April 2023 arXiv papers — page 4

Francesco Bajardi, Salvatore Capozziello

$f(Q)$ symmetric-teleparallel gravity is considered in view of Quantum Cosmology. Specifically, we derive cosmological equations for $f(Q)$ models and then investigate the related energy conditions. In the minisuperspace formalism, the point-like $f(Q)$ Hamiltonian is taken into account. In this framework, we obtain and solve the Wheeler-De Witt equation, th

Mohamed Mabrouk, Ali Zamani

For a positive element $A$ of a $C^*$-algebra $\mathfrak{A}$, let ${\|X\|}_{A}$ denote the $A$-operator semi-norm of $X\in\mathfrak{A}$. In this paper, we aim to introduce and study the notion of $A$-spectrum for $X$ such that ${\|X\|}_{A}<\infty$. In particular when $A$ is well-supported, we establish an $A$-spectral permanence property for $C^*$-algebras.

Elena-Simona Apostol, Ciprian-Octavian Truică

An important topic in medical research is the process of improving the images obtained from medical devices. As a consequence, there is also a need to improve medical image resolution and analysis. Another issue in this field is the large amount of stored medical data [16]. Human brain databases at medical institutes, for example, can accumulate tens of Tera

Xiang Qu, Yi Hu, Wenjie Cai, Yang Xu

Heterogeneous dynamics commonly emerges in anomalous diffusion with intermittent transitions of diffusion states but proves challenging to identify using conventional statistical methods. To effectively capture these transient changes of diffusion states, we propose a deep learning model (U-AnDi) for the semantic segmentation of anomalous diffusion trajector

Liangzu Peng, Paris V. Giampouras, René Vidal

The goal of continual learning is to find a model that solves multiple learning tasks which are presented sequentially to the learner. A key challenge in this setting is that the learner may forget how to solve a previous task when learning a new task, a phenomenon known as catastrophic forgetting. To address this challenge, many practical methods have been

Mirza Kamrul Bashar Shuhan, Syed Md. Hasnayeen, Tanmoy Krishna Das, Md. Nazmus Sakib

Federated Identity Management has proven its worth by offering economic benefits and convenience to Service Providers and users alike. In such federations, the Identity Provider (IdP) is the solitary entity responsible for managing user credentials and generating assertions for the users, who are requesting access to a service provider's resource. This makes

Walter Zimmer, Joseph Birkner, Marcel Brucker, Huu Tung Nguyen

Current multi-modal object detection approaches focus on the vehicle domain and are limited in the perception range and the processing capabilities. Roadside sensor units (RSUs) introduce a new domain for perception systems and leverage altitude to observe traffic. Cameras and LiDARs mounted on gantry bridges increase the perception range and produce a full

Alexander Molyakov

We prove the Hasse principle for a smooth proper model of a geometrically integral non-conical intersection of two quadrics in the projective space of dimension 7 over a number field. This result generalizes the result of Heath-Brown who established the statement in the smooth case. Our argument is built upon the ideas of Colliot-Th\'el\`ene and the fibratio

Yan Kang, Hanlin Gu, Xingxing Tang, Yuanqin He

Conventionally, federated learning aims to optimize a single objective, typically the utility. However, for a federated learning system to be trustworthy, it needs to simultaneously satisfy multiple/many objectives, such as maximizing model performance, minimizing privacy leakage and training cost, and being robust to malicious attacks. Multi-Objective Optim

Farida Enikeeva, Olga Klopp, Mathilde Rousselot

Vector autoregressive (VAR) models are widely used in multivariate time series analysis for describing the short-time dynamics of the data. The reduced-rank VAR models are of particular interest when dealing with high-dimensional and highly correlated time series. Many results for these models are based on the stationarity assumption that does not hold in se

Zhe Zhang, Xiaoyu Song

In this article, we investigate the creep mechanism of clay at the nanoscale. We conduct the molecular dynamics (MD) modeling of clay samples consisting of hexagonal particles under compression and shear. The MD simulations include oedometer creep, shear creep, direct shear tests, and stress relaxation. The numerical results show that the nanoscale creep mec

Norma Susana Mankoc Borstnik

This article presents the description of the internal spaces of fermion and boson fields in $d$-dimensional spaces, with the odd and even "basis vectors" which are the superposition of odd and even products of operators $\gamma^a$. While the Clifford odd "basis vectors" manifest properties of fermion fields, appearing in families, the Clifford even "basis ve

Manal E. Helal, Mohammed E. Helal

Patents provide a rich source of information about design innovations. Patent mining techniques employ various technologies, such as text mining, machine learning, natural language processing, and ontology-building techniques. An automated graph data modelling method is proposed for extracting functional representations for building a semantic database of pa

Paweł Parys, Aleksander Wiącek

We improve the complexity of solving parity games (with priorities in vertices) for $d={\omega}(\log n)$ by a factor of ${\theta}(d^2)$: the best complexity known to date was $O(mdn^{1.45+\log_2(d/\log_2(n))})$, while we obtain $O(mn^{1.45+\log_2(d/\log_2(n))}/d)$, where $n$ is the number of vertices, $m$ is the number of edges, and $d$ is the number of prio

Andrzej Kozlowski, Kohhei Yamaguchi

We continue our study of the topology of the spaces of $m$ tuples of real polynomials with common degree $d$ and without common roots of multiplicity $n$, and in particular their stability properties with respect to $d$. In an earlier paper we have proved a homotopy stability result and determined the stable homotopy types of such spaces in the case $m n >=4

Dmitrii A. Serkov

Let the sets of functions $Z$ and $\Omega$ be given on the time interval $T$, let there also be a multifunction (m/f) $\alpha$ acting from $\Omega$ to $Z$ and a finite set of moments $\Delta$ from $T$. The work deals with two questions: the first one is the connection between the possibility of stepwise construction (specified by $\Delta$) of a value $z$ of

Abel de Burgos, Sergio Simón-Díaz, Miguel A. Urbaneja, Ignacio Negueruela

Blue supergiants (BSGs) are important objects to study the intermediate phases of massive star evolution, helping to constrain evolutionary models. However, the lack of a holistic study of a statistically significant and unbiased sample of these objects makes several long-standing questions about their nature to remain unsolved. The present and other upcomin

Mario Alviano, Francesco Bartoli, Marco Botta, Roberto Esposito

In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a multilayer neural network model. Weighted knowledge bases for a simple description logic with typicality are considered under a (many-valued) ``concept-wise" multipreference semantics. The semantics is used to provid

Gideon Freund, Elad Sarafian, Sarit Kraus

In reinforcement learning and imitation learning, an object of central importance is the state distribution induced by the policy. It plays a crucial role in the policy gradient theorem, and references to it--along with the related state-action distribution--can be found all across the literature. Despite its importance, the state distribution is mostly disc

Yuki Okamoto, Keisuke Imoto, Shinnosuke Takamichi, Ryotaro Nagase

One way of expressing an environmental sound is using vocal imitations, which involve the process of replicating or mimicking the rhythm and pitch of sounds by voice. We can effectively express the features of environmental sounds, such as rhythm and pitch, using vocal imitations, which cannot be expressed by conventional input information, such as sound eve

Fei Liu, Xiaokai Liu, Fang Wang

In this article, we establish the Hopf-Tsuji-Sullivan dichotomy for geodesic flows on certain manifolds with no conjugate points: either the geodesic flow is conservative and ergodic, or it is completely dissipative and non-ergodic. We also show several equivalent conditions to the conservativity, such the Poincar\'e series diverges at the critical exponent,

Shady E Ahmed, Omer San, Sivaramakrishnan Lakshmivarahan, John M Lewis

The four-dimensional variational data assimilation methodology for assimilating noisy observations into a deterministic model has been the workhorse of forecasting centers for over three decades. While this method provides a computationally efficient framework for dynamic data assimilation, it is largely silent on the important question concerning the minimu

Gheorghe Craciun, Abhishek Deshpande, Jiaxin Jin

Polynomial dynamical systems (i.e. dynamical systems with polynomial right hand side) are ubiquitous in applications, especially as models of reaction networks and interaction networks. The properties of general polynomial dynamical systems can be very difficult to analyze, due to nonlinearity, bifurcations, and the possibility for chaotic dynamics. On the o

B. Amrahi, M. Asadi, F. Taghinavaz

We study the butterfly effect and pole-skipping phenomenon for the 1RCBH model which enjoys a critical point in its phase diagram. Using the holographic idea, we compute the butterfly velocity and interestingly find that this velocity can probe the critical behavior of this model. We calculate the dynamical exponent of this quantity near the critical point a

Veronica Arena, Patrick Jefferson, Stephen Obinna

Generalizing the results of 1211.6077 and 1703.00905, we prove a formula for the pushforward of an arbitrary analytic function of the exceptional divisor class of a weighted blowup of an algebraic variety centered at a smooth complete intersection with normal crossing. We check this formula extensively by computing the generating function of intersection num

Xerxes D. Arsiwalla

In this commentary article to 'The Puzzle of Ideography' by Morin, we put forth a new cognitive account of the puzzle of ideography, that complements the standardization account of Morin. Efficient standardization of spoken language is phenomenologically attributed to a modality effect coupled with chunking of cognitive representations, further aided by mult

Jian-Rui Soh, Irián Sánchez-Ramírez, Xupeng Yang, Jinzhao Sun

In the rapidly expanding field of topological materials there is growing interest in systems whose topological electronic band features can be induced or controlled by magnetism. Magnetic Weyl semimetals, which contain linear band crossings near the Fermi level, are of particular interest owing to their exotic charge and spin transport properties. Up to now,

V. Banupriya, S. Anusuya

Diabetic Retinopathy (DR) refers to a barrier that takes place in diabetes mellitus damaging the blood vessel network present in the retina. This may endanger the subjects' vision if they have diabetes. It can take some time to perform a DR diagnosis using color fundus pictures because experienced clinicians are required to identify the tumors in the imagery

Yuheng Li, Mingzhe Hu, Xiaofeng Yang

Colon polyps are considered important precursors for colorectal cancer. Automatic segmentation of colon polyps can significantly reduce the misdiagnosis of colon cancer and improve physician annotation efficiency. While many methods have been proposed for polyp segmentation, training large-scale segmentation networks with limited colonoscopy data remains a c

Keiho Matsumoto

We construct a K-theory version of Bhatt-Morrow-Scholze's Breuil-Kisin cohomology theory for $\sO_K$-linear idempotent-complete, small smooth proper stable infinity-categories, where $K$ is a discretely valued extension of $\Q_p$ with perfect residue field. As a corollary, under the assumption that $K(1)$-local K theory satisfies the K\"unneth formula for $\

Francesca Meneghello, Nicolò Dal Fabbro, Domenico Garlisi, Ilenia Tinnirello

In the last years, several machine learning-based techniques have been proposed to monitor human movements from Wi-Fi channel readings. However, the development of domain-adaptive algorithms that robustly work across different environments is still an open problem, whose solution requires large datasets characterized by strong domain diversity, in terms of e

Alberto Nardin, Iacopo Carusotto

Making use of refermionization techniques, we map the nonlinear chiral Luttinger liquid model of the edge modes of a spatially confined fractional quantum Hall cloud developed in our recent work [Phys. Rev. A 107, 033320 (2023)] onto a one-dimensional system of massive and interacting chiral fermions, whose mass and interactions are set by the filling factor

Cecilia Ka Yuk Chan, Wenjie Hu

This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education, focusing on familiarity, their willingness to engage, potential benefits and challenges, and effective integration. A survey of 399 undergraduate and postgraduate students from various disciplines in Hong Kong revealed a generally

Paweł Wyborski, Michał Gawełczyk, Paweł Podemski, Piotr Andrzej Wroński

Tuning GaAs-based quantum emitters to telecom wavelengths makes it possible to use the existing mature technology for applications in, e.g., long-haul ultra-secure communication in the fiber networks. A promising method re-developed recently is to use a metamorphic InGaAs buffer that redshifts the emission by reducing strain. However, the impact of such a bu

Ole Ossen

We explain how to determine the semistable reduction of a particular plane quartic curve at $p=3$ that appears in the attempts of Rouse, Sutherland, and Zureick-Brown to compute the rational points on the non-split Cartan modular curve $X^+_{ns}(27)$.

Zheng Liu, Fu Zhang

Bundle adjustment (BA) on LiDAR point clouds has been extensively investigated in recent years due to its ability to optimize multiple poses together, resulting in high accuracy and global consistency for point cloud. However, the accuracy and speed of LiDAR bundle adjustment depend on the quality of plane extraction, which provides point association for LiD

Mingyang Wang, Zhenshan Bing, Xiangtong Yao, Shuai Wang

Meta-reinforcement learning enables artificial agents to learn from related training tasks and adapt to new tasks efficiently with minimal interaction data. However, most existing research is still limited to narrow task distributions that are parametric and stationary, and does not consider out-of-distribution tasks during the evaluation, thus, restricting

Vishal Anand, Vivek Narsimhan

This paper examines the rigid body motion of a spheroid sedimenting in a Newtonian fluid with a spatially varying viscosity field. The fluid is at zero Reynolds number, and the viscosity varies linearly in space in an arbitrary direction with respect to the external force. First, we obtain the correction to the spheroid's rigid body motion in the limit of sm

Zhen-Fei Liu

Heterogeneous interfaces are central to many energy-related applications in the nanoscale. From the first-principles electronic structure perspective, one of the outstanding problems is accurately and efficiently calculating how the frontier quasiparticle levels of one component are aligned in energy with those of another at the interface, i.e., the so-calle

Mengjiao Xiao, Achim Stoessl, Brandon Roach, Cory Gerrity

Lithium-drifted silicon [Si(Li)] has been used for decades as an ionizing radiation detector in nuclear, particle, and astrophysical experiments, though such detectors have frequently been limited to small sizes (few cm$^2$) and cryogenic operating temperatures. The 10-cm-diameter Si(Li) detectors developed for the General Antiparticle Spectrometer (GAPS) ba

Yijun Yuan, Andreas Nuchter

Immersive novel view generation is an important technology in the field of graphics and has recently also received attention for operator-based human-robot interaction. However, the involved training is time-consuming, and thus the current test scope is majorly on object capturing. This limits the usage of related models in the robotics community for 3D reco

S. Mart/'inez-Rozas, D. Alejo, F. Caballero, L. Merino

This letter addresses the problem of trajectory planning in a marsupial robotic system consisting of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) through a non-taut tether withcontrollable length. To the best of our knowledge, this is the first method that addresses the trajectory planning of a marsupial UGV-UAV with a non-taut

Cecilia Ka Yuk Chan

This study aims to develop an AI education policy for higher education by examining the perceptions and implications of text generative AI technologies. Data was collected from 457 students and 180 teachers and staff across various disciplines in Hong Kong universities, using both quantitative and qualitative research methods. Based on the findings, the stud

Alireza Abdollahi, Majid Arezoomand, Mahdi Ebrahimi

We study subsets $T$ consisting of some transpositions $(i,j)$ of the symmetric group $S_n$ on $\{1,\dots,n\}$ such that the Cayley graph $\Gamma_T:=Cay(S_n,T)$ is an integral graph, i.e., all eigenvalues of an adjacency matrix of $\Gamma_T$ are integers. Graph properties of $\Gamma_T$ are determined in terms of ones of the graph $G_T$ whose vertex set is $\

Dongsheng Han, Chaoning Zhang, Yu Qiao, Maryam Qamar

Meta AI Research has recently released SAM (Segment Anything Model) which is trained on a large segmentation dataset of over 1 billion masks. As a foundation model in the field of computer vision, SAM (Segment Anything Model) has gained attention for its impressive performance in generic object segmentation. Despite its strong capability in a wide range of z

V K Ojha, Adithya A Rao, S D Pathak

The existence of dark energy is essential to explain the cosmic accelerated expansion. We consider a homogenous interacting tachyonic scalar field as a possible candidate for the dynamical dark energy. The interaction between the tachyonic field and matter can be gauged to be linear in the energy density of matter (or the tachyonic field) and Hubble's parame

Yuefeng Yang, Qing Zeng, Kaishun Wang

Weakly distance-regular digraphs are a natural directed version of distance-regular graphs. In [8], the third author and Suzuki proposed a question when an orientation of a distance-regular graph defines a weakly distance-regular digraph. In this paper, we initiate this project, and classify all commutative weakly distance-regular digraphs whose underlying g

Pei Zhang, Yanli Wang, Zhennan Zhou

In this work, we consider the Fokker-Planck equation of the Nonlinear Noisy Leaky Integrate-and-Fire (NNLIF) model for neuron networks. Due to the firing events of neurons at the microscopic level, this Fokker-Planck equation contains dynamic boundary conditions involving specific internal points. To efficiently solve this problem and explore the properties

Jiacheng Ge, Yao Gu, Zhongzhen Yao, Sinan Liu

Fe-based metallic glasses are promising functional materials for advanced magnetism and sensor fields. Tailoring magnetic performance in amorphous materials requires a thorough knowledge of the correlation between structural disorder and magnetic order, which remains ambiguous. Two practical difficulties remain: the first is directly observing subtle magneti

Fei Wen, Wei Wang, Zeyu Yan, Wenbin Jiang

Optimal transport (OT) has recently been shown as a promising criterion for unsupervised restoration when no explicit prior model is available. Despite its theoretical appeal, OT still significantly falls short of supervised methods on challenging tasks such as super-resolution, deraining, and dehazing. In this paper, we propose a \emph{sparsity-aware optima

Guido Boccali, Bojana Femić, Andrea Laretto, Fosco Loregian

We study the semibicategory $\textsf{Mre}$ of "Moore automata": an arrangement of objects, 1- and 2-cells which is inherently and irredeemably nonunital in dimension one. Between the semibicategory of Moore automata and the better behaved bicategory $\textsf{Mly}$ of "Mealy automata" a plethora of adjunctions insist: the well-known essential equivalence betw

Pooja Verma, Madhubani Mukherjee, Achintya Kumar Dutta

We have investigated the impact of microsolvation on the shape resonance states of nucleobases, taking cytosine as a case study. To characterize the resonance position and decay width of the metastable states, we employed the newly developed DLPNO-based EA-EOMCCSD method in conjunction with resonance via Pad\'e approximation. Our calculations show that the p

Muqing Cao, Kun Cao, Shenghai Yuan, Kangcheng Liu

Path planning for multiple tethered robots is a challenging problem due to the complex interactions among the cables and the possibility of severe entanglements. Previous works on this problem either consider idealistic cable models or provide no guarantee for entanglement-free paths. In this work, we present a new approach to address this problem using the

Dongmei Wei, Hailing Liu, Yongmei Li, Fei Gao

The Time-Fractional Schr\"odinger Equation (TFSE) is well-adjusted to study a quantum system interacting with its dissipative environment. The Quantum Speed Limit (QSL) time captures the shortest time required for a quantum system to evolve between two states, which is significant for evaluating the maximum speed in quantum processes. In this work, we solve

Oleg Nivievskyi, Roman Neyter, Olha Halytsia, Pavlo Martyshev

Exempting soybean and rapeseed exporters from VAT has a negative effect on the economy of $\$$44.5-60.5 million per year. The implemented policy aimed to increase the processing of soybeans and rapeseed by Ukrainian plants. As a result, the processors received $\$$26 million and the state budget gained $\$$2-18 million. However, soybean farmers, mostly small

Philip Tureček

Given a non-negative integer $n$, we establish a formula for the number of finite magmas on a set with cardinality $n$ up to isomorphism. We then generalize the method to operations with arbitrary finite arity, which yields a corrected version of Harrison's formula. Moreover, we present the cycle index as a helpful tool for practical computations and, based

Frode K. Hansen, Ezequiel F. Boero, Heliana E. Luparello, Diego Garcia Lambas

In Luparello et al. 2023, a new and hitherto unknown CMB foreground was detected. A systematic decrease in Cosmic Microwave Background (CMB) temperatures around nearby large spiral galaxies points to an unknown interaction with CMB photons in a sphere up to several projected Mpc around these galaxies. We investigate to which extent this foreground may impact

Ting-Feng Gong, Jie Jiang, Ming Zhang

We provide mass/energy formulas for the extended thermodynamics, mixed thermodynamics, and holographic conformal field theory (CFT) thermodynamics for the charged and rotating Kerr-Newman Anti-de Sitter black holes. Then for the CFT thermal states dual to the black hole, we find the first-order phase transitions and criticality phenomena in the canonical ens

Oleg Nivievskyi, Pavlo Iavorskyi, Oleksandr Donchenko

The Ministry of Economy has an interest and demand in exploring how to increase the set of [legally registered] small family farmers in Ukraine and to examine more in details measures that could reduce the scale of the shadow agricultural market in Ukraine. Building upon the above political economy background and demand, we will be undertaking the analysis a

Oleg Nivievskyi, Pavlo Martyshev, Sergiy Kvasha

Building upon the theory and methodology of agricultural policy developed in the previous chapter, in Chapter 2 we analyse and assess agricultural policy making in Ukraine since the breakup of Soviet Union till today. Going from top down to the bottom, we begin by describing the evolution of state policy in the agri-food sector. In the beginning, we describe

Anwar Sadad, Muazzam A. Khan, Baraq Ghaleb, Fadia Ali Khan

Blockchain (BC) and Information for Operational and Tactical Analysis (IOTA) are distributed ledgers that record a huge number of transactions in multiple places at the same time using decentralized databases. Both BC and IOTA facilitate Internet-of-Things (IoT) by overcoming the issues related to traditional centralized systems, such as privacy, security, r

Omair Faraj, David Megías, Joaquin Garcia-Alfaro

The Internet of Things (IoT) is integrating the Internet and smart devices in almost every domain such as home automation, e-healthcare systems, vehicular networks, industrial control and military applications. In these sectors, sensory data, which is collected from multiple sources and managed through intermediate processing by multiple nodes, is used for d

Alisher Duspayev, Georg Raithel

We report a measurement of the hyperfine-structure constants of the $^{85}$Rb 4$D_{3/2}$ state using a two-photon 5$S_{1/2}\rightarrow$4$D_{3/2}$ transition. The hyperfine transitions are probed by measuring the transmission of the low-power 795-nm lower-stage laser beam through a cold-atom sample as a function of 795-nm laser frequency, with the frequency o

Xinyu Lin, Yingjie Zhou, Yipeng Liu, Ce Zhu

An image line segment is a fundamental low-level visual feature that delineates straight, slender, and uninterrupted portions of objects and scenarios within images. Detection and description of line segments lay the basis for numerous vision tasks. Although many studies have aimed to detect and describe line segments, a comprehensive review is lacking, obst

Hans Marin Florez, Tadas Pyragius, Thomas Fernholz

We present results of stroboscopic microwave spectroscopy of radio-frequency dressed optically pumped magnetometer. Interaction between radio-frequency dressed atoms and a synchronously pulsed microwave field followed by Voigt effect-based optical probing allows us to perform partial state tomography and assess the efficiency of the state preparation process

Xiao Liu, Jian Zhang, Heng Zhang, Fuzhao Xue

Compared with standard text, understanding dialogue is more challenging for machines as the dynamic and unexpected semantic changes in each turn. To model such inconsistent semantics, we propose a simple but effective Hierarchical Dialogue Understanding model, HiDialog. Specifically, we first insert multiple special tokens into a dialogue and propose the tur

Kewei Zhu, Sibo Cheng, Nina Kovalchuk, Mark Simmons

Predicting drop coalescence based on process parameters is crucial for experiment design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bottleneck by training the predictive mode

Kamaryn Tanner, Ruth H. Keogh, Carol A. C. Coupland, Julia Hippisley-Cox

Over time, the performance of clinical prediction models may deteriorate due to changes in clinical management, data quality, disease risk and/or patient mix. Such prediction models must be updated in order to remain useful. Here, we investigate methods for discrete and dynamic model updating of clinical survival prediction models based on refitting, recalib

Sergii Parchenko, Davide Pecchio, Ritwik Mondal, Peter M. Oppeneer

We investigate the impact of non-collinear dual optical excitation on the magnetization precession in a permalloy thin film using two ultrashort laser pulses. By analyzing the magnetization dynamics using time-resolved magneto-optical methods, we find that the excitation with two ultrashort optical pulses introduces a long-lasting modification of the electro

Khalid A. Alobaid, Jason T. L. Wang

The Sun constantly releases radiation and plasma into the heliosphere. Sporadically, the Sun launches solar eruptions such as flares and coronal mass ejections (CMEs). CMEs carry away a huge amount of mass and magnetic flux with them. An Earth-directed CME can cause serious consequences to the human system. It can destroy power grids/pipelines, satellites, a

Ayan Gupta, Mayank Dixit, Vipul Kumar Mishra, Attulya Singh

A brain tumor, whether benign or malignant, can potentially be life threatening and requires painstaking efforts in order to identify the type, origin and location, let alone cure one. Manual segmentation by medical specialists can be time-consuming, which calls out for the involvement of technology to hasten the process with high accuracy. For the purpose o

Amin A. Nizami, Ankit W. Shrestha

Krylov complexity is an important dynamical quantity with relevance to the study of operator growth and quantum chaos, and has recently been much studied for various time-independent systems. We initiate the study of K-complexity in time-dependent (driven) quantum systems. For periodic time-dependent (Floquet) systems, we develop a natural method for doing t

Ameneh Maghsoodi, Mohand O. Saed, Eugene M. Terentjev, Kaushik Bhattacharya

Polydomain liquid crystalline (nematic) elastomers have highly unusual mechanical properties, dominated by the dramatically non-linear stress-strain response that reflects stress-induced evolution of domain patterns. Here, we study the classical Hertz indentation problem in such a material. Experimentally, we find that polydomain nematic elastomers display a

Liangyu Zhang, Yang Peng, Wenhao Yang, Zhihua Zhang

We propose a novel generalization of constrained Markov decision processes (CMDPs) that we call the \emph{semi-infinitely constrained Markov decision process} (SICMDP). Particularly, we consider a continuum of constraints instead of a finite number of constraints as in the case of ordinary CMDPs. We also devise two reinforcement learning algorithms for SICMD

Linjie Liu, Xiaojie Chen, Attila Szolnoki

Human society and natural environment form a complex giant ecosystem, where human activities not only lead to the change of environmental states, but also react to them. By using collective-risk social dilemma game, some studies have already revealed that individual contributions and the risk of future losses are inextricably linked. These works, however, of

Hao Feng, Cláudio Gomes, Peter Gorm Larsen

A digital twin (DT) monitors states of the physical twin (PT) counterpart and provides a number of benefits such as advanced visualizations, fault detection capabilities, and reduced maintenance cost. It is the ability to be able to detect the states inside the DT that enable such benefits. In order to estimate the desired states of a PT, we propose the use

Venus Rai, Anne Stunault, Wolfgang Schmidt, Subhadip Jana

Me$_{3+\delta}$Ge, being a Weyl semimetal, shows a large anomalous Hall effect (AHE), which decreases slowly with an increase in $\delta$ from 0.1 to 0.4. However, AHE in this compound remains significantly large in the whole range of $\delta$ because of the robust nature of the topology of bands. To explore the possibility of tuning the anomalous transport

Jianfeng Ning, Fuqun Han, Jun Zou

In this work, we focus on the inverse medium scattering problem (IMSP), which aims to recover unknown scatterers based on measured scattered data. Motivated by the efficient direct sampling method (DSM) introduced in [23], we propose a novel direct sampling-based deep learning approach (DSM-DL)for reconstructing inhomogeneous scatterers. In particular, we us

Alexandros Papadopoulos, Anastasios Delopoulos

Data-driven approaches for remote detection of Parkinson's Disease and its motor symptoms have proliferated in recent years, owing to the potential clinical benefits of early diagnosis. The holy grail of such approaches is the free-living scenario, in which data are collected continuously and unobtrusively during every day life. However, obtaining fine-grain

Jérôme Buzzi, Nishant Chandgotia, Matthew Foreman, Su Gao

This file is composed of questions that emerged or were of interest during the workshop "Interactions between Descriptive Set Theory and Smooth Dynamics" that took place in Banff, Canada on 2022.

Tadashi Okazaki, Douglas J. Smith

We propose confining dualities of $\mathcal{N}=(0,2)$ half-BPS boundary conditions in 3d $\mathcal{N}=2$ supersymmetric $SU(N)$, $USp(2n)$ and $SO(N)$ gauge theories. Some of these dualities have the novel feature that one (anti)fundamental chiral has Dirichlet boundary condition while the rest have Neumann boundary conditions. While some of the dualities ca

Michel Dekking, Karoly Simon, Balazs Szekely, Nora Szekeres

Can we find a self-similar set on the line with positive Lebesgue measure and empty interior? Currently, we do not have the answer for this question for deterministic self-similar sets. In this paper we answer this question negatively for random self-similar sets which are defined with the construction introduced in the paper Jordan, Pollicott and Simon (Com

Rian Dolphin, Barry Smyth, Ruihai Dong

The financial domain has proven to be a fertile source of challenging machine learning problems across a variety of tasks including prediction, clustering, and classification. Researchers can access an abundance of time-series data and even modest performance improvements can be translated into significant additional value. In this work, we consider the use

Ananya Jana, Aniruddha Maiti, Dimitris N. Metaxas

Tooth segmentation from intraoral scans is a crucial part of digital dentistry. Many Deep Learning based tooth segmentation algorithms have been developed for this task. In most of the cases, high accuracy has been achieved, although, most of the available tooth segmentation techniques make an implicit restrictive assumption of full jaw model and they report

J. Arenz, M. R. Zirnbauer

Assuming the self-consistent theory of localization due to Abou-Chacra et al., we solve the N=1 Wegner model in the regime of strong disorder and high dimension. In the process, we uncover a non-standard electronic phase with spontaneously broken U(1) symmetry -- the missing field-theory basis underlying phenomena associated with fractal eigenstates and sing

Shivani Yadav, Dipanjan Gope, Uma Maheswari K., Prasanta Kumar Ghosh

Asthma is one of the chronic inflammatory diseases of the airways, which causes chest tightness, wheezing, breathlessness, and cough. Spirometry is an effort-dependent test used to monitor and diagnose lung conditions like Asthma. Vocal breath sound (VBS) based analysis can be an alternative to spirometry as VBS characteristics change depending on the lung c

Joey Huchette, Gonzalo Muñoz, Thiago Serra, Calvin Tsay

In the past decade, deep learning became the prevalent methodology for predictive modeling thanks to the remarkable accuracy of deep neural networks in tasks such as computer vision and natural language processing. Meanwhile, the structure of neural networks converged back to simpler representations based on piecewise constant and piecewise linear functions

Pieter van Dokkum

This Research Note presents VLT B-band imaging of a candidate runaway supermassive black hole that was recently discovered in HST/ACS F606W+F814W imaging. The ACS data show an extremely thin, linear feature at z=0.964 that points toward a compact galaxy at the same redshift. There is a gap between the feature and the compact galaxy, which means that the prop

Abdulsalam Aji Suleiman, Amir Parsi, Mohammadali Razeghi, Uğur Başçı

Superionic conductors offer unique advantages for novel technological devices in various fields, such as energy storage and neuromorphic computing. Above 414 K, Cu2Se turns into a well-known superionic conductor via a phase transition, and it is demonstrated to exhibit peculiar electrical and thermoelectric properties in bulk. Here, we report a large-area sy

Fahad Maqbool, Muhammad Saad Razzaq, Hajira Jabeen

Genetic Algorithm (GA) is a popular meta-heuristic evolutionary algorithm that uses stochastic operators to find optimal solution and has proved its effectiveness in solving many complex optimization problems (such as classification, optimization, and scheduling). However, despite its performance, popularity and simplicity, not much attention has been paid t

Markus Fröb, William C. C. Lima, Albert Much, Kyriakos Papadopoulos

We show that a non-commutative structure arises naturally from perturbative quantum gravity in a de Sitter background metric. Our work builds on recent advances in the construction of observables in highly symmetric background spacetimes [Brunetti et al., JHEP 08, 032 (2016); Fr\"ob and Lima, Class. Quant. Grav. 35, 095010 (2018)], where the dynamical coordi

Mohammad Fraiwan, Natheer Khasawneh

ChatGPT is a type of artificial intelligence language model that uses deep learning algorithms to generate human-like responses to text-based prompts. The introduction of the latest ChatGPT version in November of 2022 has caused shockwaves in the industrial and academic communities for its powerful capabilities, plethora of possible applications, and the gre

Giorgio Krstulovic, Marc E. Brachet

In this work we first briefly review some of the mutual friction effects on vortex lines and rings that were obtained in the context of the truncated Gross-Pitaevskii equation in references Krstulovic \& Brachet [Phys.~Rev.~E \textbf{83}(6), 066311 and Phys.~Rev.~B \textbf{83}132506 (2011)], with particular attention to the anomalous slowdown of rings produc

Shallu Sharma, Pooja Saproo, Naresh Digra, Iqbal Kour

The main aspect of this paper is to introduce a new generalisation of nano open sets namely, nano h-open sets. These newly generalised sets serve as the foundation for the definition of nano h-continuous functions and some results involving their characterizations are established. Furthermore, the notion of nano h-open functions, nano h-irresolute functions,

Johannes Gedeon, Emadeldeen Hassan, Antonio Calà Lesina

In the last decades nanostructures have unlocked myriads of functionalities in nanophotonics by engineering light-matter interaction beyond what is possible with conventional bulk optics. The space of parameters available for design is practically unlimited due to the large variety of optical materials and geometries that can be realized by nanofabrication t

Anamaria Mojica-Hanke

Nowadays, machine learning (ML) is being used in software systems with multiple application fields, from medicine to software engineering (SE). On the one hand, the popularity of ML in the industry can be seen in the statistics showing its growth and adoption. On the other hand, its popularity can also be seen in research, particularly in SE, where not only

Bernd Hofmann, Chantal Klinkhammer, Robert Plato

In this article on variational regularization for ill-posed nonlinear problems, we are once again discussing the consequences of an oversmoothing penalty term. This means in our model that the searched-for solution of the considered nonlinear operator equation does not belong to the domain of definition of the penalty functional. In the past years, such vari

Arunoday Sarkar, Buddhadeb Ghosh

In the present paper, we perform a sub-Planckian quantum mode analysis of linear cosmological perturbation in the inflaton field over a classical quasi de-Siter metric background by dynamical horizon exit (DHE) method. In this way, we probe the inflationary regime of a quintessential $\alpha$-attractor model by analysing the COBE/Planck normalized power spec

Jeremy Cleeman, Kian Agrawala, Rajiv Malhotra

Machine Learning (ML) is of increasing interest for modeling parametric effects in manufacturing processes. But this approach is limited to established processes for which a deep physics-based understanding has been developed over time, since state-of-the-art approaches focus on reducing the experimental and/or computational costs of generating the training

Fernández Eduardo, Février Simon, Lacroix Martin, Boman Romain

Since the seminal work of Idelsohn, O\~nate and Del-Pin (2004), the Particle Finite Element Method (PFEM) has relied on a Delaunay triangulation and the Alpha--Shape (AS) algorithm in the remeshing process. This approach guarantees a good quality of the Lagrangian mesh, but introduces a list of shortcomings that demand geometrical treatments tailored to each