April 2024 arXiv papers — page 149

Aleksandr Dolgavin, Mark Yampolskiy, Moti Yung

The increased adoption of additive manufacturing (AM) and the acceptance of AM outsourcing created an ecosystem in which the sending and receiving of digital designs by different actors became normal. It has recently been shown that the STL design files -- most commonly used in AM -- contain steganographic channels. Such channels can allow additional data to

Ziyang Wang, Jian-Qing Zheng, Chao Ma, Tao Guo

Image registration, a critical process in medical imaging, involves aligning different sets of medical imaging data into a single unified coordinate system. Deep learning networks, such as the Convolutional Neural Network (CNN)-based VoxelMorph, Vision Transformer (ViT)-based TransMorph, and State Space Model (SSM)-based MambaMorph, have demonstrated effecti

Denis-Charles Cisinski

We prove that Lefschetz's principle of approximating the cohomology of a possibly singular affine scheme of finite type over a field by the cohomology of a suitable (thickening of a) hyperplane section can be made uniform: in the affine case, we can choose the hyperplane section independently of the cohomology. Using Jouanolou's trick, this gives a new way t

Ruggero Caravita

The perspectives opened by the development of a low-energy antideuteron beam are here reviewed: precision measurements of the antideuteron properties; formation and spectroscopic analysis of antideuteronic atoms and antideuterium; the pioneering synthesis of heavier anti-elements in particle traps and at low energies. Some practical aspects of generating a l

Wei Liu, Satyajit Mojumder, Wing Kam Liu, Wei Chen

A representative volume element (RVE) is a reasonably small unit of microstructure that can be simulated to obtain the same effective properties as the entire microstructure sample. Finite element (FE) simulation of RVEs, as opposed to much larger samples, saves computational expense, especially in multiscale modeling. Therefore, it is desirable to have a fr

Nazar Ponochevnyi, Anastasia Kuzminykh

Recent chart-authoring systems, such as Amazon Q in QuickSight and Copilot for Power BI, demonstrate an emergent focus on supporting natural language input to share meaningful insights from data through chart creation. Currently, chart-authoring systems tend to integrate voice input capabilities by relying on speech-to-text transcription, processing spoken a

Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad

The rise of Transformer architectures has advanced medical image segmentation, leading to hybrid models that combine Convolutional Neural Networks (CNNs) and Transformers. However, these models often suffer from excessive complexity and fail to effectively integrate spatial and channel features, crucial for precise segmentation. To address this, we propose L

Dat Mai

This paper introduces StockGPT, an autoregressive ``number'' model trained and tested on 70 million daily U.S.\ stock returns over nearly 100 years. Treating each return series as a sequence of tokens, StockGPT automatically learns the hidden patterns predictive of future returns via its attention mechanism. On a held-out test sample from 2001 to 2023, daily

Javad Amirian, Mouad Abrini, Mohamed Chetouani

With the increasing presence of social robots in various environments and applications, there is an increasing need for these robots to exhibit socially-compliant behaviors. Legible motion, characterized by the ability of a robot to clearly and quickly convey intentions and goals to the individuals in its vicinity, through its motion, holds significant impor

Hasan Arslan

In this paper, we first introduce the number of signed permutations with exactly $k$ inversions, which is denoted by $i_B(n,k)$ and called \textit{Mahonian numbers of type $B$}. Then we provide a recurrence relation for the Mahonian numbers $i_B(n,k)$. In addition, we give an explicit recursive description for the summation of inversions of all permutations

Nancy Abdallah, Chris McDaniel

We study a certain two-parameter family of non-standard graded complete intersections $A(m,n)$. In case $n=2$, we show that $A(m,2)$ has the strong Lefschetz property and the complex Hodge-Riemann property if and only if $m$ is even. This supports a strengthening of a conjecture of Almkvist on the unimodality of the Hilbert function of $A(m,n)$.

Linpeng Zhang, Noam Zilberstein, Benjamin Lucien Kaminski, Alexandra Silva

We present a novel \emph{weakest pre calculus} for \emph{reasoning about quantitative hyperproperties} over \emph{nondeterministic and probabilistic} programs. Whereas existing calculi allow reasoning about the expected value that a quantity assumes after program termination from a \emph{single initial state}, we do so for \emph{initial sets of states} or \e

Kazunori Iwaki

Cappell-Shaneson homotopy 4-spheres (CS spheres) are potential counterexamples of the smooth 4-dimensional Poincar\'e conjecture. Akbulut proved that infinite CS spheres are diffeomorphic to the standard 4-sphere by Kirby calculus. Kim and Yamada found another family of CS spheres which is composed of standard CS spheres. In this paper, we prove more CS sphe

Sheikh Ifatur Rahman, Mohammad Awwad, Chandan Joishi, Zane-Jamal Eddine

GaN/InGaN microLEDs are a very promising technology for next generation displays. Switching control transistors and their integration are key components in achieving high-performance, efficient displays. Monolithic integration of microLEDs with GaN switching devices provides an opportunity to control microLED output power with capacitive (voltage) control ra

Shurui Gui, Xiner Li, Shuiwang Ji

Test-time adaptation (TTA) addresses distribution shifts for streaming test data in unsupervised settings. Currently, most TTA methods can only deal with minor shifts and rely heavily on heuristic and empirical studies. To advance TTA under domain shifts, we propose the novel problem setting of active test-time adaptation (ATTA) that integrates active learni

R. Krechetnikov, A. Zelnikov

From the onset of the subject, granular media have been defying the toolkit of statistical mechanics thus preventing from understanding their thermodynamical and rheological properties and making them one of the key remaining mysteries in science. In the present work, we offer a resolution to this problem in the case of static granular media by considering a

Jin Zhang, Peter W. Voorhees

A large electric field is typically present in anodic or passive oxide films. Stresses induced by such a large electric field are critical in understanding the breakdown mechanism of thin oxide films and improving their corrosion resistance. In this work, we consider electromechanical coupling through the electrostrictive effect. A continuum model incorporat

Ioannis Diamantis, Sofia Lambropoulou, Sonia Mahmoudi

In this paper we define novel topological invariants of doubly periodic tangles (DP tangles). DP tangles are embeddings of curves in the thickened plane with translational symmetries in two independent directions. We first organize the components of a DP tangle into different interlinked compounds, which are invariants of a DP tangle. The notion of interlink

Kai Sun, Yushi Bai, Ji Qi, Lei Hou

To advance the evaluation of multimodal math reasoning in large multimodal models (LMMs), this paper introduces a novel benchmark, MM-MATH. MM-MATH consists of 5,929 open-ended middle school math problems with visual contexts, with fine-grained classification across difficulty, grade level, and knowledge points. Unlike existing benchmarks relying on binary a

Mohamed El Amine Seddik, Suei-Wen Chen, Soufiane Hayou, Pierre Youssef

The phenomenon of model collapse, introduced in (Shumailov et al., 2023), refers to the deterioration in performance that occurs when new models are trained on synthetic data generated from previously trained models. This recursive training loop makes the tails of the original distribution disappear, thereby making future-generation models forget about the i

Alexandre Muzio, Alex Sun, Churan He

The advancement of deep learning has led to the emergence of Mixture-of-Experts (MoEs) models, known for their dynamic allocation of computational resources based on input. Despite their promise, MoEs face challenges, particularly in terms of memory requirements. To address this, our work introduces SEER-MoE, a novel two-stage framework for reducing both the

Ishani Mondal, Abhilasha Sancheti

In this paper, we assess the robustness (reliability) of ChatGPT under input perturbations for one of the most fundamental tasks of Information Extraction (IE) i.e. Named Entity Recognition (NER). Despite the hype, the majority of the researchers have vouched for its language understanding and generation capabilities; a little attention has been paid to unde

Jingxian Wang, Michael Rubenstein

Complexity, cost, and power requirements for the actuation of individual robots can play a large factor in limiting the size of robotic swarms. Here we present PCBot, a minimalist robot that can precisely move on an orbital shake table using a bi-stable solenoid actuator built directly into its PCB. This allows the actuator to be built as part of the automat

Vlad Fomenko, Han Yu, Jongho Lee, Stanley Hsieh

LoRA (Low-Rank Adaptation) has emerged as a preferred method for efficiently adapting Large Language Models (LLMs) with remarkable simplicity and efficacy. This note extends the original LoRA paper by offering new perspectives that were not initially discussed and presents a series of insights for deploying LoRA at scale. Without introducing new experiments,

Zixuan Wang, Jishen Zhao

We present a unified programming model for heterogeneous computing systems. Such systems integrate multiple computing accelerators and memory units to deliver higher performance than CPU-centric systems. Although heterogeneous systems have been adopted by modern workloads such as machine learning, programming remains a critical limiting factor. Conventional

Hristo Tonchev, Petar Danev

In our previous works, we have studied quantum random walk search algorithm on hypercube, with traversing coin constructed by using generalized Householder reflection and a phase multiplier. When the same phases are used each iteration, the algorithm is robust (stable against errors in the phases) if a certain connection between the phases in the traversing

Yimu Wang, Shuai Yuan, Bo Xue, Xiangru Jian

Recent progress in video-text retrieval has been driven largely by advancements in model architectures and training strategies. However, the representation learning capabilities of videotext retrieval models remain constrained by lowquality and limited training data annotations. To address this issue, we present a novel ViDeoText Retrieval Paradigm with REle

Alexander Osinsky, Roman Bychkov, Mikhail Trefilov, Vladimir Lyashev

In this paper, we propose a new approach to justify a round-off error impact on the accuracy of the linear least squares (LS) solution using Cholesky decomposition. This decomposition is widely employed to inverse a matrix in the linear detector of the Multi-User multi-antenna receiver. The proposed stochastic bound is much closer to actual errors than other

Peng Gao, Liangyi Zhao

Using the method of multiple Dirichlet series, we develop L-functions ratios conjecture with one shift in both the numerator and denominator in certain ranges for quadratic families of Dirichlet and Hecke L-functions of primerelated moduli of imaginary quadratic number fields of class number one under the generalized Riemann hypothesis. As corollaries, we ev

G Palacios, A M S Macêdo, Sumanta Kundu, M A F Gomes

The Random Sequential Adsorption (RSA) problem holds crucial theoretical and practical significance, serving as a pivotal framework for understanding and optimizing particle packing in various scientific and technological applications. Here the problem of the one-dimensional RSA of k-mers onto a substrate with correlated defects controlled by uniform and pow

Yizhuo Gao, Radu Tatar

We study (0,2) two-dimensional theories in type IIB configurations with D5 branes wrapping blow-up ${\bf{P}}^1$ cycles of deformed resolutions for $A_n$ singularities or in T-dual IIA configurations with suspended D4 branes. We consider deformations of four dimensional ${\cal{N}}=2, \prod_{i=1}^{n} U(N_i)$ theories with general superpotentials for the adjoin

P. Rota, V. Bozza, M. Hundertmark, E. Bachelet

Context. Gravitational microlensing is a method that is used to discover planet-hosting systems at distances of several kiloparsec in the Galactic disk and bulge. We present the analysis of a microlensing event reported by the Gaia photometric alert team that might have a bright lens. Aims. In order to infer the mass and distance to the lensing system, the p

Norma G. Sanchez

We provide a quantum unifying picture for black holes of all masses and their main properties covering classical, semiclassical, Planckian and trans-Planckian gravity domains: Space-time, size, mass, vacuum ("zero point") energy, temperature, partition function, density of states and entropy. Novel results of this paper are: Black hole {\bf interiors} are al

Zhaolin Wang, Xidong Mu, Yuanwei Liu

The performance of near-field sensing (NISE) in a legacy wideband multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) communication system is analyzed. The maximum likelihood estimates (MLE) for the target's distance and angle relative to the antenna array are derived. To evaluate the estimation error, closed-form analytic

Yao Hu, Haihui Lan, Junjun He, Wenjing Fang

Despite the immense potential of Dual Single-Atom Compounds (DSACs), the challenges in their synthesis process, including complexity, stability, purity, and scalability, remain primary concerns in current research. Here, we present a general strategy, termed "Entropy-Engineered Middle-In Synthesis of Dual Single-Atom Compounds" (EEMIS-DSAC), which is meticul

Zetong Xuan, Alper Kamil Bozkurt, Miroslav Pajic, Yu Wang

Surrogate rewards for linear temporal logic (LTL) objectives are commonly utilized in planning problems for LTL objectives. In a widely-adopted surrogate reward approach, two discount factors are used to ensure that the expected return approximates the satisfaction probability of the LTL objective. The expected return then can be estimated by methods using t

Stefano Scanzio, Gianluca Cena, Adriano Valenzano

Embedding a programming language in a QR code is a new and extremely promising opportunity, as it makes devices and objects smarter without necessarily requiring an Internet connection. In this paper, all the steps needed to translate a program written in a high-level programming language to its binary representation encoded in a QR code, and the opposite pr

Chiara Plizzari, Shubham Goel, Toby Perrett, Jacob Chalk

As humans move around, performing their daily tasks, they are able to recall where they have positioned objects in their environment, even if these objects are currently out of their sight. In this paper, we aim to mimic this spatial cognition ability. We thus formulate the task of Out of Sight, Not Out of Mind - 3D tracking active objects using observations

Marcin Kolakowski, Jozef Modelski

This paper presents an adaptive anchor pairs selection algorithm for UWB (ultra-wideband) TDOA-based (Time Difference of Arrival) indoor positioning systems. The method assumes dividing the system operation area into zones. The most favorable anchor pairs are selected by minimizing the positioning errors in doorways leading to these zones where possible user

Sri Harsha Dumpala, Chandramouli Shama Sastry, Rudolf Uher, Sageev Oore

Previous works on depression detection use datasets collected in similar environments to train and test the models. In practice, however, the train and test distributions cannot be guaranteed to be identical. Distribution shifts can be introduced due to variations such as recording environment (e.g., background noise) and demographics (e.g., gender, age, etc

Deepak G Skariah, Muthuvel Arigovindan

We propose a regularization-based image restoration scheme for 2D images recorded over time (2D+t). We design an infimal convolution-based regularization function which we call spatio-temporal Adaptive Infimal Convolution (STAIC) regularization. We formulate the infimal convolution in the form of an additive decomposition of the 2D+t image such that the exte

Sourav Mandal, Sagar Mandal

In this paper we propose necessary upper bounds for the second, third and fourth smallest prime divisors of friends of 10 based on the number of distinct prime divisors of it.

Zihan Wang, Bowen Li, Chen Wang, Sebastian Scherer

Few-shot object detection has drawn increasing attention in the field of robotic exploration, where robots are required to find unseen objects with a few online provided examples. Despite recent efforts have been made to yield online processing capabilities, slow inference speeds of low-powered robots fail to meet the demands of real-time detection-making th

Lei Liu, Eduardo Maldonado-Cruz, Honggeun Jo, Maša Prodanović

The characterization of subsurface models relies on the accuracy of subsurface models which request integrating a large number of information across different sources through model conditioning, such as data conditioning and geological concepts conditioning. Conventional geostatistical models have a trade-off between honoring geological conditioning (i.e., q

Marcin Kolakowski

The following paper presents an adaptive anchor pairs selection method for ultra-wideband (UWB) Time Difference of Arrival (TDOA) based positioning systems. The method divides the area covered by the system into several zones and assigns them anchor pair sets. The pair sets are determined during calibration based on localization root mean square error (RMSE)

S. B. Kolonitskii, L. M. Lerman, A. I. Nazarov

We study the stationary Swift--Hohenberg equation $(\Delta + 1)^2 u - \alpha u - \beta u^2 + u^3=0$ in the whole space $\mathbb R^n$, $2\le n \le 7$. We develop and modify the variational approach introduced by Lerman, Naryshkin and Nazarov (2020) and obtain a series of periodic solutions with certain additional symmetries.

Sergey D. Prosnyak, Leonid V. Skripnikov

The effects induced by the time-reversal ($\mathcal{T}$) and spatial parity ($\mathcal{P}$) violating electron-nucleus and electron-electron interactions mediated by the axion-like particles (ALPs) in the BaF molecule were estimated. Molecular parameters characterizing these interactions were calculated across a wide range of ALP masses. In case of the elect

Zhiqiang Cai, Tong Ding, Min Liu, Xinyu Liu

In this paper, we propose a structure-guided Gauss-Newton (SgGN) method for solving least squares problems using a shallow ReLU neural network. The method effectively takes advantage of both the least squares structure and the neural network structure of the objective function. By categorizing the weights and biases of the hidden and output layers of the net

Shiwei Jin, Zhen Wang, Lei Wang, Peng Liu

Facial action unit (AU) intensity plays a pivotal role in quantifying fine-grained expression behaviors, which is an effective condition for facial expression manipulation. However, publicly available datasets containing intensity annotations for multiple AUs remain severely limited, often featuring a restricted number of subjects. This limitation places cha

Shir Nitzan, Maya Gilad, Moti Freiman

Effective surgical planning for breast cancer hinges on accurately predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Diffusion-weighted MRI (DWI) and machine learning offer a non-invasive approach for early pCR assessment. However, most machine-learning models require manual tumor segmentation, a cumbersome and error-prone ta

Entejar Alam, Peter Müller, Paul J. Rathouz

The recently developed semi-parametric generalized linear model (SPGLM) offers more flexibility as compared to the classical GLM by including the baseline or reference distribution of the response as an additional parameter in the model. However, some inference summaries are not easily generated under existing maximum-likelihood based inference (ML-SPGLM). T

Clara C. Wanjura, Amelie Mayländer, Othmar Marti, Raphael Blumenfeld

Modelling the dynamics of dense granular media is a long standing challenge and essential to many natural phenomena and technological applications. Here, we trace back puzzling experimental observation of detailed-balanced steady states to self-organisation of the neighbour probability distribution. The emergence of detailed balance in non-equilibrium granul

Wenlu Tang, Zicheng Liu

The performance of machine learning models can be impacted by changes in data over time. A promising approach to address this challenge is invariant learning, with a particular focus on a method known as invariant risk minimization (IRM). This technique aims to identify a stable data representation that remains effective with out-of-distribution (OOD) data.

Kunle Adegoke, Robert Frontczak, Taras Goy

We evaluate in closed form several alternating infinite series involving the binomial coefficients $C(4n,2n)$ and $C(4n+2,2n+1)$ in the denominator. One of our results generalizes an identity that was obtained experimentally by Sprugnoli in 2006.

Zhiyu Liang, Chen Liang, Zheng Liang, Hongzhi Wang

Unsupervised (a.k.a. Self-supervised) representation learning (URL) has emerged as a new paradigm for time series analysis, because it has the ability to learn generalizable time series representation beneficial for many downstream tasks without using labels that are usually difficult to obtain. Considering that existing approaches have limitations in the de

Michael Strauss

The mechanical properties of the human lip between relaxed and fully contracted are not enough to explain the full range of professional brass players. Brass players manipulate their mouth cavity and vocal tract which act as Helmholtz resonators driving the lips. Brass players increase their upper ranges by reducing the amount of lip mass that vibrates using

Elita A. Lobo, Cyrus Cousins, Yair Zick, Marek Petrik

In reinforcement learning, robust policies for high-stakes decision-making problems with limited data are usually computed by optimizing the \emph{percentile criterion}. The percentile criterion is approximately solved by constructing an \emph{ambiguity set} that contains the true model with high probability and optimizing the policy for the worst model in t

Jiawei Li, Zhongmin Qian

We consider Mckean-Vlasov type stochastic differential equations with multiplicative noise arising from the random vortex method. Such an equation can be viewed as the mean-field limit of interacting particle systems with singular interacting kernels such as the Biot-Savart kernel. A new estimate for the transition probability density of diffusion processes

Timothy Y. Chow

We revive an old lateral-thinking puzzle by Michael Rabin, involving poisons with strange properties. We show that the puzzle admits several unintended solutions that are just as interesting as the intended solution. Analyzing these alternative solutions using game theory yields surprisingly subtle results and several unanswered questions.

Yifan Li, Anh Dao, Wentao Bao, Zhen Tan

Facial affective behavior analysis (FABA) is crucial for understanding human mental states from images. However, traditional approaches primarily deploy models to discriminate among discrete emotion categories, and lack the fine granularity and reasoning capability for complex facial behaviors. The advent of Multi-modal Large Language Models (MLLMs) has been

Haitong Ma, Zhaolin Ren, Bo Dai, Na Li

We study sim-to-real skill transfer and discovery in the context of robotics control using representation learning. We draw inspiration from spectral decomposition of Markov decision processes. The spectral decomposition brings about representation that can linearly represent the state-action value function induced by any policies, thus can be regarded as sk

Howard Ziyu Han, Franklin Mingzhe Li, Alesandra Baca Vazquez, Daragh Byrne

Sidewalk robots are increasingly common across the globe. Yet, their operation on public paths poses challenges for people with mobility disabilities (PwMD) who face barriers to accessibility, such as insufficient curb cuts. We interviewed 15 PwMD to understand how they perceive sidewalk robots. Findings indicated that PwMD feel they have to compete for spac

Md. Shahriar Rahman Anuvab, Mishkat Sultana, Md. Atif Hossain, Shashwata Das

Automatic License Plate Recognition (ALPR) is an integral component of an intelligent transport system with extensive applications in secure transportation, vehicle-to-vehicle communication, stolen vehicles detection, traffic violations, and traffic flow management. The existing license plate detection system focuses on one-shot learners or pre-trained model

Donald V. Reames

Solar energetic particles (SEPs) in the small "impulsive" events, primarily accelerated during magnetic reconnection in solar jets, have strong enhancements of the abundances of increasingly heavy elements. In contrast, the shock acceleration of ambient coronal plasma in most large "gradual" SEP events produces flat or decreasing abundances vs. element mass-

Bishwas Mandal, George Amariucai, Shuangqing Wei

We investigate the application of large language models (LLMs), specifically GPT-4, to scenarios involving the tradeoff between privacy and utility in tabular data. Our approach entails prompting GPT-4 by transforming tabular data points into textual format, followed by the inclusion of precise sanitization instructions in a zero-shot manner. The primary obj

Liqiang Jing, Xinya Du

Large Vision-Language Models (LVLMs) have demonstrated proficiency in tackling a variety of visual-language tasks. However, current LVLMs suffer from misalignment between text and image modalities which causes three kinds of hallucination problems, i.e., object existence, object attribute, and object relationship. To tackle this issue, existing methods mainl

Roberto Gallotta, Antonios Liapis, Georgios N. Yannakakis

Evolutionary search via the quality-diversity (QD) paradigm can discover highly performing solutions in different behavioural niches, showing considerable potential in complex real-world scenarios such as evolutionary robotics. Yet most QD methods only tackle static tasks that are fixed over time, which is rarely the case in the real world. Unlike noisy envi

Sujoy Bhore, Balázs Keszegh, Andrey Kupavskii, Hung Le

We study spanners in planar domains, including polygonal domains, polyhedral terrain, and planar metrics. Previous work showed that for any constant $\epsilon\in (0,1)$, one could construct a $(2+\epsilon)$-spanner with $O(n\log(n))$ edges (SICOMP 2019), and there is a lower bound of $\Omega(n^2)$ edges for any $(2-\epsilon)$-spanner (SoCG 2015). The main op

Morteza Maleki, SeyedAli Ghahari

This report embarks on a mission to revolutionize clinical trial protocol development through the integration of advanced AI technologies. With a focus on leveraging the capabilities of generative AI, specifically GPT-4, this initiative aimed to streamline and enhance the efficiency and accuracy of clinical trial protocols. The methodology encompassed a deta

Bishwas Mandal, George Amariucai, Shuangqing Wei

We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and utility attributes. Unlike previous studies that primarily focus on scenarios where all users share identical private and utility attributes and often rely on auxiliary datasets or

Greg Knese

Motivated by studying boundary singularities of rational functions in two variables that are analytic on a domain, we investigate local integrability on $\mathbb{R}^2$ near $(0,0)$ of rational functions with denominator non-vanishing in the bi-upper half-plane but with an isolated zero (with respect to $\mathbb{R}^2$) at the origin. Building on work of Bicke

Musengamana Jean de Dieu, Peng Liang, Mojtaba Shahin

Developers reuse programming-related knowledge on Q&A sites that functionally matches the programming problems they encounter in their development. Despite extensive research on Q&A sites, being a high-level and important type of development-related knowledge, architectural solutions and their reuse are rarely explored. To fill this gap, we conducted a mixed

Harsh Sharma, David A. Najera-Flores, Michael D. Todd, Boris Kramer

Complex mechanical systems often exhibit strongly nonlinear behavior due to the presence of nonlinearities in the energy dissipation mechanisms, material constitutive relationships, or geometric/connectivity mechanics. Numerical modeling of these systems leads to nonlinear full-order models that possess an underlying Lagrangian structure. This work proposes

Nisal Perera, Shangqun Yu, Daniel Marew, Mack Tang

We introduce StaccaToe, a human-scale, electric motor-powered single-leg robot designed to rival the agility of human locomotion through two distinctive attributes: an actuated toe and a co-actuation configuration inspired by the human leg. Leveraging the foundational design of HyperLeg's lower leg mechanism, we develop a stand-alone robot by incorporating n

Illias Klanurak, Kenji Watanabe, Takashi Taniguchi, Sojiphong Chatraphorn

Bernal-stacked tetralayer graphene (4LG) exhibits intriguing low-energy properties, featuring two massive subbands and showcasing diverse features of topologically distinct, anisotropic Fermi surfaces, including Lifshitz transitions and trigonal warping. Here, we study the influence of the band structure on electron dynamics within 4LG using transverse magne

C. J. A. P. Martins, A. M. M. Vieira

The redshift dependence of the cosmic microwave background temperature, $T(z)=T_0(1+z)$, is a key prediction of standard cosmology, but this relation is violated in many extensions thereof. Current astrophysical facilities can probe it in the redshift range $0\le z\le6.34$. We extend recent work by Gelo {\it et al.} (2022) showing that for several classes of

Jonny Rhea, Alex Towle, Mihai Cosma

Hyperdrive is a protocol designed to facilitate the trading of fixed and variable rate assets. The protocol's unique pricing model consolidates liquidity into a single pool which addresses the challenges of fragmented liquidity across terms, eliminates the need for rollovers, and allows terms to be issued on demand. Its design meaningfully improves trading e

Yu Zhang, Di Jin, Jacob Klein

Fusion of lipid bilayers in membranes is important in processes from vesicle-cell interactions (as in drug delivery) to exosome-cell signaling, while transient transmembrane electric fields are known to occur spontaneously. Two contacting phosphatidylcholine (PC) lipid membranes are known to fuse into one under external electric fields, suggesting that the i

Karel Devriesere, László Csató, Dries Goossens

Every sport needs rules. Tournament design refers to the rules that determine how a tournament, a series of games between a number of competitors, is organized. This study aims to provide an overview of the tournament design literature from the perspective of operational research. Three important design criteria are discussed: efficacy, fairness, and attract

Zijian Song, Guanyu Zhu

We investigate boundaries of 3D color codes and provide a systematic classification into 101 distinct boundary types, including two novel classes. The first class consists of 1 boundary and is generated by sweeping the codimension-1 (2D) $T$-domain wall across the system and attaching it to the $X$-boundary that condenses only magnetic fluxes. Since the $T$-

Han-Sheng Li, Yicheng Feng, Fuqiang Wang

Chiral Magnetic Effect (CME) is a phenomenon in which electric charge is separated by a strong magnetic field from local domains of chirality imbalance in quantum chromodynamics. The CME-sensitive, azimuthal correlator difference $\Delta\gamma$ between opposite-sign (OS) and same-sign (SS) charged hadron pairs is contaminated by a major physics background pr

Yi-Peng Wu

Starobinsky's $R^2$ inflation manifests a best-fit scenario for the power spectrum of primordial density fluctuations. Observables derived from the slow-roll picture of the $R^2$ model in the Einstein frame relies on the conformal transformation of the metric, which inevitably induces a unique exponential-type couplings of the rolling scalaron with all matte

Anna Durkalec, Agnieszka Pollo, Ummi Abbas

Conventional studies of galaxy clustering within the framework of halo models typically assume that the density profile of all dark matter haloes can be approximated by the Navarro-Frenk-White (NFW) spherically symmetric profile. However, both modern N-body simulations and observational data suggest that most haloes are either oblate or prolate, and almost n

Shiyi Zhang, Wenxun Dai, Sujia Wang, Xiangwei Shen

Action quality assessment (AQA) has become an emerging topic since it can be extensively applied in numerous scenarios. However, most existing methods and datasets focus on single-person short-sequence scenes, hindering the application of AQA in more complex situations. To address this issue, we construct a new multi-person long-form video dataset for action

Luis A. Sánchez

In the framework of the Asymptotic Safety scenario for quantum gravity, we analyze quantum gravity modifications to the thermal characteristics of a thin accretion disk spiraling around a renormalization group improved (RGI-) Kerr black hole in the low energy regime. We focused on the quantum effects on the location of the innermost stable circular orbit (IS

Aryan Bhambu, Arabin Kumar Dey

This research paper introduces innovative approaches for multivariate time series forecasting based on different variations of the combined regression strategy. We use specific data preprocessing techniques which makes a radical change in the behaviour of prediction. We compare the performance of the model based on two types of hyper-parameter tuning Bayesia

Mojtaba Raouf, Mohammad Hossein Purabbas, Fatemeh Fazel Hesar

This review examines the relationship between black hole activity and kinematic gas-star misalignment in brightest group galaxies (BGGs) with different merger rates. The formation history of galaxy groups is assessed through "age-dating" as an indicator of distinct major mergers involving the BGG. BGGs within groups characterized by a higher frequency of maj

Boyoon Lee, Theodore Molla, Brendan Nagle

Of a given bipartite graph $G = (V, E)$, it is elementary to construct a bipartition in time $O(|V| + |E|)$. For a given $k$-graph $H = H^{(k)}$ with $k \geq 3$ fixed, Lov\'asz proved that deciding whether $H$ is bipartite is NP-complete. Let $\mathcal{B}_n$ denote the collection of all $[n]$-vertex bipartite $k$-graphs. We construct, of a given $H \in \math

Hridis K. Pal

The conventional low-energy theory employed to describe twisted bilayer graphene (TBG) relies on a local interlayer Hamiltonian. According to this theory, TBG has the same linear-in-momentum dispersion and spinor wave function at the Dirac point as single-layer graphene (SLG), albeit with a renormalized velocity that decreases as the rotation angle between t

Shenbagaraj Kannapiran, Sreenithy Chandran, Suren Jayasuriya, Spring Berman

The study of non-line-of-sight (NLOS) imaging is growing due to its many potential applications, including rescue operations and pedestrian detection by self-driving cars. However, implementing NLOS imaging on a moving camera remains an open area of research. Existing NLOS imaging methods rely on time-resolved detectors and laser configurations that require

Saravanabalagi Ramachandran, Jonathan Horgan, Ganesh Sistu, John McDonald

Hierarchical topological representations can significantly reduce search times within mapping and localization algorithms. Although recent research has shown the potential for such approaches, limited consideration has been given to the suitability and comparative performance of different global feature representations within this context. In this work, we e

Valentin Koch, Sophia J. Wagner, Salome Kazeminia, Ece Sancar

In hematology, computational models offer significant potential to improve diagnostic accuracy, streamline workflows, and reduce the tedious work of analyzing single cells in peripheral blood or bone marrow smears. However, clinical adoption of computational models has been hampered by the lack of generalization due to large batch effects, small dataset size

Nir Billfeld, Moshe Kim

We develop a novel identification strategy as well as a new estimator for context-dependent causal inference in non-parametric triangular models with non-separable disturbances. Departing from the common practice, our analysis does not rely on the strict monotonicity assumption. Our key contribution lies in leveraging on diffusion models to formulate the str

Isaiah Gray, Qinwen Deng, Qi Tian, Michael Chilcote

$\alpha$-MnTe is an antiferromagnetic semiconductor with above room temperature $T_N$ = 310 K, which is promising for spintronic applications. Recently, it was reported to be an altermagnet, containing bands with momentum-dependent spin splitting; time-resolved experimental probes of MnTe are therefore important both for understanding novel magnetic properti

Weilin Cai, Juyong Jiang, Le Qin, Junwei Cui

Expert parallelism has emerged as a key strategy for distributing the computational workload of sparsely-gated mixture-of-experts (MoE) models across multiple devices, enabling the processing of increasingly large-scale models. However, the All-to-All communication inherent to expert parallelism poses a significant bottleneck, limiting the efficiency of MoE

Boris Bilich, Adam Dor-On

Arveson's hyperrigidity conjecture predicts that if the non-commutative Choquet boundary of a separable operator system $\mathcal{S}$ is the entire spectrum of its generated C*-algebra $\mathcal{B}$ then $\mathcal{S}$ is hyperrigid in $\mathcal{B}$. We provide a counterexample to the conjecture with a C*-algebra $\mathcal{B}$ of type I generated by a single

Maria Manuel Clementino, Carlos Fitas, Dirk Hofmann

It is shown that the duals of several categories of topological flavour, like the categories of ordered sets, generalised metric spaces, probabilistic metric spaces, topological spaces, approach spaces, are quasivarieties, presenting a common proof for all such results.

Fanjie Kong, Yanbei Chen, Jiarui Cai, Davide Modolo

Open-world detection poses significant challenges, as it requires the detection of any object using either object class labels or free-form texts. Existing related works often use large-scale manual annotated caption datasets for training, which are extremely expensive to collect. Instead, we propose to transfer knowledge from vision-language models (VLMs) t

Davide Poderini, Ranieri Nery, George Moreno, Santiago Zamora

Generalizations of Bell's theorem, particularly within quantum networks, are now being analyzed through the causal inference lens. However, the exploration of interventions, a central concept in causality theory, remains significantly unexplored. In this work we give an initial step in this direction, by analyzing the instrumental scenario and proposing nove

Shenghai Yuan, Jinfa Huang, Yujun Shi, Yongqi Xu

Recent advances in Text-to-Video generation (T2V) have achieved remarkable success in synthesizing high-quality general videos from textual descriptions. A largely overlooked problem in T2V is that existing models have not adequately encoded physical knowledge of the real world, thus generated videos tend to have limited motion and poor variations. In this p