May 2022 arXiv papers — page 132

Achkan Salehi, Stephane Doncieux

While the field of Quality-Diversity (QD) has grown into a distinct branch of stochastic optimization, a few problems, in particular locomotion and navigation tasks, have become de facto standards. Are such benchmarks sufficient? Are they representative of the key challenges faced by QD algorithms? Do they provide the ability to focus on one particular chall

Gengshan Wang, Zhijia Yang, Tierui Gong

In this letter, we investigate the millimeter wave (mmWave) downlink multiuser multiple-input multiple-output (MU-MIMO) system, adopting the dynamic subarray architecture at the base station and considering the multi-stream communication for each user. Aiming at maximizing the system spectral efficiency, we propose a novel hybrid beamforming design. First, a

Frederick Anderson, Anirban Ghosh, Matthew Graham, Lucas Mougeot

The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, eleven algorithms have been designed with various trade-offs in degree and stretch factor. We have implemented these sophisticated algorithms in C++ using the CG

Maldon Patrice Goodridge, Subhash Lakshminarayana, Christopher Few

By manipulating tens of thousands of internet-of-things (IoT) enabled high-wattage electrical appliances (e.g., WiFi-controlled air-conditioners), large-scale load-altering attacks (LAAs) can cause severe disruptions to power grid operations. In this work, we present a rare-event sampling approach to identify LAAs that lead to critical network failure events

Ahmet Batal, Neslihan Gügümcü

The region select game, introduced by Ayaka Shimizu, Akio Kawauchi and Kengo Kishimoto, is a game that is played on knot diagrams whose crossings are endowed with two colors. The game is based on the region crossing change moves that induce an unknotting operation on knot diagrams. We generalize the region select game to be played on a knot diagram endowed w

Louis Pujol

In this paper, we propose a theoretical analysis of the algorithm ISDE, introduced in previous work. From a dataset, ISDE learns a density written as a product of marginal density estimators over a partition of the features. We show that under some hypotheses, the Kullback-Leibler loss between the proper density and the output of ISDE is a bias term plus the

Paolo Baldi, Hykel Hosni

We provide a logical framework in which a resource-bounded agent can be seen to perform approximations of probabilistic reasoning. Our main results read as follows. First we identify the conditions under which propositional probability functions can be approximated by a hierarchy of depth-bounded Belief functions. Second we show that under rather palatable r

Ahmet M. Elbir, Sinem Coleri, Kumar Vijay Mishra

Channel estimation is a critical task in intelligent reflecting surface (IRS)-assisted wireless systems due to the uncertainties imposed by environment dynamics and rapid changes in the IRS configuration. To deal with these uncertainties, deep learning (DL) approaches have been proposed. Previous works consider centralized learning (CL) approach for model tr

Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin

Simulation is a crucial tool for accelerating the development of autonomous vehicles. Making simulation realistic requires models of the human road users who interact with such cars. Such models can be obtained by applying learning from demonstration (LfD) to trajectories observed by cars already on the road. However, existing LfD methods are typically insuf

Alexander Fishkov, Maxim Panov

Accounting for the uncertainty in the predictions of modern neural networks is a challenging and important task in many domains. Existing algorithms for uncertainty estimation require modifying the model architecture and training procedure (e.g., Bayesian neural networks) or dramatically increase the computational cost of predictions such as approaches based

Lin Zhang, Jinping Huang, Jiamei Wang, Shao-Ming Fei

We study the uncertainties of quantum mechanical observables, quantified by the standard deviation (square root of variance) in Haar-distributed random pure states. We derive analytically the probability density functions (PDFs) of the uncertainties of arbitrary qubit observables. Based on these PDFs, the uncertainty regions of the observables are characteri

Nan Zhong, Zhenxing Qian, Xinpeng Zhang

Backdoor attacks are rapidly emerging threats to deep neural networks (DNNs). In the backdoor attack scenario, attackers usually implant the backdoor into the target model by manipulating the training dataset or training process. Then, the compromised model behaves normally for benign input yet makes mistakes when the pre-defined trigger appears. In this pap

Eva Garcia-Martin, Albert Bifet, Niklas Lavesson, Rikard König

State-of-the-art machine learning solutions mainly focus on creating highly accurate models without constraints on hardware resources. Stream mining algorithms are designed to run on resource-constrained devices, thus a focus on low power and energy and memory-efficient is essential. The Hoeffding tree algorithm is able to create energy-efficient models, but

Wei Shi, Wei Xu, Xiaohu You, Chunming Zhao

Internet-of-Everything (IoE) has gradually been recognized as an integral part of future wireless networks. In IoE, there can be an ultra-massive number of smart devices of various types to be served, imposing multi-dimensional requirements on wireless communication, sensing, and security. In this article, we provide a tutorial overview of the promising inte

Mohamed Raed El aoun, Heng Li, Foutse Khomh, Moses Openja

With the advance in quantum computing, quantum software becomes critical for exploring the full potential of quantum computing systems. Recently, quantum software engineering (QSE) becomes an emerging area attracting more and more attention. However, it is not clear what are the challenges and opportunities of quantum computing facing the software engineerin

Jin-Yan Zhu, Yong Chen

In this paper, we mainly investigate the long-time asymptotic behavior of the solution for the coupled dispersive AB system with weighted Sobolev initial data, which allows soliton solutions via the Dbar steepest descent method.Based on the spectral analysis of Lax pair, the Cauchy problem of the coupled dispersive AB system is transformed into a Riemann-Hil

Elaheh Shomali, Markus E. Gruner, Rossitza Pentcheva

The interaction of a femtosecond optical pulse with a Fe$_{1}$/(MgO)$_{3}$(001) metal/oxide heterostructure is investigated using time-dependent density functional theory (TDDFT) calculations in the real-time domain. We systematically study electronic excitations as a function of laser frequency, peak power density and polarization direction. While spin-orbi

Heloise Chomet, Samuel Plesnik, Constantin Nicolae, Jack Dunham

We study non-classical pathways and quantum interference in enhanced ionisation of diatomic molecules in strong laser fields using machine learning techniques. Quantum interference provides a bridge, which facilitates intramolecular population transfer. Its frequency is higher than that of the field, intrinsic to the system and depends on several factors, fo

Mateusz Stępniak, Jakub Mielczarek

Quantum networks open the way to an unprecedented level of communication security. However, due to physical limitations on the distances of quantum links, current implementations of quantum networks are unavoidably equipped with trusted nodes. As a consequence, the quantum key distribution can be performed only on the links. Due to this, some new authenticat

Pan Sun, Camilla Colombo, Mirko Trisolini, Shuang Li

This paper compares the continuum evolution for density equation modelling and the Gaussian mixture model on the 2D phase space long-term density propagation problem in the context of high-altitude and high area-to-mass ratio satellite long-term propagation. The density evolution equation, a pure numerical and pointwise method for the density propagation, is

N. Pontius, J. K. Dewhurst, C. Schuessler-Langeheine, S. Jana

Unveiling the key mechanisms that determine optically driven spin dynamics is essential both to probe the fundamental nature of ultrafast light-matter interactions, but also to drive future technologies of smaller, faster, and more energy efficient devices. Essential to this task is the ability to use experimental spectroscopic tools to evidence the underlyi

Michal Sobotka, Klaus G. Puschmann

High-resolution observations of horizontal motions in the penumbra are needed to complement the concept of penumbrae obtained from spectropolarimetry. Time series of intensity images of a large sunspot in AR 10634 acquired with the Swedish Solar Telescope in the G band and red continuum are analysed. The two simultaneous time series last six hours and five m

Wilhelm Ågren

Self-supervised learning is a growing paradigm in deep representation learning, showing great generalization capabilities and competitive performance in low-labeled data regimes. The SimCLR framework proposes the NT-Xent loss for contrastive representation learning. The objective of the loss function is to maximize agreement, similarity, between sampled posi

Pietro Butti, Margarita Garcia Perez, Antonio Gonzalez-Arroyo, Ken-Ichi Ishikawa

In this paper we study the large $N$ limit of four-dimensional Supersymmetric Yang-Mills on the lattice using twisted reduced models. We have generated configurations with dynamical massive gluinos and various lattice 't Hooft couplings, and verified that the Pfaffian remains positive. We have determined the lattice spacing in terms of various observable

Alisson R. Cadore, Raphaela de Oliveira, Raphael L. M. Lobato, Verônica de C. Teixeira

Naturally occurring van der Waals crystals have brought unprecedented interest to nanomaterial researchers in recent years. So far, more than 1800 layered materials (LMs) have been identified but only a few insulating and naturally occurring LMs were deeply investigated. Phyllosilicate minerals, which are a class of natural and abundant LMs, have been recent

Achkan Salehi, Alexandre Coninx, Stephane Doncieux

The Novelty Search (NS) algorithm was proposed more than a decade ago. However, the mechanisms behind its empirical success are still not well formalized/understood. This short note focuses on the effects of the archive on exploration. Experimental evidence from a few application domains suggests that archive-based NS performs in general better than when Nov

S A Dar, M Kamarujjama, R B Paris

We consider a generalisation of a definite integral involving the Bessel function of the first kind. It is shown that this integral can be expressed in terms of the Fox-Wright function ${}_pΨ_q(z)$ of one variable. Some consequences of this representation are explored by suitable choice of parameters. In addition, two closed-form evaluations of infinite seri

Cristina Balan, Jose Pena Garcia, Aymen Fassatoui, Jan Vogel

The manipulation of magnetism with a gate voltage is expected to lead the way towards the realization of energy-efficient spintronics devices and high-performance magnetic memories. Exploiting magneto-ionic effects under micro-patterned electrodes in solid-state devices adds the possibility to modify magnetic properties locally, in a non-volatile and reversi

Gcinizwe Dlamini, Imad Eddine Ibrahim Bekkouch, Adil Khan, Leon Derczynski

Misinformation has become a major concern in recent last years given its spread across our information sources. In the past years, many NLP tasks have been introduced in this area, with some systems reaching good results on English language datasets. Existing AI based approaches for fighting misinformation in literature suggest automatic stance detection as

Thanasis Vergoulis, Serafeim Chatzopoulos, Kleanthis Vichos, Ilias Kanellos

In recent years, assessing the performance of researchers has become a burden due to the extensive volume of the existing research output. As a result, evaluators often end up relying heavily on a selection of performance indicators like the h-index. However, over-reliance on such indicators may result in reinforcing dubious research practices, while overloo

Wolfgang Dvořák, Matthias König, Markus Ulbricht, Stefan Woltran

Argumentation Frameworks (AFs) are a key formalism in AI research. Their semantics have been investigated in terms of principles, which define characteristic properties in order to deliver guidance for analysing established and developing new semantics. Because of the simple structure of AFs, many desired properties hold almost trivially, at the same time hi

Zhenghang Yuan, Lichao Mou, Qi Wang, Xiao Xiang Zhu

Visual question answering (VQA) for remote sensing scene has great potential in intelligent human-computer interaction system. Although VQA in computer vision has been widely researched, VQA for remote sensing data (RSVQA) is still in its infancy. There are two characteristics that need to be specially considered for the RSVQA task. 1) No object annotations

Muhammad Alhroob

These proceedings present the first observation of single top-quark production associated with a photon using the full Run2 proton-proton dataset collected by the ATLAS experiment at the LHC.

Uwe Scheithauer

Bond pads are the electrical interconnections of a microelectronic device to the outside world. A polyimide layer (PI) on top of a microelectronic device protects the whole device against environmental impacts. The bond pads are accessible though openings in this electrically insulating layer. The oxide layer thickness and contaminations at the Al bond pad s

F. T. Brandt, J. Frenkel, D. G. C. McKeon, G. S. S. Sakoda

We examine, in the `t Hooft renormalization scheme, the analytic running coupling $\barα_t(Q^2)$ in QCD, using the two-loop $β$-function with positive expansion parameters $β_0$ and $β_1$. An exact integral representation is derived for this causal coupling, which is fully expressed in terms of the imaginary part of the Lambert function $W$. This integral fo

Yongyi Su, Xun Xu, Kui Jia

Addressing the annotation challenge in 3D Point Cloud segmentation has inspired research into weakly supervised learning. Existing approaches mainly focus on exploiting manifold and pseudo-labeling to make use of large unlabeled data points. A fundamental challenge here lies in the large intra-class variations of local geometric structure, resulting in subcl

H. M. Antia, P. C. Agrawal, Tilak Katoch, R. K. Manchanda

We present an improved background model for the Large Area X-ray Proportional Counter (LAXPC) detectors on-board AstroSat. Because of the large collecting area and high pressure, the LAXPC instrument has a large background count rate, which varies during the orbit. Apart from the variation with latitude and longitude during the orbit there is a prominent qua

Christopher Kolloff, Simon Olsson

Machine learning (ML) has emerged as a pervasive tool in science, engineering, and beyond. Its success has also led to several synergies with molecular dynamics (MD) simulations, which we use to identify and characterize the major metastable states of molecular systems. Typically, we aim to determine the relative stabilities of these states and how rapidly t

Nanny Strandqvist, Björn Erik Skovdal, Merlin Pohlit, Henry Stopfel

We demonstrate directional dependence of the self-modification of internal mesospin textures in magnetic metamaterials, arising from the coupling of the atomic- and mesoscopic length-scales. Dressing the mesospins in different directions enables the quantification of the degree of texture in the internal magnetization and its impact on the interaction energy

Jingwei Song, Qiuchen Zhu, Jianyu Lin, Maani Ghaffari

In stereoscope-based Minimally Invasive Surgeries (MIS), dense stereo matching plays an indispensable role in 3D shape recovery, AR, VR, and navigation tasks. Although numerous Deep Neural Network (DNN) approaches are proposed, the conventional prior-free approaches are still popular in the industry because of the lack of open-source annotated data set and t

Roberto Beneduci, Leon Loveridge

We give a necessary and sufficient condition for the incompatibility of a pair of effects in a general probabilistic model in which the state space is a total convex space, which can be obtained by minimising a real parameter. This has an interpretation in terms of the least noise that must be included to make the given pair compatible.

Dorothee D. Haroske, Leszek Skrzypczak, Hans Triebel

The paper deals with the problem under which conditions for the parameters $s_1,s_2\in\mathbb{R}$, $1\leq p,q_1,q_2\leq\infty$ the Fourier transform $\mathcal{F}$ is a nuclear mapping from $A^{s_1}_{p,q_1}(\mathbb{R}^n)$ into $A^{s_2}_{p,q_2}(\mathbb{R}^n)$, where $A\in\{B,F\}$ stands for a space of Besov or Triebel-Lizorkin type, and $n\in\mathbb{N}$. It ex

François A. Lavergne, Peter Sollich, Véronique Trappe

We show that the slow viscoelastic response of a foam is that of a power-law fluid with a terminal relaxation. Investigations of the foam mechanics in creep and recovery tests reveal that the power-law contribution is fully reversible, indicative of a delayed elastic response. We demonstrate how this contribution fully accounts for the non-Maxwellian feature

Károly Simon, Vilma Orgoványi

Using a similar random process to the one which yields the fractal percolation sets, starting from the deterministic Menger sponge we get the random Menger sponge. We examine its orthogonal projections from the point of Hausdorff dimension, Lebesgue measure and existence of interior points. We obtain these results as special cases of our theorems stated for

Hehan Teng, Tao He, Yuchen Guo, Guiguang Ding

Supervised person re-identification methods rely heavily on high-quality cross-camera training label. This significantly hinders the deployment of re-ID models in real-world applications. The unsupervised person re-ID methods can reduce the cost of data annotation, but their performance is still far lower than the supervised ones. In this paper, we make full

Federico De Luca, Cristian Ciracì

We propose surface modulation of the equilibrium charge density as a technique to control and enhance, via an external static potential, the free electron nonlinear response of heavily doped semiconductors. Within a hydrodynamic perturbative approach, we predict a two order of magnitude boost of free electron third-harmonic generation.

Matthew Chaffe

We study category $\mathcal{O}$ for Takiff Lie algebras $\mathfrak{g} \otimes \mathbb{C}[ε]/(ε^2)$ where $\mathfrak{g}$ is the Lie algebra of a reductive algebraic group over $\mathbb{C}$. We decompose this category as a direct sum of certain subcategories and use an analogue of parabolic induction functors and twisting functors for BGG category $\mathcal{O}

Andreas Schuler, Gabriele Kotsis

Developing energy-efficient software solutions is a tedious task. We need both, the awareness that energy-efficiency plays a key role in modern software development and the tools and techniques to support stakeholders involved in the software development lifecycle. So, we present the MANAi plugin which helps to make energy consumption of unit test methods ex

Lianming Zhang, Qian Wang, Pingping Dong, Yehua Wei

With the gradual deployment of 5G and the continuous popularization of edge intelligence (EI), the explosive growth of data on the edge of the network has promoted the rapid development of 6G and ubiquitous intelligence (UbiI). This article aims to explore a new method for modeling latency guarantees for UbiI in 6G given 6G's extremely stochastic nature

Ali Bou Nassif, Ashraf Elnagar, Omar Elgendy, Yaman Afadar

Social media is becoming a source of news for many people due to its ease and freedom of use. As a result, fake news has been spreading quickly and easily regardless of its credibility, especially in the last decade. Fake news publishers take advantage of critical situations such as the Covid-19 pandemic and the American presidential elections to affect soci

Mo Zhou, Kai Pan, Tian-Cheng Yi, Jian-Rong Zhou

The x-ray polycapillary lens is an optical device with good optic performance. Similar to the traditional X-ray polycapillary lens, square polycapillary slice lens was regulated on X-ray based on the full reflection principle of X-ray in the capillaries surfaces. According to its geometrical structure model and the X-ray tracing principle, a set of X-ray tra

Wongyu Kim, Youbin Ahn, Donghyun Kim, Kyong-Ho Lee

Each utterance in multi-turn empathetic dialogues has features such as emotion, keywords, and utterance-level meaning. Feature transitions between utterances occur naturally. However, existing approaches fail to perceive the transitions because they extract features for the context at the coarse-grained level. To solve the above issue, we propose a novel app

LAT Collaboration, S. Abdollahi, F. Acero, M. Ackermann

Cosmic rays are mostly composed of protons accelerated to relativistic speeds. When those protons encounter interstellar material, they produce neutral pions which in turn decay into gamma rays. This offers a compelling way to identify the acceleration sites of protons. A characteristic hadronic spectrum, with a low-energy break around 200 MeV, was detected

Martin Leitzinger, Petra Odert, Petr Heinzel

From the Sun we know that coronal mass ejections (CMEs) are a transient phenomenon, often correlated with flares. They have an impact on solar mass- and angular momentum loss, and therefore solar evolution, and make a significant part of space weather. The same is true for stars, but stellar CMEs are still not well constrained, although new methodologies hav

Mehedi Hasan, Abbas Khosravi, Ibrahim Hossain, Ashikur Rahman

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art performance for many applications, they still provide unreliable point predictions, which lack information about uncertainty estimates. Among various methods to enable neural networks

E. L. Brown, S. V. Jeffers, S. C. Marsden, J. Morin

Spectropolarimetric data allow for simultaneous monitoring of stellar chromospheric $\log{R^{\prime}_{\rm{HK}}}$ activity and the surface-averaged longitudinal magnetic field, $B_l$, giving the opportunity to probe the relationship between large-scale stellar magnetic fields and chromospheric manifestations of magnetism. We present $\log{R^{\prime}_{\rm{HK}}

Ankit Kumar Panda, Victor Roy

Here we study the wave propagation and stability of general relativistic non-resistive dissipative second-order magnetohydrodynamic equations in curved space-time. We solve the Boltzmann equation for a system of particles and antiparticles using the relaxation time approximation and the Chapman-Enskog-like gradient expansion for the off-equilibrium distribut

J. Stewart, P. K. Browning, M. Gordovskyy

Oscillatory reconnection is a process that has been suggested to underlie several solar and stellar phenomena, and is likely to play an important role in transient events such as flares. Quasi-periodic pulsations (QPPs) in flare emissions may be a manifestation of oscillatory reconnection, but the underlying mechanisms remain uncertain. In this paper, we pre

Depanshu Sani, Sandeep Mahato, Parichya Sirohi, Saket Anand

The integration of the modern Machine Learning (ML) models into remote sensing and agriculture has expanded the scope of the application of satellite images in the agriculture domain. In this paper, we present how the accuracy of crop type identification improves as we move from medium-spatiotemporal-resolution (MSTR) to high-spatiotemporal-resolution (HSTR)

Mathieu Bajodek, Frédéric Gouaisbaut, Alexandre Seuret

Recently, sufficient conditions of stability or instability for time-delay systems have been proven to be necessary. In this way, a remarkable necessary and sufficient condition has then been developed by Gomez et al. It is presented as a simple test of positive definiteness of a matrix issued from the Lyapunov matrix. In this paper, an extension of this res

Tianle Li, Yushi Sun, Shang-ling Hsu, Yanjia Li

The dissemination of fake news on social networks has drawn public need for effective and efficient fake news detection methods. Generally, fake news on social networks is multi-modal and has various connections with other entities such as users and posts. The heterogeneity in both news content and the relationship with other entities in social networks brin

Ian Marsh, Wolfgang John, Ali Balador, Federico Tonini

Emerging use-cases like smart manufacturing and smart cities pose challenges in terms of latency, which cannot be satisfied by traditional centralized networks. Edge networks, which bring computational capacity closer to the users/clients, are a promising solution for supporting these critical low latency services. Different from traditional centralized netw

François Copie, Pierre Suret, Stéphane Randoux

We experimentaly investigate higher-order seeded modulation instability in an optical fiber experiment. The recirculating loop configuration with round-trip losses compensation enables the observation in single-shot of the spatio-temporal evolution of an initially modulated continuous field revealing intricate yet deterministic dynamics. By tuning the modula

Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky

Machine Learning (ML) systems are getting increasingly popular, and drive more and more applications and services in our daily life. This has led to growing concerns over user privacy, since human interaction data typically needs to be transmitted to the cloud in order to train and improve such systems. Federated learning (FL) has recently emerged as a metho

Gargi Shaw, A. Ranjan

We explore indirect methods to detect Polycyclic Aromatic Hydrocarbons (PAHs) in gas-rich, absorption-selected galaxies at high redshift. We look at the optical VLT/X-shooter observations of an intervening, extremely strong damped Lyman-alpha absorber (or ESDLA, with log(N(HI))>~21.7)) towards QSO SDSS J1143+1420 at redshift, z(ESDLA)=2.323. Literature studi

Pierre Gosselin, Aïleen Lotz, Marc Wambst

This paper provides a general method to directly translate a classical economic framework with a large number of agents into a field-formalism model. This type of formalism allows the analytical treatment of economic models with an arbitrary number of agents, while preserving the system's interactions and microeconomic features of the individual level.We

Mattia Mattioni, Alessio Moreschini, Salvatore Monaco, Dorothée Normand-Cyrot

In this paper, we propose a new sampled-data controller for stabilization of the attitude dynamics at a desired constant configuration. The design is based on discrete-time interconnection and damping assignment (IDA) passivity-based control (PBC) and the recently proposed Hamiltonian representation of discrete-time nonlinear dynamics. Approximate solutions

Ferdi Kara, Hakan Kaya, Halim Yanikomeroglu

Diversity techniques have been applied for decades to overcome the effects of fading, which is one of the most challenging problems in wireless communications due to the randomness of the wireless channel. However, existing diversity techniques are resource-inefficient due to orthogonal resource usage, or they have high-power consumption due to multiple ante

Joy Ganguly

We present a model which employs $CP\times Z_3$ symmetries where quark mixing and charged leptons masses are explained by following some texture. To achieve neutrino mass and mixing, we write a non-renormalizable Lagrangian using type-II seesaw mechanism by assuming ${\mathcal{O}}(1)$ couplings predicting no $CP$ violation. Then, we calculate the value of th

Alexandros Bakas, Antonis Michalas

Secure cloud storage is an issue of paramount importance that both businesses and end-users should take into consideration before moving their data to, potentially, untrusted clouds. Migrating data to the cloud raises multiple privacy issues, as they are completely controlled by a cloud provider. Hence, an untrusted cloud provider can potentially breach user

Liangjun Song, Gang Sun, Hongfang Yu, Mohsen Guizani

In recent years, edge computing, as an important pillar for future networks, has been developed rapidly. Task offloading is a key part of edge computing that can provide computing resources for resource-constrained devices to run computing-intensive applications, accelerate computing speed and save energy. An efficient and feasible task offloading scheme can

Christian Soize

This paper deals with the taking into account a given set of realizations as constraints in the Kullback-Leibler minimum principle, which is used as a probabilistic learning algorithm. This permits the effective integration of data into predictive models. We consider the probabilistic learning of a random vector that is made up of either a quantity of intere

Markus Gahn, Iuliu Sorin Pop

In this work we present the homogenization of a reaction-diffusion model that includes an evolving microstructure. Such type of problems model, for example, mineral dissolution and precipitation in a porous medium. Hence, we are dealing with a multi-scale problem with free boundaries on the pore scale. In the initial state the microscopic geometry is given b

Zechen Li, Anders Søgaard

Synthetic datasets have successfully been used to probe visual question-answering datasets for their reasoning abilities. CLEVR (johnson2017clevr), for example, tests a range of visual reasoning abilities. The questions in CLEVR focus on comparisons of shapes, colors, and sizes, numerical reasoning, and existence claims. This paper introduces a minimally bia

Fabian Jan Schwarzendahl, Jens Grauer, Benno Liebchen, Hartmut Löwen

After more than 6 million deaths worldwide, the ongoing vaccination to conquer the COVID-19 disease is now competing with the emergence of increasingly contagious mutations, repeatedly supplanting earlier strains. Following the near-absence of historical examples of the long-time evolution of infectious diseases under similar circumstances, models are crucia

Jianing Wang, Chengyu Wang, Minghui Qiu, Qiuhui Shi

Extractive Question Answering (EQA) is one of the most important tasks in Machine Reading Comprehension (MRC), which can be solved by fine-tuning the span selecting heads of Pre-trained Language Models (PLMs). However, most existing approaches for MRC may perform poorly in the few-shot learning scenario. To solve this issue, we propose a novel framework name

Shuang Zhou, Michael Merrifield, Alfonso Aragon-Salamanca

We develop a novel semi-analytic spectral fitting approach to quantify the star-formation histories (SFHs) and chemical enrichment histories (ChEHs) of individual galaxies. We construct simple yet general chemical evolution models that account for gas inflow and outflow processes as well as star formation, to investigate the evolution of merger-free star-for

Ehsan Hamzei, Martin Tomko, Stephan Winter

Many place-related questions can only be answered by complex spatial reasoning, a task poorly supported by factoid question retrieval. Such reasoning using combinations of spatial and non-spatial criteria pertinent to place-related questions is increasingly possible on linked data knowledge bases. Yet, to enable question answering based on linked knowledge b

Guo Deng, Christopher J. Lustri

Travelling waves in woodpile chains are typically nanoptera, which are composed of a central solitary wave and exponentially small oscillations. These oscillations have been studied using exponential asymptotic methods, which typically require an explicit form for the leading-order behaviour. For many nonlinear systems, such as granular woodpile chains, it i

Alexei Sherman

To explain the low frequencies of quantum oscillations observed in lightly doped cuprates, we consider the two-dimension Hubbard model supplemented with the perpendicular magnetic field. For large Hubbard repulsions, the electron spectrum is investigated using the cluster perturbation theory. Obtained frequencies of magnetic oscillations at small deviations

M. H. Berntsen, O. Götberg, B. M. Wojek, O. Tjernberg

In spin- and angle-resolved photoemission spectroscopy (SARPES) the energy-momentum dispersion of electronic states in crystalline solids is measured along with the spin direction of the photoemitted electrons. The technique therefore allows for mapping out a material's band structure in a spin resolved fashion. By conducting SARPES measurements using lo

G. Pascoli

The determination of the velocities, accelerations and the gravitational field intensity at a given location in a galaxy could potentially be achieved in an unexpected manner with the environment of the observer, for instance, the local mean mass density in the galaxy. This idea, mathematically supported by the asymmetric distance concept, is illustrated her

Quanming Yao, Yaqing Wang, Bo Han, James Kwok

Nonconvex regularization has been popularly used in low-rank matrix learning. However, extending it for low-rank tensor learning is still computationally expensive. To address this problem, we develop an efficient solver for use with a nonconvex extension of the overlapped nuclear norm regularizer. Based on the proximal average algorithm, the proposed algori

Naoya Arakawa

We propose a new drag phenomenon, an interband magnon drag, and report on interaction effects and multiband effects in magnon transport of ferrimagnetic insulators. We study a spin-Seebeck coefficient $S_{\textrm{m}}$, a magnon conductivity $σ_{\textrm{m}}$, and a magnon thermal conductivity $κ_{\textrm{m}}$ of interacting magnons for a minimal model of ferr

Binbin Yang, Xinchi Deng, Han Shi, Changlin Li

Continual learning is a challenging real-world problem for constructing a mature AI system when data are provided in a streaming fashion. Despite recent progress in continual classification, the researches of continual object detection are impeded by the diverse sizes and numbers of objects in each image. Different from previous works that tune the whole net

Xinhong Jiang, Zhifang Yang, Lin Wu, Zhangqi Dang

We propose and experimentally demonstrate a fiber spectrum analyzer based on a planar waveguide chip butt-coupled with an input fiber and aligned to a standard camera without any free-space optical elements. The chip consists of a single-mode waveguide to connect with the fiber, a beam broadening area, and a waveguide array in which the lengths of the wavegu

Manash Kumar Kundu, Pritam Goswami, Satakshi Ghosh, Buddhadeb Sau

Arbitrary pattern formation ($\mathcal{APF}$) by mobile robots is studied by many in literature under different conditions and environment. Recently it has been studied on an infinite grid network but with full visibility. In opaque robot model, circle formation on infinite grid has also been studied. In this paper, we are solving $\mathcal{APF}$ on infinite

S. Giordanengo, M. Abujami, C. Galeone, S. Garbolino

A prototype of proton counter was developed by the University and the National Institute for Nuclear Physics of Torino to be used as online fluence beam monitor in particle therapy. The single particle identification approach aims at increasing the sensitivity and readout speed with respect to the state-of-the-art gas ionization chambers. The sensitive area

F. J. Domínguez-Gutíerrez, K. Mulewska, A. Ustrzycka, R. Alvarez-Donado

Austenitic stainless steels with low carbon have exceptional mechanical properties and are capable to reduce embrittlement, due to high chromium and nickel alloying, thus they are very attractive for efficient energy production in extreme environments. It is key to perform nanomechanical investigations of the role of chromium and the form of the particular a

Ke Yang, Wenjing Xu, Di Lu, Yuxuan Zhou

Hybrid transition metal oxides continue to attract attention due to their multiple degrees of freedom ($e.g.$, lattice, charge, spin, and orbital) and versatile properties. Here we investigate the magnetic and electronic properties of the newly synthesized double perovskite Ba$_2$NiIrO$_6$, using crystal field theory, superexchange model analysis, density fu

Thomas Loruenser, Florian Wohner, Stephan Krenn

The assignment problem is an essential problem in many application fields and frequently used to optimize resource usage. The problem is well understood and various efficient algorithms exist to solve the problem. However, it was unclear what practical performance could be achieved for privacy preserving implementations based on multiparty computation (MPC)

Lei Lu, Li Feng, Weiqun Gan

Coronal mass ejections (CMEs) are large clouds of magnetized plasma ejected from the Sun, and are often associated with acceleration of electrons that can result in radio emission via various mechanisms. However, the underlying mechanism relating the CMEs and particle acceleration still remains a subject of heated debate. Here, we report multi-instrument rad

Rui Luo, George Hobbs, Suk Yee Yong, Andrew Zic

We describe a new software package for simulating channelised, high-time resolution data streams from radio telescopes. The software simulates data from the telescope and observing system taking into account the observation strategy, receiver system and digitisation. The signatures of pulsars, fast radio bursts and flare stars are modelled, including frequen

A. Azarevich, N. Bolotina, O. Khrykina, A. Bogach

The studies of high-quality single-domain crystals of YbB12 were carried out by the precise x-ray diffraction technique in combination with the low temperature polarized THz - infrared spectroscopy and accurate magnetotransport measurements. It has been shown for the first time that this archetypal strongly correlated system with a metal-insulator transition

Yiqi Gao, Xinglin Hou, Wei Suo, Mengyang Sun

Video captioning aims to understand the spatio-temporal semantic concept of the video and generate descriptive sentences. The de-facto approach to this task dictates a text generator to learn from \textit{offline-extracted} motion or appearance features from \textit{pre-trained} vision models. However, these methods may suffer from the so-called \textbf{\tex

Thibaud Ruelle, David Jaeger, Francesco Fogliano, Floris Braakman

We describe an apparatus for the implementation of hybrid optomechanical systems at 4 K. The platform is based on a high-finesse, micrometer-scale fiber Fabry-Perot cavity, which can be widely tuned using piezoelectric positioners. A mechanical resonator can be positioned within the cavity in the object-in-the-middle configuration by a second set of position

Pedro J. Chocano, Manuel A. Morón, Francisco R. Ruiz del Portal

We give a combinatorial description of shape theory using finite topological $T_0$-spaces (finite partially ordered sets). This description may lead to a sort of computational shape theory. Then we introduce the notion of core for inverse sequences of finite spaces and prove some properties.

V. G. Klochkova, A. S. Miroshnichenko, V. E. Panchuk, N. S. Tavolzhanskaya

The optical spectra of the B-supergiant LS III+52 24 (IRAS 22023+5249) obtained at the 6-meter telescope BTA with a resolution R$\ge$60000 in 2010-2021 revealed signs of wind variability and velocity stratification in the extended atmosphere. The H$α$ and H$β$ lines have a P Cyg type profile; their wind absorption changes position in the range from $-270$ to

Axel Wismüller, Ali Vosoughi, Adora DSouza, Anas Abidin

It is a challenging research endeavor to infer causal relationships in multivariate observational time-series. Such data may be represented by graphs, where nodes represent time-series, and edges directed causal influence scores between them. If the number of nodes exceeds the number of temporal observations, conventional methods, such as standard Granger ca

Dani Kiyasseh, Runzhuo Ma, Taseen F. Haque, Jessica Nguyen

Surgery is a high-stakes domain where surgeons must navigate critical anatomical structures and actively avoid potential complications while achieving the main task at hand. Such surgical activity has been shown to affect long-term patient outcomes. To better understand this relationship, whose mechanics remain unknown for the majority of surgical procedures