July 2023 arXiv papers — page 52

Jesse Chan, Khemraj Shukla, Xinhui Wu, Ruofeng Liu

High order schemes are known to be unstable in the presence of shock discontinuities or under-resolved solution features for nonlinear conservation laws. Entropy stable schemes address this instability by ensuring that physically relevant solutions satisfy a semi-discrete entropy inequality independently of discretization parameters. This work extends high o

Kamal Das, Koushik Ghorai, Dimitrie Culcer, Amit Agarwal

The valley Hall effect arises from valley contrasting Berry curvature and requires inversion symmetry breaking. Here, we propose a nonlinear mechanism to generate a valley Hall current in systems with both inversion and time-reversal symmetry, where the linear and second-order charge Hall currents vanish along with the linear valley Hall current. We show tha

Shiheng Wang

Counterfactual Regret Minimization(CFR) has shown its success in Texas Hold'em poker. We apply this algorithm to another popular incomplete information game, Mahjong. Compared to the poker game, Mahjong is much more complex with many variants. We study two-player Mahjong by conducting game theoretical analysis and making a hierarchical abstraction to CFR bas

Cristina Draper Fontanals

A new highly symmetrical model of the compact Lie algebra $\mathfrak{g}^c_2$ is provided as a twisted ring group for the group $\mathbb{Z}_2^3$ and the ring $\mathbb{R}\oplus\mathbb{R}$. The model is self-contained and can be used without previous knowledge on roots, derivations on octonions or cross products. In particular, it provides an orthogonal basis w

Michael Bersudsky, Hao Xing

We study the limiting distribution of dense orbits of a lattice subgroup $\Gamma\le \text{SL}(m+1,\mathbb{R})$ acting on $H\backslash\text{SL}(m+1,\mathbb{R})$, with respect to a filtration of growing norm balls. The novelty of our work is that the groups $H$ we consider have infinitely many non-trivial connected components. For a specific such $H$, the homo

Hao Tang, Guolei Sun, Nicu Sebe, Luc Van Gool

We propose a novel ECGAN for the challenging semantic image synthesis task. Although considerable improvements have been achieved by the community in the recent period, the quality of synthesized images is far from satisfactory due to three largely unresolved challenges. 1) The semantic labels do not provide detailed structural information, making it challen

Kamyar Dobakhti, Jafar Ghazanfarian

The real power of artificial intelligence appears in reinforcement learning, which is computationally and physically more sophisticated due to its dynamic nature. Rotation and injection are some of the proven ways in active flow control for drag reduction on blunt bodies. In this paper, rotation will be added to the cylinder alongside the deep reinforcement

Mehdi Letafati, Safa Otoum

Metaverse-enabled digital healthcare systems are expected to exploit an unprecedented amount of personal health data, while ensuring that sensitive or private information of individuals are not disclosed. Machine learning and artificial intelligence (ML/AI) techniques can be widely utilized in metaverse healthcare systems, such as virtual clinics and intelli

Siyuan Jin, Mianmian Zhang, Yekai Guo, Yuejiang He

Software code quality is a construct with three dimensions: maintainability, reliability, and functionality. Although many firms have incorporated code quality metrics in their operations, evaluating these metrics still lacks consistent standards. We categorized distinct metrics into two types: 1) monotonic metrics that consistently influence code quality; a

Marco De Bortoli, Lukáš Chrpa, Martin Gebser, Gerald Steinbauer-Wagner

Temporal planning is an extension of classical planning involving concurrent execution of actions and alignment with temporal constraints. Durative actions along with invariants allow for modeling domains in which multiple agents operate in parallel on shared resources. Hence, it is often important to avoid resource conflicts, where temporal constraints esta

Lorenzo Giombi, Mark Hindmarsh

We use a full general relativistic framework to study the self-similar expansion of bubbles of the stable phase into a flat Friedmann-Lema\^itre-Robertson-Walker Universe in a first order phase transition in the early Universe. With a simple linear barotropic equation of state in both phases, and in the limit of a phase boundary of negligible width, we find

Mehdi Letafati, Safa Otoum

In this article, we study the privacy and security aspects of the metaverse in the context of digital healthcare. Our studies include the security aspects of data collection and communications for access to the metaverse, the privacy and security threats of employing Machine Learning and Artificial Intelligence (AI/ML) algorithms for metaverse healthcare, an

Jitendra Pal, Sourav Roychowdhury, Arindam Lala, Dibakar Roychowdhury

We study integrability and non-integrability for marginal deformations of 4d $\mathcal N =2$ SCFTs. We estimate various chaos indicators for the bulk theory which clearly shows the onset of a chaotic string dynamics in the limit of large deformations. On the other hand, for small values of the deformation parameter, the resulting dynamics exhibits a non-chao

Shiraz Khan, Inseok Hwang

A practical challenge which arises in the operation of sensor networks is the presence of sensor faults, biases, or adversarial attacks, which can lead to significant errors incurring in the localization of the agents, thereby undermining the security and performance of the network. We consider the problem of identifying and correcting the localization error

Xiaofan Guo, Xinpeng Li

In this paper, we introduce a fundamental model for independent and identically distributed sequence with model uncertainty on the canonical space $(\mathbb{R}^\mathbb{N},\mathcal{B}(\mathbb{R}^\mathbb{N}))$ via probability kernels. Thanks to the well-defined upper and lower variances, we obtain a new functional central limit theorem with mean-uncertainty on

Vladimir A. Sablikov, Aleksei A. Sukhanov

We study quasi-bound states of two electrons that arise in two-dimensional materials with a Mexican-hat dispersion (MHD) at an energy above its central maximum. The width of the resonance of the local density of states created by pairs is determined by the hybridization of atomic orbitals, due to which the MHD is formed. The mechanism of the quasi-bound stat

Sofia Yfantidou, Marios Constantinides, Dimitris Spathis, Athena Vakali

This paper explores the intersection of Artificial Intelligence and Machine Learning (AI/ML) fairness and mobile human-computer interaction (MobileHCI). Through a comprehensive analysis of MobileHCI proceedings published between 2017 and 2022, we first aim to understand the current state of algorithmic fairness in the community. By manually analyzing 90 pape

Dexin Wang, Faliang Chang, Chunsheng Liu

Manipulating objects without grasping them enables more complex tasks, known as non-prehensile manipulation. Most previous methods only learn one manipulation skill, such as reach or push, and cannot achieve flexible object manipulation.In this work, we introduce MRLM, a Multi-stage Reinforcement Learning approach for non-prehensile Manipulation of objects.M

Dhanyamol Antony, L. Sunil Chandran, Ankit Gayen, Shirish Gosavi

Domination and coloring are two classic problems in graph theory. The major focus of this paper is the CD-COLORING problem which combines the flavours of domination and colouring. Let $G$ be an undirected graph. A proper vertex coloring of $G$ is a $cd-coloring$ if each color class has a dominating vertex in $G$. The minimum integer $k$ for which there exist

P. Sivakumar, R. M. Madhusudhan, R. Muthucumaraswamy, A. Ramamoorthy

The fluid flow across an unbounded horizontal plate embedded with uniform mass diffusion is studied in this article together with the impacts of the chemical reaction and parabolic motion, while the temperature and concentration of the plate remain constant. Using initial and boundary conditions, partial differential equations were used to describe this phen

Théo Hennequin, Manoel Manghi, Adrien Noury, Francois Henn

In recent experiments, unprecedentedly large values for the conductivity of electrolytes through carbon nanotubes (CNTs) have been measured, possibly owing to flow slip and a high pore surface charge density whose origin is still unknown. By accounting for the coupling between the {quantum} CNT and the {classical} electrolyte-filled pore capacitances, we stu

Linchao He, Hongyu Yan, Mengting Luo, Hongjie Wu

Diffusion models have recently been recognised as efficient inverse problem solvers due to their ability to produce high-quality reconstruction results without relying on pairwise data training. Existing diffusion-based solvers utilize Gradient Descent strategy to get a optimal sample solution. However, these solvers only calculate the current gradient and h

Chang Chen, Ce Meng, Zhiguang Xiao, Han-Qing Zheng

Recently LHCb experimental group find an exotic state $T^+_{cc}$ from the process $p\bar{p} \to D^0D^0\pi^+ + X$. A key question is if it is just a molecule or may have confined tetraquark ingredient. To investigate this, different methods are taken, including two channel ($D^{*+}D^0$ and $D^{*0}D^+$) K-matrix unitarization and single channel Flatt\'e-like p

Ayush K Gupta, Sourabh Manna, Rajdeep Singh Rawat, Rohit Medwal

Spin Hall nano oscillators (SHNOs) have shown applications in unconventional computing schemes and broadband frequency generation in the presence of applied external magnetic field. However, under field-free conditions, the oscillation characteristics of SHNOs display a significant dependence on the effective field, which can be tuned by adjusting the constr

Roman Shapovalov, Yanir Kleiman, Ignacio Rocco, David Novotny

We introduce Replay, a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with several static cameras, as well as wearable action cameras, and recorded with a large array of microphones at different positions in the room. Overall, the dataset contains over 40

Gianluca Faraco, Subhojoy Gupta

We show that the Simple Loop Conjecture holds for any representation $\rho\colon\pi_1(S)\longrightarrow \text{PSL}(2,\,\mathbb R)$ that is discrete but not faithful. That is, we show the existence of a simple closed curve in the kernel of such a representation.

Jia Li, Yanhao Wang, Arpit Merchant

Normalized-cut graph partitioning aims to divide the set of nodes in a graph into $k$ disjoint clusters to minimize the fraction of the total edges between any cluster and all other clusters. In this paper, we consider a fair variant of the partitioning problem wherein nodes are characterized by a categorical sensitive attribute (e.g., gender or race) indica

Kristian Patrick, Qinghong Yang, Dong E. Liu

Many-body localized systems exhibit a unique characteristic of avoiding thermalization, primarily attributed to the presence of a local disorder potential in the Hamiltonian. In recent years there has been an interest in simulating these systems on quantum devices. However, actual quantum devices are subject to unavoidable decoherence that can be modeled as

Qingyang Zhang, Yiming Yang, Jingqing Ruan, Xuantang Xiong

Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) is a promising paradigm to address the exploration-exploitation dilemma in reinforcement learning. It decomposes the source task into subgoal conditional subtasks and conducts exploration and exploitation in the subgoal space. The effectiveness of GCHRL heavily relies on subgoal representation func

Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu

Deploying reinforcement learning (RL) systems requires robustness to uncertainty and model misspecification, yet prior robust RL methods typically only study noise introduced independently across time. However, practical sources of uncertainty are usually coupled across time. We formally introduce temporally-coupled perturbations, presenting a novel challeng

K. B. Alkalaev, Semyon Mandrygin

Using the shadow formalism we find global conformal blocks of torus CFT$_2$. It is shown that $n$-point torus blocks in the ``necklace'' channel (a loop with $n$ legs) are expressed in terms of a hypergeometric-type function which we refer to as the necklace function.

Jenny Ottmann, Üsame Cengiz, Frank Breitinger, Felix Freiling

Memory dumps that are acquired while the system is running often contain inconsistencies like page smearing which hamper the analysis. One possibility to avoid inconsistencies is to pause the system during the acquisition and take an instantaneous memory dump. While this is possible for virtual machines, most systems cannot be frozen and thus the ideal dump

Chun-Hee Lee, Dong-oh Kang, Hwa Jeon Song

Knowledge graphs can be used in many areas related to data semantics such as question-answering systems, knowledge based systems. However, the currently constructed knowledge graphs need to be complemented for better knowledge in terms of relations. It is called knowledge graph completion. To add new relations to the existing knowledge graph by using knowled

Yicong Li, Junbin Xiao, Chun Feng, Xiang Wang

This paper strives to solve complex video question answering (VideoQA) which features long video containing multiple objects and events at different time. To tackle the challenge, we highlight the importance of identifying question-critical temporal moments and spatial objects from the vast amount of video content. Towards this, we propose a Spatio-Temporal

Jonas R. B. Arenhart, Raoni W. Arroyo

Ever since its beginnings, standard quantum mechanics has been associated with a metaphysical view according to which the theory deals with non-individual objects, i.e., objects deprived of individuality in some sense of the term. We shall examine the grounds of the claim according to which quantum mechanics is so closely connected with a metaphysics of non-

Yihang Ding, Xiaoyu Ji, Lixian Zhang, Yifei Dong

This paper concentrates on the development of Chat-PM, a class of composite hybrid aerial/terrestrial manipulator, in concern with composite configuration design, dynamics modeling, motion control and force estimation. Compared with existing aerial or terrestrial mobile manipulators, Chat-PM demonstrates advantages in terms of reachability, energy efficiency

Ahcene Ghandriche, Mourad Sini

The original Calder\'on problem consists in recovering the potential (or the conductivity) from the knowledge of the related Neumann to Dirichlet map (or Dirichlet to Neumann map). Here, we first perturb the medium by injecting small-scaled and highly heterogeneous particles. Such particles can be bubbles or droplets in acoustics or nanoparticles in electrom

Antonio Lei

Given an elliptic curve defined over a number field $F$, we study the algebraic structure and prove a control theorem for Wuthrich's fine Mordell--Weil groups over a $\mathbb{Z}_p$-extension of $F$, generalizing results of Lee on the usual Mordell--Weil groups. In the case where $F=\mathbb{Q}$, we show that the characteristic ideal of the Pontryagin dual of

Antonio Lei

Let $p\ge5$ be a prime number. Let $E/\mathbb{Q}$ be an elliptic curve with complex multiplication by an imaginary quadratic field $K$ such that $p$ is inert in $K$ and that $E$ has good reduction at $p$. Let $K_\infty$ be the anticyclotomic $\mathbb{Z}_p$-extension of $K$. Agboola--Howard defined Kobayashi-type signed Selmer groups of $E$ over $K_\infty$ an

Mallikarjun Reddy Dorsala, V. N. Sastry, Sudhakar Chapram

With the rapid development of cloud computing, vast amounts of duplicated data are being uploaded to the cloud, wasting storage resources. Deduplication (dedup) is an efficient solution to save storage costs of cloud storage providers (CSPs) by storing only one copy of the uploaded data. However, cloud users do not benefit directly from dedup and may be relu

Georg Gottlob, Marco Manna, Cinzia Marte

Existential rules form an expressive Datalog-based language to specify ontological knowledge. The presence of existential quantification in rule-heads, however, makes the main reasoning tasks undecidable. To overcome this limitation, in the last two decades, a number of classes of existential rules guaranteeing the decidability of query answering have been p

Fábio Nascimento de Sousa, Divino Eliaquino, Fabrício Morais de Vasconcelos e Eduardo Costa Girão

We use first principles simulations to investigate the electronic properties of a set of carbon nanocages with a bipartite structure. These nanocages are exclusively formed by hexagonal and tetragonal rings and we show they feature frontier states with particular symmetries as dictated by well defined rules based on the size of the structure. We also show th

Cheng Wen, Baosheng Yu, Rao Fu, Dacheng Tao

A generative model for high-fidelity point clouds is of great importance in synthesizing 3d environments for applications such as autonomous driving and robotics. Despite the recent success of deep generative models for 2d images, it is non-trivial to generate 3d point clouds without a comprehensive understanding of both local and global geometric structures

Batu Güneysu, Kazuhiro Kuwae

We consider the Kato and the Dynkin class and their local counterparts on a smooth Riemannian manifold as Fr\'{e}chet spaces. Based on recent results by Carron, Mondello and Tewodrose we show that for a Riemannian manifold $(X,g)$ of dimension $m\geq 2$ with spectral negative part $\sigma^-_g$ of the Ricci curvature in $L^q_{\phi_g}(X,g)+L^\infty(X,g)$ for s

Eden Schirman, Cong Ling, Florian Mintert

The advent of quantum computing necessitates the transition of worldwide cryptosystems to post-quantum cryptography (PQC), which is founded upon the problem of finding short vectors in high-dimensional structured lattices. It is assumed that the structure of these lattices cannot be exploited by quantum or classical algorithms attempting to find short vector

Jaromir Tosiek, Luca Campobasso

A quantum phase space version of the continuity equation for systems with internal degrees of freedom is derived. The $1$ -- D Dirac equation is introduced and its phase space counterpart is found. The phase space representation of free motion and of scattering in a nonrelativistic and relativistic case for setups with internal degrees of freedom is discusse

Long Bai, Mobarakol Islam, Hongliang Ren

The visual-question localized-answering (VQLA) system can serve as a knowledgeable assistant in surgical education. Except for providing text-based answers, the VQLA system can highlight the interested region for better surgical scene understanding. However, deep neural networks (DNNs) suffer from catastrophic forgetting when learning new knowledge. Specific

Awadelrahman M. A. Ahmed

This article presents an experiment focused on optimizing the MLOps (Machine Learning Operations) process, a crucial aspect of efficiently implementing machine learning projects. The objective is to identify patterns and insights to enhance the MLOps workflow, considering its iterative and interdependent nature in real-world model development scenarios. The

Romain Lacombe, Andrew Gaut, Jeff He, David Lüdeke

Deep learning in computational biochemistry has traditionally focused on molecular graphs neural representations; however, recent advances in language models highlight how much scientific knowledge is encoded in text. To bridge these two modalities, we investigate how molecular property information can be transferred from natural language to graph representa

Giacomo Albi, Federica Ferrarese

In this paper, we present a model describing the collective motion of birds. The model introduces spontaneous changes in direction which are initialized by few agents, here referred as leaders, whose influence act on their nearest neighbors, in the following referred as followers. Starting at the microscopic level, we develop a kinetic model that characteriz

Alexander Aycock

We show how the formulas in paper Variae considerationes circa series hypergeometricas written by Euler imply the duplication formula for the Gamma-function. This paper can be seen as an Addendum to a previous paper by the author.

Dawei Si, Yan Zhou, Sheng Xiao, Zhigang Xiao

The energetic bremsstrahlung photons up to 100 MeV produced in heavy ion collisions can be used as a sensitive probe to the short range correlation in atomic nuclei. The energy of the $\gamma$-rays can be measured by collecting the \v{C}erenkov light in medium induced by the fast electrons generated in Compton scattering or electromagnetic shower of the inci

Samyak Jain, Ameeya Bhagwat

A geometric perspective of the Higgs Mechanism is presented. Using Thom's Catastrophe Theory, we study the emergence of the Higgs Mechanism as a discontinuous feature in a general family of Lagrangians obtained by varying its parameters. We show that the Lagrangian that exhibits the Higgs Mechanism arises as a first-order phase transition in this general fam

Wenxing Zhu, Zhipeng Huang, Jianli Chen, Yao-Wen Chang

Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analy

G. Perotti, V. Christiaens, Th. Henning, B. Tabone

Terrestrial and sub-Neptune planets are expected to form in the inner ($<10~$AU) regions of protoplanetary disks. Water plays a key role in their formation, although it is yet unclear whether water molecules are formed in-situ or transported from the outer disk. So far Spitzer Space Telescope observations have only provided water luminosity upper limits for

S. Osone

With new calibration data, thermal emission from the jet of radio galaxy M87 is studied with about 700 ks archival data with Chandra. For nucleus, HST-1, knot D, X-ray energy spectra is well fitted with a power law. However, For knot A, a power law model is rejected with a high significance and an X-ray energy spectra is well fitted with a combination model

Tanvi Agrawal, Utkarsh Anand

The Runge-Kutta 4th Order (RK4) technique is extensively employed in the numerical solution of differential equations for airbrake control system design. However, its computational efficacy may encounter restrictions when dealing with high-speed vehicles that experience intricate aerodynamic forces. Using a Neural Network, a unique technique to improving the

Sukbae Lee, Jihoon Kim, Hyun-Tak Kim, Sungyeon Im

A material called LK-99, a modified-lead apatite crystal structure with the composition Pb$_{10-x}$Cu$_x$(PO$_4$)$_6$O ($0.9<x<1.1$), has been synthesized using the solid-state method. The material exhibits the Ohmic metal characteristic of Pb(6s1) above its superconducting critical temperature, $T_c$, and the levitation phenomenon as Meissner effect of a su

Volodymyr Biryuk, Walid Maalej

Previous research has studied the impact of developer personality in different software engineering scenarios, such as team dynamics and programming education. However, little is known about how user personality affect software engineering, particularly user-developer collaboration. Along this line, we present a preliminary study about the effect of personal

Yi Qin, Xiaomeng Li

Unsupervised deformable image registration is one of the challenging tasks in medical imaging. Obtaining a high-quality deformation field while preserving deformation topology remains demanding amid a series of deep-learning-based solutions. Meanwhile, the diffusion model's latent feature space shows potential in modeling the deformation semantics. To fully

Venkateswara Rao Kagita, Anshuman Singh, Vikas Kumar, Pavan Kalyan Reddy Neerudu

Group recommender systems (GRS) are critical in discovering relevant items from a near-infinite inventory based on group preferences rather than individual preferences, like recommending a movie, restaurant, or tourist destination to a group of individuals. The traditional models of group recommendation are designed to act like a black box with a strict focu

Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor

Early detection of colorectal polyps is of utmost importance for their treatment and for colorectal cancer prevention. Computer vision techniques have the potential to aid professionals in the diagnosis stage, where colonoscopies are manually carried out to examine the entirety of the patient's colon. The main challenge in medical imaging is the lack of data

Junzi Sun, Esther Roosenbrand

Air transport poses significant environmental challenges, particularly regarding the role of flight contrails in climate change due to their potential global warming impact. Traditional computer vision techniques struggle under varying remote sensing image conditions, and conventional machine learning approaches using convolutional neural networks are limite

Alejandro Perez, Salvatore Ribisi

We explicitly express the Minkowski vacuum of a massless scalar field in terms of the particle notion associated with suitable spherical conformal killing fields. These fields are orthogonal to the light wavefronts originating from a sphere with a radius of $r_{H}$ in flat spacetime: a bifurcate conformal killing horizon that exhibits semiclassical features

Hao Zhang, Sasha Gilevich, Alan Miahnahri, Shawn Alverson

This paper presents a comprehensive technical overview of the Linac Coherent Light Source II (LCLS-II) photoinjector laser system, its first and foremost component. The LCLS-II photoinjector laser system serves as an upgrade to the original LCLS at SLAC National Accelerator Laboratory. This advanced laser system generates high-quality laser beams for LCLS-II

Yuwei Yin, Yazheng Yang, Jian Yang, Qi Liu

Financial risk prediction plays a crucial role in the financial sector. Machine learning methods have been widely applied for automatically detecting potential risks and thus saving the cost of labor. However, the development in this field is lagging behind in recent years by the following two facts: 1) the algorithms used are somewhat outdated, especially i

Yves Gaspar, Pawel Tambor

The notion that nature is subject to laws is exciting from many different viewpoints. This paper is based on the context of modern cosmology and presents a more philosophical discussion. It will list the significant interdisciplinary implications generated by various aspects of the contemporary scientific discussion about the status of laws of nature, especi

Rong Shi, Peize Lin, Min-Ye Zhang, Lixin He

The random phase approximation (RPA) as formulated as an orbital-dependent, fifth-rung functional within the density functional theory (DFT) framework offers a promising approach for calculating the ground-state energies and the derived properties of real materials. Its widespread use to large-size, complex materials is however impeded by the significantly i

Nemanja Draganić, Marc Kaufmann, David Munhá Correia, Kalina Petrova

Size-Ramsey numbers are a central notion in combinatorics and have been widely studied since their introduction by Erd\H{o}s, Faudree, Rousseau and Schelp in 1978. Research has mainly focused on the size-Ramsey numbers of $n$-vertex graphs with constant maximum degree $\Delta$. For example, graphs which also have constant treewidth are known to have linear s

Xin Luo, Yunan Zhu, Shunxin Xu, Dong Liu

Several recent studies advocate the use of spectral discriminators, which evaluate the Fourier spectra of images for generative modeling. However, the effectiveness of the spectral discriminators is not well interpreted yet. We tackle this issue by examining the spectral discriminators in the context of perceptual image super-resolution (i.e., GAN-based SR),

Beatriz Elizaga Navascués, Guillermo A. Mena Marugán, Jesús Yébana Carrilero

In scenarios of physical interest in Loop Quantum Cosmology, with a preinflationary epoch where the kinetic energy of the inflaton dominates, the analytic study of the dynamics of the primordial fluctuations has been carried out by neglecting the inflaton potential in those stages of the evolution. In this work we develop approximations to investigate the in

Tsz On Mario Chan, Young-Jun Choi, Shin-ichi Matsumura

Let $(X,D)$ be a log-canonical (lc) pair, in which $X$ is a compact K\"ahler manifold and $D$ is a reduced snc divisor, and let $F$ be a holomorphic line bundle on $X$ equipped with a smooth metric $h_F = e^{-\varphi_F}$. Via the use of the adjoint ideal sheaves (constructed from $\varphi_F$ and $D$) and the associated residue morphisms, sections of $K_D \ot

Zeyu Chen, Chunhe Xiong, Kamil Khadiev, Junde Wu

Identical preparation creates permutation symmetry that can be used for lossless quantum compression. For $n$ copies of an unknown $d$-dimensional pure state, the tensor-power input lies in the fully symmetric subspace, whose dimension is polynomial in $n$ for fixed local dimension. Schur--Weyl duality isolates this subspace coherently, allowing the fixed re

Takuya Midooka, Misaki Mizumoto, Ken Ebisawa

Recent radiation-magnetohydrodynamic simulations of active galactic nuclei predict the presence of the disk winds, which may get unstable and turn into fragmented clumps far from the central black hole. These inner winds and the outer clumps may be observed as the ultrafast outflows (UFOs) and the partial absorbers, respectively. However, it is challenging t

Jung-Wan Ryu

We reveal that non-Hermitian Hamiltonians with nonreciprocal coupling can achieve amplification of initial states without external gain due to a kind of inherent source. We discuss the source and its effect on time evolution in terms of complex eigenenergies and non-orthogonal eigenstates. Demonstrating two extreme cases of Hamiltonians, namely one having co

Chenye Qin, Mi Jiang, Liang Si

Infinite-layer nickelate superconductors have recently been discovered to share both similarities and differences with cuprate superconductors. Notably, the incorporation of hydrogen (H) through topotactic reduction has been found to play a critical role in their electronic structure and, consequently, their superconductivity. In this study, we utilized a th

Jon Eskreis-Winkler, Yubin Kim, Andrew Stanton

In e-commerce, head queries account for the vast majority of gross merchandise sales and improvements to head queries are highly impactful to the business. While most supervised approaches to search perform better in head queries vs. tail queries, we propose a method that further improves head query performance dramatically. We propose XWalk, a random-walk b

Jing Hao, Moyun Liu, Jinrong Yang, Kuo Feng Hung

Detecting glass regions is a challenging task due to the inherent ambiguity in their transparency and reflective characteristics. Current solutions in this field remain rooted in conventional deep learning paradigms, requiring the construction of annotated datasets and the design of network architectures. However, the evident drawback with these mainstream s

Ahmad Samer Wazan, Imran Taj, Abdulhadi Shoufan, Romain Laborde

In this position paper, we advocate for the idea that courses and exams in the AI era have to be designed based on two factors: (1) the strengths and limitations of AI, and (2) the pedagogical educational objectives. Based on insights from the Delors report on education [1], we first address the role of education and recall the main objectives that education

Samik Basu, David Blanc, Debasis Sen

We explain how the simplicial higher-order unstable homotopy operations defined in [BBS2] may be composed and inserted one in another, thus forming a coherent if complicated algebraic structure.

Yi C. Huang, Yanlu Lian, Fei Xue

Let $\omega>0$. Given a strongly continuous semigroup $\{e^{tA}\}$ on a Banach space and an element $f\in\mathbf{D}(A^2)$ satisfying the exponential orbital estimates $$\|e^{tA}f\|\leq e^{-\omega t}\|f\| \quad\text{and}\quad \|e^{tA}A^2f\|\leq e^{-\omega t}\|A^2f\|,\quad t\geq0,$$ a dynamical inequality for $\|Af\|$ in terms of $\|f\|$ and $\|A^2f\|$ was der

Eleonora Maria Aiello, Mehrad Jaloli, Marzia Cescon

We present the design and \textit{in-silico} evaluation of a closed-loop insulin delivery algorithm to treat type 1 diabetes (T1D) consisting in a data-driven multi-step-ahead blood glucose (BG) predictor integrated into a Linear Time-Varying (LTV) Model Predictive Control (MPC) framework. Instead of identifying an open-loop model of the glucoregulatory syst

Jiancong Feng, Yuan-Gen Wang, Fengchuang Xing

Pursuing the precise details of super-resolution images is challenging for single-image super-resolution tasks. This paper presents a single-image super-resolution network with hairline details (termed NLCUnet), including three core designs. Specifically, a non-local attention mechanism is first introduced to restore local pieces by learning from the whole i

Wei Wang, Meng Zhai, Gang Zhao, Shen Wang

[Abridged] It is expected that the ongoing and future space-borne planet survey missions including TESS, PLATO, and Earth 2.0 will detect thousands of small to medium-sized planets via the transit technique, including over a hundred habitable terrestrial rocky planets. To conduct a detailed study of these terrestrial planets, particularly the cool ones with

Jodi Dianetti, Giorgio Ferrari, Ioannis Tzouanas

This paper studies a class of stationary mean-field games of singular stochastic control with regime-switching. The representative agent adjusts the dynamics of a Markov-modulated It\^o-diffusion via a two-sided singular stochastic control and faces a long-time-average expected profit criterion. The mean-field interaction is of scalar type and it is given th

Tapan Saha, Pranali Roy Chowdhury, Pallav Jyoti Pal, Malay Banerjee

Over the last few decades, complex oscillations of slow-fast systems have been a key area of research. In the theory of slow-fast systems, the location of singular Hopf bifurcation and maximal canard is determined by computing the first Lyapunov coefficient. In particular, the analysis of canards is based on the genericity condition that the first Lyapunov c

Jianli Bai, Xiaowu Zhang, Xiangfu Song, Hang Shao

Face recognition is a widely-used technique for identification or verification, where a verifier checks whether a face image matches anyone stored in a database. However, in scenarios where the database is held by a third party, such as a cloud server, both parties are concerned about data privacy. To address this concern, we propose CryptoMask, a privacy-pr

Dario A. Bini

This paper deals with the problem of numerically computing the roots of polynomials $p_k(x)$, $k=1,2,\ldots$, of degree $n=2^k-1$ recursively defined by $p_1(x)=x+1$, $p_k(x)=xp_{k-1}(x)^2+1$. An algorithm based on the Ehrlich-Aberth simultaneous iterations complemented by the Fast Multi-pole Method and the fast search of near neighbors of a set of complex n

Sukbae Lee, Ji-Hoon Kim, Young-Wan Kwon

For the first time in the world, we succeeded in synthesizing the room-temperature superconductor ($T_c \ge 400$ K, 127$^\circ$C) working at ambient pressure with a modified lead-apatite (LK-99) structure. The superconductivity of LK-99 is proved with the Critical temperature ($T_c$), Zero-resistivity, Critical current ($I_c$), Critical magnetic field ($H_c$

Du Nguyen Duy, Michael Affenzeller, Ramin-Nikzad Langerodi

Symbolic Regression is a powerful data-driven technique that searches for mathematical expressions that explain the relationship between input variables and a target of interest. Due to its efficiency and flexibility, Genetic Programming can be seen as the standard search technique for Symbolic Regression. However, the conventional Genetic Programming algori

Subham De

In the paper, we shall establish the existence of a meromorphic continuation of the Global Zeta Function $\zeta(f,\chi)$ of a Global Number Field $K$ and also deduce the functional equation for the same, using different properties of the id\`ele class group $\mathcal{C}_K^1$ of a global field $K$ extensively defined using basic notions of Ad\`eles ($\mathbb{

Afsah Saleem, Zaid Ilyas, David Suter, Ghulam Mubashar Hassan

Abdominal Aortic Calcification (AAC) is a known marker of asymptomatic Atherosclerotic Cardiovascular Diseases (ASCVDs). AAC can be observed on Vertebral Fracture Assessment (VFA) scans acquired using Dual-Energy X-ray Absorptiometry (DXA) machines. Thus, the automatic quantification of AAC on VFA DXA scans may be used to screen for CVD risks, allowing early

Tara Gheshlaghi, Shahabedin Nabavi, Samire Shirzadikia, Mohsen Ebrahimi Moghaddam

Radiation therapy is the primary method used to treat cancer in the clinic. Its goal is to deliver a precise dose to the planning target volume (PTV) while protecting the surrounding organs at risk (OARs). However, the traditional workflow used by dosimetrists to plan the treatment is time-consuming and subjective, requiring iterative adjustments based on th

Han Liu, Hao Li, Xing Yao, Yubo Fan

Medical image segmentation is a critical task in medical image analysis. In recent years, deep learning based approaches have shown exceptional performance when trained on a fully-annotated dataset. However, data annotation is often a significant bottleneck, especially for 3D medical images. Active learning (AL) is a promising solution for efficient annotati

Jakob Pietschnig, Sandra Oberleiter, Enrico Toffalini, David Giofre

Generational intelligence test score gains over large parts of the 20th century have been observed to be negatively associated with psychometric g. Recent reports about changes in the cross-temporal IQ trajectory suggest that ability differentiation may be responsible for both changes in g as well as increasingly (sub)domain specific and inconsistent traject

Shubhalaxmi Rath, Sadhana Dash

We have studied the effect of the nonextensive Tsallis mechanism on the viscous properties of hot QCD matter in the presence of a strong magnetic field. The results are compared to the case of absence of magnetic field. The viscous coefficients, such as the shear viscosity ($\eta$) and the bulk viscosity ($\zeta$) are determined in the similar environment by

Mateusz Krukowski

It is common knowledge that the Fourier transform enjoys the convolution property, i.e., it turns convolution in the time domain into multiplication in the frequency domain. It is probably less known that this property characterizes the Fourier transform amongst all linear and bounded operators $T:L^1 \longrightarrow C^b.$ Thus, a natural question arises: ar

A. Shabanpour, S. H. Rasouli, N. Fonseka

We study positive solutions to the steady state reaction diffusion systems of the form: \begin{equation} \left\{\begin{array}{ll} -\Delta u = \lambda f(v)+\mu h(u), & \Omega,\\ -\Delta v = \lambda g(u)+\mu q(v),& \Omega,\\ \frac{\partial u}{\partial \eta}+\sqrt[]{\lambda +\mu}\, u=0,& \partial\Omega,\\ \frac{\partial v}{\partial \eta}+\sqrt[]{\lambda +\mu}\,

Ryan Covey, Lucca Buonamano

The use of big data in official statistics and the applied sciences is accelerating, but statistics computed using only big data often suffer from substantial selection bias. This leads to inaccurate estimation and invalid statistical inference. We rectify the issue for a broad class of linear and nonlinear statistics by producing estimating equations that c

Daegyu Lee, Hyunwoo Nam, D. Hyunchul Shim

In recent years, deep-learning-based point cloud registration methods have shown significant promise. Furthermore, learning-based 3D detectors have demonstrated their effectiveness in encoding semantic information from LiDAR data. In this paper, we introduce ELiOT, an end-to-end LiDAR odometry framework built on a transformer architecture. Our proposed Self-