April 2023 arXiv papers — page 9

Chen Fengxian, Lv Xiaoyao

Based on the panel data of 283 prefecture-level cities in China from 2006 to 2019, this paper measures the extent and mechanism of the impact of RMB real effective exchange rate fluctuations on carbon emission intensity. The results show that: (1) For every 1% appreciation of the real effective exchange rate of RMB, the carbon emission intensity decreases by

Meagan Sundstrom, Rebeckah K. Fussell, Anna McLean Phillips, Mark Akubo

Research on nontraditional laboratory (lab) activities in physics shows that students often expect to verify predetermined results, as takes place in traditional activities. This understanding of what is taking place, or epistemic framing, may impact their behaviors in the lab, either productively or unproductively. In this paper, we present an analysis of s

Akio Kawasaki

Charged particle tracking has played a key role in the development of particle physics, particularly for understanding phenomena involving short-lived particles precisely. As a platform for high-resolution charged particle tracking, an array of Rydberg atoms is theoretically analyzed. Utilizing the Ramsey sequence to accumulate the phase shift between the gr

Julian J. Lenz, Michael Mandl, Andreas Wipf

We perform a lattice study of the ($2+1$)-dimensional Gross-Neveu model in a background magnetic field $B$ and at non-zero chemical potential $\mu$. The complex-action problem arising in our simulations using overlap fermions is under control. For $B=0$ we observe a first-order phase transition in $\mu$ even at non-vanishing temperatures. Our main finding, h

Junge Zhang, Feihu Zhang, Shaochen Kuang, Li Zhang

Labeling LiDAR point clouds for training autonomous driving is extremely expensive and difficult. LiDAR simulation aims at generating realistic LiDAR data with labels for training and verifying self-driving algorithms more efficiently. Recently, Neural Radiance Fields (NeRF) have been proposed for novel view synthesis using implicit reconstruction of 3D scen

David Bouget, Demah Alsinan, Valeria Gaitan, Ragnhild Holden Helland

For patients suffering from central nervous system tumors, prognosis estimation, treatment decisions, and postoperative assessments are made from the analysis of a set of magnetic resonance (MR) scans. Currently, the lack of open tools for standardized and automatic tumor segmentation and generation of clinical reports, incorporating relevant tumor character

Saddem Mamache, Marta Gałyńska, Katharina Boguslawski

The electron-detachment energy is measured by its ionization potential (IP). As a result, it is a fundamental observable and important molecular electronic signature in photoelectron spectroscopy. A precise theoretical prediction of electron-detachment energies or ionization potentials is essential for organic optoelectronic systems like transistors, solar c

Benedikt Fesl, Nurettin Turan, Wolfgang Utschick

This work proposes a generative modeling-aided channel estimator based on mixtures of factor analyzers (MFA). In an offline step, the parameters of the generative model are inferred via an expectation-maximization (EM) algorithm in order to learn the underlying channel distribution of a whole communication scenario inside a base station (BS) cell. Thereby, t

Alban Puech, Tristan Rigaut, Adrien Le Franc, William Templier

Microgrids are local energy systems that integrate energy production, demand, and storage units. They are generally connected to the regional grid to import electricity when local production and storage do not meet the demand. In this context, Energy Management Systems (EMS) are used to ensure the balance between supply and demand, while minimizing the elect

Pratik Ghosh, Bhaskar Chaudhury, Shishir Purohit, Vishv Joshi

The electron density is a key parameter to characterize any plasma. Most of the plasma applications and research in the area of low-temperature plasmas (LTPs) are based on the accurate estimations of plasma density and plasma temperature. The conventional methods for electron density measurements offer axial and radial profiles for any given linear LTP devic

Om Prakash Bhardwaj, Indranath Sengupta

If the Krull dimension of the semigroup ring is greater than one, then affine semigroups of maximal projective dimension ($\mathrm{MPD}$) are not Cohen-Macaulay, but they may be Buchsbaum. We give a necessary and sufficient condition for simplicial $\mathrm{MPD}$-semigroups to be Buchsbaum in terms of pseudo-Frobenius elements. We give certain characterizati

E. A. Martínez, J. Dai, M. Tallarida, N. M. Nemes

Oxide-based two-dimensional electron gases (2DEGs) have generated significant interest due to their potential for discovering novel physical properties. Among these, 2DEGs formed in KTaO3 stand out due to the recently discovered crystal face-dependent superconductivity and large Rashba splitting, both of which hold potential for future oxide electronics devi

Juan Vidal Alegria, Fredrik Rusek

Orthogonal multi-user multiple-input multiple-output (MU-MIMO) channels allow for optimum performance with simplified precoding/equalization, and they achieve maximum multiplexing gain which is shared fairly among users. Reconfigurable intelligent surface (RIS) constitutes a promising cost-efficient solution to improve the wireless channel, since they consis

Elisa Leonardelli, Alexandra Uma, Gavin Abercrombie, Dina Almanea

NLP datasets annotated with human judgments are rife with disagreements between the judges. This is especially true for tasks depending on subjective judgments such as sentiment analysis or offensive language detection. Particularly in these latter cases, the NLP community has come to realize that the approach of 'reconciling' these different subjective inte

Shufang Xie, Huishuai Zhang, Junliang Guo, Xu Tan

Transformer networks have become the preferred architecture for many tasks due to their state-of-the-art performance. However, the optimal way to implement residual connections in Transformer, which are essential for effective training, is still debated. Two widely used variants are the Post-Layer-Normalization (Post-LN) and Pre-Layer-Normalization (Pre-LN)

Jesper Derehag, Åke Johansson

In high performance systems it is sometimes hard to build very large graphs that are efficient both with respect to memory and compute. This paper proposes a data structure called Markov-chain-priority-queue (MCPrioQ), which is a lock-free sparse markov-chain that enables online and continuous learning with time-complexity of $O(1)$ for updates and $O(CDF^{-

Shoumeng Qiu, Feng Jiang, Haiqiang Zhang, Xiangyang Xue

3D point cloud semantic segmentation is one of the fundamental tasks for environmental understanding. Although significant progress has been made in recent years, the performance of classes with few examples or few points is still far from satisfactory. In this paper, we propose a novel multi-to-single knowledge distillation framework for the 3D point cloud

Agustina Fragueiro, Giorgia Committeri, Claire Cury

The incomplete hippocampal inversion (IHI) is an atypical anatomical pattern of the hippocampus. However, the hippocampus is not a homogeneous structure, as it consists of segregated subfields with specific characteristics. While IHI is not related to whole hippocampal volume, higher IHI scores have been associated to smaller CA1 in aging. Although the segme

Anand Pillay, Ningyuan Yao

In \cite{Pillay} and more formally in \cite{Onshuus-Pillay} it was asked whether open subgroups of $p$-adic algebraic groups are ($p$-adic) semialgebraic, equivalently, definable in the structure $(\mathbb Q_{p}, +, \times)$. We give a positive answer in the commutative case. Together with results of \cite{Prasad} this leads to a positive answer for reductiv

Lorenzo Mercolli, Konstantinos Zeimpekis, George A. Prenosil, Hendrik G. Rathke

Purpose: The physical properties of yttrium-90 (90Y) allow for imaging with positron emission tomography/computed tomography (PET/CT). The increased sensitivity of long axial field-of-view (LAFOV) PET/CT scanners possibly allows to overcome the small branching ratio for positron production from 90Y decays and to improve for the post-treatment dosimetry of 90

Sonal Sannigrahi, Josef van Genabith, Cristina Espana-Bonet

Dense vector representations for textual data are crucial in modern NLP. Word embeddings and sentence embeddings estimated from raw texts are key in achieving state-of-the-art results in various tasks requiring semantic understanding. However, obtaining embeddings at the document level is challenging due to computational requirements and lack of appropriate

Weidong Wang, Cheng Luo, Jiancheng An, Lu Gan

As a promising non-password authentication technology, radio frequency (RF) fingerprinting can greatly improve wireless security. Recent work has shown that RF fingerprinting based on deep learning can significantly outperform conventional approaches. The superiority, however, is mainly attributed to supervised learning using a large amount of labeled data,

N. I. Bondar', M. M. Katsova

BE Cet is a young solar analog with an age of 0.6 Gyr and a rotation period of 7.655 days. According to chromospheric and photospheric indices, its activity is higher than the solar one. An analysis of photometric data on the time interval between 1977 and 2019 shows the presence of only 6.76 yr cyclic variations in the mean brightness with an amplitude of 0

Jeroen Bollen, Jasper Steegmans, Jan Van den Bussche, Stijn Vansummeren

Graph Neural Networks (GNNs) are a form of deep learning that enable a wide range of machine learning applications on graph-structured data. The learning of GNNs, however, is known to pose challenges for memory-constrained devices such as GPUs. In this paper, we study exact compression as a way to reduce the memory requirements of learning GNNs on large grap

Yekimov Sergiy

Modeling of urban traffic flows is required due to the complexity of their successful forecasting, as well as due to the impact of various random factors on them, and the complexity of transport systems in modern cities. Forecasting of traffic flows can be used as an effective tool for making scientifically sound decisions when creating a long-term plan for

Anthony Gauvan

Given a set of integers $A \subset \mathbb{Z}$, we consider the smallest family $\mathcal{B}_{A^{n-1}}$ invariant by translation which contains the rectangles $$ R_{\boldsymbol{a}} = I_{a_1} \times \dots \times I_{a_{n-1}} \times I_{-(a_1+\dots+a_{n-1})}$$ for any $\boldsymbol{a} = (a_1,\dots,a_{n-1}) \in A^{n-1}$ and where $I_k = [0,2^k]$ for $k$ integer. W

Naif Mehanna, Walter Rudametkin

Web browsers have come a long way since their inception, evolving from a simple means of displaying text documents over the network to complex software stacks with advanced graphics and network capabilities. As personal computers grew in popularity, developers jumped at the opportunity to deploy cross-platform games with centralized management and a low barr

José Manuel Sánchez Ruiz, Francisco José Domínguez Mayo, Xavier Oriol, José Francisco Crespo

The popularity of open-source software (OSS) projects has grown significantly over the last few years with more organizations relying on them. As these projects become larger, the need for higher quality also increases. DevOps practices have been shown to improve quality and performance. The DORA benchmarking reports provide useful information to compare Dev

Nhi Nguyen, Le Nguyen, Constantino Álvarez Casado, Olli Silvén

Remote photoplethysmography (rPPG) offers a state-of-the-art, non-contact methodology for estimating human pulse by analyzing facial videos. Despite its potential, rPPG methods can be susceptible to various artifacts, such as noise, occlusions, and other obstructions caused by sunglasses, masks, or even involuntary facial contact, such as individuals inadver

Andrew Slattery

We extend the classical work of Kock on strong and commutative monads, as well as the work of Hyland and Power for 2-monads, in order to define strong and pseudocommutative relative pseudomonads. In order to achieve this, we work in the more general setting of 2-multicategories rather than monoidal 2-categories. We prove analogous implications to the classic

Leonore Röseler, Ingo Scholtes, Christoph Gote

Background: Despite a growing body of literature on the impact of software bots on open source software development teams, their effects on team communication, coordination, and collaboration practices are not well understood. Bots can have negative consequences, such as producing information overload or reducing interactions between developers. Objective: T

Tiangang Cui, Josef Dick, Friedrich Pillichshammer

We study numerical integration over bounded regions in $\mathbb{R}^s, s\ge1$ with respect to some probability measure. We replace random sampling with quasi-Monte Carlo methods, where the underlying point set is derived from deterministic constructions that aim to fill the space more evenly than random points. Such quasi-Monte Carlo point sets are ordinarily

Ľubomír Baňas, Jean Daniel Mukam

We study the sharp interface limit of the stochastic Cahn-Hilliard equation with cubic double-well potential and additive space-time white noise $\epsilon^{\sigma}\dot{W}$ where $\epsilon>0$ is an interfacial width parameter. We prove that, for sufficiently large scaling constant $\sigma >0$, the stochastic Cahn-Hilliard equation converges to the determinist

Bao Wang, Jun-Jie Wei, Xue-Feng Wu, Martín López-Corredoira

Fast radio bursts (FRBs) have been suggested as an excellent celestial laboratory for testing the zero-mass hypothesis of the photon. In this work, we use the dispersion measure (DM)--redshift measurements of 23 localized FRBs to revisit the photon rest mass $m_{\gamma}$. As an improvement over previous studies, here we take into account the more realistic p

Yekimov Sergiy

Agricultural production is the main source of greenhouse gas emissions, and therefore it has a great influence on the dynamics of changes in global warming. The article investigated the problems faced by Czech agricultural producers on the way to reduce greenhouse gas emissions. The author analyzed the dynamics of greenhouse gas emissions by various branches

Son Pham-Ba, Jean-François Molinari

We employ a novel discrete element method (DEM) force formulation to simulate adhesive wear and assess the effects of material and loading parameters on the properties of the third-body layer (TBL) formed during sliding motion. The study emphasizes the role of a material's critical length scale d* in the rheology of the TBL. This critical length scale is alr

Takehiro Ito, Naonori Kakimura, Naoyuki Kamiyama, Yusuke Kobayashi

We prove that the computation of a combinatorial shortest path between two vertices of a graph associahedron, introduced by Carr and Devadoss, is NP-hard. This resolves an open problem raised by Cardinal. A graph associahedron is a generalization of the well-known associahedron. The associahedron is obtained as the graph associahedron of a path. It is a tant

Antonin Chambolle, Vincent Duval, Joao Miguel Machado

We propose a variational approach to approximate measures with measures uniformly distributed over a 1 dimentional set. The problem consists in minimizing a Wasserstein distance as a data term with a regularization given by the length of the support. As it is challenging to prove existence of solutions to this problem, we propose a relaxed formulation, which

Felix Stollenwerk

This paper provides a detailed discussion of the multilingual tokenizer used for GPT-SW3. It was trained on the Nordic Pile using the SentencePiece library and the BPE algorithm. We outline the tokenizer's most important features and share details on its learned vocabulary. In addition, we systematically analyze the properties and evaluate the performance of

D. Dorer, M. H. Frosz, S. Haze, M. Deiß

We report on an anti-resonant hollow-core fiber (AR-HCF) designed for stable transmission of laser light in a broad wavelength range of 250 nm to 450 nm. We tested for wavelengths of 300 nm and 320 nm. The characterized fiber shows a low transmission power attenuation of 0.13 dB/m and an excellent single-mode profile. The fiber maintains stable transmission

Arvid Becker, Pedro Cabalar, Martín Diéguez, Torsten Schaub

In temporal extensions of Answer Set Programming (ASP) based on linear-time, the behavior of dynamic systems is captured by sequences of states. While this representation reflects their relative order, it abstracts away the specific times associated with each state. However, timing constraints are important in many applications like, for instance, when plann

Florin Fabsits, Alfred Geroldinger, Andreas Reinhart, Qinghai Zhong

Let $G$ be an additive abelian group. A sequence $S=g_1\cdot\ldots\cdot g_{\ell}$ of terms from $G$ is a plus-minus weighted zero-sum sequence if there are $\varepsilon_1,\ldots,\varepsilon_{\ell}\in\{-1,1\}$ such that $\varepsilon_1 g_1+\ldots+\varepsilon_{\ell} g_{\ell}=0$. We first characterize (in terms of $G$) when the monoid $\mathcal{B}_{\pm}(G)$ of p

Jorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski

Preoperative radiological identification of mandibular canals is essential for maxillofacial surgery. This study demonstrates the reproducibility of a deep learning system (DLS) by evaluating its localisation performance on 165 heterogeneous cone beam computed tomography (CBCT) scans from 72 patients in comparison to an experienced radiologist's annotations.

Pavel Exner, Semjon Vugalter

The aim of this paper is to show that a two-dimensional Schr\"odinger operator with the potential in the form of a `ditch' of a fixed profile can have a geometrically induced discrete spectrum; this happens if such a potential channel has a single or multiple bends being straight outside a compact. Moreover, under stronger geometric restrictions the claim re

Ruslan Salikhov, Fabian Samad, Sebastian Schneider, Darius Pohl

Magnetic nano-objects possess great potential for more efficient data processing, storage and neuromorphic type of applications. Using high perpendicular magnetic anisotropy synthetic antiferromagnets in the form of multilayer-based metamaterials we purposely reduce the antiferromagnetic (AF) interlayer exchange energy below the out-of-plane demagnetization

Carlos Sebastián, Carlos E. González-Guillén

Feature selection is one of the most relevant processes in any methodology for creating a statistical learning model. Usually, existing algorithms establish some criterion to select the most influential variables, discarding those that do not contribute to the model with any relevant information. This methodology makes sense in a static situation where the j

Vassilis Lyberatos, Paraskevi-Antonia Theofilou, Jason Liartis, Georgios Siolas

The growing availability of digitized art collections has created the need to manage, analyze and categorize large amounts of data related to abstract concepts, highlighting a demanding problem of computer science and leading to new research perspectives. Advances in artificial intelligence and neural networks provide the right tools for this challenge. The

Aram-Alexandre Pooladian, Heli Ben-Hamu, Carles Domingo-Enrich, Brandon Amos

Simulation-free methods for training continuous-time generative models construct probability paths that go between noise distributions and individual data samples. Recent works, such as Flow Matching, derived paths that are optimal for each data sample. However, these algorithms rely on independent data and noise samples, and do not exploit underlying struct

M. Halilsoy, V. Memari

Certain well-known spacetimes of general relativity (GR) are generated from the collision of suitable null-sources coupled with gravitational waves. This is a classical process underlying the full nonlinearity of GR that may be considered alternative to the quantum creativity at a large scale. Schwarzschild, de Sitter, anti de Sitter and the $\gamma $-metric

Chengyuan Liu, Fubang Zhao, Yangyang Kang, Jingyuan Zhang

Universal Information Extraction (UIE) is an area of interest due to the challenges posed by varying targets, heterogeneous structures, and demand-specific schemas. However, previous works have only achieved limited success by unifying a few tasks, such as Named Entity Recognition (NER) and Relation Extraction (RE), which fall short of being authentic UIE mo

Tomohiro Inagaki, Hiroki Sakamoto, Masahiko Taniguchi

The cosmology of the $F(R)$ gravity rebuilding by the Cartan formalism is investigated. This is called Cartan $F(R)$ gravity. The well-known $F(R)$ gravity has been introduced to extend the standard cosmology, e.g. to explain the cosmological accelerated expansion as the inflation. Cartan $F(R)$ gravity is based on the Riemann-Cartan geometry. The curvature

Antonia Bertolino, Guglielmo De Angelis, Felicita Di Giandomenico, Francesca Lonetti

Cross-coverage of a program P refers to the test coverage measured over a different program Q that is functionally equivalent to P. The novel concept of cross-coverage can find useful applications in the test of redundant software. We apply here cross-coverage for test suite augmentation and show that additional test cases generated from the coverage of an e

Mor Geva, Jasmijn Bastings, Katja Filippova, Amir Globerson

Transformer-based language models (LMs) are known to capture factual knowledge in their parameters. While previous work looked into where factual associations are stored, only little is known about how they are retrieved internally during inference. We investigate this question through the lens of information flow. Given a subject-relation query, we study ho

Bruno Mlodozeniec, Matthias Reisser, Christos Louizos

Well-tuned hyperparameters are crucial for obtaining good generalization behavior in neural networks. They can enforce appropriate inductive biases, regularize the model and improve performance -- especially in the presence of limited data. In this work, we propose a simple and efficient way for optimizing hyperparameters inspired by the marginal likelihood,

Andrei Voinea, Robin Kock, Maruf A. Dhali

Losing pets can be highly distressing for pet owners, and finding a lost pet is often challenging and time-consuming. An artificial intelligence-based application can significantly improve the speed and accuracy of finding lost pets. To facilitate such an application, this study introduces a contrastive neural network model capable of accurately distinguishi

Arun Debray

In the presence of a nonzero B-field, the symmetries of the $\mathrm E_8\times \mathrm E_8$ heterotic string form a 2-group, or a categorified group, as do the symmetries of the CHL string. We express the bordism groups of the corresponding tangential structures as twisted string bordism groups, then compute them through dimension 11 modulo a few unresolved

Joaquim Bruna

We discuss a version of the fundamental theorem of calculus in several variables and some applications, of potential interest as a teaching material in undergraduate courses.

Xing Liu, Andrew B. Duncan, Axel Gandy

Kernelized Stein discrepancy (KSD) is a score-based discrepancy widely used in goodness-of-fit tests. It can be applied even when the target distribution has an unknown normalising factor, such as in Bayesian analysis. We show theoretically and empirically that the KSD test can suffer from low power when the target and the alternative distributions have the

Gaven Martin, Cong Yao

The generalised Hopf equation is the first order nonlinear equation with data $\Phi$ a holomorphic functions and $\eta\geq 1$ a positive weight, \[ h_w\,\overline{h_\wbar}\,\eta(w) = \Phi.\] The Hopf equation is the special case $\eta(w)=\tilde{\eta}(h(w))$ and reflects that $h$ is harmonic with respect to the conformal metric $\sqrt{\tilde{\eta}(z)}|dz|$. T

Chunxi Ji, Adnan Darwiche

Two types of explanations have been receiving increased attention in the literature when analyzing the decisions made by classifiers. The first type explains why a decision was made and is known as a sufficient reason for the decision, also an abductive explanation or a PI-explanation. The second type explains why some other decision was not made and is know

Josep Martí, Pedro L. Luque-Escamilla, Estrella Sánchez-Ayaso

Aims. We address the problem of young stellar objects that are found too far away from possible star formation sites. Different mechanisms have been proposed before to explain this unexpected circumstance. The idea of high-velocity protostars is one of these mechanisms, although observational support is not always easy to obtain. We aim to shed light on this

Arkadiusz Bochniak, Andrzej Sitarz

We derive the exact form of the spectral interaction of two strings mediated by a constant scalar field using methods derived from noncommutative geometry. This is achieved by considering a non-product modification of the Connes-Lott model with two-dimensional manifolds. The analogy with the latter construction justifies the interpretation of the scalar fiel

Magali Bardet, Rocco Mora, Jean-Pierre Tillich

A long standing open question is whether the distinguisher of high rate alternant codes or Goppa codes \cite{FGOPT11} can be turned into an algorithm recovering the algebraic structure of such codes from the mere knowledge of an arbitrary generator matrix of it. This would allow to break the McEliece scheme as soon as the code rate is large enough and would

Olga I. Vinogradova, Elena F. Silkina, Evgeny S. Asmolov

We discuss how the wettability of solid walls impacts electrokinetic properties, from large systems to a nanoscale. We show in particular how could the hydrophobic slippage, coupled to confinement effects, be exploited to induce novel electrokinetic properties, such as a salt-dependent giant amplification of zeta potential and conductivity, and a much more e

Stefano Berrone, Stefano Scialò, Gioana Teora

The use of orthonormal polynomial bases has been found to be efficient in preventing ill-conditioning of the system matrix in the primal formulation of Virtual Element Methods (VEM) for high values of polynomial degree and in presence of badly-shaped polygons. However, we show that using the natural extension of a orthogonal polynomial basis built for the pr

Bijendra Kumar Vishvakarma, Dharm Veer Singh, Sanjay Siwach

We investigate the black hole (BH) solution of the Einstein's gravity coupled with non-linear electrodynamics (NED) source in the background of a cloud of strings. We analyze the horizon structure of the obtained BH solution. The optical features of the BH are explored. The photon radius and shadows of the BH are obtained as a function of black hole paramete

Yuki Miyakawa, Hidenori Sonoda, Hiroshi Suzuki

The gradient flow exact renormalization group (GFERG) is an idea that incorporates gauge invariant gradient flows into the formalism of the exact renormalization group (ERG). GFERG introduces a Wilson action with a cutoff while keeping vector gauge invariance manifestly. The details of the formalism are still to be worked out. In this paper, we apply GFERG t

José Espírito Santo, Filipa Mendes

The essence of compiling with continuations is that conversion to continuation-passing style (CPS) is equivalent to a source language transformation converting to administrative normal form (ANF). Taking as source language Moggi's computational lambda-calculus (lbc), we define an alternative to the CPS-translation with target in the sequent calculus LJQ, nam

Renan Câmara Pereira, Pedro Costa

In this work we introduce the concept of Cartan-Polyakov loops, a special subset of Polyakov loops in the fundamental representation of the $\mathrm{SU}(N_c)$ group, with charges $k=1,\ldots,(N_c-1)/2$. It constitutes a sufficient set of independent degrees of freedom and it is used to parametrize the thermal Wilson line. Polyakov loops not contained in this

Joris Mulder, Nial Friel, Philip Leifeld

The exponential random graph (ERGM) model is a commonly used statistical framework for studying the determinants of tie formations from social network data. To test scientific theories under the ERGM framework, statistical inferential techniques are generally used based on traditional significance testing using p-values. This methodology has certain limitati

Jennifer Cobbe, Michael Veale, Jatinder Singh

Academic and policy proposals on algorithmic accountability often seek to understand algorithmic systems in their socio-technical context, recognising that they are produced by 'many hands'. Increasingly, however, algorithmic systems are also produced, deployed, and used within a supply chain comprising multiple actors tied together by flows of data between

Jiaxin Geng, Heping Wang

We study multivariate approximation of periodic function in the worst case setting with the error measured in the $L_\infty$ norm. We consider algorithms that use standard information $\Lambda^{\rm std}$ consisting of function values or general linear information $\Lambda^{\rm all}$ consisting of arbitrary continuous linear functionals. We investigate the eq

S. Doner, S. Ak, O. Onal Tas, O. Plevne

Age-metallicity relation for the Galactic disc is a crucial tool and to constrain the Galactic chemical evolution models. We investigate the age-metallicity relation of the Galactic disc using the red giant branch stars in the Solar neighbourhood. The data cover the Galactocentric radius of $7\leq R_{\rm gc} (\rm kpc) \leq9.5$, but extends up to 4 kpc in hei

Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke

This paper presents the FlowTransformer framework, a novel approach for implementing transformer-based Network Intrusion Detection Systems (NIDSs). FlowTransformer leverages the strengths of transformer models in identifying the long-term behaviour and characteristics of networks, which are often overlooked by most existing NIDSs. By capturing these complex

Annerose Eichel, Helena Schlipf, Sabine Schulte im Walde

We propose a novel approach to learn domain-specific plausible materials for components in the vehicle repair domain by probing Pretrained Language Models (PLMs) in a cloze task style setting to overcome the lack of annotated datasets. We devise a new method to aggregate salient predictions from a set of cloze query templates and show that domain-adaptation

Jean-Baptiste Casteras, Ilkka Holopainen, Léonard Monsaingeon

We construct a blowing-up solution for the energy critical focusing biharmonic nonlinear Schr\"odinger equation in infinite time in dimension $N\geq 13$. Our solution is radially symmetric and converges asymptotically to the sum of two bubbles. The scale of one of the bubble is of order $1$ whereas the other one is of order $|t|^{-\frac{2}{N-12}}$. Moreover,

A. Frasca, J. Alonso-Santiago, G. Catanzaro, A. Bragaglia

ASCC 123 is a little-studied young and dispersed open cluster. Recently, we conducted the first research devoted to it. In this paper, we complement our previous work with TESS photometry for the 55 likely members of the cluster. We pay special attention to seven of these high-probability members, all with FGK spectral types, for which we have high-resolutio

Caglar Demir, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo

Most real-world knowledge graphs, including Wikidata, DBpedia, and Yago are incomplete. Answering queries on such incomplete graphs is an important, but challenging problem. Recently, a number of approaches, including complex query decomposition (CQD), have been proposed to answer complex, multi-hop queries with conjunctions and disjunctions on such graphs.

Arindam Mallick, Alexei Andreanov, Sergej Flach

We demonstrate the existence of an intermediate super-exponential localization regime for eigenstates of the Aubry-Andr\'e chain. In this regime, the eigenstates localize factorially similarly to the eigenstates of the Wannier-Stark ladder. The super-exponential decay emerges on intermediate length scales for large values of the $\textit{winding length}$ --

R. A. Burns, Y. Uno, N. Sakai, J. Blanchard

High-mass protostars (M$_{\star} >$ 8 M$_{\odot}$) are thought to gain the majority of their mass via short, intense bursts of growth. This episodic accretion is thought to be facilitated by gravitationally unstable and subsequently inhomogeneous accretion disks. Limitations of observational capabilities, paired with a lack of observed accretion burst events

R. A. Burns, K. Sugiyama, T. Hirota, Kee-Tae Kim

High-mass stars are thought to accumulate much of their mass via short, infrequent bursts of disk-aided accretion. Such accretion events are rare and difficult to observe directly but are known to drive enhanced maser emission. In this Letter we report high-resolution, multi-epoch methanol maser observations toward G358.93-0.03 which reveal an interesting ph

Harsh Rangwani, Shrinivas Ramasubramanian, Sho Takemori, Kato Takashi

Self-training based semi-supervised learning algorithms have enabled the learning of highly accurate deep neural networks, using only a fraction of labeled data. However, the majority of work on self-training has focused on the objective of improving accuracy, whereas practical machine learning systems can have complex goals (e.g. maximizing the minimum of r

Martin Averseng, Euan A. Spence, Jeffrey Galkowski

For $h$-FEM discretisations of the Helmholtz equation with wavenumber $k$, we obtain $k$-explicit analogues of the classic local FEM error bounds of [Nitsche, Schatz 1974], [Wahlbin 1991], [Demlow, Guzm\'an, Schatz 2011], showing that these bounds hold with constants independent of $k$, provided one works in Sobolev norms weighted with $k$ in the natural way

Hendrik Sommerhoff, Shashank Agnihotri, Mohamed Saleh, Michael Moeller

The success of deep learning is frequently described as the ability to train all parameters of a network on a specific application in an end-to-end fashion. Yet, several design choices on the camera level, including the pixel layout of the sensor, are considered as pre-defined and fixed, and high resolution, regular pixel layouts are considered to be the mos

Horst Stühler, Marc-André Zöller, Dennis Klau, Alexandre Beiderwellen-Bedrikow

Price forecasting for used construction equipment is a challenging task due to spatial and temporal price fluctuations. It is thus of high interest to automate the forecasting process based on current market data. Even though applying machine learning (ML) to these data represents a promising approach to predict the residual value of certain tools, it is har

Yuri Hasegawa, Takuma Yamaguchi, Matthias Meissner, Takahiro Ueba

The impact of van der Waals interaction on the electronic structure between a pentacene monolayer and a graphite surface was investigated. Upon cooling the monolayer, newly formed dispersive bands, showing the constant final state nature overlapping with the non-dispersive, discrete molecular orbital state, is observed by low-energy angle-resolved photoelect

Reza Rastegar

We offer elementary proofs for several results in consecutive pattern containment that were previously demonstrated using ideas from cluster method and analytical combinatorics. Furthermore, we establish new general bounds on the growth rates of consecutive pattern avoidance in permutations.

Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng

Making the content generated by Large Language Model (LLM), accurate, credible and traceable is crucial, especially in complex knowledge-intensive tasks that require multi-step reasoning and each step needs knowledge to solve. Retrieval-augmented generation is good potential to solve this problem. However, where and how to introduce Information Retrieval (IR

Sabuzima Nayak, Ripon Patgiri

K-mer counting is a requisite process for DNA assembly because it speeds up its overall process. The frequency of K-mers is used for estimating the parameters of DNA assembly, error correction, etc. The process also provides a list of district K-mers which assist in searching large databases and reducing the size of de Bruijn graphs. Nonetheless, K-mer count

Laura Puente-Santamaría, Luis del Peso

Single-cell transcriptomics techniques, such as scRNA-seq, attempt to characterize gene expression profiles in each cell of a heterogeneous sample individually. Due to growing amounts of data generated and the increasing complexity of the computational protocols needed to process the resulting datasets, the demand for dedicated training in mathematical and p

Toby Kay, Luca Giuggioli

We derive, through subordination techniques, a generalized Feynman-Kac equation in the form of a time fractional Schrodinger equation. We relate such equation to a functional which we name the subordinated local time. We demonstrate through a stochastic treatment how this generalized Feynman-Kac equation describes subdiffusive processes with reactions. In th

Santiago Márquez Solís

This research article presents various design patterns for improving interoperability in Polkadot, a blockchain platform. These patterns include chain bridges, interoperability standards, common asset identifiers, governance agreements, oracle chains, and a hypothetical design pattern called Zero Trust Chain. Implementation of these design patterns can help

Sajanthan Sekaran, Oussama Bindech, Emmanuel Fromager

The equivalence in one-electron quantum bath between the practical implementation of density matrix embedding theory (DMET) and the more recent Householder-transformed density matrix functional embedding theory has been shown previously in the standard but special case where the reference full-size (one-electron reduced) density matrix, from which the bath i

Yu Pang, Jinjin Liu, Zeyu Xiang, Xuanhui Fan

This work reports the thermal conductivity of RbV3Sb5 and CsV3Sb5 with three-dimensional charge density wave phase transitions from 80 K to 400 K measured by pump-probe thermoreflectance techniques. The in-plane (basal plane) thermal conductivities are found moderate, i.e., 12 W/mK of RbV3Sb5 and 8.8 W/mK of CsV3Sb5 at 300 K. Low cross-plane (stacking direct

Giuseppe Ortolano, Alberto Paniate, Pauline Boucher, Carmine Napoli

Quantum entanglement and squeezing have significantly improved phase estimation and imaging in interferometric settings beyond the classical limits. However, for a wide class of non-interferometric phase imaging/retrieval methods vastly used in the classical domain e.g., ptychography and diffractive imaging, a demonstration of quantum advantage is still miss

Christoph Walker

The generator of the semigroup associated with linear age-structured population models including spatial diffusion is shown to have compact resolvent.

Vicente Azcoiti

Using general properties of the $Q=0$ topological sector we previously argued that a vector-like theory, with chiral $U(1)_A$ anomaly, and exact non-Abelian chiral symmetry, should exhibit divergent susceptibilities in the chiral limit, the two-flavor Schwinger model being a paradigmatic example of the realization of this scenario. Two flavor $QCD$ at $T>T_c

Michael Lampis, Manolis Vasilakis

We revisit two well-studied problems, Bounded Degree Vertex Deletion and Defective Coloring, where the input is a graph $G$ and a target degree $\Delta$ and we are asked either to edit or partition the graph so that the maximum degree becomes bounded by $\Delta$. Both are known to be parameterized intractable for treewidth. We revisit the parameterization by

Hüsnü Ata Erbay, Saadet Erbay, Albert Kohen Erkip

We consider a second-order nonlinear wave equation with a linear convolution term. When the convolution operator is taken as the identity operator, our equation reduces to the classical elasticity equation which can be written as a $p$-system of first-order differential equations. We first establish the local well-posedness of the Cauchy problem. We then inv

Ilia Kopchinskii, Petr Satunin

We study the process of resonant generation of high-order harmonics in a closed cavity in the model of vacuum nonlinear electrodynamics. Concretely, we study the possibility of resonant generation of the third harmonic induced by a single electromagnetic mode in a radiofrequency cavity, as well as resonant generation of a combined frequency mode induced by t