August 2022 arXiv papers — page 126

David Xu, A. Barış Özgüler, Giuseppe Di Guglielmo, Nhan Tran

Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outside of the simulation. Existing hardware solutions structured as lookup tables are imprecise and costly. By desi

Ahmad Naghavi, Mohammad Sadegh Fazel, Mojtaba Beheshti, Ehsan Yazdian

Synthetic aperture radar (SAR) tomography (TomoSAR) is an appealing tool for the extraction of height information of urban infrastructures. Due to the widespread applications of the MUSIC algorithm in source localization, it is a suitable solution in TomoSAR when multiple snapshots (looks) are available. While the classical MUSIC algorithm aims to estimate t

Alexander Lenz, Maria Laura Piscopo, Aleksey V. Rusov

We update the Standard Model (SM) predictions for $B$-meson lifetimes within the heavy quark expansion (HQE). Including for the first time the contribution of the Darwin operator, SU(3)$_F$ breaking corrections to the matrix element of dimension-six four-quark operators and the so-called eye-contractions, we obtain for the total widths $\Gamma (B^+) = (0.58^

Xiaoru Gao, GuoYan Zheng

Registration plays an important role in medical image analysis. Deep learning-based methods have been studied for medical image registration, which leverage convolutional neural networks (CNNs) for efficiently regressing a dense deformation field from a pair of images. However, CNNs are limited in its ability to extract semantically meaningful intra- and int

Saswath Ghosh, Sitikantha Roy

This study presents the analytical modeling of a fiber-reinforced tubular conducting polymer (FTCP) actuator. The FTCP actuator is a low voltage-driven electroactive polymer arranged in an electrochemical cell. The electrochemical model is developed following an electrical circuit analogy that predicts the charge diffused inside the actuator for an applied v

Pierre Fraigniaud, Pedro Montealegre, Pablo Paredes, Ivan Rapaport

During the last two decades, a small set of distributed computing models for networks have emerged, among which LOCAL, CONGEST, and Broadcast Congested Clique (BCC) play a prominent role. We consider hybrid models resulting from combining these three models. That is, we analyze the computing power of models allowing to, say, perform a constant number of roun

Pan-Pan Shi, Feng-Kun Guo, Zhi Yang

The semi-inclusive electroproduction of exotic hadrons, including the $T_{cc}$, $P_{cs}$, and hidden-charm baryon-antibaryon states, is explored under the assumption that they are $S$-wave hadronic molecules of a pair of charmed hadrons. We employ the Monte Carlo event generator Pythia to produce the hadron pairs and then bind them together to form hadronic

Virginia N. L. Franqueira, Jessica A. Annor, Ozgur Kafali

The presence of children in the online world is increasing at a rapid pace. As children interact with services such as video sharing, live streaming, and gaming, a number of concerns arise regarding their security and privacy as well as their safety. To address such concerns, the UK's Information Commissioner's Office (ICO) sets out 15 criteria alongside a r

Mihail N. Kolountzakis, Effie Papageorgiou

Suppose $a_n$ is a real, nonnegative sequence that does not increase exponentially. For any $p<1$ we contruct a Lebesgue measurable set $E \subseteq \mathbb{R}$ which has measure at least $p$ in any unit interval and which contains no affine copy $\{x+ta_n:\ n\in\mathbb{N}\}$ of the given sequence (for any $x \in \mathbb{R}, t > 0$). We generalize this to hi

A. Scordo, C. Amsler, M. Bazzi, D. Bosnar

In this paper, we present the first tests performed after the full installation of the SIDDHARTA-2 experimental apparatus on the Interaction Region of the DA{\Phi}NE collider at the INFN National Laboratories of Frascati. Before starting the first measurement of the kaonic deuterium 2p{\rightarrow}1s transition, accurate evaluation of the background rejectio

Jiajia Wen, Zhongyin Xu, Yanyong Hong

In this paper, we give a complete classification of all free $U(\mathbb{C}L_0 \oplus \mathbb{C}Y_0\oplus \mathbb{C}M_0)$-modules of rank 1 over a Schr{\"o}dinger-Virasoro type algebra $\mathfrak{tsv}$.

Steven van Kesteren, Xueting Shen, Michele Aldeghi, Lucio Isa

Additive manufacturing at the micro- and nanoscale has seen a recent upsurge to suit the increasing demand for more elaborate structures. However, the integration and precise placement of multiple distinct materials at small scales remain a challenge. To this end, we combine here the directed capillary assembly of colloidal particles and two-photon direct la

Junais, S. Boissier, A. Boselli, L. Ferrarese

Low-surface-brightness galaxies (LSBs) contribute to a significant fraction of all the galaxies in the Universe. Ultra-diffuse galaxies (UDGs) form a subclass of LSBs that has attracted a lot of attention in recent years (although its definition may vary between studies). Although UDGs are found in large numbers in galaxy clusters, groups, and in the field,

Maximilian Fichtl

We study the problem of computing optimal prices for a version of the Product-Mix auction with budget constraints. In contrast to the ``standard'' Product-Mix auction, the objective is to maximize revenue instead of social welfare. We prove correctness of an algorithm proposed by Paul Klemperer and DotEcon which is sufficiently efficient in smaller markets.

Junxia You, Lihua Yang

In this paper, we propose the construction of critically sampled perfect reconstruction two-channel filterbanks on arbitrary undirected graphs.Inspired by the design of graphQMF proposed in the literature, we propose a general ``spectral folding property'' similar to that of bipartite graphs and provide sufficient conditions for constructing perfect reconstr

Xi Xie, Sihem Mesnager, Nian Li, Debiao He

In this article, we focus on the concept of locally-APN-ness (``APN" is the abbreviation of the well-known notion of Almost Perfect Nonlinear) introduced by Blondeau, Canteaut, and Charpin, which makes the corpus of S-boxes somehow larger regarding their differential uniformity and, therefore, possibly, more suitable candidates against the differential attac

Vadim A. Naumov, Dmitry S. Shkirmanov

Within a covariant perturbative field-theoretical approach, the wave-packet modified neutrino propagator is expressed as an asymptotic expansion in powers of dimensionless Lorentz- and rotation-invariant variables. The expansion is valid at high energies and short but macroscopic space-time distances between the vertices of the proper Feynman macrodiagram. I

Jyong-Hao Chen, Vadim Cheianov

We investigate why, in quantum many-body systems, the adiabatic fidelity and the overlap between the initial state and instantaneous ground states often yield nearly identical values. Our analysis suggests that this phenomenon results from an interplay between two intrinsic limits of many-body systems: the limit of small evolution parameters and the limit of

Nicolas Rougerie

The fractional quantum Hall effect in 2D electron gases submitted to large magnetic fields remains one of the most striking phenomena in condensed matter physics. Historically, the first observed signature is a Hall resistance quantized to the value (2m+1) when the filling factor (electron density divided by magnetic flux quantum density) of a 2D electron ga

Victor Mayoral Vilches, Ruffin White, Gianluca Caiazza, Mikael Arguedas

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding security to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to

Tomer Shenar

Wolf-Rayet (WR) stars comprise a class of stars whose spectra are dominated by strong, broad emission lines that are associated with copious mass loss. In the massive-star regime, roughly 90% of the known WR stars are thought to have evolved off the main sequence. Dubbed classical WR (cWR) stars, these hydrogen-depleted objects represent a crucial evolutiona

Yongkun Liu, Kesong Ni, Yuhan Zhang, Lijian Zhou

Multi-Label Remote Sensing Image Classification (MLRSIC) has received increasing research interest. Taking the cooccurrence relationship of multiple labels as additional information helps to improve the performance of this task. Current methods focus on using it to constrain the final feature output of a Convolutional Neural Network (CNN). On the one hand, t

Zhenqiang Li, Lin Gu, Weimin Wang, Ryosuke Nakamura

Automated video-based assessment of surgical skills is a promising task in assisting young surgical trainees, especially in poor-resource areas. Existing works often resort to a CNN-LSTM joint framework that models long-term relationships by LSTMs on spatially pooled short-term CNN features. However, this practice would inevitably neglect the difference amon

Sattarov Otabek, Jaeyoung Choi

Aspiring to achieve an accurate Bitcoin price prediction based on people's opinions on Twitter usually requires millions of tweets, using different text mining techniques (preprocessing, tokenization, stemming, stop word removal), and developing a machine learning model to perform the prediction. These attempts lead to the employment of a significant amount

Zied Chaieb, Djibril Gueye

The main goal of this paper is to use the enlargement of ltration framework for pricing zerocoupon CAT bonds. For this purpose, we develop two models where the trigger event time is perfectly covered by an increasing sequence of stopping times with respect to a reference ltration. Hence, depending on the nature of these stopping times the trigger event time

Jaroslav Hrdina, Dietmar Hildenbrand, Aleš Návrat, Christian Steinmetz

We introduce Quantum Register Algebra (QRA) as an efficient tool for quantum computing. We show the direct link between QRA and Dirac formalism. We present GAALOP (Geometric Algebra Algorithms Optimizer) implementation of our approach. Using the QRA basis vectors definitions given in Section 4 and the framework based on the de Witt basis presented in Section

Manh Hung Nguyen, Lisheng Sun, Nathan Grinsztajn, Isabelle Guyon

Meta-learning from learning curves is an important yet often neglected research area in the Machine Learning community. We introduce a series of Reinforcement Learning-based meta-learning challenges, in which an agent searches for the best suited algorithm for a given dataset, based on feedback of learning curves from the environment. The first round attract

Felipe Albuquerque Portella, David Buchaca Prats, José Roberto Pereira Rodrigues, Josep Lluís Berral

Reservoir simulations for petroleum fields and seismic imaging are known as the most demanding workloads for high-performance computing (HPC) in the oil and gas (O&G) industry. The optimization of the simulator numerical parameters plays a vital role as it could save considerable computational efforts. State-of-the-art optimization techniques are based on ru

Masataka Matsumoto

We study critical phenomena at a tricritical point associated with a chiral phase transition which emerges in the D3/D7 model in the presence of a finite baryon number density and an external magnetic field. We numerically determine critical exponents related to the thermodynamic quantities and correlation functions. We find that the values of the critical e

Sergey Afonin, Timofey Solomko

We derive and analyze the confinement potential of the Cornell type within the framework of the generalized Soft Wall holographic model that includes a parameter controlling the intercept of the linear Regge spectrum. In the phenomenology of Regge trajectories, this parameter is very important for the quantitative description of experimental data. Our analys

Mihail N. Kolountzakis

We discuss problems of simultaneous tiling. This means that we have an object (set, function) which tiles space with two or more different sets of translations. The most famous problem of this type is the Steinhaus problem which asks for a set simultaneously tiling the plane with all rotates of the integer lattice as translation sets.

Andronikos Paliathanasis

We apply the theory of Lie point symmetries for the study of a family of partial differential equations which are integrable by the hyperbolic reductions method and are reduced to members of the Painlev\'{e} transcendents. The main results of this study is that from the application of the similarity transformations provided by the Lie point symmetries all th

Bram van der Linden, Tadeus Hogenelst, Roland Bliem, Kateřina Dohnalová

High entropy materials (HEMs) are of great interest for their mechanical, chemical and electronic properties. In this paper we analyse (TaNbHfTiZr)C, a carbide type of HEM, both in crystalline and amorphous phases, using density functional theory (DFT). We find that the relaxed lattice volume of the amorphous phase is larger, while its bulk modulus is lower,

Daniel Kressner, Bart Vandereycken, Rik Voorhaar

Tensor trains are a versatile tool to compress and work with high-dimensional data and functions. In this work we introduce the Streaming Tensor Train Approximation (STTA), a new class of algorithms for approximating a given tensor $\mathcal T$ in the tensor train format. STTA accesses $\mathcal T$ exclusively via two-sided random sketches of the original da

Andronikos Paliathanasis

We consider a cosmological model in a Friedmann--Lema\^{\i}tre--Robertson--Walker background space with an ideal gas defined in Weyl Integrable gravity. In the Einstein-Weyl theory a scalar field is introduced in a geometric way. Furthermore, the scalar field and the ideal gas interact in the gravitational Action Integral. Furthermore, we introduce a potenti

Andrei T. Patrascu

All entropy is entanglement entropy. This appears as the result of the existence of black holes. The origin of entropy and the way in which it defines the perceived time direction in macroscopic systems has been discussed and can be debated as long as one ignores black holes. In such a case, thermodynamic entropy may define the arrow of time and entanglement

Jadson Santos, Daniel Alencar da Costa, Uirá Kulesza

Background: Much research has been conducted to investigate the impact of Continuous Integration (CI) on the productivity and quality of open-source projects. Most of studies have analyzed the impact of adopting a CI server service (e.g, Travis-CI) but did not analyze CI sub-practices. Aims: We aim to evaluate the impact of five CI sub-practices with respect

Anil Kanduri, Sina Shahhosseini, Emad Kasaeyan Naeini, Hamidreza Alikhani

Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics. Smart eHealth applications sense input data from multiple modalities, transmit the data to edge and/or cloud nodes, and process the data with compute intensive machine learning (ML) algorithm

Giacomo Petrillo

I consider the Lerch-Hurwitz or periodic zeta function as covariance function of a periodic continuous-time stationary stochastic process. The function can be parametrized with a continuous index $\nu$ which regulates the continuity and differentiability properties of the process in a way completely analogous to the parameter $\nu$ of the Mat\'ern class of c

Yakov Miron, Yuval Goldfracht, Chana Ross, Dotan Di Castro

Surface grading, the process of leveling an uneven area containing pre-dumped sand piles, is an important task in the construction site pipeline. This labour-intensive process is often carried out by a dozer, a key machinery tool at any construction site. Current attempts to automate surface grading assume perfect localization. However, in real-world scenari

Anders Dyhr Sandgaard, Valerij G. Kiselev, Rafael Neto Henriques, Noam Shemesh

Accurate estimation of microscopic magnetic field variations induced in biological tissue can be valuable for mapping tissue composition in health and disease. Here, we present an extension to Quantitative susceptibility mapping (QSM) to account for local white matter (WM) magnetic microstructure by using our previously presented model for solid cylinders wi

Jaimandeep Singh, Chintan Patel, Naveen Kumar Chaudhary

In recent cyber attacks, credential theft has emerged as one of the primary vectors of gaining entry into the system. Once attacker(s) have a foothold in the system, they use various techniques including token manipulation to elevate the privileges and access protected resources. This makes authentication and token based authorization a critical component fo

Daniel Schiwietz, Eva M. Weig, Peter Degenfeld-Schonburg

Microelectromechanical systems (MEMS) gyroscopes are widely used, e.g. in modern automotive and consumer applications, and require signal stability and accuracy in rather harsh environmental conditions. In many use cases, device reliability must be guaranteed under large external loads at high frequencies. The sensitivity of the sensor to such external loads

Maximilian Böther, Otto Kißig, Christopher Weyand

Computing a directed minimum spanning tree, called arborescence, is a fundamental algorithmic problem, although not as common as its undirected counterpart. In 1967, Edmonds discussed an elegant solution. It was refined to run in $O(\min(n^2, m\log n))$ by Tarjan which is optimal for very dense and very sparse graphs. Gabow et al.~gave a version of Edmonds'

Elena Kosygina, Thomas Mountford, Jonathon Peterson

We use generalized Ray-Knight theorems introduced by B\'alint T\'oth in 1996 together with techniques developed for excited random walks as main tools for establishing positive and negative results concerning convergence of some classes of diffusively scaled self-interacting random walks (SIRWs) to Brownian motions perturbed at extrema (BMPE). T\'oth's work

Yuly Chamorro, Anastasia Borschevsky, Ephraim Eliav, Steven Hoekstra

High-precision tests of fundamental symmetries are looking for the parity- (P), time-reversal- (T) violating electric dipole moment of the electron (eEDM) as proof of physics beyond the Standard Model. Particularly, in polyatomic molecules, the complex vibrational and rotational structure gives the possibility to reach high enhancement of the P, T-odd effect

Syed Imtiaz Ahamed, Vadlamani Ravi

The Machine Learning and Deep Learning Models require a lot of data for the training process, and in some scenarios, there might be some sensitive data, such as customer information involved, which the organizations might be hesitant to outsource for model building. Some of the privacy-preserving techniques such as Differential Privacy, Homomorphic Encryptio

Paolo Aceto, Duncan McCoy, JungHwan Park

This paper considers the problem of determining the smallest (as measured by the second Betti number) smooth negative-definite filling of a lens space. The main result is to classify those lens spaces for which the associated negative-definite canonical plumbing is minimal. The classification takes the form of a list of 10 "forbidden" subgraphs that cannot a

Ilya Chevyrev, Kurusch Ebrahimi-Fard, Frédéric Patras

The role of coalgebras as well as algebraic groups in non-commutative probability has long been advocated by the school of von Waldenfels and Sch\"urmann. Another algebraic approach was introduced more recently, based on shuffle and pre-Lie calculus, and results in another construction of groups of characters encoding the behaviour of states. Comparing the t

Chris Bowman, Maud De Visscher, Amit Hazi, Emily Norton

We calculate the $p$-Kazhdan--Lusztig polynomials for Hermitian symmetric pairs and prove that the corresponding anti-spherical Hecke categories categories are standard Koszul. We prove that the combinatorial invariance conjecture can be lifted to the level of graded Morita equivalences between subquotients of these Hecke categories.

Kristina Oganesyan

We prove that for any even algebraic polynomial $p$ one can find a cosine polynomial with an arbitrary small $l_1$-norm of coefficients such that the first coefficients of its representation as an algebraic polynomial in $\cos x$ coincide with those of $p$.

Lei Li, Zhiyuan Zhang, Ruihan Bao, Keiko Harimoto

Traditional knowledge distillation in classification problems transfers the knowledge via class correlations in the soft label produced by teacher models, which are not available in regression problems like stock trading volume prediction. To remedy this, we present a novel distillation framework for training a light-weight student model to perform trading v

Changbin Im, Björn Kirchhoff, Igor Krivtsov, Dariusz Mitoraj

Detailed understanding of the structural and photophysical properties of polymeric carbon nitride (PCN) materials is of critical importance to derive future material optimization strategies towards more desirable optical properties and more photocatalytically active materials. However, the wide range of structural motifs found in synthesized PCNs complicates

Rémi Lassalle

In this work, we investigate an optimization problem over adapted couplings between pairs of real valued random variables, possibly describing random times. We relate those couplings to a specific class of causal transport plans between probabilities on the set of real numbers endowed with a filtration, for which their provide a specific representation, whic

Fatih Emre Simsek, Cevahir Cigla, Koray Kayabol

Multi-object tracking (MOT) has been dominated by the use of track by detection approaches due to the success of convolutional neural networks (CNNs) on detection in the last decade. As the datasets and bench-marking sites are published, research direction has shifted towards yielding best accuracy on generic scenarios including re-identification (reID) of o

Guillermo Pineda-Villavicencio

It is folklore that the cycle space of graphs of polytopes is generated by the cycles bounding the 2-faces. We provide a proof of this result that bypass homological arguments, which seem to be the most widely known proof. As a corollary, we obtain a result of Blind & Blind (1994) stating that graphs of polytopes are bipartite if and only if graphs of every

Shiki Sato, Reina Akama, Hiroki Ouchi, Ryoko Tokuhisa

Avoiding the generation of responses that contradict the preceding context is a significant challenge in dialogue response generation. One feasible method is post-processing, such as filtering out contradicting responses from a resulting n-best response list. In this scenario, the quality of the n-best list considerably affects the occurrence of contradictio

Serge Kas Hanna, Rawad Bitar, Parimal Parag, Venkat Dasari

We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on $n$ workers, each having a subset of the data. Distributed SGD may suffer from the effect of stragglers, i.e., slow or unresponsive workers who cause delays. One solution studied in the literature is to wait at each iteration for the responses of

Andreas Scalas

The evolution of 3D visual content calls for innovative methods for modelling shapes based on their intended usage, function and role in a complex scenario. Even if different attempts have been done in this direction, shape modelling still mainly focuses on geometry. However, 3D models have a structure, given by the arrangement of salient parts, and shape an

Dominik Dold, Josep Soler Garrido, Victor Caceres Chian, Marcel Hildebrandt

Knowledge graphs are an expressive and widely used data structure due to their ability to integrate data from different domains in a sensible and machine-readable way. Thus, they can be used to model a variety of systems such as molecules and social networks. However, it still remains an open question how symbolic reasoning could be realized in spiking syste

Jean Douçot, Gabriele Rembado

We will define and study (moduli) spaces of deformations of irregular classes on Riemann surfaces, which provide an intrinsic viewpoint on the `times' of irregular isomonodromy systems in general. Our aim is to study the deeper generalisation of the G-braid groups that occur as fundamental groups of such deformation spaces, with particular focus on the gener

Alexei Kuzmin, Milena Dile, Katrina Laganovska, Aleksejs Zolotarjovs

Undoped and Mn-doped ZnS nanocrystals were produced by the microwave-assisted solvothermal method and characterized by X-ray diffraction, photoluminescence spectroscopy and scanning electron microscopy with energy-dispersive X-ray spectroscopy. All samples have the cubic zinc blende structure with the lattice parameter in the range of $a$ = 5.406-5.411 \r{A}

Constantinos Kardaras, Hyeng Keun Koo, Johannes Ruf

Fund models are statistical descriptions of markets where all asset returns are spanned by the returns of a lower-dimensional collection of funds, modulo orthogonal noise. Equivalently, they may be characterised as models where the global growth-optimal portfolio only involves investment in the aforementioned funds. The loss of growth due to estimation error

Sergey V. Sergeyev, Mahmoud Eliwa, Hani Kbashi

Soliton rain is a bunch of small soliton pulses slowly drifting nearby the main pulse having the period of a round trip. For Er-doped fiber laser mode-locked by carbon nanotubes, for the first time, we demonstrate both experimentally and theoretically a new type of polarization attractors controllable by the vector soliton rain. With adjusting the pump power

Volodymyr Vovchenko, Volker Koch, Chun Shen

We analyze the behavior of (net-)proton number cumulants in central collisions of heavy ions across a broad collision energy range by utilizing hydrodynamic simulations. The calculations incorporate essential non-critical contributions to proton fluctuations such as repulsive baryonic core and exact baryon number conservation. The experimental data are consi

Jing Qi, Paula M. Weber, Tilman Kißlinger, Lutz Hammer

The Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction mediates collinear magnetic interactions via the conduction electrons of a non-magnetic spacer, resulting in a ferro- or antiferromagnetic magnetization in magnetic multilayers. The resulting spin-polarized charge transport effects have found numerous applications. Recently it has been discovered that heav

Yingying Wang

We give a description of the cohomology groups of the structure sheaf on smooth compactifications $\overline{X}(w)$ of Deligne--Lusztig varieties $X(w)$ for ${\rm GL}_n$, for all elements $w$ in the Weyl group. As a consequence, we obtain the ${\rm mod}\ p^m$ and integral $p$-adic \'{e}tale cohomology of $\overline{X}(w)$. Moreover, using our result for $\ov

Rick Tanner, Stefano Agosteo, Hans Rabus

This paper is the editorial of a special issue of Radiation Measurements on EURADOS intercomparisons in computational dosimetry. The articles in this special issue cover complex problems in terms of geometry, particle types, energy ranges, coupled calculations and also scale, with the possibility of performing Monte Carlo calculations on micro and nano dosim

Yue Xu, Yong-Lu Li, Jiefeng Li, Cewu Lu

Long-tailed image recognition presents massive challenges to deep learning systems since the imbalance between majority (head) classes and minority (tail) classes severely skews the data-driven deep neural networks. Previous methods tackle with data imbalance from the viewpoints of data distribution, feature space, and model design, etc. In this work, instea

Ming Hao Quek

We provide a new, geometric proof of the motivic monodromy conjecture for non-degenerate hypersurfaces in dimension $3$, which has been proven previously by the work of Lemahieu--Van Proeyen and Bories--Veys. More generally, given a non-degenerate complex polynomial $f$ in any number of variables and a set $\mathbf{B}$ of $B_1$-facets of the Newton polyhedro

JooYoung Seo, Mine Dogucu

Although there are various ways to represent data patterns and models, visualization has been primarily taught in many data science courses for its efficiency. Such vision-dependent output may cause critical barriers against those who are blind and visually impaired and people with learning disabilities. We argue that instructors need to teach multiple data

Tongyue Shi, Haining Wang

This paper studied the relationship between the decomposition rate of fungi and temperature, humidity, fungus elongation, moisture tolerance and fungus density in a given volume in the presence of a variety of fungi, and established a series of models to describe the decomposition of fungi in different states. Since the volume of soil was given in this case,

Rebekka V. Woldseth, Niels Aage, J. Andreas Bærentzen, Ole Sigmund

The question of how methods from the field of artificial intelligence can help improve the conventional frameworks for topology optimisation has received increasing attention over the last few years. Motivated by the capabilities of neural networks in image analysis, different model-variations aimed at obtaining iteration-free topology optimisation have been

Karla Z. Arellano-Córdova, Danielle A. Berg, John Chisholm, Pablo Arrabal Haro

We analyze the rest-frame near-UV and optical nebular spectra of three $z > 7$ galaxies from the Early Release Observations taken with the Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope (JWST). These three high-z galaxies show the detection of several strong-emission nebular lines, including the temperature-sensitive [O III] $\lambda$

Soumya Chakrabarti, Soumya Bhattacharya, Rabin Banerjee, Amitabha Lahiri

We argue that Nash theory, a quadratic theory of Gravity, can describe a late-time cosmic acceleration without any exotic matter or cosmological constant. The observational viability of an exact cosmological solution of Nash theory is adjudged using a Markov chain Monte Carlo simulation and JLA+OHD+BAO data sets. Departures from standard {\Lambda}CDM cosmolo

Hamed Pezeshki, Pingzhi Li, Reinoud Lavrijsen, Jos J. G. M. van der Tol

In this paper, we propose a compact integrated hybrid plasmonic-photonic device for optical reading of nanoscale magnetic bits with perpendicular magnetic anisotropy in a magnetic racetrack on top of a photonic waveguide on the indium phosphide membrane on silicon platform. The hybrid device is constructed by coupling a doublet of V-shaped gold plasmonic nan

En Xu, Tao Zhou, Zhiwen Yu, Zhuo Sun

Predictability is an emerging metric that quantifies the highest possible prediction accuracy for a given time series, being widely utilized in assessing known prediction algorithms and characterizing intrinsic regularities in human behaviors. Lately, increasing criticisms aim at the inaccuracy of the estimated predictability, caused by the original entropy-

Vladimir Dzhunushaliev, Vladimir Folomeev, Daulet Berkimbayev

Particlelike solutions in SU(3) gauge Yang-Mills theory with color magnetic and electric fields sourced by a nonlinear spinor field are obtained. The asymptotic behavior of these fields is studied. It is shown that the electric field exhibits the Coulomb asymptotic behavior, and one of the color components of the magnetic field behaves asymptotically as the

Tian Zhou, Leonardo Modesto

Throughout the study of the geodesics of some popular spherically symmetric regular black holes, we hereby prove that the analytically extended Hayward black hole is geodetically incomplete. The simplest extension of the Culetu-Simpson-Visser's non-analytic smooth black hole is also geodetically incomplete, with the exception of the antipodal continuation of

Zheng Qi, AprilPyone MaungMaung, Hitoshi Kiya

In this paper, we propose a privacy-preserving image classification method using encrypted images under the use of the ConvMixer structure. Block-wise scrambled images, which are robust enough against various attacks, have been used for privacy-preserving image classification tasks, but the combined use of a classification network and an adaptation network i

Rosa C. J. Kraaijveld, Marielle E. P. Philippens, Wietse S. C. Eppinga, Ina M. Jürgenliemk-Schulz

Explainable artificial intelligence (XAI) is increasingly used to analyze the behavior of neural networks. Concept activation uses human-interpretable concepts to explain neural network behavior. This study aimed at assessing the feasibility of regression concept activation to explain detection and classification of multi-modal volumetric data. Proof-of-conc

Priyanka Singh, Vladislav D. Mosin, Ivan P. Yamshchikov

Working within specific NLP subdomains presents significant challenges, primarily due to a persistent deficit of data. Stringent privacy concerns and limited data accessibility often drive this shortage. Additionally, the medical domain demands high accuracy, where even marginal improvements in model performance can have profound impacts. In this study, we i

Yuichiro Mori, Shiro Kawabata, Yuichiro Matsuzaki

We propose an experimental method for evaluating the adiabatic condition during quantum annealing (QA), which will be essential for solving practical problems. The adiabatic condition consists of the transition matrix element and the energy gap, and our method simultaneously provides information about these components without diagonalizing the Hamiltonian. T

Amir Jahangiri, Xiao Han, Dmitry Lesovoy, Tatiana Agback

A new deep neural network based on the WaveNet architecture (WNN) is presented, which is designed to grasp specific patterns in the NMR spectra. When trained at a fixed non-uniform sampling (NUS) schedule, the WNN benefits from pattern recognition of the corresponding point spread function (PSF) pattern produced by each spectral peak resulting in the highest

Miodrag Mateljević, Ruslan Salimov, Evgeny Sevost'Yanov

In this article, we consider the H\"{o}lder continuity of injective maps in Orlicz-Sobolev classes defined on the unit ball. Under certain conditions on the growth of dilatations, we obtain the H\"{o}lder continuity of the indicated class of mappings. In particular, under certain special restrictions, we show that Lipschitz continuity of mappings holds. We a

Gianluca Francica

An indefinite causal order, where the causes of events are not necessarily in past events, is predicted by the process matrix framework. A fundamental question is how these non-separable causal structures can be related to the thermodynamic phenomena. Here, we approach this problem by considering the existence of two cooperating local Maxwell's demons which

Manuel Paredes, Marc Sartor, Cédric Masclet

This paper analyses the advantages of using a stock spring selection tool that manages the uncertainty of designer requirements. Firstly, the manual search and its main drawbacks are described. Then a computer assisted stock spring selection tool is presented which performs all necessary calculations to extract the most suitable spring from within a database

Yves Benoist

This note contains a short proof of a classical result: any rational symplectic matrix can be put in diagonal form after right and left multiplication by integral symplectic matrices.

Semyon Germanskiy, Renato M. A. Dantas, Sergey Kovalev, Chris Reinhoffer

We report on terahertz high-harmonic generation in a Dirac semimetal as a function of the driving-pulse ellipticity and on a theoretical study of the field-driven intraband kinetics of massless Dirac fermions.Very efficient control of third-harmonic yield and polarization state is achieved in electron-doped Cd$_3$As$_2$ thin films at room temperature. The ob

Nilasis Chaudhuri, Eduard Feireisl, Ewelina Zatorska

We prove nonuniqueness of weak solutions to multi-dimensional generalisation of the Aw-Rascle model of vehicular traffic. Our generalisation includes the velocity offset in a form of gradient of density function, which results in a dissipation effect, similar to viscous dissipation in the compressible viscous fluid models. We show that despite this dissipati

John A. Regan, Fabio Pacucci, M. J. Bustamante-Rosell

Observational evidence is mounting regarding the population demographics of Massive Black Holes (MBHs), from the most massive cluster galaxies down to the dwarf galaxy regime. However, the progenitor pathways from which these central MBHs formed remain unclear. Here we report a potentially powerful observational signature of MBH formation in dwarf galaxies.

Kritti Sharma, Koustav Chandra, Archana Pai

Hierarchical mergers in a dense environment are one of the primary formation channels of intermediate-mass black hole (IMBH) binary system. We expect that the resulting massive binary system will exhibit mass asymmetry. The emitted gravitational-wave (GW) carry significant contribution from higher-order modes and hence complex waveform morphology due to supe

Joël Mabillard, Pierre Gaspard

The macroscopic hydrodynamic equations are derived for many-body systems in the local-equilibrium approach, using the Schr\"odinger picture of quantum mechanics. In this approach, statistical operators are defined in terms of microscopic densities associated with the fundamentally conserved quantities and other slow modes possibly emerging from continuous sy

Huan Cao, Chao Zhang, Yun-Feng Huang, Bi-Heng Liu

Entanglement enhanced quantum metrology has been well investigated for beating the standard quantum limit (SQL). However, the metrological advantage of entangled states becomes much more elusive in the presence of noise. Under strictly Markovian dephasing noise, the uncorrelated and maximally entangled states achieve exactly the same measurement precision. H

Brodie J. Norfolk, Christophe Pinte, Josh Calcino, Iain Hammond

Companions at sub-arcsecond separation from young stars are difficult to image. However their presence can be inferred from the perturbations they create in the dust and gas of protoplanetary disks. Here we present a new interpretation of SPHERE polarised observations that reveal the previously detected inner spiral in the disk of HD 100546. The spiral coinc

Chenjie Cao, Xinlin Ren, Yanwei Fu

Feature representation learning is the key recipe for learning-based Multi-View Stereo (MVS). As the common feature extractor of learning-based MVS, vanilla Feature Pyramid Networks (FPNs) suffer from discouraged feature representations for reflection and texture-less areas, which limits the generalization of MVS. Even FPNs worked with pre-trained Convolutio

Roberto D. Pascual-Marqui, Kieko Kochi, Toshihiko Kinoshita

Brain function as measured by multichannel EEG recordings can be described to a high level of accuracy by microstates, characterized as a sequence of time intervals within which the sign invariant normalized scalp electric potential field remains quasi-stable, concatenated by fast transitions. Filtering the EEG has a small effect on the spatial microstate sc

Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang

Recently, graph neural networks (GNNs) have been widely used to develop successful recommender systems. Although powerful, it is very difficult for a GNN-based recommender system to attach tangible explanations of why a specific item ends up in the list of suggestions for a given user. Indeed, explaining GNN-based recommendations is unique, and existing GNN

Johannes Huebschmann

The aim here is to sketch the development of ideas related to brackets and similar concepts: Some purely group theoretical combinatorics due to Ph. Hall led to a proof of the Jacobi identity for the Whitehead product in homotopy theory. Whitehead introduced crossed modules to characterize a second relative homotopy group; guided by combinatorial group theory

Ervin Győri, Zhen He, Zequn Lv, Nika Salia

We determine the maximum number of copies of $K_{s,s}$ in a $C_{2s+2}$-free $n$-vertex graph for all integers $s \ge 2$ and sufficiently large $n$. Moreover, for $s\in\{2,3\}$ and any integer $n$ we obtain the maximum number of cycles of length $2s$ in an $n$-vertex $C_{2s+2}$-free bipartite graph.