ab initio calculations of reactions at graphene edges by the example of the first stage of reconstruction of zigzag graphene edges, formation of a pentagon-heptagon pair. It is shown that to converge pr

Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann, Daniel Rueckert

The prediction of pancreatic ductal adenocarcinoma therapy response is a clinically challenging and important task in this high-mortality tumour entity. The training of neural networks able to tackle this challenge is impeded by a lack of large datasets and the difficult anatomical localisation of the pancreas. Here, we propose a hybrid deep neural network p

Shenwei Huang, Jiawei Li, Wen Xia

Given two graphs $H_1$ and $H_2$, a graph is $(H_1,H_2)$-free if it contains no induced subgraph isomorphic to $H_1$ or $H_2$. Let $P_t$ and $C_t$ be the path and the cycle on $t$ vertices, respectively. A bull is the graph obtained from a triangle with two disjoint pendant edges. In this paper, we show that there are finitely many 5-vertex-critical ($P_5$,b

P. S. Ens, A. F. Santos

In this work, a way to consider together two originally different corrections to the Friedmann equations is presented. The first is the Barrow entropy, which imposes a fractal structure on the black hole horizon area. While the second is the well-known $f(R)$ gravity, which comes from a generalization of the Einstein-Hilbert action. Using the ideas of gravit

Alisha Marriott-Best

Quantum cosmology uses a wave function to model the universe, but finding solutions for this poses a problem as it is difficult to define the boundary conditions or identify the correct path for a path integral. We begin the discussion by going over various proposals and look at how bubble universe nucleation can be used as an analogy for the tunneling wave

Simone Ricci, Tiberio Uricchio, Alberto Del Bimbo

In this paper, we introduced the novel concept of advisor network to address the problem of noisy labels in image classification. Deep neural networks (DNN) are prone to performance reduction and overfitting problems on training data with noisy annotations. Weighting loss methods aim to mitigate the influence of noisy labels during the training, completely r

H. Lattaud

The Edelweiss collaboration performs light Dark Matter (DM) particles searches with germanium bolometer collecting charge and phonon signals. Thanks to the Neganov-Trofimov-Luke (NTL) effect, a RMS resolution of 4.46 electron-hole pairs was obtained on a massive (200g) germanium detector instrumented with a NbSi Transition Edge Sensor (TES) operated undergro

Fan Mo, Mohammad Malekzadeh, Soumyajit Chatterjee, Fahim Kawsar

Ubiquitous wearable and mobile devices provide access to a diverse set of data. However, the mobility demand for our devices naturally imposes constraints on their computational and communication capabilities. A solution is to locally learn knowledge from data captured by ubiquitous devices, rather than to store and transmit the data in its original form. In

Xiao Fang, Song-Hao Liu

Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional approximations, Stein's method has also been used to prove Edgeworth expansion results. However, these results assume that either

Yunli Li, Changsheng You, Young Jin Chun

Active intelligent reflecting surface (IRS) enables flexible signal reflection control with \emph{power amplification}, thus effectively compensating the product-distance path-loss in conventional passive-IRS aided systems. In this letter, we characterize the communication performance of an active-IRS aided single-cell wireless network. To this end, we first

ATLAS Collaboration

A search for diphoton resonances in the mass range between 10 and 70 GeV with the ATLAS experiment at the Large Hadron Collider (LHC) is presented. The analysis is based on $pp$ collision data corresponding to an integrated luminosity of 138 fb$^{-1}$ at a centre-of-mass energy of 13 TeV recorded from 2015 to 2018. Previous searches for diphoton resonances a

André H. Deutz, Michael T. M. Emmerich, Hao Wang

The problem of approximating the Pareto front of a multiobjective optimization problem can be reformulated as the problem of finding a set that maximizes the hypervolume indicator. This paper establishes the analytical expression of the Hessian matrix of the mapping from a (fixed size) collection of $n$ points in the $d$-dimensional decision space (or $m$ di

Martin Himmel

Motivated by children inventing creatively laws on how to add or multiply fractions, we introduce four fraction operations and discover some of their properties.

Filipe C Thewes, Matthias Krüger, Peter Sollich

Understanding the phase behavior of mixtures with many components is important in many contexts, including as a key step toward a physics-based description of intracellular compartmentalization. Here, we study the instabilities of a mixture model where the second virial coefficients are taken as random Gaussian variables. Using tools from free probability th

Arpit Merchant, Michael Mathioudakis, Yanhao Wang

Graph summarization via node grouping is a popular method to build concise graph representations by grouping nodes from the original graph into supernodes and encoding edges into superedges such that the loss of adjacency information is minimized. Such summaries have immense applications in large-scale graph analytics due to their small size and high query p

Yafeng Chen, Siqi Zheng, Hui Wang, Luyao Cheng

Training robust speaker verification systems without speaker labels has long been a challenging task. Previous studies observed a large performance gap between self-supervised and fully supervised methods. In this paper, we apply a non-contrastive self-supervised learning framework called DIstillation with NO labels (DINO) and propose two regularization term

Rujing Xiong, Xuihui Dong, Tiebin Mi, Kai Wan

This paper studies the beamforming optimization challenge in reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) systems, where the RIS phase configuration is discrete. Conventional optimization methods for this discrete optimization problem necessitate resource-intensive exponential search and thus fall within the universal (N

Chunming Jiang, Yilei Zhang

Sparse representation has attracted great attention because it can greatly save storage resources and find representative features of data in a low-dimensional space. As a result, it may be widely applied in engineering domains including feature extraction, compressed sensing, signal denoising, picture clustering, and dictionary learning, just to name a few.

Marin Kačan, Marko Ševrović, Siniša Šegvić

Road-safety inspection is an indispensable instrument for reducing road-accident fatalities contributed to road infrastructure. Recent work formalizes road-safety assessment in terms of carefully selected risk factors that are also known as road-safety attributes. In current practice, these attributes are manually annotated in geo-referenced monocular video

Tobias Boege

This short expository paper outlines applications of computer algebra to the implication problem of conditional independence for Gaussian random variables. We touch on certificates for validity and invalidity of inference rules from the perspective of reproducibility of research data, computational complexity of the inference problem and draw a parallel to a

Ela Liberman-Pincu, Elmer D. van Grondelle, Tal Oron-Gilad

Robots' visual qualities (VQs) impact people's perception of their characteristics and affect users' behaviors and attitudes toward the robot. Recent years point toward a growing need for Socially Assistive Robots (SARs) in various contexts and functions, interacting with various users. Since SAR types have functional differences, the user experience must va

Ľubomír Baňas, Michael Röckner, André Wilke

We consider fully discrete finite element approximation of the stochastic total variation flow equation (STVF) with linear multiplicative noise which was previously proposed in \cite{our_paper}. Due to lack of a discrete counterpart of stronger a priori estimates in higher spatial dimensions the original convergence analysis of the numerical scheme was limit

Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens

The clinical interest is often to measure the volume of a structure, which is typically derived from a segmentation. In order to evaluate and compare segmentation methods, the similarity between a segmentation and a predefined ground truth is measured using popular discrete metrics, such as the Dice score. Recent segmentation methods use a differentiable sur

Leo Irudayam, Frank Breitinger

This paper analyses the feasibility of including emerging IT-topics into secondary education (K9-12). We developed a class on Blockchain for K9-12 students which delivers relevant content but is also indented to motivate them to further engage with the topic. Our course consists of theory material as well as a hands-on application. Gamification techniques ar

Thomas Pfeil, Miles Cranmer, Shirley Ho, Philip J. Armitage

Planet formation is a multi-scale process in which the coagulation of $\mathrm{\mu m}$-sized dust grains in protoplanetary disks is strongly influenced by the hydrodynamic processes on scales of astronomical units ($\approx 1.5\times 10^8 \,\mathrm{km}$). Studies are therefore dependent on subgrid models to emulate the micro physics of dust coagulation on to

Antoine Gérardin, Jana N. Guenther, Lukas Varnhorst, Willem E. A. Verplanke

We report on our progress toward the computation of the $\pi^0$, $\eta$ and $\eta^{\prime}$ transition form factors using staggered quarks on $N_f=2+1+1$ gauge ensembles generated by the Budapest-Marseille-Wuppertal collaboration. These form factors are essential ingredients to evaluate the pseudoscalar-pole contributions to the hadronic light-by-light scatt

Evans Kiptoo Korir, Zsolt Vizi

Mathematical models have been used to understand the spread patterns of infectious diseases such as Coronavirus Disease 2019 (COVID-19). The transmission component of the models can be modelled in an age-dependent manner via introducing contact matrix for the population, which describes the contact rates between the age groups. Since social contact patterns

Burak Büke, Goncalo dos Reis, Vadim Platonov

In most service systems, the servers are humans who desire to experience a certain level of idleness. In call centers, this manifests itself as the call avoidance behavior, where servers strategically adjust their service rate to strike a balance between the idleness they receive and effort to work harder. Moreover, being humans, each server values this trad

Raksha Ramakrishna, György Dán

Property inference attacks against machine learning (ML) models aim to infer properties of the training data that are unrelated to the primary task of the model, and have so far been formulated as binary decision problems, i.e., whether or not the training data have a certain property. However, in industrial and healthcare applications, the proportion of lab

Lanpeng Ji, Xiaofan Peng

In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian processes with trend. For different scales of the time horizon we obtain different normalizing functions for the convergence of the maxima. The obtained results not only have potential applications in estimating the delay of certain Gaussian fork-join queueing

Kaushik Paul, Chandra Kant Mishra

We compute the leading and sub-leading spin effects through the second post-Newtonian order (2PN) in spherical harmonic modes of gravitational waveforms from inspiralling compact binaries in non-circular orbits with non-precessing components. The two spin couplings, linear-in-spin (spin-orbit; SO) and quadratic-in-spin (spin-spin; SS), that appear in 2PN wav

Muhammad Ahsan, Sacheendra Talluri, Alexandru Iosup

Microservices is an architectural style that structures an application as a collection of loosely coupled services, making it easy for developers to build and scale their applications. The microservices architecture approach differs from the traditional monolithic style of treating software development as a single entity. Microservice architecture is becomin

Dominique Geissler, Dominik Bär, Nicolas Pröllochs, Stefan Feuerriegel

The Russian invasion of Ukraine in February 2022 was accompanied by practices of information warfare, yet existing evidence is largely anecdotal while large-scale empirical evidence is lacking. Here, we analyze the spread of pro-Russian support on social media. For this, we collected N = 349,455 messages from Twitter with pro-Russian support. Our findings su

Peter Borg, Carl Feghali, Rémi Pellerin

A subset $I$ of the vertex set $V(G)$ of a graph $G$ is called a $k$-clique independent set of $G$ if no $k$ vertices in $I$ form a $k$-clique of $G$. An independent set is a $2$-clique independent set. Let $\pi_k(G)$ denote the number of $k$-cliques of $G$. For a function $w: V(G) \rightarrow \{0, 1, 2, \dots\}$, let $G(w)$ be the graph obtained from $G$ by

Shashi Kant, José Mairton B. da Silva, Gabor Fodor, Bo Göransson

Federated learning (FL) has emerged as an instance of distributed machine learning paradigm that avoids the transmission of data generated on the users' side. Although data are not transmitted, edge devices have to deal with limited communication bandwidths, data heterogeneity, and straggler effects due to the limited computational resources of users' device

Fedele Lizzi

A room, a teacher and many friends.

Takeru Utsugi, Rui Asaoka, Yuuki Tokunaga, Takao Aoki

We investigate atom-photon entangling gates based on cavity quantum electrodynamics (QED) for a finite photon-pulse duration, where not only the photon loss but also the temporal mode-mismatch of the photon pulse becomes a severe source of error. We analytically derive relations between cavity parameters, including transmittance, length, and effective cross-

I-Te Lu, Dongbin Shin, Umberto De Giovannini, Hannes Hübener

To define the topology of driven systems, recent works have proposed synthetic dimensions as a way to uncover the underlying parameter space of topological invariants. Using time as a synthetic dimension, together with a momentum dimension, gives access to a synthetic 2D Chern number. It is, however, still unclear how the synthetic 2D Chern number is related

Bokeon Kwak, Jun Shintake, Lu Zhang, Dario Floreano

Drones have shown to be useful aerial vehicles for unmanned transport missions such as food and medical supply delivery. This can be leveraged to deliver life-saving nutrition and medicine for people in emergency situations. However, commercial drones can generally only carry 10 % - 30 % of their own mass as payload, which limits the amount of food delivery

Alexander Scriven, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys

With most technical fields, there exists a delay between fundamental academic research and practical industrial uptake. Whilst some sciences have robust and well-established processes for commercialisation, such as the pharmaceutical practice of regimented drug trials, other fields face transitory periods in which fundamental academic advancements diffuse gr

Yuri A. Fadeyev

Evolutionary tracks of stars with masses on the main sequence $0.84M_\odot\le M_\textrm{ZAMS}\le 0.95M_\odot$ and initial metal abundances $Z=0.006$ and $Z=0.01$ were computed under various assumptions about the mass loss rate at the red giant stage as well as at the AGB and the post--AGB stages. Among 160 evolutionary sequences we selected nearly 30 sequenc

Daniel Schuster, Michael Martini, Sebastiaan J. van Zelst, Wil M. P. van der Aalst

Event logs, as viewed in process mining, contain event data describing the execution of operational processes. Most process mining techniques take an event log as input and generate insights about the underlying process by analyzing the data provided. Consequently, handling large volumes of event data is essential to apply process mining successfully. Tradit

Archit Bubna, Ashish Chiplunkar

In the prophet inequality problem, a gambler faces a sequence of items arriving online with values drawn independently from known distributions. On seeing an item, the gambler must choose whether to accept its value as her reward and quit the game, or reject it and continue. The gambler's aim is to maximize her expected reward relative to the expected maximu

Fabio Marangi, Luigi Fenzi, Michele Bellingeri, Francesco Scotognella

The optical and electrical properties of films made of nanoparticles of indium tin oxide (ITO) are widely studied because of the significance of this material for transparent electrodes, smart windows, and nonlinear optics components. In this work, a systematic study of the resistance in ITO nanocrystalline films, as a function of post-fabrication parameters

Tsai-Chen Lee, Zezhou Hu, Minyong Guo, Bin Chen

In this work, we study circular motions of charged particles and their polarized images around the Kerr black hole immersed in a weak magnetic field. We pay special attention to the case that both the magnetic field and the charge-to-mass ratio are not big, thus the effective potential along the radial motion reduce to a cubic form approximately so that we c

Iain Mackie, Jeffrey Dalton

Across the financial domain, researchers answer complex questions by extensively "searching" for relevant information to generate long-form reports. This workshop paper discusses automating the construction of query-specific document and entity knowledge graphs (KGs) for complex research topics. We focus on the CODEC dataset, where domain experts (1) create

Richard Moot

In this paper I will present a novel way of combining proof net proof search with neural networks. It contrasts with the 'standard' approach which has been applied to proof search in type-logical grammars in various different forms. In the standard approach, we first transform words to formulas (supertagging) then match atomic formulas to obtain a proof. I w

Felix S. Fauer, Henning W. Rust

Extreme precipitation shows non-stationary behavior over time, but also with respect to other large-scale variables. While this effect is often neglected, we propose a model including the influence of North Atlantic Oscillation, time, surface temperature and a blocking index. The model features flexibility to use annual maxima as well as seasonal maxima to b

Charalampos Verasdanis

We develop the theory of costratification in the setting of relative tensor-triangular geometry, in the sense of Stevenson, providing a unified approach to classification results of Neeman and Benson--Iyengar--Krause, while laying the foundations for future applications. In addition, we introduce and study prime localizing submodules and prime colocalizing $

Lhoussain El Fadil, Omar Kchit

In this paper, we deal with the problem of monogenity of number fields defined by monic irreducible trinomials $F(x)=x^{12}+ax^m+b\in \mathbb{Z}[x]$ with $1\leq m\leq11$. We give sufficient conditions on $a$, $b$, and $m$ so that the number field $K$ is not monogenic. In particular, for $m=1$ and for every rational prime $p$, we characterize when $p$ divides

Nils Frederik Hasselmann, Maxime Nicloux, Alexander Sell

We discuss an algorithm that eliminates the periodic non-linearity of a bimorph piezo actuator by modifying the phase of the voltage waveforms used for driving the actuator. The procedure presented allows for a separate optimization of the motion of the actuator groups in order to obtain the properties desired (such as a specific stepsize or maximum force).

Jonathan D. Mitchell, Elizabeth S. Allman, John A. Rhodes

The Akaike information criterion (AIC) is a common tool for model selection. It is frequently used in violation of regularity conditions at parameter space singularities and boundaries. The expected AIC is generally not asymptotically equivalent to its target at singularities and boundaries, and convergence to the target at nearby parameter points may be slo

Chang Liu, Wilhelm Eschen, Lars Loetgering, Daniel S. Molina

Table-top extreme ultraviolet (EUV) microscopy offers unique opportunities for label-free investigation of biological samples. Here, we demonstrate ptychographic EUV imaging of two dried, unstained model specimens: germlings of a fungus (Aspergillus nidulans), and bacteria (Escherichia coli) cells at 13.5 nm wavelength. We find that the EUV spectral region,

Aziz Amezian El Khalfioui, Jef Wijsen

The problem of consistent query answering for primary keys and self-join-free conjunctive queries has been intensively studied in recent years and is by now well understood. In this paper, we study an extension of this problem with counting. The queries we consider count how many times each value occurs in a designated (possibly composite) column of an answe

Malay Dutta, Anjana K. Mahanta

In this paper we introduce the notion of a complete time graph of order n. We define time paths and Hamiltonian time paths in a complete time graph. Each Hamiltonian time path (htp) is associated with some permutation p of the integers 1 to n. The characteristic function of this path forms a vector in the vector space of rational-valued functions on the set

Subhrajit Sahoo, Praveen C. Srivastava, Toshio Suzuki

In this work, Na isotopes with mass varying from $A=$ 20 to 31 have been studied using DJ16A, JISP16 and N3LO microscopic effective interactions in the $sd$-shell. These effective interactions are derived for $sd$-shell using no-core shell model wavefunctions and a unitary transformation method. We have also performed calculation with IMSRG effective interac

Yuchang Sun, Jiawei Shao, Yuyi Mao, Songze Li

Federated learning (FL) has achieved great success as a privacy-preserving distributed training paradigm, where many edge devices collaboratively train a machine learning model by sharing the model updates instead of the raw data with a server. However, the heterogeneous computational and communication resources of edge devices give rise to stragglers that s

Xin-Hai Tong, Hong Gong, Yao Wang, Rui-Xue Xu

In this work, we investigate the multimode Brownian oscillators in nonequilibrium scenarios with multiple reservoirs at different temperatures. For this purpose, an algebraic method is proposed. This approach gives the exact time-local equation of motion for reduced density operator, from which we can easily extract not only the reduced system but also hybri

Raffaella Fiamma Cabini, Anna Pichiecchio, Alessandro Lascialfari, Silvia Figini

In this work, we apply a kinetic version of a bounded confidence consensus model to biomedical segmentation problems. In the presented approach, time-dependent information on the microscopic state of each particle/pixel includes its space position and a feature representing a static characteristic of the system, i.e. the gray level of each pixel. From the in

P. Zhang, A. Zarassi, M. Pendharkar, J. S. Lee

More and more materials, with a growing variety of properties, are built into electronic devices. This is motivated both by increased device performance and by the studies of materials themselves. An important type of device is a Josephson junction based on the proximity effect between a quantum material and a superconductor, useful for fundamental research

Danny D'Agostino

In this work, we present a new deterministic partition-based global optimization algorithm, HALO (Hybrid Adaptive Lipschitzian Optimization), which uses estimates of the local Lipschitz constants associated with different sub-regions of the objective function's domain to compute lower bounds and guide the search toward global minimizers. These estimates are

Martin Ringsquandl, Aneta Koleva

Despite recent advancements in tabular language model research, real-world applications are still challenging. In industry, there is an abundance of tables found in spreadsheets, but acquisition of substantial amounts of labels is expensive, since only experts can annotate the often highly technical and domain-specific tables. Active learning could potential

Simone Billi

We give an answer to the Nielsen realization problem for hyper-K\"ahler manifolds in terms of the same invariant used for K3 surfaces. We determine that, for some of the known deformation types, the representation of the mapping class group on the second cohomology admits a section on its image.

Felix Stahlberg, Aashish Kumar, Chris Alberti, Shankar Kumar

We report on novel investigations into training models that make sentences concise. We define the task and show that it is different from related tasks such as summarization and simplification. For evaluation, we release two test sets, consisting of 2000 sentences each, that were annotated by two and five human annotators, respectively. We demonstrate that c

Chiara Marzi, Marco Giannelli, Andrea Barucci, Carlo Tessa

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when appli

Ayaz Zeynalov, Kristina Tiron

Oil price fluctuations severely impact the economies of both oil-exporting and importing countries. High oil prices can benefit oil exporters by increasing foreign currency inflow; however, an economy can suffer from a weakening of the manufacturing sectors and experience a significant downtrend in the country's price competitiveness as the domestic currency

Koichi Saito, Naoki Murata, Toshimitsu Uesaka, Chieh-Hsin Lai

Removing reverb from reverberant music is a necessary technique to clean up audio for downstream music manipulations. Reverberation of music contains two categories, natural reverb, and artificial reverb. Artificial reverb has a wider diversity than natural reverb due to its various parameter setups and reverberation types. However, recent supervised derever

Roland Becker, Maximilian Brunner, Michael Innerberger, Jens Markus Melenk

We consider scalar semilinear elliptic PDEs where the nonlinearity is strongly monotone, but only locally Lipschitz continuous. We formulate an adaptive iterative linearized finite element method (AILFEM) which steers the local mesh refinement as well as the iterative linearization of the arising nonlinear discrete equations. To this end, we employ a damped

Douwe Hoekstra, Florian Zeiser

We compute the Poisson cohomology associated with several three dimensional Lie algebras. Together with existing results and the classification of three dimensional Lie algebras, this provides the Poisson cohomology of all linear Poisson structures in dimension 3.

Ning Mao, Runhan Li, Xiaorong Zou, Ying Dai

The interplay between ferroelectricity and band topology can give rise to a wide range of both fundamental and applied research. Here, we map out the emergence of nontrivial corner states in two-dimensional ferroelectrics, and remarkably demonstrate that ferroelectricity and corner states are coupled together by crystallographic symmetry to realize the elect

Yann Damour, Raúl Quintero-Monsebaiz, Michel Caffarel, Denis Jacquemin

We report ground- and excited-state dipole moments and oscillator strengths (computed in different ``gauges'' or representations) of full configuration interaction (FCI) quality using the selected configuration interaction method known as \textit{Configuration Interaction using a Perturbative Selection made Iteratively} (CIPSI). Thanks to a set encompassing

Lucas Meyer, Alejandro Ribés, Bruno Raffin

Numerical simulations are ubiquitous in science and engineering. Machine learning for science investigates how artificial neural architectures can learn from these simulations to speed up scientific discovery and engineering processes. Most of these architectures are trained in a supervised manner. They require tremendous amounts of data from simulations tha

Jinta Weng, Yifan Deng, d Donghao Li, Hao You

The prompt has become an effective linguistic tool for utilizing pre-trained language models. However, in few-shot scenarios, subtle changes in the prompt design always make the result widely different, and the prompt learning methods also make it easy to overfit the limited samples. To alleviate this, we explore utilizing suitable contrastive samples and mu

Ioannis Caragiannis, Zhile Jiang

Cut games are among the most fundamental strategic games in algorithmic game theory. It is well-known that computing an exact pure Nash equilibrium in these games is PLS-hard, so research has focused on computing approximate equilibria. We present a polynomial-time algorithm that computes $2.7371$-approximate pure Nash equilibria in cut games. This is the fi

Ruihan Zhang, Junze Deng, Yan Sun, Zhong Fang

Recently, unconventional materials (or obstructed atomic insulators) have attracted much attention owing to the unconventional feature of mismatch between Wannier centers and atomic positions. In this paper, we demonstrate that the trigonal selenium and tellurium host an unconventional nature in both electronic and phonon spectra. In electronic band structur

Adrien Flahault, Mathilde Keck, Pierre-Emmanuel Girault-Sotias, Lucie Esteoulle

Apelin is a neuro-vasoactive peptide that plays a major role in the control of cardiovascular functions and water balance, but has an in-vivo half-life in the minute range, limiting its therapeutic use. We previously developed LIT01-196, a systemically active metabolically stable apelin-17 analog, produced by chemical addition of a fluorocarbon chain to the

Florian Semmer, Marie-Charlotte Emperauger, Colin Lopez, Christine Bogicevic

Three-dimension real-time tracking of single emitters is an emerging tool for assessment of biological behavior as intraneuronal transport, for which spatiotemporal resolution is crucial to understand the microscopic interactions between molecular motors. We report the use of second harmonic signal from nonlinear nanoparticles to localize them in a super-loc

Kiyoshi Takeuchi

Based on the recent developments in the irregular Riemann-Hilbert correspondence for holonomic D-modules and the Fourier-Sato transforms for enhanced ind-sheaves, we study the Fourier transforms of some irregular holonomic D-modules. For this purpose, the singularities of rational and meromorphic functions on complex affine varieties will be studied precisel

Parinya Chalermsook, Manoj Gupta, Wanchote Jiamjitrak, Nidia Obscura Acosta

Greedy BST (or simply Greedy) is an online self-adjusting binary search tree defined in the geometric view ([Lucas, 1988; Munro, 2000; Demaine, Harmon, Iacono, Kane, Patrascu, SODA 2009). Along with Splay trees (Sleator, Tarjan 1985), Greedy is considered the most promising candidate for being dynamically optimal, i.e., starting with any initial tree, their

Ravi A. Rao, Sampat Sharma

In this paper, we study the action of special $n\times n $ linear (resp. symplectic) matrices which are homotopic to identity on the right invertible $n\times m$ matrices. We also prove that the commutator subgroup of $\rm{O}_{2n}(R[X])$ is two stably elementary orthogonal for a local ring $R$ with $\frac{1}{2}\in R$ and $n\geq 3.$

Saifullah Saifullah, Dominique Mercier, Adriano Lucieri, Andreas Dengel

Since the mid-10s, the era of Deep Learning (DL) has continued to this day, bringing forth new superlatives and innovations each year. Nevertheless, the speed with which these innovations translate into real applications lags behind this fast pace. Safety-critical applications, in particular, underlie strict regulatory and ethical requirements which need to

Mengcheng Huang, Chang Liu, Zongliang Du, Shan Tang

In this article, an efficient sequential linear programming algorithm (SLP) for uncertainty analysis-based data-driven computational mechanics (UA-DDCM) is presented. By assuming that the uncertain constitutive relationship embedded behind the prescribed data set can be characterized through a convex combination of the local data points, the upper and lower

Yiming Wang, Dongxia Chang, Zhiqiang Fu, Jie Wen

Multi-view representation learning has developed rapidly over the past decades and has been applied in many fields. However, most previous works assumed that each view is complete and aligned. This leads to an inevitable deterioration in their performance when encountering practical problems such as missing or unaligned views. To address the challenge of rep