July 2023 arXiv papers — page 6

Tianshu Yu, Changqun Xia, Jia Li

Video portrait segmentation (VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale Multi-scene Video Portrait Segmentation dataset MVPS c

Francesco Camilli, Marc Mézard

Matrix factorization is an inference problem that has acquired importance due to its vast range of applications that go from dictionary learning to recommendation systems and machine learning with deep networks. The study of its fundamental statistical limits represents a true challenge, and despite a decade-long history of efforts in the community, there is

Eric A. Arsenault, Yiliu Li, Birui Yang, Xi Wang

Two-dimensional moiré materials have emerged as the most versatile platforms for realizing quantum phases of electrons. Here, we explore the stability origins of correlated states in WSe2/WS2 moiré superlattices. We find that ultrafast electronic excitation leads to melting of the Mott states on time scales five times longer than predictions from the charge

Suma Bhat, Canhui Chen, Zerui Cheng, Zhixuan Fang

Large AI models (e.g., Dall-E, GPT4) have electrified the scientific, technological and societal landscape through their superhuman capabilities. These services are offered largely in a traditional web2.0 format (e.g., OpenAI's GPT4 service). As more large AI models proliferate (personalizing and specializing to a variety of domains), there is a tremendous n

M. Nelissen, A. Natta, P. McGinnis, C. Pittman

Classical T Tauri stars (cTTs) accrete from their circumstellar disk. The material falls onto the stellar surface, producing an accretion shock, which generates veiling in a star's spectra. In addition, the shock causes a localized accretion spot at the level of the chromosphere. Our goal is to investigate the accretion, particularly the mass accretion rates

Laurent Orseau, Marcus Hutter

Golden-section search and bisection search are the two main principled algorithms for 1d minimization of quasiconvex (unimodal) functions. The first one only uses function queries, while the second one also uses gradient queries. Other algorithms exist under much stronger assumptions, such as Newton's method. However, to the best of our knowledge, there is n

Adi Szeskin, Roei Yehuda, Or Shmueli, Jaime Levy

Purpose: Disease progression of retinal atrophy associated with AMD requires the accurate quantification of the retinal atrophy changes on longitudinal OCT studies. It is based on finding, comparing, and delineating subtle atrophy changes on consecutive pairs (prior and current) of unregistered OCT scans. Methods: We present a fully automatic end-to-end pipe

Flavien Breuvart, Dylan McDermott, Tarmo Uustalu

We define a notion of grading of a monoid T in a monoidal category C, relative to a class of morphisms M (which provide a notion of M-subobject). We show that, under reasonable conditions (including that M forms a factorization system), there is a canonical grading of T. Our application is to graded monads and models of computational effects. We demonstrate

Trevor Dunlap, Yasemin Acar, Michel Cucker, William Enck

Recent years have shown increased cyber attacks targeting less secure elements in the software supply chain and causing fatal damage to businesses and organizations. Past well-known examples of software supply chain attacks are the SolarWinds or log4j incidents that have affected thousands of customers and businesses. The US government and industry are equal

A. I. Bogomazov, A. V. Tutukov

In this population synthesis work we study a variety of possible origin channels of supernovae type Ia (SNe Ia) Among them mergers of carbon-oxygen (CO) and oxygen-neon (ONe) white dwarfs (WDs) under the influence of gravitational waves are considered as the primary channel of SNe Ia formation. We estimated frequencies of mergers of WDs with different chemic

Ri Cheng, Xuhao Jiang, Ruian He, Shili Zhou

The video frame interpolation (VFI) model applies the convolution operation to all locations, leading to redundant computations in regions with easy motion. We can use dynamic spatial pruning method to skip redundant computation, but this method cannot properly identify easy regions in VFI tasks without supervision. In this paper, we develop an Uncertainty-G

Richard S. J. Tol

Stringent climate policy compatible with the targets of the 2015 Paris Agreement would pose a substantial fiscal challenge. Reducing carbon dioxide emissions by 95% or more by 2050 would raise 7% (1-17%) of GDP in carbon tax revenue, half of current, global tax revenue. Revenues are relatively larger in poorer regions. Subsidies for carbon dioxide sequestrat

Matthew Di Meglio

A comprehensive account of the categorical properties of the category of small categories and asymmetric delta lenses is given in the recent works of Chollet et al. and Di Meglio. An important construction for proving many of these properties is Johnson and Rosebrugh's "pullback" of lenses, which we call the proxy pullback of lenses. We give a new treatment

Ezra Schoen

Liftings of endofunctors on sets to endofunctors on relations are commonly used to capture bisimulation of coalgebras. Lax versions have been used in those cases where strict lifting fails to capture bisimilarity, as well as in modeling other notions of simulation. This paper provides tools for defining and manipulating lax liftings. As a central result, we

Masahito Kubo, Yukio Katsukawa, David Hernández Expósito, Antonio Sánchez Gómez

The Sunrise Chromospheric Infrared spectroPolarimeter (SCIP) has been developed for the third flight of the SUNRISE balloon-borne stratospheric solar observatory. The aim of SCIP is to reveal the evolution of three-dimensional magnetic fields in the solar photosphere and chromosphere using spectropolarimetric measurements with a polarimetric precision of 0.0

Gilles Monnoyer, Thomas Feuillen, Maxime Drouguet, Laurent Jacques

This paper presents a novel signal processing technique, coined grid hopping, as well as an active multistatic Frequency-Modulated Continuous Wave (FMCW) radar system designed to evaluate its performance. The design of grid hopping is motivated by two existing estimation algorithms. The first one is the indirect algorithm estimating ranges and speeds separat

Hyung-Seok Oh, Sang-Hoon Lee, Seong-Whan Lee

Expressive text-to-speech systems have undergone significant advancements owing to prosody modeling, but conventional methods can still be improved. Traditional approaches have relied on the autoregressive method to predict the quantized prosody vector; however, it suffers from the issues of long-term dependency and slow inference. This study proposes a nove

Atiyah Elsheikh

This documentation specifies a simplified non-calibrated demographic agent-based model of the UK, a largely simplified version of the Lone Parent Model presented in [Gostolil and Silverman 2020]. In the presented model, individuals of an initial population are subject to ageing, deaths, births, divorces and marriages throughout a simplified map of towns of t

Xin-Ying Song

The recent extremely bright gamma-ray burst (GRB), GRB 230307A from a binary neutron star merger may offer a good probe for the production of GRB-neutrinos. Within the constraint from IceCube neutrino non-detection, the limits for key physical parameters of this burst are extracted in different scenarios including the fireball, Poynting-flux-dominated (PFD)

Johannes Siegele, Martin Pfurner

In this article, we will construct an overconstrained closed-loop linkage consisting of four revolute and one cylindrical joint. It is obtained by factorization of a prescribed vertical Darboux motion. We will investigate the kinematic behaviour of the obtained mechanism, which turns out to have multiple operation modes. Under certain conditions on the desig

Ke Sun, Shen Chen, Taiping Yao, Haozhe Yang

Deepfakes are realistic face manipulations that can pose serious threats to security, privacy, and trust. Existing methods mostly treat this task as binary classification, which uses digital labels or mask signals to train the detection model. We argue that such supervisions lack semantic information and interpretability. To address this issues, in this pape

Rasheed Mohammad, Oliver Favell, Shariq Shah, Emmett Cooper

Businesses have sought out new solutions to provide support and improve customer satisfaction as more products and services have become interconnected digitally. There is an inherent need for businesses to provide or outsource fast, efficient and knowledgeable support to remain competitive. Support solutions are also advancing with technologies, including us

Walter Morales-Alvarez, Novel Certad, Alina Roitberg, Rainer Stiefelhagen

For driver observation frameworks, clean datasets collected in controlled simulated environments often serve as the initial training ground. Yet, when deployed under real driving conditions, such simulator-trained models quickly face the problem of distributional shifts brought about by changing illumination, car model, variations in subject appearances, sen

GERDA collaboration, M. Agostini, A. Alexander, G. Araujo

We search for tri-nucleon decays of $^{76}$Ge in the dataset from the GERmanium Detector Array (GERDA) experiment. Decays that populate excited levels of the daughter nucleus above the threshold for particle emission lead to disintegration and are not considered. The ppp-, ppn-, and pnn-decays lead to $^{73}$Cu, $^{73}$Zn, and $^{73}$Ga nuclei, respectively.

Franz Deimling, Michela Fazzolari

The recent spread of cloud services has enabled many companies to take advantage of them. Nevertheless, the main concern about the adoption of cloud services remains the lack of transparency perceived by customers regarding security and privacy. To overcome this issue, Cloud Service Certifications (CSCs) have emerged as an effective solution to increase the

Junxiong Wang, Immanuel Trummer, Ahmet Kara, Dan Olteanu

The performance of worst-case optimal join algorithms depends on the order in which the join attributes are processed. Selecting good orders before query execution is hard, due to the large space of possible orders and unreliable execution cost estimates in case of data skew or data correlation. We propose ADOPT, a query engine that combines adaptive query p

Pavel S. Gevorgyan

In this paper, continuous binary operations of a topological space are studied and a criterion of their invertibility is proved. The classification problem of groups of invertible continuous binary operations of locally compact and locally connected spaces is solved. A theorem on the binary distributive representation of a topological group is also proved.

N. A. Bogoslovskiy, P. V. Petrov, N. S. Averkiev

We study the theoretical model of a ferromagnetic semiconductor as a system of randomly distributed Ising spins with a long-range exchange interaction. Using the density-of-states approach, we analytically obtain the magnetic susceptibility and heat capacity over a wide range of temperatures and magnetic fields. It is shown that the finite system of spins in

Óscar Martín, Alberto Verdejo, Narciso Martí-Oliet

In previous work, summarized in this paper, we proposed an operation of parallel composition for rewriting-logic theories, allowing compositional specification of systems and reusability of components. The present paper focuses on compositional verification. We show how the assume/guarantee technique can be transposed to our setting, by giving appropriate de

Nouman Khan, Vijay Subramanian

We study the problem of decentralized constrained POMDPs in a team-setting where the multiple non-strategic agents have asymmetric information. Strong duality is established for the setting of infinite-horizon expected total discounted costs when the observations lie in a countable space, the actions are chosen from a finite space, and the immediate cost fun

Ryan Shah, Manuel Maarek, Shenando Stals, Lynne Baillie

Cybersecurity is an important topic which is often viewed as one that is inaccessible due to steep learning curves and a perceived requirement of needing specialist knowledge. With a constantly changing threat landscape, practical solutions such as best-practices are employed, but the number of critical cybersecurity-related incidents remains high. To addres

Kamal Hajian

The geometries with SL$(2,\mathbb{R})$ and some axial U$(1)$ isometries are called ``near-horizon extremal geometries" and are found usually, but not necessarily, in the near-horizon limit of the extremal black holes. We present a new member of this family of solutions in five-dimensional Einstein-Hilbert gravity that has only one nonzero angular momentum. I

Bernard Ousmane Sane, Rodney Van Meter, Michal Hajdušek

Recent work has identified cosmic ray events as an error source limiting the lifetime of quantum data. These errors are correlated and affect a large number of qubits, leading to the loss of data across a quantum chip. Previous works attempting to address the problem in hardware or by building distributed systems still have limitations. We approach the probl

Yang Liu, Feng Wang, Naiyan Wang, Zhaoxiang Zhang

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability to bad weather. Nevertheless, the radar detection performance is usually inferior because its point cloud is sparse and not accurate due to the poor azimuth and elevation resolution. Moreover, point cloud generation algorithms already drop weak signals to reduce the f

Toby Peterken

In this work, we attempt to define a notion of compositeness compatible with Quantum Field Theory. Considering the analytic properties of the S-matrix, we conclude that there is no satisfactory definition of compositeness compatible with Quantum Field Theory. Without this notion, one must claim that all bound states are equally fundamental, that is, one cann

Novel Certad, Sebastian Tschernuth, Cristina Olaverri-Monreal

In this work, we utilized the methodology outlined in the IEEE Standard 2846-2022 for "Assumptions in Safety-Related Models for Automated Driving Systems" to extract information on the behavior of other road users in driving scenarios. This method includes defining high-level scenarios, determining kinematic characteristics, evaluating safety relevance, and

Meng Lian, Yin-Jie Chen, Yue Geng, Yun-Tian Chen

In isolated nonlinear optical waveguide arrays with bounded energy spectrum, simultaneous conservation of energy and power of the optical modes enables study of coupled thermal and particle transport in the negative temperature regime. Here, based on exact numerical simulation and rationale from Landauer formalism, we predict generic violation of the Wiedema

Mona Ashtari-Majlan, Mohammad Mahdi Dehshibi, David Masip

Glaucoma is the leading cause of irreversible blindness worldwide and poses significant diagnostic challenges due to its reliance on subjective evaluation. However, recent advances in computer vision and deep learning have demonstrated the potential for automated assessment. In this paper, we survey recent studies on AI-based glaucoma diagnosis using fundus,

Scipio Cuccagna, Masaya Maeda, Federico Murgante, Stefano Scrobogna

We extend the result M. Kowalczyk, Y. Martel, C. Mu\~noz, JEMS 2022, on the existence, in the context of spatially even solutions, of asymptotic stability on a center hypersurface at the soliton of the defocusing power Nonlinear Klein Gordon Equation with $p>3$, to the case $2\ge p> \frac{5}{3}$.

Charles Jones, Daniel C. Castro, Fabio De Sousa Ribeiro, Ozan Oktay

As machine learning methods gain prominence within clinical decision-making, addressing fairness concerns becomes increasingly urgent. Despite considerable work dedicated to detecting and ameliorating algorithmic bias, today's methods are deficient with potentially harmful consequences. Our causal perspective sheds new light on algorithmic bias, highlighting

Junjie Fei, Teng Wang, Jinrui Zhang, Zhenyu He

Image-to-text generation aims to describe images using natural language. Recently, zero-shot image captioning based on pre-trained vision-language models (VLMs) and large language models (LLMs) has made significant progress. However, we have observed and empirically demonstrated that these methods are susceptible to modality bias induced by LLMs and tend to

Pedro Rosario, Andrés F. Ducuara, Cristian E. Susa

We address the swapping of various quantum correlation measures including: Bell-nonlocality, EPR-steering, usefulness for teleportation, entanglement, quantum obesity, as well as the effect that local filtering operations have on the swapping of such correlations. In the first part of this work we address the raw swapping protocol (i. e. without local filter

Qibin Chen, Yaonan Zhu, Kay Hansel, Tadayoshi Aoyama

With the continuous advancement of robot teleoperation technology, shared control is used to reduce the physical and mental load of the operator in teleoperation system. This paper proposes an alternating shared control framework for object grasping that considers both operator's preferences through their manual manipulation and the constraints of the follow

Stefano Crespi Reghizzi, Antonio Restivo, Pierluigi San Pietro

We propose different ways of lifting the notion of Dyck language from words to 2-dimensional (2D) pictures, by means of new definitions of increasing comprehensiveness. Two of the proposals are based on alternative definitions of a Dyck language, which are equivalent over words but not on pictures. First, the property that any two pairs of matching parenthes

Alexandre T. R. Guibert, Murtaza Bookwala, Ashley Cronk, Y. Shirley Meng

A persistent challenge with the development of electric vertical take-off and landing vehicles (eVTOL) to meet flight power and energy demands is the mass of the load and thermal management systems for batteries. One possible strategy to overcome this problem is to employ optimization techniques to obtain a lightweight battery pack while satisfying structura

Partha Mukhopadhyay

We study lattice wouldsheet theory with continuous time describing free motion of a system of bound string bits. We use a non-local lattice derivative that allows us to preserve all the symmetries of the continuum including the worldsheet local symmetries. There exists a ``local correspondence'' between the continuum and lattice theories in the sense that ev

Felix Fießinger, Mitja Stadje

This paper proves an extension of the It\^o-Ventzell formula that applies to stochastic flows in $C^{0,1}$ for continuous weak Dirichlet processes. We apply this theorem, for example, to give a representation result for strong solutions of time-dependent elliptic SPDEs, to derive formulas for quadratic variations, and to relax assumptions in a financial math

Mingyao Cui, Hao Jiang, Yuhao Chen, Yang Du

Channel prediction is critical to address the channel aging issue in mobile scenarios. Existing channel prediction techniques are mainly designed for discrete channel prediction, which can only predict the future channel in a fixed time slot per frame, while the other intra-frame channels are usually recovered by interpolation. However, these approaches suff

Yuntao Liu, Qian Huang, Rongpeng Li, Xianfu Chen

Collaborative perception by leveraging the shared semantic information plays a crucial role in overcoming the individual limitations of isolated agents. However, existing collaborative perception methods tend to focus solely on the spatial features of semantic information, while neglecting the importance of the temporal dimension. Consequently, the potential

Changsheng Quan, Xiaofei Li

This work proposes a neural network to extensively exploit spatial information for multichannel joint speech separation, denoising and dereverberation, named SpatialNet. In the short-time Fourier transform (STFT) domain, the proposed network performs end-to-end speech enhancement. It is mainly composed of interleaved narrow-band and cross-band blocks to resp

Julie Munch Torndal, Jenny List

The Higgs sector of particle physics is still largely uncovered, where establishing the Higgs mechanism is central to advance the field. The Higgs self-coupling is the key ingredient missing and an important puzzle piece for potentially uncovering new physics beyond the standard model. With the energy reach and precision reach of linear $e^+e^-$ colliders, t

N. Vukašinović, I. Božović-Jelisavčić, G. Kačarević

Although the studies of tensor structure of the Higgs boson interactions with vector bosons and fermions at CMS and ATLAS experiments have established that the $J^{\mathrm{PC}}$ quantum numbers of the Higgs boson should be $0^{++}$, small CP violation in the Higgs sector (up to 10% contribution of the CP-odd state) cannot be excluded with the current experim

Tomáš Peltan, Eva Vilímová, Tomáš Czakoj, Zdeněk Matěj

Graphite is important reactor material used as a neutron moderator in various reactor designs. It is not only structural material used in previous reactors design but even material to which attention is focused due to the very high-temperature reactor design, which uses graphite as moderator and reflector. Due to the well-characterised cross-section of graph

Thilo Hagendorff

Large language models (LLMs) are currently at the forefront of intertwining artificial intelligence (AI) systems with human communication and everyday life. Thus, aligning them with human values is of great importance. However, given the steady increase in reasoning abilities, future LLMs are under suspicion of becoming able to deceive human operators and ut

Giorgio Domenichini, Christoph Dellago

In this article we present a machine learning model to obtain fast and accurate estimates of the molecular Hessian matrix. In this model, based on a random forest, the second derivatives of the energy with respect to redundant internal coordinates are learned individually. The internal coordinates together with their specific representation guarantee rotatio

Ivania Donoso-Guzmán, Jeroen Ooge, Denis Parra, Katrien Verbert

While research on explainable AI (XAI) is booming and explanation techniques have proven promising in many application domains, standardised human-centred evaluation procedures are still missing. In addition, current evaluation procedures do not assess XAI methods holistically in the sense that they do not treat explanations' effects on humans as a complex u

Matthias Aßenmacher, Nadja Sauter, Christian Heumann

Annotating costs of large corpora are still one of the main bottlenecks in empirical social science research. On the one hand, making use of the capabilities of domain transfer allows re-using annotated data sets and trained models. On the other hand, it is not clear how well domain transfer works and how reliable the results are for transfer across differen

Ole Steuernagel, Ray-Kuang Lee

For a simple quantum system weakly interacting with the environment Wigner's 1932 formulation of quantum physics can be used to derive coupling to the environment using simple algebra. We show that the correct expressions, using coupling terms of `Lindblad form', are forced upon us. This is remarkable given that it took several decades before Lindblad's resu

Zhelun Shen, Xibin Song, Yuchao Dai, Dingfu Zhou

Due to the domain differences and unbalanced disparity distribution across multiple datasets, current stereo matching approaches are commonly limited to a specific dataset and generalize poorly to others. Such domain shift issue is usually addressed by substantial adaptation on costly target-domain ground-truth data, which cannot be easily obtained in practi

Feng Zhang, Bin Xu, Zhiqiang Li, Xinran Liu

Modeling and synthesizing low-light raw noise is a fundamental problem for computational photography and image processing applications. Although most recent works have adopted physics-based models to synthesize noise, the signal-independent noise in low-light conditions is far more complicated and varies dramatically across camera sensors, which is beyond th

Xiaoli Hu, Naihuan Jing

Skew information is a pivotal concept in quantum information, quantum measurement, and quantum metrology. Further studies have lead to the uncertainty relations grounded in metric-adjusted skew information. In this work, we present an in-depth investigation using the methodologies of sampling coordinates of observables and convex functions to refine the unce

Alexander Bogatskiy, Timothy Hoffman, David W. Miller, Jan T. Offermann

PELICAN is a novel permutation equivariant and Lorentz invariant or covariant aggregator network designed to overcome common limitations found in architectures applied to particle physics problems. Compared to many approaches that use non-specialized architectures that neglect underlying physics principles and require very large numbers of parameters, PELICA

Kyoung-Min Kim, Gyungchoon Go, Moon Jip Park, Se Kwon Kim

The investigation of twist engineering in easy-axis magnetic systems has revealed the remarkable potential for generating topological spin textures, such as magnetic skyrmions. Here, by implementing twist engineering in easy-plane magnets, we introduce a novel approach to achieve fractional topological spin textures such as merons. Through atomistic spin sim

Adrian Pacheco-Pozo, Igor M. Sokolov

In recent years, several experiments highlighted a new type of diffusion anomaly, which was called Brownian yet non-Gaussian diffusion. In systems displaying this behavior, the mean squared displacement of the diffusing particles grows linearly in time, like in a normal diffusion, but the distribution of displacements is non-Gaussian. In situations when the

Tao Huang, Kai Chen, Wang Wei, Jianan Li

Reinforcement learning is still struggling with solving long-horizon surgical robot tasks which involve multiple steps over an extended duration of time due to the policy exploration challenge. Recent methods try to tackle this problem by skill chaining, in which the long-horizon task is decomposed into multiple subtasks for easing the exploration burden and

Marianna Bolla, Hannu Reittu, Runtian Zhou

In this survey paper it is illustrated how spectral clustering methods for unweighted graphs are adapted to the dense and sparse regimes. Whereas Laplacian and modularity based spectral clustering is apt to dense graphs, recent results show that for sparse ones, the non-backtracking spectrum is the best candidate to find assortative clusters of nodes. Here b

Raheleh Jafari, Ignacio Ojeda

We recall and delve into the different characterizations of the depth of an affine semigroup ring, providing an original characterization of depth two in three and four dimensional cases which are closely related to the existence of a maximal element in certain Apery sets.

Paul Gallot, Sebastian Maneth, Keisuke Nakano, Charles Peyrat

We present a novel normal form for (total deterministic) macro tree transducers (mtts), called depth proper normal form. If an mtt is in this normal form, then it is guaranteed that each parameter of each state of the mtt appears at arbitrary depth in the output trees of that state. Intuitively, if some parameter only appears at certain bounded depths in the

Malte Mosbach, Sven Behnke

Tool use, a hallmark feature of human intelligence, remains a challenging problem in robotics due the complex contacts and high-dimensional action space. In this work, we present a novel method to enable reinforcement learning of tool use behaviors. Our approach provides a scalable way to learn the operation of tools in a new category using only a single dem

Giorgi Khomeriki, Lado Samushia

We derive general expressions for how the Alcock-Paczynski distortions affect the power spectrum and the bispectrum of cosmological fields. We compute explicit formulas for the mixing coefficients of bispectrum multipoles in the linear approximation. The leading-order effect for the bispectrum is the uniform dilation of all three wavevectors. The mixing coef

Hao Liu, Shingyu Leung, Jianliang Qian

The classical Minkowski problem for convex bodies has deeply influenced the development of differential geometry. During the past several decades, abundant mathematical theories have been developed for studying the solutions of the Minkowski problem, however, the numerical solution of this problem has been largely left behind, with only few methods available

Jia-shun Yan, Jun Jing

It is not a general opinion that that a quantum system could be purified into a target eigenstate via repeated measurements on a coupled qubit rather than direct transitions in the Hamiltonian. The projective measurement on the ancillary qubit gives rise to the positive operator-valued measures on the system that can filter out the unwanted states except the

Lihong Ao, Aymeric Ramiere

Cooling high-power electronics in multilayer integrated circuits (ICs) is challenging for existing cooling methods. In this work, we designed through-chip microchannels (TCMCs) that cross the entire chip perpendicularly to the layers, with water circulating inside to provide direct cooling to each layer. TCMCs are organized in a square array where the pitch

Thales Coelho Leite Fava, Dan Henningson, Ardeshir Hanifi

Laminar-turbulent transition on a rotating wind turbine blade at a chord Reynolds number of $1 \times 10^5$ and varying angles of attack ($AoA$) is studied with direct numerical simulations and linear stability theory. The rotation effects depend on the streamwise pressure gradient and direct/reverse flow state. In the $AoA=12.8^\circ$ case, rotation retards

Nazmiye Alemdar, Hasan Arslan

The main purpose of this paper is to introduce the structure of soft group category. In this category, we determine some special objects and morphisms having a universal structure such as the final object and product. Therefore, the category of soft groups is a symmetric monodial category.

Ali El Boutaybi, Thomas Maroutian, Ludovic Largeau, Nathaniel Findling

We report on the crystal structure and ferroelectric properties of epitaxial ZrO$_2$ films ranging from 7 to 42 nm thickness grown on La$_{0.67}$Sr$_{0.33}$MnO$_3$-buffered (110)-oriented SrTiO$_3$ substrate. By employing X-ray diffraction, we confirm a tetragonal phase at all investigated thicknesses, with slight in-plane strain due to the substrate in the

Kotaro Hisa, Mizuki Kojima

We are concerned with the following time-fractional semilinear heat equation in the $N$-dimensional whole space ${\bf R}^N$ with $N \geq 1$. \[ {\rm (P)}_\alpha \qquad \partial_t^\alpha u -\Delta u = u^p,\quad t>0,\,\,\, x\in{\bf R}^N, \qquad u(0) = \mu \quad \mbox{in}\quad {\bf R}^N, \] where $\partial_t^\alpha$ denotes the Caputo derivative of order $\alph

Kamran Shafafi, André Coelho, Rui Campos, Manuel Ricardo

Unmanned Aerial Vehicles (UAVs) are increasingly used as cost-effective and flexible Wi-Fi Access Points (APs) and cellular Base Stations (BSs) to enhance Quality of Service (QoS). In disaster management scenarios, UAV-based networks provide on-demand wireless connectivity when traditional infrastructures fail. In obstacle-rich environments like urban areas,

Jordan Vice, Naveed Akhtar, Richard Hartley, Ajmal Mian

The rise in popularity of text-to-image generative artificial intelligence (AI) has attracted widespread public interest. We demonstrate that this technology can be attacked to generate content that subtly manipulates its users. We propose a Backdoor Attack on text-to-image Generative Models (BAGM), which upon triggering, infuses the generated images with ma

Philipp Schillinger, Miroslav Gabriel, Alexander Kuss, Hanna Ziesche

This paper presents a novel method for model-free prediction of grasp poses for suction grippers with multiple suction cups. Our approach is agnostic to the design of the gripper and does not require gripper-specific training data. In particular, we propose a two-step approach, where first, a neural network predicts pixel-wise grasp quality for an input imag

Xinchao Cui, Feidi Xiang, Chong Lu, Chunping Liu

Magnetic nanoparticle (MNP) has attracted interest in various research fields due to its special superparamagnetic and strong magneto-optical effects, especially as contrast agents to enhance the contrast of medical imaging. By introducing the interaction coefficient, we propose a model of the nonlinear Faraday rotation of MNP under the excitation of an exte

Tuomas Lappi, Anh Dung Le, Heikki Mäntysaari

We use the Kovchegov-Levin equation to resum contributions of large invariant mass diffractive final states to diffractive structure functions in the dipole picture of deep inelastic scattering. For protons we use a (modified) McLerran-Venugopalan model as the initial condition for the evolution, with free parameters obtained from fits to the HERA inclusive

Yuga Iguchi, Alexandros Beskos, Matthew Graham

We study parametric inference for ergodic diffusion processes with a degenerate diffusion matrix. Existing research focuses on a particular class of hypo-elliptic SDEs, with components split into `rough'/`smooth' and noise from rough components propagating directly onto smooth ones, but some critical model classes arising in applications have yet to be explo

Mohammad N. Ivaki, Emanuel Milman

Let $K$ be a smooth, origin-symmetric, strictly convex body in $\mathbb{R}^n$. If for some $\ell\in GL(n,\mathbb{R})$, the anisotropic Riemannian metric $\frac{1}{2}D^2 \Vert\cdot\Vert_{\ell K}^2$, encapsulating the curvature of $\ell K$, is comparable to the standard Euclidean metric of $\mathbb{R}^{n}$ up-to a factor of $\gamma > 1$, we show that $K$ satis

Hervé Le Dret, Annie Raoult

We show that the Oldroyd B fluid model is the Eulerian form of a Lagrangian model with an internal variable that satisfies the second law of thermodynamics under some conditions on the initial value of the internal variable. We similarly derive several new nonlinear versions of the Oldroyd B model as well as Lagrangian formulations of the Zaremba-Jaumann and

Akio Kawauchi

It is shown that if a link in 3-space bounds a proper oriented surface (without closed component) in the upper half 4-space, then the link bounds a proper oriented ribbon surface in the upper half 4-space which is a renewal embedding of the original surface. In particular, every slice knot is a ribbon knot, answering an old question by R. H. Fox affirmativel

Xavier Sido

The aim of this chapter is to identify and characterise the pedagogical model prescribed for this particular mathematics teaching delivered in post-primary vocational training. More specifically, the contribution investigates two major questions: what specificities, proximities, differences with the pedagogical models of mathematics teaching for elementary p

Sebastian Meier, Katrin Glinka

Taxonomy building is a task that requires interpreting and classifying data within a given frame of reference, which comes to play in many areas of application that deal with knowledge and information organization. In this paper, we explore how taxonomy building can be supported with systems that integrate machine learning (ML). However, relying only on blac

Satsuki Oda, Nobuchika Okada, Nathan Papapietro, Dai-suke Takahashi

We propose a minimal gauged U(1)$_X$ extension of the MSSM with R-parity conservation. In this model, U(1)$_X$ is a generalization of the well-known U(1) $B-L$. Apart from the MSSM particle content, the model includes three right-handed neutrino (RHN) chiral superfields, each carrying a unit U(1)$_X$ charge. In the presence of RHNs, the model is free from al

Paweena Suebsombut, Aicha Sekhari, Pradorn Sureepong, Pittawat Ueasangkomsate

Climate change has affected the cultivation in all countries with extreme drought, flooding, higher temperature, and changes in the season thus leaving behind the uncontrolled production. Consequently, the smart farm has become part of the crucial trend that is needed for application in certain farm areas. The aims of smart farm are to control and to enhance

Quentin Marolleau, Charlie Leprince, Victor Gondret, Denis Boiron

We study the feasibility of sub-shot-noise interferometry with imperfect detectors, starting from twin-Fock states and two mode squeezed vacuum states. We derive analytical expressions for the corresponding phase uncertainty. We find that one can achieve phase shift measurements below the standard quantum limit, as long as the losses are smaller than a given

Costas A. Kokke, Mario Coutiño, Laura Anitori, Richard Heusdens

Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cram\'er-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. We propose to tackle the sens

Pierre Larrenie, Cédric Buron, Frédéric Barbaresco

Coordination of radars can be performed in various ways. To be more resilient radar networks can be coordinated in a decentralized way. In this paper, we introduce a highly resilient algorithm for radar coordination based on decentralized and collaborative bundle auctions. We first formalize our problem as a constrained optimization problem and apply a marke

Jarosław Rybusiński, Tomasz Fąs, Pablo Martin-Ramos, Victor Lavín

We demonstrate the selective control of the magnetic response and photoluminescence properties of Er3+ centers with light, by associating them with a highly conjugated beta-diketonate (1,3-di(2-naphthyl)-1,3-propanedione) ligand. We demonstrate this system to be an optically-pumped molecular compound emittingin infra-red, which can be employed as a precise h

Philippe Gille, Ting-Yu Lee

We provide a characterization of homogeneous spaces under a reductive group scheme such that the geometric stabilizers are maximal tori. The quasi-split case over a semilocal base is of special interest and permits to answer a question raised by Marc Levine on homogeneous SL$_n$-spaces. At the end, we provide an application to the local-global principles for

Stefano Berrone, Stefano Scialò, Gioana Teora

In this paper, we discuss the accuracy and the robustness of the mixed Virtual Element Methods when dealing with highly-anisotropic diffusion problems. In particular, we analyze the performances of different approaches which are characterized by different sets of both boundary and internal degrees of freedom in presence of a strong anisotropy of the diffusio

Makoto Ohsaki, Saku Aoyagi, Kazuki Hayashi

A multiobjective optimization method is proposed for obtaining the optimal plane trusses simultaneously for various aspect ratios of the initial ground structure as a set of Pareto optimal solutions generated through a single optimization process. The shape and topology are optimized simultaneously to minimize the compliance under constraint on the total str

Xi-Han Zhou, Tao Yu

We predict that ferromagnetic resonance in insulating magnetic film with inplane magnetization radiates electric fields polarized along the magnetization with opposite amplitudes at two sides of the magnetic insulator, which can be modulated strongly by adjacent superconductors. With a single superconductor adjacent to the magnetic insulator this radiated el

Nicola Picenni

We consider a class of non-local functionals recently introduced by H. Brezis, A. Seeger, J. Van Schaftingen, and P.-L. Yung, which offers a novel way to characterize functions with bounded variation. We give a positive answer to an open question related to these functionals in the case of functions with bounded variation. Specifically, we prove that in this

Yu-Cheng Qiu, Jin-Wei Wang, Tsutomu T. Yanagida

The seesaw mechanism is the most attractive mechanism to explain the small neutrino masses, which predicts the neutrinoless double beta decay ($0\nu\beta\beta$) of the nucleus. Thus the discovery of $0\nu\beta\beta$ is extremely important for future particle physics. However, the present data on the neutrino oscillation is not sufficient to predict the value