May 2024 arXiv papers — page 139

Zakaria Abdellah Sellam, Cosimo Distante, Abdelmalik Taleb-Ahmed, Pier Luigi Mazzeo

Evaluating house prices is crucial for various stakeholders, including homeowners, investors, and policymakers. However, traditional spatial interpolation methods have limitations in capturing the complex spatial relationships that affect property values. To address these challenges, we have developed a new method called Multi-Head Gated Attention for spatia

Carlos F. S. Pereira, Ébano L. Martins, Denis C. Rodrigues, Júlio C. Fabris

In the present study, we generalize the possible ghost field configurations within the framework of $k$-essence theory to the Simpson-Visser metric area function $\Sigma^2=x^2+a^2$. Our analysis encompasses field configurations for the region-defined metric function $dA_\pm$ as well as the general solution that asymptotically behaves as Schwarzschild-de Sitt

Ning Liu, Xuxiao Li, Manoj R. Rajanna, Edward W. Reutzel

A digital twin (DT), with the components of a physics-based model, a data-driven model, and a machine learning (ML) enabled efficient surrogate, behaves as a virtual twin of the real-world physical process. In terms of Laser Powder Bed Fusion (L-PBF) based additive manufacturing (AM), a DT can predict the current and future states of the melt pool and the re

Rimpi Borah, J. Harshan

Analog Lagrange Coded Computing (ALCC) is a recently proposed coded computing paradigm wherein certain computations over analog datasets can be efficiently performed using distributed worker nodes through floating point implementation. While ALCC is known to preserve privacy of data from the workers, it is not resilient to adversarial workers that return err

Hao Yang, Ayberk Acar, Keshuai Xu, Anton Deguet

Robot-assisted minimally invasive surgery, such as through the da Vinci systems, improves precision and patient outcomes. However, da Vinci systems prior to da Vinci 5, lacked direct force-sensing capabilities, forcing surgeons to operate without the haptic feedback they get through laparoscopy. Our prior work restored force sensing through machine learning-

Takushi Yoshikawa, Ryoji Tanabe

Feature-based offline algorithm selection has shown its effectiveness in a wide range of optimization problems, including the black-box optimization problem. An algorithm selection system selects the most promising optimizer from an algorithm portfolio, which is a set of pre-defined optimizers. Thus, algorithm selection requires a well-constructed algorithm

Anjaneya Teja Kalvakolanu, NagaSai Chandra, Michael Fekadu

FAQ documents are commonly used with text documents and websites to provide important information in the form of question answer pairs to either aid in reading comprehension or provide a shortcut to the key ideas. We suppose that salient sentences from a given document serve as a good proxy fro the answers to an aggregated set of FAQs from readers. We propos

Karim Abbasi, Parvin Razzaghi, Amin Ghareyazi, Hamid R. Rabiee

The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has received much attention. Two steps are involved in deep learning-based approaches: feature extraction and task prediction step. Many deep learning-based approaches concentrate on in

Yuanyuan Jiang, Jianqin Yin

While vision-language pretrained models (VLMs) excel in various multimodal understanding tasks, their potential in fine-grained audio-visual reasoning, particularly for audio-visual question answering (AVQA), remains largely unexplored. AVQA presents specific challenges for VLMs due to the requirement of visual understanding at the region level and seamless

Ludi Wang, Xueqing Chen, Yi Du, Yuanchun Zhou

The field of catalysis holds paramount importance in shaping the trajectory of sustainable development, prompting intensive research efforts to leverage artificial intelligence (AI) in catalyst design. Presently, the fine-tuning of open-source large language models (LLMs) has yielded significant breakthroughs across various domains such as biology and health

Tsukasa Fukusato, Akinobu Maejima, Takeo Igarashi

This paper proposes a method to estimate the locations of grid handles in free-form deformation (FFD) while preserving the local shape characteristics of the 2D/3D input model embedded into the grid, named locality-preserving FFD (lp-FFD). Users first specify some vertex locations in the input model and grid handle locations. The system then optimizes all lo

Rajapaksha HKK, Fernando MN, Nelumdeniya NRM, Bandara AWMKK

Phytochemicals are still a valuable source to develop clinically important drugs in treating chronic and acute diseases. Inflammation is a response to an injurious stimulus of the body and novel therapeutic agents are needed to alleviate the condition with minimum side effects. Matured and fully expanded fresh leaves and barks of H. iryaghedhi were collected

Sonia Elizabeth Teodorescu

This work provides an exact mathematical characterization of the meniscus formed by a liquid of density $\rho$ (model for tumor tissue) when probed with a cantilever device, operating by gravity (acceleration $g$) and with surface tension coefficient $\sigma$ (material-dependent for the specific choice of liquid and cantilever). The shape and extremal parame

Naisheng Liang, Alex Potanin

With the increasing popularity of plugin-based software systems, ensuring the security of plugins has become a critical concern. When users install plugins or browse websites with plugins from an untrusted source, how can we be sure that they do have any undesirable functions implicitly? In this research, we present a comprehensive study on language-based se

Joseph J. P. Simons, Wong Liang Ze, Prasanta Bhattacharya, Brandon Siyuan Loh

Large language models are increasingly being used to label or rate psychological features in text data. This approach helps address one of the limiting factors of digital trace data - their lack of an inherent target of measurement. However, this approach is also a form of psychological measurement (using observable variables to quantify a hypothetical laten

Yushan Chen, Hao Tong

The repeated fast radio burst FRB 121102A and FRB 190520B has been reported, along with a spatially coincident, compact, persistent radio emission. In this paper, we present a parameterized one-zone model, with a basic scenario that a relativistic magnetized wind from the pulsar sweeps up the surroundings, e.g. freely expanding supernova ejecta, giving rise

Carmen Scheidemann, Andrei Cramariuc, Marco Hutter

Assistance robots are the future for people who need daily care due to limited mobility or being wheelchair-bound. Current solutions of attaching robotic arms to motorized wheelchairs only provide limited additional mobility at the cost of increased size. We present a mouth joystick control interface, augmented with voice commands, for an independent quadrup

Clinton Mo, Kun Hu, Chengjiang Long, Dong Yuan

In the character animation field, modern supervised keyframe interpolation models have demonstrated exceptional performance in constructing natural human motions from sparse pose definitions. As supervised models, large motion datasets are necessary to facilitate the learning process; however, since motion is represented with fixed hierarchical skeletons, su

Lixi Zhu, Xiaowen Huang, Jitao Sang

Conversational Recommender System (CRS) leverages real-time feedback from users to dynamically model their preferences, thereby enhancing the system's ability to provide personalized recommendations and improving the overall user experience. CRS has demonstrated significant promise, prompting researchers to concentrate their efforts on developing user simula

Yu Chen, Wei Wang

This paper is concerned with the state estimation problem for two-dimensional systems with asynchronous multichannel delays and energy harvesting constraints. In the system, each smart sensor has a certain probability of harvesting energy from the external environment, the authorized transmission between the sensor and the remote filter is contingent upon th

Pengfei Zhang, Zhihang Zheng, Shichen Zhang, Minghao Yang

Compared with invasive examinations that require tissue sampling, respiratory sound testing is a non-invasive examination method that is safer and easier for patients to accept. In this study, we introduce Rene, a pioneering large-scale model tailored for respiratory sound recognition. Rene has been rigorously fine-tuned with an extensive dataset featuring a

Jesus Gonzalez-Sieiro, David Pardo, Vincenzo Nava, Victor M. Calo

We propose a method for reducing the spatial discretization error of coarse computational fluid dynamics (CFD) problems by enhancing the quality of low-resolution simulations using deep learning. We feed the model with fine-grid data after projecting it to the coarse-grid discretization. We substitute the default differencing scheme for the convection term b

Mu-Huan Miles Chung, Sharon Li, Jaturong Kongmanee, Lu Wang

Redacted emails satisfy most privacy requirements but they make it more difficult to detect anomalous emails that may be indicative of data exfiltration. In this paper we develop an enhanced method of Active Learning using an information gain maximizing heuristic, and we evaluate its effectiveness in a real world setting where only redacted versions of email

R. Luo, R. D. Ekers, G. Hobbs, A. Dunning

Fast Radio Bursts (FRBs) are short-duration radio transients that occur at random times in host galaxies distributed all over the sky. Large field of view instruments can play a critical role in the blind search for rare FRBs. We present a concept for an all-sky FRB monitor using a compact all-sky phased array (CASPA), which can efficiently achieve an extrem

Yao Sun, Tengyu Jing, Jiapeng Wang, Wei Wang

Quickly and accurately predicting the flight trajectory of a blue army fighter in close-range air combat helps a red army fighter gain a dominant situation, which is the winning factor in later air combat. However,due to the high speed and even hypersonic capabilities of advanced fighters, the diversity of tactical maneuvers,and the instantaneous nature of s

Jaxon Kneipp, Alex Potanin, Michael Anenburg

Modern geological studies and mineral exploration techniques rely heavily on being able to digitally visualise and interpret data. Rare earth elements (REEs) are vital for renewable energy technologies. REE concentrations, when normalised to a standard material, show unique geometric curves (or patterns) in geological samples due to their similar chemical pr

Hao Yu, Aoran Gan, Kai Zhang, Shiwei Tong

Retrieval-Augmented Generation (RAG) has recently gained traction in natural language processing. Numerous studies and real-world applications are leveraging its ability to enhance generative models through external information retrieval. Evaluating these RAG systems, however, poses unique challenges due to their hybrid structure and reliance on dynamic know

Dane Sherburn, Bilal Chughtai, Owain Evans

Large language models (LLMs) perform well at a myriad of tasks, but explaining the processes behind this performance is a challenge. This paper investigates whether LLMs can give faithful high-level explanations of their own internal processes. To explore this, we introduce a dataset, ArticulateRules, of few-shot text-based classification tasks generated by

Junichiro Niimi

Today, the acquisition of various behavioral log data has enabled deeper understanding of customer preferences and future behaviors in the marketing field. In particular, multimodal deep learning has achieved highly accurate predictions by combining multiple types of data. Many of these studies utilize with feature fusion to construct multimodal models, whic

Gal Sela, Erez Petrank

Concurrent data structures serve as fundamental building blocks for concurrent computing. Many concurrent counterparts have been designed for basic sequential mechanisms; however, one notable omission is a concurrent tree that supports aggregate queries. Aggregate queries essentially compile succinct information about a range of data items, for example, calc

Andrew Shin, Yusuke Mori, Kunitake Kaneko

Text-to-video generation task has witnessed a notable progress, with the generated outcomes reflecting the text prompts with high fidelity and impressive visual qualities. However, current text-to-video generation models are invariably focused on conveying the visual elements of a single scene, and have so far been indifferent to another important potential

Nadine Meister, Christopher A. Pattison, John Preskill

Decoders that provide an estimate of the probability of a logical failure conditioned on the error syndrome ("soft-output decoders") can reduce the overhead cost of fault-tolerant quantum memory and computation. In this work, we construct efficient soft-output decoders for the surface code derived from the Minimum-Weight Perfect Matching and Union-Find decod

Boya Hou, Sina Sanjari, Nathan Dahlin, Alec Koppel

The Koopman operator provides a powerful framework for representing the dynamics of general nonlinear dynamical systems. However, existing data-driven approaches to learning the Koopman operator rely on batch data. In this work, we present a sparse online learning algorithm that learns the Koopman operator iteratively via stochastic approximation, with expli

Vansh Murad Kalia

Packing peanuts, as defined by Wikipedia, is a common loose-fill packaging and cushioning material that helps prevent damage to fragile items. In this paper, I propose that synthetic data, akin to packing peanuts, can serve as a valuable asset for economic prediction models, enhancing their performance and robustness when integrated with real data. This hybr

Linyi Han, Shidong Pan, Zhenchang Xing, Jiamou Sun

Augmenting missing key aspects in Textual Vulnerability Descriptions (TVDs) is crucial for effective vulnerability analysis. For instance, in TVDs, key aspects include Attack Vector, Vulnerability Type, among others. These key aspects help security engineers understand and address the vulnerability in a timely manner. For software with a large user base (non

Xubo Luo, Xue Wan, Yixing Gao, Yaolin Tian

Unmanned aerial vehicles (UAVs) visual localization in planetary aims to estimate the absolute pose of the UAV in the world coordinate system through satellite maps and images captured by on-board cameras. However, since planetary scenes often lack significant landmarks and there are modal differences between satellite maps and UAV images, the accuracy and r

Katie Denny, Matthew Hedman, Dominique Bockelée-Morvan, Gianrico Filacchione

Water vapor produces a series of diagnostic emission lines in the near infrared between 2.60 and 2.75 microns. The Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft detected this emission signal from Enceladus' plume, and so VIMS observations provide information about the variability of the plume's water vapor content. Using a da

Vladimir Angulo-Castillo, Edison Cuba, Lucas C. F. Ferreira

In this paper we show the existence of time-periodic vortex patches for the generalized surface quasi-geostrophic equation within a bounded domain. This construction is carried out for values of $\gamma$ in the range of $(1,2)$. The resulting vortex patches possess a fixed vorticity and total flux, and they are located in the neighborhood of critical points

Quanlong Yang, Zhibo Yao, Lei Xu, Yapeng Dou

Bound states in the continuum (BICs) are an excellent platform enabling highly efficient light-matter interaction in applications for lasing, nonlinear generation, and sensing. However, the current focus in implementing BICs has primarily been on single sharp resonances, limiting the extent of electric field enhancement for multiple resonances. In this study

Zhenglin Pan

Hand-drawn cartoon animation employs sketches and flat-color segments to create the illusion of motion. While recent advancements like CLIP, SVD, and Sora show impressive results in understanding and generating natural video by scaling large models with extensive datasets, they are not as effective for cartoons. Through our empirical experiments, we argue th

Cuicui Zheng, Jiahui Xie, Ming Zhang, Yajiang Chen

Few-body physics for anyons has been intensively studied within the anyon-Hubbard model, including the quantum walk and Bloch oscillations of two-anyon states. However, the known theoretical proposal and experimental simulations of two-anyon states in one-dimensional lattice have been carried out by expanding the wavefunction in terms of non-orthogonal basis

Yexin Hu, Alexandra Gillespie, Akhil Padmanabha, Kavya Puthuveetil

Liquids and granular media are pervasive throughout human environments, yet remain particularly challenging for robots to sense and manipulate precisely. In this work, we present a systematic approach at integrating capacitive sensing within robotic end effectors to enable robust sensing and precise manipulation of liquids and granular media. We introduce th

Berkay Cetkin, Lejla Begic Fazlic, Kristof Ueding, Rüdiger Machhamer

In this paper, we propose an innovative method for determining the fill level of containers, such as trash cans, addressing a critical aspect of waste management. The method combines spatial impulse response analysis with machine learning (ML) techniques, offering a unique and effective approach for sound-based classification that can be extended to various

Hung P. Tong-Viet

Let $G$ be a finite group and let $\textrm{cd}(G)$ be the set of all complex irreducible character degrees of $G.$ In this paper, we show that if $\textrm{cd}(G)=\textrm{cd}(H),$ where $H$ is a finite simple exceptional group of Lie type, then $G\cong H\times A,$ where $A$ is an abelian group. This completes the verification of Huppert's Conjecture for all f

Avner Ash, Paul E. Gunnells, Mark McConnell

We extend the computations in our prior work to find the cohomology in degree five of a congruence subgroup Gamma of SL_4(Z) with coefficients in Sym^g(K^4), twisted by a nebentype character eta, along with the action of the Hecke algebra. This is the top cuspidal degree. In this paper we take K to be a finite field of large characteristic, as a proxy for th

Jiti Gao, Fei Liu, Bin Peng, Yayi Yan

This paper provides the relevant literature with a complete toolkit for conducting robust estimation and inference about the parameters of interest involved in a high-dimensional panel data framework. Specifically, (1) we allow for non-Gaussian, serially and cross-sectionally correlated and heteroskedastic error processes, (2) we develop an estimation method

Mahira Arefin, Md. Anwar Hussen Wadud, Anichur Rahman

Crowd density level estimation is an essential aspect of crowd safety since it helps to identify areas of probable overcrowding and required conditions. Nowadays, AI systems can help in various sectors. Here for safety purposes or many for public service crowd detection, tracking or estimating crowd level is essential. So we decided to build an AI project to

Pedro Guillermo Feijóo-García, Chase Wrenn, Alexandre Gomes de Siqueira, Rashi Ghosh

Virtual humans (i.e., embodied conversational agents) have the potential to support college students' mental health, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields where students are at a heightened risk of mental disorders such as anxiety and depression. A comprehensive understanding of students, considering their cultural c

Adit Jain, Vikram Krishnamurthy

This paper studies the problem of autonomous agents performing Bayesian social learning for sequential detection when the observations of the state belong to a high-dimensional space and are expensive to analyze. Specifically, when the observations are textual, the Bayesian agent can use a large language model (LLM) as a map to get a low-dimensional private

Hyonggi Kim, Atsushi Ikeda

Glassy soft matter is often continuously polydisperse, in which the sizes or various properties of the constituent particles are distributed continuously. However, most of the microscopic theories of the glass transition focus on the monodisperse particles. Here, we developed a replica theory for the dynamic glass transition of continuously polydisperse hard

Adit Jain, Vikram Krishnamurthy

This paper studies how a stochastic gradient algorithm (SG) can be controlled to hide the estimate of the local stationary point from an eavesdropper. Such problems are of significant interest in distributed optimization settings like federated learning and inventory management. A learner queries a stochastic oracle and incentivizes the oracle to obtain nois

Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho, Moonjung Eo

The ability of deep networks to learn superior representations hinges on leveraging the proper inductive biases, considering the inherent properties of datasets. In tabular domains, it is critical to effectively handle heterogeneous features (both categorical and numerical) in a unified manner and to grasp irregular functions like piecewise constant function

Yuanjie Ning, Wenjun Wu, Liang Dai, Shuo Sun

Li2WO4 (LWO) is recognized for its potential as a solid-state electrolyte and it has demonstrated the ability to enhance the electrochemical performance of LiCoO2 (LCO) cathodes in Li-ion batteries. However, prior investigations into LWO have predominantly involved polycrystalline structures, thereby lacking a comprehensive understanding of its behavior when

Karina Koval, Ruanui Nicholson

We consider optimal experimental design (OED) for nonlinear inverse problems within the Bayesian framework. Optimizing the data acquisition process for large-scale nonlinear Bayesian inverse problems is a computationally challenging task since the posterior is typically intractable and commonly-encountered optimality criteria depend on the observed data. Sin

Haijiang Tian, Jingkun Yue, Xiaohong Liu, Guoxing Yang

Medical images are often more difficult to acquire than natural images due to the specialism of the equipment and technology, which leads to less medical image datasets. So it is hard to train a strong pretrained medical vision model. How to make the best of natural pretrained vision model and adapt in medical domain still pends. For image classification, a

Liyan Ni, Yihao Zhao, Zhonghan Hu

An outstanding property of any Hamiltonian system is the symplecticity of its flow, namely, the continuous trajectory preserves volume in phase space. Given a symplectic but discrete trajectory generated by a transition matrix applied at a fixed time-increment ($\tau > 0$), it was generally believed that there exists a unique Hamiltonian producing a continuo

Chiyu Chen, Yuliang Lu, Guozheng Yang, Yi Xie

Fast large-scale network scanning is an important way to understand internet service configurations and security in real time, among which stateless scan is representative. Existing stateless scanners can perform single-packet scans for internet-wide network measurements but are limited to host discovery or port scanning. To obtain further information over T

Jingcheng Meng, Yimeng Ren, Xuening Zhu, Guanyu Hu

The Gini coefficient is an universally used measurement of income inequality. Intersectoral GDP contributions reveal the economic development of different sectors of the national economy. Linking intersectoral GDP contributions to Gini coefficients will provide better understandings of how the Gini coefficient is influenced by different industries. In this p

Kyle E. Marlantes, Piotr J. Bandyk, Kevin J. Maki

A machine learning (ML) method is generalizable if it can make predictions on inputs which differ from the training dataset. For predictions of wave-induced ship responses, generalizability is an important consideration if ML methods are to be useful in design evaluations. Furthermore, the size of the training dataset has a significant impact on the practica

Jerrin Bright, Bavesh Balaji, Yuhao Chen, David A Clausi

In the high-stakes world of baseball, every nuance of a pitcher's mechanics holds the key to maximizing performance and minimizing runs. Traditional analysis methods often rely on pre-recorded offline numerical data, hindering their application in the dynamic environment of live games. Broadcast video analysis, while seemingly ideal, faces significant challe

Weiqi Wang, Zhiyi Tian, Chenhan Zhang, Shui Yu

As the right to be forgotten has been legislated worldwide, many studies attempt to design unlearning mechanisms to protect users' privacy when they want to leave machine learning service platforms. Specifically, machine unlearning is to make a trained model to remove the contribution of an erased subset of the training dataset. This survey aims to systemati

Koki Nukui, Satoshi Iihama, Kazuaki Ishibashi, Shogo Yamashita

We investigated photon-helicity-induced magnetization precession in Co$_{1-x}$Pt$_{x}$ alloy thin films. In addition to field-like torque, attributable to magnetic field generation owing to {\it the inverse Faraday effect}, we observed non-trivial and large damping-like torque which has never been discussed for single ferromagnetic layer. The composition dep

Wenhua Yu, Bahareh Nakisa, Seng W. Loke, Svetlana Stevanovic

Exposure to poor indoor air quality poses significant health risks, necessitating thorough assessment to mitigate associated dangers. This study aims to predict hourly indoor fine particulate matter (PM2.5) concentrations and investigate their correlation with outdoor PM2.5 levels across 24 distinct buildings in Australia. Indoor air quality data were gather

Alan Herschtal

Kummer's function, also known as the confluent hypergeometric function (CHF), is an important mathematical function, in particular due to its many special cases, which include the Bessel function, the incomplete Gamma function and the error function (erf). The CHF has no closed form expression, but instead is most commonly expressed as an infinite sum of rat

Juan A. Cañas, A. Martín-Ruiz, J. Bernal

Classical and quantum mechanical descriptions of motion are fundamentally different. The universality of free fall (UFF) is a distinguishing feature of the classical motion (which has been verified with astonishing precision), while quantum theory tell us only about probabilities and uncertainties thus breaking the UFF. There are strong reasons to believe th

Caelan Ritter

Given a finite graph $G$, we define the Ceresa period $\alpha(G)$ as a tool for studying algebraic triviality of the tropical Ceresa cycle introduced by Zharkov. We show that $\alpha(G) = 0$ if and only if $G$ is of hyperelliptic type; then a theorem of Corey implies that having $\alpha(G) = 0$ is a minor-closed condition with forbidden minors $K_4$ and $L_3

Fadi Wassaf

In an attempt to better leverage superconducting quantum computers, scaling efforts have become the central concern. These efforts have been further exacerbated by the increased complexity of these circuits. The added complexity can introduce parasitic couplings and resonances, which may hinder the overall performance and scalability of these devices. We exp

Troy Shinbrot

Exploratory missions have found that regolith on interplanetary bodies can be loosely packed and freely flowing, a state that strongly affects mission plans and that may also influence the large scale shapes of these bodies. We investigate whether notable circumferential ridges seen on Saturn's moons may be a byproduct of free flow of loosely packed regolith

Feng-qing Zhu, Xue-ping Wang

In this article, we first give the characterizations of quasi-homogeneous aggregation functions, which show us that quasi-homogeneous aggregation functions are classified into three classes. We then introduce the concept of triple generator of quasi-homogeneous aggregation function, which is applied to construct a quasi-homogeneous aggregation function.

Frederick Rajasekaran

In this work, we study a class of random matrices which interpolate between the Wigner matrix model and various types of patterned random matrices such as random Toeplitz, Hankel, and circulant matrices. The interpolation mechanism is through the correlations of the entries, and thus these interpolating models are highly inhomogeneous in their correlation st

Alzayat Saleh, Alex Olsen, Jake Wood, Bronson Philippa

Weeds present a significant challenge in agriculture, causing yield loss and requiring expensive control measures. Automatic weed detection using computer vision and deep learning offers a promising solution. However, conventional deep learning methods often require large amounts of labelled training data, which can be costly and time-consuming to acquire. T

Jian Wang, Qinglong Zhou

In this paper, we examine the homotopy classes of positive loops in ${\rm Sp}(2n)$. We demonstrate that two positive loops are homotopic if and only if they are homotopic through positive loops. As consequences, we can extend several results of McDuff \cite{McD} and Chance \cite{Cha} to higher dimensional symplectic manifolds without dimensional restrictions

Yuwen Liu, Jie Ren, Shuangge Ma, Cen Wu

Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy-tailed distributions in the complex traits. In the past decade, robust variable selection methods have emerged as powerful alternatives to the non-robust ones to identify important genes associated with heterogeneous disease traits and build superior predi

Dong-Yeop Na, Fernando L. Teixeira, Yuri A. Omelchenko

A novel electromagnetic particle-in-cell algorithm has been developed for fully kinetic plasma simulations on unstructured (irregular) meshes in complex body-of-revolution geometries. The algorithm, implemented in the BORPIC++ code, utilizes a set of field scalings and a coordinate mapping, reducing the Maxwell field problem in a cylindrical system to a Cart

Zijie Li, Anthony Zhou, Saurabh Patil, Amir Barati Farimani

Accurate weather forecasting is crucial in various sectors, impacting decision-making processes and societal events. Data-driven approaches based on machine learning models have recently emerged as a promising alternative to numerical weather prediction models given their potential to capture physics of different scales from historical data and the significa

Woodrow Hao Chi Kiang

We presents the closed form formulae for the likelihood Hessian matrix of a family of multivariate continuous-trait Gaussian Markov trait evolution model along a given phylogeny, in which the trait vector's mean is an affine function of that of its ancestor and the variance is not dependent of the trait. Accompanied with this work is an R package called 'gli

Meiyu Zhong, Ravi Tandon

With the growing adoption of machine learning (ML) systems in areas like law enforcement, criminal justice, finance, hiring, and admissions, it is increasingly critical to guarantee the fairness of decisions assisted by ML. In this paper, we study the tradeoff between fairness and accuracy under the statistical notion of equalized odds. We present a new uppe

Yuhao Zhang, Mihai Bujanca, Mikel Luján

Many existing visual SLAM methods can achieve high localization accuracy in dynamic environments by leveraging deep learning to mask moving objects. However, these methods incur significant computational overhead as the camera tracking needs to wait for the deep neural network to generate mask at each frame, and they typically require GPUs for real-time oper

Max Yang, Chenghua Lu, Alex Church, Yijiong Lin

Human hands are capable of in-hand manipulation in the presence of different hand motions. For a robot hand, harnessing rich tactile information to achieve this level of dexterity still remains a significant challenge. In this paper, we present AnyRotate, a system for gravity-invariant multi-axis in-hand object rotation using dense featured sim-to-real touch

Wenshuai Jiang, Guofang Wei

In this paper we prove that the space $\cM(n,\rv,D,\Lambda):=\{(M^n,g) \text{ closed }: ~~\Ric\ge -(n-1),~\Vol(M)\ge \rv>0, \diam(M)\le D \text{ and } \int_{M}|\Rm|^{n/2}\le \Lambda\}$ has at most $C(n,\rv,D,\Lambda)$ many diffeomorphism types. This removes the upper Ricci curvature bound of Anderson-Cheeger's finite diffeomorphism theorem in \cite{AnCh}. Fu

Sofiane Chalal, Nina H. Amini, Gaoyue Guo, Hamed Amini

In this paper, we consider a system of heterogeneously interacting quantum particles subject to indirect continuous measurement. The interaction is assumed to be of the mean-field type. We derive a new limiting quantum graphon system, prove the well-posedness of this system, and establish a stability result.

Loren D. Alegria, Alex Abelson, Eunjeong Kim, Soohyun Im

Tantalum films incorporated into superconducting circuits have exhibited low surface losses, resulting in long-lived qubit states. Remaining loss pathways originate in microscopic defects which manifest as two level systems (TLS) at low temperature. These defects limit performance, so careful attention to tantalum film structures is critical for optimal use

Kareem Ahmed, Stefano Teso, Paolo Morettin, Luca Di Liello

Structured output prediction problems are ubiquitous in machine learning. The prominent approach leverages neural networks as powerful feature extractors, otherwise assuming the independence of the outputs. These outputs, however, jointly encode an object, e.g. a path in a graph, and are therefore related through the structure underlying the output space. We

Belle II Collaboration, I. Adachi, L. Aggarwal, H. Aihara

We present the result of a search for the charged-lepton-flavor violating decay $\tau^- \to \mu^-\mu^+\mu^-$ using a $424fb^{-1}$ sample of data recorded by the Belle II experiment at the SuperKEKB $e^{-}e^{+}$ collider. The selection of $e^{-}e^{+}\to\tau^+\tau^-$ events is based on an inclusive reconstruction of the non-signal tau decay, and on a boosted d

Peer-Olaf Siebers

ChatGPT, the AI-powered chatbot with a massive user base of hundreds of millions, has become a global phenomenon. However, the use of Conversational AI Systems (CAISs) like ChatGPT for research in the field of Social Simulation is still limited. Specifically, there is no evidence of its usage in Agent-Based Social Simulation (ABSS) model design. This paper t

Patrick Copinger, James P. Edwards, Anton Ilderton, Karthik Rajeev

We use the worldline formalism to derive Bern-Kosower type Master Formulae for the tree-level scattering of a charged particle and an arbitrary number of photons on impulsive PP-waves, where the coupling of the PP-wave to matter is treated fully non-perturbatively. We show that, in a certain kinematic regime characterised by a semi-classical positive energy

Changxin Dong, Andrea I. d'Aquino, Samya Sen, Ian A. Hall

A promising strategy to address the pressing challenges with wildfire, particularly in the wildland-urban interface (WUI), involves developing new approaches for preventing and controlling wildfire within wildlands. Among sprayable fire-retardant materials, water-enhancing gels have emerged as exceptionally effective for protecting civil infrastructure. They

Mariia Krasikova, Felix Kronowetter, Sergey Krasikov, Mikhail Kuzmin

Resonant states underlie a variety of metastructures that exhibit remarkable capabilities for effective control of acoustic waves at subwavelength scales. The development of metamaterials relies on the rigorous mode engineering providing the implementation of the desired properties. At the same time, the application of metamaterials is still limited as their

Aseem Dalal, Jessica McDonald, Songling Shan

We prove that for any graph $G$, the total chromatic number of $G$ is at most $\Delta(G)+2\left\lceil \frac{|V(G)|}{\Delta(G)+1} \right\rceil$. This saves one color in comparison with a result of Hind from 1992. In particular, our result says that if $\Delta(G)\ge \frac{1}{2}|V(G)|$, then $G$ has a total coloring using at most $\Delta(G)+4$ colors. When $G$

Xiang Cao, Qiaoqiao Ding, Xiaoqun Zhang

The regularized D-bar method is a popular method for solving Electrical Impedance Tomography (EIT) problems due to its efficiency and simplicity. It utilizes the low-pass truncated scattering data in the non-linear Fourier domain to solve the associated D-bar integral equations, yielding a smooth conductivity approximation. However, the D-bar reconstruction

Touraj Soleymani, John S. Baras, Deniz Gündüz

We study feedback control of a dynamical process over a lossy channel equipped with a hybrid automatic repeat request protocol that connects a sensor to an actuator. The dynamical process is modeled by a Gauss-Markov process, and the lossy channel by a packet-erasure channel with ideal feedback. We suppose that data is communicated in the format of packets w

Piotr Frąckiewicz, Anna Gorczyca-Goraj, Marek Szopa

The study focuses on strategic-form games extended in the Eisert-Wilkens-Lewenstein scheme by two unitary operations. Conditions are determined under which the pair of unitary operators, along with classical strategies, form a game invariant under isomorphic transformations of the input classical game. These conditions are then applied to determine these ope

Ali Gharizadeh, Karim Abbasi, Amin Ghareyazi, Mohammad R. K. Mofrad

Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using bio

Nina H. Amini, Paolo Mason, Ibrahim Ramadan

This paper considers a simplified model of open quantum systems undergoing imperfect measurements obtained via a projection filter approach. We use this approximate filter in the feedback stabilization problem specifically in the case of Quantum Non-Demolition (QND) measurements. The feedback design relies on the structure of the exponential family utilized

Thomas Mildner, Albert Inkoom, Rainer Malaka, Jasmin Niess

Throughout the past decade, research in HCI has identified numerous instances of dark patterns in digital interfaces. These efforts have led to a well-fostered typology describing harmful strategies users struggle to navigate. However, an in-depth understanding of the underlying mechanisms that deceive, coerce, or manipulate users is missing. We explore the

François Joint, Kazi Rafsanjani Amin, Ivo Cools, Simone Gasparinetti

Local control of superconducting circuits by high-impedance electrical gates offers potential advantages in superconducting logic, quantum processing units, and cryoelectronics. Recent experiments have reported gate-controlled supercurrent in Dayem bridges made of metallic superconductors, mediated by direct current leakage, out-of-equilibrium phonons, or po

Nan Miles Xi, Hong-Long Ji, Lin Wang

Sarcoidosis is a rare inflammatory disease characterized by the formation of granulomas in various organs. The disease presents diagnostic and treatment challenges due to its diverse manifestations and unpredictable nature. In this study, we employed a Large Language Model (LLM) to analyze sarcoidosis-related discussions on the social media platform Reddit.

Guido Cavraro

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal objectives.

Micah Chrisman, Anup Poudel

A virtual link is said to be almost classical (AC) if it has a homologically trivial representative in some thickened surface $\Sigma \times [0,1]$, where $\Sigma$ is a closed orientable surface. AC links provide a useful window for observing the geometric topology of virtual knots. Here we take a different approach and look at AC links through the lens of q

Shi-ang Qi, Yakun Yu, Russell Greiner

Discrimination and calibration represent two important properties of survival analysis, with the former assessing the model's ability to accurately rank subjects and the latter evaluating the alignment of predicted outcomes with actual events. With their distinct nature, it is hard for survival models to simultaneously optimize both of them especially as man