November 2022 arXiv papers — page 13

Florian Rupp, Benjamin Schnabel, Kai Eckert

The Resource Description Framework is well-established as a lingua franca for data modeling and is designed to integrate heterogeneous data at instance and schema level using statements. While RDF is conceptually simple, data models nevertheless get complex, when complex data needs to be represented. Additional levels of indirection with intermediate resourc

Vitalii Vertogradov

The center-of-mass energy can be arbitrarily high in Schwarzschild spacetime if one considers the front collision of two particles, one of which moves along so-called white hole geodesics and another one along a black hole geodesic. This process can take place if one considers the gravitational collapse model. In this paper, we consider the well-known naked

Dallas Albritton, Tobias Barker, Christophe Prange

We give a new concise proof of a certain one-scale epsilon regularity criterion using weak-strong uniqueness for solutions of the Navier-Stokes equations with non-zero boundary conditions. It is inspired by an analogous approach for the stationary system due to Struwe.

Mathias Lechner, Đorđe Žikelić, Krishnendu Chatterjee, Thomas A. Henzinger

We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be rob

Łucja Kipczak, Artur O. Slobodeniuk, Tomasz Woźniak, Mukul Bhatnagar

Excitons in thin layers of semiconducting transition metal dichalcogenides are highly subject to the strongly modified Coulomb electron-hole interaction in these materials. Therefore, they do not follow the model system of a two-dimensional hydrogen atom. We investigate experimentally and theoretically excitonic properties in both the monolayer (ML) and the

Zhuohang Dang, Jihong Wang, Minnan Luo, Chengyou Jia

Few-shot learning (FSL), which aims to classify unseen classes with few samples, is challenging due to data scarcity. Although various generative methods have been explored for FSL, the entangled generation process of these methods exacerbates the distribution shift in FSL, thus greatly limiting the quality of generated samples. To these challenges, we propo

Ervin Győri, Nika Salia

Extensions of Erd\H{o}s-Gallai Theorem for general hypergraphs are well studied. In this work, we prove the extension of Erd\H{o}s-Gallai Theorem for linear hypergraphs. In particular, we show that the number of hyperedges in an $n$-vertex $3$-uniform linear hypergraph, without a Berge path of length $k$ as a subgraph is at most $\frac{(k-1)}{6}n$ for $k\geq

Songjie Yang, Wanting Lyu, Yue Xiu, Zhongpei Zhang

Double-reconfigurable intelligent surface (RIS) is a promising technique, achieving a substantial gain improvement compared to single-RIS techniques. However, in double-RIS-aided systems, accurate channel estimation is more challenging than in single-RIS-aided systems. This work solves the problem of double-RIS-based channel estimation based on active RIS ar

Kaiyue Wen, Tengyao Wang, Yuhao Wang

We consider the problem of testing whether a single coefficient is equal to zero in linear models when the dimension of covariates $p$ can be up to a constant fraction of sample size $n$. In this regime, an important topic is to propose tests with finite-sample valid size control without requiring the noise to follow strong distributional assumptions. In thi

Daniela Moreno-Chaparro, Nicolas Moreno, Florencio Balboa-Usabiaga, Marco Ellero

Functionalized nanoparticles (NPs) are complex objects present in a variety of systems ranging from synthetic grafted nanoparticles to viruses. The morphology and number of the decorating groups can vary widely between systems. Thus, the modelling of functionalized NPs typically considers simplified spherical objects as a first-order approximation. At the na

Xiaohuan Zhou, Jiaming Wang, Zeyu Cui, Shiliang Zhang

In this paper, we propose a novel multi-modal multi-task encoder-decoder pre-training framework (MMSpeech) for Mandarin automatic speech recognition (ASR), which employs both unlabeled speech and text data. The main difficulty in speech-text joint pre-training comes from the significant difference between speech and text modalities, especially for Mandarin s

Camille Labourie, Antoine Lemenant

In this paper we prove that if (u, K) is an almost-minimizer of the Griffith functional and K is $\epsilon$-close to a plane in some ball B $\subset$ R N while separating the ball B in two big parts, then K is C 1,$\alpha$ in a slightly smaller ball. Our result contains and generalizes the 2 dimensional result of [4], with a different and more sophisticate a

Thales Augusto Barbosa Pinto Silva, Renato Moreira Angelo

Of indisputable relevance for non-equilibrium thermodynamics, fluctuations theorems have been generalized to the framework of quantum thermodynamics, with the notion of work playing a key role in such contexts. The typical approach consists of treating work as a stochastic variable and the acting system as an eminently classical device with a deterministic d

ATLAS Collaboration

Measurements and searches performed with the ATLAS detector at the CERN Large Hadron Collider often involve signatures with one or more prompt leptons. Such analyses are subject to `fake/non-prompt' lepton backgrounds, where either a hadron or a lepton from a hadron decay or an electron from a photon conversion satisfies the prompt-lepton selection criteria.

Diego M. Mateos, Leonardo E. Riveaud, Pedro W. Lamberti

Divergences or similarity measures between probability distributions have become a very useful tool for studying different aspects of statistical objects such as time series, networks and images. Notably not every divergence provides identical results when applied to the same problem. Therefore it is convenient to have the widest possible set of divergences

Takeshi Yoshihara, Taisei Kaizoji

We applied the SVAR-LiNGAM to illustrate the causal relationships between the spot exchange rate, and three crypto-asset exchange rates, Bitcoin, Ethereum, and Ripple. It was notable that the causal order, the EUR_USD spot rate->Bitcoin->Ethereum->Ripple, was obtained by this approach. All the instantaneous effects were strongly positive. Moreover, it was no

Xiaofeng Mao, Yuefeng Chen, Xiaojun Jia, Rong Zhang

Contrastive Language-Image Pre-trained (CLIP) models have zero-shot ability of classifying an image belonging to "[CLASS]" by using similarity between the image and the prompt sentence "a [CONTEXT] of [CLASS]". Based on exhaustive text cues in "[CONTEXT]", CLIP model is aware of different contexts, e.g. background, style, viewpoint, and exhibits unprecedente

Josef Jon, Martin Popel, Ondřej Bojar

We present the CUNI-Bergamot submission for the WMT22 General translation task. We compete in English$\rightarrow$Czech direction. Our submission further explores block backtranslation techniques. Compared to the previous work, we measure performance in terms of COMET score and named entities translation accuracy. We evaluate performance of MBR decoding comp

Mattia Radice

We study the first-passage time to the origin of a mortal Brownian particle, with mortality rate $ \mu $, diffusing in one dimension. The particle starts its motion from $ x>0 $ and it is subject to stochastic resetting with constant rate $ r $. We first unveil the relation between the probability of reaching the target and the mean first-passage time of the

Devansh Mehta, Harshita Diddee, Ananya Saxena, Anurag Shukla

The primary obstacle to developing technologies for low-resource languages is the lack of representative, usable data. In this paper, we report the deployment of technology-driven data collection methods for creating a corpus of more than 60,000 translations from Hindi to Gondi, a low-resource vulnerable language spoken by around 2.3 million tribal people in

Johannes Bracher, Nils Koster, Fabian Krüger, Sebastian Lerch

We report on a course project in which students submit weekly probabilistic forecasts of two weather variables and one financial variable. This real-time format allows students to engage in practical forecasting, which requires a diverse set of skills in data science and applied statistics. We describe the context and aims of the course, and discuss design p

Martin Hasenbusch

We study the cubic fixed point for $N=3$ and $4$ by using finite size scaling applied to data obtained from Monte Carlo simulations of the $N$-component $\phi^4$ model on the simple cubic lattice. We generalize the idea of improved models to a two-parameter family of models. The two-parameter space is scanned for the point, where the amplitudes of the two le

Sergei M. Kuzenko, Emmanouil S. N. Raptakis

We propose a superspace formulation for conformal $(p,q)$ supergravity in two dimensions as a gauge theory of the superconformal group $\mathsf{OSp}_0 (p|2; {\mathbb R} ) \times \mathsf{OSp}_0 (q|2; {\mathbb R} )$ with a flat connection. Upon degauging of certain local symmetries, this conformal superspace is shown to reduce to a conformally flat $\mathsf{SO

V. Dominguez, C. Turc

Helmholtz decompositions of the elastic fields open up new avenues for the solution of linear elastic scattering problems via boundary integral equations (BIE) [Dong, Lai, Li, Mathematics of Computation,2021]. The main appeal of this approach is that the ensuing systems of BIE feature only integral operators associated with the Helmholtz equation. However, t

Jinghai Shao

A comparison theorem for state-dependent regime-switching diffusion processes is established, which enables us to control pathwisely the evolution of the state-dependent switching component simply by Markov chains. Moreover, a sharp estimate on the stability of Markovian regime-switching processes under the perturbation of transition rate matrices is provide

Jamison Sloan, Nicholas Rivera, John D Joannopoulos, Marin Soljačić

Time-varying optical materials have attracted recent interest for their potential to enable frequency conversion, nonreciprocal physics, photonic time-crystals, and more. However, the description of time-varying materials has been primarily limited to regimes where material resonances (i.e., dispersion) can be neglected. In this work, we describe how the opt

Jacob T. Willson, William Liu, Daniel Balzer, Ivan Kassal

Developing devices using disordered organic semiconductors requires accurate and practical models of charge transport. In these materials, charge transport occurs through partially delocalised states in an intermediate regime between localised hopping and delocalised band conduction. Partial delocalisation can increase mobilities by orders of magnitude over

Ruifeng Yuan, Zili Wang, Ziqiang Cao, Wenjie Li

Query-focused summarization has been considered as an important extension for text summarization. It aims to generate a concise highlight for a given query. Different from text summarization, query-focused summarization has long been plagued by the problem of lacking high-quality large-scale datasets. In this paper, we investigate the idea that whether we ca

Yongliang Hao, Dongdong Ni

In some extensions of the Standard Model (SM), two neutrons are allowed to decay into two sterile anti-neutrinos ($nn \rightarrow \bar{\chi}\bar{\chi}$) via new scalar bosons. This process violates both the baryon number ($\mathcal{B}$) and the lepton number ($\mathcal{L}$) by two units but conserves their difference $(\mathcal{B}-\mathcal{L})$. Neutron star

Seyed Mohammad Azimi-Abarghouyi, Viktoria Fodor

When implementing hierarchical federated learning over wireless networks, scalability assurance and the ability to handle both interference and device data heterogeneity are crucial. This work introduces a new two-level learning method designed to address these challenges, along with a scalable over-the-air aggregation scheme for the uplink and a bandwidth-l

Cameron Dahan, Stergios Christodoulidis, Maria Vakalopoulou, Joseph Boyd

In the clinical setting of histopathology, whole-slide image (WSI) artifacts frequently arise, distorting regions of interest, and having a pernicious impact on WSI analysis. Image-to-image translation networks such as CycleGANs are in principle capable of learning an artifact removal function from unpaired data. However, we identify a surjection problem wit

S Rozen, S Larroque, N Dudovich, Y Mairesse

Strong-field light-matter interactions initiate a wide range of phenomena in which the quantumpaths of electronic wavepackets can be manipulated by tailoring the laser field. Among the electronsreleased by a strong laser pulse from atomic and molecular targets, some are subsequently drivenback to the vicinity of the ionic core by the oscillating laser field.

Sarah Kaakai, Anis Matoussi, Achraf Tamtalini

Systemic risk measures were introduced to capture the global risk and the corresponding contagion effects that is generated by an interconnected system of financial institutions. To this purpose, two approaches were suggested. In the first one, systemic risk measures can be interpreted as the minimal amount of cash needed to secure a system after aggregating

Joris Guérin, Kevin Delmas, Raul Sena Ferreira, Jérémie Guiochet

The usage of deep neural networks in safety-critical systems is limited by our ability to guarantee their correct behavior. Runtime monitors are components aiming to identify unsafe predictions and discard them before they can lead to catastrophic consequences. Several recent works on runtime monitoring have focused on out-of-distribution (OOD) detection, i.

Yves Achdou, Claude Le Bris

We study homogenization for a class of stationnary Hamilton-Jacobi equations in which the Hamiltonian is obtained by perturbing near the origin an otherwise periodic Hamiltonian. We prove that the limiting problem consists of a Hamilton-Jacobi equation outside the origin, with the same effective Hamiltonian as in periodic homogenization, supplemented at the

D. H. J. Polymath

An $n$-sided die is an $n$-tuple of positive integers. We say that a die $(a_1,\dots,a_n)$ beats a die $(b_1,\dots,b_n)$ if the number of pairs $(i,j)$ such that $a_i>b_j$ is greater than the number of pairs $(i,j)$ such that $a_i<b_j$. We show that for a natural model of random $n$-sided dice, if $A, B$ and $C$ are three random dice then the probability tha

Jan O. Bauer

The assumption of independent subvectors arises in many aspects of multivariate analysis. In most real-world applications, however, we lack prior knowledge about the number of subvectors and the specific variables within each subvector. Yet, testing all these combinations is not feasible. For example, for a data matrix containing 15 variables, there are alre

Laurent Manivel

This note is devoted to a special Fano fourfold defined by a four-dimensional space of skew-symmetric forms in five variables. This fourfold appears to be closely related with the classical Segre cubic and its Cremona-Richmond configuration of planes. Among other exceptional properties, it is infinitesimally rigid and has Picard number six. We show how to co

Bingbing Ding, Yu Lu, Huicheng Yin

For the 3D quasilinear wave equation $-\big(1+(\partial_t\phi)^p\big)\partial_t^2\phi+\Delta\phi=0$ with the short pulse initial data $(\phi,\partial_t\phi)(1,x)=\big(\delta^{2-\varepsilon_0}\phi_0(\frac{r-1}{\delta},\omega), \delta^{1-\varepsilon_0}\phi_1(\frac{r-1}{\delta},\omega)\big)$, where $p\in\mathbb N$, $p\geq 2$, $0<\varepsilon_0<1$, $r=|x|$, $\ome

Arina Kudriavtseva, Olga Gadyatskaya

In recent years, the number of cyber attacks has grown rapidly. An effective way to reduce the attack surface and protect software is adoption of methodologies that apply security at each step of the software development lifecycle. While different methodologies have been proposed to address software security, recent research shows an increase in the number o

Hao Phung, Quan Dao, Anh Tran

Diffusion models are rising as a powerful solution for high-fidelity image generation, which exceeds GANs in quality in many circumstances. However, their slow training and inference speed is a huge bottleneck, blocking them from being used in real-time applications. A recent DiffusionGAN method significantly decreases the models' running time by reducing th

Max Berre, Benjamin Le Pendeven

How do business-cycles impact startup-valuations? While several studies explore VC startupecosystems and pre-money valuations, relatively-few delve deeper into the role of macro-level economic factors in influencing those startup deals valuations. Using a dataset of 1,089 venturecapital investments in European Union and European Economic Area markets, this a

Koichi Hattori, Daiki Suenaga, Kei Suzuki, Shigehiro Yasui

We develop a mean-field theory of a novel Kondo effect emerging in systems without a Fermi surface, which instead emerges under strong magnetic fields. We determine the magnitude of the Kondo condensate which is a particle pairing composed of conducting Dirac fermions and localized impurities. We focus on the competition between the Kondo effect and the ener

Raphael J. F. Berger

The problem of a spin-free electron with mass $m$, charge $e$ confined onto a ring of radius $R_0$ and with an attractive Dirac delta potential with scaling factor (depth) $\kappa$ in non-relativistic theory has closed form analytical solutions. The single bound state function is of the form of a hyperbolic cosine that however contains a parameter $d>0$ whic

Rassen Boukraa, Claire Poujouly, Pedro Gonzalez-Losada, Jean Gamby

Here, we proposed to test the limits of the bounded diffusion impedance model by using electrochemical impedance spectroscopy (EIS) measurements in a microfluidic device architecture bearing a set of microelectrodes integrated in microchannel. This EIS Nyquist plot behaviour was currently modelled with the Randles equivalent circuit. In this work, one of the

Lucas Noëmie, Clément Salah, Chahan Vidal-Gorène

HTR models development has become a conventional step for digital humanities projects. The performance of these models, often quite high, relies on manual transcription and numerous handwritten documents. Although the method has proven successful for Latin scripts, a similar amount of data is not yet achievable for scripts considered poorly-endowed, like Ara

Junde Wu, Huihui Fang, Yehui Yang, Yu Zhang

Different from the general visual classification, some classification tasks are more challenging as they need the professional categories of the images. In the paper, we call them expert-level classification. Previous fine-grained vision classification (FGVC) has made many efforts on some of its specific sub-tasks. However, they are difficult to expand to th

Olivier Couronné

By modifying the automaton used by P{\"o}nitz and Tittman [4], and considering loops of length up to 26, we obtain 2.662343 as an upper bound for the connective constant in the lattice Z 2 .

William Rohde, Fulvio Forni

Improving the efficiency of agriculture is a growing priority due to food security issues, environmental concerns, and economics. Precision agriculture and variable rate application technology could enable increases in yield while maintaining or reducing fertiliser use. However, this requires the development of control algorithms which are suitable for the c

Jacky Cresson, Rouba Safi

Following the discrete embedding formalism, we give a new derivation of the mid-point variational integrators as developed by J.M. Wendlandt and J.E. Marsden by defining an adapted order two discrete differential and integral calculus. This allows us to obtain a clearer correspondence between the discrete and continuous case. We also discuss the correspondin

Xiaolin Bu, Zihao Li, Shengxin Liu, Jiaxin Song

We consider the fair division problem of indivisible items. It is well-known that an envy-free allocation may not exist, and a relaxed version of envy-freeness, envy-freeness up to one item (EF1), has been widely considered. In an EF1 allocation, an agent may envy others' allocated shares, but only up to one item. In many applications, we may wish to specify

Ying Lin, Scott B. Lindstrom, Bruno F. Lourenço, Ting Kei Pong

Error bounds are a requisite for trusting or distrusting solutions in an informed way. Until recently, provable error bounds in the absence of constraint qualifications were unattainable for many classes of cones that do not admit projections with known succinct expressions. We build such error bounds for the generalized power cones, using the recently devel

Frauke Wilm, Marco Fragoso, Christof A. Bertram, Nikolas Stathonikos

Computer-aided systems in histopathology are often challenged by various sources of domain shift that impact the performance of these algorithms considerably. We investigated the potential of using self-supervised pre-training to overcome scanner-induced domain shifts for the downstream task of tumor segmentation. For this, we present the Barlow Triplets to

Alizée Thomas, Guillaume Fribourg, Jean-Jacques Blandin, Pierre Lhuissier

Electrical conductors are usually made of pure copper because this material shows outstanding electrical conductivity (IACS > 100%). Additive manufacturing can be used to further improve the performances of such electrical conductors because it enables to consider sophisticated geometries impossible to be fabricated by conventional processing routes such as

Stephen Owusu, Pedro da Silveira Ferreira, Alessio Notari, Miguel Quartin

The Cosmic Microwave Background (CMB) anisotropies are thought to be statistically isotropic and Gaussian. However, several anomalies are observed, including the CMB Cold Spot, an unexpected cold $\sim 10^{\circ}$ region with $p$-value $\lesssim 0.01$ in standard $\Lambda$CDM. One of the proposed origins of the Cold Spot is an unusually large void on the lin

Abigail J. Burdon, Lisa V. Hampson, Christopher Jennison

Often in Phase 3 clinical trials measuring a long-term time-to-event endpoint, such as overall survival or progression-free survival, investigators also collect repeated measures on biomarkers which may be predictive of the primary endpoint. Although these data may not be leveraged directly to support early stopping decisions, can we make greater use of thes

Alain Rapaport, Ismail Mimouni

We consider a two-patches SIR model where communication occurs thru commuters, distinguishing explicitly permanently resident populations from commuters populations. We give an explicit formula of the reproduction number, and show how the proportions of permanently resident populations impact it. We exhibit non-intuitive situations for which allowing commuti

Adán Reyes, Delphine Sinoquet, André Nasr, Sami Hlioui

In this paper, deterministic and robust design optimizations of a permanent magnet assisted synchronous reluctance machine were performed to increase its mean torque while reducing torque ripple. These optimizations were carried out using a surrogate model based on 2-D finite element simulations. The results of the robust optimizations, which considered manu

Sicong Liu, Xiaochen Li, Zimu Zhou, Bin Guo

The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services for privacy and robustness concerns. However, the performance of these applications is constrained by the raw

Aurélien Djament, Antoine Touzé

Let A be a finitely-generated commutative ring and k a noetherian commutative ring. We show that, in the category of functors from finitely-generated projective A-modules to k-modules, each finitely-generated polynomial functor is noetherian and has a finitely-generated projective resolution.

Chong Shen, Xiaoyong Xi, Dongsheng Zhao

The open well-filtered spaces were introduced by Shen, Xi, Xu and Zhao to answer the problem whether every core-compact well-filtered space is sober. In the current paper we explore further properties of open well-filtered spaces. One of the main results is that if a space is open well-filtered, then so is its upper space (the set of all nonempty saturated c

Hideki Miyachi, Ken'Ichi Ohshika, Athanase Papadopoulos

In this paper, we introduce a new asymmetric weak metric on the Teichm{\"u}ller space of a closed orientable surface with (possibly empty) punctures.This new metric, which we call the Teichm{\"u}ller-Randers metric, is an asymmetric deformation of the Teichm{\"u}ller metric, and is obtained by adding to the infinitesimal form of the Teichm{\"u}ller metric a

Thomas Cavallazzi

We prove It{\^o}'s formula for the flow of measures associated with a jump process defined by a drift, an integral with respect to a Poisson random measure and with respect to the associated compensated Poisson random measure. We work in $\mathcal{P}_{\beta}(\mathbb{R}^d)$, the space of probability measures on $\mathbb{R}^d$ having a finite moment of order $

Robert Schippa, Roland Schnaubelt

We prove Strichartz estimates for Maxwell equations in media in the fully anisotropic case with H\"older-continuous coefficients. To this end, we use the FBI transform to conjugate the problem to phase space. After reducing to a scalar estimate by means of a matrix symmetrizer, we show oscillatory integral estimates for a variable-coefficient Fourier extensi

Vladimiro Benedetti, Daniele Faenzi

We study the rationality of the Peskine sixfolds in P^9. We prove the rationality of the Peskine sixfolds in the divisor D^{3,3,10} inside the moduli space of Peskine sixfolds and we provide a cohomological condition which ensures the rationality of the Peskine sixfolds in the divisor D^{1,6,10} (notation from [BS]). We conjecture, as in the case of cubic fo

Sina Tabakhi, Mohammod Naimul Islam Suvon, Pegah Ahadian, Haiping Lu

With advanced imaging, sequencing, and profiling technologies, multiple omics data become increasingly available and hold promises for many healthcare applications such as cancer diagnosis and treatment. Multimodal learning for integrative multi-omics analysis can help researchers and practitioners gain deep insights into human diseases and improve clinical

Samuel Dobson, Steven Galbraith, Benjamin Smith

Groups of unknown order are of major interest due to their applications including time-lock puzzles, verifiable delay functions, and accumulators. In this paper we focus on trustless setup: in this setting, the most popular unknown-order group construction is ideal class groups of imaginary quadratic fields. We argue that the full impact of Sutherland's gene

Saumen Acharjee, Arindam Boruah, Reeta Devi, Nimisha Dutta

In this letter, we have studied the spin torque based magnetization oscillations and switching in presence of Rashba - Zeeman (RZ), Ruderman - Kittel - Kasuya - Yoside (RKKY) and Dzyaloshinskii - Moriya (DM) interactions in a double barrier RZ$|$Heavy Metal (HM)$|$RZ magnetic tunnel junction (MTJ). The system has stable magnetization oscillations and can wor

Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo

Sensors in cyber-physical systems often capture interconnected processes and thus emit correlated time series (CTS), the forecasting of which enables important applications. The key to successful CTS forecasting is to uncover the temporal dynamics of time series and the spatial correlations among time series. Deep learning-based solutions exhibit impressive

Ludovico Battista, Stefano Francaviglia, Marco Moraschini, Filippo Sarti

On negatively curved compact manifolds, it is possible to associate to every closed form a bounded cocycle - hence a bounded cohomology class - via integration over straight simplices. The kernel of this map is contained in the space of exact forms. We show that in degree 2 this kernel is trivial, in contrast with higher degree. In other words, exact non-zer

O. Mryglod, S. Nazarovets, S. Kozmenko

This paper presents the results of further exploration of Crossref data related to Ukrainian Economics research (the first part can be found in [Mryglod, O., Nazarovets, S. & Kozmenko, S. (2021) Scientometrics, 126, 8187]). Our purpose is to supplement the quantitative portrait of Ukrainian Economics discipline with the results of gender and author ordering

Jeroen Bouwman, Sarah Kendrew, Thomas P. Greene, Taylor J. Bell

We present here the first ever mid-infrared spectroscopic time series observation of the transiting exoplanet \object{L 168-9 b} with the Mid-Infrared Instrument (MIRI) on the James Webb Space Telescope. The data were obtained as part of the MIRI commissioning activities, to characterize the performance of the Low Resolution Spectroscopy (LRS) mode for these

Nivedita Bijlani, Oscar Mendez Maldonado, Samaneh Kouchaki

Sensor-based remote health monitoring is used in industrial, urban and healthcare settings to monitor ongoing operation of equipment and human health. An important aim is to intervene early if anomalous events or adverse health is detected. In the wild, these anomaly detection approaches are challenged by noise, label scarcity, high dimensionality, explainab

Matteo Iacopini, Francesco Ravazzolo, Luca Rossini

This article proposes a novel Bayesian multivariate quantile regression to forecast the tail behavior of energy commodities, where the homoskedasticity assumption is relaxed to allow for time-varying volatility. In particular, we exploit the mixture representation of the multivariate asymmetric Laplace likelihood and the Cholesky-type decomposition of the sc

Sofia Abrunhosa, Ian Gibb, Rita Macedo, Emrys Williams

Information encoding in barcodes using magnetic-based technology is a unique strategy to read data buried underneath non-transparent surfaces since a direct line-of-sight between the code and the reader is not required. This technology is of particular interest in secure labelling and recyclable packaging applications. However, current magnetic reading heads

Andrés Megías, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Anton I. Vasyunin

Recent observations of the pre-stellar core L1544 and the younger starless core L1498 have revealed that complex organic molecules (COMs) are enhanced in the gas phase toward their outer and intermediate-density shells. Our goal is to determine the level of chemical complexity toward the starless core L1517B, which seems younger than L1498, and compare it wi

Nir Oren, Bruno Yun

A gradual semantics takes a weighted argumentation framework as input and outputs a final acceptability degree for each argument, with different semantics performing the computation in different manners. In this work, we consider the problem of attack inference. That is, given a gradual semantics, a set of arguments with associated initial weights, and the f

Deepika Saxena, Ashutosh Kumar Singh

Massive upsurge in cloud resource usage stave off service availability resulting into outages, resource contention, and excessive power-consumption. The existing approaches have addressed this challenge by providing multi-cloud, VM migration, and running multiple replicas of each VM which accounts for high expenses of cloud data centre (CDC). In this context

Henry Addison, Elizabeth Kendon, Suman Ravuri, Laurence Aitchison

Climate change is causing the intensification of rainfall extremes. Precipitation projections with high spatial resolution are important for society to prepare for these changes, e.g. to model flooding impacts. Physics-based simulations for creating such projections are very computationally expensive. This work demonstrates the effectiveness of diffusion mod

Guy R. McPherson, Beril Kallfelz Sirmacek, William M. Kallfelz

The aerosol masking effect, or global dimming, is a well-documented instance of our ongoing climate predicament: Efforts to mitigate greenhouse gas production by curbing industrial activity or transitioning to clean sources such as solar or nuclear inevitably and inadvertently accelerate planetary warming. This undesired outcome results from aerosols that re

Gabriele Cenedese, Giuliano Benenti, Maria Bondani

Characterizing and mitigating errors in current noisy intermediate-scale devices is important to improve performance of next generations of quantum hardware. In order to investigate the importance of the different noise mechanisms affecting quantum computation, we perform full quantum process tomography of single qubits in a real quantum processor in which e

Thilo von Neumann, Christoph Boeddeker, Keisuke Kinoshita, Marc Delcroix

We propose a general framework to compute the word error rate (WER) of ASR systems that process recordings containing multiple speakers at their input and that produce multiple output word sequences (MIMO). Such ASR systems are typically required, e.g., for meeting transcription. We provide an efficient implementation based on a dynamic programming search in

Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters

PAC-Bayes has recently re-emerged as an effective theory with which one can derive principled learning algorithms with tight performance guarantees. However, applications of PAC-Bayes to bandit problems are relatively rare, which is a great misfortune. Many decision-making problems in healthcare, finance and natural sciences can be modelled as bandit problem

Ken Sato

We construct a collection of families of higher Chow cycles of type $(2,1)$ on a 2-dimensional family of Kummer surfaces, and prove that for a very general member, they generate a subgroup of rank $\ge 18$ in the indecomposable part of the higher Chow group. Construction of the cycles uses a finite group action on the family, and the proof of their linear in

Rakesh Das, Anirban Saha

We study the interaction of a quantum mechanical particle with gravitational wave (GW) in the framework of modified theory of gravity (MTG) where apart from the two standard tensorial modes of polarization of GW there exists another massless scalar mode. The purpose of using the MTG framework in our study is to uncover key features in matter's response to GW

Alexander Bylinkin, Joakim Nystrand, Daniel Tapia Takaki

We discuss the physics prospects of photon-induced measurements using the high-granularity FoCal detector to be installed at the ALICE experiment, covering the pseudorapidity interval $3.4 \leq \eta \leq 5.8$. This new detector, scheduled to be in operation from Run 4, will explore the small Bjorken-$x$ physics region in an unprecedented way. In this region

Efrén Rama-Maneiro, Pablo Monteagudo-Lago, Juan C. Vidal, Manuel Lama

Predictive monitoring is a subfield of process mining that aims to predict how a running case will unfold in the future. One of its main challenges is forecasting the sequence of activities that will occur from a given point in time -- suffix prediction -- . Most approaches to the suffix prediction problem learn to predict the suffix by learning how to predi

Gillian D. Beltz-Mohrmann, Adam O. Szewciw, Andreas A. Berlind, Manodeep Sinha

This paper represents an effort to provide robust constraints on the galaxy-halo connection and simultaneously test the Planck LCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the lar

Gianluca Curzi, Anupam Das

Cyclic and non-wellfounded proofs are now increasingly employed to establish metalogical results in a variety of settings, in particular for type systems with forms of (co)induction. Under the Curry-Howard correspondence, a cyclic proof can be seen as a typing derivation 'with loops', closer to low-level machine models, and so comprise a highly expressive co

Sara Salamat, Nima Tavassoli, Behnam Sabeti, Reza Fahmi

Graph neural networks (GNNs) have been utilized for various natural language processing (NLP) tasks lately. The ability to encode corpus-wide features in graph representation made GNN models popular in various tasks such as document classification. One major shortcoming of such models is that they mainly work on homogeneous graphs, while representing text da

A. C. Aguilar, M. N. Ferreira, D. Ibañez, B. M. Oliveira

The correlation functions of Yang-Mills theories formulated in the background field method satisfy linear Slavnov-Taylor identities, which are naive generalizations of simple tree level relations, with no deformations originating from the ghost sector of the theory. In recent years, a stronger version of these identities has been found to hold at the level o

Bing Liu, Tiancheng Lan, Wen Hua, Guido Zuccon

Entity Alignment (EA), which aims to detect entity mappings (i.e. equivalent entity pairs) in different Knowledge Graphs (KGs), is critical for KG fusion. Neural EA methods dominate current EA research but still suffer from their reliance on labelled mappings. To solve this problem, a few works have explored boosting the training of EA models with self-train

Peter C. Kroon, Fabian Grünewald, Jonathan Barnoud, Marco van Tilburg

Ongoing advances in force field and computer hardware development enable the use of molecular dynamics (MD) to simulate increasingly complex systems with the ultimate goal of reaching cellular complexity. At the same time, rational design by high-throughput (HT) simulations is another forefront of MD. In these areas, the Martini coarse-grained force field, e

Hui-Ying Ren, Ya-Ning Ren, Qi Zheng, Jia-Qi He

Graphene quantum dots (GQDs) can exhibit a range of spectacular phenomena such as the Klein-tunneling-induced quasibound states1-6 and Berry-phase-tuned energy spectra7-15. According to previous studies, all these interesting quantum phenomena seem to be well understood in the free electron picture1-15. However, electronic motion in the GQDs is reduced to qu

Simon Forest, Samuel Mimram

Precategories generalize both the notions of strict $n$-category and sesquicategory: their definition is essentially the same as the one of strict $n$-categories, excepting that we do not require the various interchange laws to hold. Those have been proposed as a framework in which one can express semi-strict definitions of weak higher categories: in dimensi

Rui-Yang Ju, Yu-Shian Lin, Yanlin Jin, Chih-Chia Chen

The efficient extraction of text information from the background in degraded color document images is an important challenge in the preservation of ancient manuscripts. The imperfect preservation of ancient manuscripts has led to different types of degradation over time, such as page yellowing, staining, and ink bleeding, seriously affecting the results of d

Maria-Andreea Filip, David Muñoz Ramo, Nathan Fitzpatrick

Subspace diagonalisation methods have appeared recently as promising means to access the ground state and some excited states of molecular Hamiltonians by classically diagonalising small matrices, whose elements can be efficiently obtained by a quantum computer. The recently proposed Variational Quantum Phase Estimation (VQPE) algorithm uses a basis of real

Vivien van Veldhuizen

This work is an exploratory research concerned with determining in what way reinforcement learning can be used to predict optimal PID parameters for a robot designed for apple harvest. To study this, an algorithm called Advantage Actor Critic (A2C) is implemented on a simulated robot arm. The simulation primarily relies on the ROS framework. Experiments for

Siddhartha Siddhiprada Bhoi, Paramapalli Udaya, Abhay Kumar Singh

DNA sequences are prone to creating secondary structures by folding back on themselves by non-specific hybridization among its nucleotides. The formation of secondary structures makes the sequences chemically inactive towards synthesis and sequencing processes. In this letter, our goal is to tackle the problems due to the creation of secondary structures in

Seong-Woong Kim, Dong-Wan Choi

This paper introduces and studies zero-base generalized few-shot learning (zero-base GFSL), which is an extreme yet practical version of few-shot learning problem. Motivated by the cases where base data is not available due to privacy or ethical issues, the goal of zero-base GFSL is to newly incorporate the knowledge of few samples of novel classes into a pr