January 2022 arXiv papers — page 56

Mojtaba Sahraee-Ardakan, Melikasadat Emami, Parthe Pandit, Sundeep Rangan

Empirical observation of high dimensional phenomena, such as the double descent behaviour, has attracted a lot of interest in understanding classical techniques such as kernel methods, and their implications to explain generalization properties of neural networks. Many recent works analyze such models in a certain high-dimensional regime where the covariates

Qi Shi, Qian Liu, Bei Chen, Yu Zhang

Language-based environment manipulation requires agents to manipulate the environment following natural language instructions, which is challenging due to the huge space of the environments. To address this challenge, various approaches have been proposed in recent work. Although these approaches work well for their intended environments, they are difficult

Michael Krebsbach, Björn Trauzettel, Alessio Calzona

Quantum error mitigation is a key concept for the development of practical applications based on current noisy intermediate scale quantum (NISQ) devices. One of the most promising methods is Richardson extrapolation to the zero noise limit. While its main idea is rather simple, the full potential of Richardson extrapolation has not been completely uncovered

Charlotte Avery, Stijn Wuyts, Natascha M. Förster Schreiber, Carolin Villforth

This paper investigates the neutral gas phase of galactic winds via the Na I D$\lambda\lambda 5890,5895${\AA} feature within $z \sim 0.04$ MaNGA galaxies, and directly compares their incidence and strength to the ionized winds detected within the same parent sample. We find evidence for neutral outflows in 127 galaxies ($\sim 5$ per cent of the analysed line

Martin Waltz, Ostap Okhrin

Value-based reinforcement-learning algorithms have shown strong results in games, robotics, and other real-world applications. Overestimation bias is a known threat to those algorithms and can sometimes lead to dramatic performance decreases or even complete algorithmic failure. We frame the bias problem statistically and consider it an instance of estimatin

Yong-Gwan Ji, Hyeonbae Kang

This paper concerns the spectral properties of the Neumann-Poincar\'e operator on $m$-fold rotationally symmetric planar domains. An $m$-fold rotationally symmetric simply connected domain $D$ is realized as the $m$th-root transform of a certain domain, say $\Omega$. We prove that the domain of definition of the Neumann-Poincar\'e operator on $D$ is decompos

Olivier Ramare, Alisa Sedunova, Ritika Sharma

When restricted to some non-negative multiplicative function, say f, bounded on primes and that vanishes on non square-free integers, our result provides us with an asymptotic for $\sum_{n \le X}f(n)/n$ with error term $O((\log X)^{\kappa-h-1+\varepsilon})$ (for any positive $\varepsilon>0$) as soon as we have $\sum_{p\le Q}f(p)(\log p)/p=\kappa\log Q+\eta+O

Pedro Sancho

We revisit the problem of absorption by identical atoms with entanglement and symmetrization acting at once. We introduce the recoil of the atoms in the calculations and compare the results with those of distinguishable systems instead of mixtures. These absorption rates have been proposed to test entanglement-induced exclusion. The manifestation of exclusio

Curran Kalha, Michael Reisinger, Pardeep. K. Thakur, Tien-Lin Lee

Power semiconductor device architectures require the inclusion of a diffusion barrier to suppress, or at best prevent the interdiffusion between the copper metallisation interconnects and the surrounding silicon substructure. The binary pseudo-alloy of titanium-tungsten (TiW), with $>$70~at.\% W, is a well established copper diffusion barrier but is prone to

Junyang Zhang, Sanming Zhou

We correct the statements of two theorems and two corollaries in our paper [On subgroup perfect codes in Cayley graphs, European J. Combin. 91 (2021) 103228]. Proofs of these theorems and three other results are given as well.

Mariya Mamajiwala, Debasish Roy, Serge Guillas

Markov Chain Monte Carlo (MCMC) is one of the most powerful methods to sample from a given probability distribution, of which the Metropolis Adjusted Langevin Algorithm (MALA) is a variant wherein the gradient of the distribution is used towards faster convergence. However, being set up in the Euclidean framework, MALA might perform poorly in higher dimensio

Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Temporal sentence grounding in videos (TSGV), \aka natural language video localization (NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that semantically corresponds to a language query from an untrimmed video. Connecting computer vision and natural language, TSGV has drawn significant attention from researchers in both communities.

Zhuoyuan Mao, Chenhui Chu, Sadao Kurohashi

In the present study, we propose novel sequence-to-sequence pre-training objectives for low-resource machine translation (NMT): Japanese-specific sequence to sequence (JASS) for language pairs involving Japanese as the source or target language, and English-specific sequence to sequence (ENSS) for language pairs involving English. JASS focuses on masking and

Mingming Meng, Ying D. Liu, Chong Chen, Rui Wang

The S-shaped magnetic structure in the solar wind formed by the twisting of magnetic field lines is called a switchback, whose main characteristics are the reversal of the magnetic field and the significant increase in the solar wind radial velocity. We identify 242 switchbacks during the first two encounters of Parker Solar Probe (PSP). Statistics methods a

Evgeny Bobrov, Boris Chinyaev, Viktor Kuznetsov, Dmitrii Minenkov

Modern 5G wireless cellular networks use massive multiple-input multiple-output (MIMO) technology. This concept entails using an antenna array at a base station to concurrently service many mobile devices that have several antennas on their side. In this field, a significant role is played by the precoding (beamforming) problem. During downlink, an important

Tomoki Yamagami, Etsuo Segawa, Nicolas Chauvet, André Röhm

Quantum walks (QWs) exhibit different properties compared with classical random walks (RWs), most notably by linear spreading and localization. In the meantime, random walks that replicate quantum walks, which we refer to as quantum-walk-replicating random walks (QWRWs), have been studied in the literature where the eventual properties of QWRW coincide with

Zarrin Tasnim Sworna, Zahra Mousavi, Muhammad Ali Babar

Host based Intrusion Detection System (HIDS) is an effective last line of defense for defending against cyber security attacks after perimeter defenses (e.g., Network based Intrusion Detection System and Firewall) have failed or been bypassed. HIDS is widely adopted in the industry as HIDS is ranked among the top two most used security tools by Security Oper

Sylvain Gaulhiac

If $k$ is a complete non-archimedean field and $X$ an adic space locally of finite type over $\mathrm{Spa}(k)$, let $\textbf{Cov}_{X}^{\mathrm{oc}}$ (resp. $\textbf{Cov}_{X}^{\mathrm{adm}}$) be the category of \'etale coverings of $X$ that are locally for the Berkovich overconvergent topology (resp. for the admissible topology) disjoint union of finite \'eta

Dominik Dorsel, Sebastian Staacks, Heidrun Heinke, Christoph Stampfer

In this article, an experiment to measure air velocity with the barometer of a smartphone is presented utilizing the concept of a Pitot tube. For the experiment, the app phyphox is used which has a set of useful features for performing smartphone-based experiments 9,10 . Both the data analysis tools included in the app phyphox and the remote access function

Masoud Kamgarpour, Daxin Xu, Lingfei Yi

In a previous paper, the first and third authors gave an explicit realization of the geometric Langlands correspondence for hypergeometric sheaves, considered as $\textrm{GL}_n$-local systems. Certain hypergeometric local systems admit a symplectic or orthogonal structure, which can be viewed as $\check{G}$-local systems, for a classical group $\check{G}$. T

Peng Zhu, Shenglan Xie, Xiaoshen Wang

In this article, we present and analyze a stabilizer-free $C^0$ weak Galerkin (SF-C0WG) method for solving the biharmonic problem. The SF-C0WG method is formulated in terms of cell unknowns which are $C^0$ continuous piecewise polynomials of degree $k+2$ with $k\geq 0$ and in terms of face unknowns which are discontinuous piecewise polynomials of degree $k+1

K. Hagino

The concept of compound nucleus was proposed by Niels Bohr in 1936 to explain narrow resonances observed in scattering of a slow neutron off atomic nuclei. A compound nucleus is a metastable state with a long lifetime, in which all the degrees of freedom are in a sort of thermal equilibrium. Fusion reactions are defined as reactions to form such compound nuc

Rishabh, Chandan Kumar, Geetu Narang, Arvind

We explore the relative robustness of squeezing and entanglement (which are quantum resources interconvertible via passive optics) for two-mode Gaussian states under different dissipative environments. When the individual modes interact with identical local baths, entanglement and squeezing decay at the same rate. However, when only one of the modes interact

Dongyan Fu, Bao-Dong Sun, Yubing Dong

In this work, the electromagnetic and gravitational form factors of a spin-$3/2$ particle, $\Delta$ resonance, are simultaneously calculated with the help of a relativistic covariant quark-diquark approach. The two kinds of form factors are separately extracted from the matrix elements of the electromagnetic current and of the energy-momentum tensor of the s

Lucas Gren, Paul Ralph

Effective leadership is one of the key drivers of business and project success, and one of the most active areas of management research. But how does leadership work in agile software development, which emphasizes self-management and self-organization and marginalizes traditional leadership roles? To find out, this study examines agile leadership from the pe

Jiancheng Jiang, Jiang Xuejun, Wang Haofeng

We propose an empirical likelihood ratio test for nonparametric model selection, where the competing models may be nested, nonnested, overlapping, misspecified, or correctly specified. It compares the squared prediction errors of models based on the cross-validation and allows for heteroscedasticity of the errors of models. We develop its asymptotic distribu

Zoltan Nagy, Davison E. Soper

One can use more than one scale variable to specify the family of surfaces in the space of parton splitting parameters that define the evolution of a parton shower. Considering $e^+e^-$ annihilation, we use two variables, with shower evolution following a special path in this two dimensional space. In addition, we treat in a special way the part of the split

Anoop Singh, Abhitosh Upadhyay

We investigate the relative opers over the complex analytic family of compact complex manifolds of relative dimension one. We introduce the notion of relative opers arising from the second fundamental form associated with a relative holomorphic connection. We also investigate the relative differential operators over the complex analytic family of compact com

Yihang Li, Shuichiro Shimizu, Weiqi Gu, Chenhui Chu

Existing multimodal machine translation (MMT) datasets consist of images and video captions or general subtitles, which rarely contain linguistic ambiguity, making visual information not so effective to generate appropriate translations. We introduce VISA, a new dataset that consists of 40k Japanese-English parallel sentence pairs and corresponding video cli

Yuko Kakikawa, Kaito Shimamura, Shuichi Kawano

Bayesian fused lasso is one of the sparse Bayesian methods, which shrinks both regression coefficients and their successive differences simultaneously. In this paper, we propose a Bayesian fused lasso modeling via horseshoe prior. By assuming a horseshoe prior on the difference of successive regression coefficients, the proposed method enables us to prevent

Haidong Xie, Yizhou Xu, Yuanqing Chen, Nan Ji

The common jamming mode in wireless communication is band barrage jamming, which is controllable and difficult to resist. Although this method is simple to implement, it is obviously not the best jamming waveform. Therefore, based on the idea of adversarial examples, we propose the adversarial jamming waveform, which can independently optimize and find the b

Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet, Nesrine Chehata

We propose a new deep learning-based method for estimating the occupancy of vegetation strata from airborne 3D LiDAR point clouds. Our model predicts rasterized occupancy maps for three vegetation strata corresponding to lower, medium, and higher cover. Our weakly-supervised training scheme allows our network to only be supervised with vegetation occupancy v

Sheng Xu, Yanjing Li, Teli Ma, Bohan Zeng

Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-constrained devices. In this paper, we introduce a ternary vision transformer (TerViT) to ternarize the weights in ViTs, which are challenged by the large loss surface gap between rea

Gongyang Li, Zhi Liu, Zhen Bai, Weisi Lin

Salient object detection in optical remote sensing images (ORSI-SOD) has been widely explored for understanding ORSIs. However, previous methods focus mainly on improving the detection accuracy while neglecting the cost in memory and computation, which may hinder their real-world applications. In this paper, we propose a novel lightweight ORSI-SOD solution,

Yaser Rowshan

Let $H=(V(H),E(H))$ be a graph. A $k$-coloring of $H$ is a mapping $\pi : V(H) \longrightarrow \{1,2,\ldots, k\}$ so that each color class induces a $K_2$-free subgraph. For a graph $G$ of order at least $2$, a $G$-free $k$-coloring of $H$ is a mapping $\pi : V(H) \longrightarrow \{1,2,\ldots,k\}$ so that the subgraph of $H$ induced by each color class of $\

Yasuhiko Asao

In this article, we show that magnitude homology and path homology are closely related, and we give some applications. We define differentials ${\mathrm MH}^{\ell}_k(G) \longrightarrow {\mathrm MH}^{\ell-1}_{k-1}(G)$ between magnitude homologies of a digraph $G$, which make them chain complexes. Then we show that its homology ${\mathcal MH}^{\ell}_k(G)$ is n

Nicholas Adrian, Van-Thach Do, Quang-Cuong Pham

Classical Visual Servoing (VS) rely on handcrafted visual features, which limit their generalizability. Recently, a number of approaches, some based on Deep Neural Networks, have been proposed to overcome this limitation by comparing directly the entire target and current camera images. However, by getting rid of the visual features altogether, those approac

Michael T. Jury, Robert T. W. Martin, Eli Shamovich

We characterize the non-commutative Aleksandrov--Clark measures and the minimal realization formulas of contractive and, in particular, isometric non-commutative rational multipliers of the Fock space. Here, the full Fock space over $\mathbb{C} ^d$ is defined as the Hilbert space of square--summable power series in several non-commuting formal variables, and

Guangyao Zhou

Hamiltonian Monte Carlo (HMC) is a powerful Markov Chain Monte Carlo (MCMC) method for sampling from complex high-dimensional continuous distributions. However, in many situations it is necessary or desirable to combine HMC with other Metropolis-Hastings (MH) samplers. The common HMC-within-Gibbs strategy implies a trade-off between long HMC trajectories and

Jang-Ho Park, Jae Woo Lee

We present the photometric properties of V608 Cas from detailed studies of light curves and eclipse timings. The light curve synthesis indicates that the eclipsing pair is an overcontact binary with parameters of $\Delta T$ = 155 K, $q$ = 0.328, and $f$ = 26 %. We detected the third light $\ell_{3}$, which corresponds to about 8 % and 5 % of the total system

Ervin Dervishaj, Paolo Cremonesi

Proposed in 2014, Generative Adversarial Networks (GAN) initiated a fresh interest in generative modelling. They immediately achieved state-of-the-art in image synthesis, image-to-image translation, text-to-image generation, image inpainting and have been used in sciences ranging from medicine to high-energy particle physics. Despite their popularity and abi

O. Vikhrova, S. Pizzi, A. Terzani, L. Araujo

Devices with multiple Subscriber Identification Modules (SIM)s are expected to prevail over the conventional devices with only one SIM. Despite the growing demand for such devices, only proprietary solutions are available so far. To fill this gap, the Third Generation Partnership Project (3GPP) is aiming at the development of unified cross-platform solutions

Ritu Devi, Jaydip Singh, Baba Potukuchi

The ultimate objectives of ongoing and upcoming neutrino experiments are the precise measurement of neutrino mixing parameters and the confirmation of mass hierarchy. The systematic inaccuracy in the cross-section models introduces inaccuracy in the neutrino mixing parameters estimation. It is important to secure a large decrease of uncertainties, particular

Haidong Xie, Jia Tan, Xiaoying Zhang, Nan Ji

Deep learning is applied to many complex tasks in the field of wireless communication, such as modulation recognition of spectrum waveforms, because of its convenience and efficiency. This leads to the problem of a malicious third party using a deep learning model to easily recognize the modulation format of the transmitted waveform. Some existing works addr

Matheus Jacobs, Jannis Krumland, Caterina Cocchi

Understanding the fundamental mechanisms ruling laser-induced coherent charge transfer in hybrid organic/inorganic interfaces is of paramount importance to exploit these systems in next-generation opto-electronic applications. In a first-principles work based on real-time time-dependent density-functional theory, we investigate the ultrafast charge-carrier d

Daisuke Suzuki, Yujin Takahashi, Ikumi Yamashita, Taichi Aida

In grammatical error correction (GEC), automatic evaluation is an important factor for research and development of GEC systems. Previous studies on automatic evaluation have demonstrated that quality estimation models built from datasets with manual evaluation can achieve high performance in automatic evaluation of English GEC without using reference sentenc

Ilya D. Shkredov

We obtain some asymptotic formulae (with power savings in their error terms) for the number of quadruples in the Cartesian product of an arbitrary set $A \subset \mathbf{R}$ and for the number of quintuplets in $A\times A$ for any subset $A$ of the prime field $\mathbf{F}_p$. Also, we obtain some applications of our results to incidence problems in $\mathbf{

Abhinandan Panda, Srinivas Pinisetty, Partha Roop

Biophysical signals such as Electrocardiogram (ECG) and Photoplethysmogram (PPG) are key to the sensing of vital parameters for wellbeing. Coincidentally, ECG and PPG are signals, which provide a "different window" into the same phenomena, namely the cardiac cycle. While they are used separately, there are no studies regarding the exact correction of the dif

Sergey V. Gusev

The sets of all neutral, distributive and lower-modular elements of the lattice of semigroup varieties are finite, countably infinite and uncountably infinite, respectively. In 2018, we established that there are precisely three neutral elements of the lattice of monoid varieties. In the present work, it is shown that the neutrality, distributivity and lower

Tipaluck Krityakierne, Thotsaporn Aek Thanatipanonda

Given a sequence 1, 1, 5, 23, 135, 925, 7285, 64755, 641075, 6993545, 83339745,..., how can we guess a formula for it? This article will quickly walk you through the concept of ansatz for classes of polynomial, $C$-finite, holonomic, and the most recent addition $C^2$-finite sequences. For each of these classes, we discuss in detail various aspects of the gu

J. W. Seo, W. T. Kim, Y. D. Kim, H. Y. Lee

AMoRE-II is the second phase of the Advanced Molybdenum-based Rare process Experiment aiming to search for the neutrino-less double beta decay of 100Mo isotopes using ~ 200 kg of molybdenum-containing cryogenic detectors. The AMoRE-II needs to keep the background level below 10-5 counts/keV/kg/year with various methods to maximize the sensitivity. One of the

René Geromel, Christian Weinberger, Katja Brormann, Michael Tiemann

With the rapid advances of functional dielectric metasurfaces and their integration on on-chip nanophotonic devices, the necessity of metasurfaces working in different environments, especially in biological applications, arose. However, the metasurfaces' performance is tied to the unit cell's efficiency and ultimately the surrounding environment it was desig

Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Due to extensive spread of fake news on social and news media it became an emerging research topic now a days that gained attention. In the news media and social media the information is spread highspeed but without accuracy and hence detection mechanism should be able to predict news fast enough to tackle the dissemination of fake news. It has the potential

Zehua Li, Shasha Li, John-Paul Castellan, Rolf Heid

We present a study of the soft transverse optic phonon mode in SnTe in comparison to the corresponding mode in PbTe using inelastic neutron scattering and ab-initio lattice dynamical calculations. In contrast to previous reports our calculations predict that the soft mode in SnTe features a strongly asymmetric spectral weight distribution qualitatively simil

Yu Min, Yupeng Wang

Let $\frakX$ be a smooth $p$-adic formal scheme over $\calO_K$ with adic generic fiber $X$. We obtain a global equivalence between the category $\Vect((\frakX)_{\Prism},\overline\calO_{\Prism}[\frac{1}{p}])$ of rational Hodge--Tate crystals on the absolute prismatic site $(\frakX)_{\Prism}$ and the category $\HIG^{\nil}_*(X)$ of enhanced Higgs bundles on $X$

Jingye Wang, Ruoyi Du, Dongliang Chang, Kongming Liang

Adaptation to out-of-distribution data is a meta-challenge for all statistical learning algorithms that strongly rely on the i.i.d. assumption. It leads to unavoidable labor costs and confidence crises in realistic applications. For that, domain generalization aims at mining domain-irrelevant knowledge from multiple source domains that can generalize to unse

Qiang Zeng

Quantum steering has been exploited as an important resource in modern quantum information processing. Owing to its directional nature, some quantum states that are asymmetric under the exchange of parties have been found to manifest steering only in specific direction, thus called one-way steering. Existing works focused on one-way steering in systems of qu

Zengfu Hou, Wei Li

Multi-temporal hyperspectral images can be used to detect changed information, which has gradually attracted researchers' attention. However, traditional change detection algorithms have not deeply explored the relevance of spatial and spectral changed features, which leads to low detection accuracy. To better excavate both spectral and spatial information o

Shun Zhang

In this paper, we present proofs of the coerciveness of first-order system least-squares methods for general (possibly indefinite) second-order linear elliptic PDEs under a minimal uniqueness assumption. For general linear second-order elliptic PDEs, the uniqueness, existence, and well-posedness are equivalent due to the compactness of the operator and Fredh

Devansh Bisla, Jing Wang, Anna Choromanska

In this paper, we study the sharpness of a deep learning (DL) loss landscape around local minima in order to reveal systematic mechanisms underlying the generalization abilities of DL models. Our analysis is performed across varying network and optimizer hyper-parameters, and involves a rich family of different sharpness measures. We compare these measures a

Zixuan Xu, Penghui Wei, Weimin Zhang, Shaoguo Liu

In online advertising, conventional post-click conversion rate (CVR) estimation models are trained using clicked samples. However, during online serving the models need to estimate for all impression ads, leading to the sample selection bias (SSB) issue. Intuitively, providing reliable supervision signals for unclicked ads is a feasible way to alleviate the

N. Medvedev, F. Akhmetov, R. A. Rymzhanov, R. Voronkov

We present a concurrent Monte Carlo (MC) - molecular dynamics (MD) approach to modeling of matter response to excitation of its electronic system. The two methods are combined on-the-fly at each time step in one code, TREKIS-4. The MC model describes arrival of irradiation, which in the current implementation can consist of a photon, an electron, or a fast i

Su Zheng, Zhen Li, Yao Lu, Jingbo Gao

We propose an optimization method for the automatic design of approximate multipliers, which minimizes the average error according to the operand distributions. Our multiplier achieves up to 50.24% higher accuracy than the best reproduced approximate multiplier in DNNs, with 15.76% smaller area, 25.05% less power consumption, and 3.50% shorter delay. Compare

Binzhou Xia, Shasha Zheng, Sanming Zhou

A graphical regular representation (GRR) of a group $G$ is a Cayley graph of $G$ whose full automorphism group is equal to the right regular permutation representation of $G$. In this paper we study cubic GRRs of $\mathrm{PSL}_{n}(q)$ ($n=4, 6, 8$), $\mathrm{PSp}_{n}(q)$ ($n=6, 8$), $\mathrm{P}\Omega_{n}^{+}(q)$ ($n=8, 10, 12$) and $\mathrm{P}\Omega_{n}^{-}(

Shivangi Agarwal, Sanjit K. Kaul, Saket Anand, P. B. Sujit

We propose a novel deep neural network (DNN) based approximation architecture to learn estimates of measurements. We detail an algorithm that enables training of the DNN. The DNN estimator only uses measurements, if and when they are received over a communication network. The measurements are communicated over a network as packets, at a rate unknown to the e

Beili Ying, Li Feng, Bernd Inhester, Marilena Mierla

Context. Observations reveal that shocks can be driven by fast coronal mass ejections (CMEs) and play essential roles in particle accelerations. A critical ratio, $\delta$, derived from a shock standoff distance normalized by the radius of curvature (ROC) of a CME, allows us to estimate shock and ambient coronal parameters. However, true ROCs of CMEs are dif

Fatemeh Mohammadi Shakiba, Milad Shojaee, S. Mohsen Azizi, Mengchu Zhou

Recent artificial intelligence-based methods have shown great promise in the use of neural networks for real-time sensing and detection of transmission line faults and estimation of their locations. The expansion of power systems including transmission lines with various lengths have made a fault detection, classification, and location estimation process mor

Chenxing Wang, Fang Zhao, Haichao Zhang, Haiyong Luo

Travel Time Estimation (TTE) is indispensable in intelligent transportation system (ITS). It is significant to achieve the fine-grained Trajectory-based Travel Time Estimation (TTTE) for multi-city scenarios, namely to accurately estimate travel time of the given trajectory for multiple city scenarios. However, it faces great challenges due to complex factor

Francis Borceux, Federico Campanini, Marino Gran

We prove that the stable category associated with the category $\mathsf{PreOrd}(\mathbb C)$ of internal preorders in a pretopos $\mathbb C$ satisfies a universal property. The canonical functor from $\mathsf{PreOrd}(\mathbb C)$ to the stable category $\mathsf{Stab}(\mathbb C)$ universally transforms a pretorsion theory in $\mathsf{PreOrd}(\mathbb C)$ into a

Kang Zuo

This is an expository article on the recent developments of Hodge theory on moduli spaces of smooth projective varieties with semi-ample canonical line bundles.

Kyosuke Yamamoto, Kakeru Murakami, Ryota Shin, Yukihiko Okada

This study proposes a method for estimating the mechanical parameters of vehicles and bridges and the road unevenness, using only vehicle vibration and position data. In the proposed method, vehicle input and bridge vibration are estimated using randomly assumed vehicle and bridge parameters. Then, the road profiles at the front and rear wheels can be determ

Abolfazl Zolfaghari, Maryam Khoshkhoo

One of the methods to design products is reliability-based design, in which failure probability is usually used instead of safety factors. In the technique, it should not be less than a predetermined value. Choosing the proper design criterion is a challenging problem for designers who are dealing with the technique, particularly, when there are various crit

Rui Chen, Guanhua Chen, Menggang Yu

In this paper, we focus on estimating the average treatment effect (ATE) of a target population when individual-level data from a source population and summary-level data (e.g., first or second moments of certain covariates) from the target population are available. In the presence of heterogeneous treatment effect, the ATE of the target population can be di

Xiangyang Zhu, Kede Ma, Wufeng Xue

Predicting cardiac indices has long been a focal point in the medical imaging community. While various deep learning models have demonstrated success in quantifying cardiac indices, they remain susceptible to mild input perturbations, e.g., spatial transformations, image distortions, and adversarial attacks. This vulnerability undermines confidence in using

Guillaume Deffrennes, Jean-Marc Joubert, Benoit Oudot

High-pressure Gibbs energy approaches are promising for establishing multi-component thermodynamic databases. However, so far, they have often been considered unsuccessful, because of their tendency to lead to unphysical extrapolations of the thermodynamic properties at elevated temperatures and pressures. Beyond this symptom, the root causes of the problem

Hirotatsu Nagoji

In this paper, we study the stochastic nonlinear heat equations (SNLH) and stochastic nonlinear wave equations (SNLW) on two-dimensional torus driven by a subordinate cylindrical Brownian noise, which we define by the time-derivative of a cylindrical Brownian motion subordinated to a nondecreasing cadlag stochastic process. To construct the solution, we intr

Tomohiro Hayashi, Jeong Hee Hong, Wojciech Szymański

We apply a method inspired by Popa's intertwining-by-bimodules technique to investigate inner conjugacy of MASAs in graph $C^*$-algebras. First we give a new proof of non-inner conjugacy of the diagonal MASA ${\mathcal D}_n$ to its non-trivial image under a quasi-free automorphism, where $E$ is a finite transitive graph. Changing graphs representing the alge

Jaime Fabián Nieto Castellanos, Wolfgang Bietenholz, Ivan Hip

We consider the Schwinger model with two degenerate, light fermion flavors by means of lattice simulations. At finite temperature, we probe the viability of a bosonization method by Hosotani et al. Next we explore an analogue to the pion decay constant, which agrees for independent formulations based on the Gell-Mann--Oakes--Renner relation, the 2-dimensiona

Hongtao Wang, Yanping Su, Xue Ge, Yongyun Chen

By means of the data sets from the Pan-STARRAS1 survey, we have systematically examined the relationship between the variability characteristics and the physical parameters of the largest NLS1 galaxy sample up to now. The results are summarized as follows: (1). We find significant anti-correlations between variability amplitude and absolute magnitude in g, r

Katherine Hoffmann Pham, Miguel Luengo-Oroz

Predicting forced displacement is an important undertaking of many humanitarian aid agencies, which must anticipate flows in advance in order to provide vulnerable refugees and Internally Displaced Persons (IDPs) with shelter, food, and medical care. While there is a growing interest in using machine learning to better anticipate future arrivals, there is li

Giulia Preti, Gianmarco De Francisci Morales, Francesco Bonchi

Simplicial complexes are a generalization of graphs that model higher-order relations. In this paper, we introduce simplicial patterns -- that we call simplets -- and generalize the task of frequent pattern mining from the realm of graphs to that of simplicial complexes. Our task is particularly challenging due to the enormous search space and the need for h

Harshvardhan Uppaluru, Hossein Rastgoftar

Mechanics of materials is a classic course of engineering presenting the fundamentals of strain and stress analysis to junior undergraduate students in several engineering majors. So far, material deformation and strain have been only analyzed using theoretical and numerical approaches, and they have been experimentally validated by expensive machines and to

Xin Bing, Wei Cheng, Huijie Feng, Yang Ning

This paper studies the inference of the regression coefficient matrix under multivariate response linear regressions in the presence of hidden variables. A novel procedure for constructing confidence intervals of entries of the coefficient matrix is proposed. Our method first utilizes the multivariate nature of the responses by estimating and adjusting the h

Weihuang Xu, Guohao Yu, Yiming Cui, Romain Gloaguen

Understanding a plant's root system architecture (RSA) is crucial for a variety of plant science problem domains including sustainability and climate adaptation. Minirhizotron (MR) technology is a widely-used approach for phenotyping RSA non-destructively by capturing root imagery over time. Precisely segmenting roots from the soil in MR imagery is a critica

Suhas Kotha, Anirudh Koul, Siddha Ganju, Meher Kasam

A common class of problems in remote sensing is scene classification, a fundamentally important task for natural hazards identification, geographic image retrieval, and environment monitoring. Recent developments in this field rely label-dependent supervised learning techniques which is antithetical to the 35 petabytes of unlabelled satellite imagery in NASA

Wei Ren

Owing to the difference in $K$-theory, an example by Dugger and Shipley implies that the equivalence of stable categories of Gorenstein projective modules should not be a Quillen equivalence. We give a sufficient and necessary condition for the Frobenius pair of faithful functors between two abelian categories to be a Quillen equivalence, which is also equiv

Bhanu Prakash Reddy Guda, Mashrin Srivastava, Deep Karkhanis

In this work, we predict the sentiment of restaurant reviews based on a subset of the Yelp Open Dataset. We utilize the meta features and text available in the dataset and evaluate several machine learning and state-of-the-art deep learning approaches for the prediction task. Through several qualitative experiments, we show the success of the deep models wit

Yi Ding, Yingying Li, Rui Song

We establish a high-dimensional statistical learning framework for individualized asset allocation. Our proposed methodology addresses continuous-action decision-making with a large number of characteristics. We develop a discretization approach to model the effect of continuous actions and allow the discretization frequency to be large and diverge with the

D. V. Karlovets, S. S. Baturin, G. Geloni, G. K. Sizykh

The hard X-ray twisted photons and relativistic massive particles with orbital angular momentum -- vortex electrons, muons, protons, etc. -- have many potential applications in high-energy and nuclear physics. However, such states can be obtained so far mainly via diffraction techniques, not applicable for relativistic energies. Here we show that the vortex

Md Nadim, Manishankar Mondal, Chanchal K. Roy, Kevin Schneider

Co-change candidates are the group of code fragments that require a change if any of these fragments experience a modification in a commit operation during software evolution. The cloned co-change candidates are a subset of the co-change candidates, and the members in this subset are clones of one another. The cloned co-change candidates are usually created

H. J. M. Jönsson, M. Ekholm, I. Leonov, M. Dahlqvist

We perform a theoretical study of the electronic structure and magnetic properties of the prototypical magnetic MAX-phase Mn$_2$GaC with the main focus given to the origin of magnetic interactions in this system. Using the density functional theory+dynamical mean-field theory (DFT+DMFT) method we explore the effects of electron-electron interactions and magn

Chenyue Guo, Zi Cai

We study the localization phenomena in a one-dimensional lattice system with a uniformly moving disordered potential. At a low moving velocity, we find a sliding localized phase in which the initially localized matter wave adiabatically follows the moving potential without diffusion, thus resulting in an initial state memory in the many-body dynamics. Such a

Takamitsu Shioi, Takashi Kambayashi, Suguru Arakawa, Ryoji Kurosawa

Concurrency Control (CC) ensuring consistency of updated data is an essential element of OLTP systems. Recently, hybrid transactional/analytical processing (HTAP) systems developed for executing OLTP and OLAP have attracted much attention. The OLAP side CC domain has been isolated from OLTP's CC and in many cases has been achieved by snapshot isolation (SI)

Tengkuo Zhu, Stephen D. Boyles, Avinash Unnikrishnan

The idea of deploying electric vehicles and unmanned aerial vehicles (UAVs), also known as drones, to perform "last-mile" delivery in logistics operations has attracted increasing attention in the past few years. In this paper, we propose the electric vehicle traveling salesman problem with drone (EVTSPD), in which the electric vehicle (EV) and the drone per

Lan-Lan Gao, Xu-Guang Huang

Chiral anomaly and the novel quantum phenomena it induces have been widely studied for Dirac and Weyl fermions. In most typical cases, the Lorentz covariance is assumed and thus the linear dispersion relations are maintained. However, in realistic materials, such as Dirac and Weyl semimetals, the non-linear dispersion relations appear naturally. We develop a

Sruthi Ramadurai, Heejin Jeong

Human-robot collaboration has significant potential in recycling due to the wide variation in the composition of recyclable products. Six participants performed a recyclable item sorting task collaborating with a robot arm equipped with a vision system. The effect of three different levels of human involvement or assistance to the robot (Level 1- occlusion r

Cheng-En Wu, Farley Lai, Yu Hen Hu, Asim Kadav

Self-supervised video representation learning has been shown to effectively improve downstream tasks such as video retrieval and action recognition. In this paper, we present the Cascade Positive Retrieval (CPR) that successively mines positive examples w.r.t. the query for contrastive learning in a cascade of stages. Specifically, CPR exploits multiple view

Enyu Yu, Duanbing Chen, Yan Fu, Yuanyuan Xu

Because of its wide application, critical nodes identification has become an important research topic at the micro level of network science. Influence maximization is one of the main problems in critical nodes mining and is usually handled with heuristics. In this paper, a deep graph learning framework IMGNN is proposed and the corresponding training sample

S. B. Dubovichenko, A. S. Tkachenko, R. Ya. Kezerashvili, N. A. Burkova

We present new calculations of the astrophysical $S-$factor and reaction rate for the $^{6}$Li$(p,\gamma )^{7}$Be reaction at energies of 10 keV to 5 MeV in the framework of a modified potential cluster model with forbidden states, including low lying resonances. The astrophysical $S(E)-$factor is compared with the available experimental data and calculation

Sixiao Zhang, Hongxu Chen, Xiangguo Sun, Yicong Li

Graph contrastive learning is the state-of-the-art unsupervised graph representation learning framework and has shown comparable performance with supervised approaches. However, evaluating whether the graph contrastive learning is robust to adversarial attacks is still an open problem because most existing graph adversarial attacks are supervised models, whi