August 2022 arXiv papers — page 56

Darpan Dubey, Rohit Kumar, Abhishek Dwivedi, Rahul Agarwal

The present manuscript reports the elemental as well as molecular study of the Green Crackers. Laser-induced breakdown spectroscopy has been used for elemental analysis, UV-Vis and Photoacoustic Spectroscopy (PAS) are used for molecular study of the green crackers. The spectral lines of several elements including heavy/toxic such as Al, Ba, Sr, Cr, Cu are ob

Mateusz Krukowski

Inspired by Jaming's characterization of the Fourier transform on specific groups via the convolution property, we provide a novel approach which characterizes the Fourier transform on any locally compact abelian group. In particular, our characterization encompasses Jaming's results. Furthermore, we demonstrate that the cosine transform as well as the Lapla

Jonas Sylneon

In this article, we develop a deterministic compartmental model including the spatio-temporal aspect and the wearing of masks by the general public for the spread of the Covid-19 epidemic. This model is based on the SIR model of Kermack and McKendrick and includes mobility terms that model the movement of individuals wearing masks between Guadeloupe andMarti

Jun Zhang, Sirui Liu, Mengyun Chen, Haotian Chu

Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and medical development. Determining accurate folding landscape using co-evolutionary information is fundamental to the success of modern protein structure prediction methods. As the s

Brahmanandam Javvaji, Bohayra Mortazavi, Timon Rabczuk, Xiaoying Zhuang

Recent experimental advances [Liu \textit{et al., npj 2D Materials and Applications}, 2019, \textbf{3}, 23] propose the design of graphene nanoribbon spring (GNRS) to substantially enhance the stretchability of pristine graphene. GNRS is a periodic undulating graphene nanoribbon, where undulations are of sinus or half-circles or horseshoe shapes. Besides tho

Ugochukwu Orji, Chikodili Ugwuishiwu, Mathew Okoronkwo, Caroline Asogwa

The coronavirus outbreak in 2020 devastated the world's economy, including Nigeria, even resulted in a severe recession. Slowly the country is building back again, and the vaccines are helping to reduce the spread of covid-19. Since the covid-19 vaccine came to Nigeria; 18,728,188 people have been fully vaccinated as at May 31st, 2022. This is roughly 10% of

Bob Ross, Cong Ling

Wang algebra was initiated by Ki-Tung Wang as a short-cut method for the analysis of electrical networks. It was later popularized by Duffin and has since found numerous applications in electrical engineering and graph theory. This is a semi-tutorial paper on Wang algebra, its history, and modern applications. We expand Duffin's historic notes on Wang algebr

Tong Wang

The research on the brain mechanism of creativity mainly has two aspects, one is the creative thinking process, and the other is the brain structure and functional connection characteristics of highly creative people. The billions of nerve cells in the brain connect and interact with each other. The hundreds of millions of nerve cells in the brain connect an

Peitao Liu, Jiantao Wang, Noah Avargues, Carla Verdi

Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges to theoretical modeling. Pretty much all existing density functionals fail to accurately describe surface energies, CO adsorption site preference, as well as adsorption energies sim

Xinrui Yan, Jiangyan Yi, Jianhua Tao, Chenglong Wang

Many effective attempts have been made for fake audio detection. However, they can only provide detection results but no countermeasures to curb this harm. For many related practical applications, what model or algorithm generated the fake audio also is needed. Therefore, We propose a new problem for detecting vocoder fingerprints of fake audio. Experiments

Yunxiang Xie, Ercai Chen, Rui Yang

We introduce the notion of Feldman-Katok metric mean dimensions in this note. We show metric mean dimensions defined by different metrics coincide under weak tame growth of covering numbers, and establish variational principles for Feldman-Katok metric mean dimensions in terms of FK Katok $\epsilon$-entropy and FK local $\epsilon$-entropy function.

Xiaoying Zhuang, Bo He, Brahmanandam Javvaji, Harold S. Park

Flexoelectricity is a form of electromechanical coupling that has recently emerged because, unlike piezoelectricity, it is theoretically possible in any dielectric material. Two-dimensional (2D) materials have also garnered significant interest because of their unusual electromechanical properties and high flexibility, but the intrinsic flexoelectric propert

Eduardo Sany Laber

We study the computational complexity of some explainable clustering problems in the framework proposed by [Dasgupta et al., ICML 2020], where explainability is achieved via axis-aligned decision trees. We consider the $k$-means, $k$-medians, $k$-centers and the spacing cost functions. We prove that the first three are hard to optimize while the latter can b

Lioba Heimbach, Eric Schertenleib, Roger Wattenhofer

Financial markets have evolved over centuries, and exchanges have converged to rely on the order book mechanism for market making. Latency on the blockchain, however, has prevented decentralized exchanges (DEXes) from utilizing the order book mechanism and instead gave rise to the development of market designs that are better suited to a blockchain. Although

Pengyu Wen, Xuan Mao, Min Wang, Chuan Wang

Simultaneous ground-state cooling of multiple degenerate mechanical modes is a tough issue in optomechanical system due to the existence of the dark mode effect. Here we propose a universal and scalable method to break the dark mode effect of two degenerate mechanical modes by introducing the cross-Kerr (CK) nonlinearity. At most four stable steady states ca

Brahmanandam Javvaji, Bo He, Xiaoying Zhuang, Harold S Park

Due to their combination of mechanical stiffness and flexibility, two-dimensional (2D) materials have received significant interest as potential electromechanical materials. Flexoelectricity is an electromechanical coupling between strain gradient and polarization. Unlike piezoelectricity, which exists only in non-centrosymmetric materials, flexoelectricity

Tommaso Sorgente, Fabio Vicini, Stefano Berrone, Silvia Biasotti

We propose a quality-based optimization strategy to reduce the total number of degrees of freedom associated to a discrete problem defined over a polygonal tessellation with the Virtual Element Method. The presented Quality Agglomeration algorithm relies only on the geometrical properties of the problem polygonal mesh, agglomerating groups of neighboring ele

Maximilian Kasy, Jann Spiess

What is the purpose of pre-analysis plans, and how should they be designed? We model the interaction between an agent who analyzes data and a principal who makes a decision based on agent reports. The agent could be the manufacturer of a new drug, and the principal a regulator deciding whether the drug is approved. Or the agent could be a researcher submitti

M. C. Crabb

Let $G$ be a finite group and $V$ a finite dimensional (non-zero) orthogonal $G$-module such that, for each prime $p$ dividing the order of $G$, the subspace of $V$ fixed by a Sylow $p$-subgroup of $G$ is non-zero and, if the dimension of $V$ is odd, has dimension greater than $1$. Using ideas of Avvakumov, Karasev, Kudrya and Skopenkov and work of Noakes on

Akansh Maurya, Kunal Dashrath Patil, Rohan Padhy, Kalluri Ramakrishna

In this work, we present our proposed method to segment the pulmonary arteries from the CT scans using Swin UNETR and U-Net-based deep neural network architecture. Six models, three models based on Swin UNETR, and three models based on 3D U-net with residual units were ensemble using a weighted average to make the final segmentation masks. Our team achieved

Li Fan, Jianchang Liu

This work proposes a novel transformation termed the conformal navigation transformation to achieve collision-free navigation of a robot in a workspace populated with arbitrary polygonal obstacles. The properties of the conformal navigation transformation in the polygonal workspace are investigated in this work as well as its capability to provide a solution

Yeqi Gao, Zhao Song, Baocheng Sun

Fourier transformation is an extensively studied problem in many research fields. It has many applications in machine learning, signal processing, compressed sensing, and so on. In many real-world applications, approximated Fourier transformation is sufficient and we only need to do the Fourier transform on a subset of coordinates. Given a vector $x \in \mat

P. A. Glendinning, D. J. W. Simpson

We show that a one-dimensional differential equation depending on a parameter $\mu$ with a saddle-node bifurcation at $\mu =0$ can be modelled by an extended normal form $\dot y = \nu (\mu )-y^2+a(\mu )y^3$, where the functions $\nu$ and $a$ are solutions to equations that can be written down explicitly. The equivalence to the original equations is a local d

Yushun Zhang, Congliang Chen, Naichen Shi, Ruoyu Sun

Ever since Reddi et al. 2018 pointed out the divergence issue of Adam, many new variants have been designed to obtain convergence. However, vanilla Adam remains exceptionally popular and it works well in practice. Why is there a gap between theory and practice? We point out there is a mismatch between the settings of theory and practice: Reddi et al. 2018 pi

Ibrahima Bakayoko

The purpose of this paper is to study some Ternary color algebras. We generalize some results on ternary Leibniz algebras to the case of ternary Leibniz color algebras. In order to produce examples of ternary Leibniz color algebras from Leibniz color algebras, several results on Leibniz color algebras are given. Next, We introduce ternary Leibniz color algeb

U. Munari, N. Masetti, F. M. Walter, R. E. Williams

We report on the fast Nova Sgr 2016 N.4 being surprisingly trapped in a long-lasting and bright plateau (Delta I >= 10 mag above quiescence) six years past the nova eruption. Very few other novae experience a similar occurrence. We carried out an intensive observing campaign collecting daily BVRI photometry and monthly high-resolution optical spectroscopy, a

Gayan K. Kulatilleke

Credit cards play an exploding role in modern economies. Its popularity and ubiquity have created a fertile ground for fraud, assisted by the cross boarder reach and instantaneous confirmation. While transactions are growing, the fraud percentages are also on the rise as well as the true cost of a dollar fraud. Volume of transactions, uniqueness of frauds an

K. Kefi, N. Irzi, M. M. Al-Shomrani, D. D. Repovš

We prove the existence of at least three weak solutions for the fourth-order problem with indefinite weight involving the Leray-Lions operator with nonstandard growth conditions. The proof of our main result uses variational methods and the critical theorem of Bonanno and Marano (Appl. Anal. 89 (2010), 1-10).

Betty Lala, Srikant Manas Kala, Anmol Rastogi, Kunal Dahiya

Indoor thermal comfort in smart buildings has a significant impact on the health and performance of occupants. Consequently, machine learning (ML) is increasingly used to solve challenges related to indoor thermal comfort. Temporal variability of thermal comfort perception is an important problem that regulates occupant well-being and energy consumption. How

Aymen Khaleel, Ertugrul Basar

Reconfigurable intelligent surface (RIS)-assisted communications recently appeared as a game-changing technology for next-generation wireless communications due to its unprecedented ability to reform the propagation environment. One of the main aspects of using RISs is the exploitation of the so-called passive beamforming (PB), which is carried out by adjust

Yaman Kumar Singla, Rajat Jha, Arunim Gupta, Milan Aggarwal

Modeling what makes an advertisement persuasive, i.e., eliciting the desired response from consumer, is critical to the study of propaganda, social psychology, and marketing. Despite its importance, computational modeling of persuasion in computer vision is still in its infancy, primarily due to the lack of benchmark datasets that can provide persuasion-stra

Jiacheng Li, Yannis Katsis, Tyler Baldwin, Ho-Cheol Kim

Knowledge-enhanced pre-trained models for language representation have been shown to be more effective in knowledge base construction tasks (i.e.,~relation extraction) than language models such as BERT. These knowledge-enhanced language models incorporate knowledge into pre-training to generate representations of entities or relationships. However, existing

Ebraheem Farag, Mathieu Renzo, Robert Farmer, Morgan T. Chidester

Gravitational wave (GW) detections of binary black hole (BH) mergers have begun to sample the cosmic BH mass distribution. The evolution of single stellar cores predicts a gap in the BH mass distribution due to pair-instability supernova (PISN). Determining the upper and lower edges of the BH mass gap can be useful for interpreting GW detections from merging

Morteza Zakeri-Nasrabadi, Saeed Parsa

The high cost of the test can be dramatically reduced, provided that the coverability as an inherent feature of the code under test is predictable. This article offers a machine learning model to predict the extent to which the test could cover a class in terms of a new metric called Coverageability. The prediction model consists of an ensemble of four regre

Victor Volfson

We define the asymptotic behavior "almost everywhere" of additive and multiplicative arithmetic functions in the paper. Classes of additive and multiplicative arithmetic functions are singled out for which the asymptotics coincides "almost everywhere" with the asymptotics of the corresponding strongly additive and multiplicative arithmetic functions. Several

Fumitake Hyodo

The present paper studies Hecke rings derived by the automorphism groups of certain algebras $L_p$ over the ring of $p$-adic integers. Our previous work considered the case where $L_p$ is the Heisenberg Lie algebra (of dimension 3) over the ring of $p$-adic integers. Although this Hecke ring is noncommutative, we showed that a formal power series with coeffi

Francesco Giuli

The Future Circular Collider (FCC) is a post-LHC project aiming at direct and indirect searches for physics beyond the SM in a new 100 km tunnel at CERN. In addition, the FCC-ee offers unique possibilities for high-precision studies of the strong interaction in the clean environment provided by $e^{+}e^{-}$ collisions, thanks to its broad span of center-of-m

Jin Cao, Huan Yang, Zhen Su, Xin-Yao Wang

We report on the preparation of a quantum degenerate mixture of $^{23}$Na$^{40}$K molecules and $^{40}$K atoms. A deeply degenerate atomic mixture of $^{23}$Na and $^{40}$K atoms with a large number ratio ($N_F/N_B\approx 6$) is prepared by the mode-matching loading of atoms from a cloverleaf-type magnetic trap into a large-volume horizontal optical dipole t

Asif Newaz, Farhan Shahriyar Haq

Class imbalance is a frequently occurring scenario in classification tasks. Learning from imbalanced data poses a major challenge, which has instigated a lot of research in this area. Data preprocessing using sampling techniques is a standard approach to deal with the imbalance present in the data. Since standard classification algorithms do not perform well

Chenglong Wang, Jiangyan Yi, Jianhua Tao, Haiyang Sun

The existing fake audio detection systems often rely on expert experience to design the acoustic features or manually design the hyperparameters of the network structure. However, artificial adjustment of the parameters can have a relatively obvious influence on the results. It is almost impossible to manually set the best set of parameters. Therefore this p

Yanjie Gou, Yinjie Lei, Lingqiao Liu, Yong Dai

Aspect Sentiment Triplet Extraction (ASTE) aims to extract the spans of aspect, opinion, and their sentiment relations as sentiment triplets. Existing works usually formulate the span detection as a 1D token tagging problem, and model the sentiment recognition with a 2D tagging matrix of token pairs. Moreover, by leveraging the token representation of Pretra

Gregor Gantner, Rob Stevenson

In this work, we show that the space-time first-order system least-squares (FOSLS) formulation [F\"uhrer, Karkulik, Comput. Math. Appl. 92 (2021)] for the heat equation and its recent generalization [Gantner, Stevenson, ESAIM Math. Model. Numer. Anal. 55 (2021)] to arbitrary second-order parabolic PDEs can be used to efficiently solve parameter-dependent pro

Aris L. Moustakas, George C. Alexandropoulos, Mérouane Debbah

Reconfigurable Intelligent Surfaces (RISs), comprising large numbers of low-cost and almost passive metamaterials with tunable reflection properties, have been recently proposed as an enabling technology for programmable wireless propagation environments. In this paper, we present asymptotic closed-form expressions for the mean and variance of the mutual inf

Morteza Zakeri-Nasrabadi, Saeed Parsa

Unlike most other software quality attributes, testability cannot be evaluated solely based on the characteristics of the source code. The effectiveness of the test suite and the budget assigned to the test highly impact the testability of the code under test. The size of a test suite determines the test effort and cost, while the coverage measure indicates

Yongzhou Chen, Ammar Tahir, Radhika Mittal

Realizing that it is inherently difficult to precisely match the sending rates at the endhost with the available capacity on dynamic cellular links, we build a system, Octopus, that sends real-time data streams over cellular networks using an imprecise controller (that errs on the side of over-estimating network capacity), and then drops appropriate packets

Huadai Liu, Wenqiang Xu, Xuan Lin, Jingjing Huo

Argument mining aims to detect all possible argumentative components and identify their relationships automatically. As a thriving task in natural language processing, there has been a large amount of corpus for academic study and application development in this field. However, the research in this area is still constrained by the inherent limitations of exi

The Viet Bui, Tien Mai, Patrick Jaillet

We study inverse reinforcement learning (IRL) and imitation learning (IM), the problems of recovering a reward or policy function from expert's demonstrated trajectories. We propose a new way to improve the learning process by adding a weight function to the maximum entropy framework, with the motivation of having the ability to learn and recover the stochas

Hongxin Li, Xu Yang, Yuran Yang, Shuqi Mei

Image-goal navigation is a challenging task, as it requires the agent to navigate to a target indicated by an image in a previously unseen scene. Current methods introduce diverse memory mechanisms which save navigation history to solve this task. However, these methods use all observations in the memory for generating navigation actions without considering

Hao Yu, Noah F. Q. Yuan, Wei-Jian Li, Liu-Cheng Chen

Topological superconductivity is an exotic quantum phenomenon with coupled nontrivial topological order and superconductivity together. A direct idea for producing topological superconductors is to create superconductivity based on the well recognized topological insulators. The topological insulating states in highly efficient thermoelectric materials Bi$_2

Saul Ancari, Xu Cheng

$\lambda$-self-expanders $\Sigma$ in $\mathbb{R}^{n+1}$ are the solutions of the isoperimetric problem with respect to the same weighted area form as in the study of the self-expanders. In this paper, we mainly extend the results on self-expanders which we obtained in \cite{ancari2020volum} to $\lambda$-self-expanders. We prove some results that characterize

Dmitrijs Trizna

We propose a hybrid machine learning architecture that simultaneously employs multiple deep learning models analyzing contextual and behavioral characteristics of Windows portable executable, producing a final prediction based on a decision from the meta-model. The detection heuristic in contemporary machine learning Windows malware classifiers is typically

Venkata Sirimuvva Chirala, Kaarthik Sundar, Saravanan Venkatachalam, Jonathon M. Smereka

Unmanned ground vehicles (UGVs) are being used extensively in civilian and military applications for applications such as underground mining, nuclear plant operations, planetary exploration, intelligence, surveillance and reconnaissance (ISR) missions and manned-unmanned teaming. We consider a multi-objective, multiple-vehicle routing problem in which teams

João Pedro Norenberg, Roberto Luo, Vinicius Goncaalves Lopes, João Victor L. L. Peterson

The paper investigates asymmetries effects over a nonlinear vibration energy harvester dynamics. The asymmetric system performance is compared with symmetric ones. Different asymmetry levels on restoring force and gravity action are investigated from a system-sloping angle variation. Bifurcation diagrams and basins of attraction are used to examine the local

Rui Meng, Tong Wang, Xingdi Yuan, Yingbo Zhou

Training keyphrase generation (KPG) models require a large amount of annotated data, which can be prohibitively expensive and often limited to specific domains. In this study, we first demonstrate that large distribution shifts among different domains severely hinder the transferability of KPG models. We then propose a three-stage pipeline, which gradually g

Kai Lu, Min He

Charm-hadrons possess versatile hadro-chemistry as characterized by various transverse-momentum-dependent ratios between their different species. In particular, the charm hadro-chemistry may be modified in relativistic heavy-ion collisions with respect to proton-proton collisions at the same energy, as caused by novel diffusion and hadronization mechanisms o

Yi Shen, Lin Chen, Li Yu

The multipartite unitary gates are called genuine if they are not product unitary operators across any bipartition. We mainly investigate the classification of genuine multipartite unitary gates of Schmidt rank two, by focusing on the multiqubit scenario. For genuine multipartite (excluding bipartite) unitary gates of Schmidt rank two, there is an essential

Ke Zhang, Wenzhao Sun, Yikun Chen, Hanke Feng

Integrated electro-optic (EO) frequency combs are essential components for future applications in optical communications, light detection and ranging, optical computation, sensing and spectroscopy. To date, broadband on-chip EO combs are typically generated in high-quality-factor micro-resonators, while the more straightforward and flexible non-resonant meth

Gihyun Kim, Juyeop Kim, Jong-Seok Lee

The Vision Transformer has emerged as a powerful tool for image classification tasks, surpassing the performance of convolutional neural networks (CNNs). Recently, many researchers have attempted to understand the robustness of Transformers against adversarial attacks. However, previous researches have focused solely on perturbations in the spatial domain. T

Souvik Das, Sougata Saha, Rohini K. Srihari

Personalized response selection systems are generally grounded on persona. However, there exists a co-relation between persona and empathy, which is not explored well in these systems. Also, faithfulness to the conversation context plunges when a contradictory or an off-topic response is selected. This paper attempts to address these issues by proposing a su

Vedant Sandeep Joshi, Sivanagaraja Tatinati, Yubo Wang

Recently, e-learning platforms have grown as a place where students can post doubts (as a snap taken with smart phones) and get them resolved in minutes. However, the significant increase in the number of student-posted doubts with high variance in quality on these platforms not only presents challenges for teachers' navigation to address them but also incre

Jitendra Pal, Hemant Rathi, Arindam Lala, Dibakar Roychowdhury

We explore a novel class of Yang-Baxter deformed AdS$_{4}$ $\times$ CP$^{3}$ backgrounds [Jour. High Ener. Phys. \textbf{01} (2021) 056] which exhibit a non-chaotic dynamics for (super)strings propagating over it. We explicitly use the \textit{Kovacic's algorithm} in order to establish non-chaotic dynamics of string $ \sigma $ models over these deformed back

Qiu-ping Yang, Feng Wang, Hui Deng, Ying Mei

As a dedicated solar radioheliograph, the MingantU SpEctral RadioHeliograph (MUSER) has a maximum baseline of more than 3000 meters and a frequency range of 400 MHz -- 15 GHz. According to the classical radio interferometry theory, the non-coplanar baseline effect (i.e., w-term effect) would be considered and calibrated for such a radio instrument. However,

Leishingam Kumrah, S. Surendra Singh, L. Anjana Devi, Md Khurshid Alam

In this work a new law of varying deceleration parameter of third degree have been proposed. The solutions of the modified field equations have been derived under the newly proposed law of the deceleration parameter. Model exhibits the Big-bang singularity at cosmic time ($t=0$) and shows Big Rip at ($t=n$) then it re-enter the phase of initial singularity a

Qingrong Cheng, Keyu Wen, Xiaodong Gu

Text-to-image synthesis aims to generate a photo-realistic and semantic consistent image from a specific text description. The images synthesized by off-the-shelf models usually contain limited components compared with the corresponding image and text description, which decreases the image quality and the textual-visual consistency. To address this issue, we

Wael Alghamdi, Shahab Asoodeh, Flavio P. Calmon, Juan Felipe Gomez

We introduce a new differential privacy (DP) accountant called the saddle-point accountant (SPA). SPA approximates privacy guarantees for the composition of DP mechanisms in an accurate and fast manner. Our approach is inspired by the saddle-point method -- a ubiquitous numerical technique in statistics. We prove rigorous performance guarantees by deriving u

Wei Zheng, Fengming Xue, Ming Zhang, Zhongyong Chen

Predicting disruptions across different tokamaks is a great obstacle to overcome. Future tokamaks can hardly tolerate disruptions at high performance discharge. Few disruption discharges at high performance can hardly compose an abundant training set, which makes it difficult for current data-driven methods to obtain an acceptable result. A machine learning

Ce Xu, Lu Yan, Jianqiang Zhao

In this paper, we define and study a variant of multiple zeta values (MZVs) of level four, called alternating multiple mixed values or alternating multiple $M$-values (AMMVs), forming a $\Q[i]$-subspace of the colored MZVs of level four. This variant includes the alternating version of Hoffman's multiple $t$-values, Kaneko-Tsumura's multiple $T$-values, and

Wentao Liu, Chaofan Ma, Yuhuan Yang, Weidi Xie

The goal of this paper is to interactively refine the automatic segmentation on challenging structures that fall behind human performance, either due to the scarcity of available annotations or the difficulty nature of the problem itself, for example, on segmenting cancer or small organs. Specifically, we propose a novel Transformer-based architecture for In

François Mazé, Faez Ahmed

Structural topology optimization, which aims to find the optimal physical structure that maximizes mechanical performance, is vital in engineering design applications in aerospace, mechanical, and civil engineering. Generative adversarial networks (GANs) have recently emerged as a popular alternative to traditional iterative topology optimization methods. Ho

Debo Cheng, Jiuyong Li, Lin Liu, Jixue Liu

In many fields of scientific research and real-world applications, unbiased estimation of causal effects from non-experimental data is crucial for understanding the mechanism underlying the data and for decision-making on effective responses or interventions. A great deal of research has been conducted to address this challenging problem from different angle

Chia-Min Lin

We investigate a static, cylindrically symmetric cosmic string on the brane without a perturbative approximation. We find there could be a (large) enhancement of the (effective) string tension when the energy density at the center of the string is (much) larger than twice the brane tension. We also point out a new way to evade the cosmic string problem when

Victor Adewopo, Nelly Elsayed, Zag ElSayed, Murat Ozer

Action detection and public traffic safety are crucial aspects of a safe community and a better society. Monitoring traffic flows in a smart city using different surveillance cameras can play a significant role in recognizing accidents and alerting first responders. The utilization of action recognition (AR) in computer vision tasks has contributed towards h

L. D. Blokhintsev, A. S. Kadyrov, A. M. Mukhamedzhanov, D. A. Savin

Asymptotic normalization coefficients (ANC) determine the overall normalization of cross sections of peripheral radiative capture reactions. In the present paper, we treat the ANC $C$ for the virtual decay $^{16}$O$(0^+; 6.05$ MeV)$\to \alpha+^{12}$C(g.s.), the known values of which are characterized by a large spread $(0.29-1.65)\times 10^3$ fm$^{-1/2}$. Th

Sichun Luo, Xinyi Zhang, Yuanzhang Xiao, Linqi Song

The recent popularity of edge devices and Artificial Intelligent of Things (AIoT) has driven a new wave of contextual recommendations, such as location based Point of Interest (PoI) recommendations and computing resource-aware mobile app recommendations. In many such recommendation scenarios, contexts are drifting over time. For example, in a mobile game rec

Michał Dereziński, Elizaveta Rebrova

Sketch-and-project is a framework which unifies many known iterative methods for solving linear systems and their variants, as well as further extensions to non-linear optimization problems. It includes popular methods such as randomized Kaczmarz, coordinate descent, variants of the Newton method in convex optimization, and others. In this paper, we develop

Amir N. Khan

We explore the possibility of relating extra dimensions with light and heavy Dirac-type neutral leptons and develop a framework for testing them in various laboratory experiments. The Kaluza-Klein modes in the large extra dimension models of the light neutral leptons could mix with the standard model neutrinos and produce observable effects in the oscillatio

Gergely Csáji, Tamás Király, Yu Yokoi

The Stable Marriage problem (SM), solved by the famous deferred acceptance algorithm of Gale and Shapley (GS), has many natural generalizations. If we allow ties in preferences, then the problem of finding a maximum stable matching becomes NP-hard, and the best known approximation ratio is 1.5 (McDermid 2009, Paluch 2011, Z. Kir\'aly 2012), achievable by run

Aaron S. Wolf, Noah Jäggi, Paolo A. Sossi, Dan J. Bower

Silicate vapors play a key role in planetary evolution, especially dominating early stages of rocky planet formation through outgassed magma ocean atmospheres. Our open-source thermodynamic modeling software "VapoRock" combines the MELTS liquid model (Ghiorso et al., 1995) with gas-species properties from multiple thermochemistry tables (e.g., Chase et al.,

Junji Fujimoto

The quantum field theoretical approach with the Kubo formula has successfully captured spin torques, such as spin-transfer torques and spin-orbit torques, for continuum systems. We examine the field theoretical approach to current-induced spin-transfer torques in a magnetic junction system. We first give a brief overview of the field theoretical approach to

Sami Alperen Akgun, Moojan Ghafurian, Mark Crowley, Kerstin Dautenhahn

Emotions can provide a natural communication modality to complement the existing multi-modal capabilities of social robots, such as text and speech, in many domains. We conducted three online studies with 112, 223, and 151 participants to investigate the benefits of using emotions as a communication modality for Search And Rescue (SAR) robots. In the first e

Yake Wei, Di Hu, Yapeng Tian, Xuelong Li

Sight and hearing are two senses that play a vital role in human communication and scene understanding. To mimic human perception ability, audio-visual learning, aimed at developing computational approaches to learn from both audio and visual modalities, has been a flourishing field in recent years. A comprehensive survey that can systematically organize and

Zhenrui Yue, Huimin Zeng, Ziyi Kou, Lanyu Shang

Despite recent progress in improving the performance of misinformation detection systems, classifying misinformation in an unseen domain remains an elusive challenge. To address this issue, a common approach is to introduce a domain critic and encourage domain-invariant input features. However, early misinformation often demonstrates both conditional and lab

Yan Ke, Minqing Zhang, Xinpeng Zhang, Yiliang Han

Considering the prospects of public key embedding (PKE) mechanism in active forensics on the integrity or identity of ciphertext for distributed deep learning security, two reversible data hiding in encrypted domain (RDH-ED) algorithms with PKE mechanism are proposed, in which all the elements of the embedding function shall be open to the public, while the

Xudong Gong, Qinlin Feng, Yuan Zhang, Jiangling Qin

Short video applications have attracted billions of users in recent years, fulfilling their various needs with diverse content. Users usually watch short videos on many topics on mobile devices in a short period of time, and give explicit or implicit feedback very quickly to the short videos they watch. The recommender system needs to perceive users' prefere

Jinsoo Park, Yao Luo, Jin-Jian Zhou, Marco Bernardi

First-principles calculations enable accurate predictions of electronic interactions and dynamics. However, computing the electron spin dynamics remains challenging. The spin-orbit interaction causes various dynamical phenomena that couple with phonons, such as spin precession and spin-flip e-ph scattering, which are difficult to describe with current first-

W. Shi, Y. Li, R. C. de Lamare

A novel sparse array (SA) structure is proposed based on the maximum inter-element spacing (IES) constraint (MISC) criterion. Compared with the traditional MISC array, the proposed SA configurations, termed as improved MISC (IMISC) has significantly increased uniform degrees of freedom (uDOF) and reduced mutual coupling. In particular, the IMISC arrays are c

Michael Famiano, Grant Mathews, A. Baha Balantekin, Toshitaka Kajino

We report on the effects of strong magnetic fields on neutrino emission in the modified Urca process. We show that the effect of Landau levels on the various Urca pairs affects the neutrino emission spectrum and leads to an angular asymmetry in the neutrino emission. For low magnetic fields the Landau levels have almost no effect on the cooling. However, as

Huanhuan Yang, Lingling Song, Yunshan Cao, Peng Yan

Long-range interactions (LRIs) are ubiquitous in nature. Higher-order topological (HOT) insulator represents a new phase of matter. A critical issue is how LRI dictates the HOT phases. In this work, we discover four topologically distinct phases, i.e., HOT phase, the bound state in the continuum, Dirac semimetal (DSM) phase, and trivial insulator phase in a

Huicong Li, Tian Xiang

In this work, we study global existence, boundedness and convergence of nonnegative classical solutions of a Neumann initial-boundary value problem for a cross diffusive SIS (susceptible-infected-susceptible) epidemic model with power-like infection mechanism generalizing the standard mass action mechanism. Global existence and boundedness of classical solut

Erik Jenner, Herke van Hoof, Adam Gleave

In reinforcement learning, different reward functions can be equivalent in terms of the optimal policies they induce. A particularly well-known and important example is potential shaping, a class of functions that can be added to any reward function without changing the optimal policy set under arbitrary transition dynamics. Potential shaping is conceptually

Ang Li, Judea Pearl

The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one way if encouraged and a different way if not encouraged. Using a combination of experimental and observational data, Li and Pearl derived tight bounds on the "benefit function", w

Harold R. Parks, Dean C. Wills

The egg-drop experiment introduced by Konhauser, Velleman, and Wagon, later generalized by Boardman, is further generalized to two additional types. The three separate types of egg-drop experiment under consideration are examined in the context of binary decision trees. It is shown that all three types of egg-drop experiment are binary decision problems that

Ang Li, Judea Pearl

This paper deals with the problem of estimating the probabilities of causation when treatment and effect are not binary. Tian and Pearl derived sharp bounds for the probability of necessity and sufficiency (PNS), the probability of sufficiency (PS), and the probability of necessity (PN) using experimental and observational data. In this paper, we provide the

Ayush Singla, Qingyu Zhao, Daniel K. Do, Yuyin Zhou

For the first time, we propose using a multiple instance learning based convolution-free transformer model, called Multiple Instance Neuroimage Transformer (MINiT), for the classification of T1weighted (T1w) MRIs. We first present several variants of transformer models adopted for neuroimages. These models extract non-overlapping 3D blocks from the input vol

Teruyuki Kitabayashi

If mirror matter exists but cannot comprise all of the dark matter (DM) in the universe, we can expect that the additional DM component may only interact with the other sectors gravitationally. One of the natural candidate of a gravitationally interacting component is a primordial black hole (PBH). Therefore, if mirror matter exists but cannot comprise all o

Jared McDonald, Michael R. von Spakovsky, William T. Reynolds

The Replica Exchange Wang-Landau Method is used to estimate the energy landscape of a polymer composed of a simple hydrophobic and polar sequence using the HP protein model. Calculations of state transitions between the energy levels of the derived energy landscape are made using an equation of motion from the steepest-entropy-ascent quantum thermodynamic (S

Elvis A. Agüero, Luke Alventosa, Daniel M. Harris, Carlos A. Galeano-Rios

We study the axisymmetric impact of a rigid sphere onto an elastic membrane theoretically and experimentally. We derive governing equations from first principles and impose natural kinematic and geometric constraints for the coupled motion of the sphere and the membrane during contact. The free-boundary problem of finding the contact surface, over which forc

Rasoul Kheiri, Alexey A Tsukanov, Nikolai V Brilliantov

We performed molecular dynamics (MD) experiments to explore dry sliding friction at the nanoscale. We used the setup comprised of a spherical particle built up of 32,000 aluminium atoms, resting on a semi-space with a free surface, modelled by a stack of merged graphene layers. We utilized LAMMPS with the COMB3 many-body potentials for the inter-atomic inter

Sohan Bendre, Shiva Maharaj, Nick Polson, Vadim Sokolov

How likely is it that Magnus Carlsen will achieve an Elo rating of $2900$? This has been a goal of Magnus and is of great current interest to the chess community. Our paper uses probabilistic methods to address this question. The probabilistic properties of Elo's rating system have long been studied, and we provide an application of such methods. By applying

Shichao Xu, Yikang Li, Jenhao Hsiao, Chiuman Ho

In computer vision, multi-label recognition are important tasks with many real-world applications, but classifying previously unseen labels remains a significant challenge. In this paper, we propose a novel algorithm, Aligned Dual moDality ClaSsifier (ADDS), which includes a Dual-Modal decoder (DM-decoder) with alignment between visual and textual features,