April 2024 arXiv papers — page 148

Jiadong Chen, Matthew J. Powell-Palm, Wenhao Sun

Designing thermodynamic conditions to improve (or reduce) the stability of a target material is a key task in materials engineering. For example, during materials synthesis one aims to enhance the stability of a target phase relative to its precursors or competing byproduct phases. If an undesired phase forms in experiment, one aims to destabilize the undesi

Woohyeon Baek, Sambit Das, Shibo Tan, Vikram Gavini

Are quasicrystals stable or metastable? Density functional theory (DFT) is often used to evaluate thermodynamic stability, but quasicrystals are long-range aperiodic and their energies cannot be calculated using conventional ab initio methods. Here, we perform first-principles calculations on quasicrystal nanoparticles of increasing sizes, from which we can

Jie Zhang, Jun Li, Long Shi, Zhe Wang

As the next generation of mobile systems evolves, artificial intelligence (AI) is expected to deeply integrate with wireless communications for resource management in variable environments. In particular, deep reinforcement learning (DRL) is an important tool for addressing stochastic optimization issues of resource allocation. However, DRL has to start each

Haris Aziz, Xinhang Lu, Mashbat Suzuki, Jeremy Vollen

In pursuit of participatory budgeting (PB) outcomes with broader fairness guarantees, we initiate the study of lotteries over discrete PB outcomes. As the projects have heterogeneous costs, the amount spent may not be equal ex ante and ex post. To address this, we develop a technique to bound the amount by which the ex-post spend differs from the ex-ante spe

Jiadong Chen, Matthew J. Powell-Palm, Wenhao Sun

Modern materials are often synthesized or operated in complex chemical environments, where there can be numerous elemental species, competing phases, and reaction pathways. When analyzing reactions using the Gibbs free energy, which has a natural variable of composition, it is often cumbersome to solve for the equilibrium states of a complicated heterogeneou

Chenhao Xu, Chang-Tsun Li, Chee Peng Lim, Douglas Creighton

Due to its deficiency in prior knowledge (inductive bias), Vision Transformer (ViT) requires pre-training on large-scale datasets to perform well. Moreover, the growing layers and parameters in ViT models impede their applicability to devices with limited computing resources. To mitigate the aforementioned challenges, this paper introduces a novel horizontal

Pablo Rocha

Let $\rho(\cdot)$ be the Koranyi norm on the Heisenberg group $\mathbb{H}^{n} \equiv (\mathbb{R}^{2n} \times \mathbb{R}, \, \cdot \, )$ defined by \[ \rho(x,t) = \left( |x|^{4} + 16 t^{2} \right)^{1/4}, \,\,\,\, (x,t) \in \mathbb{H}^{n}. \] For $0 \leq \alpha < Q:=2n+2$, $m \in \mathbb{N} \cap \left(1 - \frac{\alpha}{Q}, \infty \right)$, and $m$ positive con

Anthony Pisani, Tomasz Popiel

We determine the conjugacy class fusion from certain maximal subgroups of the Monster to the Monster, to justify the addition of these data to the Character Table Library in the computational algebra system GAP. The maximal subgroups in question are $(\text{PSL}_2(11) {\times} \text{PSL}_2(11)){:}4$, $11^2{:}(5 {\times} 2\text{A}_5)$, $7^2{:}\text{SL}_2(7)$,

Giovanni Ferrer

An operator algebraic tricategory is a higher categorical analogue of an operator algebra. For algebraic tricategories, Gordon, Power, and Street proved that every algebraic tricategory is equivalent to a Gray-category, a result later refined by Gurski. We adapt this result to the context of functional analysis, showing that every operator algebraic tricateg

Hengyu Ye, Jiadong Chen, Shijin Gong, Fuxin Jiang

The intricate nature of time series data analysis benefits greatly from the distinct advantages offered by time and frequency domain representations. While the time domain is superior in representing local dependencies, particularly in non-periodic series, the frequency domain excels in capturing global dependencies, making it ideal for series with evident p

Hao Chang, Branka Vucetic, Wibowo Hardjawana

Inter-carrier interference (ICI) caused by mobile reflectors significantly degrades the conventional orthogonal frequency division multiplexing (OFDM) performance in high-mobility environments. The orthogonal time frequency space (OTFS) modulation system effectively represents ICI in the delay-Doppler domain, thus significantly outperforming OFDM. Existing i

H Laxmi, Anupam Saikia

We consider an infinite family of real quadratic fields $k$ where the discriminant has three distinct odd prime factors, and the prime 2 splits. We show that the unramified Iwasawa module $X(k_{\infty})$ associated with the $\mathbb{Z}_2$-extension of $k$ has a bounded quotient. Thus, we also verify Greenberg's conjecture on the vanishing of Iwasawa invarian

H. Baranwal, A. K. B. Chand

Cyclic contractions generalize the usual contractivities in metric spaces and $b$-MSs. In this paper, we enhance several fixed point theorems related to cyclic (i) Banach self-maps, (ii) Chatterjea contractivities, (iii) Kannan self-mappings, (iv) \'{C}iri\'c and Hardy-Rogers, and (v) Reich contractions including local versions in $b$-metric spaces while als

Melissa Cruz Torres

Precise measurements of the $B_s^0 - \overline{B}_s^0$ mixing parameters provide a powerful test of the Standard Model, offering potential hints to new physics. The LHCb collaboration has performed updated measurements of the $CP$-violating phases $\phi_s^{c\bar{c}s}$ and $\phi_s^{s\bar{s}s}$, which supersede previous results. Also, an alternative approach t

Tianshuo Cong, Delong Ran, Zesen Liu, Xinlei He

Model merging is a promising lightweight model empowerment technique that does not rely on expensive computing devices (e.g., GPUs) or require the collection of specific training data. Instead, it involves editing different upstream model parameters to absorb their downstream task capabilities. However, uncertified model merging can infringe upon the Intelle

Yufeng Yue, Yinan Deng, Jiahui Wang, Yi Yang

Implicit reconstruction of ESDF (Euclidean Signed Distance Field) involves training a neural network to regress the signed distance from any point to the nearest obstacle, which has the advantages of lightweight storage and continuous querying. However, existing algorithms usually rely on conflicting raw observations as training data, resulting in poor map p

Chan-Ho Kim

In his ground-breaking work, K. Kato constructed the Euler system of Beilinson--Kato's zeta elements and proved spectacular results on the Iwasawa main conjecture for elliptic curves and the classical and $p$-adic Birch and Swinnerton-Dyer conjectures by using these elements. The goal of this expository lecture note is to explain how Kato's Euler systems fit

Juan Camilo Mejía-Fragoso, Manuel A. Florez, Rocío Bernal-Olaya

Accurate determination of the geothermal gradient is critical for assessing the geothermal energy potential of a given region. Of particular interest is the case of Colombia, a country with abundant geothermal resources. A history of active oil and gas exploration and production has left drilled boreholes in different geological settings, providing direct me

Chih-Chung Hsu, Chia-Ming Lee, Chun-Hung Sun, Kuang-Ming Wu

Traditional defect classification approaches are facing with two barriers. (1) Insufficient training data and unstable data quality. Collecting sufficient defective sample is expensive and time-costing, consequently leading to dataset variance. It introduces the difficulty on recognition and learning. (2) Over-dependence on visual modality. When the image pa

Chao Gao, Sai Qian Zhang

To enhance the performance of large language models (LLM) on downstream tasks, one solution is to fine-tune certain LLM parameters and make it better align with the characteristics of the training dataset. This process is commonly known as parameter-efficient fine-tuning (PEFT). Due to the scale of LLM, PEFT operations are usually executed in the public envi

Qinglu Min, Jie Zhao, Zhihao Zhang, Chen Min

Deep learning has recently demonstrated its excellent performance on the task of multi-view stereo (MVS). However, loss functions applied for deep MVS are rarely studied. In this paper, we first analyze existing loss functions' properties for deep depth based MVS approaches. Regression based loss leads to inaccurate continuous results by computing mathematic

Zhiyuan Yang, Ryan Rad

Solar Photovoltaic (PV) technology is increasingly recognized as a pivotal solution in the global pursuit of clean and renewable energy. This technology addresses the urgent need for sustainable energy alternatives by converting solar power into electricity without greenhouse gas emissions. It not only curtails global carbon emissions but also reduces relian

Joshua Evan Greene, Andrew Lobb

We construct a version of Lagrangian Floer homology whose chain complex is generated by the inscriptions of a rectangle into a real analytic Jordan curve. By using its associated spectral invariants, we establish that a rectifiable Jordan curve admits inscriptions of a whole interval of rectangles. In particular, it inscribes a square if the area it encloses

Willem P Sijp, Anastasios Panagiotelis

A new methodology is proposed to approximate the time-dependent house price distribution at a fine regional scale using Gaussian mixtures. The means, variances and weights of the mixture components are related to time, location and dwelling type through a non linear function trained by a deep functional approximator. Price indices are derived as means, media

Yasunori Kinoshita, Baitian Li

We present an algebraic algorithm that computes the composition of two power series in softly linear time complexity. The previous best algorithms are $\mathop{\mathrm O}(n^{1+o(1)})$ by Kedlaya and Umans (FOCS 2008) and an $\mathop{\mathrm O}(n^{1.43})$ algebraic algorithm by Neiger, Salvy, Schost and Villard (JACM 2023). Our algorithm builds upon the recen

Jarod Hattab, Eran Palti

The Emergence Proposal suggests that some Swampland criteria, in particular on large field distances, are a consequence of the emergent nature of dynamics for fields in the infrared. In the context of type II string theory compactified on Calabi-Yau manifolds, it proposes that the cubic tree-level piece of the genus-zero prepotential is emergent from integra

Jiajun Feng, Kangzhi Zhou, Xiaowei Zhou, Xiao Fu

Improving the high-temperature performance and low-temperature plasticity of tantalum (Ta) alloys is a significant scientific challenge. We employed first-principles calculations to study the interaction between screw dislocations and solute atoms in the body centered cubic (BCC) structure of Ta, with a particular focus on solid solution softening and streng

Cleaven Chia, Ding Huang, Victor Leong, Jian Feng Kong

The development of single-platform qubits, predominant for most of the last few decades, has driven the progress of quantum information technologies but also highlighted the limitations of various platforms. Some inherent issues such as charge/spin noise in materials hinder certain platforms, while increased decoherence upon attempts to scale-up severely imp

Shayan Zargari, Diluka Galappaththige, Chintha Tellambura, Vincent Poor

This paper introduces a new resource allocation framework for integrated sensing and communication (ISAC) systems, which are expected to be fundamental aspects of sixth-generation networks. In particular, we develop an augmented Lagrangian manifold optimization (ALMO) framework designed to maximize communication sum rate while satisfying sensing beampattern

Elena Grigorescu, Nithish Kumar, Young-San Lin

We present a framework that unifies directed buy-at-bulk network design and directed spanner problems, namely, buy-at-bulk spanners. The goal is to find a minimum-cost routing solution for network design problems that capture economies at scale, while satisfying demands and distance constraints for terminal pairs. A more restricted version of this problem wa

Yiping Li, Gao-Yuan Zhang, Yang Chen, Lei Sun

Resonant scattering (RS) of X-ray line emission in supernova remnants (SNRs) may modify the observed line profiles and fluxes and has potential impact on estimating the physical properties of the hot gas and hence on understanding the SNR physics, but has not been theoretically modeled ever. Here we present our Monte-Carlo simulation of RS effect on X-ray re

Zhengyang Zhao, Haitao Yuan, Nan Jiang, Minxiao Chen

Accurate Traffic Prediction is a challenging task in intelligent transportation due to the spatial-temporal aspects of road networks. The traffic of a road network can be affected by long-distance or long-term dependencies where existing methods fall short in modeling them. In this paper, we introduce a novel framework known as Spatial-Temporal Multi-Granula

Kaustav Das, Greg Markowsky, Binghao Wu

We show that the derivative of the intersection and self-intersection local times of alpha-stable processes are exponentially integrable for certain parameter values. This includes the Brownian motion case. We also discuss related results present in the literature for fractional Brownian motion, and in particular give a counter-example to a result in [Guo, J

Junlin Hou, Jilan Xu, Rui Feng, Hao Chen

Due to the complexity of medical image acquisition and the difficulty of annotation, medical image datasets inevitably contain noise. Noisy data with wrong labels affects the robustness and generalization ability of deep neural networks. Previous noise learning methods mainly considered noise arising from images being mislabeled, i.e. label noise, assuming t

Tham Yik Foong, Heng Zhang, Mao Po Yuan, Danilo Vasconcellos Vargas

Input distribution shift presents a significant problem in many real-world systems. Here we present Xenovert, an adaptive algorithm that can dynamically adapt to changes in input distribution. It is a perfect binary tree that adaptively divides a continuous input space into several intervals of uniform density while receiving a continuous stream of input. Th

Yoshiaki Inoue, Tetsuya Takine

We consider a situation that multiple monitoring applications (each with a different sensor-monitor pair) compete for a common service resource such as a communication link. Each sensor reports the latest state of its own time-varying information source to its corresponding monitor, incurring queueing and processing delays at the shared resource. The primary

Wenyu Cong, Jingtao Shi

This paper is concerned with an indefinite linear-quadratic mean field games of stochastic large-population system, where the individual diffusion coefficients can depend on both the state and the control of the agents. Moreover, the control weights in the cost functionals could be indefinite. A direct approach is used to derive the $\epsilon$-Nash equilibri

Fangyuan Xiao, Xiaoke Wang, Kaitong Sun, Qian Zhao

Corrosion and the formation of by-products resulting from parasitic side reactions, as well as random dendrite growth, pose significant challenges for aqueous zinc-ion batteries (AZIBs). In this study, phytate ammonium is introduced into the traditional dilute Zinc sulfate electrolyte as a multi-functional additive. Leveraging the inherent zincophilic nature

Yu Sheng, Lu Zhang, Xingchen Li, Yifan Duan

Prior point cloud provides 3D environmental context, which enhances the capabilities of monocular camera in downstream vision tasks, such as 3D object detection, via data fusion. However, the absence of accurate and automated registration methods for estimating camera extrinsic parameters in roadside scene point clouds notably constrains the potential applic

Fengrui Tian, Yueqi Duan, Angtian Wang, Jianfei Guo

In this work, we pioneer Semantic Flow, a neural semantic representation of dynamic scenes from monocular videos. In contrast to previous NeRF methods that reconstruct dynamic scenes from the colors and volume densities of individual points, Semantic Flow learns semantics from continuous flows that contain rich 3D motion information. As there is 2D-to-3D amb

Junxu Li, Xingyu Gao

Perturbation theory (PT) might be one of the most powerful and fruitful tools for both physicists and chemists, which has led to a wide variety of applications. Over the past decades, advances in quantum computing provide opportunities for alternatives to classical methods. Recently, a general quantum circuit estimating the low order PT corrections has been

Junze Zhou, P. A. D. Gonçalves, Fabrizio Riminucci, Scott Dhuey

Probing strongly coupled quasiparticle excitations at their intrinsic length scales offers unique insights into their properties and facilitates the design of devices with novel functionalities. In this work, we investigate the formation and emission characteristics of plexcitons, arising from the interaction between surface plasmons in narrow gold nanotrenc

Jonathan Crawford

Parkinsons disease is the second most prevalent neurodegenerative disorder with over ten million active cases worldwide and one million new diagnoses per year. Detecting and subsequently diagnosing the disease is challenging because of symptom heterogeneity with respect to complexity, as well as the type and timing of phenotypic manifestations. Typically, la

Roopkatha Dey, Aivy Debnath, Sayak Kumar Dutta, Kaustav Ghosh

In various real-world applications such as machine translation, sentiment analysis, and question answering, a pivotal role is played by NLP models, facilitating efficient communication and decision-making processes in domains ranging from healthcare to finance. However, a significant challenge is posed to the robustness of these natural language processing m

Manman Wang, Yanfeng Li, Hanqing Liu, Haiqiao Ni

Two-photon interference (TPI) is a fundamental phenomenon in quantum optics and plays a crucial role in quantum information science and technology. TPI is commonly considered as quantum interference with an upper bound of $100\%$ for both the TPI visibility and the beat visibility in contrast to its classical counterpart with a maximum visibility of $50\%$.

Yekaterina Epshteyn, Chun Liu, Masashi Mizuno

In this paper, we study the asymptotic behavior of a class of nonlinear Fokker-Planck type equations in a bounded domain with periodic boundary conditions. The system is motivated by our study of grain boundary dynamics, especially under the non-isothermal environments. To obtain the long time behavior of the solutions, in particular, the exponential decay,

Xing-Xiang Wang, Toshikaze Kariyado, Xiao Hu

In the Letter, Xu et al. reported that edge modes disappear in the expanded structure of Wu-Hu model characterized by $\mathbb{Z}_2$ topological index, while appear in the trivial shrunken structure, when the edge cuts through the hexagonal unit cell. They then concluded that these edge modes are defect modes lacking topological protection. Unfortunately, th

Ali Mortazavi, Junhao Lin, Nishant A. Mehta

In one view of the classical game of prediction with expert advice with binary outcomes, in each round, each expert maintains an adversarially chosen belief and honestly reports this belief. We consider a recently introduced, strategic variant of this problem with selfish (reputation-seeking) experts, where each expert strategically reports in order to maxim

Kohei Ueno

Let $f(z,w)=(p(z),q(z,w))$ be a polynomial skew product such that the degrees of $p$ and $q$ are grater than or equal to $2$. Under one or two conditions, we prove that $f$ is conjugate to a monomial map on an invariant region near infinity. The monomial map and the region are determined by the degree of $p$ and a Newton polygon of $q$. Moreover, the region

Alexander Hazeltine, Baiying Liu, Chi-Heng Lo

In this paper, applying the intersection theory of local Arthur packets, for symplectic and split odd special orthogonal groups G_n, we give the first complete proof of the enhanced Shahidi conjecture on generic representations in local Arthur packets. We also classify unramified representations of Arthur type for G_n, and show that they lie in exactly one l

Saúl Rodríguez Martín

We prove that the Gromov-Hausdorff distance from the circle with its geodesic metric to any simply connected geodesic space is never smaller than $\frac{\pi}{4}$. We also prove that this bound is tight through the construction of a simply connected geodesic space $\mathrm{E}$ which attains the lower bound $\frac{\pi}{4}$. We deduce the first statement from a

Hongxuan Wang, Fan Wang, Ming Tang

The prediction of battery rate performance traditionally relies on computation-intensive numerical simulations. While simplified analytical models have been developed to accelerate the calculation, they usually assume battery performance to be controlled by a single rate-limiting process, such as solid diffusion or electrolyte transport. Here, we propose an

Kush Hari, Hansoul Kim, Will Panitch, Kishore Srinivas

We present STITCH: an augmented dexterity pipeline that performs Suture Throws Including Thread Coordination and Handoffs. STITCH iteratively performs needle insertion, thread sweeping, needle extraction, suture cinching, needle handover, and needle pose correction with failure recovery policies. We introduce a novel visual 6D needle pose estimation framewor

Jungsoo Kang, Jun Zhang

We show that every dynamically convex toric domain in $\mathbb R^4$ admits a $C^1$-neighborhood $\mathcal U$ within the space of star-shaped domains of $\mathbb R^4$ with the following property: for any $X \in \mathcal U$, every Legendrian knot in $\partial X$ admits a Reeb chord with distinct endpoints. A higher dimensional analog is also discussed.

Taotao Ji, Meng Hua, Xuanhong Yan, Chunguo Li

Integrating wireless sensing capabilities into base stations (BSs) has become a widespread trend in the future beyond fifth-generation (B5G)/sixth-generation (6G) wireless networks. In this paper, we investigate intelligent reflecting surface (IRS) enabled wireless localization, in which an IRS is deployed to assist a BS in locating a target in its non-line-

Aramayis Dallakyan, Yang Ni

The discovery of causal relationships from observational data is very challenging. Many recent approaches rely on complexity or uncertainty concepts to impose constraints on probability distributions, aiming to identify specific classes of directed acyclic graph (DAG) models. In this paper, we introduce a novel identifiability criterion for DAGs that places

Rui Mao, Guojing Tian, Xiaoming Sun

Compared to general quantum states, the sparse states arise more frequently in the field of quantum computation. In this work, we consider the preparation for $n$-qubit sparse quantum states with $s$ non-zero amplitudes and propose two algorithms. The first algorithm uses $O(ns/\log n + n)$ gates, improving upon previous methods by $O(\log n)$. We further es

Juan Pablo Alfonzo, Kartheik G. Iyer, Masayuki Akiyama, Greg L. Bryan

The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morphology-SFR connection is well studied, the correlation with past star formation activity is not as well understood. To quan

Haimei Zhao, Jing Zhang, Zhuo Chen, Shanshan Zhao

LiDAR semantic segmentation (LSS) is a critical task in autonomous driving and has achieved promising progress. However, prior LSS methods are conventionally investigated and evaluated on datasets within the same domain in clear weather. The robustness of LSS models in unseen scenes and all weather conditions is crucial for ensuring safety and reliability in

HyoJe Jung, Yunha Kim, Heejung Choi, Hyeram Seo

Medical documentation, including discharge notes, is crucial for ensuring patient care quality, continuity, and effective medical communication. However, the manual creation of these documents is not only time-consuming but also prone to inconsistencies and potential errors. The automation of this documentation process using artificial intelligence (AI) repr

Rohan Deepak Ajwani, Zining Zhu, Jonathan Rose, Frank Rudzicz

Transformer-based Large Language Models (LLMs) have shown exceptional language generation capabilities in response to text-based prompts. However, controlling the direction of generation via textual prompts has been challenging, especially with smaller models. In this work, we explore the use of Prompt Tuning to achieve controlled language generation. Genera

Tomonori Nakamura, Yitao Chen, Ryohei Nemoto, Wenxuan Qian

Moir\'e superlattices consisting of two-dimensional materials have attracted immense attention because of emergent phenomena such as flat band-induced Mott insulating states and unconventional superconductivity. However, the effects of spin-orbit coupling on these materials have not yet been fully explored. Here, we show that single- and double-bilayer antim

Sudhakantha Girmohanta, Yuichiro Nakai, Motoo Suzuki, Yaoduo Wang

We study radius stabilization in the Randall-Sundrum model without assuming any unnaturally large stabilizing scalar potential parameter at the boundary branes ($\gamma$) by the frequently used superpotential method. Employing a perturbative expansion in $1/\gamma^2$ and the backreaction parameter, we obtain approximate analytical expressions for the radion

J. L. B. Line, C. M. Trott, J. H. Cook, B. Greig

We present the first of two papers dedicated to verifying the Australian Epoch of Reionisation pipeline (AusEoRPipe) through simulation. The AusEoRPipe aims to disentangle 21-cm radiation emitted by gas surrounding the very first stars from contaminating foreground astrophysical sources, and has been in development for close to a decade. In this paper, we bu

Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz, Katie Z Luo

Accurate 3D object detection is crucial to autonomous driving. Though LiDAR-based detectors have achieved impressive performance, the high cost of LiDAR sensors precludes their widespread adoption in affordable vehicles. Camera-based detectors are cheaper alternatives but often suffer inferior performance compared to their LiDAR-based counterparts due to inh

Junze Li, Junchao Hu, Ting Luo, Dongliang Chen

Active optical waveguides combine light source and waveguides together in an individual component, which are essential for the integrated photonic chips. Although 1D luminescent materials based optical waveguides were extensively investigated, 2D waveguides allow photons to flow within a plane and serve as an ideal component for the ultracompact photonic cir

Wei Fan

In celestial holography, the massive and massless scalars in 4d space-time are represented by the Fourier transform of the bulk-to-boundary propagators and the Mellin transform of plane waves respectively. Recently, the 3pt celestial amplitude of one massive scalar and two massless scalars was discussed in arXiv:2312.08597. In this paper, we compute the 3pt

Zijia Lu, Bing Shuai, Yanbei Chen, Zhenlin Xu

In this paper, we propose a novel concept of path consistency to learn robust object matching without using manual object identity supervision. Our key idea is that, to track a object through frames, we can obtain multiple different association results from a model by varying the frames it can observe, i.e., skipping frames in observation. As the differences

Myles B. Sherman, Vikram Ravi, Kareem El-Badry, Kritti Sharma

Core-collapse Supernovae (CCSNe) are considered the primary magnetar formation channel, with 15 magnetars associated with supernova remnants (SNRs). A large fraction of these should occur in massive stellar binaries that are disrupted by the explosion, meaning that $\sim45\%$ of magnetars should be nearby high-velocity stars. Here we conduct a multi-waveleng

Haotian Zhou, Yunhan Lin, Longwu Yan, Jihong Zhu

Large Language Models (LLMs) have been widely utilized to perform complex robotic tasks. However, handling external disturbances during tasks is still an open challenge. This paper proposes a novel method to achieve robotic adaptive tasks based on LLMs and Behavior Trees (BTs). It utilizes ChatGPT to reason the descriptive steps of tasks. In order to enable

Francesca Grasso, Stefano Locci, Giovanni Siragusa, Luigi Di Caro

Anthropogenic ecological crisis constitutes a significant challenge that all within the academy must urgently face, including the Natural Language Processing (NLP) community. While recent years have seen increasing work revolving around climate-centric discourse, crucial environmental and ecological topics outside of climate change remain largely unaddressed

Hongbin Cui, Xiaowei Xu

In this paper, we study the stability and minimizing properties of higher codimensional surfaces in Euclidean space associated with the $f$-weighted area-functional $$\mathcal{E}_f(M)=\int_M f(x)\; d \mathcal{H}_k$$ with the density function $f(x)=g(|x|)$ and $g(t)$ is non-negative, which develop the recent works by U. Dierkes and G. Huisken (Math. Ann., 20

Rusiru Gambheera, Daniel Vallières

We initiate the study of Iwasawa theory for branched $\mathbb{Z}_{p}$-towers of finite connected graphs. These towers are more general than what have been studied so far, since the morphisms of graphs involved are branched covers, a particular kind of harmonic morphisms of graphs. We prove an analogue of Iwasawa's asymptotic class number formula for the $p$-

Yu Bi, Yekai Li, Xuan Feng, Xianghang Mi

Despite achieving good performance and wide adoption, machine learning based security detection models (e.g., malware classifiers) are subject to concept drift and evasive evolution of attackers, which renders up-to-date threat data as a necessity. However, due to enforcement of various privacy protection regulations (e.g., GDPR), it is becoming increasingly

Irwandi Hipiny, Johari Abdullah, Noor Alamshah Bolhassan

The manual extraction method of Agarwood resinous compound is laborious work, requires skilled workers, and is subject to human errors. Commercial Agarwood industries have been actively exploring using Computer Numerical Control (CNC) machines to replace human effort for this particular task. The CNC machine accepts a G-code script produced from a binary ima

Nazifa Azam Khan, Mikolaj Cieslak, Ian McQuillan

Artificial neural networks are often used to identify features of crop plants. However, training their models requires many annotated images, which can be expensive and time-consuming to acquire. Procedural models of plants, such as those developed with Lindenmayer-systems (L-systems) can be created to produce visually realistic simulations, and hence images

Hao Chen, Gastón Vergara-Hermosilla, Jihong Zhao

In this paper, we are mainly concerned with the well-posedness of the dissipative surface quasi-geostrophic equation in the framework of variable Lebesgue spaces. Based on some analytical results developed in the variable Lebesgue spaces and the $L^{p}$-$L^{q}$ decay estimates of the fractional heat kernel, we establish the local existence and regularity of

Makoto Enokizono, Kenta Hashizume

We study the minimal model program for lc pairs on projective morphism between complex analytic spaces. More precisely, we generalize the results by Birkar and the second author to the setup by Fujino.

Babak Taheri, Rahul K. Gupta, Daniel K. Molzahn

The DistFlow model accurately represents power flows in distribution systems, but the model's nonlinearities result in computational challenges for many applications. Accordingly, a linear approximation known as \mbox{LinDistFlow} (and its three-phase extension LinDist3Flow) is commonly employed. This paper introduces a parameter optimization algorithm for e

Makoto Enokizono, Kenta Hashizume

Semistable reduction theorem for projective morphisms in the category of complex analytic spaces is established.

Casey O. Barkan

This work explores the manner in which classical phase space distribution functions converge to the microcanonical distribution. We first prove a theorem about the lack of convergence, then define a generalization of the coarse-graining procedure that leads to convergence. We prove that the time evolution of phase space distributions is an isometry for a bro

Oguzhan Can, Marcel Franz

We introduce a novel superconducting qubit architecture utilizing parallel arrays of Josephson junctions. This design offers a substantialy improved relative anharmonicity, typically within the range of $|\alpha_r| \approx 0.1 - 0.3$, while maintaining transition matrix elements in both the charge and flux channels that are on par with those of transmon qubi

Kangkang Deng, Jiang Hu, Jiayuan Wu, Zaiwen Wen

In this paper, we present two novel manifold inexact augmented Lagrangian methods, \textbf{ManIAL} for deterministic settings and \textbf{StoManIAL} for stochastic settings, solving nonsmooth manifold optimization problems. By using the Riemannian gradient method as a subroutine, we establish an $\mathcal{O}(\epsilon^{-3})$ oracle complexity result of \textb

Jingxian Wang, Michael Rubenstein

Spherical robots typically require at least two actuators to achieve controlled 2D planar motion. Here we present Rollbot, the first spherical robot capable of controllably maneuvering on a 2D plane with a single actuator, challenging this assumption. Rollbot rolls on the ground in a circular pattern and controls its motion by changing the trajectory's curva

Hyunjun Park, Jiwon Shin, Hanseok Kim, Jihee Kim

This paper presents an I/O interface with Xtalk Minimizing Affine Signaling (XMAS), which is designed to support high-speed data transmission in die-to-die communication over silicon interposers or similar high-density interconnects susceptible to crosstalk. The operating principles of XMAS are elucidated through rigorous analyses, and its advantages over ex

Yueqi Shen, Matthew A. Psioda, Joseph G. Ibrahim

The BayesPPDSurv (Bayesian Power Prior Design for Survival Data) R package supports Bayesian power and type I error calculations and model fitting using the power and normalized power priors incorporating historical data with for the analysis of time-to-event outcomes. The package implements the stratified proportional hazards regression model with piecewise

Maxim Vavilin, Juan Diego Mazo-Vásquez, Ivan Fernandez-Corbaton

The interaction of light with short light pulses is relevant in optical traps, optical tweezers, and many other applications. The theoretical description of such polychromatic light-matter interaction is challenging, and more so when the object is moving with respect to the light source, albeit with constant speed. Light sails are futuristic examples where s

Ruwayda Alharbi, Ondřej Strnad, Markus Hadwiger, Ivan Viola

Rendering huge biological scenes with atomistic detail presents a significant challenge in molecular visualization due to the memory limitations inherent in traditional rendering approaches. In this paper, we propose a novel method for the interactive rendering of massive molecular scenes based on hardware-accelerated ray tracing. Our approach circumvents GP

Jorge A. Lizarraga

Two systems for a charged particle are studied, the first one when it is under the effect of a constant electric field, and the second one when it is under the effect of a constant electromagnetic field. For both systems, it is possible to find time-dependent conserved operators that can be used to derive time-dependent wave functions to the complete Schr\"o

Hao-Nan Wang, Li-Sheng Geng, Gang Li, Ju-Jun Xie

We have phenomenologically investigated the decays $B_s^0 \to X(3872) \pi^+\pi^- (K^+ K^-)$ and $B_s^0 \to \psi(2S) \pi^+ \pi^- (K^+K^-)$. In our analysis, the scalar meson $f_0(980)$ is formed through the final state interactions of coupled channels $\pi \pi$ and $K\bar{K}$. Our findings indicate that the $\pi^+\pi^-$ invariant mass distribution of the $B_s

Hoang-Long Ngo, Dai Taguchi

We consider the numerical approximation for a class of radial Dunkl processes corresponding to arbitrary (reduced) root systems in $\mathbb{R}^{d}$. This class contains some well-known processes such as Bessel processes, Dyson's Brownian motions, and Wishart processes. We propose some semi--implicit and truncated Euler--Maruyama schemes for radial Dunkl proc

Sebastian Grieninger, Kazuki Ikeda, Ismail Zahed

We analyze the quasi-parton distributions of the lightest $\eta'$ meson in massive two-dimensional Quantum electrodynamics (QED2) by performing a digital quantum simulation on a classical computer (exact diagonalization). The Hamiltonian and boost operators are mapped onto spin qubits in a spatial lattice with open boundary conditions. The lowest excited sta

Shihong Wang, Ruixun Liu, Kaiyu Li, Jiawei Jiang

In Generalized Few-shot Segmentation (GFSS), a model is trained with a large corpus of base class samples and then adapted on limited samples of novel classes. This paper focuses on the relevance between base and novel classes, and improves GFSS in two aspects: 1) mining the similarity between base and novel classes to promote the learning of novel classes,

Teo Susnjak, Peter Hwang, Napoleon H. Reyes, Andre L. C. Barczak

This research pioneers the use of fine-tuned Large Language Models (LLMs) to automate Systematic Literature Reviews (SLRs), presenting a significant and novel contribution in integrating AI to enhance academic research methodologies. Our study employed the latest fine-tuning methodologies together with open-sourced LLMs, and demonstrated a practical and effi

Ioannis Chrysikos, Vicente Cortés, Jan Gregorovič

This articles is devoted to a description of the second-order differential geometry of torsion-free almost quaternionic skew-Hermitian manifolds, that is, of quaternionic skew-Hermitian manifolds $(M, Q, ω)$. We provide a curvature characterization of such integrable geometric structures, based on the holonomy theory of symplectic connections and we study qu

Tanmoy Bera

In this note, we extend the notion of minimal gaps to the higher dimensional sequences. We bound the minimal gap for $(\{\boldsymbol{a}_n\boldsymbolα\}),$ $(\{a_n\boldsymbolα\})$ and $(\{\boldsymbol{a}_n\cdot\boldsymbolα\})$ in terms of cardinality of the difference set of $a_n$ and $\boldsymbol{a}_n,$ where $a_n$ and $a_n^{(1)},\dots,a_n^{(d)}$ are sequence

Yi Yu, Brendan P. Malone, Luigi J. Renzullo

The evaluation of modelled or satellite-derived soil moisture (SM) estimates is usually dependent on comparisons against in-situ SM measurements. However, the inherent mismatch in spatial support (i.e., scale) necessitates a cautious interpretation of point-to-pixel comparisons. The upscaling of the in-situ measurements to a commensurate resolution to that o

Robert J. Ewart, Patrick Reichherzer, Archie F. A. Bott, Matthew W. Kunz

Radio bubbles, ubiquitous features of the intracluster medium around active galactic nuclei, are known to rise buoyantly for multiple scale heights through the intracluster medium (ICM). It is an open question how the bubbles can retain their high-energy cosmic-ray content over such distances. We propose that the enhanced scattering of cosmic rays due to mic

Mainak Bhowmik, Poornendu Kumar

We provide necessary and sufficient conditions for operator-valued functions on arbitrary sets associated with a collection of test functions to have factorizations in several situations.

Yujian Xiong, Wenhui Zhu, Zhong-Lin Lu, Yalin Wang

The reconstruction of human visual inputs from brain activity, particularly through functional Magnetic Resonance Imaging (fMRI), holds promising avenues for unraveling the mechanisms of the human visual system. Despite the significant strides made by deep learning methods in improving the quality and interpretability of visual reconstruction, there remains