April 2023 arXiv papers — page 39

Jie Shao, Wei Yao, Puzuo Wang, Zhiyi He

Developments in three-dimensional real worlds promote the integration of geoinformation and building information models (BIM) known as GeoBIM in urban construction. Light detection and ranging (LiDAR) integrated with global navigation satellite systems can provide geo-referenced spatial information. However, constructing detailed urban GeoBIM poses challenge

Ihab Bendidi, Adrien Bardes, Ethan Cohen, Alexis Lamiable

Self-supervised representation learning in computer vision relies heavily on hand-crafted image transformations to learn meaningful and invariant features. However few extensive explorations of the impact of transformation design have been conducted in the literature. In particular, the dependence of downstream performances to transformation design has been

Surya Prakash Tiwari, Sudhir Kumar Chaturvedi, Subhrangshu Adhikary, Saikat Banerjee

The advancement of multi-channel synthetic aperture radar (SAR) system is considered as an upgraded technology for surveillance activities. SAR sensors onboard provide data for coastal ocean surveillance and a view of the oceanic surface features. Vessel monitoring has earlier been performed using Constant False Alarm Rate (CFAR) algorithm which is not a sma

Haichen Jia, Bowen Ma, Zidan Wang, Gang Chen

Based on the recent experiments on the triangular lattice antiferromagnet Na$_2$BaCo(PO$_4$)$_2$, we propose the easy-axis XXZ spin-1/2 model on the triangular lattice, that exhibits a quantum spin supersolid, to be a precursory Dirac spin liquid. Despite the presence of a three-sublattice magnetic order as a spin supersolid, we suggest that this system is c

Chunxiang Wang, Ran Li, Kai Zhu, Huanyuan Shan

We present the measurement of total and stellar/dark matter decomposed mass density profile around a sample of galaxy groups and clusters with dynamical masses derived from integral-field stellar kinematics from the MaNGA survey in Paper I and weak lensing derived from the DECaLS imaging survey. Combining the two data sets enables accurate measurement of the

Kai Zhu, Shengdong Lu, Michele Cappellari, Ran Li

We present dynamical scaling relations, combined with the stellar population properties, for a subsample of about 6000 nearby galaxies with the most reliable dynamical models extracted from the full MaNGA sample of 10K galaxies. We show that the inclination-corrected mass plane (MP) for both early-type galaxies (ETGs) and late-type galaxies (LTGs), which lin

Qusay Raghib Ali Al-Taai, Matěj Hejda, Weikang Zhang, Bruno Romeira

This work reports a nanostructure resonant tunnelling diode-photodetector (RTD-PD) device and demonstrates its operation as a controllable, optically-triggered excitable spike generator. The top contact layer of the device is designed with a nanopillar structure 500 nm in diameter) to restrain the injection current, yielding therefore lower energy operation

Shengdong Lu, Kai Zhu, Michele Cappellari, Ran Li

This is the second paper of the MaNGA DynPop series, which analyzes the global stellar population, radial gradients, and non-parametric star-formation history of $\sim 10$K galaxies from the MaNGA Survey final data release 17 (DR17) and relates them with dynamical properties of galaxies. We confirm the correlation between the stellar population properties an

Kai Zhu, Shengdong Lu, Michele Cappellari, Ran Li

This is the first paper in our series on the combined analysis of the Dynamics and stellar Population (DynPop) for the MaNGA survey in the final SDSS Data Release 17 (DR17). Here we present a catalogue of dynamically-determined quantities for over 10000 nearby galaxies based on integral-field stellar kinematics from the MaNGA survey. The dynamical properties

Patrick Dorey, Anastasia Gorina, Tomasz Romańczukiewicz, Yakov Shnir

We investigate soliton collisions a one-parameter family of scalar field theories in 1+1 dimensions which was first discussed by Christ and Lee. The models have a sextic potential with three local minima, and for suitably small values of the parameter its kinks have an internal structure in the form of two weakly-bound subkinks. We show that for these values

Vladimir Drinfeld

Let G be a smooth group scheme over $F_p$ equipped with a $G_m$-action such that all weights of $G_m$ on the Lie algebra of G are not greater than 1. Let $Disp_n^G$ be Eike Lau's stack of n-truncated G-displays (this is an algebraic stack over $F_p$). In the case n=1 we introduce an algebraic stack equipped with a morphism to $Disp_1^G$. We conjecture that i

Wonjun Yi, Jung-Woo Choi, Jae-Woo Lee

The drone has been used for various purposes, including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur. To improve the safety of drone operations, one should detect the mechanical faults of drones in real-time. This paper p

Céline Ruscher, Robinson Cortes-Huerto, Robert Hannebauer, Debashish Mukherji

Using large scale molecular dynamics simulations, we study the thermal conductivity of bare and surface passivated silicon nanowires (SiNWs). For the cross-sectional widths $w \le 2$ nm, SiNWs become unstable because of the surface amorphosization and also due to the evaporation of a certain fraction of Si atoms. The observed surface (in-)stability is relate

Shay Dekel, Yosi Keller, Aharon Bar-Hillel

We propose a novel formulation of deep networks that do not use dot-product neurons and rely on a hierarchy of voting tables instead, denoted as Convolutional Tables (CT), to enable accelerated CPU-based inference. Convolutional layers are the most time-consuming bottleneck in contemporary deep learning techniques, severely limiting their use in Internet of

Cristiano Saltori, Aljoša Ošep, Elisa Ricci, Laura Leal-Taixé

The ability to deploy robots that can operate safely in diverse environments is crucial for developing embodied intelligent agents. As a community, we have made tremendous progress in within-domain LiDAR semantic segmentation. However, do these methods generalize across domains? To answer this question, we design the first experimental setup for studying dom

Saideep Pavuluri, Ran Holtzman, Luqman Kazeem, Malyah Mohammed

Direct numerical simulations are used to elucidate the interplay of wettability and fluid viscosities on immiscible fluid displacements in a heterogeneous porous medium.We classify the flow regimes based using qualitative and quantitative analysis into viscous fingering (low $M$), compact displacement (high $M$), and an intermediate transition regime ($M \ap

Md. Tarek Hasan, Mohammad Nazmush Shamael, Arifa Akter, Rokibul Islam

Sustainable development is a framework for achieving human development goals. It provides natural systems' ability to deliver natural resources and ecosystem services. Sustainable development is crucial for the economy and society. Artificial intelligence (AI) has attracted increasing attention in recent years, with the potential to have a positive influence

Jiawei Xiong, Olga Fink, Jian Zhou, Yizhong Ma

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic data that is physically plausible is a promising way to tackle this challenge. In this study, a novel hyb

Di Wang, Bo Du, Liangpei Zhang, Dacheng Tao

Recent neural architecture search (NAS) based approaches have made great progress in hyperspectral image (HSI) classification tasks. However, the architectures are usually optimized independently of the network weights, increasing searching time and restricting model performances. To tackle these issues, in this paper, different from previous methods that ex

Matteo Castellani, Owen Medeiros, Reed A. Foster, Alessandro Buzzi

Decreasing the number of cables that bring heat into the cryostat is a critical issue for all cryoelectronic devices. Especially, arrays of superconducting nanowire single-photon detectors (SNSPDs) could require more than $10^6$ readout lines. Performing signal processing operations at low temperatures could be a solution. Nanocryotrons, superconducting nano

Seth Bassetti, Brian Hutchinson, Claudia Tebaldi, Ben Kravitz

Earth System Models (ESMs) are essential tools for understanding the impact of human actions on Earth's climate. One key application of these models is studying extreme weather events, such as heat waves or dry spells, which have significant socioeconomic and environmental consequences. However, the computational demands of running a sufficient number of sim

Pierre Gervais, Bertrand Lods

Triggered by the fact that, in the hydrodynamic limit, several different kinetic equations of physical interest all lead to the same Navier-Stokes-Fourier system, we develop in the paper an abstract framework which allows to explain this phenomenon. The method we develop can be seen as a significant improvement of known approaches for which we fully exploit

Xinyu Zhang, Zhiwei Li, Zhenhong Zou, Xin Gao

Noise has always been nonnegligible trouble in object detection by creating confusion in model reasoning, thereby reducing the informativeness of the data. It can lead to inaccurate recognition due to the shift in the observed pattern, that requires a robust generalization of the models. To implement a general vision model, we need to develop deep learning m

Alexandru Pascadi

We show that smooth numbers are equidistributed in arithmetic progressions to moduli of size $x^{66/107-o(1)}$. This overcomes a longstanding barrier of $x^{3/5-o(1)}$ present in previous works of Bombieri-Friedlander-Iwaniec, Fouvry-Tenenbaum, Drappeau, and Maynard. We build on Drappeau's variation of the dispersion method and on exponential sum manipulatio

Pishtiwan Othman Sabir, Ravi P. Agarwal, Shabaz Jalil MohammedFaeq, Pshtiwan Othman Mohammed

Making use of the Hankel determinant and the Ruscheweyh derivative, in this work, we consider a general subclass of m-fold symmetric normalized bi-univalent functions defined in the open unit disk. Moreover, we investigate the bounds for the second Hankel determinant of this class and some consequences of the results are presented. In addition, to demonstrat

Xinchen Li, Levent Guvenc, Bilin Aksun-Guvenc

This paper presents methods for vehicle state estimation and prediction for autonomous driving. A roundabout is chosen to apply the methods and illustrate the results as autonomous vehicles have difficulty in handling roundabouts. State estimation based on the unscented Kalman filter (UKF) is introduced first with application to a roundabout. The microscopic

Noam Buckman, Sertac Karaman, Daniela Rus

Semi-cooperative behaviors are intrinsic properties of human drivers and should be considered for autonomous driving. In addition, new autonomous planners can consider the social value orientation (SVO) of human drivers to generate socially-compliant trajectories. Yet the overall impact on traffic flow for this new class of planners remain to be understood.

Inyoung Paik, Jaesik Choi

Deep neural networks, which employ batch normalization and ReLU-like activation functions, suffer from instability in the early stages of training due to the high gradient induced by temporal gradient explosion. In this study, we analyze the occurrence and mitigation of gradient explosion both theoretically and empirically, and discover that the correlation

William Linz

In this note, we improve the lower bounds for the maximum size of the $k$th largest eigenvalue of the adjacency matrix of a graph for several values of $k$. In particular, we show that closed blowups of the icosahedral graph improve the lower bound for the maximum size of the fourth largest eigenvalue of a graph, answering a question of Nikiforov.

Jaehoon Kim, Hyunwoo Lee

Hansel's lemma states that $\sum_{H\in \mathcal{H}}|H| \geq n \log_2 n$ holds where $\mathcal{H}$ is a collection of bipartite graphs covering all the edges of $K_n$. We generalize this lemma to the corresponding multigraph covering problem and the graphon covering problem. We also prove an upper bound on $\sum_{H\in \mathcal{H}}|H|$ which shows that our gen

Yury A. Neretin

We consider the subalgebra $\Delta$ in the group algebra of the symmetric group $G=S_{n_1+\dots+n_\nu}$ consisting of all functions invariant with respect to left and right shifts by elements of the Young subgroup $H:=S_{n_1}\times \dots \times S_{n_\nu}$. We discuss structure constants of the algebra $\Delta$ and construct an algebra with continuous paramet

Tim Engel

We study the soft limit of one-photon radiation at next-to-leading power (NLP) in the framework of heavy-quark effective theory (HQET) to all orders in perturbation theory. We establish the soft theorem that for unpolarised scattering the radiative contribution up to NLP is entirely determined by the non-radiative amplitude. This generalises the Low-Burnett-

Wei Ju, Xiao Luo, Meng Qu, Yifan Wang

This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adopt graph neural networks to learn graph-level representations for classification, failing to explicitly leverage features derived from graph topology (e.g., paths). Moreover, when l

Alexander Alexandrov, Boris Bychkov, Petr Dunin-Barkowski, Maxim Kazarian

For a given spectral curve, we construct a family of symplectic dual spectral curves for which we prove an explicit formula expressing the $n$-point functions produced by the topological recursion on these curves via the $n$-point functions on the original curve. As a corollary, we prove topological recursion for the generalized fully simple maps generating

Tsz-On Li, Wenxi Zong, Yibo Wang, Haoye Tian

Automatically detecting software failures is an important task and a longstanding challenge. It requires finding failure-inducing test cases whose test input can trigger the software's fault, and constructing an automated oracle to detect the software's incorrect behaviors. Recent advancement of large language models (LLMs) motivates us to study how far this

Magnus Falkenberg, Anders Bensen Ottsen, Mathias Ibsen, Christian Rathgeb

We address the need for a large-scale database of children's faces by using generative adversarial networks (GANs) and face age progression (FAP) models to synthesize a realistic dataset referred to as HDA-SynChildFaces. To this end, we proposed a processing pipeline that initially utilizes StyleGAN3 to sample adult subjects, which are subsequently progresse

Yu Zheng, Sridhar Babu Mudhangulla, Olugbenga Moses Anubi

Systematic attack design is essential to understanding the vulnerabilities of cyber-physical systems (CPSs), to better design for resiliency. In particular, false data injection attacks (FDIAs) are well-known and have been shown to be capable of bypassing bad data detection (BDD) while causing targeted biases in resulting state estimates. However, their effe

Vishakha Ramani, Jiachen Chen, Roy D. Yates

We examine status updating systems in which time-stamped status updates are stored/written in shared-memory. Specifically, we compare Read-Copy-Update (RCU) and Readers-Writer lock (RWL) as shared-memory synchronization primitives on the update freshness. To demonstrate the tension between readers and writers accessing shared-memory, we consider a network sc

Marina Jansen, Peter Reinholdt, Erik D. Hedegård, Carolin König

Quantum-mechanical (QM) and classical embedding models approximate a supermolecular quantum chemical calculation. This is particularly useful when the supermolecular calculation has a size that is out of reach for present QM models. Although QM and classical embedding methods share the same goal, they approach this goal from different starting points. In thi

Ian W. Gray, Jack Cable, Benjamin Brown, Vlad Cuiujuclu

Ransomware operations have evolved from relatively unsophisticated threat actors into highly coordinated cybercrime syndicates that regularly extort millions of dollars in a single attack. Despite dominating headlines and crippling businesses across the globe, there is relatively little in-depth research into the modern structure and economics of ransomware

Giuseppe Greco, Patrick Fiorenza, Emanuela Schilirò, Corrado Bongiorno

In this paper, the Ni Schottky barrier on GaN epilayer grown on free standing substrates has been characterized. First, transmission electrical microscopy (TEM) images and nanoscale electrical analysis by conductive atomic force microscopy (C-AFM) of the bare material allowed visualizing structural defects in the crystal, as well as local inhomogeneities of

Xiaoming Wang, Chen Liang, Yulin Mei

In order to improve low-frequency characteristics of micro-perforated panel absorbers, sound absorption structures composed of micro-perforated panels and expansion chambers are design, and an optimization design method is constructed based on the transfer function model and the simulated annealing algorithm. First, a single-chamber structure composed of a m

Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, Lin Zhang

Domain knowledge refers to the in-depth understanding, expertise, and familiarity with a specific subject, industry, field, or area of special interest. The existing benchmarks are all lack of an overall design for domain knowledge evaluation. Holding the belief that the real ability of domain language understanding can only be fairly evaluated by an compreh

Hoil Kim, Taejung Kim

We describe an explicit formula of the canonical pairing on the twisted de Rham cohomology associated with the category of local matrix factorizations and by characterizing its relation to Saito's higher residue pairings, we reprove the conjecture of Shklyarov.

Guolei Sun, Xiaogang Cheng, Zhaochong An, Xiaokang Wang

Recently, indiscernible/camouflaged scene understanding has attracted lots of research attention in the vision community. We further advance the frontier of this field by systematically studying a new challenge named indiscernible object counting (IOC), the goal of which is to count objects that are blended with respect to their surroundings. Due to a lack o

Mengdi Zhao, Yunkai Wang, Shanhui Fan, Kejie Fang

Photons, by nature, typically do not exhibit interactions with each other. Creating photon-photon interactions holds immense importance in both fundamental physics and quantum technologies. Currently, such interactions have only been achieved indirectly as mediated by atomic-like quantum emitters with resonant photon-atom interactions. However, the use of th

Hoil Kim, Taejung Kim

We formulate a realization of the canonical pairing in the negative cyclic homology of the category of local matrix factorizations and for global matrix factorizations, by introducing a twisted de Rham valued Todd class we establish a formula of the Hirzebruch-Riemann-Roch theorem in the case of periodic cyclic homology.

Yu Zhou, Yu Chen, Xiao Zhang, Pan Lai

Recently, deep learning-based compressed sensing (CS) has achieved great success in reducing the sampling and computational cost of sensing systems and improving the reconstruction quality. These approaches, however, largely overlook the issue of the computational cost; they rely on complex structures and task-specific operator designs, resulting in extensiv

Chiara Boiti, Renato Manfrin

We prove a second order identity for the Kirchhoff equation which yields, in particular, a simple and direct proof of Pokhozhaev's second order conservation law when the nonlinearity has the special form $(C_1 s +C_2)^{-2}$. As applications, we give: an estimate of order $\varepsilon^{-4}$ for the lifespan $T_\varepsilon$ of the solution of the Cauchy proble

Zijian Wang, Huaquan Ying, Rafael Sacks, André Borrmann

Interoperability remains a challenge in the construction industry. In this study, we propose a semantic enrichment approach to construct BIM knowledge graphs from pure building object geometries and demonstrate its potential to support BIM interoperability. Our approach involves machine learning and rule-based methods for object classification, relationship

Huang Zhang, Faisal Altaf, Torsten Wik

Abrupt capacity fade can have a significant impact on performance and safety in battery applications. To address concerns arising from possible knee occurrence, this work aims for a better understanding of their cause by introducing a new definition of capacity knees and their onset. A curvature-based identification of a knee and its onset is proposed, which

Yang Hou, Qing Guo, Yihao Huang, Xiaofei Xie

In recent years, as various realistic face forgery techniques known as DeepFake improves by leaps and bounds,more and more DeepFake detection techniques have been proposed. These methods typically rely on detecting statistical differences between natural (i.e., real) and DeepFakegenerated images in both spatial and frequency domains. In this work, we propose

Tomasz Szydlo, Marcin Nagy

Deployment of solutions based on TinyML requires meeting several challenges. These include hardware heterogeneity, microprocessor (MCU) architectures, and resource availability constraints. Another challenge is the variety of operating systems for MCU, limited memory management implementations and limited software interoperability between devices. A number o

Youzhe Song, Feng Wang

The discriminability of feature representation is the key to open-set face recognition. Previous methods rely on the learnable weights of the classification layer that represent the identities. However, the evaluation process learns no identity representation and drops the classifier from training. This inconsistency could confuse the feature encoder in unde

Haibiao Zhou, Nadav Auerbach, Indranil Roy, Matan Bocarsly

The scanning superconducting quantum interference device (SQUID) fabricated on the tip of a sharp quartz pipette (SQUID-on-tip) has emerged as a versatile tool for nanoscale imaging of magnetic, thermal, and transport properties of microscopic devices of quantum materials. We present the design and performance of a scanning SQUID-on-tip microscope in a top-l

TaeYoung Kang

Based on the 10.9K articles from top 40 news providers of South Korea, this paper analyzed the media framing of Itaewon Halloween Crowd Crush during the first 72 hours after the incident. By adopting word-vector embedding and clustering, we figured out that conservative media focused on political parties' responses and the suspect's identity while the libera

Zebang Shen, Hui Qian, Tongzhou Mu, Chao Zhang

Nowadays, algorithms with fast convergence, small memory footprints, and low per-iteration complexity are particularly favorable for artificial intelligence applications. In this paper, we propose a doubly stochastic algorithm with a novel accelerating multi-momentum technique to solve large scale empirical risk minimization problem for learning tasks. While

Arash Ghafouri, Hasan Naderi, Mohammad Aghajani asl, Mahdi Firouzmandi

Nowadays, one of the main challenges for Question Answering Systems is to answer complex questions using various sources of information. Multi-hop questions are a type of complex questions that require multi-step reasoning to answer. In this article, the IslamicPCQA dataset is introduced. This is the first Persian dataset for answering complex questions base

Bac Nguyen, Lukas Mauch

Deep equilibrium models (DEQs) have proven to be very powerful for learning data representations. The idea is to replace traditional (explicit) feedforward neural networks with an implicit fixed-point equation, which allows to decouple the forward and backward passes. In particular, training DEQ layers becomes very memory-efficient via the implicit function

Hongyu Sun, Yongcai Wang, Xudong Cai, Peng Wang

One fundamental limitation to the research of bird strike prevention is the lack of a large-scale dataset taken directly from real-world airports. Existing relevant datasets are either small in size or not dedicated for this purpose. To advance the research and practical solutions for bird strike prevention, in this paper, we present a large-scale challengin

Tian-Jiao Shao

We have theoretically studied the field-strength dependent high-harmonic generation (HHG) in doped systems like nano-size or bulk materials. Our results show when the amplitude of the vector potential A_peak of the driving laser reaches the half-width of the Brillouin zone ({\pi}/a0), the harmonic yield of the undoped systems is larger than the doped systems

Zhaohui Dong, Xianfeng Chen, Avik Dutt, Luqi Yuan

The study of dissipative systems has attracted great attention, as dissipation engineering has become an important candidate towards manipulating light in classical and quantum ways. Here,we investigate the behavior of a topological system with purely dissipative couplings in a synthetic time-frequency space. An imaginary bandstructure is shown, where eigen-

Sheung Man Yuen, Warut Suksompong

We study the problem of fairly allocating a divisible resource in the form of a graph, also known as graphical cake cutting. Unlike for the canonical interval cake, a connected envy-free allocation is not guaranteed to exist for a graphical cake. We focus on the existence and computation of connected allocations with low envy. For general graphs, we show tha

Lin Shu, Chuan Chen, Zibin Zheng

Graph contrastive learning defines a contrastive task to pull similar instances close and push dissimilar instances away. It learns discriminative node embeddings without supervised labels, which has aroused increasing attention in the past few years. Nevertheless, existing methods of graph contrastive learning ignore the differences between diverse semantic

Jiashuo Sun, Yi Luo, Yeyun Gong, Chen Lin

Large language models (LLMs) can achieve highly effective performance on various reasoning tasks by incorporating step-by-step chain-of-thought (CoT) prompting as demonstrations. However, the reasoning chains of demonstrations generated by LLMs are prone to errors, which can subsequently lead to incorrect reasoning during inference. Furthermore, inappropriat

Christin Katharina Kreutz, Philipp Schaer, Ralf Schenkel

Scientific digital libraries provide users access to large amounts of data to satisfy their diverse information needs. Factors influencing users' decisions on the relevancy of a publication or a person are individual and usually only visible through posed queries or clicked information. However, the actual formulation or consideration of information requirem

Feng-Yu Lu, Ze-Hao Wang, Víctor Zapatero, Jia-Lin Chen

The passive approach to quantum key distribution (QKD) consists of removing all active modulation from the users' devices, a highly desirable countermeasure to get rid of modulator side-channels. Nevertheless, active modulation has not been completely removed in QKD systems so far, due to both theoretical and practical limitations. In this work, we present a

Zachary Feinstein, Marcel Kleiber, Stefan Weber

We introduce a rigorous framework for stochastic cell transmission models for general traffic networks. The performance of traffic systems is evaluated based on preference functionals and acceptable designs. The numerical implementation combines simulation, Gaussian process regression, and a stochastic exploration procedure. The approach is illustrated in tw

Chao Zhang, Hui Qian, Jiahao Xie

Wasserstein Barycenter Problem (WBP) has recently received much attention in the field of artificial intelligence. In this paper, we focus on the decentralized setting for WBP and propose an asynchronous decentralized algorithm (A$^2$DWB). A$^2$DWB is induced by a novel stochastic block coordinate descent method to optimize the dual of entropy regularized WB

Rudresh Dwivedi, Ritesh Kumar, Deepak Chopra, Pranay Kothari

The extensive utilization of biometric authentication systems have emanated attackers / imposters to forge user identity based on morphed images. In this attack, a synthetic image is produced and merged with genuine. Next, the resultant image is user for authentication. Numerous deep neural convolutional architectures have been proposed in literature for fac

Dylan Bellier, Massimo Benerecetti, Dario Della Monica, Fabio Mogavero

Hintikka and Sandu originally proposed Independence Friendly Logic (IF) as a first-order logic of imperfect information to describe game-theoretic phenomena underlying the semantics of natural language. The logic allows for expressing independence constraints among quantified variables, in a similar vein to Henkin quantifiers, and has a nice game-theoretic s

Christin Katharina Kreutz, Martin Blum, Philipp Schaer, Ralf Schenkel

Evaluations of digital library information systems are typically centred on users correctly, efficiently, and quickly performing predefined tasks. Additionally, users generally enjoy working with the evaluated system, and completed questionnaires show an interface's excellent user experience. However, such evaluations do not explicitly consider comparing or

Daniel Gosálbez-Martínez, Alberto Crepaldi, Oleg V. Yazyev

We introduce a classification of the radial spin textures in momentum space that emerge at high-symmetry points in crystals characterized by non-polar chiral point groups ($D_2$, $D_3$, $D_4$, $D_6$, $T$, $O$). Based on the symmetry constraints imposed by these point groups in a vector field, we study the general expression for the radial spin textures up to

Yao Meng, Mark Broom, Aming Li

Human societies are organized and developed through collective cooperative behaviors, in which interactions between individuals are governed by the underlying social connections. It is well known that, based on the information in their environment, individuals can form collective cooperation by strategically imitating superior behaviors and changing unfavora

Chitralekha Gupta, Purnima Kamath, Yize Wei, Zhuoyao Li

In this paper, we propose a data-driven approach to train a Generative Adversarial Network (GAN) conditioned on "soft-labels" distilled from the penultimate layer of an audio classifier trained on a target set of audio texture classes. We demonstrate that interpolation between such conditions or control vectors provides smooth morphing between the generated

Hristina Topalova, Nadia Zlateva

We develop a new perturbation method in Orlicz sequence spaces $\ell_M$ with Orlicz function $M$ satisfying $\Delta_2$ condition at zero. This result allows one to support from below any bounded below lower semicontinuous function with bounded support, with a perturbation of the defining function $\sigma_M$. We give few examples how the method can be used fo

Francesco Cellarosi, Zachary Selk

Rough paths theory allows for a pathwise theory of solutions to differential equations driven by highly irregular signals. The fundamental observation of rough paths theory is that if one can define "iterated integrals" above a signal, then one can construct solutions to differential equations driven by the signal. The typical examples of the signals of inte

Tao Fang

Given a graph $T$ and a family of graphs $\mathcal{H}$. The generalized Tur\'an number of $\mathcal{H}$ is the maximum number of copies of $T$ in an $\mathcal{H}$-free graph on $n$ vertices, denoted by $ex(n, T, \mathcal{H})$. Let $ex(n, T, \mathcal{H})$ denote the maximum number of copies of $T$ in an $n$-vertex $\mathcal{H}$-free graph. Recently, Alon and

Hannes Thiel, Eduard Vilalta

We say that a C*-algebra is soft if it has no nonzero unital quotients, and we connect this property to the Hjelmborg-R{\o}rdam condition for stability and to property (S) of Ortega-Perera-R{\o}rdam. We further say that an operator in a C*-algebra is soft if its associated hereditary subalgebra is, and we provide useful spectral characterizations of this con

Daren Sitchepping Fosso, Castaly Fan, Larry Zamick

We show 2 matrices that have identical eigenvalues but different eigenfunctions. This shows that in obtaining two body nuclear matrix elements empirically, it is not sufficient to consider only energy levels. Other quantities like transitions must also be included.

Chuan Chen, Yuecheng Li, Zhenpeng Wu, Chengyuan Mai

Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. Wi

Ivan Markin, Anna Neuweiler, Adrian Abac, Swami Vivekanandji Chaurasia

Over the last few years, there has been an increasing interest in sub-solar mass black holes due to their potential to provide valuable information about cosmology or the black hole population. Motivated by this, we study observable phenomena connected to the merger of a sub-solar mass black hole with a neutron star. For this purpose, we perform new numerica

Lening Li, Hazhar Rahmani, Jie Fu

This paper studies temporal planning in probabilistic environments, modeled as labeled Markov decision processes (MDPs), with user preferences over multiple temporal goals. Existing works reflect such preferences as a prioritized list of goals. This paper introduces a new specification language, termed prioritized qualitative choice linear temporal logic on

Bijender, Ajay Kumar

Given a simplicial complex $\Delta$, we investigate how to construct a new simplicial complex $\bar{\Delta}$ such that the corresponding monomial ideals satisfy nice algebraic properties. We give a procedure to check the vertex decomposability of an arbitrary hypergraph. As a consequence, we prove that attaching non-pure skeletons at all vertices of a cycle

Guangji Chen, Qingqing Wu, Celimuge Wu, Mengnan Jian

Intelligent reflecting surface (IRS) has been considered as a revolutionary technology to enhance the wireless communication performance. To cater for multiple mobile users, adjusting IRS beamforming patterns over time, i.e., dynamic IRS beamforming (DIBF), is generally needed for achieving satisfactory performance, which results in high controlling power co

Sam Patrick, Ansh Gupta, Ruth Gregory, Carlo F. Barenghi

Multiply quantised vortices (MQVs) within single component Bose-Einstein condensates are unstable and decay rapidly. We show that MQVs can be stabilised by adding a small number of atoms of a second species to the vortex cores, and that these atoms remain in the vortex core as the system evolves. A consequence of the stabilisation is that nearby co-rotating

Constantino Rodriguez-Ramos, Colin M. Wilmott

In this paper, we consider the local unitary classification of the class of qudit bipartite mixed states for which no information can be obtained locally. These states are represented by symmetrical density matrices in which both tracial states are maximally mixed. Interestingly, this symmetry facilitates the local unitary classification of two-qubit states.

Markus Borg, Adam Tornhill, Enys Mones

[Context] Accurate time estimation is a critical aspect of predictable software engineering. Previous work shows that low source code quality increases the uncertainty in issue resolution times. [Objective] Our goal is to evaluate how developers' project experience and file ownership are related to issue resolution times. [Method] We mine 40 proprietary soft

V. Ryzhii, C. Tang, T. Otsuji, M. Ryzhii

We propose the terahertz (THz) detectors based on field-effect transistors (FETs) with the graphene channel (GC) and the black-Arsenic (b-As) black-Phosphorus (b-P), or black-Arsenic-Phosphorus (b-As$_x$P$_{1-x}$) gate barrier layer. The operation of the GC-FET detectors is associated with the carrier heating in the GC by the THz electric field resonantly ex

Assaf Hallak, Gal Dalal

Consider a stochastic matrix $P$ and diagonal matrix $D.$ In this work, we introduce Tilted matrices. A Tilted matrix is the product $D'PD$, where $D'$ is a diagonal normalization that makes the product stochastic. We then provide several results on products of Tilted matrices, which can be desirable for analyses of Markov Decision Processes. Lastly, we obta

Bo Li, Gexiang Fang, Yang Yang, Quansen Wang

The capability of Large Language Models (LLMs) like ChatGPT to comprehend user intent and provide reasonable responses has made them extremely popular lately. In this paper, we focus on assessing the overall ability of ChatGPT using 7 fine-grained information extraction (IE) tasks. Specially, we present the systematically analysis by measuring ChatGPT's perf

Yiming Gao, Feiyu Liu, Liang Wang, Zhenjie Lian

MOBA games, e.g., Dota2 and Honor of Kings, have been actively used as the testbed for the recent AI research on games, and various AI systems have been developed at the human level so far. However, these AI systems mainly focus on how to compete with humans, less on exploring how to collaborate with humans. To this end, this paper makes the first attempt to

Dongjingdin Liu, Pengpeng Chen, Miao Yao, Yijing Lu

Skeleton-based action recognition has achieved remarkable results in human action recognition with the development of graph convolutional networks (GCNs). However, the recent works tend to construct complex learning mechanisms with redundant training and exist a bottleneck for long time-series. To solve these problems, we propose the Temporal-Spatio Graph Co

Bijender, Ajay Kumar, Rajiv Kumar

In $2011$, Herzog, Hibi, and Ohsugi conjectured that if $J$ is the cover ideal of a chordal graph, then $J^s$ is componentwise linear for all $s \ge 1.$ In 2022, H\`a and Tuyl considered objects more general than chordal graphs and posed the following problem: Let $J(\Delta)$ be the cover ideal of a simplicial tree $\Delta.$ Is it true that $J(\Delta)^s$ is

Carl M. Bender, Sarben Sarkar

This paper presents new classes of exact radial solutions to the nonlinear ordinary differential equation that arises as a saddle-point condition for a Euclidean scalar field theory in $D$-dimensional spacetime. These solutions are found by exploiting the dimensional consistency of the radial differential equation for a single {\it massless} scalar field, wh

Tinghui Chen, Shuai Li

With the widespread application of industrial robots, the problem of absolute positioning accuracy becomes increasingly prominent. To ensure the working state of the robots, researchers commonly adopt calibration techniques to improve its accuracy. However, an industrial robot's working space is mostly restricted in real working environments, making the coll

Shuang Wang, Jun Yang

In this study, we employ and modify the Lorenz energy cycle (LEC) framework as another way to understand the atmospheric circulation on tidally locked terrestrial planets. It well describes the atmospheric general circulation in the perspective of energy transformation, involved with several dynamical processes. We find that on rapidly rotating, tidally lock

Liliana M. Cantú, Martín Figallo

Involutive Stone algebras (or {\bf S}--algebras) were introduced by R. Cignoli and M. Sagastume in connection to the theory of $n$-valued \L ukasiewicz--Moisil algebras. In this work we focus on the logic that preserves degrees of truth associated to involutive Stone algebras, named {\bf \em Six}. This follows a very general pattern that can be considered fo

Yuchen Zhu, Kailash Budhathoki, Jonas Kuebler, Dominik Janzing

In aggregated variables the impact of interventions is typically ill-defined because different micro-realizations of the same macro-intervention can result in different changes of downstream macro-variables. We show that this ill-definedness of causality on aggregated variables can turn unconfounded causal relations into confounded ones and vice versa, depen

Monika di Angelo, Gernot Salzer

Smart contracts are small programs on the blockchain that often handle valuable assets. Vulnerabilities in smart contracts can be costly, as time has shown over and over again. Countermeasures are high in demand and include best practice recommendations as well as tools supporting development, program verification, and post-deployment analysis. Many tools fo