December 2023 arXiv papers — page 41

S. Stanley Young, Warren B. Kindzierski

The Implicit Association Test, IAT, is widely used to measure hidden (subconscious) human biases, implicit bias, of many topics: race, gender, age, ethnicity, religion stereotypes. There is a need to understand the reliability of these measures as they are being used in many decisions in society today. A case study was undertaken to independently test the re

Jay Shenoy, Axel Levy, Frédéric Poitevin, Gordon Wetzstein

X-ray free-electron lasers (XFELs) offer unique capabilities for measuring the structure and dynamics of biomolecules, helping us understand the basic building blocks of life. Notably, high-repetition-rate XFELs enable single particle imaging (X-ray SPI) where individual, weakly scattering biomolecules are imaged under near-physiological conditions with the

Henry Whitehead, Connar Rowan, Tjarda Boekholt, Bence Kocsis

We investigate the thermodynamics of close encounters between stellar mass black holes (BHs) in the gaseous discs of active galactic nuclei (AGN), during which binary black holes (BBHs) may form. We consider a suite of 2D viscous hydrodynamical simulations within a shearing box prescription using the Eulerian grid code Athena++. We study formation scenarios

Ryuichiro Higashinaka, Takashi Minato, Hiromitsu Nishizaki, Takayuki Nagai

The Dialogic Robot Competition 2023 (DRC2023) is a competition for humanoid robots (android robots that closely resemble humans) to compete in interactive capabilities. This is the third year of the competition. The top four teams from the preliminary competition held in November 2023 will compete in the final competition on Saturday, December 23. The task f

Tomohiro Asano, Yuichi Ike, Wenyuan Li

We study exact Lagrangian cobordisms between exact Lagrangians in a cotangent bundle in the sense of Arnol'd, using microlocal theory of sheaves. We construct a sheaf quantization for an exact Lagrangian cobordism between Lagrangians with conical ends, prove an iterated cone decomposition of the sheaf quantization for cobordisms with multiple ends, and show

Jay Lee, Hanqi Su

The recent emergence of large language models (LLMs) demonstrates the potential for artificial general intelligence, revealing new opportunities in Industry 4.0 and smart manufacturing. However, a notable gap exists in applying these LLMs in industry, primarily due to their training on general knowledge rather than domain-specific knowledge. Such specialized

Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot, Paul Novello

Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models in real-world applications. Existing methods typically focus on feature representations or output-space analysis, often assuming a distribution over these spaces or leveraging gradient norms with respect to model parameters. However, these approaches struggle

Siqi Mao, Yaping Yuan, Yinpu Li, Ziren Wang

Energy conservation in buildings is a paramount concern to combat greenhouse gas emissions and combat climate change. The efficient management of room occupancy, involving actions like lighting control and climate adjustment, is a pivotal strategy to curtail energy consumption. In contexts where surveillance technology isn't viable, non-intrusive sensors are

Weihang Ren, Yongpei Guan, Feng Qiu, Todd Levin

Energy justice, at the intersection of energy and societal ethics, studies the origins, quantification, and resolution of persistent and potential inequities within the energy sector, serving as a foundational pillar for societal harmony. In this review, we overview the historical and modern definitions of energy equity and frameworks of energy justice. We h

Patrick M. Wensing, Jean-Jacques E. Slotine

Many energy-based control strategies for mechanical systems require the choice of a Coriolis factorization satisfying a skew-symmetry property. This paper (a) explores if and when a control designer has flexibility in this choice, (b) develops a canonical choice related to the Christoffel symbols, and (c) describes how to efficiently perform control computat

Zoe Horn, Liam Magee, Anna Munster

From the deployment of chatbots as procurement negotiators by corporations such as Walmart to autonomous agents providing 'differentiated chat' for managing overbooked flights, synthetic media are making the world of logistics their 'natural' habitat. Here the coordination of commodities, parts and labour design the problems and produce the training sets fro

Samaksh Gulati, Anshit Verma, Manoj Parmar, Palash Chaudhary

Large "instruction-tuned" language models (i.e., finetuned to respond to instructions) have demonstrated a remarkable ability to generalize zero-shot to new tasks. Nevertheless, they depend heavily on human-written instruction data that is often limited in quantity, diversity, and creativity, therefore hindering the generality of the tuned model. We conducte

L. Lourenço, A. P. Chippendale, B. Indermuehle, V. A. Moss

We present an initial analysis of Radio Frequency Interference (RFI) flagging statistics from archived Australian SKA Pathfinder (ASKAP) observations for the 'Survey and Monitoring of ASKAP's RFI environment and Trends' (SMART) project. The survey component covers ASKAP's full 700 MHz to 1800 MHz frequency range, including bands not typically used due to sev

Ayao Bobi, Rokia Missaoui, Mohamed Hamza Ibrahim

In knowledge discovery applications, the pattern set generated from data can be tremendously large and hard to explore by analysts. In the Formal Concept Analysis (FCA) framework, there have been studies to identify important formal concepts through the stability index and other quality measures. In this paper, we introduce the Base-Equivalent Conceptual Rel

Qianqian Jiang, Jiaxin Qiu, Zeng Li

This paper studies the asymptotic spectral properties of the sample covariance matrix for high dimensional compositional data, including the limiting spectral distribution, the limit of extreme eigenvalues, and the central limit theorem for linear spectral statistics. All asymptotic results are derived under the high-dimensional regime where the data dimensi

Ari Dwi Hartanto, Katsuyoshi Ohara

A Gr\"obner basis computation for the Weyl algebra with respect to a tropical term order and by using a homogenization-dehomogenization technique is sufficiently sluggish. A significant number of reductions to zero occur. To improve the computation, a tropical F5 algorithm is developed for this context. As a member of the family of signature-based algorithms

Shashank Sule, Luke Evans, Maria Cameron

We obtain asymptotically sharp error estimates for the consistency error of the Target Measure Diffusion map (TMDmap) (Banisch et al. 2020), a variant of diffusion maps featuring importance sampling and hence allowing input data drawn from an arbitrary density. The derived error estimates include the bias error and the variance error. The resulting convergen

King-Fai Li, Ka-Kit Tung

Severity of warming predicted by climate models depends on their Transient Climate Response (TCR). Inter-model spread of TCR has persisted at ~100% of its mean for decades. Existing observational constraints of TCR are based on observed historical warming to historical forcing and their uncertainty spread is just as wide, mainly due to forcing uncertainty, a

Jiaming Liu, Lili Zheng, Zhengwu Zhang, Genevera I. Allen

Multi-modal populations of networks arise in many scenarios including in large-scale multi-modal neuroimaging studies that capture both functional and structural neuroimaging data for thousands of subjects. A major research question in such studies is how functional and structural brain connectivity are related and how they vary across the population. we dev

Antu Laha, Asish K. Kundu, Niraj Aryal, Emil S. Bozin

We report the topological electronic structure, magnetic, and magnetotransport properties of a noncentrosymmetric compound GdAlSi. Magnetic susceptibility shows an antiferromagnetic transition at $T_\mathrm{N}$ = 32 K. In-plane isothermal magnetization exhibits an unusual hysteresis behavior at higher magnetic field, rather than near zero field. Moreover, th

Hao-Long Zhang, Jia-Hao Lv, Ken Chen, Xue-Jia Yu

Parametrically driven nonlinear resonators represent a building block for realizing fault-tolerant quantum computation and are useful for critical quantum sensing. From a fundamental viewpoint, the most intriguing feature of such a system is perhaps the critical phenomena, which can occur without interaction with any other quantum system. The non-analytic be

Hanlun Lei

In our Solar system, spin-orbit resonances are common under Sun--planet, planet--satellite and binary asteroid configurations. In this work, high-order and secondary spin-orbit resonances are investigated by taking numerical and analytical approaches. Poincar\'e sections as well as two types of dynamical maps are produced, showing that there are complicated

Petr Hořava

The main purpose of this article is to provide access to a previously unpublished and nearly lost paper: P. Ho\v{r}ava, "Covariant Hamilton-Jacobi Equation for Pure Gravity", which appeared originally in July 1990 as a Prague Preprint PRA-HEP-90/4, at the Institute of Physics, Czechoslovak Academy of Sciences, but appears otherwise unavailable online. The au

Amarjit Budhiraja, Michael Conroy, Dane Johnson

Dynamic capacity allocation control for resource sharing networks (RSN) is studied when the networks are in heavy traffic. The goal is to minimize an ergodic cost with a linear holding cost function. Our main result shows that the optimal cost associated with an associated Brownian control problem provides a lower bound for the asymptotic ergodic cost in the

Shinan Zou, Jianbo Xiong, Chao Fan, Shiqi Yu

Gait recognition is a biometric technology that has received extensive attention. Most existing gait recognition algorithms are unimodal, and a few multimodal gait recognition algorithms perform multimodal fusion only once. None of these algorithms may fully exploit the complementary advantages of the multiple modalities. In this paper, by considering the te

Zhe Chang, Yu-Ting Kuang, Di Wu, Jing-Zhi Zhou

We revisit the calculation of third order \acp{SIGW} and extend it from a monochromatic primordial power spectrum to a more general log-normal one. We investigate the impact of third order SIGWs on \ac{SNR} of \ac{LISA} and \ac{PTA} observations, and find that third order SIGWs significantly contribute to the total energy density spectrum of \acp{GW} in high

Yunfeng Kong, Chenchen Lian, Guangli Zhang, Shiyan Zhai

This article deals with the location problem for balancing the service efficiency and equality. In public service systems, some individuals may experience envy if they have to travel longer distances to access services compared to others. This envy can be simplified by comparing an individual's travel distance to a service facility against a threshold distan

Xuannan Liu, Yaoyao Zhong, Xing Cui, Yuhang Zhang

With extensive face images being shared on social media, there has been a notable escalation in privacy concerns. In this paper, we propose AdvCloak, an innovative framework for privacy protection using generative models. AdvCloak is designed to automatically customize class-wise adversarial masks that can maintain superior image-level naturalness while prov

Ze Yu Zhao, Zheng Zhu, Guilin Li, Wenhan Wang

In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems. Our approach innovatively confronts token explosion and reconstructs behavioral sequences, providing a nuanced understanding of transactional behavior through temporal and contextual

Qi Xu, Lijie Wang, Jing Wang, Lin Cheng

In recent years, analog circuits have received extensive attention and are widely used in many emerging applications. The high demand for analog circuits necessitates shorter circuit design cycles. To achieve the desired performance and specifications, various geometrical symmetry constraints must be carefully considered during the analog layout process. How

Shinan Zou, Chao Fan, Jianbo Xiong, Chuanfu Shen

Gait datasets are essential for gait research. However, this paper observes that present benchmarks, whether conventional constrained or emerging real-world datasets, fall short regarding covariate diversity. To bridge this gap, we undertake an arduous 20-month effort to collect a cross-covariate gait recognition (CCGR) dataset. The CCGR dataset has 970 subj

Jisu Kim, Su Houng Lee

We study the modification of the properties of the axial-vector meson, dynamically generated through the unitarization procedure, in the vacuum where the chiral symmetry is restored. This is accomplished by scaling the pion decay constant as the chiral order parameter while keeping the other input parameters fixed. We find that the mass and width of the axia

Hadi Hosseini

Fairness is one of the most desirable societal principles in collective decision-making. It has been extensively studied in the past decades for its axiomatic properties and has received substantial attention from the multiagent systems community in recent years for its theoretical and computational aspects in algorithmic decision-making. However, these stud

Zixin Chen, Shiyi Liu, Zhihua Jin, Gaoping Huang

Multiplayer Online Battle Arenas (MOBAs) have gained a significant player base worldwide, generating over two billion US dollars in annual game revenue. However, the presence of griefers, who deliberately irritate and harass other players within the game, can have a detrimental impact on players' experience, compromising game fairness and potentially leading

Cristian Rodriguez-Opazo, Edison Marrese-Taylor, Ehsan Abbasnejad, Hamed Damirchi

Contrastive Language-Image Pretraining (CLIP) stands out as a prominent method for image representation learning. Various neural architectures, spanning Transformer-based models like Vision Transformers (ViTs) to Convolutional Networks (ConvNets) like ResNets, are trained with CLIP and serve as universal backbones across diverse vision tasks. Despite utilizi

Xiao-Dong Zhang, Bin-Bin Cai, Song Lin

We proposed two classes of multiparticle entangled states, the multigraph states and multihypergraph states, defined by unique operations on the edges and hyperedges. A key discovery is the one-to-one correspondence between the proposed multihypergraph states and the generalized real equally weighted states when d is prime. While for composite d, multihyperg

Amarjit Budhiraja, Dane Johnson

We consider a family of resource sharing networks, known as bandwidth sharing models, in heavy traffic with general service and interarrival times. These networks, introduced in Massoulie and Roberts (2000) as models for internet flows, have the feature that a typical job may require simultaneous processing by multiple resources in the network. We construct

Cheng Gong, Xin Wang, Erica Cooper, Dan Wells

Neural text-to-speech (TTS) has achieved human-like synthetic speech for single-speaker, single-language synthesis. Multilingual TTS systems are limited to resource-rich languages due to the lack of large paired text and studio-quality audio data. TTS systems are typically built using a single speaker's voices, but there is growing interest in developing sys

Hung-Hsun Hans Yu

A sock ordering is a sequence of socks with different colors. A sock ordering is foot-sortable if the sequence of socks can be sorted by a stack so that socks with the same color form a contiguous block. The problem of deciding whether a given sock ordering is foot-sortable was first considered by Defant and Kravitz, who resolved the case for alignment-free

Hongfu Li, Qian Tao, Song Yu, Shufeng Gong

An efficient data structure is fundamental to meeting the growing demands in dynamic graph processing. However, the dual requirements for graph computation efficiency (with contiguous structures) and graph update efficiency (with linked list-like structures) present a conflict in the design principles of graph structures. After experimental studies of existi

Enoch Solomon, Abraham Woubie, Eyael Solomon Emiru

Although deep learning are commonly employed for image recognition, usually huge amount of labeled training data is required, which may not always be readily available. This leads to a noticeable performance disparity when compared to state-of-the-art unsupervised face verification techniques. In this work, we propose a method to narrow this gap by leveragin

Tangwen Qian, Yile Chen, Gao Cong, Yongjun Xu

Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects in dynamic systems, has attracted significant research attention in recent years. Despite the promising advances, existing studies all follow the assumption that data distribution observed during model learning matches that encountered in real-world deployments.

Yevgen Grynko, Dustin Siebert, Jan Sperling, Jens Förstner

We investigate light transport in three-dimensional disordered media composed of irregular dielectric particles using large scale full-wave simulations. For subwavelength particles with size parameter $kr \approx 1$ and high refractive index contrast, we observe a transition from diffusion to a regime characterized by non-exponential decay of time-resolved t

Ruiyuan Ming, Peng Ye, Kuojun Yang, Zhixiang Pan

A sample rate converter(SRC) is designed to adjust the sampling rate of digital signals flexibly for different application requirements in the broadband signal processing system. In this paper, a novel parallel-serial structure is proposed to improve the bandwidth and flexibility of SRC. The core of this structure is a parallel decimation filter followed by

Ruifeng Yuan, Shichao Sun, Yongqi Li, Zili Wang

With the rapid development of large language models, AI assistants like ChatGPT have become increasingly integrated into people's works and lives but are limited in personalized services. In this paper, we present a plug-and-play framework that could facilitate personalized large language model assistants with evolving conditional memory. The personalized as

Dan-Dan Lian, Peng-Ming Zhang

In this work, we explore the motion of a twisted particle possessing intrinsic orbital angular momentum (OAM) as it traverses a weak stellar gravitational field, which we approximate using a polytropic model. We disregard the spin characteristic of the twisted particle, modeling it as a massless complex twisted scalar wave packet to simplify its interaction

Juliette Soule, Andrew C. Doherty, Arne L. Grimsmo

Rotation symmetric bosonic codes are an attractive encoding for qubits into oscillator degrees of freedom, particularly in superconducting qubit experiments. While these codes can tolerate considerable loss and dephasing, they will need to be combined with higher level codes to achieve large-scale devices. We investigate concatenating these codes with the pl

Wanchao Su, Can Wang, Chen Liu, Hangzhou Han

Creating fine-retouched portrait images is tedious and time-consuming even for professional artists. There exist automatic retouching methods, but they either suffer from over-smoothing artifacts or lack generalization ability. To address such issues, we present StyleRetoucher, a novel automatic portrait image retouching framework, leveraging StyleGAN's gene

E Chen, Yang Cao, Yifei Ge

The shuffle model of local differential privacy is an advanced method of privacy amplification designed to enhance privacy protection with high utility. It achieves this by randomly shuffling sensitive data, making linking individual data points to specific individuals more challenging. However, most existing studies have focused on the shuffle model based o

Chaowei Fang, Ziyin Zhou, Junye Chen, Hanjing Su

Point-based interactive image segmentation can ease the burden of mask annotation in applications such as semantic segmentation and image editing. However, fully extracting the target mask with limited user inputs remains challenging. We introduce a novel method, Variance-Insensitive and Target-Preserving Mask Refinement to enhance segmentation quality with

Anshul Dadwal, Xiao-Tao He

For the first time, we conducted a comprehensive analysis of the rotational bands in the \( A\sim250 \) mass region. Utilizing a variety of rotational energy models and formulas, we have extracted free parameters for 36 rotational bands within this mass region, encompassing neutron numbers from N = 148 to 152. A significant enhancement has been made to the v

Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun

As the development of large-scale Generative AI models evolve beyond text (1D) generation to include image (2D) and video (3D) generation, processing spatial and temporal information presents unique challenges to quality, performance, and efficiency. We present the first work towards understanding this new system design space for multi-modal text-to-image (T

Kai-Xuan Zhang, Hwiin Ju, Hyuncheol Kim, Jingyuan Cui

Inversion symmetry breaking is critical for many quantum effects and fundamental for spin-orbit torque, which is crucial for next-generation spintronics. Recently, a novel type of gigantic intrinsic spin-orbit torque has been established in the topological van-der-Waals (vdW) magnet iron germanium telluride. However, it remains a puzzle because no clear evid

Yicheng Leng, Chaowei Fang, Gen Li, Yixiang Fang

Visible watermarks, while instrumental in protecting image copyrights, frequently distort the underlying content, complicating tasks like scene interpretation and image editing. Visible watermark removal aims to eliminate the interference of watermarks and restore the background content. However, existing methods often implement watermark component removal a

Carlos Daniel Tamayo Castro, Juan Bory Reyes, Ricardo Abreu Blaya

In this paper, we study the existence of solutions to the scalar additive Jump problem and the Riemann boundary value problems in the context of vectorial Clifford analysis on domains with fractal boundaries. A reduction procedure is applied with great effectiveness to find the solution of the problems.

Manni He, Bryce P. Hickam, Nathan Harper, Scott K. Cushing

Resonant intermediate states have been proposed to increase the efficiency of entangled two-photon absorption (ETPA). Although resonance-enhanced ETPA (r-ETPA) has been demonstrated in atomic systems using bright squeezed vacuum, it has not been studied in organic molecules. We investigate for the first time r-ETPA in an organic molecular dye, indocyanine gr

Benjamin Bacq-Labreuil, Chafic Fawaz, Yuichi Okazaki, Yukiko Obata

We study two related universal anomalies of the spectral function of cuprates, so called waterfall and high-energy kink features, by a combined cellular dynamical mean-field theory and angle-resolved photoemission study for the oxychloride Na$_x$Ca$_{2-x}$CuO$_2$Cl$_2$ (Na-CCOC). Tracing their origin back to an interplay of spin-polaron and local correlation

Tiejin Chen, Yuanpu Cao, Yujia Wang, Cho-Jui Hsieh

Federated learning enables joint training of machine learning models from distributed clients without sharing their local data. One key challenge in federated learning is to handle non-identically distributed data across the clients, which leads to deteriorated model training performances. Prior works in this line of research mainly focus on utilizing last-s

Naoki Endo

As part of stratification of Cohen-Macaulay rings, we introduce and develop the theory of Goto rings, generalizing the notion of almost Gorenstein rings originally defined by V. Barucci and R. Fr\"oberg in 1997. What has dominated the series of researches on almost Gorenstein rings is the fact that the reduction numbers of extended canonical ideals are at mo

Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan, Shalini Ghosh

Training large foundation models using self-supervised objectives on unlabeled data, followed by fine-tuning on downstream tasks, has emerged as a standard procedure. Unfortunately, the efficacy of this approach is often constrained by both limited fine-tuning compute and scarcity in labeled downstream data. We introduce Multimodal Attention Merging (MAM), a

Abhishek Kumar, Premala Chandra, Pavel A. Volkov

We demonstrate the emergence of collective spin modes with hyperbolic dispersion in three-dimensional spin-orbit coupled polar metals magnetized by intrinsic ordering or applied fields. These particle-hole bound states exist for arbitrarily weak repulsive interactions; they are optically accessible and can be used to generate pure spin current when magnetiza

Mingwen Fei, Xinghong Pan, Jianfeng Zhao

In this paper, we establish vanishing viscosity limit of the 2D Navier-Stokes equations in a horizontally periodic strip. On the vertical direction, the horizontal component of the velocity is subjected to two different types of boundary conditions: at the lower boundary, we give the degenerate zero boundary condition, while at the upper boundary, a small sm

Kaili Wang, Qinchen Wang, Calvin Cai, Dan Boneh

ERC-20R is a wrapper around ERC-20 that supports asset recovery within a limited time window after an asset is transferred. It is designed to reduce theft and losses on the blockchain by allowing a victim to recover their stolen or lost assets during the recovery window. When an honest recipient receives an ERC-20R asset, they must wait until the recovery wi

Dawn Michaelson, Gopalan Nadathur, Eric Van Wyk

This paper concerns the development of metatheory for extensible languages. It uses as its starting point a view that programming languages tailored to specific application domains are to be constructed by composing components from an open library of independently-developed extensions to a host language. In the elaboration of this perspective, static analyse

Diego Alves

In 1902, Paul St\"ackel constructed an analytic function $f(z)$ in a neighborhood of the origin, which was transcendental, and with the property that both $f(z)$ and its inverse, as well as its derivatives, assumed algebraic values at all algebraic points in this neighborhood. Inspired by this result, Mahler in 1976 questioned the existence of an transcenden

Yuke Li, Lixiong Chen, Guangyi Chen, Ching-Yao Chan

In order to predict a pedestrian's trajectory in a crowd accurately, one has to take into account her/his underlying socio-temporal interactions with other pedestrians consistently. Unlike existing work that represents the relevant information separately, partially, or implicitly, we propose a complete representation for it to be fully and explicitly capture

Z. Fu, C. Grant, D. M. Krawiec, A. Li

The next generation of searches for neutrinoless double beta decay (0{\nu}\b{eta}\b{eta}) are poised to answer deep questions on the nature of neutrinos and the source of the Universe's matter-antimatter asymmetry. They will be looking for event rates of less than one event per ton of instrumented isotope per year. To claim discovery, accurate and efficient

Aliaa Rehan Youssef, Mohammed Gumaa, Ahmad Al-Kabbany

This study is concerned with the application of virtual reality (VR) in rehabilitation programs for faulty neck posture which is a primary source of neck pain (NP). The latter is a highly prevalent musculoskeletal disorder that is associated with serious societal and economic burden. VR has been shown to be effective in the physical rehabilitation of various

Deok-Kyu Jang, Kyungsoo Kim, Hyea Hyun Kim

Partitioned neural network functions are used to approximate the solution of partial differential equations. The problem domain is partitioned into non-overlapping subdomains and the partitioned neural network functions are defined on the given non-overlapping subdomains. Each neural network function then approximates the solution in each subdomain. To obtai

Allen Chang, Matthew C. Fontaine, Serena Booth, Maja J. Matarić

Generative models can serve as surrogates for some real data sources by creating synthetic training datasets, but in doing so they may transfer biases to downstream tasks. We focus on protecting quality and diversity when generating synthetic training datasets. We propose quality-diversity generative sampling (QDGS), a framework for sampling data uniformly a

Robert Cardona, Nathan Duignan, David Perrella

Ideal magnetohydrodynamic (MHD) equilibria on a Riemannian 3-manifold satisfy the stationary Euler equations for ideal fluids. A stationary solution $X$ admits a large set of ``adapted" metrics in $M$ for which $X$ solves the corresponding MHD equilibrium equations with the same pressure function. We prove different versions of the following statement: an MH

Wenxiong Li, Huiyi Chen, Suiyin Chen, Zhiwei Liu

In this paper, a force-based beam finite element model based on a modified higher-order shear deformation theory is proposed for the accurate analysis of functionally graded beams. In the modified higher-order shear deformation theory, the distribution of transverse shear stress across the beam's thickness is obtained from the differential equilibrium equati

Wenhuan Huang

This paper gives an algorithm to determine whether a number in a cyclic quartic field is a sum of two squares, mainly based on local-global principle of isotropy of quadratic forms.

E. A. Michael, F. E. Besser, M. Hadjara, E. Moreno

A consistent and explicit spectral comparison between heterodyne (HD) and direct detection (DD) derived from first principles including the atmospheric transmission and low beam-filling factors could not be found yet in literature but is needed for decisions in technology planification for future infrared interferometry facilities which are e.g. focused on p

Akshit Gupta, Simone Mora, Fan Zhang, Martine Rutten

Healthy urban greenery is a fundamental asset to mitigate climate change phenomena such as extreme heat and air pollution. However, urban trees are often affected by abiotic and biotic stressors that hamper their functionality, and whenever not timely managed, even their survival. While the current greenery inspection techniques can help in taking effective

Jinlu Li

In this paper, we study the generalized differentiability of the metric projection operator in Hilbert spaces. We find exact expressions for Mordukhovich derivatives for the metric projection operator onto closed balls in Hilbert spaces and positive cones in Euclidean spaces and in real Hilbert space l2. We investigate the connections between Frechet differe

The CEPC Study Group

The Circular Electron Positron Collider (CEPC) is a large scientific project initiated and hosted by China, fostered through extensive collaboration with international partners. The complex comprises four accelerators: a 30 GeV Linac, a 1.1 GeV Damping Ring, a Booster capable of achieving energies up to 180 GeV, and a Collider operating at varying energy mod

Jinlu Li

In this paper, we prove strict Frechet differentiability of the metric projection operator onto closed balls in Hilbert spaces and onto positive cones in Euclidean spaces. We find the exact expressions for Frechet derivatives. Since Frechet differentiability implies Gateaux directional differentiability, the results obtained in this paper strengthen the resu

Mengqi Hu, Bian Li, Yi-An Ma, Yifei Lou

In this paper, we propose a novel approach to solving optimization problems by reformulating the optimization problem into a dynamical system, followed by the adaptive spectral Koopman (ASK) method. The Koopman operator, employed in our approach, approximates the evolution of an ordinary differential equation (ODE) using a finite number of eigenfunctions and

Miguel Abreu, Luis Paulo Reis, Nuno Lau

The RoboCup 3D Soccer Simulation League serves as a competitive platform for showcasing innovation in autonomous humanoid robot agents through simulated soccer matches. Our team, FC Portugal, developed a new codebase from scratch in Python after RoboCup 2021. The team's performance relies on a set of skills centered around novel unifying primitives and a cus

Alexander Grushin

Today's most powerful machine learning approaches are typically designed to train stateless architectures with predefined layers and differentiable activation functions. While these approaches have led to unprecedented successes in areas such as natural language processing and image recognition, the trained models are also susceptible to making mistakes that

Natalie Friedman, Asmita Mehta, Kari Love, Alexandra Bremers

Clothing for robots can help expand a robot's functionality and also clarify the robot's purpose to bystanders. In studying how to design clothing for robots, we can shed light on the functional role of aesthetics in interactive system design. We present a case study of designing a utility belt for an agricultural robot. We use reflection-in-action to consid

Chiara Boccato, Joachim Kerner, Maximilian Pechmann

We study interacting Bose gases of dimensions $2\le d \in \mathbb N$ at zero temperature in a random model known as the Kac-Luttinger model. Choosing the pair-interaction between the bosons to be of a mean-field type, we prove (complete) Bose-Einstein condensation in probability or with probability almost one into the minimizer of a Hartree-type functional.

Magdalena C. Schneider, Fabian Hinterer, Alexander Jesacher, Gerhard J. Schütz

The point spread function (PSF) is fundamental to any type of microscopy, most importantly so for single-molecule localization techniques, where the exact PSF shape is crucial for precise molecule localization at the nanoscale. However, optical aberrations and fixed fluorophore dipoles can lead to non-isotropic and distorted PSFs, thereby complicating and bi

Benjamin Avanzi, Lewis de Felice

A retiree's appetite for risk is a common input into the lifetime utility models that are traditionally used to find optimal strategies for the decumulation of retirement savings. In this work, we consider a retiree with potentially differing appetites for the key financial risks of decumulation: liquidity risk and investment risk. We set out to determine wh

Manu Kurian, Mayank Singh, Sangyong Jeon, Charles Gale

We study the transport dynamics of charm quarks within an expanding quark-gluon plasma for Pb+Pb collisions at 2.76 TeV. The analysis incorporates the hydrodynamical approach-MUSIC with fluctuating IP-Glasma initial state and Bayesian-quantified viscous coefficients. We study the interaction strength of charm quarks in the medium, including elastic collision

Jun Park, Changhoon Lee

A data-driven model for predicting the surface temperature using neural networks was proposed to alleviate the computational burden of numerical weather prediction (NWP). Our model, named TPTNet uses only 2m temperature measured at the weather stations of the South Korean Peninsula as input to predict the local temperature at finite forecast hours. The turbu

D M Kane, M Radziunas

Maximizing the rf bandwidth associated with the chaotic output from tailored operation of nonlinear semiconductor laser systems is an ongoing research effort. The early pioneering research was done in semiconductor laser with delayed optical feedback systems, which continue to be researched. We report numerical simulations of this system, using a travelling

Di Xiao, Zi-Gao Dai, Xue-Feng Wu

The field of fast radio bursts (FRBs) has entered the age of fine characterization as observational results from different radio telescopes become more and more abundant. The large FRB sample is suitable for a statistical study. There is an interesting finding that the waiting-time distributions of very active repeating FRBs show a universal double-peaked fe

Kassie Archer, Aaron Geary

In a recent paper, Bona and Smith define the notion of \textit{strong avoidance}, in which a permutation and its square both avoid a given pattern. In this paper, we generalize this idea to what we call \textit{chain avoidance}. We say that a permutation avoids a chain of patterns $(\tau_1 : \tau_2: \cdots : \tau_k)$ if the $i$-th power of the permutation av

Vishal Srikanth, Andrey V. Kuznetsov

Convolution Neural Networks (CNN) are well-suited to model the nonlinear relationship between the microscale geometry of porous media and the corresponding flow distribution, thereby accurately and efficiently coupling the flow behavior at the micro- and macro- scale levels. In this paper, we have identified the challenges involved in implementing CNNs for m

Chandregowda Pachegowda

Artificial intelligence (AI) is an emerging technology that has the potential to transform many aspects of society, including the economy, healthcare, and transportation. This article synthesizes recent research literature on the global impact of AI, exploring its potential benefits and risks. The article highlights the implications of AI, including its impa

Y. F. Adans, Jose F. Gomes, G. V. Lobo, A. H. Zimerman

The construction of negative grade KdV hierarchy is proposed in terms of a Miura-gauge transformation. Such gauge transformation is employed within the zero curvature representation and maps the Lax operator of the mKdV into its couterpart within the KdV setting. Each odd negative KdV flow is obtained from an odd and its subsequent even negative mKdV flows.

Alexandr Garbali, Jan de Gier, William Mead, Michael Wheeler

We study the stochastic six-vertex model in half-space with generic integrable boundary weights, and define two families of multivariate rational symmetric functions. Using commutation relations between double-row operators, we prove a skew Cauchy identity of these functions. In a certain degeneration of the right-hand side of the Cauchy identity we obtain t

K. Abe, H. Nakada

By applying the angular-momentum projection (AMP) to the self-consistent axial mean-field solutions with the semi-realistic effective Hamiltonian M3Y-P6, the pairing effects on the pure rotational energy of nuclei, \textit{i.e.}, the rotational energy at a fixed intrinsic state, have been investigated. While it was shown at the Hartree-Fock (HF) level that t

Priyesh Vakharia, Devavrat Joshi, Meenal Chavan, Dhananjay Sonawane

Large Language Models (LLMs) are adept at text manipulation -- tasks such as machine translation and text summarization. However, these models can also be prone to hallucination, which can be detrimental to the faithfulness of any answers that the model provides. Recent works in combating hallucinations in LLMs deal with identifying hallucinated sentences an

Behnam Rahdari, Hao Ding, Ziwei Fan, Yifei Ma

The unique capabilities of Large Language Models (LLMs), such as the natural language text generation ability, position them as strong candidates for providing explanation for recommendations. However, despite the size of the LLM, most existing models struggle to produce zero-shot explanations reliably. To address this issue, we propose a framework called Lo

Ian Geiger, Diran Apelian, Xiaoqing Pan, Penghui Cao

Grain boundary structural transitions can lead to significant changes in the properties and performance of materials. In multi-principal element alloys, understanding these transitions becomes complex due to phenomena such as local chemical ordering and multi-component segregation. Using atomistic simulations, we explore a metastable-to-equilibrium grain bou

Frederic W. Lathrop, Clark N. Taylor

Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method was developed

Luka Maisuradze, Megan C. King, Ivan V. Surovtsev, Simon G. J. Mochrie

Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a