April 2023 arXiv papers — page 79

Ahmad Kokhahi, Dan Li

As Industry 4.0 and digitalization continue to advance, the reliance on information technology increases, making the world more vulnerable to cyber-attacks, especially cyber-physical attacks that can manipulate physical systems and compromise operational data integrity. Detecting cyber-attacks in multistage manufacturing systems (MMS) is crucial due to the g

Xin Peng, Paolo Piersanti, Xiaoqin Shen

This paper is devoted to the analysis of a numerical scheme based on the Finite Element Method for approximating the solution of Koiter's model for a linearly elastic elliptic membrane shell subjected to remaining confined in a prescribed half-space. First, we show that the solution of the obstacle problem under consideration is uniquely determined and satis

Aria Masoomi, Davin Hill, Zhonghui Xu, Craig P Hersh

As machine learning algorithms are deployed ubiquitously to a variety of domains, it is imperative to make these often black-box models transparent. Several recent works explain black-box models by capturing the most influential features for prediction per instance; such explanation methods are univariate, as they characterize importance per feature. We exte

M. I. Naher, M. A. Ali, M. M. Hossain, M. M. Uddin

In this paper, we have presented a comprehensive study of the physical properties of Kagome superconductor CsV3Sb5 using the density functional theory (DFT). The structural, mechanical, electronic, atomic bonding, hardness, thermodynamic, and optical properties, and their pressure dependences have been investigated for the first time. The calculated ground s

Nazar Waheed, Ateeq Ur Rehman, Anushka Nehra, Mahnoor Farooq

The rapid adoption of Internet of Things (IoT) devices in healthcare has introduced new challenges in preserving data privacy, security and patient safety. Traditional approaches need to ensure security and privacy while maintaining computational efficiency, particularly for resource-constrained IoT devices. This paper proposes a novel hybrid approach combin

Hsin-Po Wang, Chi-Wei Chin

Constructing a polar code is all about selecting a subset of rows from a Kronecker power of $[^1_1{}^0_1]$. It is known that, under successive cancellation decoder, some rows are Pareto-better than the other. For instance, whenever a user sees a substring $01$ in the binary expansion of a row index and replaces it with $10$, the user obtains a row index that

Yikang Liu, Ziyin Zhang, Wanyang Zhang, Shisen Yue

AI generated content (AIGC) presents considerable challenge to educators around the world. Instructors need to be able to detect such text generated by large language models, either with the naked eye or with the help of some tools. There is also growing need to understand the lexical, syntactic and stylistic features of AIGC. To address these challenges in

Upala Junaida Islam, Kamran Paynabar, George Runger, Ashif Sikandar Iquebal

Active learning provides a framework to adaptively query the most informative experiments towards learning an unknown black-box function. Various approaches of active learning have been proposed in the literature, however, they either focus on exploration or exploitation in the design space. Methods that do consider exploration-exploitation simultaneously em

Ting-Chun Lin, Hsin-Po Wang

$1 - (1-x^M) ^ {2^M} > (1 - (1-x)^M) ^{2^M}$ is proved for all $x \in [0,1]$ and all $M > 1$. This confirms a conjecture about polar code, made by Wu and Siegel in 2019, that $W^{0^m 1^M}$ is more reliable than $W^{1^m 0^M}$, where $W$ is any binary erasure channel and $M = 2^m$. The proof relies on a remarkable relaxation that $m$ needs not be an integer, a

Zoe Z. Yan, Yiqi Ni, Alexander Chuang, Pavel E. Dolgirev

Interacting mixtures of bosons and fermions are ubiquitous in nature. They form the backbone of the standard model of physics, provide a framework for understanding quantum materials and are of technological importance in helium dilution refrigerators. However, the description of their coupled thermodynamics and collective behaviour is challenging. Bose-Ferm

Takayuki Myo, Emiko Hiyama

We calculated the energy spectra of the neutron-rich He $\Lambda$ hypernuclei with $A=6$ to 9 within the framework of an $\alpha + \Lambda +Xn$ ($X=1$--4) cluster model using the cluster orbital shell model. The employed constituent particles reproduce their observed properties. For resonant states of core nuclei such as $^5$He, $^6$He, and $^7$He, the compl

S. I. Kruglov

The modified $F(R)$ gravity theory with the function $F(R)=-(1/\beta)\ln(1-\beta R)$ is studied. The action at small coupling $\beta$ becomes Einstein--Hilbert action. The bound on the parameter $\beta$ from local tests is $\beta\leq 2\times 10^{-6}$ cm$^2$. We find the constant curvature solutions and it was shown that the de Sitter space is unstable but a

Xiang Cui, Alexandra Chronopoulou

In this paper, we focus on multiple sampling problems for the estimation of the fractional Brownian motion when the maximum number of samples is limited, extending existing results in the literature in a non-Markovian framework. Two classes of sampling schemes are proposed: a deterministic scheme and a level-triggered scheme. For the deterministic sampling s

Amy L. Ferrick, Jun Korenaga

Convection in planetary mantles is in the so-called mixed heating mode; it is driven by heating from below, due to a hotter core, as well as heating from within, due to radiogenic heating and secular cooling. Thus, in order to model the thermal evolution of terrestrial planets, we require the parameterization of heat flux for mixed heated convection in parti

David Boozer

Kronheimer and Mrowka used gauge theory to define a functor $J^\sharp$ from a category of webs in $\mathbb{R}^3$ to the category of finite-dimensional vector spaces over the field of two elements. They also suggested a possible combinatorial replacement $J^\flat$ for $J^\sharp$, which Khovanov and Robert proved is well-defined on a subcategory of planar webs

Aditya Ravuri, Francisco Vargas, Vidhi Lalchand, Neil D. Lawrence

Dimensionality reduction (DR) algorithms compress high-dimensional data into a lower dimensional representation while preserving important features of the data. DR is a critical step in many analysis pipelines as it enables visualisation, noise reduction and efficient downstream processing of the data. In this work, we introduce the ProbDR variational framew

Christian Krattenthaler

We give bijective proofs using Fomin's growth diagrams for identities involving numbers of vacillating tableaux that arose in the representation theory of partition algebras or are inspired by such identities.

Goulnara Arzhantseva, Liviu Paunescu

An action trace is a function naturally associated to a probability measure preserving action of a group on a standard probability space. For countable amenable groups, we characterise stability in permutations using action traces. We extend such a characterisation to constraint stability. We give sufficient conditions for a group to be constraint stable. As

Meredith Ringel Morris, Carrie J. Cai, Jess Holbrook, Chinmay Kulkarni

Card et al.'s classic paper "The Design Space of Input Devices" established the value of design spaces as a tool for HCI analysis and invention. We posit that developing design spaces for emerging pre-trained, generative AI models is necessary for supporting their integration into human-centered systems and practices. We explore what it means to develop an A

Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang

Privacy and Byzantine resilience are two indispensable requirements for a federated learning (FL) system. Although there have been extensive studies on privacy and Byzantine security in their own track, solutions that consider both remain sparse. This is due to difficulties in reconciling privacy-preserving and Byzantine-resilient algorithms. In this work, w

Xi Chen, Siwei Mai, Konstantinos Michmizos

A vast majority of spiking neural networks (SNNs) are trained based on inductive biases that are not necessarily a good fit for several critical tasks that require low-latency and power efficiency. Inferring brain behavior based on the associated electroenchephalography (EEG) signals is an example of how networks training and inference efficiency can be heav

Igor F. Herbut

Wilson-Fisher expansion near upper critical dimension has proven to be an invaluable conceptual and computational tool in our understanding of the universal critical behavior in the $\phi ^4$ field theories that describe low-energy physics of the canonical models such as Ising, XY, and Heisenberg. Here I review its application to a class of the Gross-Neveu-Y

Dirk Bergemann, Alessandro Bonatti

We analyze digital markets where a monopolist platform uses data to match multiproduct sellers with heterogeneous consumers who can purchase both on and off the platform. The platform sells targeted ads to sellers that recommend their products to consumers and reveals information to consumers about their values. The revenue-optimal mechanism is a managed adv

Nicholas Schiefer, Justin Y. Chen, Piotr Indyk, Shyam Narayanan

An $\varepsilon$-approximate quantile sketch over a stream of $n$ inputs approximates the rank of any query point $q$ - that is, the number of input points less than $q$ - up to an additive error of $\varepsilon n$, generally with some probability of at least $1 - 1/\mathrm{poly}(n)$, while consuming $o(n)$ space. While the celebrated KLL sketch of Karnin, L

Eugene M. Taranta, Adam Seiwert, Anthony Goeckner, Khiem Nguyen

Swarm robotics systems have the potential to transform warfighting in urban environments, but until now have not seen large-scale field testing. We present the Rapid Integration Swarming Ecosystem (RISE), a platform for future multi-agent research and deployment. RISE enables rapid integration of third-party swarm tactics and behaviors, which was demonstrate

Jonathan Parsons, Michael Schrider, Oyebanjo Ogunlela, Sepideh Ghanavati

With the growing global emphasis on regulating the protection of personal information and increasing user expectation of the same, developing with privacy in mind is becoming ever more important. In this paper, we study the concerns, questions, and solutions developers discuss on Reddit forums to enhance our understanding of their perceptions and challenges

C. Nick Arge, Andrew Leisner, Samantha Wallace, Carl J. Henney

The solar magnetic fields emerging from the photosphere into the chromosphere and corona are comprised of a combination of "closed" and "open" fields. The closed magnetic field lines are defined as those having both ends rooted in the solar surface, while the open field lines are those having one end extending out into interplanetary space and the other root

Junrui Liu, Ian Kretz, Hanzhi Liu, Bryan Tan

Zero-knowledge (ZK) proof systems have emerged as a promising solution for building security-sensitive applications. However, bugs in ZK applications are extremely difficult to detect and can allow a malicious party to silently exploit the system without leaving any observable trace. This paper presents Coda, a novel statically-typed language for building ze

Jiani Huang, Ziyang Li, Mayur Naik, Ser-Nam Lim

Supervised approaches for learning spatio-temporal scene graphs (STSG) from video are greatly hindered due to their reliance on STSG-annotated videos, which are labor-intensive to construct at scale. Is it feasible to instead use readily available video captions as weak supervision? To address this question, we propose LASER, a neuro-symbolic framework to en

Jonas Skackauskas, Tatiana Kalganova

Currently available dynamic optimization strategies for Ant Colony Optimization (ACO) algorithm offer a trade-off of slower algorithm convergence or significant penalty to solution quality after each dynamic change occurs. This paper proposes a discrete dynamic optimization strategy called Ant Colony Optimization (ACO) with Aphids, modelled after a real-worl

Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca

Hypernetworks, neural networks that predict the parameters of another neural network, are powerful models that have been successfully used in diverse applications from image generation to multi-task learning. Unfortunately, existing hypernetworks are often challenging to train. Training typically converges far more slowly than for non-hypernetwork models, an

Adam Chapman, Ilan Levin

We want to bound the symbol length of classes in ${_{2^{m-1}}Br}(F)$ which are represented by tensor products of 5 or 6 cyclic algebras of degree $2^m$. The main ingredients are the chain lemma for quadratic forms, a form of a generalized Clifford invariant and Pfister's and Rost's descriptions of 12- and 14-dimensional forms in $I^3 F$.

Damiano Anselmi

We study the free and dressed propagators of physical and purely virtual particles in a finite interval of time $\tau $ and on a compact space manifold $\Omega $, using coherent states. In the free-field limit, the propagators are described by the entire function $(e^{z}-1-z)/z^{2}$, whose shape on the real axis is similar to the one of a Breit-Wigner functi

Damiano Anselmi

We provide a diagrammatic formulation of perturbative quantum field theory in a finite interval of time $\tau $, on a compact space manifold $\Omega $. We explain how to compute the evolution operator $U(t_{\text{f}},t_{\text{i}})$ between the initial time $t_{\text{i}}$ and the final time $t_{\text{f}}=t_{\text{i}}+\tau $, study unitarity and renormalizabil

Olgur Celikbas, Yongwei Yao

We study the vanishing of (co)homology along ring homomorphisms for modules that admit certain filtrations, and generalize a theorem of O. Celikbas-Takahashi. Our work produces new classes of rigid and test modules, in particular over local rings of prime characteristic. It also gives applications in the study of torsion in tensor products of modules, for ex

Ana Flack, Alexander Gorsky, Sergei Nechaev

We discuss a two-parameter renormalization group (RG) flow when parameters are organized in a single complex variable, $\tau$, with modular properties. Throughout the work we consider a special limit when the imaginary part of $\tau$ characterizing the disorder strength tends to zero. We argue that generalized Riemann-Thomae (gRT) function and the correspond

Yi Hu, Yongki Lee, Shijun Zheng

In this work, we study a Lighthill-Whitham-Richard (LWR) type traffic flow model with a non-local flux. We identify a threshold condition for shock formation for traffic flow models with Arrhenius look-ahead-behind (i.e., nudging) dynamics with concave-convex flux.

Robin Lorenz, Sean Tull

The framework of causal models provides a principled approach to causal reasoning, applied today across many scientific domains. Here we present this framework in the language of string diagrams, interpreted formally using category theory. A class of string diagrams, called network diagrams, are in 1-to-1 correspondence with directed acyclic graphs. A causal

Abhishek Bamotra, Phani Krishna Uppala

While OCR has been used in various applications, its output is not always accurate, leading to misfit words. This research work focuses on improving the optical character recognition (OCR) with ML techniques with integration of OCR with long short-term memory (LSTM) based sequence to sequence deep learning models to perform document translation. This work is

Erik Olsén, Benjamin Midtvedt, Adrián González, Fredrik Eklund

The interaction between metallic and biological nanoparticles (NPs) is widely used in various biotechnology and biomedical applications. However, detailed characterization of this type of interaction is challenging due to a lack of high-throughput techniques that can quantify both size and composition of suspended NP complexes. Here, we introduce a technique

Clinton DeW. Van Siclen

The Menger sponge is a three-dimensional cube that comprises a self-similar, fractal domain and a non-fractal domain, both of which are continuous. Thus it is a useful heuristic model for natural and engineered fractal systems. For this purpose the effective transport coefficient associated with the transport properties (e.g., electrical conductivity, therma

César García Veloso, Mario Paolone, José María Maza Ortega

The paper proposes a synchropahsor estimation (SE) algorithm that leverages the use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The estimator, which uses a three-point IpDFT combined with a three-cycle Hanning window, incorporates a new detection mechanism to iteratively estimate and remove the effects

Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui

Recent years have witnessed the sustained evolution of misinformation that aims at manipulating public opinions. Unlike traditional rumors or fake news editors who mainly rely on generated and/or counterfeited images, text and videos, current misinformation creators now more tend to use out-of-context multimedia contents (e.g. mismatched images and captions)

Olufunke Oyebamiji, Peter Balogun, Emmanuel Stephen, Najeem Oladosu

Agricultural fertilizers are essential to enhance proper growth and crop yield. Chemical fertilizers endanger ecosystems, soil, plants, and animal and human lives. This has increased interest in biofertilizers which are products that contain living microorganisms or natural compounds derived from organisms such as bacteria, fungi, and algae that improve soil

Jean-Christophe Pain

In this note, we propose two series expansions of the logarithm of the Glaisher-Kinkelin constant. The relations are obtained using expressions of derivatives of the Riemann zeta function, and one of them involves hypergeometric functions.

Hubert Nourtel, Pierre Champion, Denis Jouvet, Anthony Larcher

Speech data carries a range of personal information, such as the speaker's identity and emotional state. These attributes can be used for malicious purposes. With the development of virtual assistants, a new generation of privacy threats has emerged. Current studies have addressed the topic of preserving speech privacy. One of them, the VoicePrivacy initiati

Casimir Kothari

We construct smooth projective families of algebraic varieties in characteristic $p$ such that the dimensions of the de Rham and Hodge cohomology groups of the fibers can be made to jump by an arbitrarily large amount. To do this, we first construct an example using the classifying stack of a finite flat group scheme which degenerates $\mathbb{Z}/p^2\mathbb{

Sungwoo Sohn, Naijia Liu, Geun Hee Yoo, Aya Ochiai

The understanding and quantification of ductility in crystalline metals, which has led to their widespread and effective usage as a structural material, is lacking in metallic glasses (MGs). Here, we introduce such a framework for ductility. This very practical framework is based on a MGs ability to support stable shear band growth, quantified in a stress gr

Jaye K. Harada, Nenian Charles, Nathan Z. Koocher, Yiran Wang

We present electronic structure calculations on layered nickelate oxyfluorides derived from the Ruddlesden-Popper arisotype structure in search of unidentified materials that may host nickelate superconductivity. By performing anion exchange of oxygen with fluorine, we create two heteroanionic La$_2$NiO$_3$F polymorphs and stabilize Ni$^{1+}$ in 4-coordinate

Walid Hariri

The article aims to analyze the performance of ChatGPT, a large language model developed by OpenAI, in the context of cardiology and vascular pathologies. The study evaluated the accuracy of ChatGPT in answering challenging multiple-choice questions (QCM) using a dataset of 190 questions from the Siamois-QCM platform. The goal was to assess ChatGPT potential

Klim Zaporojets

Artificial Intelligence (AI) has huge impact on our daily lives with applications such as voice assistants, facial recognition, chatbots, autonomously driving cars, etc. Natural Language Processing (NLP) is a cross-discipline of AI and Linguistics, dedicated to study the understanding of the text. This is a very challenging area due to unstructured nature of

Muhammad Sahimi

Rapid evolution of sensor technology, advances in instrumentation, and progress in devising data-acquisition softwares/hardwares are providing vast amounts of data for various complex phenomena, ranging from those in atomospheric environment, to large-scale porous formations, and biological systems. The tremendous increase in the speed of scientific computin

Jorge Antonio Cruz Chapital, Osvaldo Guzmán, Stevo Todorcevic

A structural analysis of construction schemes is developed. That analysis is used to give simple and new constructions of combinatorial objects which have been of interest to set theorists and topologists. We then continue the study of capturing axioms associated to construction schemes. From them, we deduce the existence of several uncountable structures wh

Sandra Müller, Grigor Sargsyan

Let $\Gamma^\infty$ be the set of all universally Baire sets of reals. Inspired by recent work of the second author and Nam Trang, we introduce a new technique for establishing generic absoluteness results for models containing $\Gamma^\infty$. Our main technical tool is an iteration that realizes $\Gamma^\infty$ as the sets of reals in a derived model of so

Somnath Chakraborty

A randomized scheme that succeeds with probability $1-\delta$ (for any $\delta>0$) has been devised to construct (1) an equidistributed $\epsilon$-cover of a compact Riemannian symmetric space $\mathbb M$ of dimension $d_{\mathbb M}$ and antipodal dimension $\bar{d}_{\mathbb M}$, and (2) an approximate $(\lambda_r,2)$-design, using $n(\epsilon,\delta)$-many

Kate Z. Yang, Jishnu Suresh, Giulia Cusin, Sharan Banagiri

We study the cross-correlation between the stochastic gravitational-wave background (SGWB) generated by binary black hole (BBH) mergers across the universe and the distribution of galaxies across the sky. We use the anisotropic SGWB measurement obtained using data from the third observing run (O3) of Advanced LIGO detectors and galaxy over-density obtained f

Hannah Back, Riley May, Divya Sree Naidu, Steffen Eikenberry

Earth systems may fall into an undesirable system state if 1.5 degrees celsius (C) of warming is exceeded. Carbon release from substantial permafrost stocks vulnerable to near-term warming represents a positive climate feedback that may increase the risk of 1.5 C warming or greater. Methane (CH4) is a short-lived but powerful greenhouse gas with a global war

Alejandro Lopez-Lira, Yuehua Tang

We document the capability of large language models (LLMs) like ChatGPT to predict stock market reactions from news headlines without direct financial training. Using post-knowledge-cutoff headlines, GPT-4 captures initial market responses, achieving approximately 90% portfolio-day hit rates for the non-tradable initial reaction. GPT-4 scores also significan

Luis Giraldo, Guillermo Sánchez Arellano

In this paper we introduce the notion of the realifications of an arbitrary \emph{partial holomorphic relation}. Our main result states that if any realification of an open partial holomorphic relation over a Stein manifold satisfies a relative to domain $h$--principle, then it is possible to deform any formal solution into one that is holonomic in a neighbo

Xiuli Zhu, Seshu Kumar Damarla, Biao Huang

Minimum miscibility pressure (MMP) prediction plays an important role in design and operation of nitrogen based enhanced oil recovery processes. In this work, a comparative study of statistical and machine learning methods used for MMP estimation is carried out. Most of the predictive models developed in this study exhibited superior performance over correla

Anna Ijjas

To numerically evolve the full Einstein equations (or modifications thereof), simulations of cosmological spacetimes must rely on a particular formulation of the field equations combined with a specific gauge/frame choice. Yet truly physical results cannot depend on the given formulation or gauge/frame choice. In this paper, we present a resolution of the ga

Zily Burstein, David D. Reid, Peter J. Thomas, Jack D. Cowan

While our understanding of the way single neurons process chromatic stimuli in the early visual pathway has advanced significantly in recent years, we do not yet know how these cells interact to form stable representations of hue. Drawing on physiological studies, we offer a dynamical model of how the primary visual cortex tunes for color, hinged on intracor

Taehun Lee

We study an eigenvalue problem for prescribed $\sigma_k$-curvature equations of star-shaped, $k$-convex, closed hypersurfaces. We establish the existence of a unique eigenvalue and its associated hypersurface, which is also unique, provided that the given data is even. Moreover, we show that the hypersurface must be strictly convex. A crucial aspect of our p

Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Saleh Ashkboos

As deep learning models grow, sparsity is becoming an increasingly critical component of deep neural networks, enabling improved performance and reduced storage. However, existing frameworks offer poor support for sparsity. Specialized sparsity engines focus exclusively on sparse inference, while general frameworks primarily focus on sparse tensors in classi

Akhil Jalan

The discrete Cheeger inequality, due to Alon and Milman (J. Comb. Theory Series B 1985), is an indispensable tool for converting the combinatorial condition of graph expansion to an algebraic condition on the eigenvalues of the graph adjacency matrix. We prove a generalization of Cheeger's inequality, giving an algebraic condition equivalent to small set exp

Ruchao Fan, Wei Chu, Peng Chang, Abeer Alwan

Recently, end-to-end models have been widely used in automatic speech recognition (ASR) systems. Two of the most representative approaches are connectionist temporal classification (CTC) and attention-based encoder-decoder (AED) models. Autoregressive transformers, variants of AED, adopt an autoregressive mechanism for token generation and thus are relativel

Faaiq G. Waqar, Swati Patel, Cory M. Simon

Inverse problems are ubiquitous in the sciences and engineering. Two categories of inverse problems concerning a physical system are (1) estimate parameters in a model of the system from observed input-output pairs and (2) given a model of the system, reconstruct the input to it that caused some observed output. Applied inverse problems are challenging becau

Chul Gwon, Steven C. Howell

Techniques for generating saliency maps continue to be used for explainability of deep learning models, with efforts primarily applied to the image classification task. Such techniques, however, can also be applied to object detectors, not only with the classification scores, but also for the bounding box parameters, which are regressed values for which the

Ishan Thakkar, Sairam Sri Vatsavai, Venkata Sai Praneeth Karempudi

In this paper, we present microring resonator (MRR) based polymorphic E-O circuits and architectures that can be employed for high-speed and energy-efficient non-binary reconfigurable computing. Our polymorphic E-O circuits can be dynamically programmed to implement different logic and arithmetic functions at different times. They can provide compactness and

Zhangxing Bian, Jiayang Zhong, Yanglong Lu, Charles R. Hatt

Landmark detection is a critical component of the image processing pipeline for automated aortic size measurements. Given that the thoracic aorta has a relatively conserved topology across the population and that a human annotator with minimal training can estimate the location of unseen landmarks from limited examples, we proposed an auxiliary learning task

Davood Bakhshesh, Michael A. Henning, Dinabandhu Pradhan

Let $G$ be graph with vertex set $V$ and order $n=|V|$. A coalition in $G$ is a combination of two distinct sets, $A\subseteq V$ and $B\subseteq V$, which are disjoint and are not dominating sets of $G$, but $A\cup B$ is a dominating set of $G$. A coalition partition of $G$ is a partition $\mathcal{P}=\{S_1,\ldots,S_k\}$ of its vertex set $V$, where each set

Tian-Xiao He, Peter J. -S. Shiue

We study the divisibility of the sums of the odd power of consecutive integers, $S(m,k)=1^{mk}+2^{mk}+\cdots+k^{mk}$ and $1^k+2^k+\cdots+n^k$ for odd integers $m$ and $k$, by using the Girard-Waring identity. Faulhaber's approach for the divisibilities is discussed. Some expressions of power sums in terms of Stirling numbers of the second kind are represente

Hermann Kroll, Christin Katharina Kreutz, Pascal Sackhoff, Wolf-Tilo Balke

Providing effective access paths to content is a key task in digital libraries. Oftentimes, such access paths are realized through advanced query languages, which, on the one hand, users may find challenging to learn or use, and on the other, requires libraries to convert their content into a high quality structured representation. As a remedy, narrative inf

Bogdan Chornomaz, Francis Wagner

We prove that for any $\varepsilon>0$, a non-deterministic Turing machine $\mathcal{T}$ with time complexity $T(n)$ can be emulated by an $S$-machine with time and space complexities at most $T(n)^{1+\varepsilon}$ and $T(n)$, respectively. This improves the bounds on the emulation in arXiv:math/9811105 and leads to improved bounds in the main theorem of arXi

Mahroo Shiranzaei, Jonas Fransson, Vahid Azimi-Mousolou

Quantum squeezing is an essential asset in the field of quantum science and technology. In this study, we investigate the impact of temperature and anisotropy on squeezing of quantum fluctuations in two-mode magnon states within uniaxial antiferromagnetic materials. Through our analysis, we discover that the inherent nonlinearity in these bipartite magnon sy

Sara Maad Sasane, Wilhelm Treschow

We investigate the persistance of embedded eigenvalues under perturbations of a certain self-adjoint Schr\"odinger-type differential operator in $L^2(\mathbb{R};\mathbb{R}^n)$, with an asymptotically periodic potential. The studied perturbations are small and belong to a certain Banach space with a specified decay rate, in particular, a weighted space of con

Hendrik Scheidel, Houshyar Asadi, Tobias Bellmann, Andreas Seefried

Motion cueing algorithms (MCA) are used to control the movement of motion simulation platforms (MSP) to reproduce the motion perception of a real vehicle driver as accurately as possible without exceeding the limits of the workspace of the MSP. Existing approaches either produce non-optimal results due to filtering, linearization, or simplifications, or the

Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields

Operator regression provides a powerful means of constructing discretization-invariant emulators for partial-differential equations (PDEs) describing physical systems. Neural operators specifically employ deep neural networks to approximate mappings between infinite-dimensional Banach spaces. As data-driven models, neural operators require the generation of

Trishie Sharma, Rachit Agarwal, Sandeep Kumar Shukla

The explosive growth of non-fungible tokens (NFTs) on Web3 has created a new frontier for digital art and collectibles, but also an emerging space for fraudulent activities. This study provides an in-depth analysis of NFT rug pulls, which are fraudulent schemes aimed at stealing investors' funds. Using data from 758 rug pulls across 10 NFT marketplaces, we e

Christoph Reich, Tim Prangemeier, André O. Françani, Heinz Koeppl

Extracting single-cell information from microscopy data requires accurate instance-wise segmentations. Obtaining pixel-wise segmentations from microscopy imagery remains a challenging task, especially with the added complexity of microstructured environments. This paper presents a novel dataset for segmenting yeast cells in microstructures. We offer pixel-wi

Alisha Sharma, Jason Geder, Joseph Lingevitch, Theodore Martin

Unmanned air vehicles often produce significant noise from their propulsion systems. Using this broadband signal as "acoustic illumination" for an auxiliary sensing system could make vehicles more robust at a minimal cost. We present an acoustic beamforming-based algorithm that estimates object-relative distance with a small two-microphone array using the ge

Christoph Schmid

We show that the acceleration-difference of neighboring free-falling particles (= geodesic deviation) measured in the local reference frame of a GR-noninertial observer is not given by the Riemann tensor. With the gravito-electric field of GR defined as the acceleration of free-falling quasistatic particles relative to the observer, the divergence of the gra

Jami Gayatri Manjeera, Alisha Malla, Masani Venkata Lakshmi Pravallika

Multinational corporations routinely track how its employees use their computers, the internet, or email. There are roughly a thousand devices on the market that enable businesses to monitor their workforce. Observe what their users do online, in their emails, and on their so-called personal laptops while at work. Our team will develop a key-logger for this

Pia Čuk, Robin Senge, Mikko Lauri, Simone Frintrop

We investigate cross-quality knowledge distillation (CQKD), a knowledge distillation method where knowledge from a teacher network trained with full-resolution images is transferred to a student network that takes as input low-resolution images. As image size is a deciding factor for the computational load of computer vision applications, CQKD notably reduce

Giovanni Trezza, Eliodoro Chiavazzo

In this study, we evaluate several classifiers and focus on selecting a minimal set of appropriate material features. Our objective is to propose and discuss general strategies for reducing the number of descriptors required for material classification. The first strategy involves testing whether the critical temperature of the target material property is in

Jonathan Robert Pool

Automated web accessibility testing tools have been found complementary. The implication: To catch as many issues as possible, use multiple tools. Doing this efficiently entails integration costs. Is there a small set of tools that, together, make additional tools redundant? I approach this problem by comparing nine comprehensive accessibility testing tools

Yihong Dong, Xue Jiang, Zhi Jin, Ge Li

Although Large Language Models (LLMs) have demonstrated remarkable code-generation ability, they still struggle with complex tasks. In real-world software development, humans usually tackle complex tasks through collaborative teamwork, a strategy that significantly controls development complexity and enhances software quality. Inspired by this, we present a

Daniel Sternheimer

This is a brief reminder, with extensions, from a different angle and for a less specialized audience, of my presentation at WGMP32 in July 2013, to which I refer for more details on the topics hinted at in the title, mainly deformation theory applied to quantization and symmetries (of elementary particles).

Alexandre Bousse, Venkata Sai Sundar Kandarpa, Simon Rit, Alessandro Perelli

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relativ

Jean Hélder Marques Ribeiro, Jacob Neal, Anton Burtsev, Michael Amitay

While tapered swept wings are widely used, the influence of taper on their post-stall wake characteristics remains largely unexplored. To address this issue, we conduct an extensive study using direct numerical simulations to characterize the wing taper and sweep effects on laminar separated wakes. We analyze flows behind NACA 0015 cross-sectional profile wi

Arkady Bolotin

In black hole physics, inflationary cosmology, and quantum field theories, it is conjectured that the physical laws are subject to radical changes below the Planck length. Such changes are due to effects of quantum gravity believed to become significant at the Planck length. However, a complete and consistent quantum theory of gravity is still missing, and c

F. S. Oliveira, L. M. S. Alves, M. S. da Luz, E. C. Romão

Simulations carried out with COMSOL software in order to study the electrical resistivity of rectangular samples are reported. The comparison of the results with the four-probe method allows to understand the meaning of the geometric factor (H) and the effectiveness thickness (E) defined in the Montgomery method.

Andreas-Stephan Elsenhans, Jörg Jahnel

We provide a lower bound for the number of components of the algebraic monodromy group in the situation of a $K3$ surface over a number field $k$. In the CM case, our bound is sharp. As an application, we describe, in the case of CM, the jump character \cite[Definition~2.4.6]{CEJ} entirely in terms of the endomorphism field and the geometric Picard rank.

Li Zhu, Jiahui Xiong, Wenxian Wu, Hongyu Yu

Fire is one of the common disasters in daily life. To achieve fast and accurate detection of fires, this paper proposes a detection network called FSDNet (Fire Smoke Detection Network), which consists of a feature extraction module, a fire classification module, and a fire detection module. Firstly, a dense connection structure is introduced in the basic fea

Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu

Recently, Meta AI Research releases a general Segment Anything Model (SAM), which has demonstrated promising performance in several segmentation tasks. As we know, polyp segmentation is a fundamental task in the medical imaging field, which plays a critical role in the diagnosis and cure of colorectal cancer. In particular, applying SAM to the polyp segmenta

Jacob Raymond

In this work, we prove that every SFT, sofic shift, and strongly irreducible shift on locally finite groups has strong dynamical properties. These properties include that every sofic shift is an SFT, every SFT is strongly irreducible, every strongly irreducible shift is an SFT, every SFT is entropy minimal, and every SFT has a unique measure of maximal entro

Thi Altenschmidt

The main task of this work is to give an improvement for the upper bounds of the Laplace transform $$\int_0^{+\infty}\Bigl|\zeta\left(\frac{1}{2}+it\right)\Bigr|^{2\beta}e^{-\delta t}dt \ll_{\beta,\varepsilon} \frac{1}{\delta^{\frac{\beta-1}{2}+\varepsilon}}, \quad 0 < \delta < \frac{\pi}{2}, \delta \to 0^+, \forall \varepsilon > 0, \forall \beta \geqslant 3

Hao Fang, Ajian Liu, Jun Wan, Sergio Escalera

Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios. Specifically, compared with FAS in traditional scenes such as phone unlocking, face payment, and self-service security inspection, FAS in long-distance such as station squares, p

Tomasz Weiss, Piotr Zakrzewski

We study a strengthening of the notion of a universally meager set and its dual counterpart that strengthens the notion of a universally null set. We say that a subset $A$ of a perfect Polish space $X$ is countably perfectly meager (respectively, countably perfectly null) in $X$, if for every perfect Polish topology $\tau$ on $X$, giving the original Borel s

Simone A. Padoan, Stefano Rizzelli, Matteo Schiavone

Marginal expected shortfall is unquestionably one of the most popular systemic risk measures. Studying its extreme behaviour is particularly relevant for risk protection against severe global financial market downturns. In this context, results of statistical inference rely on the bivariate extreme values approach, disregarding the extremal dependence among