August 2022 arXiv papers — page 96

Eiichi Oishi, Yasuhiro Fujii, Akitoshi Koreeda, Takuya Satoh

We observed quasi-elastic light scattering (QELS) in BiFeO$_3$ using Raman spectroscopy over a temperature range of 300-860 K. The QELS has two components: a narrow and broad component. The temperature dependence of the intensity and linewidth of the broad component differed below and beyond the N\'eel point, and the broad QELS may have a magnetic origin.

Xiaowen Cao, Zhonghao Lyu, Guangxu Zhu, Jie Xu

Over-the-air federated edge learning (Air-FEEL) has emerged as a promising solution to support edge artificial intelligence (AI) in future beyond 5G (B5G) and 6G networks. In Air-FEEL, distributed edge devices use their local data to collaboratively train AI models while preserving data privacy, in which the over-the-air model/gradient aggregation is exploit

Hyoje Lee, Yeachan Park, Hyun Seo, Myungjoo Kang

To boost the performance, deep neural networks require deeper or wider network structures that involve massive computational and memory costs. To alleviate this issue, the self-knowledge distillation method regularizes the model by distilling the internal knowledge of the model itself. Conventional self-knowledge distillation methods require additional train

T. J. Woinoski, I. V. Bajic

Sports analytics has been an up-and-coming field of research among professional sporting organizations and academic institutions alike. With the insurgence and collection of athlete data, the primary goal of such analysis is to improve athletes' performance in a measurable and quantifiable manner. This work is aimed at alleviating some of the challenges enco

Zhemin Li, Tao Sun, Hongxia Wang, Bao Wang

The explicit low-rank regularization, e.g., nuclear norm regularization, has been widely used in imaging sciences. However, it has been found that implicit regularization outperforms explicit ones in various image processing tasks. Another issue is that the fixed explicit regularization limits the applicability to broad images since different images favor di

Chang-Zhi Lu, Tingting Zhang, Tong-Jie Zhang

Damped Lyman-$\alpha$ Absorber (DLA), or HI 21cm Absorber (H21A), is an important probe to model-independently measure the acceleration of spectroscopic velocity ($v_\mathrm{S}$) via the Sandage-Loeb (SL) effect. Confined by the shortage of DLAs and Background Radio Sources (BRSs) with adequate information, the detectable amount of DLAs is ambiguous in the b

Hiroto Akaike

We study automorphism groups of fibered surfaces for finite cyclic covering fibrations of an elliptic surface. We estimate the order of a finite subgroup of automorphism groups in terms of the genus of the fiber, the genus of the base curve, the covering degree and the square of the relative canonical divisor.

Jie Zhu, Leye Wang, Xiao Han

The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, which hinders the large-scale deployment on resource-restricted devices (e.g., smartphones). To mitigate this issue, AI software compression plays a crucial role, which aims to compress model size while keeping high performance. However, the intrinsic defects in

Tianchen Zhao, James Stokes, Shravan Veerapaneni

Variational optimization of neural-network representations of quantum states has been successfully applied to solve interacting fermionic problems. Despite rapid developments, significant scalability challenges arise when considering molecules of large scale, which correspond to non-locally interacting quantum spin Hamiltonians consisting of sums of thousand

Yujiang Pu, Xiaoyu Wu

Video anomaly detection is recently formulated as a multiple instance learning task under weak supervision, in which each video is treated as a bag of snippets to be determined whether contains anomalies. Previous efforts mainly focus on the discrimination of the snippet itself without modeling the temporal dynamics, which refers to the variation of adjacent

Yang Liu, Pengfei Li, Yukun Liu

Capture-recapture experiments are widely used to estimate the abundance of a finite population. Based on capture-recapture data, the empirical likelihood (EL) method has been shown to outperform the conventional conditional likelihood (CL) method. However, the current literature on EL abundance estimation ignores behavioral effects, and the EL estimates may

Santanu Mondal, Biswaraj Palit, Sandip K. Chakrabarti

We study the spectral properties and accretion flow behavior of an ultraluminous X-ray source M82\,X-1 using {\it NuSTAR} observations. We use the physical two component advective flow (TCAF) model to fit the data and to derive the accretion flow properties of the source. From the model fitted parameters, we found that M82\,X-1 is harboring an intermediate m

Jerome Taupin, Yassir Jedra, Alexandre Proutiere

We investigate the problem of best policy identification in discounted linear Markov Decision Processes in the fixed confidence setting under a generative model. We first derive an instance-specific lower bound on the expected number of samples required to identify an $\varepsilon$-optimal policy with probability $1-\delta$. The lower bound characterizes the

Yufei Wang, David Held, Zackory Erickson

Robotic manipulation of highly deformable cloth presents a promising opportunity to assist people with several daily tasks, such as washing dishes; folding laundry; or dressing, bathing, and hygiene assistance for individuals with severe motor impairments. In this work, we introduce a formulation that enables a collaborative robot to perform visual haptic re

Ke Xu, Jianqiao Wangni, Yifan Zhang, Deheng Ye

Data explosion and an increase in model size drive the remarkable advances in large-scale machine learning, but also make model training time-consuming and model storage difficult. To address the above issues in the distributed model training setting which has high computation efficiency and less device limitation, there are still two main difficulties. On o

David C Groothuizen Dijkema, Claire M Postlethwaite

Dynamical systems containing heteroclinic cycles and networks can be invoked as models of intransitive competition between three or more species. When populations are assumed to be well-mixed, a system of ordinary differential equations (ODEs) describes the interaction model. Spatially extending these equations with diffusion terms creates a system of partia

Fei Cao, Pierre-Emmanuel Jabin

We investigate the unbiased model for money exchanges: agents give at random time a dollar to one another (if they have one). Surprisingly, this dynamics eventually leads to a geometric distribution of wealth (shown empirically by Dragulescu and Yakovenko in [11] and rigorously in [2,12,15,18]). We prove a uniform-in-time propagation of chaos result as the n

Sayantan Chakraborty, Aditya Nema, Francesco Buscemi

Local pure states represent a fundamental resource in quantum information theory. In this work we obtain one-shot achievable bounds on the rates for local purity distillation, in the single-party and in the two-party cases. In both situations, local noisy operations are freely available, while in the two-party case also one-way classical communication can be

Anj Simmons, Rajesh Vasa, Antonio Giardina

This paper demonstrates our vision for knowledge graphs that assist machines to reason about the cause of signals observed by sensors. We show how the approach allows for constructing smarter surveillance systems that reason about the most likely cause (e.g., an attacker breaking a window) of a signal rather than acting directly on the received signal withou

Constantine Yannouleas, Uzi Landman

The influence of strong electron-electron interactions and Wigner-molecule (WM) formation on the spectra of $2e$ singlet-triplet double-dot Si qubits is presented based on a full configuration interaction (FCI) approach that incorporates the valley degree of freedom (VDOF) in the context of the continuous (effective mass) description of semiconductor materia

Amir M. Jazayeri

Space-time reflection symmetry (PT symmetry) in non-Hermitian electronic models has drawn much attention over the past decade mainly because it guarantees that the band structures calculated under open boundary conditions be the same as those calculated under periodic boundary conditions. PT symmetry in electromagnetic (EM) models, which are usually borrowed

Rishabh Singh Chauhan, Christoffer Riis, Shishir Adhikari, Sybil Derrible

This article presents one of the pioneering studies on causal modeling in travel mode choice decision-making using causal discovery algorithms. These models are a major advancement from conventional correlation-based techniques. We propose a novel methodology that combines causal discovery with structural equation modeling (SEM). This modeling approach overc

Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang

Product description generation is a challenging and under-explored task. Most such work takes a set of product attributes as inputs then generates a description from scratch in a single pass. However, this widespread paradigm might be limited when facing the dynamic wishes of users on constraining the description, such as deleting or adding the content of a

Qihan Guo, Siwei Wang, Jun Zhu

We study an extension of standard bandit problem in which there are R layers of experts. Multi-layered experts make selections layer by layer and only the experts in the last layer can play arms. The goal of the learning policy is to minimize the total regret in this hierarchical experts setting. We first analyze the case that total regret grows linearly wit

Xujie Zhang, Yu Sha, Michael C. Kampffmeyer, Zhenyu Xie

Cross-modal fashion image synthesis has emerged as one of the most promising directions in the generation domain due to the vast untapped potential of incorporating multiple modalities and the wide range of fashion image applications. To facilitate accurate generation, cross-modal synthesis methods typically rely on Contrastive Language-Image Pre-training (C

Rishabh Singh Chauhan, Matthew Wigginton Bhagat-Conway, Tassio Magassy, Nicole Corcoran

The COVID-19 pandemic is an unprecedented global crisis that has impacted virtually everyone. We conducted a nationwide online longitudinal survey in the United States to collect information about the shifts in travel-related behavior and attitudes before, during, and after the pandemic. The survey asked questions about commuting, long distance travel, worki

Jingyi Chen, Yuxiang Li

We prove uniform convergence of metrics $g_k$ on a closed surface with bounded integral curvature (measure) in the sense of A.D. Alexandrov, under the assumption that the curvature measures $\mathbb{K}_{g_k}=\mu^1_k-\mu^2_k$, where $\mu^1_k,\mu^2_k$ are nonnegative Radon measures converging weakly to measures $\mu^1,\mu^2$ respectively, and $\mu^1$ is less t

Raúl Fuentes-Azcatl, José Rafael Bordin, Marcia C. Barbosa

In this work, the dielectric behavior of water inside charged nanoslit of graphene is studied to analized the water molecules under electrical confinement; through polarizing the nanoslit of graphene, creating an electric field inside the nanopore. How the water molecules are structured under this type of electrical confinement is studied with two force fiel

Yue Fu, Wenquan Liu, Xiangyu Ye, Ya Wang

We report an experimental investigation of quantum correlations in a two-qutrit spin system in a single nitrogen-vacancy center in diamond at room temperatures. Quantum entanglement between two qutrits was observed at room temperature and the existence of non-classical correlations beyond entanglement in the qutrit case has been revealed. Our work demonstrat

Tiankai Hang, Huan Yang, Bei Liu, Jianlong Fu

Recent works on language-guided image manipulation have shown great power of language in providing rich semantics, especially for face images. However, the other natural information, motions, in language is less explored. In this paper, we leverage the motion information and study a novel task, language-guided face animation, that aims to animate a static fa

Jia-Xin Zhuang, Xiansong Huang, Yang Yang, Jiancong Chen

In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms. Various medical image analysis methods, including 2D/3D medical image classification, segmentation, localisation, and detection, have been included

Tommaso Grigoletto, Francesco Ticozzi

The problem of reducing a Hidden Markov Model (HMM) to one of smaller dimension that exactly reproduces the same marginals is tackled by using a system-theoretic approach. Realization theory tools are extended to HMMs by leveraging suitable algebraic representations of probability spaces. We propose two algorithms that return coarse-grained equivalent HMMs o

Ibrahim Yilmaz, Mahmoud Abouyoussef

Fingerprint evidence plays an important role in a criminal investigation for the identification of individuals. Although various techniques have been proposed for fingerprint classification and feature extraction, automated fingerprint identification of fingerprints is still in its earliest stage. The performance of traditional \textit{Automatic Fingerprint

Qiang Gao, Shiyu Fan, Qisi Wang, Jiarui Li

Strongly correlated materials often respond sensitively to the external perturbations. In the recently discovered superconducting infinite-layer nickelates, the superconducting transition temperature can be dramatically enhanced via only ~1% compressive strain-tuning enabled by substrate design. However, the root of such enhancement remains elusive. While th

Peter Humphries, Rizwanur Khan

Let $g$ be a Hecke-Maass cusp form on the modular surface ${\rm SL}_2(\mathbb{Z})\backslash\mathbb{H}$, namely an $L^2$-normalised nonconstant Laplacian eigenfunction on ${\rm SL}_2(\mathbb{Z})\backslash\mathbb{H}$ that is additionally a joint eigenfunction of every Hecke operator. We prove the $L^4$-norm bound $\|g\|_4\ll_{\varepsilon}\lambda_g^{3/304+\vare

Seong-Kyun Mok, Seoyeon Kang, Jeongwoo Kim, Eun-Sun Cho

MBA (mixed boolean and arithmetic) expressions are hard to simplify, so used for malware obfuscation to hinder analysts' diagnosis. Some MBA simplification methods with high performance have been developed, but they narrowed the target to "linear" MBA expressions, which allows efficient solutions based on logic/term-rewriting. However such restrictions are n

Katepalli R. Sreenivasan, Kartik P. Iyer, Ashvin Vinodh

We use well-resolved direct numerical simulations of high-Reynolds-number turbulence to study a fundamental statistical property of turbulence -- the asymmetry of velocity increments -- with likely implications on important dynamics. This property, ignored by existing small-scale phenomenological models, manifests most prominently in the non-monotonic trend

Zhong Ji, Zhishen Hou, Xiyao Liu, Yanwei Pang

Few-shot Class-Incremental Learning (FSCIL) aims at learning new concepts continually with only a few samples, which is prone to suffer the catastrophic forgetting and overfitting problems. The inaccessibility of old classes and the scarcity of the novel samples make it formidable to realize the trade-off between retaining old knowledge and learning novel co

Tapas Tripura, Souvik Chakraborty

Extracting governing physics from data is a key challenge in many areas of science and technology. The existing techniques for equations discovery are dependent on both input and state measurements; however, in practice, we only have access to the output measurements only. We here propose a novel framework for learning governing physics of dynamical system f

Brais González-Rodríguez, Raúl Alvite-Pazó, Samuel Alvite-Pazó, Bissan Ghaddar

Conic optimization has recently emerged as a powerful tool for designing tractable and guaranteed algorithms for non-convex polynomial optimization problems. On the one hand, tractability is crucial for efficiently solving large-scale problems and, on the other hand, strong bounds are needed to ensure high quality solutions. In this research, we investigate

Muhammad Karam Shehzad, Luca Rose, Muhammad Furqan Azam, Mohamad Assaad

Channel state information (CSI) is of pivotal importance as it enables wireless systems to adapt transmission parameters more accurately, thus improving the system's overall performance. However, it becomes challenging to acquire accurate CSI in a highly dynamic environment, mainly due to multi-path fading. Inaccurate CSI can deteriorate the performance, par

Akshay Thakur, Tapas Tripura, Souvik Chakraborty

Operator learning frameworks, because of their ability to learn nonlinear maps between two infinite dimensional functional spaces and utilization of neural networks in doing so, have recently emerged as one of the more pertinent areas in the field of applied machine learning. Although these frameworks are extremely capable when it comes to modeling complex p

Sangjun Han, Hyeongrae Ihm, Moontae Lee, Woohyung Lim

Since most of music has repetitive structures from motifs to phrases, repeating musical ideas can be a basic operation for music composition. The basic block that we focus on is conceptualized as loops which are essential ingredients of music. Furthermore, meaningful note patterns can be formed in a finite space, so it is sufficient to represent them with co

Vivek Nair, Gonzalo Munilla Garrido, Dawn Song

Virtual reality (VR) telepresence applications and the so-called "metaverse" promise to be the next major medium of human-computer interaction. However, with recent studies demonstrating the ease at which VR users can be profiled and deanonymized, metaverse platforms carry many of the privacy risks of the conventional internet (and more) while at present off

Alexander J. Barrios

Let $n>1$ be an integer such that $X_{0}\!\left( n\right) $ has genus $0$, and let $K$ be a field of characteristic $0$ or relatively prime to $6n$. In this article, we explicitly classify the isogeny graphs of all rational elliptic curves that admit a non-trivial isogeny over $\mathbb{Q}$. We achieve this by introducing $56$ parameterized families of ellipt

T. Kobayashi, Y. Kato, H. Taniguchi, T. Tsumuraya

We present $^{127}$I nuclear quadrupole resonance spectra and nuclear relaxation of $\alpha$-(BEDT-TTF)$_2$I$_3$ that undergoes a charge-ordering transition. Only one of the two I$_3$ anion sites shows a significant differentiation in the electric field gradients across the first-order transition. The charge modulation only in the BEDT-TTF layers can not rep

Durmus Demir

Universality of motion under gravity, the equivalence principle, is violated for quantum particles. Here, we study time it takes for a quantum particle to scatter from the gravitational potential, and show that the scattering time, formulated here using the opportune Bohmian formulation, acts as an indicator of the equivalence principle violation. The scatte

Theerapat Tansuwannont, Balint Pato, Kenneth R. Brown

The Shor fault-tolerant error correction (FTEC) scheme uses transversal gates and ancilla qubits prepared in the cat state in syndrome extraction circuits to prevent propagation of errors caused by gate faults. For a stabilizer code of distance $d$ that can correct up to $t=\lfloor(d-1)/2\rfloor$ errors, the traditional Shor scheme handles ancilla preparatio

Mousumi Roy, Swarnendu Mandal, Chittaranjan Hens, Awadhesh Prasad

In the field of complex dynamics, multistable attractors have been gaining a significant attention due to its unpredictability in occurrence and extreme sensitivity to initial conditions. Co-existing attractors are abundant in diverse systems ranging from climate to finance, ecological to social systems. In this article, we investigate a data-driven approach

Samuel Ozminkowski, Claudia Solis-Lemus

1. In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify regions in the brain that are associated with specific human traits, yet their potential to elucidate microbial drivers in biological phenotypes for microbiome research remains unknow

Daniel Duarte, Jack Jeffries, Luis Núñez-Betancourt

We initiate the study of the resolution of singularities properties of Nash blowups over fields of prime characteristic. We prove that the iteration of normalized Nash blowups desingularizes normal toric surfaces. We also introduce a prime characteristic version of the logarithmic Jacobian ideal of a toric variety and prove that its blowup coincides with the

René L. Warren

The ability to characterize proteins at sequence-level resolution is vital to biological research. Currently, the leading method for protein sequencing is by liquid chromatography mass spectrometry (LC-MS) whereas proteins are reduced to their constituent peptides by enzymatic digest and subsequently analyzed on an LC-MS instrument. The short peptide sequenc

Gill Barequet, Shion Fukuzawa, Michael T. Goodrich, David M. Mount

Motivated by blockchain technology for supply-chain tracing of ethically sourced diamonds, we study geometric polyhedral point-set pattern matching as minimum-width polyhedral annulus problems under translations and rotations. We provide two $(1 + \varepsilon)$-approximation schemes under translations with $O(\varepsilon^{-d} n)$-time for $d$ dimensions and

Patrick Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin

Programming Language Processing (PLP) using machine learning has made vast improvements in the past few years. Increasingly more people are interested in exploring this promising field. However, it is challenging for new researchers and developers to find the right components to construct their own machine learning pipelines, given the diverse PLP tasks to b

Samudra Dasgupta, Travis S. Humble

Quantum computation has made considerable progress in the last decade with multiple emerging technologies providing proof-of-principle experimental demonstrations of such calculations. However, these experimental demonstrations of quantum computation face technical challenges due to the noise and errors that arise from imperfect implementation of the technol

Mohammad Taghi Dabiri, Mazen Hasna, Walid Saad

In this paper, an unmanned aerial vehicles (UAV)-based heterogeneous network is studied to solve the problem of transferring massive traffic of distributed small cells to the core network. First, a detailed three-dimensional (3D) model of the downlink channel is characterized by taking into account the real antenna pattern, UAVs' vibrations, random distribut

Ruben Merlijn van Dijk, Enis Kaya

Metrized graphs are nonarchimedean analogues of Riemann surfaces, and Arakelov-Green functions on these graphs are of fundamental importance for some aspects of arithmetic geometry. In the present paper, we give an explicit formula for an admissible Arakelov-Green function on a metrized graph, extending Cinkir's formula for the canonical Arakelov-Green f

Ting-Wei Chao, Zichao Dong

We give a new unified proof that any simple graph on $n$ vertices with maximum degree at most $Δ$ has no more than $a\binom{Δ+1}{t}+\binom{b}{t}$ cliques of size $t \ (t \ge 3)$, where $n = a(Δ+1)+b \ (0 \le b \le Δ)$.

Merlin Carl, Philipp Schlicht

We introduce and study some variants of a notion of canonical set theoretical truth. By this, we mean truth in a transitive proper class model $M$ of ZFC that is uniquely characterized by some $\in$-formula. We show that there are interesting statements that hold in all such models, but do not follow from ZFC, such as the ground model axiom and the nonexiste

Jason J. Wang, Peter Gao, Jeffrey Chilcote, Julien Lozi

The atmospheres of gas giant planets are thought to be inhomogeneous due to weather and patchy clouds. We present two full nights of coronagraphic observations of the HR 8799 planets using the CHARIS integral field spectrograph behind the SCExAO adaptive optics system on the Subaru Telescope to search for spectrophomometric variability. We did not detect sig

Cristina-Madalina Dragan, Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Publicly available diabetic retinopathy (DR) datasets are imbalanced, containing limited numbers of images with DR. This imbalance contributes to overfitting when training machine learning classifiers. The impact of this imbalance is exacerbated as the severity of the DR stage increases, affecting the classifiers' diagnostic capacity. The imbalance can be ad

Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song

Open-vocabulary models like CLIP achieve high accuracy across many image classification tasks. However, there are still settings where their zero-shot performance is far from optimal. We study model patching, where the goal is to improve accuracy on specific tasks without degrading accuracy on tasks where performance is already adequate. Towards this goal, w

Maria E. Camisassa, Nicholas A. Featherstone

The solar convection zone rotates differentially, with its equatorial region rotating more rapidly than the polar regions. This form of differential rotation, also observed in many other low-mass stars, is understood to arise when Coriolis effects are stronger than those associated with buoyant driving of the convection. When buoyancy dominates, a so-called

H. Akatsuka, T. Andalib, B. Bell, J. Berean-Dutcher

Electroless nickel plating is an established industrial process that provides a robust and relatively low-cost coating suitable for transporting and storing ultracold neutrons (UCN). Using roughness measurements and UCN-storage experiments we characterized UCN guides made from polished aluminum or stainless-steel tubes plated by several vendors. All electrol

Joshua Stucky

We study the sums $$ S_f(x) = \sum_{n\leq x} f\left(\left\lfloor\frac{x}{n}\right\rfloor\right) $$ when $f$ is supported on $r$th powers with $r\geq 2$. This restriction allows us to give nontrivial estimates for one of the error terms in the asymptotic expansion of $S_f(x)$. We also state several conjectures related to our results.

Antong Zhang, Jiani Yang, Yangcheng Luo, Siteng Fan

Energy has been propelling the development of human civilization for millennia, and technologies acquiring energy beyond human and animal power have been continuously advanced and transformed. In 1964, the Kardashev Scale was proposed to quantify the relationship between energy consumption and the development of civilizations. Human civilization presently st

A. S. Pereira, A. S. Lemos, F. A. Brito

We obtain the squeezed coherent states (SCS) for a free particle with exponentially time-varying mass. We write these states in terms of the squeeze and displacement parameters on the time-independent Fock states. Thus, we find a condition on the displacement parameter such that the SCS can be considered semiclassical states. We show that it is possible to o

Arkady Shekhter, Chandra M. Varma

We present Hartree-Fock calculations on a simple model to obtain the conditions of formation of local magnetic moments due to loop-currents $L_o$ and spin-loop currents $L_s$ and compare them to the conditions of formation of local spin-moments $M$ which were given long ago in a similar approximation by Anderson. A model with three degenerate orbitals sittin

Vivek Nair, Dawn Song

We present the first general construction of a Multi-Factor Key Derivation Function (MFKDF). Our function expands upon password-based key derivation functions (PBKDFs) with support for using other popular authentication factors like TOTP, HOTP, and hardware tokens in the key derivation process. In doing so, it provides an exponential security improvement ove

Benjamin Kuznets-Speck, David T Limmer

We develop a theory for inferring equilibrium transition rates from trajectories driven by a time dependent force using results from stochastic thermodynamics. Applying the Kawasaki relation to approximate the nonequilibrium distribution function in terms of the equilibrium distribution function and the excess dissipation, we formulate a nonequilibrium trans

Damian Pinasco

We prove that given any set of $n$ unit vectors $\{v_i\}_{i=1}^{n}\subset \mathbb R^n,$ the inequality \[ \sup\limits_{\Vert x \Vert_{\mathbb R^n} =1} \vert \langle x, v_1 \rangle \cdots \langle x, v_n\rangle\vert \ge n^{-n/2} \] holds for $n \le 14.$ Moreover, the equality is attained if and only if $\{v_i\}_{i=1}^{n}$ is an orthonormal system.

Hossein Moshafi, Hassan Firouzjahi, Alireza Talebian

We study the effects of multiple transitions in the vacuum dark energy density on the $H_0$ tension problem. We consider a phenomenological model in which the vacuum energy density undergoes multiple transitions in the early as well as the late universe and compare the model's predictions using the three sets of data from CMB+BAO+SN. The transient dark energ

Rachana Agrawal, Weston P. Buchanan, Archit Arora, Athul P. Girija

Venus is known for its extreme surface temperature and its sulfuric acid clouds. But the cloud layers on Venus have similar temperature and pressure conditions to those on the surface of Earth and are conjectured to be a possible habitat for microscopic life forms. We propose a mission concept to explore the clouds of Venus for up to 30 days to evaluate habi

Maedeh Taheri, Jonas Brown, Adil Rehman, Nicholas R. Sesing

We report on electrical gating of the charge-density-wave phases and current in h-BN capped three-terminal 1T-TaS$_2$ heterostructure devices. It is demonstrated that the application of a gate bias can shift the source-drain current-voltage hysteresis associated with the transition between the nearly commensurate and incommensurate charge-density wave phases

Yang Wang, Qiang Zhang, Xiao-hui Xiao

To simply and effectively realize the trajectory tracking control of a bionic joint actuated by a single pneumatic artificial muscle (PAM), a cascaded control strategy is proposed based on the robust modeling method. Firstly, the relationship between the input voltage of the proportional directional control valve and the inner driving pressure of PAM is expr

Y. Cheng, J. D. Treado, B. Lonial, P. Habdas

Numerous experimental and computational studies show that continuous hopper flows of granular materials obey the Beverloo equation that relates the volume flow rate $Q$ and the orifice width $w$: $Q \sim (w/\sigma_{\rm avg}-k)^{\beta}$, where $\sigma_{\rm avg}$ is the average particle diameter, $k\sigma_{\rm avg}$ is an offset where $Q\sim 0$, the power-law

Jiaxin Hu, Zhenyu Yu

In this paper we firstly derive the weak elliptic Harnack inequality from the generalized capacity condition, the tail estimate of jump measure and the Poincar\'{e} inequality, for any regular Dirichlet form without killing part on a measure metric space, by using the lemma of growth and the John-Nirenberg inequality. We secondly show several equivalent char

Weston P. Buchanan, Maxim de Jong, Rachana Agrawal, Janusz J. Petkowski

Mounting evidence of chemical disequilibria in the Venusian atmosphere has heightened interest in the search for life within the planet's cloud decks. Balloon systems are currently considered to be the superior class of aerial platform for extended atmospheric sampling within the clouds, providing the highest ratio of science return to risk. Balloon-based ae

Xin Fan, Yue Wang, Yan Huo, Zhi Tian

The valuable data collected by IoT devices in edge networks together with the resurgence of ML stimulate the latest trend of edge AI. However, recent FL methods face major challenges including communication bottleneck, data heterogeneity and security concerns in edge IoT scenarios, especially when being adopted for distributed learning among massive IoT devi

Brian Lester, Joshua Yurtsever, Siamak Shakeri, Noah Constant

Parameter-efficient methods are able to use a single frozen pre-trained large language model (LLM) to perform many tasks by learning task-specific soft prompts that modulate model behavior when concatenated to the input text. However, these learned prompts are tightly coupled to a given frozen model -- if the model is updated, corresponding new prompts need

Jordy Lopez Garcia, Kelly Maluccio, Frank Sottile, Thomas Yahl

The Macaulay2 package RealRoots provides symbolic methods to study real solutions to systems of polynomial equations. It updates and expands an earlier package developed by Grayson and Sottile in 1999. We provide mathematical background and descriptions of the RealRoots package, giving examples which illustrate some of its implemented methods. We also prove

Kenneth Dadedzi, Stephan Wagner

We prove that the multiplicity of a fixed eigenvalue $\alpha$ in a random recursive tree on $n$ vertices satisfies a central limit theorem with mean and variance asymptotically equal to $\mu_{\alpha} n$ and $\sigma^2_{\alpha} n$ respectively. It is also shown that $\mu_{\alpha}$ and $\sigma^2_{\alpha}$ are positive for every totally real algebraic integer. T

J. Hermosillo-Valadez, E. Morales-González, F. Fernández-Reyes, M. Montes-y-Gómez

The goal of rank fusion in information retrieval (IR) is to deliver a single output list from multiple search results. Improving performance by combining the outputs of various IR systems is a challenging task. A central point is the fact that many non-obvious factors are involved in the estimation of relevance, inducing nonlinear interrelations between the

Mia Mohammad Imran, Yashasvi Jain, Preetha Chatterjee, Kostadin Damevski

Emotions (e.g., Joy, Anger) are prevalent in daily software engineering (SE) activities, and are known to be significant indicators of work productivity (e.g., bug fixing efficiency). Recent studies have shown that directly applying general purpose emotion classification tools to SE corpora is not effective. Even within the SE domain, tool performance degrad

Congyi Zhang, Lei Yang, Nenglun Chen, Nicholas Vining

Creating 3D shapes from 2D drawings is an important problem with applications in content creation for computer animation and virtual reality. We introduce a new sketch-based system, CreatureShop, that enables amateurs to create high-quality textured 3D character models from 2D drawings with ease and efficiency. CreatureShop takes an input bitmap drawing of a

N. Janzen, X. Dai, S. Ren, J. Shi

Two-level systems (TLS) coupled to waveguides are a fundamental paradigm for light-matter interactions and quantum networks. We introduce and experimentally demonstrate a method to tune the interaction between a TLS, implemented as a flux qubit, and a transmission line waveguide from a decoupled state to a coupling strength that is a significant fraction of

Sara Seager, Janusz J. Petkowski, Christopher E. Carr, David H. Grinspoon

Finding evidence of extraterrestrial life would be one of the most profound scientific discoveries ever made, advancing humanity into a new epoch of cosmic awareness. The Venus Life Finder (VLF) missions feature a series of three direct atmospheric probes designed to assess the habitability of the Venusian clouds and search for signs of life and life itself.

Sridhar Majety, Stefan Strohauer, Pranta Saha, Fabian Wietschorke

Triangular cross-section SiC photonic devices have been studied as an efficient and scalable route for integration of color centers into quantum hardware. In this work, we explore efficient collection and detection of color center emission in a triangular cross-section SiC waveguide by introducing a photonic crystal mirror on its one side and a superconducti

Anil Yaman, Joel Z. Leibo, Giovanni Iacca, Sang Wan Lee

Human ecological success relies on our characteristic ability to flexibly self-organize into cooperative social groups, the most successful of which employ substantial specialization and division of labor. Unlike most other animals, humans learn by trial and error during their lives what role to take on. However, when some critical roles are more attractive

Catia Nicodemo, Sonia Oreffice, Climent Quintana-Domeque

Using administrative data on all induced abortions recorded in Spain in 2019, we analyze the characteristics of women undergoing repeat abortions and the spacing between these procedures. Our findings indicate that compared to women experiencing their first abortion, those who undergo repeat abortions are more likely to have lower education levels, have depe

Abeer Al Ghamdi, Benjamin Dawson, Gin Jose, Almut Beige

One way of optically monitoring molecule concentrations is to utilise the high sensitivity of the transmission and reflection rates of Fabry-Perot cavities to changes of their optical properties. Up to now, intrinsic and extrinsic Fabry-Perot cavity sensors have been considered with analytes either being placed inside the resonator or coupled to evanescent f

John Rick D. Manzanares, Paul Samuel P. Ignacio

Network centrality measures play a crucial role in understanding graph structures, assessing the importance of nodes, paths, or cycles based on directed or reciprocal interactions encoded by vertices and edges. Estrada and Ross extended these measures to simplicial complexes to account for higher-order connections. In this work, we introduce novel centrality

Amr Gomaa, Alexandra Alles, Elena Meiser, Lydia Helene Rupp

Several researchers have focused on studying driver cognitive behavior and mental load for in-vehicle interaction while driving. Adaptive interfaces that vary with mental and perceptual load levels could help in reducing accidents and enhancing the driver experience. In this paper, we analyze the effects of mental workload and perceptual load on psychophysio

Matan Menahem, Nimrod Benshalom, Maor Asher, Sigalit Aharon

The anharmonic lattice dynamics of oxide and halide perovskites play a crucial role in their mechanical and optical properties. Raman spectroscopy is one of the key methods used to study these structural dynamics. However, despite decades of research, existing interpretations cannot explain the temperature dependence of the observed Raman spectra. We demonst

Christiane Helling, Dominic Samra, David Lewis, Robb Calder

With observational efforts moving from the discovery into the characterisation mode, systematic campaigns that cover large ranges of global stellar and planetary parameters will be needed. We aim to uncover cloud formation trends and globally changing chemical regimes due to the host star's effect on the thermodynamic structure of their atmospheres. We aim t

Jiahao Deng, Eli T. Brown

Clustering analysis is one of the critical tasks in machine learning. Traditionally, clustering has been an independent task, separate from outlier detection. Due to the fact that the performance of clustering can be significantly eroded by outliers, a small number of algorithms try to incorporate outlier detection in the process of clustering. However, most

Maarten Golterman

We review Standard-Model evaluations of hadronic contributions to the muon anomalous magnetic moment $g-2$. Most space is devoted to the hadronic vacuum polarization contribution, in view of the discrepancy between the data-based dispersive evaluation and the lattice evaluation by the BMW collaboration.

Felix Stutz, Damien Zufferey

Communicating state machines provide a formal foundation for distributed computation. Unfortunately, they are Turing-complete and, thus, challenging to analyse. In this paper, we classify restrictions on channels which have been proposed to work around the undecidability of verification questions. We compare half-duplex communication, existential B-boundedne

Latif U. Khan, Ehzaz Mustafa, Junaid Shuja, Faisal Rehman

Emerging intelligent transportation applications, such as accident reporting, lane change assistance, collision avoidance, and infotainment, will be based on diverse requirements (e.g., latency, reliability, quality of physical experience). To fulfill such requirements, there is a significant need to deploy a digital twin-based intelligent transportation sys

Juliana J. Park, Yu-Kun Lu, Alan O. Jamison, Timur Tscherbul

Collisional resonances are an important tool which has been used to modify interactions in ultracold gases, for realizing novel Hamiltonians in quantum simulations, for creating molecules from atomic gases and for controlling chemical reactions. So far, such resonances have been observed for atom-atom collisions, atom-molecule collisions and collisions betwe