August 2022 arXiv papers — page 55

Allan Merino, Hadi Salmasian

In this paper, we obtain a full classification of reductive dual pairs in a, real or complex, Lie superalgebra $\mathfrak{spo}(E)$ and Lie supergroup $\textbf{SpO}(E)$. Moreover, by looking at the natural action of the orthosymplectic Lie supergroup $\textbf{SpO}(E)$ on the Weyl-Clifford algebra $\textbf{WC}(E)$, we prove that for a reductive dual pair $(\ma

Vance Blankers, Sebastian Bozlee

In this paper, we study all ways of constructing modular compactifications of the moduli space $\mathcal{M}_{g,n}$ of $n$-pointed smooth algebraic curves of genus $g$ by allowing markings to collide. We find that for any such compactification, collisions of markings are controlled by a simplicial complex which we call the collision complex. Conversely, we id

Ritesh Ahuja, Sepanta Zeighami, Gabriel Ghinita, Cyrus Shahabi

Several companies (e.g., Meta, Google) have initiated "data-for-good" projects where aggregate location data are first sanitized and released publicly, which is useful to many applications in transportation, public health (e.g., COVID-19 spread) and urban planning. Differential privacy (DP) is the protection model of choice to ensure the privacy of the indiv

Talat Nazir, Mujahid Abbas, Sergei Silvestrov

Fixed point results of Perov type mapping which satisfy generalized Tcontractive conditions in the setup of cone b-metric spaces associated with generalized c-distance are proved and illustrated by nontrivial examples.

Jiaqi Jiang, Guanqun Cao, Aaron Butterworth, Thanh-Toan Do

Picking up transparent objects is still a challenging task for robots. The visual properties of transparent objects such as reflection and refraction make the current grasping methods that rely on camera sensing fail to detect and localise them. However, humans can handle the transparent object well by first observing its coarse profile and then poking an ar

Lorenzo Gavassino, Marcelo M. Disconzi

We prove that the classical Dirac equation in the presence of an external (nondynamical) electromagnetic field is a relativistically causal theory. As a corollary, we show that it is impossible to use quantum tunneling to transmit particles or information faster than light. When an electron tunnels through a barrier, it is bound to remain within its future l

Anomadarshi Barua, Mohammad Abdullah Al Faruque

Sensors are one of the most pervasive and integral components of today's safety-critical systems. Sensors serve as a bridge between physical quantities and connected systems. The connected systems with sensors blindly believe the sensor as there is no way to authenticate the signal coming from a sensor. This could be an entry point for an attacker. An attack

K. R. Jayaram, Ashish Verma, Gegi Thomas, Vinod Muthusamy

The increasing number and scale of federated learning (FL) jobs necessitates resource efficient scheduling and management of aggregation to make the economics of cloud-hosted aggregation work. Existing FL research has focused on the design of FL algorithms and optimization, and less on the efficacy of aggregation. Existing FL platforms often employ aggregato

Angela Weiss

We propose a polynomially bounded, in time and space, method to decide whether a given 3-SAT formula is satisfiable or not. The tools we use here are, in fact, very simple. We first decide satisfiability for a particular 3-SAT formula, called pivoted 3-SAT and, after a plain transformation, still keeping the polynomial boundaries, it is shown that 3-SAT form

Angel Garcia-Chung, Matthew F. Carney, James B. Mertens, Aliasghar Parvizi

We compute the expected response of detector arms of gravitational wave observatories to polymerized gravitational waves. The mathematical and theoretical features of these waves were discussed in our previous work. In the present manuscript, we find both perturbative analytical, and full nonperturbative numerical solutions to the equations of motion of the

Alexander Perepechko, Mikhail Zaidenberg

It is known that the identity component of the automorphism group of a projective algebraic variety is an algebraic group. This is not true in general for quasi-projective varieties. In this note we address the question: given an affine algebraic surface $Y$, as to when the identity component ${\rm Aut}^0 (Y)$ of the automorphism group ${\rm Aut} (Y)$ is an

Yisong Yang

We derive the equations of motion governing static dyonic matters, described in terms of two real scalar fields, in nonlinear electrodynamics of the Born--Infeld theory type. We then obtain exact finite-energy solutions of these equations in the quadratic and logarithmic nonlinearity cases subject to dyonic point-charge sources and construct dyonically charg

Yanyong Huang, Zongxin Shen, Yuxin Cai, Xiuwen Yi

Multi-view unsupervised feature selection (MUFS) has been demonstrated as an effective technique to reduce the dimensionality of multi-view unlabeled data. The existing methods assume that all of views are complete. However, multi-view data are usually incomplete, i.e., a part of instances are presented on some views but not all views. Besides, learning the

Mingxi Zhu, Yinyu Ye

Distributed optimization algorithms are widely used in machine learning. This paper investigates how a small amount of data sharing can improve their performance. Focusing on general linear models, we analyze the effects of data sharing on both primal and primal-dual optimization methods. Our contributions are threefold. First, from a theoretical perspective

Xu Cheng, Chendan Li, Xiufeng Liu

With increasing concerns for data privacy and ownership, recent years have witnessed a paradigm shift in machine learning (ML). An emerging paradigm, federated learning (FL), has gained great attention and has become a novel design for machine learning implementations. FL enables the ML model training at data silos under the coordination of a central server,

Gyuhak Kim, Zixuan Ke, Bing Liu

This paper studies class incremental learning (CIL) of continual learning (CL). Many approaches have been proposed to deal with catastrophic forgetting (CF) in CIL. Most methods incrementally construct a single classifier for all classes of all tasks in a single head network. To prevent CF, a popular approach is to memorize a small number of samples from pre

Alonso Contreras-Astorga, David J. Fernández C., César Muro-Cabral

In this work, we generate a family of quantum potentials that are non-rational extensions of the harmonic oscillator. Such a family can be obtained via two different but equivalent supersymmetric transformations. We construct ladder operators for these extensions as the product of the intertwining operators of both transformations. Then, we generate families

Mikko Parviainen

The objective is the interplay between stochastic processes and partial differential equations. To be more precise, we focus on the connection between the nonlinear p-Laplace equation, and the stochastic game called tug-of-war with noise. The connection in this context was discovered roughly 15 years ago, and has provided novel insight and approaches ever si

Jianbo Wang, Chao Xu, Siyun Zhou

Let $\mathbb{F}$ be any field, we consider solving $Ax=b$ repeatedly for a matrix $A\in\mathbb{F}^{n\times n}$ of $m$ non-zero elements, and multiple different $b\in\mathbb{F}^{n}$. If we are given a zero forcing set of $A$ of size $k$, we can then build a data structure in $O(mk)$ time, such that each instance of $Ax=b$ can be solved in $O(k^2+m)$ time. As

Ethan Smith, Ilham Variansyah, Ryan McClarren

We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as $\alpha$ eigenvalues) by extending the dynamic mode decomposition (DMD) to allow for non-uniform time steps. The new method, called variable dynamic mode decomposition (VDMD), is shown to be accurate when computing eigenvalues for systems that were infe

Mustafa Basaran, Tevfik Can Yüce, Yusuf Ilker Yaman, Roman Vetter

Bacterial biofilms collectively develop distinct and ordered structures, including fibers, bundles, and branches. Often, it is unclear how these structural motifs convey specific advantages to bacterial strains under challenging conditions. In oxygen-limited environments, dense bacterial aggregates generally deplete oxygen, which leads to arrest of bacterial

Erik A. R. Mendoza

Let $K$ be the algebraic closure of $\mathbb{F}_{q}$. We provide an explicit description of the Weierstrass semigroup $H(Q_\infty)$ at the only place at infinity $Q_{\infty}$ of the curve $\mathcal{X}$ defined by the Kummer extension with equation $y^m=f(x)$, where $f(x)\in K[x]$ is a polynomial satisfying $\gcd (m, \text{deg} f)=1$. As a consequence, we det

Gabriel Adam Bilato, Cleber Damião Rocco, Anibal Tavares de Azevedo

The Vehicle Routing Problem (VRP) has been widely studied throughout its history as a way of optimizing routes by minimizing distances, and the issue of risk in VRP has been received less attention, which is essential to increase transport safety, to reduce accident costs and to improve delivery reliability. In this way, this paper aims to support decision m

Gustavo Sandoval, Hammond Pearce, Teo Nys, Ramesh Karri

Large Language Models (LLMs) such as OpenAI Codex are increasingly being used as AI-based coding assistants. Understanding the impact of these tools on developers' code is paramount, especially as recent work showed that LLMs may suggest cybersecurity vulnerabilities. We conduct a security-driven user study (N=58) to assess code written by student programmer

Abdessamad Dehaj, Mohamed Guessous, Noureddine Sabiri

We provide a permutation-invariant version of the Koml\'os' theorem for non-negative random variables. The proof is quite elementary in the sense that it did not use the Axiom of Choice, and was based on a recent result in [3].

Johannes O. Royset

In the context of structured nonconvex optimization, we estimate the increase in minimum value for a decision that is robust to parameter perturbations as compared to the value of a nominal problem. The estimates rely on detailed expressions for subgradients and local Lipschitz moduli of min-value functions in nonconvex robust optimization and require only t

Wesley Fussner, Nick Galatos

Semiconic idempotent logic sCI is a common generalization of intuitionistic logic, semilinear idempotent logic sLI, and in particular relevance logic with mingle. We establish the projective Beth definability property and the deductive interpolation property for many extensions of sCI, and identify extensions where these properties fail. We achieve these res

HanQin Cai, Longxiu Huang, Pengyu Li, Deanna Needell

While uniform sampling has been widely studied in the matrix completion literature, CUR sampling approximates a low-rank matrix via row and column samples. Unfortunately, both sampling models lack flexibility for various circumstances in real-world applications. In this work, we propose a novel and easy-to-implement sampling strategy, coined Cross-Concentrat

Sean Cox, Matthew Elpers

Hardin and Taylor \cite{MR2384262} proved that any function on the reals -- even a nowhere continuous one -- can be correctly predicted, based solely on its past behavior, at almost every point in time. They showed in \cite{MR3100500} that one could even arrange for the predictors to be robust with respect to simple time shifts, and asked whether they could

Evgeny Mukhin, Alexander Varchenko

We study the qKZ difference equations with values in the $n$-th tensor power of the vector $sl_2$ representation $V$, variables $z_1,\dots,z_n$ and integer step $\kappa$. For any integer $N$ relatively prime to the step $\kappa$, we construct a family of polynomials $f_r(z)$ in variables $z_1,\dots,z_n$ with values in $V^{\otimes n}$ such that the coordinate

Raj Agrawal, Prarthana Bhatia, Kratik Gupta, Powers Lamb

A $\textit{covering system}$ is a collection of integer congruences such that every integer satisfies at least one congruence in the collection. A covering system is called $\textit{distinct}$ if all of its moduli are distinct. An expansive literature has developed on covering systems since their introduction by Erd\H{o}s. Here we provide a full classificati

Animesh Nighojkar, Anna Khlyzova, John Licato

Can deep language models be explanatory models of human cognition? If so, what are their limits? In order to explore this question, we propose an approach called hyperparameter hypothesization that uses predictive hyperparameter tuning in order to find individuating descriptors of cognitive-behavioral profiles. We take the first step in this approach by pred

Abhineet Singh Rajput, Sarath Chandra Varma, Aloke Kumar

We present a theoretical framework for capturing the coalescence of a pendant drop with a sessile drop in polymeric fluids. The framework is based on the unification of various constitutive laws under high Weissenberg creeping flow limit. Our results suggests that the phenomenon comes under a new regime namely, the sub-Newtonian regime followed by the limiti

Jianpeng Yang, Yuhang Niu, Xuemei Xie, Guangming Shi

Few-shot learning (FSL) aims to learn a classifier that can be easily adapted to recognize novel classes with only a few labeled examples. Some recent work about FSL has yielded promising classification performance, where the image-level feature is used to calculate the similarity among samples for classification. However, the image-level feature ignores abu

Wenxuan Yu, Minghui Xu, Dongxiao Yu, Xiuzhen Cheng

Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy issues including balance secrecy, relationship anonymity and payment privacy. Moreover, protecting privacy causes low transaction success rates. To address this dilemma, we propose

Nikhil Goel, Ranjith Reddy

This work is about finding the similarity between a pair of news articles. There are seven different objective similarity metrics provided in the dataset for each pair and the news articles are in multiple different languages. On top of the pre-trained embedding model, we calculated cosine similarity for baseline results and feed-forward neural network was t

Alok Shukla, Prakash Vedula

A hybrid classical-quantum approach for evaluation of multi-dimensional Walsh-Hadamard transforms and its applications to quantum image processing are proposed. In this approach, multidimensional Walsh-Hadamard transforms are obtained using quantum Hadamard gates (along with state-preparation, shifting, scaling and measurement operations). The proposed appro

Ambrish Pandey, Dmitry Krasnov, Jörg Schumacher, Ravi Samtaney

To understand turbulent convection at very high Rayleigh numbers typical of natural phenomena, computational studies in slender cells are an option if the needed resources have to be optimized within available limits. However, the accompanying horizontal confinement affects some properties of the flow. Here, we explore the characteristics of turbulent fluctu

Derek Shank, Timothy C. Beers, Vinicius M. Placco, Dmitrii Gudin

Orbital characteristics based on Gaia Early Data Release 3 astrometric parameters are analyzed for ${\sim} 1700$ $r$-process-enhanced (RPE; [Eu/Fe] $> +0.3$) metal-poor stars ([Fe/H] $\leq -0.8$) compiled from the $R$-Process Alliance, the GALactic Archaeology with HERMES (GALAH) DR3 survey, and additional literature sources. We find dynamical clusters of th

Yuhua Yin, Julian Jang-Jaccard, Fariza Sabrina, Jin Kwak

Machine learning algorithms have been widely used in intrusion detection systems, including Multi-layer Perceptron (MLP). In this study, we proposed a two-stage model that combines the Birch clustering algorithm and MLP classifier to improve the performance of network anomaly multi-classification. In our proposed method, we first apply Birch or Kmeans as an

Sheyda Peyman, Minh Tang, Vince Lyzinski

As graph data becomes more ubiquitous, the need for robust inferential graph algorithms to operate in these complex data domains is crucial. In many cases of interest, inference is further complicated by the presence of adversarial data contamination. The effect of the adversary is frequently to change the data distribution in ways that negatively affect sta

Amir Hossein Fahim Raouf

The current literature on quantum key distribution (QKD) is mainly limited to the transmissions over fiber optic, atmospheric or satellite links and are not directly applicable to underwater environments with different channel characteristics. Absorption, scattering, and turbulence experienced in underwater channels severely limit the range of quantum commun

Serj Aristarhov

In this paper we critically analyse W. Heisenberg's arguments against the ontology of point particles following trajectories in quantum theory, presented in his famous 1927 paper and in his Chicago lectures (1929). Along the way, we will clarify the meaning of Heisenberg's uncertainty relation and help resolve some confusions related to it.

Chowdhury Rafeed Rahman, MD. Hasibur Rahman, Samiha Zakir, Mohammad Rafsan

Bangla typing is mostly performed using English keyboard and can be highly erroneous due to the presence of compound and similarly pronounced letters. Spelling correction of a misspelled word requires understanding of word typing pattern as well as the context of the word usage. A specialized BERT model named BSpell has been proposed in this paper targeted t

Xinlin Li, Bang Liu, Rui Heng Yang, Vanessa Courville

Efficiently deploying deep neural networks on low-resource edge devices is challenging due to their ever-increasing resource requirements. To address this issue, researchers have proposed multiplication-free neural networks, such as Power-of-Two quantization, or also known as Shift networks, which aim to reduce memory usage and simplify computation. However,

Muhammad Ilyas

A quantum computer can perform exponentially faster than its classical counterpart. It works on the principle of superposition. But due to the decoherence effect, the superposition of a quantum state gets destroyed by the interaction with the environment. It is a real challenge to completely isolate a quantum system to make it free of decoherence. This probl

Zeyu Li, Ruizhi Shi, Yan Liu, Shizhuo Long

The overdraw problem of scatterplots seriously interferes with the visual tasks. Existing methods, such as data sampling, node dispersion, subspace mapping, and visual abstraction, cannot guarantee the correspondence and consistency between the data points that reflect the intrinsic original data distribution and the corresponding visual units that reveal th

Yanzeng Li, Lei Zou

We design a user-friendly and scalable knowledge graph construction (KGC) system for extracting structured knowledge from the unstructured corpus. Different from existing KGC systems, gBuilder provides a flexible and user-defined pipeline to embrace the rapid development of IE models. More built-in template-based or heuristic operators and programmable opera

Tangi Pasquer

In this article, we modify the classical Floer complex $CF(L_0,L_1)$ of a pair of two compact exact Lagrangian submanifolds $L_0,L_1$ of an exact symplectic 2-manifold $M$ into a $\mathbb{Z}_2[T]$-complex $CF_h(L_0,L_1)$, whose differential keeps track of how many times a pseudo-holomorphic strip passes through a distinguished point $h\in M$. We show that th

Sixiang Chen, Tian Ye, Yun Liu, Erkang Chen

Due to various and complicated snow degradations, single image desnowing is a challenging image restoration task. As prior arts can not handle it ideally, we propose a novel transformer, SnowFormer, which explores efficient cross-attentions to build local-global context interaction across patches and surpasses existing works that employ local operators or va

James R. Schatz

In this note we show that any proof of Wallis's formula or of the probability integral formula proves both assertions.

Csaba D. Tóth, Jorge Urrutia, Giovanni Viglietta

We prove that, given a polyhedron $\mathcal P$ in $\mathbb{R}^3$, every point in $\mathbb R^3$ that does not see any vertex of $\mathcal P$ must see eight or more edges of $\mathcal P$, and this bound is tight. More generally, this remains true if $\mathcal P$ is any finite arrangement of internally disjoint polygons in $\mathbb{R}^3$. We also prove that eve

S. Gupta, G. Longobardi, R. Trombetti

In [A. Neri, P. Santonastaso, F. Zullo. Extending two families of maximum rank distance codes], the authors extended the family of $2$-dimensional $\mathbb{F}_{q^{2t}}$-linear MRD codes recently found in [G. Longobardi, G. Marino, R. Trombetti, Y. Zhou. A large family of maximum scattered linear sets of $\mathrm{PG}(1,q^n)$ and their associated MRD codes]. A

CMS Collaboration

The first search is presented for vector-like leptons (VLLs) in the context of the "4321 model", an ultraviolet-complete model with the potential to explain existing B physics measurements that are in tension with standard model predictions. The analyzed data, corresponding to an integrated luminosity of 96.5 fb$^{-1}$, were recorded in 2017 and 2018 with th

Tahsin Aziz, Tashreef Muhammad, Md. Rashedul Karim Chowdhury, Mohammad Shafiul Alam

Numerous meta-heuristic algorithms have been influenced by nature. Over the past couple of decades, their quantity has been significantly escalating. The majority of these algorithms attempt to emulate natural biological and physical phenomena. This research concentrates on the Flower Pollination algorithm, which is one of several bio-inspired algorithms. Th

Ujjal Kr Dutta

While deep Embedding Learning approaches have witnessed widespread success in multiple computer vision tasks, the state-of-the-art methods for representing natural images need not necessarily perform well on images from other domains, such as paintings, cartoons, and sketch. This is because of the huge shift in the distribution of data from across these doma

Fehmi Can Ay, Nesim Bilici, Rahmetullah Varol, Atasangu Yilmaz

Creating the best possible conditions is essential for proper cell growth. Incubators, a type of biotechnological instrument, are used to simulate this condition and maintain the cells within them. The processes involved in creating a mobile incubator, which are essential for monitoring a cell culture's physiological parameters, are outlined in this article.

Kiran Sharma, Sudhanwa Patra

We present the approximated analytic expressions for the muon survival probability in a $3+1$ mixing scenario in the presence of matter effect using the S-matrix formalism. We find that all the individual terms contributing to the muon survival probability can significantly reduce to just three contributions. The leading order contribution comes from the thr

Andrea Giorgini, Patrik Knopf

We derive a novel thermodynamically consistent Navier--Stokes--Cahn--Hilliard system with dynamic boundary conditions. This model describes the motion of viscous incompressible binary fluids with different densities. In contrast to previous models in the literature, our new model allows for surface diffusion, a variable contact angle between the diffuse inte

Shingo Yashima

Knowledge distillation is an effective approach for training compact recognizers required in autonomous driving. Recent studies on image classification have shown that matching student and teacher on a wide range of data points is critical for improving performance in distillation. This concept (called function matching) is suitable for driving scene recogni

Chowdhury Rafeed Rahman

Data sparsity is a well-known problem for grammatical error correction (GEC). Generating synthetic training data is one widely proposed solution to this problem, and has allowed models to achieve state-of-the-art (SOTA) performance in recent years. However, these methods often generate unrealistic errors, or aim to generate sentences with only one error. We

George Marchant, Bora Karasulu, Livia B. Partay

In the present work we detail how the many-body potential energy landscape of interatomic potentials for carbon can be explored by utilising the nested sampling algorithm, allowing the calculation of their pressure-temperature phase diagram up to high pressures. We present a comparison of three interatomic potential models, Tersoff, EDIP and GAP-20, focusing

King Cho Wong, San Lam Ng, Kin On Ho, Yang Shen

Single color centers in solid have emerged as promising physical platforms for quantum information science. Creating these centers with excellent quantum properties is a key foundation for further technological developments. In particular, the microscopic understanding of the spin bath environments is the key to engineer color centers for quantum control. In

Denizalp Goktas, Amy Greenwald

Min-max optimization problems (i.e., min-max games) have attracted a great deal of attention recently as their applicability to a wide range of machine learning problems has become evident. In this paper, we study min-max games with dependent strategy sets, where the strategy of the first player constrains the behavior of the second. Such games are best unde

Rong Lu

IMPORTANCE: Time-to-event outcomes are commonly used in clinical trials and biomarker discovery studies and have been primarily analyzed using Cox proportional hazards models. But it's unclear which statistical models should be recommended for feature selection tasks when time-to-event outcomes are of the primary interest. OBJECTIVE: To explore if Gaussian r

Wentao Chao, Xuechun Wang, Yingqian Wang, Guanghui Wang

Light field (LF) depth estimation plays a crucial role in many LF-based applications. Existing LF depth estimation methods consider depth estimation as a regression problem, where a pixel-wise L1 loss is employed to supervise the training process. However, the disparity map is only a sub-space projection (i.e., an expectation) of the disparity distribution,

Mengmou Li, Jeremy Watson, Ioannis Lestas

Distributed secondary frequency control for power systems, is a problem that has been extensively studied in the literature, and one of its key features is that an additional communication network is required to achieve optimal power allocation. Therefore, being able to provide stability guarantees in the presence of communication delays is an important requ

Yuheng Shi, Naiyan Wang, Xiaojie Guo

Video object detection (VID) is challenging because of the high variation of object appearance as well as the diverse deterioration in some frames. On the positive side, the detection in a certain frame of a video, compared with that in a still image, can draw support from other frames. Hence, how to aggregate features across different frames is pivotal to V

V. Borka Jovanović, D. Borka, A. Arsenić, P. Jovanović

The goal of this paper is to investigate the flux and spectral index distribution of FR II radio galaxy 4C 14.11. We focused on the distribution of flux and spectral indices over the lobes, as well as in their hot spots. For that purpose, we used publicly available observations of this radio galaxy given at 1450 and 8440 MHz. Particularly, we used Leahy's At

Rajiv Movva, Jinhao Lei, Shayne Longpre, Ajay Gupta

Quantization, knowledge distillation, and magnitude pruning are among the most popular methods for neural network compression in NLP. Independently, these methods reduce model size and can accelerate inference, but their relative benefit and combinatorial interactions have not been rigorously studied. For each of the eight possible subsets of these technique

Ante Sikirica, Luka Grbčić, Lado Kranjčević

Microchannel heat sinks are an efficient cooling method for semiconductor packages. However, to properly cool increasingly complex and thermally dense circuits, microchannel designs should be improved and expanded on. In this paper, microchannel designs with secondary channels and with ribs are investigated using computational fluid dynamics and are coupled

Xifeng Su, Enrico Valdinoci, Yuanhong Wei, Jiwen Zhang

We consider the mixed local-nonlocal semi-linear elliptic equations driven by the superposition of Brownian and L\'evy processes \begin{equation*} \left\{ \begin{array}{ll} - \Delta u + (-\Delta)^s u = g(x,u) & \hbox{in $\Omega$,} u=0 & \hbox{in $\mathbb{R}^n\backslash\Omega$.} \\ \end{array} \right. \end{equation*} Under mild assumptions on the nonlinear te

Amit Acharya, Marshall Slemrod

This paper examines a system of partial differential equations describing dislocation dynamics in a crystalline solid. In particular we consider dynamics linearized about a state of zero stress and use linear semigroup theory to establish existence, uniqueness, and time asymptotic behavior of the linear system.

Hiromu Tanaka

Given a boundary divisor $B$ on a projective toric variety $X$ such that $(X, B)$ is klt, we establish the Kawamata-Viehweg vanishing theorem for $(X, B)$.

Maria Loseva, Alexandr Prishlyak

We investigate the topological structure of flows on the Girl's surfaces which is one of two possible immersions of the projective plane in three-dimensional space with one triple point of the selfintersection. First, we describe the cellular structure of the Boy's and Girl's surfaces and prove that there are unique images of the project plane in the form of

Siddartha Dalal, Sierra Vo, Michael Lesk, Wesley Yuan

Machine learning has been used to recognize emotions in faces, typically by looking for 8 different emotional states (neutral, happy, sad, surprise, fear, disgust, anger and contempt). We consider two approaches: feature recognition based on facial landmarks and deep learning on all pixels; each produced 58% overall accuracy. However, they produced different

Domenic Bersch, Kshitij Dwivedi, Martina Vilas, Radoslaw M. Cichy

We introduce Net2Brain, a graphical and command-line user interface toolbox for comparing the representational spaces of artificial deep neural networks (DNNs) and human brain recordings. While different toolboxes facilitate only single functionalities or only focus on a small subset of supervised image classification models, Net2Brain allows the extraction

Hongliang Zhang, Boya Di

The development of metasurfaces has unlocked various use cases in wireless communication networks to improve performance by manipulating the propagation environment. Intelligent omni-surface (IOS), an innovative technique in this category, is proposed for coverage extension. In contrast to the widely studied reflective metasurfaces, i.e., intelligent reflect

Jong-Phil Lee

We implement the $\chi^2$ fit for $R(K^{(*)})$ with possible tree-level new physics in a model-independent parametrization. Relevant Wilson coefficients are decomposed into the new physics scale, its power, and the fermionic couplings. Constraints from the branching ratio of $B_s\to\mu^+\mu^-$ can be naturally incorporated with the scheme. For a reasonable s

Sourav Mondal, Alessandro Lunghi

The study of how spin interacts with lattice vibrations and relaxes to equilibrium provides unique insights on its chemical environment and the relation between electronic structure and molecular composition. Despite its importance for several disciplines, ranging from magnetic resonance to quantum technologies, a convincing interpretation of spin dynamics i

Ali Akoglu, José-Luis Zechinelli-Martini, Hamamache Kheddouci, Genoveva Vargas-Solar

This paper discusses our vision of multirole-capable decision-making systems across a broad range of Data Science (DS) workflows working on graphs through disaggregated data centres. Our vision is that an alternative is possible to work on a disaggregated solution for the provision of computational services under the notion of a disaggregated data centre. We

Fumihide Takeda

Physical Wavelets can offer real-time significant and megathrust earthquake predictions and disaster prevention warnings up to three months in advance, saving lives and minimizing damages.

Genoveva Vargas-Solar, Pierre Marrec, Mirian Halfeld Ferrari Alves

This paper presents an experimental study to compare analysis tools with management systems for querying and analysing graphs. Our experiment compares classic graph navigational operations queries where analytics tools and management systems adopt different execution strategies. Then, our experiment addresses data science pipelines with clustering and predic

Foto N. Afrati

It is expensive to compute joins, often due to large intermediate relations. For acyclic joins, monotone join expressions are guaranteed to produce intermediate relations not larger than the size of the output of the join when it is computed on a fully reduced database. Any subexpression of an acyclic join does not offer this guarantee, as it is easy to prov

Aderson Farias do Nascimento, Martin A. Musicante, Umberto Souza da Costa, Bruno M. Carvalho

This paper describes and discusses our vision to develop and reason about best practices and novel ways of curating data-centric geosciences knowledge (data, experiments, models, methods, conclusions, and interpretations). This knowledge is produced from applying statistical modelling, Machine Learning, and modern data analytics methods on geo-data collectio

Zhimin Liu, Shenglin Zhu

For a quasi-triangular Hopf algebra $\left( H,R\right) $, there is a notion of transmuted braided group $H_{R}$ of $H$ introduced by Majid. The transmuted braided group $H_{R}$ is a Hopf algebra in the braided category $_{H}\mathcal{M}$. The $R$-adjoint-stable algebra associated with any simple left $H_{R}$-comodule is defined by the authors, and is used to

Yile Wang, Yue Zhang

Contextualized word embeddings in language models have given much advance to NLP. Intuitively, sentential information is integrated into the representation of words, which can help model polysemy. However, context sensitivity also leads to the variance of representations, which may break the semantic consistency for synonyms. We quantify how much the context

Jiawei Liu, Jing Zhang, Ruikai Cui, Kaihao Zhang

We propose a new setting that relaxes an assumption in the conventional Co-Salient Object Detection (CoSOD) setting by allowing the presence of "noisy images" which do not show the shared co-salient object. We call this new setting Generalised Co-Salient Object Detection (GCoSOD). We propose a novel random sampling based Generalised CoSOD Training (GCT) stra

Wei Li, Su-Yan Pei, Tianhong Wang, Ying-Long Wang

We study the electromagnetic (EM) decays of $X(3823)$ as the $\psi_2(1^{3}D_{2})$ state by using the relativistic Bethe-Salpeter method. Our results are $\Gamma[X(3823)\rightarrow\chi_{_{c0}}\gamma]=1.2$ keV, $\Gamma[X(3823)\rightarrow\chi_{_{c1}}\gamma]=265$ keV, $\Gamma[X(3823)\rightarrow\chi_{_{c2}}\gamma]=57$ keV and $\Gamma[X(3823)\rightarrow\eta_{_c}\g

Hyeongnam Jang, Yeejin Lee, Jong-Seok Lee

Assessing image aesthetics is a challenging computer vision task. One reason is that aesthetic preference is highly subjective and may vary significantly among people for certain images. Thus, it is important to properly model and quantify such \textit{subjectivity}, but there has not been much effort to resolve this issue. In this paper, we propose a novel

Jun Yuan, Mengchen Liu, Fengyuan Tian, Shixia Liu

Recent advances in artificial intelligence largely benefit from better neural network architectures. These architectures are a product of a costly process of trial-and-error. To ease this process, we develop ArchExplorer, a visual analysis method for understanding a neural architecture space and summarizing design principles. The key idea behind our method i

Haoran Xu, Yulu Huang, Rui Zhang, Yilin Wu

Elastic active matter or active solid consists of self-propelled units embedded in an elastic matrix. Active solid resists deformation; the shape-preserving property and the intrinsic non-equilibrium nature make active solids a superior component for self-driven devices. Nonetheless, the mechanical properties and emergent behavior of active solids are poorly

Shizheng Wen, Michael W. Lee, Kai M. Kruger Bastos, Earl H. Dowell

Recent efforts have shown machine learning to be useful for the prediction of nonlinear fluid dynamics. Predictive accuracy is often a central motivation for employing neural networks, but the pattern recognition central to the network function is equally valuable for purposes of enhancing our dynamical insight into confounding dynamics. In this paper, convo

Ujjwal Thakur, Anuj Sharma

Offline Handwritten Mathematical Expression Recognition (HMER) is a major area in the field of mathematical expression recognition. Offline HMER is often viewed as a much harder problem as compared to online HMER due to a lack of temporal information and variability in writing style. In this paper, we purpose a encoder-decoder model that uses paired adversar

Eugenija A. Bondar

We classify the $\mathscr{R}$-cross-sections of the monoid of order-preserving transformations on the $n$-element chain in terms of certain binary trees.

Leonardo N. Ferreira

Network science established itself as a prominent tool for modeling time series and complex systems. This modeling process consists of transforming a set or a single time series into a network. Nodes may represent complete time series, segments, or single values, while links define associations or similarities between the represented parts. R is one of the m

Jiachen Zhao, Haiqin Yang

Event detection (ED), aiming to detect events from texts and categorize them, is vital to understanding actual happenings in real life. However, mainstream event detection models require high-quality expert human annotations of triggers, which are often costly and thus deter the application of ED to new domains. Therefore, in this paper, we focus on low-reso

Elizaveta Vinogradova, Abay Artykbayev, Alisher Amanatay, Mukhamejan Karatayev

While generative models have recently become ubiquitous in many scientific areas, less attention has been paid to their evaluation. For molecular generative models, the state-of-the-art examines their output in isolation or in relation to its input. However, their biological and functional properties, such as ligand-target interaction is not being addressed.

Christofer Meinecke, Estelle Guéville, David Joseph Wrisley, Stefan Jänicke

Distant viewing approaches have typically used image datasets close to the contemporary image data used to train machine learning models. To work with images from other historical periods requires expert annotated data, and the quality of labels is crucial for the quality of results. Especially when working with cultural heritage collections that contain myr

Aristotelis Ballas, Christos Diou

Deep Learning systems have achieved great success in the past few years, even surpassing human intelligence in several cases. As of late, they have also established themselves in the biomedical and healthcare domains, where they have shown a lot of promise, but have not yet achieved widespread adoption. This is in part due to the fact that most methods fail