April 2023 arXiv papers — page 110

Tatsuya Miki, Hiroaki Ikeda, Shintaro Hoshino

The effect of impurities on a superconductor with Bogoliubov Fermi surfaces (BFSs) is studied using a realistic tight-binding model. Based on the band structure composed of $d$-orbitals in tetragonal FeSe, whose S-doped sample is a potential material for BFS, we construct the superconducting state by introducing a time-reversal broken pair potential in terms

Sen-Peng Eu, Louis Kao

The Springer numbers, introduced by Arnold, are generalizations of Euler numbers in the sense of Coxeter groups. They appear as the row sums of a double triangular array $(v_{n,k})$ of integers, $1\leq|k|\leq n$, defined recursively by a boustrophedon algorithm. We say a sequence of combinatorial objects $(X_{n,k})$ is an Arnold family if $X_{n,k}$ is counte

S. Prajnanaswaroopa

The Alon-Tarsi number of a polynomial is a parameter related to the exponents of its monomials. For graphs, their Alon-Tarsi number is the Alon-Tarsi number of their graph polynomials. As such, it provides an upper bound on their choice and online choice numbers. In this paper, we obtain the Alon-Tarsi number of some complete multipartite graphs, line graphs

Gyounghun Ko, Chanwoo Kim, Donghyun Lee

Establishing global well-posedness and convergence toward equilibrium of the Boltzmann equation with specular reflection boundary condition has been one of the central questions in the subject of kinetic theory. Despite recent significant progress in this question when domains are strictly convex, as shown by Guo and Kim-Lee, the same question without the st

Huanjing Yue, Yubo Peng, Biting Yu, Xuanwu Yin

High dynamic range (HDR) video reconstruction is attracting more and more attention due to the superior visual quality compared with those of low dynamic range (LDR) videos. The availability of LDR-HDR training pairs is essential for the HDR reconstruction quality. However, there are still no real LDR-HDR pairs for dynamic scenes due to the difficulty in cap

Ming Li, Naiyin Liu, Xiaofeng Pan, Yang Huang

Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit negative user behaviors (e.g., dislikes) or simply treat non-clicks as negative feedback, failing to learn negative user interests comprehensively. In such situations, u

Jiaxin Liang, Tse-Tin Chan, Haoyuan Pan

This paper investigates the information freshness of Industrial Internet of Things (IIoT) systems, where each IoT device makes a partial observation of a common target and transmits the information update to a central receiver to recover the complete observation. We consider the age of collection (AoC) performance as a measure of information freshness. Unlik

Mandan Naresh, Paresh Saxena, Manik Gupta

Adaptive bitrate (ABR) algorithms are used to adapt the video bitrate based on the network conditions to improve the overall video quality of experience (QoE). Recently, reinforcement learning (RL) and asynchronous advantage actor-critic (A3C) methods have been used to generate adaptive bit rate algorithms and they have been shown to improve the overall QoE

Daniel Zhang, Jan Lukas Bosse, Toby Cubitt

Systems in thermal equilibrium at non-zero temperature are described by their Gibbs state. For classical many-body systems, the Metropolis-Hastings algorithm gives a Markov process with a local update rule that samples from the Gibbs distribution. For quantum systems, sampling from the Gibbs state is significantly more challenging. Many algorithms have been

Guowei Dai, Yong Zhang

We establish local interval bifurcation theorem and global interval bifurcation theorem for Fredholm operator with index $0$ via $0$-group. As one of applications, we investigate the existence of a family of nontrivial domains $\Omega_{\rho}\subset \mathbb{R}^N$ ($N=2,3$ or $4$), bifurcating from a small ball, such that the problem \begin{equation} -\Delta u

Kumari Saloni, Anoot Kumar Yadav

Let $(R,\mathfrak{m})$ be a Cohen-Macaulay local ring of dimension $d\geq 3$ and $I$ an integrally closed $\mathfrak{m}$-primary ideal. We establish bounds for the third Hilbert coefficient $e_3(I)$ in terms of the lower Hilbert coefficients $e_i(I),~0\leq i\leq 2$ and the reduction number of $I$. When $d=3$, the boundary cases of these bounds characterize c

Yuyang Tu, Junnan Jiang, Shuang Li, Norman Hendrich

Accurate estimation of the relative pose between an object and a robot hand is critical for many manipulation tasks. However, most of the existing object-in-hand pose datasets use two-finger grippers and also assume that the object remains fixed in the hand without any relative movements, which is not representative of real-world scenarios. To address this i

Dmytro Yaremchuk, Dmytro Ivaneyko, Jaroslav Ilnytskyi

We analyze the magnetostriction effect occurring in the magneto-sensitive elastomers (MSEs) containing inhomogeneously magnetized particles. As it was shown before, the expression for the interaction potential between two magnetic spheres, that accounts for their mutual inhomogeneous magnetization, can be obtained from the Laplace equation. We use this poten

Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa

Zero-shot out-of-distribution (OOD) detection is a task that detects OOD images during inference with only in-distribution (ID) class names. Existing methods assume ID images contain a single, centered object, and do not consider the more realistic multi-object scenarios, where both ID and OOD objects are present. To meet the needs of many users, the detecti

Aman Asthana, Alexander A. Mushtukov, Alexandra A. Dobrynina, Igor S. Ognev

High mass accretion rate onto strongly magnetised neutron stars results in the appearance of accretion columns supported by the radiation pressure and confined by the strong magnetic field of a star. At mass accretion rates above $\sim 10^{19}\,{\rm g\,s^{-1}}$, accretion columns are expected to be advective. Under such conditions, a noticeable part of the t

Alberto Fernández-de-Marcos, Eduardo García-Portugués

Two new omnibus tests of uniformity for data on the hypersphere are proposed. The new test statistics exploit closed-form expressions for orthogonal polynomials, feature tuning parameters, and are related to a "smooth maximum" function and the Poisson kernel. We obtain exact moments of the test statistics under uniformity and rotationally symmetric alternati

João Maria Janeiro, Stanislav Frolov, Alaaeldin El-Nouby, Jakob Verbeek

Reducing the data footprint of visual content via image compression is essential to reduce storage requirements, but also to reduce the bandwidth and latency requirements for transmission. In particular, the use of compressed images allows for faster transfer of data, and faster response times for visual recognition in edge devices that rely on cloud-based s

Dimitrios M. Thilikos, Sebastian Wiederrecht

The branchwidth of a graph has been introduced by Roberson and Seymour as a measure of the tree-decomposability of a graph, alternative to treewidth. Branchwidth is polynomially computable on planar graphs by the celebrated ``Ratcatcher'' algorithm of Seymour and Thomas. We explore how this algorithm can be extended to minor-closed graph classes beyond plana

Wladimir Silva

This work describes a method to prepare the quantum state of the Heisenberg spin-1/2 Hamiltonian for the Kagome Lattice in an IBM 16 qubit quantum computer with a fidelity below 1% of the ground state computed via a classical Eigen-solver. Furthermore, this solution has a very high noise tolerance (or overall success rate above 98%). With industrious care ta

Wei Hua, Dingkang Liang, Jingyu Li, Xiaolong Liu

Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approaches mainly focus on horizontal objects, leaving multi-oriented objects that are common in aerial images unexplored. This paper proposes a novel Semi-supervised Oriented Object Detect

Yuting Zhan, Hamed Haddadi, Afra Mashhadi

Preserving the individuals' privacy in sharing spatial-temporal datasets is critical to prevent re-identification attacks based on unique trajectories. Existing privacy techniques tend to propose ideal privacy-utility tradeoffs, however, largely ignore the fairness implications of mobility models and whether such techniques perform equally for different grou

Lewei Yao, Jianhua Han, Xiaodan Liang, Dan Xu

This paper presents DetCLIPv2, an efficient and scalable training framework that incorporates large-scale image-text pairs to achieve open-vocabulary object detection (OVD). Unlike previous OVD frameworks that typically rely on a pre-trained vision-language model (e.g., CLIP) or exploit image-text pairs via a pseudo labeling process, DetCLIPv2 directly learn

Masaki J. S. Yang

In this letter, we perform a perturbative analysis by the lightest singular value $m_{D1}$ of the Dirac mass matrix $m_{D}$ in the type-I seesaw mechanism. A mass relation $M_{1} = m_{D1}^{2}/ |(m_{\nu})_{11}|$ is obtained for the lightest mass $M_{1}$ of the right-handed neutrino $\nu_{R1}$ and the mass matrix of the left-handed neutrinos $m_{\nu}$ in the d

Hiroki Azuma, Yusuke Matsui

Vision-language pre-training models (VLPs) have exhibited revolutionary improvements in various vision-language tasks. In VLP, some adversarial attacks fool a model into false or absurd classifications. Previous studies addressed these attacks by fine-tuning the model or changing its architecture. However, these methods risk losing the original model's perfo

Chengzhi Liu, Yue Qiu, Li Zhang

The geometric iterative method (GIM) is widely used in data interpolation/fitting, but its slow convergence affects the computational efficiency. Recently, much work was done to guarantee the acceleration of GIM in the literature. In this work, we aim to further accelerate the rate of convergence by introducing a preconditioning technique. After constructing

Suhaib Ardah, Francisco J. Profito, Tom Reddyhoff, Daniele Dini

Tackling fluid-flow problems involving intricate surface geometries has been the catalyst for a plethora of numerical investigations aimed at accommodating curved complex boundaries. An example is the application of body-fitted curvilinear coordinate transformation, where the one-to-one correspondence of grid points from the physical to the computational dom

Yuri B. Ovchinnikov, Folly Eli Ayi-Yovo, Alessio Spampinato

Optical dipole micro-traps for atoms based on constructive superposition of two-colour evanescent light waves, formed by corresponding optical modes of two crossed suspended photonic rib waveguides, are modelled. The main parameters of the traps for rubidium atoms, such as potential depth, tunnelling rates of atoms from the trap and coherence time of the tra

Yu Wang, Shuhui Bu, Lin Chen, Yifei Dong

Recently, cross-source point cloud registration from different sensors has become a significant research focus. However, traditional methods confront challenges due to the varying density and structure of cross-source point clouds. In order to solve these problems, we propose a cross-source point cloud fusion algorithm called HybridFusion. It can register cr

Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham, Lois Browne

Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC). However, in the clinic, molecular profiling is primarily used for ER+ breast cancer, which is costly, tissue destructive, requires specialized platforms and takes several

Kensuke Ohtake

The purpose of this paper is to provide a micro-economic foundation for an argument that the direct employment by the government is more desirable than the government purchase of private goods to eliminate unemployment. A general equilibrium model with monopolistic competition is devised, and the effects of policies (government purchase, tax rate operation,

Frederik Baymler Mathiesen, Licio Romao, Simeon C. Calvert, Alessandro Abate

This paper proposes a new framework to compute finite-horizon safety guarantees for discrete-time piece-wise affine systems with stochastic noise of unknown distributions. The approach is based on a novel approach to synthesise a stochastic barrier function (SBF) from noisy data and rely on the scenario optimization theory. In particular, we show that the st

J. Pascal Gollin, Sebastian Wiederrecht

We investigate a structural generalisation of treewidth we call $\mathcal{A}$-blind-treewidth where $\mathcal{A}$ denotes an annotated graph class. This width parameter is defined by evaluating only the size of those bags $B$ of tree-decompositions for a graph $G$ where ${(G,B) \notin \mathcal{A}}$. For the two cases where $\mathcal{A}$ is (i) the class $\ma

Pau Gallés, Xi Chen

This paper presents a new loss function for the prediction of oriented bounding boxes, named head-tail-loss. The loss function consists in minimizing the distance between the prediction and the annotation of two key points that are representing the annotation of the object. The first point is the center point and the second is the head of the object. However

Alessandra Celletti

The universe is composed of ordinary matter (for example, stars, planets, ourselves), dark matter and dark energy. The estimated percentage of dark matter is about $27\%$ of the entire universe, while $5\%$ is ordinary matter and the remaining part is dark energy. This article introduces the fundamental ingredients that led to conjecture the existence of dar

Wafaa B. M. Fadlelmula, Sanaa H. Mohamed, Taisir E. H. El-Gorashi, Jaafar M. H. Elmirghani

In this paper, we propose an energy efficient passive optical network (PON) architecture for backhaul connectivity in indoor visible light communication (VLC) systems. The proposed network is used to support a fog computing architecture designed to allow users with processing demands to access dedicated fog nodes and idle processing resources in other user d

B. Feigin, L. Rybnikov, F. Uvarov

We show that the construction of the higher Gaudin Hamiltonians associated to the Lie algebra $\mathfrak{gl}_{n}$ admits an interpolation to any complex $n$. We do this using the Deligne's category $\mathcal{D}_{t}$, which is a formal way to define the category of finite-dimensional representations of the group $GL_{n}$, when $n$ is not necessarily a natural

Shota Fukushima, Hyeonbae Kang, Yoshihisa Miyanishi

If the boundary of a domain in three dimensions is smooth enough, then the decay rate of the eigenvalues of the Neumann-Poincar\'e operator is known and it is optimal. In this paper, we deal with domains with less regular boundaries and derive quantitative estimates for the decay rates of the Neumann-Poincar\'e eigenvalues in terms of the H\"older exponent o

Mustafa Mullahasanoglu

In this study we work on a novel Hamiltonian system which is Liouville integrable. In the integrable Hamiltonian model, conserved currents can be represented as Binomial polynomials in which each order corresponds to the integral of motion of the system. From a mathematical point of view, the equations of motion can be written as integrable second-order nonl

Mariia O. Savchenko, Igor I. Skrypnik, Yevgeniia A. Yevgenieva

We prove the weak Harnack inequality for the functions $u$ which belong to the corresponding De Giorgi classes $DG^{-}(\Omega)$ under the additional assumption that $u\in L^{s}_{loc}(\Omega)$ with some $s> 0$. In particular, our result covers new cases of functionals with a variable exponent or double-phase functionals under the non-logarithmic condition.

Yoichi Ochiai, Naruya Kondo, Tatsuki Fushimi

In this paper, we propose a novel approach to establish a connection between linguistic objects and classes in Large Language Model Machines (LLMMs) such as GPT3.5 and GPT4, and their counterparts in high level programming languages like Python. Our goal is to promote the development of Digital Nature: a worldview where digital and physical realities are sea

Yu Hou, Cong Tran, Ming Li, Won-Yong Shin

In social networks, the discovery of community structures has received considerable attention as a fundamental problem in various network analysis tasks. However, due to privacy concerns or access restrictions, the network structure is often uncertain, thereby rendering established community detection approaches ineffective without costly network topology ac

Xiaoning Sun, Huaijiang Sun, Bin Li, Dong Wei

Let us rethink the real-world scenarios that require human motion prediction techniques, such as human-robot collaboration. Current works simplify the task of predicting human motions into a one-off process of forecasting a short future sequence (usually no longer than 1 second) based on a historical observed one. However, such simplification may fail to mee

Dan Barbasch, Jia-Jun Ma, Binyong Sun, Chen-Bo Zhu

Let G be a special linear group over the real, the complex or the quaternion, or a special unitary group. In this note, we determine all special unipotent representations of G in the sense of Arthur and Barbasch-Vogan, and show in particular that all of them are unitarizable.

Liang Chen, Yong Zhang, Yibing Song, Ying Shan

The main challenge in domain generalization (DG) is to handle the distribution shift problem that lies between the training and test data. Recent studies suggest that test-time training (TTT), which adapts the learned model with test data, might be a promising solution to the problem. Generally, a TTT strategy hinges its performance on two main factors: sele

Y. Zeng, Sanaa H. Mohamed, Ahmad Qidan, Taisir E. H. El-Gorashi

In this paper, we propose applying Non-Orthogonal Multiple Access (NOMA) technology in a multiuser beam steering OWC system. We study the performance of the NOMA-based multiuser beam steering system in terms of the achievable rate and Bit Error Rate (BER). We investigate the impact of the power allocation factor of NOMA and the number of users in the room. T

Y. Zeng, Sanaa H. Mohamed, Ahmad Qidan, Taisir E. H. El-Gorashi

This paper proposes using cooperative communication based on optoelectronic (O-E-O) amplify-and-forward relay terminals to reduce the influence of the blockage and shadowing resulting from human movement in a beam steering Optical Wireless Communication (OWC) system. The simulation results indicate that on average, the outage probability of the cooperative c

Cao H. Nam

We aim to provide a microscopic explanation of observed 4D black holes based on the compactification of 5D Einstein gravity plus a positive cosmological constant on a circle. The framework of the dimensional reduction in this work allows us to compute the statistical entropy of general 4D black holes independent of the symmetries of the black hole solution,

Olgur Celikbas, Souvik Dey, Toshinori Kobayashi

In this paper, we consider finitely generated modules over commutative Noetherian rings whose tensor products have finite projective dimension. We construct examples of modules of infinite projective dimension (and also of infinite Gorenstein dimension) whose tensor products nonetheless have finite projective dimension. Furthermore, we establish nontrivial c

Ji Yao, Huanyuan Shan, Ran Li, Youhua Xu

The precise estimation of the statistical errors and accurate removal of the systematical errors are the two major challenges for the stage IV cosmic shear surveys. We explore their impact for the China Space-Station Telescope (CSST) with survey area $\sim17,500\deg^2$ up to redshift $\sim4$. We consider statistical error contributed from Gaussian covariance

Pratyush Patel, Katie Lim, Kushal Jhunjhunwalla, Ashlie Martinez

Field-Programmable Gate Arrays (FPGAs) are more energy efficient and cost effective than CPUs for a wide variety of datacenter applications. Yet, for latency-sensitive and bursty workloads, this advantage can be difficult to harness due to high FPGA spin-up costs. We propose that a hybrid FPGA and CPU computing framework can harness the energy efficiency ben

Nan Yang, Tao Ge, Liang Wang, Binxing Jiao

We propose LLMA, an LLM accelerator to losslessly speed up Large Language Model (LLM) inference with references. LLMA is motivated by the observation that there are abundant identical text spans between the decoding result by an LLM and the reference that is available in many real world scenarios (e.g., retrieved documents). LLMA first selects a text span fr

Robin Strässer, Julian Berberich, Frank Allgöwer

In this paper, we present a state-feedback controller design method for bilinear systems. To this end, we write the bilinear system as a linear fractional representation by interpreting the state in the bilinearity as a structured uncertainty. Based on that, we derive convex conditions in terms of linear matrix inequalities for the controller design, which a

Masayo Fujimura, Rahim Kargar, Matti Vuorinen

We prove several new formulas for the visual angle metric of the unit disk in terms of the hyperbolic metric and apply these to prove a sharp Schwarz lemma for the visual angle metric under quasiregular mappings.

Keke Ying, Zhen Gao, Sheng Chen, Mingyu Zhou

Low earth orbit (LEO) satellite constellation-enabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where

Ruobing Jiang, Tianyi Yang, Sitian Qian, Yong Ban

Majorana properties of neutrinos have long been a focus in the pursuit of possible new physics beyond the standard model, which has motivated lots of dedicated theoretical and experimental studies. A future same-sign muon collider is an ideal platform to search for Majorana neutrinos through the Lepton Number Violation process. Specifically, this t-channel k

Adam Parhi, Dina Prialnik

Kuiper belt objects, such as Arrokoth, the probable progenitors of short-period comets, formed and evolved at large heliocentric distances, where the ambient temperatures appear to be sufficiently low for preserving volatile ices. By detailed numerical simulations, we follow the long-term evolution of small bodies, composed of amorphous water ice, dust, and

Sergio Cecotti

In Special Geometry there are two inequivalent notions of "Kodaira type" for a singular fiber: one associated with its local monodromy and one with its Hwang-Oguiso characteristic cycle. When the two Kodaira types are not equal the geometry is subtler and its deformation space gets smaller ("partially frozen" singularities). The paper analyzes the physical i

V. Liagkou, P. E. Nastou, P. Spirakis, Y. C. Stamatiou

In this paper we investigate phenomena of spontaneous emergence or purposeful formation of highly organized structures in networks of related agents. We show that the formation of large organized structures requires exponentially large, in the size of the structures, networks. Our approach is based on Kolmogorov, or descriptional, complexity of networks view

Chun-Chun Zhu, Qin Tan, Yu-Peng Zhang, Yu-Xiao Liu

In this work, we investigate numerical evolution of massive Kaluza-Klein (KK) modes of a Dirac field on a thick brane. We deduce the Dirac equation in five-dimensional spacetime, and obtain the time-dependent evolution equation and Schr\"odinger-like equation of the extra-dimensional component. We use the Dirac KK resonances as the initial data and study the

Daniel Ortega, Chia-Yu Li, Ngoc Thang Vu

This paper presents our latest investigation on modeling backchannel in conversations. Motivated by a proactive backchanneling theory, we aim at developing a system which acts as a proactive listener by inserting backchannels, such as continuers and assessment, to influence speakers. Our model takes into account not only lexical and acoustic cues, but also i

J. Maldonado, A. Petralia, G. Mantovan, M. Rainer

Context. Massive substellar companions orbiting active low-mass stars are rare. They, however, offer an excellent opportunity to study the main mechanisms involved in the formation and evolution of substellar objects. Aims. We aim to unravel the physical nature of the transit signal observed by the TESS space mission on the active M dwarf TOI-5375. Methods.

Aymen Khaleel, Ertugrul Basar

Reconfigurable intelligent surface (RIS)-empowered communication is an emerging technology that has recently received growing attention as a potential candidate for next-generation wireless communications. Although RISs have shown the potential of manipulating the wireless channel through passive beamforming, it is shown that they can also bring undesired si

Gaurav Deshkar, Jayanta Kshirsagar, Harshal Hayatnagarkar, Janani Venugopalan

To mitigate the impact of the pandemic, several measures include lockdowns, rapid vaccination programs, school closures, and economic stimulus. These interventions can have positive or unintended negative consequences. Current research to model and determine an optimal intervention automatically through round-tripping is limited by the simulation objectives,

Weiqi Zhang, Guanlue Li, Jianheng Tang, Jia Li

Data imputation is a crucial task due to the widespread occurrence of missing data. Many methods adopt a two-step approach: initially crafting a preliminary imputation (the "draft") and then refining it to produce the final missing data imputation result, commonly referred to as "draft-then-refine". In our study, we examine this prevalent strategy through th

Daniel Graf, Alex J. W. Thom

The crucial step in density-corrected Hartree-Fock density functional theory (DC(HF)-DFT) is to decide whether the density produced by the density functional for a specific calculation is erroneous and hence should be replaced by, in this case, the HF density. We introduce an indicator, based on the difference in non-interacting kinetic energies between DFT

Daniel Ortega, Sarina Meyer, Antje Schweitzer, Ngoc Thang Vu

We present our latest findings on backchannel modeling novelly motivated by the canonical use of the minimal responses Yeah and Uh-huh in English and their correspondent tokens in German, and the effect of encoding the speaker-listener interaction. Backchanneling theories emphasize the active and continuous role of the listener in the course of the conversat

Zhanyu Ma, Cheolhee Han, Yigal Meir, Eran Sela

Environment-induced localization transitions (LT) occur when a small quantum system interacts with a bath of harmonic oscillators. At equilibrium, LTs are accompanied by an entropy change, signaling the loss of coherence. Despite extensive efforts, equilibrium LTs have yet to be observed. Here, we demonstrate that ongoing experiments on double quantum dots t

NallappaBhavithran G, Selvakumar R

The biggest challenge when using DNA as a storage medium is maintaining its stability. The relative occurrence of Guanine (G) and Cytosine (C) is essential for the longevity of DNA. In addition to that, reverse complementary base pairs should not be present in the code. These challenges are overcome by a proper choice of group homomorphisms. Algorithms for s

V. V. Flambaum, A. J. Mansour

Atomic spectroscopy is used to search for the space-time variation of fundamental constants which may be due to an interaction with scalar and pseudo-scalar (axion) dark matter. In this letter, we study the effects which are produced by the variation of the nuclear radius and electric quadrupole moment. The sensitivity of the electric quadrupole hyperfine st

Changshuo Liu, Wenqiao Zhang, Beng Chin Ooi, James Wei Luen Yip

Electronic Health Records (EHR) are generated from clinical routine care recording valuable information of broad patient populations, which provide plentiful opportunities for improving patient management and intervention strategies in clinical practice. To exploit the enormous potential of EHR data, a popular EHR data analysis paradigm in machine learning i

Saharon Shelah

Was paper 839 in the author's list until winter 2023 when it was divided into three. Part I: We would like to generalize imaginary elements, weight of ortp$(a,M,N), {\mathbf P}$-weight, ${\mathbf P}$-simple types, etc. from [She90, Ch. III,V,\S4] to the context of good frames. This requires allowing the vocabulary to have predicates and function symbols of i

Felix Leinen, Orazio Puglisi

Let G be a finite solvable group, and let h(G) denote its Fitting height, namely the length of a shortest normal series in G with nilpotent factors. We show, that any law in G has length at least h(G). This result is then used to improve a previously given bound on the nonsolvable length of finite nonsolvable groups.

Fujia Li, Jing Wang, Fengwei Xu, Xu Kong

We select a disk-like galaxy sample with observations of the $HI$, $H_{2}$ and dust from Herschel Reference Survey (HRS), and derive inner HI masses within the optical radius. We find that the inner gas-to-dust ratio is almost independent of gas-phase metallicity, and confirm that the inner gas mass ($HI$+$H_{2}$) shows tighter relationship with dust mass an

Ru Li, Guanghui Liu, Bing Zeng, Shuaicheng Liu

This paper proposes a hybrid synthesis method for multi-exposure image fusion taken by hand-held cameras. Motions either due to the shaky camera or caused by dynamic scenes should be compensated before any content fusion. Any misalignment can easily cause blurring/ghosting artifacts in the fused result. Our hybrid method can deal with such motions and mainta

Bihag Dave, Gaurav Goswami

One of the most important questions in cosmology is concerning the fundamental nature of dark matter (DM). DM could consist of spinless particles of very small mass i.e. $m \sim 10^{-22}\ \text{eV}$. This kind of ultralight dark matter (ULDM) would form cored density profiles (called "solitons") at the centre of galaxies. In this context, recently it has bee

Weisong Zhao, Xiangyu Zhu, Kaiwen Guo, Xiao-Yu Zhang

Compared with the feature-based distillation methods, logits distillation can liberalize the requirements of consistent feature dimension between teacher and student networks, while the performance is deemed inferior in face recognition. One major challenge is that the light-weight student network has difficulty fitting the target logits due to its low model

Agus Gunawan, Soo Ye Kim, Hyeonjun Sim, Jae-Ho Lee

This paper firstly presents old photo modernization using multiple references by performing stylization and enhancement in a unified manner. In order to modernize old photos, we propose a novel multi-reference-based old photo modernization (MROPM) framework consisting of a network MROPM-Net and a novel synthetic data generation scheme. MROPM-Net stylizes old

Kumiko Hori, Chris A. Jones, Arrate Antuñano, Leigh N. Fletcher

Jupiter's weather layer exhibits long-term and quasi-periodic cycles of meteorological activity that can completely change the appearance of its belts and zones. There are cycles with intervals from 4 to 9 years, dependent on the latitude, which were detected in 5$\mu$m radiation, which provides a window into the cloud-forming regions of the troposphere; how

Qin Tang, Dandan Zhang, Tingting Liu, Wenxing Liu

The magneto-optical Faraday and Kerr effects are widely used in modern optical devices. In this letter, we propose an all-dielectric metasurface composed of perforated magneto-optical thin films, which can support the highly confined toroidal dipole resonance and provide full overlap between the localized electromagnetic field and the thin film, and conseque

Maxim Subbotin, Alexander Kodukov, Dmitry Pavlov

Modern lunar-planetary ephemerides are numerically integrated on the observational timespan of more than 100 years (with the last 20 years having very precise astrometrical data). On such long timespans, not only finite difference approximation errors, but also the accumulating arithmetic roundoff errors become important because they exceed random errors of

Chanyong Park

By applying the holographic method, we study a non-perturbative renormalization group (RG) flow triggered by a gluon condensate. After introducing a bulk scalar field in an AdS space related to the gluon condensate, we investigate the trace anomaly proportional to the gluon condensate. The holographic calculation reproduces the one-loop trace anomaly known i

Md. Hamjajul Ashmafee, Tasnim Ahmed, Sabbir Ahmed, Md. Bakhtiar Hasan

Correct identification and categorization of plant diseases are crucial for ensuring the safety of the global food supply and the overall financial success of stakeholders. In this regard, a wide range of solutions has been made available by introducing deep learning-based classification systems for different staple crops. Despite being one of the most impor

Mohamed Fakhfakh, Lotfi Chaari

In the literature on deep neural networks, there is considerable interest in developing activation functions that can enhance neural network performance. In recent years, there has been renewed scientific interest in proposing activation functions that can be trained throughout the learning process, as they appear to improve network performance, especially b

Kareem T. Elgindy

This paper introduces a new accurate model for periodic fractional optimal control problems (PFOCPs) using Riemann-Liouville (RL) and Caputo fractional derivatives (FDs) with sliding fixed memory lengths. The paper also provides a novel numerical method for solving PFOCPs using Fourier and Gegenbauer pseudospectral methods. By employing Fourier collocation a

Claudio Fontana, Simone Pavarana, Wolfgang J. Runggaldier

In this paper, we consider a generic interest rate market in the presence of roll-over risk, which generates spreads in spot/forward term rates. We do not require classical absence of arbitrage and rely instead on a minimal market viability assumption, which enables us to work in the context of the benchmark approach. In a Markovian setting, we extend the co

Liao Wang, Qiang Hu, Qihan He, Ziyu Wang

The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that utilize neural rendering for facilitating free-view videos (FVVs) are restricted to either offline rendering or are capable of processing only brief sequences with minimal motion. In t

Giovanni Conforti, Alain Durmus, Giacomo Greco

We show non-asymptotic exponential convergence of Sinkhorn iterates to the Schr\"odinger potentials, solutions of the quadratic Entropic Optimal Transport problem on $\mathbb{R}^ d$. Our results hold under mild assumptions on the marginal inputs: in particular, we only assume that they admit an asymptotically positive log-concavity profile, covering as speci

Patricia Arroba, Rajkumar Buyya, Román Cárdenas, José L. Risco-Martín

An increasing amount of data is being injected into the network from IoT (Internet of Things) applications. Many of these applications, developed to improve society's quality of life, are latency-critical and inject large amounts of data into the network. These requirements of IoT applications trigger the emergence of Edge computing paradigm. Currently, data

Zhengyu Qiao, Yong Huang, Qun Hao

We propose an image resolution improvement method for optical coherence tomography (OCT) based on sparse continuous deconvolution. Traditional deconvolution techniques such as Lucy-Richardson deconvolution suffers from the artifact convergence problem after a small number of iterations, which brings limitation to practical applications. In this work, we take

Ruoxi Qi, Yueyuan Zheng, Yi Yang, Caleb Chen Cao

Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. In image classification, we found that humans adopted more explorative attention strategies for explanation than the classification task itself. Two representative explanation strategies were identified through cl

Pedro P. Ferreira, Lewis J. Conway, Alessio Cucciari, Simone Di Cataldo

Motivated by the recent report of room-temperature superconductivity at near-ambient pressure in N-doped lutetium hydride by Dasenbrock et al. [Nature 615, 244 (2023)], we performed a comprehensive, detailed study of the phase diagram of the Lu-N-H system, looking for superconducting phases. We combined ab initio crystal structure prediction with ephemeral d

Jinxian Liu, Ye Chen, Bingbing Ni, Jiyao Mao

Humans have a strong intuitive understanding of physical processes such as fluid falling by just a glimpse of such a scene picture, i.e., quickly derived from our immersive visual experiences in memory. This work achieves such a photo-to-fluid-dynamics reconstruction functionality learned from unannotated videos, without any supervision of ground-truth fluid

Michael Elkin, Idan Shabat

Given an $n$-vertex undirected graph $G=(V,E,w)$, and a parameter $k\geq1$, a path-reporting distance oracle (or PRDO) is a data structure of size $S(n,k)$, that given a query $(u,v)\in V^2$, returns an $f(k)$-approximate shortest $u-v$ path $P$ in $G$ within time $q(k)+O(|P|)$. Here $S(n,k)$, $f(k)$ and $q(k)$ are arbitrary functions. A landmark PRDO due to

Moritz Reintjes

In this paper we propose a weaker version of Penrose's much heeded Strong Cosmic Censorship (SCC) conjecture, asserting inextentability of maximal Cauchy developments by manifolds with Lipschitz continuous Lorentzian metrics and Riemann curvature bounded in $L^p$. Lipschitz continuity is the threshold regularity for causal structures, and curvature bounds ru

Linhao Song, Jun Fan, Di-Rong Chen, Ding-Xuan Zhou

In recent years, functional neural networks have been proposed and studied in order to approximate nonlinear continuous functionals defined on $L^p([-1, 1]^s)$ for integers $s\ge1$ and $1\le p<\infty$. However, their theoretical properties are largely unknown beyond universality of approximation or the existing analysis does not apply to the rectified linear

Boyang Li, Yingqian Wang, Longguang Wang, Fei Zhang

Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds on infrared images. Recently, deep learning based methods have achieved promising performance on SIRST detection, but at the cost of a large amount of training data with expensive pixel-level annotations. To reduce the annotation burden, we propose

Zhanhong Qiu, Haitao Gan, Ming Shi, Zhongwei Huang

In the field of semi-supervised medical image segmentation, the shortage of labeled data is the fundamental problem. How to effectively learn image features from unlabeled images to improve segmentation accuracy is the main research direction in this field. Traditional self-training methods can partially solve the problem of insufficient labeled data by gene

Javier Sanchez-Rivero, Daniel Talaván, Jose Garcia-Alonso, Antonio Ruiz-Cortés

Quantum algorithms are a very promising field. However, creating and manipulating these kind of algorithms is a very complex task, specially for software engineers used to work at higher abstraction levels. The work presented here is part of a broader research focused on providing operations of a higher abstraction level to manipulate integers codified as a

Duc Ninh Le, Van Dung Le, Duc Truyen Le, Van Cuong Le

We investigate possible effects of unparticles at the MUonE experiment by considering a general model for unparticle with broken scale invariance, characterized by the scaling dimension $d$ and the energy scale $\mu$ at which the scale invariance is broken. Taking into account available relevant constraints on the couplings of the unparticles with the Standa

Charlotte Deconinck, Karel Dekimpe

A nilmanifold is a quotient N\G of a connected and simply connected nilpotent Lie group G by a uniform lattice N. In this paper we determine the Reidemeister and Nielsen number of affine n-valued maps on such a nilmanifold. These are maps for which a given lifting to G splits into n affine maps of the Lie group G. In order to obtain this result we also estab