October 2023 arXiv papers — page 30

Françoise Pène, Benoit Saussol

We are interested in the study of the asymptotic behaviour of return times in small balls for the $T,T^{-1}$-transformation. We exhibit different asymptotic behaviours (different scaling, different limit point process) depending on the respective dimensions of the measures of the two underlying dynamical systems. It behaves either as for the direct product o

Ludovic Levy Patey, Ahmed Mimouni

The Erd\H{o}s-Moser theorem $(\mathsf{EM})$ says that every infinite tournament admits an infinite transitive subtournament. We study the computational behavior of the Erd\H{o}s-Moser theorem with respect to the arithmetic hierarchy, and prove that $\Delta^0_n$ instances of $\mathsf{EM}$ admit low${}_{n+1}$ solutions for every $n \geq 1$, and that if a set $

Francesco Perciavalle, Oliver Morsch, Davide Rossini, Luigi Amico

The coherent quantum transport of matter wave through a ring-shaped circuit attached to leads defines an iconic system in mesoscopic physics that has allowed both to explore fundamental questions in quantum science and to draw important avenues for conceiving devices of practical use. Here we study the source-to-drain transport of excitations going through a

Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Gaetan Lin

Offline-to-online reinforcement learning (RL) is a training paradigm that combines pre-training on a pre-collected dataset with fine-tuning in an online environment. However, the incorporation of online fine-tuning can intensify the well-known distributional shift problem. Existing solutions tackle this problem by imposing a policy constraint on the policy i

Sudipta Ghosh, Steven Sivek, Raphael Zentner

We use instanton gauge theory to prove that if $Y$ is a closed, orientable $3$-manifold such that $H_1(Y;\mathbb{Z})$ is nontrivial and either $2$-torsion or $3$-torsion, and if $Y$ is neither $\#^r \mathbb{RP}^3$ for some $r\geq 1$ nor $\pm L(3,1)$, then there is an irreducible representation $\pi_1(Y) \to \mathrm{SL}(2,\mathbb{C})$. We apply this to show t

Jiayu Qiu, Hai Zhang

Recent progress in topological insulators and topological phases of matter has motivated new methods for the localization of waves in photonic structures. Especially, it is established that a Dirac point of a periodic structure can bifurcate into in-gap eigenvalues if the periodic structure is perturbed differently on the two sides of an interface and if a c

Ömer Şahin Taş, Philipp Heinrich Brusius, Christoph Stiller

Continuous optimization based motion planners require specifying a maneuver class before calculating the optimal trajectory for that class. In traffic, the intentions of other participants are often unclear, presenting multiple maneuver options for the autonomous vehicle. This uncertainty can make it difficult for the vehicle to decide on the best option. Th

Alessia Cattabriga, Paolo Cavicchioli

In this article we deal with the problem of finding equivalence moves for links in Dunwoody and periodic Takahashi manifolds. We represent these manifolds using Heegaard splitting and we represent the embedded links as plat closure of elements in the braid group of the corresponding Heegaard surfaces. More precisely, starting from an open Heegaard diagram fo

I. Akushevich, H. Avakian, A. Ilyichev, S. Srednyak

The lowest order radiative corrections to the cross section and asymmetries measured in experiments on semi-inclusive deep inelastic scattering of polarized particles were calculated. Both exact and leading log expressions were presented and discussed for the total correction that include the contributions from the processes of (i) real photon emission with

Dumitru Motreanu, Abdelkrim Moussaoui

We establish the existence of multiple solutions for singular quasilinear elliptic problems with a precise sign information: two opposite constant sign solutions and a nodal solution. The approach combines sub-supersolutions method and Leray-Schauder topological degree involving perturbation argument.

Simthembile Dlamini, Sheean Jolicoeur, Roy Maartens

In the pursuit of understanding the large-scale structure of the Universe, the synergy between complementary cosmological surveys has proven to be a powerful tool. Using multiple tracers of the large-scale structure can significantly improve the constraints on cosmological parameters. We explore the potential of combining the Square Kilometre Array Observato

Nasibeh Aramideh, Ahmad Moussavi

Birkenmeier and Heider, in [2], say that a ring R is right cP-Baer if the right annihilator of a cyclic projective right R-module in R is generated by an idempotent. These rings are a generalization of the right p.q.-Baer and abelian rings. Generally, a formal power series ring over one indeterminate, wherein its base ring is right p.q.-Baer, is not necessar

Giancarlo Urzúa, Juan Pablo Zúñiga

It is known that all degenerations of the complex projective plane into a surface with only quotient singularities are controlled by the positive integer solutions $(a,b,c)$ of the Markov equation $$x^2+y^2+z^2=3xyz.$$ It turns out that these degenerations are all connected through finite sequences of other simpler degenerations by means of birational geomet

Junling Liu, Ziming Wang, Qichen Ye, Dading Chong

Large Language Models (LLMs) have introduced a new era of proficiency in comprehending complex healthcare and biomedical topics. However, there is a noticeable lack of models in languages other than English and models that can interpret multi-modal input, which is crucial for global healthcare accessibility. In response, this study introduces Qilin-Med-VL, t

D B A Tran, Olivier Lopez, M Manceau, A Goncharov

We report the upgrade and operation of a frequency-comb-assisted high-resolution mid-infrared molecular spectrometer allowing us to combine high spectral purity, SI-traceability, wide tunability and high sensitivity. An optical frequency comb is used to transfer the spectral purity of a SI-traceable 1.54 $\mu$m metrology-grade frequency reference to a 10.3 $

Muhammad Bilal, Dinis Martinho, Reiner Sim, Adnan Qayyum

Coronary angiography analysis is a common clinical task performed by cardiologists to diagnose coronary artery disease (CAD) through an assessment of atherosclerotic plaque's accumulation. This study introduces an end-to-end machine learning solution developed as part of our solution for the MICCAI 2023 Automatic Region-based Coronary Artery Disease diagnost

Peng Xie, Kani Chen

The existing audio datasets are predominantly tailored towards single languages, overlooking the complex linguistic behaviors of multilingual communities that engage in code-switching. This practice, where individuals frequently mix two or more languages in their daily interactions, is particularly prevalent in multilingual regions such as Hong Kong, China.

Shuang Li, Jiaxu Leng, Ji Gan, Mengjingcheng Mo

Visible-Infrared Person Re-Identification (VI-ReID) plays a critical role in all-day surveillance systems. However, existing methods primarily focus on learning appearance features while overlooking body shape features, which not only complement appearance features but also exhibit inherent robustness to modality variations. Despite their potential, effectiv

Shuo Wang, Issei Sato

Deep neural networks are being increasingly implemented throughout society in recent years. It is useful to identify which parameters trigger misclassification in diagnosing undesirable model behaviors. The concept of parameter saliency is proposed and used to diagnose convolutional neural networks (CNNs) by ranking convolution filters that may have caused m

Jorge Martinez Romeral, Aron W. Cummings, Stephan Roche

Topological quantum matter exhibits novel transport phenomena driven by entanglement between internal degrees of freedom, as for instance generated by spin-orbit coupling effects. Here we report on a direct connection between the mechanism driving spin relaxation and the intertwined dynamics between spin and sublattice degrees of freedom in disordered graphe

Chao Yang, Gaoshen Liang, Tianle Cheng, Yang Li

The restoration control of the modern alternating current-direct current (AC-DC) hybrid power grid after a major blackout is difficult and complex. Taking into account the interaction between the line-commutated converter high-voltage direct current (LCC-HVDC) and the AC power grid, this paper proposes a novel optimization method of restoration path to recon

Son Nguyen, Mikel Lainsa, Hung Dao, Daeyoung Kim

Occlusion is a long-standing problem in computer vision, particularly in instance segmentation. ACM MMSports 2023 DeepSportRadar has introduced a dataset that focuses on segmenting human subjects within a basketball context and a specialized evaluation metric for occlusion scenarios. Given the modest size of the dataset and the highly deformable nature of th

Christian Bauer, Yoshiyuki Sakai, Markus Uhlmann

We conducted direct numerical simulations of turbulent open channel flow (OCF) and closed channel flow (CCF) of friction Reynolds numbers up to $\mathrm{Re}_\tau \approx 900$ in large computational domains up to $L_x\times L_z=12\pi h \times 4\pi h$ to analyse the Reynolds number scaling of turbulence intensities. Unlike CCF, our data suggests that the strea

Ge Li, Luming Sun, Xiangjun Chen, Hongyan Zhou

[O III]$\lambda\lambda$4960,5008 doublet are often the strongest narrow emission lines in starburst galaxies and quasi-stellar objects (QSOs), and thus are a promising probe to possible variation of the fine-structure constant $\alpha$ over cosmic time. Previous such studies using QSOs optical spectra were limited to $z<1$. In this work, we constructed a sam

Jorge Olmos-Trigo

The multipolar expansion of the electromagnetic field plays a key role in the study of light-matter interactions. All the information about the radiation and coupling between the incident wavefield and the object is embodied in the electric and magnetic scattering coefficients $\{a_{\ell m}, b_{\ell m} \}$ of the expansion. However, the experimental determin

Dong Qin, George Amariucai, Daji Qiao, Yong Guan

The limited transparency of the inner decision-making mechanism in deep neural networks (DNN) and other machine learning (ML) models has hindered their application in several domains. In order to tackle this issue, feature attribution methods have been developed to identify the crucial features that heavily influence decisions made by these black box models.

Xiaojie Wang, Beibei Wang, Yu Wu, Zhaolong Ning

Edge Intelligence (EI) integrates Edge Computing (EC) and Artificial Intelligence (AI) to push the capabilities of AI to the network edge for real-time, efficient and secure intelligent decision-making and computation. However, EI faces various challenges due to resource constraints, heterogeneous network environments, and diverse service requirements of dif

Yufei Chen, Lei Liu, Yuhao Chi, Ying Li

This paper considers a generalized multiple-input multiple-output (GMIMO) with practical assumptions, such as massive antennas, practical channel coding, arbitrary input distributions, and general right-unitarily-invariant channel matrices (covering Rayleigh fading, certain ill-conditioned and correlated channel matrices). Orthogonal/vector approximate messa

Kun-Yu Lin, Jia-Run Du, Yipeng Gao, Jiaming Zhou

Video domain generalization aims to learn generalizable video classification models for unseen target domains by training in a source domain. A critical challenge of video domain generalization is to defend against the heavy reliance on domain-specific cues extracted from the source domain when recognizing target videos. To this end, we propose to perceive d

Yuta Hyodo, Teruyuki Kitabayashi

Recently, the precise observations have yielded values for the neutrino mixing angles, denoted as ${\theta}_{12}$ and ${\theta}_{13}$. Therefore, constructing a neutrino mixing model capable of accurately reflecting a these measurements is crucial. In this paper, we propose a novel neutrino mixing model similar to the trimaximal mixing model. Unlike the trim

Shaolei Zhang, Yang Feng

Simultaneous sequence generation is a pivotal task for real-time scenarios, such as streaming speech recognition, simultaneous machine translation and simultaneous speech translation, where the target sequence is generated while receiving the source sequence. The crux of achieving high-quality generation with low latency lies in identifying the optimal momen

Rebecca L. Davies, Sirio Belli, Minjung Park, J. Trevor Mendel

We use deep JWST/NIRSpec R~1000 slit spectra of 113 galaxies at 1.7 < z < 3.5, selected from the mass-complete Blue Jay survey, to investigate the prevalence and typical properties of neutral gas outflows at cosmic noon. We detect excess Na I D absorption (beyond the stellar contribution) in 46% of massive galaxies ($\log$ M$_*$/M$_\odot >$ 10), with similar

Luan Alberto Ferreira

This small note proves that the set of triangular numbers is a finitely stable additive basis. This, together with a previous result by the author, shows that triangular numbers and squares are, among all polygonal numbers, the only ones that are finitely stable additive bases.

Xianyu Hu, Johannes Krah

Let X be the blow-up of the projective plane in a finite set of very general points. We deduce from the work of Uehara that X has only standard autoequivalences, no nontrivial Fourier-Mukai partners, and admits no spherical objects. If X is the blow-up of the projective plane in 9 very general points, we provide an alternate and direct proof of the correspon

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using a sample of $(10087\pm44)\times 10^6$ $J/\psi$ events, which is about 45 times larger than that was previously analyzed, a further investigation on the $J/\psi\rightarrow \gamma 3(\pi^+\pi^-)$ decay is performed. A significant distortion at 1.84 GeV/$c^2$ in the line-shape of the $3(\pi^+\pi^-)$ invariant mass spectrum is observed for the first time, w

James Henderson, Alireza Mohammadshahi, Andrei C. Coman, Lesly Miculicich

We argue that Transformers are essentially graph-to-graph models, with sequences just being a special case. Attention weights are functionally equivalent to graph edges. Our Graph-to-Graph Transformer architecture makes this ability explicit, by inputting graph edges into the attention weight computations and predicting graph edges with attention-like functi

Hirotoshi Hirai

Quantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for materials informatics (MI) problems. However, there are only a few examples of the application of QNN to multivariate regress

A. V. Zolotaryuk, Y. Zolotaryuk, V. P. Gusynin

The spectrum of a one-dimensional pseudospin-one Hamiltonian with a three-component potential is studied for two configurations: (i) all the potential components are constants over the whole coordinate space and (ii) the profile of some components is of a rectangular form. In case (i), it is illustrated how the structure of three (lower, middle and upper) ba

Mohana Prasad Sathya Moorthy

Data centers are on the rise and scientists are re-thinking and re-designing networks for data centers. The concept of central control which was not effective in the Internet era is now gaining popularity and is used in many data centers due to lower scale of operation (compared to Internet), structured topologies and as the entire network resources is under

Camille Le Coz, Alexis Tantet, Rémi Flamary, Riwal Plougonven

Ensemble forecasts and their combination are examined from the perspective of probability spaces. Manipulating ensemble forecasts as discrete probability distributions, multi-model ensemble (MME) forecasts are reformulated as barycenters of these distributions. We consider two barycenters, each defined with respect to a different distance metric: the L2 bary

A. I. Ryzhov, O. V. Ivakhnenko, S. N. Shevchenko, M. F. Gonzalez-Zalba

A conventional realization of quantum logic gates and control is based on resonant Rabi oscillations of the occupation probability of the system. This approach has certain limitations and complications, like counter-rotating terms. We study an alternative paradigm for implementing quantum logic gates based on Landau-Zener-St\"{u}ckelberg-Majorana (LZSM) inte

Toshihiro Takahashi, Takaaki Tateishi, Michiaki Tatsubori

Semantic text similarity plays an important role in software engineering tasks in which engineers are requested to clarify the semantics of descriptive labels (e.g., business terms, table column names) that are often consists of too short or too generic words and appears in their IT systems. We formulate this type of problem as a task of matching descriptive

Minquan Cheng, Yun Xie, Zhenhao Huang, Mingming Zhang

In this paper, we study the coded caching scheme for the $(K,L,M_{\text{T}},M_{\text{U}},N)$ partially connected linear network, where there are $N$ files each of which has an equal size, $K+L-1$ transmitters and $K$ users; each user and transmitter caches at most $M_{\text{U}}$ and $M_{\text{T}}$ files respectively; each user cyclically communicates with $L

Akash Yadav, S. K. Mishra

Electrostatic charge dissipation is one of the major concerns for satellites operating in the Earth's orbits. Under energetic plasma conditions, they may acquire very high negative potential (up to 10's of kV) due to the collection of energetic plasma constituents - resulting in temporary outages and permanent damages to onboard equipment. This study propose

Andreas Dechant

Based on a variational expression for the steady-state entropy production rate in overdamped Langevin dynamics, we derive concrete upper bounds on the entropy production rate in various physical settings. For particles in a thermal environment and driven by non-conservative forces, we show that the entropy production rate can be upper bounded by considering

Philip Winchester, Vassilios Dallas, Peter D. Howell

We study the effects of Prandtl number $Pr$ and Rayleigh number $Ra$ in two-dimensional Rayleigh-B\'enard convection without boundaries, i.e. with periodic boundary conditions. In the limits of $Pr \to 0$ and $\infty$, we find that the dynamics are dominated by vertically oriented elevator modes that grow without bound, even at high Rayleigh numbers and with

Tobias King, Yexu Zhou, Tobias Röddiger, Michael Beigl

Designing domain specific neural networks is a time-consuming, error-prone, and expensive task. Neural Architecture Search (NAS) exists to simplify domain-specific model development but there is a gap in the literature for time series classification on microcontrollers. Therefore, we adapt the concept of differentiable neural architecture search (DNAS) to so

Da You Lv, An Min Wang

By introducing the "comparison and replacement" (CNR) operation, we propose a general-purpose pure quantum approximate optimization algorithm and derive its core optimization mechanism quantitatively. The algorithm is constructed to a $p$-level divide-and-conquer structure based on the CNR operations. The quality of approximate optimization improves with the

Jacek Gatlik, Tomasz Dobrowolski, Panayotis G. Kevrekidis

In the present work we explore the interaction of a one-dimensional kink-like front of the sine-Gordon equation moving in 2-dimensional spatial domains. We develop an effective equation describing the kink motion, characterizing its center position dynamics as a function of the transverse variable. The relevant description is valid both in the Hamiltonian re

Shin-itiro Goto

We draw connections between contact topology and Maxwell fields in vacuo on 3-dimensional closed Riemannian submanifolds in 4-dimensional Lorentzian manifolds. This is accomplished by showing that contact topological methods can be applied to reveal topological features of a class of solutions to Maxwell's equations. This class of Maxwell fields is such that

Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, Lidong Bing

Sentiment analysis is a well-established natural language processing task, with sentiment polarity classification being one of its most popular and representative tasks. However, despite the success of pre-trained language models in this area, they often fall short of capturing the broader complexities of sentiment analysis. To address this issue, we propose

Yannick Burkhardt, Qian Feng, Jianxiang Feng, Karan Sharma

Dexterous grasping of unseen objects in dynamic environments is an essential prerequisite for the advanced manipulation of autonomous robots. Prior advances rely on several assumptions that simplify the setup, including environment stationarity, pre-defined objects, and low-dimensional end-effectors. Though easing the problem and enabling progress, it underm

Wei Fan, Weijia Zhang, Weiqi Wang, Yangqiu Song

Conversational Recommender Systems (CRS) illuminate user preferences via multi-round interactive dialogues, ultimately navigating towards precise and satisfactory recommendations. However, contemporary CRS are limited to inquiring binary or multi-choice questions based on a single attribute type (e.g., color) per round, which causes excessive rounds of inter

S. M. Troshin, N. E. Tyurin

The observed absence of the small-$t$ oscillations in differential cross--section of the elastic scattering is considered as a consequence of the reflective scattering mode appearance at the highest energy of the LHC $\sqrt{s}=13$ TeV.

Yu-Tzu Chang, Yang-Hao Chan

Optical responses of atomically thin 2D materials are greatly influenced by electron-hole interactions. It is by far established that exciton signatures can be well-identified in the optical absorption spectrum of quasi-2D materials. However, the same level of understanding of excitonic effects on nonlinear optical responses and the ability to compute them a

Hubert Baty, Vincent Vigon

We present a novel numerical approach aiming at computing equilibria and dynamics structures of magnetized plasmas in coronal environments. A technique based on the use of neural networks that integrates the partial differential equations of the model, and called Physics-Informed Neural Networks (PINNs), is introduced. The functionality of PINNs is explored

Yi Lu, Fei Gao, Yu-Xin Liu, Jan M. Pawlowski

We study the QCD equation of state and other thermodynamic observables including the isentropic trajectories and the speed of sound. These observables are of eminent importance for the understanding of experimental results in heavy ion collisions and also provide a QCD input for studies of the timeline of heavy-ion-collisions with hydrodynamical simulations.

Yukun Zhao, Lingyong Yan, Weiwei Sun, Guoliang Xing

Large Language Models (LLMs) have shown great potential in Natural Language Processing (NLP) tasks. However, recent literature reveals that LLMs generate nonfactual responses intermittently, which impedes the LLMs' reliability for further utilization. In this paper, we propose a novel self-detection method to detect which questions that a LLM does not know t

Harri Hemilä, Matti Pirinen

The effects of treatments on continuous outcomes can be estimated by the mean difference (i.e. by measurement units) and the relative effect scales (i.e. by percentages), both of which provide only a single effect size estimate over the study population. Quantile treatment effect (QTE) analysis is more informative as it describes the effect of the treatment

E. Elson

Measurements of the dependence of stellar specific angular momentum ($j_*$) on stellar mass ($M_*$) are presented for large samples of ALFALFA galaxies spanning the stellar mass range $\sim 10^8$-$10^{11}$ M$_{\odot}$. Accurate estimates of $j_*$ are generated using measurements of $I$-band effective radius and velocity width of the HI line profile. While th

Shao-Bo Lin, Tao Li, Shaojie Tang, Yao Wang

With the help of massive data and rich computational resources, deep Q-learning has been widely used in operations research and management science and has contributed to great success in numerous applications, including recommender systems, supply chains, games, and robotic manipulation. However, the success of deep Q-learning lacks solid theoretical verific

Xingrui Wang, Wufei Ma, Zhuowan Li, Adam Kortylewski

Despite rapid progress in Visual question answering (VQA), existing datasets and models mainly focus on testing reasoning in 2D. However, it is important that VQA models also understand the 3D structure of visual scenes, for example to support tasks like navigation or manipulation. This includes an understanding of the 3D object pose, their parts and occlusi

Md Isfakul Anam, Tuyen Vu

Reducing the fuel consumption within a power network is crucial to enhance the overall system efficiency and minimize operating costs. Fuel consumption minimization can be achieved through different optimization techniques where the output power of the generators is regulated based on their individual efficiency characteristics. Existing studies primarily fo

Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Byung Hoon Ahn

Deep learning accelerators address the computational demands of Deep Neural Networks (DNNs), departing from the traditional Von Neumann execution model. They leverage specialized hardware to align with the application domain's structure. Compilers for these accelerators face distinct challenges compared to those for general-purpose processors. These challeng

Pai Chet Ng, Zhixiang Chi, Yannick Verdie, Juwei Lu

We introduce Hyper-Skin, a hyperspectral dataset covering wide range of wavelengths from visible (VIS) spectrum (400nm - 700nm) to near-infrared (NIR) spectrum (700nm - 1000nm), uniquely designed to facilitate research on facial skin-spectra reconstruction. By reconstructing skin spectra from RGB images, our dataset enables the study of hyperspectral skin an

Chaowei Liu, Jichun Li, Yihua Teng, Chaoqun Wang

For capturing colored document images, e.g. posters and magazines, it is common that multiple degradations such as shadows, wrinkles, etc., are simultaneously introduced due to external factors. Restoring multi-degraded colored document images is a great challenge, yet overlooked, as most existing algorithms focus on enhancing color-ignored document images v

Daniela Elia, Fang Chen, Didar Zowghi, Marian-Andrei Rizoiu

The fast adoption of new technologies forces companies to continuously adapt their operations making it harder to predict workforce requirements. Several recent studies have attempted to predict the emergence of new roles and skills in the labour market from online job ads. This paper aims to present a novel ontology linking business transformation initiativ

Kwang-il Seon

Observations of metallic doublet emission lines, particularly Mg II 2796, 2803, provide crucial information for understanding galaxies and their circumgalactic medium. This study explores the effects of resonant scattering on the Mg II doublet lines and the stellar continuum in spherical and cylindrical geometries. Our findings show that under certain circum

Klaus Zollner, Simão M. João, Branislav K. Nikolić, Jaroslav Fabian

We present a DFT-based investigation of the twist-angle dependent proximity spin-orbit coupling (SOC) in graphene/TMDC structures. We find that for Mo-based TMDCs the proximity valley-Zeeman SOC exhibits a maximum at around 15--20{\deg}, and vanishes at 30{\deg}, while for W-based TMDCs we find an almost linear decrease of proximity valley-Zeeman SOC when tw

Kyu-Hwan Lee

We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of partitions and use them to describe a sufficient condition for Kronecker coefficients to be nonzero. The results provide new methods and perspectives for the study of these coefficient

Ze-Shi Guo, Dan Xing, Xiong-Yu Xi, Cun-Guang Liang

Many countries and commercial organizations have shown great interest in constructing Martian base. In-situ resource utilization (ISRU) provides a cost-effective way to achieve this ambitious goal. In this paper, we proposed to use Martian soil simulant to produce fiber to satisfy material requirement for the construction of Martian base. The composition, me

Rianne C. Prins, Sonja Billerbeck

Small open reading frames are understudied as they have been historically excluded from genome annotations. However, evidence for the functional significance of small proteins in various cellular processes accumulates. Proteins with less than 70 residues can also confer resistance to antimicrobial compounds, including intracellularly-acting protein toxins, m

Thomas R. Cameron, Leslie Hogben, Franklin H. J. Kenter, Seyed Ahmad Mojallal

The (disjoint) fort number and fractional zero forcing number are introduced and related to existing parameters including the (standard) zero forcing number. The fort hypergraph is introduced and hypergraph results on transversals and matchings are applied to the zero forcing number and fort number. These results are used to establish a Vizing-like lower bou

Xinyu She, Yue Liu, Yanjie Zhao, Yiling He

Modern language models (LMs) have been successfully employed in source code generation and understanding, leading to a significant increase in research focused on learning-based code intelligence, such as automated bug repair, and test case generation. Despite their great potential, language models for code intelligence (LM4Code) are susceptible to potential

Nan Ying, Yanli Lei, Tianyi Zhang, Shangqing Lyu

Pathological image analysis is a crucial field in computer-aided diagnosis, where deep learning is widely applied. Transfer learning using pre-trained models initialized on natural images has effectively improved the downstream pathological performance. However, the lack of sophisticated domain-specific pathological initialization hinders their potential. Se

Yang Le, Gao Siyang, Ho Chin Pang

The knowledge gradient (KG) algorithm is a popular policy for the best arm identification (BAI) problem. It is built on the simple idea of always choosing the measurement that yields the greatest expected one-step improvement in the estimate of the best mean of the arms. In this research, we show that this policy has limitations, causing the algorithm not as

Dohoon Lim, Dongkyu Kim, Kyungdeuk Park, Dong-Gil Im

In practical applications to free-space quantum communications, the utilization of active beam coupling and stabilization techniques offers notable advantages, particularly when dealing with limited detecting areas or coupling into single-mode fibers(SMFs) to mitigate background noise. In this work, we introduce highly-enhanced active beam-wander-correction

JoAnn Stonier, Lauren Woodman, Majed Alshammari, Renée Cummings

This briefing paper focuses on data equity within foundation models, both in terms of the impact of Generative AI (genAI) on society and on the further development of genAI tools. GenAI promises immense potential to drive digital and social innovation, such as improving efficiency, enhancing creativity and augmenting existing data. GenAI has the potential to

Yakun Wang, Pengwei Zhao, Jie Meng

The Relativistic Configuration-interaction Density functional (ReCD) theory that combines the advantages of large-scale configuration-interaction shell model and relativistic density functional theory is extended to study nuclear chiral rotation. The energy spectra and transition probabilities of the chiral doublet bands are reproduced satisfactorily without

Shunji Nishimura

In the field of Boolean satisfiability problems (SAT), at-most-k constraints, which suppress the number of true target variables at most k, are often used to describe objective problems. At-most-k constraints are used not only for absolutely necessary constraints (hard constraints) but also for challenging constraints (soft constraints) to search for better

Chu-Cheng Pan, Xiang Dong, Yu-Chang Sun, Ao-Yan Cheng

In the field of modern high-energy physics research, there is a growing emphasis on utilizing deep learning techniques to optimize event simulation, thereby expanding the statistical sample size for more accurate physical analysis. Traditional simulation methods often encounter challenges when dealing with complex physical processes and high-dimensional data

Arunava Patra, Supratim Sengupta, Ayan Paul, Sagar Chakraborty

Strategies for sustaining cooperation and preventing exploitation by selfish agents in repeated games have mostly been restricted to Markovian strategies where the response of an agent depends on the actions in the previous round. Such strategies are characterized by lack of learning. However, learning from accumulated evidence over time and using the eviden

Minjae Cho, Ben Mazel, Xi Yin

We construct the symplectic form on the covariant phase space of the open string field theory on a ZZ-brane in c=1 string theory, and determine the energy of the rolling tachyon solution, confirming Sen's earlier proposal based on boundary conformal field theory and closed string considerations.

Weixu Zhang, Yifei Wang, Yuanfeng Song, Victor Junqiu Wei

The emergence of natural language processing has revolutionized the way users interact with tabular data, enabling a shift from traditional query languages and manual plotting to more intuitive, language-based interfaces. The rise of large language models (LLMs) such as ChatGPT and its successors has further advanced this field, opening new avenues for natur

Chandan Sarma, Praveen C. Srivastava

We have done a systematic no-core shell-model study of $^{20-23}$Na isotopes. The low-energy spectra of these sodium isotopes consisting of natural and un-natural parity states were reported, considering three realistic interactions: inside nonlocal outside Yukawa (INOY), charge-dependent Bonn 2000 (CDB2K), and the chiral next-to-next-to-next-to-leading orde

Md Sabbirul Haque, Md Shahedul Amin, Jonayet Miah, Duc Minh Cao

Prediction of stock prices plays a significant role in aiding the decision-making of investors. Considering its importance, a growing literature has emerged trying to forecast stock prices with improved accuracy. In this study, we introduce an innovative approach for forecasting stock prices with greater accuracy. We incorporate external economic environment

Wujun Shao, Pengli Ji, Dongwei Fan, Yaohua Hu

Astronomical knowledge entities, such as celestial object identifiers, are crucial for literature retrieval and knowledge graph construction, and other research and applications in the field of astronomy. Traditional methods of extracting knowledge entities from texts face challenges like high manual effort, poor generalization, and costly maintenance. Conse

Kosaku Takanashi, Kenichiro McAlinn

We discuss the relation between the statistical question of inadmissibility and the probabilistic question of transience. Brown (1971) proved the mathematical link between the admissibility of the mean of a Gaussian distribution and the recurrence of a Brownian motion, which holds for $\mathbb{R}^{2}$ but not for $\mathbb{R}^{3}$ in Euclidean space. We exten

Wenzhi Fang, Dong-Jun Han, Christopher G. Brinton

Hierarchical federated learning (HFL) has demonstrated promising scalability advantages over the traditional "star-topology" architecture-based federated learning (FL). However, HFL still imposes significant computation, communication, and storage burdens on the edge, especially when training a large-scale model over resource-constrained wireless devices. In

Jawaria Maqbool, Syed Talal Hassan, M. Imran Cheema

Deep learning techniques provide a plausible route towards achieving practical imaging through multimode fibers. The results produced by these methods are often influenced by physical factors like temperature, fiber length, external perturbations, and polarization state of the input light. Literature focuses on these different elements impacting deep-learnin

Gabriel Simmons, Christopher Hare

Of the many commercial and scientific opportunities provided by large language models (LLMs; including Open AI's ChatGPT, Meta's LLaMA, and Anthropic's Claude), one of the more intriguing applications has been the simulation of human behavior and opinion. LLMs have been used to generate human simulcra to serve as experimental participants, survey respondents

Julia Kruk, Caleb Ziems, Diyi Yang

Is aesthetic impact different from beauty? Is visual salience a reflection of its capacity for effective communication? We present Impressions, a novel dataset through which to investigate the semiotics of images, and how specific visual features and design choices can elicit specific emotions, thoughts and beliefs. We posit that the impactfulness of an imag

Gary Hoppenworth

Given an input graph $G = (V, E)$, an additive emulator $H = (V, E', w)$ is a sparse weighted graph that preserves all distances in $G$ with small additive error. A recent line of inquiry has sought to determine the best additive error achievable in the sparsest setting, when $H$ has a linear number of edges. In particular, the work of [Kogan and Parter, ICA

Rui Li, Shuangping Tao

This paper is devoted to studying the regularity properties for the new maximal operator $M_{\varphi}$ and the fractional new maximal operator $M_{\varphi,\beta}$ in the local case. Some new pointwise gradient estimates of $M_{\varphi,\Omega}$ and $M_{\varphi,\beta,\Omega}$ are given. Moreover, the boundedness of $M_{\varphi,\Omega}$ and $M_{\varphi,\beta,\O

Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov

The interactive use of large language models (LLMs) in AI assistants (at work, home, etc.) introduces a new set of inference-time privacy risks: LLMs are fed different types of information from multiple sources in their inputs and are expected to reason about what to share in their outputs, for what purpose and with whom, within a given context. In this work

Mojtaba Ahmadi-Yazdi, Mohammad-Hossein Zare, Hamid Mosadeq, Farhad Fazileh

We study the ground state properties of the $S=\frac{1}{2}$ staggered Heisenberg-$\Gamma$ honeycomb model under a magnetic field based on analytical and numerical methods. Our calculations show that the conventional zigzag and stripy phases are favored because of the staggered Heisenberg interaction away from the pure $\Gamma$ limit. In our classical analysi

Meiyi Li, Javad Mohammadi

Amid the increasing interest in the deployment of Distributed Energy Resources (DERs), the Virtual Power Plant (VPP) has emerged as a pivotal tool for aggregating diverse DERs and facilitating their participation in wholesale energy markets. These VPP deployments have been fueled by the Federal Energy Regulatory Commission's Order 2222, which makes DERs and

Le Hu, Andrew N. Jordan

Determining the Markovianity and non-Markovianity of a quantum process is a critical problem in the theory of open quantum systems, as their behaviors differ significantly in terms of complexity. It is well recognized that a quantum process is Markovian if and only if the quantum master equation can be written in the standard Lindblad form with all rates non

Tristan Aumentado-Armstrong, Ashkan Mirzaei, Marcus A. Brubaker, Jonathan Kelly

Neural Radiance Fields (NeRFs) have proven to be powerful 3D representations, capable of high quality novel view synthesis of complex scenes. While NeRFs have been applied to graphics, vision, and robotics, problems with slow rendering speed and characteristic visual artifacts prevent adoption in many use cases. In this work, we investigate combining an auto

Susu Fang, Yanhao Li, Hao Li

Accurate and efficient localization with conveniently-established map is the fundamental requirement for mobile robot operation in warehouse environments. An accurate AprilTag map can be conveniently established with the help of LiDAR-based SLAM. It is true that a LiDAR-based system is usually not commercially competitive in contrast with a vision-based syst