July 2023 arXiv papers — page 150

Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li

Image super-resolution (SR) with generative adversarial networks (GAN) has achieved great success in restoring realistic details. However, it is notorious that GAN-based SR models will inevitably produce unpleasant and undesirable artifacts, especially in practical scenarios. Previous works typically suppress artifacts with an extra loss penalty in the train

Qingyuan Jiang

This paper establishes semiorthogonal decompositions for derived Grassmannians of perfect complexes with Tor-amplitude in $[0,1]$. This result verifies the author's Quot formula conjecture [J21a] and generalizes and strengthens Toda's result in [Tod23]. We give applications of this result to various classical situations such as blowups of determinant

Carsten Hartmann, Lorenz Richter

The recent advances in machine learning in various fields of applications can be largely attributed to the rise of deep learning (DL) methods and architectures. Despite being a key technology behind autonomous cars, image processing, speech recognition, etc., a notorious problem remains the lack of theoretical understanding of DL and related interpretability

Sergei Stishov

The thermodynamic properties of the Boltzmann hard sphere system is discussed. It was found that zero point energy decreases with temperature so slowly that it turned out to be an almost a constant addition to the classical value. In result the heat capacity of the system differs little from the classical value of 1.5 k everywhere except for the narrow regio

John A. Snoap, Dimitrie C. Popescu, Chad M. Spooner

The paper considers the problem of deep-learning-based classification of digitally modulated signals using I/Q data and studies the generalization ability of a trained neural network (NN) to correctly classify digitally modulated signals it has been trained to recognize when the training and testing datasets are distinct. Specifically, we consider both a res

Alifia Puspaningrum, Muhammad Anis Al Hilmi, Darsih, Muhamad Mustamiin

In Software Development Life Cycle (SDLC), security vulnerabilities are one of the points introduced during the construction stage. Failure to detect software defects earlier after releasing the product to the market causes higher repair costs for the company. So, it decreases the company's reputation, violates user privacy, and causes an unrepairable is

Dennis Tilipman, Maria Kazachenko, Benoit Tremblay, Ivan Milic

Poynting flux is the flux of magnetic energy, which is responsible for chromospheric and coronal heating in the solar atmosphere. It is defined as a cross product of electric and magnetic fields, and in ideal MHD conditions it can be expressed in terms of magnetic field and plasma velocity. Poynting flux has been computed for active regions and plages, but e

Max Hort, Anastasiia Grishina, Leon Moonen

Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair. Large amounts of data for training such models benefit the models' performance. However, the size of the data and models results in long training times and high energy consumption. While publishing source code

Deepak Raina, SH Chandrashekhara, Richard Voyles, Juan Wachs

Ultrasound is a vital imaging modality utilized for a variety of diagnostic and interventional procedures. However, an expert sonographer is required to make accurate maneuvers of the probe over the human body while making sense of the ultrasound images for diagnostic purposes. This procedure requires a substantial amount of training and up to a few years of

M. K. Keshari, Soumi Tikader

Let $A$ be a regular ring of dimension $d$ essentially of finite type over an infinite field $k$ of characteristic $\neq 2$. Let $P$ be a projective $A$-module of rank $n$ with $2n\geq d+3$. Let $I$ be an ideal of $A[T]$ of height $n$ and $ϕ:P[T]\twoheadrightarrow I/I^2$ be a surjection. If $ϕ\otimes A(T)$ has a surjective lift $θ:P[T]\otimes A(T)\twoheadrig

Kuni H Iwasa

Avian prestin is sensitive to membrane thickness as much as mammalian prestin, which undergoes conformational transitions in membrane area and thereby drives length changes of the cylindrical cell body of outer hair cells. The membrane thickness dependence of mammalian prestin stems from changes in hydrophobic profile in conformational states, accompanied by

Zonglin Li, Nadav Yesha

For a real-valued sequence $(x_n)_{n=1}^\infty$, denote by $S_N(\ell)$ the number of its first $N$ fractional parts lying in a random interval of size $\ell:=L/N$, where $L=o(N)$ as $N\to\infty$. We study the variance of $S_N(\ell)$ (the number variance) for sequences of the form $x_n=αa_n$, where $(a_n)_{n=1}^\infty$ is a sequence of distinct integers. We s

Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li

Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training large-scale language models is computationally expensive. Therefore, Continual Learning (CL) is an important aspect that remains underexplored in the code domain. In this paper, we int

Johannes Wirtz, Stéphane Guindon

The introduction of the spatial Lambda-Fleming-Viot model (LV) in population genetics was mainly driven by the pioneering work of Alison Etheridge, in collaboration with Nick Barton and Amandine Véber about ten years ago (1,2). The LV model provides a sound mathematical framework for describing the evolution of a population of related individuals along a spa

Yalda Foroutan, Alon Harell, Anderson de Andrade, Ivan V. Bajić

A basic premise in scalable human-machine coding is that the base layer is intended for automated machine analysis and is therefore more compressible than the same content would be for human viewing. Use cases for such coding include video surveillance and traffic monitoring, where the majority of the content will never be seen by humans. Therefore, base lay

Md Washik Al Azad, Hasniuj Zahan, Sifat Ut Taki, Spyridon Mastorakis

Tor is the most popular anonymous communication overlay network which hides clients' identities from servers by passing packets through multiple relays. To provide anonymity to both clients and servers, Tor onion services were introduced by increasing the number of relays between a client and a server. Because of the limited bandwidth of Tor relays, larg

Oana Vesa, Jason Jackiewicz, Kevin Reardon

Atmospheric gravity waves (AGWs) are low-frequency, buoyancy-driven waves that are generated by turbulent convection and propagate obliquely throughout the solar atmosphere. Their proposed energy contribution to the lower solar atmosphere and sensitivity to atmospheric parameters (e.g. magnetic fields and radiative damping) highlight their diagnostic potenti

Stephan Sinzig, Christoph P. Schmidt, Wolfgang A. Wall

A novel approach is presented to efficiently include transport effects in thin active material coating layers of all-solid-state batteries using a dimensionally reduced formulation embedded into a three-dimensionally resolved coupled electrochemo-mechanical continuum model. In the literature, the effect of coating layers is so far captured by additional zero

Karthik Adimurthi, Wontae Kim

In this paper, we study some regularity issues concerning the gradient of weak solutions of $u_t - {\rm div} \mathcal{A}(x,t,\nabla u) = g$, where $\mathcal{A}(x,t,\nabla u)$ is modeled after the $p$-Laplace operator. The main results we are interested in is to obtain optimal conditions on the datum $g$ (independent of time) such that borderline higher integ

Yeqi Gao, Zhao Song, Shenghao Xie

Large language models (LLMs) have brought significant and transformative changes in human society. These models have demonstrated remarkable capabilities in natural language understanding and generation, leading to various advancements and impacts across several domains. We consider the in-context learning under two formulation for attention related regressi

Xin Sheng, Lizhong Zhang, Omer Blaes, Yan-Fei Jiang

We present relativistic, radiation magnetohydrodynamic simulations of supercritical neutron star accretion columns in Cartesian geometry, including temperature-dependent, polarization-averaged Rosseland mean opacities accounting for classical electron scattering in a magnetic field. Just as in our previous pure Thomson scattering simulations, vertical oscill

Enrique Saurez, Harshit Gupta, Henriette Roger, Sukanya Bhowmik

Real-time video analytics typically require video frames to be processed by a query to identify objects or activities of interest while adhering to an end-to-end frame processing latency constraint. Such applications impose a continuous and heavy load on backend compute and network infrastructure because of the need to stream and process all video frames. Vi

Yu. M. Andreev, D. Banerjee, B. Banto Oberhauser, J. Bernhard

Thermal dark matter models with particle $χ$ masses below the electroweak scale can provide an explanation for the observed relic dark matter density. This would imply the existence of a new feeble interaction between the dark and ordinary matter. We report on a new search for the sub-GeV $χ$ production through the interaction mediated by a new vector boson,

Pritam P Shetty, Hemalatha V, Mahalingam Babu, Jayachandra Bingi

Common path interferometers (CPI) are significant due to their compactness and vibration resistance. The usual challenge in CPI would arise due to a very small separation between reference and sample beams, where sending a reference beam through a sample is considered as a limitation. But this limitation also makes it difficult to probe the interaction of be

Henri De Plaen, Pierre-François De Plaen, Johan A. K. Suykens, Marc Proesmans

During training, supervised object detection tries to correctly match the predicted bounding boxes and associated classification scores to the ground truth. This is essential to determine which predictions are to be pushed towards which solutions, or to be discarded. Popular matching strategies include matching to the closest ground truth box (mostly used in

Zhaoze Wang, Junsong Wang

Hub structure, characterized by a few highly interconnected nodes surrounded by a larger number of nodes with fewer connections, is a prominent topological feature of biological brains, contributing to efficient information transfer and cognitive processing across various species. In this paper, a mathematical model of hub structure is presented. The propose

Shengding Hu, Yifan Luo, Huadong Wang, Xingyi Cheng

Pre-trained language models (PLMs) have shown unprecedented potential in various fields, especially as the backbones for question-answering (QA) systems. However, they tend to be easily deceived by tricky questions such as "How many eyes does the sun have?". Such frailties of PLMs often allude to the lack of knowledge within them. In this paper, we f

Parul Janagal, Samuel J. McSweeney, Manoneeta Chakraborty, N. D. Ramesh Bhat

PSR J0026-1955 was independently discovered by the Murchison Widefield Array (MWA) recently. The pulsar exhibits subpulse drifting, where the radio emission from a pulsar appears to drift in spin phase within the main pulse profile, and nulling, where the emission ceases briefly. The pulsar showcases a curious case of drift rate evolution as it exhibits rapi

Renato Sortino, Thomas Cecconello, Andrea DeMarco, Giuseppe Fiameni

Along with the nearing completion of the Square Kilometre Array (SKA), comes an increasing demand for accurate and reliable automated solutions to extract valuable information from the vast amount of data it will allow acquiring. Automated source finding is a particularly important task in this context, as it enables the detection and classification of astro

Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster

Understanding the causal relationships that underlie a system is a fundamental prerequisite to accurate decision-making. In this work, we explore how expert knowledge can be used to improve the data-driven identification of causal graphs, beyond Markov equivalence classes. In doing so, we consider a setting where we can query an expert about the orientation

Christian Ikenmeyer, Sathyawageeswar Subramanian

We prove that the computation of the Kronecker coefficients of the symmetric group is contained in the complexity class #BQP. This improves a recent result of Bravyi, Chowdhury, Gosset, Havlicek, and Zhu. We use only the quantum computing tools that are used in their paper and additional classical representation theoretic insights. We also prove the analogou

Manuel Concha, Luc Lapointe

Bisymmetric Macdonald polynomials can be obtained through a process of antisymmetrization and $t$-symmetrization of non-symmetric Macdonald polynomials. Using the double affine Hecke algebra, we show that the evaluation of the bisymmetric Macdonald polynomials satisfies a symmetry property generalizing that satisfied by the usual Macdonald polynomials. We th

Zahra Molaee, Ahmad Shirzad

We present a new Lagrangian approach for the dynamical structure of the generalized Proca theory (GP). This approach includes the A-Z constraint structure of the model in the Lagrangian formalism and ends up with an accurate count of the number of degrees of freedom. We also give the complete Hamiltonian constraint structure of the model.

Brian A. Bittner, Jason Reid, Kevin C. Wolfe

To achieve high-dexterity motion planning on floating-base systems, the base dynamics induced by arm motions must be treated carefully. In general, it is a significant challenge to establish a fixed-base frame during tasking due to forces and torques on the base that arise directly from arm motions (e.g. arm drag in low Reynolds environments and arm momentum

Radu Iosif, Florian Zuleger

In this paper we study a Separation Logic of Relations (SLR) and compare its expressiveness to (Monadic)Second Order Logic (M)SO. SLR is based on the well-known Symbolic Heap fragment of Separation Logic, whose formulae are composed of points-to assertions, inductively defined predicates, with the separating conjunction as the only logical connective. SLR ge

Kam Cheong Au

We consider the counting function of ideals in a given ideal class of a number field of degree $d$. This describes, at least conjecturally, the Fourier coefficients of an automorphic form on $\text{GL}(d)$, typically not a Hecke eigenform and not cuspidal. We compute its moments, and also investigate the moments of the corresponding cuspidal projection.

Alessandro Ingrosso, Emanuele Panizon

The cost of information processing in physical systems calls for a trade-off between performance and energetic expenditure. Here we formulate and study a computation-dissipation bottleneck in mesoscopic systems used as input-output devices. Using both real datasets and synthetic tasks, we show how non-equilibrium leads to enhanced performance. Our framework

Dong-Xu Sun, Pei-Pei Zhang, Yi-Qing Guo, Wei Liu

The observations of the energy spectra of cosmic-ray have revealed complicated structures. Especially, spectral hardenings in the boron-to-carbon and boron-to-oxygen ratios above $\sim 200$ GV has been revealed by AMS-02 and DAMPE experiments. One scenario to account for the hardenings of secondary-to-primary ratios is the nuclear fragmentation of freshly ac

Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton

Providing accurate uncertainty estimations is essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard method for this task, but they can struggle with large, high-dimensional datasets. Combining deep neural networks wi

Luisa Fiorot, Riccardo Gilblas, Alberto Tonolo

We study, through new recurrence relations for certain binomial coefficients modulo a power of a prime, the evolution of the primitives of a modular periodic sequence. We prove that we can reduce to study primitives of constant sequences and that the latter are controlled by modular binomial coefficients. Finally we apply our results to describe the dynamics

Deepika Venkattu, Peter Lundqvist, Miguel Pérez-Torres, Leah Morabito

We present an International LOFAR Telescope sub-arcsecond resolution image of the nearby galaxy M 51 with a beam size of 0.436" x 0.366" and rms of 46 $μ$Jy. We compare this image with an European VLBI Network study of M 51, and discuss the supernovae in this galaxy, which have not yet been probed at these low radio frequencies. We find a flux densit

Wei Li, Likang Zhang, Hao Tan, Yichen Lu

Quantum key distribution (QKD) can provide fundamentally proven security for secure communication. Toward application, the secret key rate (SKR) is a key figure of merit for any QKD system. So far, the SKR has been limited to about a few megabit-per-second. Here we report a QKD system that is able to generate key at a record high SKR of 115.8 Mb/s over 10-km

Daria Gazizova, J. P. F. LeBlanc

We compute the perturbative expansion for the effective interaction $W$ of the half-filled 2-dimensional Hubbard model. We derive extensions of standard RPA resummations that include arbitrarily high order contributions in the $W_{\uparrow\uparrow}$ and $W_{\uparrow\downarrow}$ basis. Using algorithmic tools we explore the static $Q$-dependent interaction as

Umberto D'Alesio, Leonard Gamberg, Francesco Murgia, Marco Zaccheddu

We present a phenomenological study on the role of charm contribution and $SU(2)$ isospin symmetry in the extraction of the $Λ$ polarizing fragmentation functions from $e^+e^- \to Λ^\uparrow (\barΛ^\uparrow) \,h + X$ annihilation processes. We adopt the well-established transverse-momentum-dependent factorization formalism, within the Collins-Soper-Sterman e

Ana Guerberof Arenas, Antonio Toral

This article presents the results of a study involving the reception of a fictional story by Kurt Vonnegut translated from English into Catalan and Dutch in three conditions: machine-translated (MT), post-edited (PE) and translated from scratch (HT). 223 participants were recruited who rated the reading conditions using three scales: Narrative Engagement, En

Arif Wider, Sumedha Verma, Atif Akhtar

Data mesh is a socio-technical approach to decentralized analytics data management. To manage this decentralization efficiently, data mesh relies on automation provided by a self-service data infrastructure platform. A key aspect of this platform is to enable decentralized data governance. Because data mesh is a young approach, there is a lack of coherence i

Ester Piedipalumbo, Stefano Vignolo, Pasquale Feola, Salvatore Capozziello

In the framework of scalar-tensor gravity, we consider non-flat interacting quintessence cosmology where a scalar field is interacting with dark matter. Such a scalar field can be a standard or a phantom one. We use the Noether Symmetry Approach to obtain general exact solutions for cosmological equations and to select scalar-field self-interaction potential

S. Kladov, M. Bossard, J. Brandt, Y-K. Kim

We built a test stand for evaluating the performance of the thermionic electron sources for the electron lens project at the Integrable Optics Test Accelerator (IOTA) in Fermilab. The lens will be used to study nonlinear dynamics and electron cooling of 2.5 MeV protons with strong space charge. The test stand will validate the characteristics of the thermion

Lorenzo Lombardi, Alessandro Kovtun, Sebastiano Mantovani, Giulio Bertuzzi

We present an environmentally benign methodology for the covalent functionalization (arylation) of reduced graphene oxide (rGO) nanosheets with arylazo sulfones. A variety of tagged aryl units were conveniently accommodated at the rGO surface via visible light irradiation of suspensions of carbon nanostructured materials in aqueous media. Mild reaction condi

Haoran Miao, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan

Recently, there has been increasing progress in end-to-end automatic speech recognition (ASR) architecture, which transcribes speech to text without any pre-trained alignments. One popular end-to-end approach is the hybrid Connectionist Temporal Classification (CTC) and attention (CTC/attention) based ASR architecture. However, how to deploy hybrid CTC/atten

Matthias Grundmann, Hannes Hartenstein

Payment channel networks are an approach to improve the scalability of blockchain-based cryptocurrencies. Because payment channel networks are used for transfer of financial value, their security in the presence of adversarial participants should be verified formally. We formalize the protocol of the Lightning Network, a payment channel network built for Bit

Timo Pierre Schrader, Teresa Bürkle, Sophie Henning, Sherry Tan

Scientific publications follow conventionalized rhetorical structures. Classifying the Argumentative Zone (AZ), e.g., identifying whether a sentence states a Motivation, a Result or Background information, has been proposed to improve processing of scholarly documents. In this work, we adapt and extend this idea to the domain of materials science research. W

Ludwig Mohr, Ismail Geles, Friedrich Fraundorfer

Rigid registration of point clouds is a fundamental problem in computer vision with many applications from 3D scene reconstruction to geometry capture and robotics. If a suitable initial registration is available, conventional methods like ICP and its many variants can provide adequate solutions. In absence of a suitable initialization and in the presence of

Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada

Flatness of the loss curve around a model at hand has been shown to empirically correlate with its generalization ability. Optimizing for flatness has been proposed as early as 1994 by Hochreiter and Schmidthuber, and was followed by more recent successful sharpness-aware optimization techniques. Their widespread adoption in practice, though, is dubious beca

Oleg Melichev, Roberto Percacci

Poincaré Gauge Theories are a class of Metric-Affine Gravity theories with a metric-compatible (i.e. Lorentz) connection and with an action quadratic in curvature and torsion. We perform an explicit one-loop calculation starting with a single term of each type and show that not only are all other terms generated, but also many others. In our particular model

Jiaxin Yu, Liming Fu, Peng Liang, Amjed Tahir

Background: Despite the widespread use of automated security defect detection tools, software projects still contain many security defects that could result in serious damage. Such tools are largely context-insensitive and may not cover all possible scenarios in testing potential issues, which makes them susceptible to missing complex security defects. Hence

Alexandre Mota, Fei Yang, Cristiano Teixeira

Nowadays, smart contracts have become increasingly popular and, as with software development in general, testing is the standard method for verifying their correctness. However, smart contracts require a higher level of certainty regarding correctness because they are diffcult to modify once deployed and errors can result in significant financial losses. The

Taku Nakajima, Shuro Takano, Tomoka Tosaki, Akio Taniguchi

We present an imaging molecular line survey in the 3-mm band (85-114 GHz) focused on one of the nearest galaxies with an active galactic nucleus (AGN), NGC 1068, based on observations taken with the Atacama Large Millimeter/submillimeter Array (ALMA). Distributions of 23 molecular transitions are obtained in the central ~3 kpc region, including both the circ

Elizabeth Maggie Penn, John W. Patty

Classification algorithms are increasingly used in areas such as housing, credit, and law enforcement in order to make decisions affecting peoples' lives. These algorithms can change individual behavior deliberately (a fraud prediction algorithm deterring fraud) or inadvertently (content sorting algorithms spreading misinformation), and they are increasi

F. Di Vruno, B. Winkel, C. G. Bassa, G. I. G. Józsa

We report on observations of 68 satellites belonging to the SpaceX Starlink constellation with the LOFAR radio telescope. Radiation associated with Starlink satellites was detected at observing frequencies between 110 and 188 MHz. A combination of broad-band features, covering the entire observed bandwidth, as well as narrow-band (bandwidth < 12.2 kHz) emiss

Josnei Novacoski, Mark Spivakovsky

The main goal of this paper is to characterize the module of Kähler differentials for an extension of valuation rings. More precisely, we consider a simple algebraic valued field extension $(L/K,v)$ and the corresponding valuation rings $\VR_L$ and $\VR_K$. In the case when $e(L/K,v)=1$ we present a characterization for $Ω_{\VR_L/\VR_K}$ in terms of a given

Zdeněk Dvořák, Abhiruk Lahiri

The maximum edge colouring problem considers the maximum colour assignment to edges of a graph under the condition that every vertex has at most a fixed number of distinct coloured edges incident on it. If that fixed number is $q$ we call the colouring a maximum edge $q$-colouring. The problem models a non-overlapping frequency channel assignment question on

J. W. Bruce, F. Tari

Congruences, or $2$-parameter families of lines in $3$-space are of interest in many situations, in particular in geometric optics. In this paper we consider elements of their geometry which are invariant under affine changes of co-ordinates, for example that associated with their focal sets, and less well studied focal planes. We use tools from singularity

Shan Cheng, Shu-Lei Zhang

In this paper we revisit $D_s \to f_0$ form factors from the light-cone sum rules with the light meson light-cone distribution amplitudes. The main motivation of this study is the differential decay width of $D_s \to \left[ππ\right]_{\rm S} e ν_e$ measured recently by BESIII collaboration and the $D_s \to f_0$ form factor extracted under the intermediate res

Saisai Ding, Jun Wang, Juncheng Li, Jun Shi

Whole slide image (WSI) classification is an essential task in computational pathology. Despite the recent advances in multiple instance learning (MIL) for WSI classification, accurate classification of WSIs remains challenging due to the extreme imbalance between the positive and negative instances in bags, and the complicated pre-processing to fuse multi-s

Berkin Bilgic, Mauro Costagli, Kwok-Shing Chan, Jeff Duyn

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generati

Leyla Fathollahi, Mahmood Mohassel Feghhi, Mahmoud Atashbar

In this paper, we propose a novel design for the rotary-wing unmanned aerial vehicle (UAV)-enabled full-duplex (FD) wireless-powered Internet of Things (IoT) networks. In this network, the UAV is equipped with an antenna array, and the $K$ IoT sensors, which are distributed randomly, use single-antenna to communicate. By sending the energy, the UAV as a hybr

Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok

Natural language processing (NLP) made an impressive jump with the introduction of Transformers. ChatGPT is one of the most famous examples, changing the perception of the possibilities of AI even outside the research community. However, besides the impressive performance, the quadratic time and space complexity of Transformers with respect to sequence lengt

André V. Duarte, Arlindo L. Oliveira

Matching addresses is a critical task for companies and post offices involved in the processing and delivery of packages. The ramifications of incorrectly delivering a package to the wrong recipient are numerous, ranging from harm to the company&#39;s reputation to economic and environmental costs. This research introduces a deep learning-based model designe

Frédéric Berthommier

A simplified model of articulatory synthesis involving four stages is presented. The planning of articulatory gestures is based on syllable graphs with arcs and nodes that are implemented in a complex representation. This was first motivated by a reduction in the many-to-one relationship between articulatory parameters and formant space. This allows for cons

Heming Zha, Wenjing Liu, Deyang Wang, Bo Zhao

Spin- and angle-resolved photoemission spectroscopy (SARPES) with high efficiency and resolution plays a crucial role in exploring the fine spin-resolved band structures of quantum materials. Here we report the performance of SARPES instrument with a second-generation home-made multichannel very-low-energy-electron-diffraction (VLEED) spin polarimeter. Its e

Tai D. Nguyen, Long H. Pham, Jun Sun

Fuzzing has emerged as a powerful technique for finding security bugs in complicated real-world applications. American fuzzy lop (AFL), a leading fuzzing tool, has demonstrated its powerful bug finding ability through a vast number of reported CVEs. However, its random mutation strategy is unable to generate test inputs that satisfy complicated branching con

Cyril Rauch, Panagiota Kyratzi, Andras Paldi

Based on the normal distribution and its properties, i.e., average and variance, Fisher works have provided a conceptual framework to identify genotype-phenotype associations. While Fisher intuition has proved fruitful over the past century, the current demands for higher mapping precisions have led to the formulation of a new genotype-phenotype association

Kun Li, George Vosselman, Michael Ying Yang

Interactive image segmentation aims to segment the target from the background with the manual guidance, which takes as input multimodal data such as images, clicks, scribbles, and bounding boxes. Recently, vision transformers have achieved a great success in several downstream visual tasks, and a few efforts have been made to bring this powerful architecture

Mohamed Amouch, Fernando León-Saavedra, M. P. Romero de la Rosa

An operator $T$ acting on a separable complex Hilbert space $H$ is said to be hypercyclic if there exists $f\in H$ such that the orbit $\{T^n f:\ n\in \mathbb{N}\}$ is dense in $H$. Godefroy and Shapiro \cite{GoSha} characterized those elements in the commutant of the Hardy backward shift which are hypercyclic. In this paper we study some dynamics properties

Yuguang Shi

One of the key problems in 3D object detection is to reduce the accuracy gap between methods based on LiDAR sensors and those based on monocular cameras. A recently proposed framework for monocular 3D detection based on Pseudo-Stereo has received considerable attention in the community. However, so far these two problems are discovered in existing practices,

Lasha Abzianidze, Joost Zwarts, Yoad Winter

While many natural language inference (NLI) datasets target certain semantic phenomena, e.g., negation, tense & aspect, monotonicity, and presupposition, to the best of our knowledge, there is no NLI dataset that involves diverse types of spatial expressions and reasoning. We fill this gap by semi-automatically creating an NLI dataset for spatial reasoning,

Elspeth K. H. Lee

Insight into the formation and global distribution of cloud particles in exoplanet atmospheres continues to be a key problem to tackle going into the JWST era. Understanding microphysical cloud processes and atmospheric feedback mechanisms in 3D has proven to be a challenging prospect for exoplaneteers. In an effort to address the large computational burden

Y. Y. Kovalev, A. V. Plavin, A. B. Pushkarev, S. V. Troitsky

The advancement of neutrino observatories has sparked a surge in multi-messenger astronomy. Multiple neutrino associations among blazars are reported while neutrino production site is located within their central (sub)parsecs. Yet many questions remain on the nature of those processes. The next generation Event Horizon Telescope (ngEHT) is uniquely positione

A. R. Kuzmak

The preparation of entangled quantum states is an inherent and indispensable step for the implementation of many quantum information algorithms. Depending on the physical system, there are different ways to control and measure them, which allow one to achieve the predefined quantum states. The diamond spin cluster is the system that can be applied for this p

A. Adıgüzel, H. Çetinkaya, Ş. Esen, D. Halis

High gradient accelerator injectors have been widely studied throughout the world-leading accelerator facilities. The demand for high frequency cavities have led the Detector, Accelerator and instrumentation laboratory (KAHVELab) in Istanbul to deploy a four-vane Radio Frequency Quadrupole (RFQ) operating at 800~MHz to accelerate 20~keV protons to 2~MeV. The

Mohamed Abouelnaga, Christine Jakobs

Nowadays, systematic security risk analysis plays a vital role in the automotive domain. The demand for advanced driver assistance systems and connectivity of vehicles to the internet makes cyber-security a crucial requirement for vehicle manufacturers. This paper summarizes the risk analysis method stated in the recently released automotive security standar

Nandini Iyer, Ronaldo Menezes, Hugo Barbosa

With trends of urbanisation on the rise, providing adequate housing to individuals remains a complex issue to be addressed. Often, the slow output of relevant housing policies, coupled with quickly increasing housing costs, leaves individuals with the burden of finding housing that is affordable and safe. In this paper, we unveil how urban planning, not just

Lars Martin Sektnan, Carl Tipler

We study the zero locus of the Futaki invariant on K-polystable Fano threefolds, seen as a map from the Kähler cone to the dual of the Lie algebra of the reduced automorphism group. We show that, apart from families 3.9, 3.13, 3.19, 3.20, 4.2, 4.4, 4.7 and 5.3 of the Iskovskikh-Mori-Mukai classification of Fano threefolds, the Futaki invariant of such manifo

Jiayi Lei, Tiankui Zhang, Yuanwei Liu

In this paper, a hybrid non-orthogonal multiple access (NOMA) framework for the simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) enhanced cell-edge communication is investigated. Specifically, one transmitted user and one reflected user are paired as one NOMA-pair, while multiple NOMA-pairs are served via time division m

J Dedecker, F Merlevède, Emmanuel Rio

In this paper, we give precise rates of convergence in the strong invariance principle for stationary sequences of bounded real-valued random variables satisfying weak dependence conditions. One of the main ingredients is a new Fuk-Nagaev type inequality for a class of weakly dependent sequences. We describe also several classes of processes to which our res

Suvojit Dhara, Adrijit Goswami

In many real-world multi-attribute decision-making (MADM) problems, mining the inter-relationships and possible hierarchical structures among the factors are considered to be one of the primary tasks. But, besides that, one major task is to determine an optimal strategy to work on the factors to enhance the effect on the goal attribute. This paper proposes t

Mohamed Abouelnaga, Julien Vitay, Aida Farahani

This paper investigates different methods and various neural network architectures applicable in the time series classification domain. The data is obtained from a fleet of gas sensors that measure and track quantities such as oxygen and sound. With the help of this data, we can detect events such as occupancy in a specific environment. At first, we analyze

Hannah Schuster, Axel Polleres, Johannes Wachs

This research studies how populations depend on road networks for access to health care during crises or natural disasters. So far, most researchers rather studied the accessibility of the whole network or the cost of network disruptions in general, rather than as a function of the accessibility of specific priority destinations like hospitals. Even short de

Saketh Virupakshi, Katarzyna Kowalczyk-Gajewska

The crystal plasticity finite element method (CPFEM) is used to investigate the coupling between the cylindrical void growth or collapse and grain refinement in face-centered cubic (FCC) single crystals. A 2D plane strain model with one void is used. The effect of the initial lattice orientation, similarities, and differences between stress- and strain-drive

Guangqiang Mei, Wei Tan, Xingxia Cui, Cong Wang

The quest for pragmatic room-temperature (RT) magnetic semiconductors (MSs) with a suitable bandgap constitutes one of the contemporary opportunities to be exploited. This may provide a materials platform for to bring new-generation ideal information device technologies into real-world applications where the otherwise conventionally separately utilized charg

Jayateja Kalla, Soma Biswas

Few-shot class-incremental learning (FSCIL) aims to learn progressively about new classes with very few labeled samples, without forgetting the knowledge of already learnt classes. FSCIL suffers from two major challenges: (i) over-fitting on the new classes due to limited amount of data, (ii) catastrophically forgetting about the old classes due to unavailab

Sandipana Dowerah, Ajinkya Kulkarni, Romain Serizel, Denis Jouvet

The paper introduces Diff-Filter, a multichannel speech enhancement approach based on the diffusion probabilistic model, for improving speaker verification performance under noisy and reverberant conditions. It also presents a new two-step training procedure that takes the benefit of self-supervised learning. In the first stage, the Diff-Filter is trained by

Garrett Allen, Gaole He, Ujwal Gadiraju

We are amidst an explosion of artificial intelligence research, particularly around large language models (LLMs). These models have a range of applications across domains like medicine, finance, commonsense knowledge graphs, and crowdsourcing. Investigation into LLMs as part of crowdsourcing workflows remains an under-explored space. The crowdsourcing resear

Stefan Kratsch, Pascal Kunz

An $α$-approximate polynomial Turing kernelization is a polynomial-time algorithm that computes an $(αc)$-approximate solution for a parameterized optimization problem when given access to an oracle that can compute $c$-approximate solutions to instances with size bounded by a polynomial in the parameter. Hols et al. [ESA 2020] showed that a wide array of gr

Paul Schwenteck, Sandra Zimmermann, Caspar von Lengerke, Giang T. Nguyen

This paper provides an overview of the hardware and software components used in our test bed project the NET Playground. All source information is stored in the GitLab repository (https://gitlab.com/Paulteck/net-playground). In the Hardware section, we present sketches and 3D views of mechanical parts and technical drawings of printed boards. The Software se

Shuai Chen, Subhradeep Kayal, Marleen de Bruijne

The paradigm of self-supervision focuses on representation learning from raw data without the need of labor-consuming annotations, which is the main bottleneck of current data-driven methods. Self-supervision tasks are often used to pre-train a neural network with a large amount of unlabeled data and extract generic features of the dataset. The learned model

Fernando León-Saavedra, M. del Carmen Listán-García, María Pilar Romero de la Rosa

We survey some results that provide different versions of classical results through different summability methods. Specifically, in order to adapt such classical results, we analyze which properties should satisfy the summability methods. Sometimes very sharp conditions are obtained, giving a focused view of the subject and from which new problems emerge.

Muzaffar M. Rahmatullaev, Obid Sh. Karshiboev

In this paper, we consider a three-state solid-on-solid (SOS) model with two competing interactions (nearest-neighbour, one-level next-nearest-neighbour) on the Cayley tree of order two. We show that at some values of parameters the model exhibits a phase transition. We prove that for the model under some conditions there is no antiferromagnetic phases.

Dirk - André Deckert, Franz Merkl, Markus Nöth

In honour of Detlef Dürr, we report on a mathematical rigorous computation of the electric vacuum polarisation current and extract the well-known expression for the second order perturbation. Intermediate steps in the presented calculation demonstrate, to the knowledge of the authors for the first time, mathematical rigorous versions of the combined dimensio