April 2023 arXiv papers — page 25

Badri Adhikari

The landscape of educational practices for teaching and learning languages has been predominantly centered around outcome-driven approaches. The recent accessibility of large language models has thoroughly disrupted these approaches. As we transform our language teaching and learning practices to account for this disruption, it is important to note that lang

Michael T. Jury, Georgios Tsikalas

Let $F=(\phi, \psi):\mathbb{D}^2\to\mathbb{D}^2$ denote a holomorphic self-map of the bidisk without interior fixed points. It is well-known that, unlike the case with self-maps of the disk, the sequence of iterates $$\{F^n:=F\circ F\circ \cdots \circ F\}$$ needn't converge. The cluster set of $\{F^n\}$ was described in a classical 1954 paper of Herv\'{e}. M

Harshvardhan Jog, Luminita Harnagea, Dibyata Rout, Takashi Taniguchi

The strongly correlated charge density wave (CDW) phase of 1T-TiSe$_2$ is being extensively researched to verify the claims of a unique chiral order due to the presence of three equivalent Fermi wavevectors involved in the CDW formation. Characterization of the symmetries is therefore critical to understand the origin of their intriguing properties but can b

Yonatan Dukler, Benjamin Bowman, Alessandro Achille, Aditya Golatkar

We present Synergy Aware Forgetting Ensemble (SAFE), a method to adapt large models on a diverse collection of data while minimizing the expected cost to remove the influence of training samples from the trained model. This process, also known as selective forgetting or unlearning, is often conducted by partitioning a dataset into shards, training fully inde

Myeongjong Kang

We propose a novel nonparametric regression framework subject to the positive definiteness constraint. It offers a highly modular approach for estimating covariance functions of stationary processes. Our method can impose positive definiteness, as well as isotropy and monotonicity, on the estimators, and its hyperparameters can be decided using cross validat

Lluís Ros

This note briefly introduces the computed torque control method for trajectory tracking. The method is applicable to fully actuated robots, i.e, those whose inverse dynamics can be solved for any feasible acceleration. This includes many systems, like robot arms or hands, or any tree-like mechanism with all its joints actuated. Using simple explanations, we

Sheng Liu, Cong Phuoc Huynh, Cong Chen, Maxim Arap

We present a simple yet effective self-supervised pre-training method for image harmonization which can leverage large-scale unannotated image datasets. To achieve this goal, we first generate pre-training data online with our Label-Efficient Masked Region Transform (LEMaRT) pipeline. Given an image, LEMaRT generates a foreground mask and then applies a set

Tanya Khovanova, Gregory Marton

What follows is the story of a family of integer sequences, which started life as a Google interview puzzle back in the previous century when VHS video tapes were in use.

Timothy Collier, Daniel Hauer

The aim of this paper is to provide sufficient conditions implying that the effective domain $D(A\phi)$ of an $m$-accretive operator $A\phi$ in $L^1$ is dense in $L^1$. Here, $A\phi$ refers to the composition $A\circ \phi$ in $L^1$ of the part $A=(\partial\mathcal{E})_{\vert L^{1\cap \infty}}$ in $L^{1\cap\infty}\times L^{1\cap\infty}$ of the subgradient $\p

Massimo Caccia, Alexandre Galashov, Arthur Douillard, Amal Rannen-Triki

The field of transfer learning is undergoing a significant shift with the introduction of large pretrained models which have demonstrated strong adaptability to a variety of downstream tasks. However, the high computational and memory requirements to finetune or use these models can be a hindrance to their widespread use. In this study, we present a solution

Yuri Kozitsky, Krzysztof Pilorz

There exists a wide variety of works on the dynamics of large populations ranging from simple heuristic modeling to those based on advanced computer supported methods. Their interconnections, however, remain mostly vague, which significantly limits the effectiveness of using computer methods in this domain. The aim of the present publication is to propose a

Joshua P. Ebenezer, Zaixi Shang, Yixu Chen, Yongjun Wu

We conducted a large-scale study of human perceptual quality judgments of High Dynamic Range (HDR) and Standard Dynamic Range (SDR) videos subjected to scaling and compression levels and viewed on three different display devices. HDR videos are able to present wider color gamuts, better contrasts, and brighter whites and darker blacks than SDR videos. While

Bilin Aksun-Guvenc, Levent Guvenc

Unexpected yaw disturbances like braking on unilaterally icy road, side wind forces and tire rupture are very difficult to handle by the driver of a road vehicle, due to his/her large panic reaction period ranging between 0.5 to 2 seconds. Automatic driver assist systems provide counteracting yaw moments during this driver panic reaction period to maintain t

Dong-Woo Kim, Amanda Malnati, Alyssa Cassity, Giuseppina Fabbiano

X-ray bright optically normal galaxies (XBONGs) are galaxies with X-ray luminosities consistent with those of active galactic nuclei (AGNs) but no evidence of AGN optical emission lines. Crossmatching the Chandra Source Catalog version 2 (CSC2) with the Sloan Digital Sky Survey (SDSS) sample of spectroscopically classified galaxies, we have identified 817 XB

Dong-Woo Kim, Alyssa Cassity, Binod Bhatt, Giuseppina Fabbiano

We present an extensive and well-characterized Chandra X-ray Galaxy Catalog (CGC) of 8557 galaxy candidates in the redshift range z ~ 0.04 - 0.7, optical luminosity 1010 - 1011 Lro, and X-ray luminosity (0.5-7 keV) LX = 2x1040 - 2x1043 erg s-1. We estimate ~5% false match fraction and contamination by QSOs. The CGC was extracted from the Chandra Source Catal

Ali Owfi, Fatemeh Afghah

Passive space-borne radiometers operating in the 1400-1427 MHz protected frequency band face radio frequency interference (RFI) from terrestrial sources. With the growth of wireless devices and the appearance of new technologies, the possibility of sharing this spectrum with other technologies would introduce more RFI to these radiometers. This band could be

Iain Mackie, Shubham Chatterjee, Jeffrey Dalton

Current query expansion models use pseudo-relevance feedback to improve first-pass retrieval effectiveness; however, this fails when the initial results are not relevant. Instead of building a language model from retrieved results, we propose Generative Relevance Feedback (GRF) that builds probabilistic feedback models from long-form text generated from Larg

Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu, Hai Wei

We present a no-reference video quality model and algorithm that delivers standout performance for High Dynamic Range (HDR) videos, which we call HDR-ChipQA. HDR videos represent wider ranges of luminances, details, and colors than Standard Dynamic Range (SDR) videos. The growing adoption of HDR in massively scaled video networks has driven the need for vide

I. Novitski, A. V. Zlobin, E. Barzi, D. Turrioni

The stress-management cos-theta (SMCT) coil is a new concept which has been proposed and is being developed at Fermilab in the framework of US Magnet Development Program (US-MDP) for high-field and/or large-aperture accelerator magnets based on low-temperature and high-temperature superconductors. The SMCT structure is used to reduce large coil deformations

Abin Varghese, Adityanarayan Pandey, Pooja Sharma, Yuefeng Yin

Strain can efficiently modulate the bandgap and carrier mobilities in two-dimensional (2D) materials. Conventional mechanical strain-application methodologies that rely on flexible, patterned or nano-indented substrates are severely limited by low thermal tolerance, lack of tunability and/or poor scalability. Here, we leverage the converse piezoelectric effe

Boyang Deng, Yifan Wang, Gordon Wetzstein

Unsupervised learning of 3D human faces from unstructured 2D image data is an active research area. While recent works have achieved an impressive level of photorealism, they commonly lack control of lighting, which prevents the generated assets from being deployed in novel environments. To this end, we introduce LumiGAN, an unconditional Generative Adversar

Xiaoxiang Chai, Gaoming Wang

Let $(M, g)$ be a compact 3-manifold with nonnegative scalar curvature $R_g\geq 0$. The boundary $\partial M$ is diffeomorphic to the boundary of a rotationally symmetric and weakly convex body $\bar{M}$ in $\mathbb{R}^3$. We call $(\bar{M}, \delta)$ a model or a reference. Let $H_{\partial M}$ and $\bar{H}_{\partial M}$ be respectively the mean curvatures o

Georgy Yu. Prokhorov, Oleg V. Teryaev, Valentin I. Zakharov

We consider gas of massless fermions at certain temperature T and acceleration a. We find a second order phase transition at temperature T approaching the Unruh temperature TU. The implications for hadronization of the quark-gluon plasma produced in heavy-ion collisions (HIC) and for black-hole physics are discussed. In particular, this novel phase transitio

Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala, Wolfgang Merkt

This paper proposes a simple strategy for sim-to-real in Deep-Reinforcement Learning (DRL) -- called Roll-Drop -- that uses dropout during simulation to account for observation noise during deployment without explicitly modelling its distribution for each state. DRL is a promising approach to control robots for highly dynamic and feedback-based manoeuvres, a

Christophe Van Gysel

Virtual assistants are becoming increasingly important speech-driven Information Retrieval platforms that assist users with various tasks. We discuss open problems and challenges with respect to modeling spoken information queries for virtual assistants, and list opportunities where Information Retrieval methods and research can be applied to improve the qua

Martin Wessel, Tomáš Horych, Terry Ruas, Akiko Aizawa

Although media bias detection is a complex multi-task problem, there is, to date, no unified benchmark grouping these evaluation tasks. We introduce the Media Bias Identification Benchmark (MBIB), a comprehensive benchmark that groups different types of media bias (e.g., linguistic, cognitive, political) under a common framework to test how prospective detec

Christopher Lang, Alexander Braun, Lars Schillingmann, Abhinav Valada

Self-supervised multi-object trackers have tremendous potential as they enable learning from raw domain-specific data. However, their re-identification accuracy still falls short compared to their supervised counterparts. We hypothesize that this drawback results from formulating self-supervised objectives that are limited to single frames or frame pairs. Su

Yudai Matsumura, Yu Tokizane, Eiji Hase, Naoya Kuse

THz waves are promising wireless carriers for next-generation wireless communications, where a seamless connection from wireless to optical communication is required. In this study, we demonstrate carrier conversion from THz waves to dual-wavelength NIR light injection-locking to an optical frequency comb using asynchronous nonpolarimetric electro-optic down

Zahra Tayebi, Sarwan Ali, Prakash Chourasia, Taslim Murad

Cancer is a complex disease characterized by uncontrolled cell growth and proliferation. T cell receptors (TCRs) are essential proteins for the adaptive immune system, and their specific recognition of antigens plays a crucial role in the immune response against diseases, including cancer. The diversity and specificity of TCRs make them ideal for targeting c

Evgeny Podryabinkin, Kamil Garifullin, Alexander Shapeev, Ivan Novikov

Nowadays, academic research relies not only on sharing with the academic community the scientific results obtained by research groups while studying certain phenomena, but also on sharing computer codes developed within the community. In the field of atomistic modeling these were software packages for classical atomistic modeling, later -- quantum-mechanical

Yi Cao, Swetava Ganguli, Vipul Pandey

There exists a correlation between geospatial activity temporal patterns and type of land use. A novel self-supervised approach is proposed to stratify landscape based on mobility activity time series. First, the time series signal is transformed to the frequency domain and then compressed into task-agnostic temporal embeddings by a contractive autoencoder,

Samuel Sokota, Gabriele Farina, David J. Wu, Hengyuan Hu

The process of revising (or constructing) a policy at execution time -- known as decision-time planning -- has been key to achieving superhuman performance in perfect-information games like chess and Go. A recent line of work has extended decision-time planning to imperfect-information games, leading to superhuman performance in poker. However, these methods

Amine Bouali, Himanshu Chaudhary, Ujjal Debnath, Alok Sardar

Constraining the dark energy deceleration parameter is one of the fascinating topics in the recent cosmological paradigm. This work aims to reconstruct the dark energy using parametrization of the deceleration parameter in a flat FRW universe filled with radiation, dark energy, and pressure-less dark matter. Thus, we have considered four well-motivated param

Samuel Goldman, Janet Li, Connor W. Coley

The accurate prediction of tandem mass spectra from molecular structures has the potential to unlock new metabolomic discoveries by augmenting the community's libraries of experimental reference standards. Cheminformatic spectrum prediction strategies use a "bond-breaking" framework to iteratively simulate mass spectrum fragmentations, but these methods are

Lin Yang, Shuihua Wang, Yudong Zhang

Coronavirus disease 2019 (COVID-19) has spread all over the world for three years, but medical facilities in many areas still aren't adequate. There is a need for rapid COVID-19 diagnosis to identify high-risk patients and maximize the use of limited medical resources. Motivated by this fact, we proposed the deep learning framework MEDNC for automatic predic

Ke Wu, Ehsan Variani, Tom Bagby, Michael Riley

We introduce LAST, a LAttice-based Speech Transducer library in JAX. With an emphasis on flexibility, ease-of-use, and scalability, LAST implements differentiable weighted finite state automaton (WFSA) algorithms needed for training \& inference that scale to a large WFSA such as a recognition lattice over the entire utterance. Despite these WFSA algorithms

Konstantin Tikhomirov

The classical theorem of Wendel provides an exact formula for the probability that the convex hull of independent symmetrically distributed vectors in ${\mathbb R}^d$ contains the origin as long as the distributions of the vectors are continuous. In this note, we provide an extension to Wendel's theorem for independent random vectors $X_1,\dots,X_n$ with i.i

Elisa Davoli, Giovanni Di Fratta, Alberto Fiorenza, Leon Happ

In the context of Sobolev spaces with variable exponents, Poincar\'e--Wirtinger inequalities are possible as soon as Luxemburg norms are considered. On the other hand, modular versions of the inequalities in the expected form \begin{equation*} \int_\Omega \left|f(x)-\langle f\rangle_{\Omega}\right|^{p(x)} \ {\mathrm{d} x} \leqslant C \int_\Omega|\nabla f(x)|

Ming Min, Ruimeng Hu, Tomoyuki Ichiba

Real-world data can be multimodal distributed, e.g., data describing the opinion divergence in a community, the interspike interval distribution of neurons, and the oscillators natural frequencies. Generating multimodal distributed real-world data has become a challenge to existing generative adversarial networks (GANs). For example, neural stochastic differ

Giacomo Nebbia, Adriana Kovashka

Named entities are ubiquitous in text that naturally accompanies images, especially in domains such as news or Wikipedia articles. In previous work, named entities have been identified as a likely reason for low performance of image-text retrieval models pretrained on Wikipedia and evaluated on named entities-free benchmark datasets. Because they are rarely

Amifa Raj, Bhaskar Mitra, Nick Craswell, Michael D. Ekstrand

Users of search systems often reformulate their queries by adding query terms to reflect their evolving information need or to more precisely express their information need when the system fails to surface relevant content. Analyzing these query reformulations can inform us about both system and user behavior. In this work, we study a special category of que

Andrew Na, Meixin Zhang, Justin Wan

In this paper, we propose a generative adversarial network (GAN) approach for efficiently computing volatility surfaces. The idea is to make use of the special GAN neural architecture so that on one hand, we can learn volatility surfaces from training data and on the other hand, enforce no-arbitrage conditions. In particular, the generator network is assiste

Renteng Yuan, Mohamed Abdel-Aty, Xin Gu, Ou Zheng

Accurately detecting and predicting lane change (LC)processes of human-driven vehicles can help autonomous vehicles better understand their surrounding environment, recognize potential safety hazards, and improve traffic safety. This paper focuses on LC processes, first developing a temporal convolutional network with an attention mechanism (TCN-ATM) model t

Luis O. Silva, Julio H. Toloza

A de Branges space $\mathcal B$ is regular if the constants belong to its space of associated functions and is symmetric if it is isometrically invariant under the map $F(z) \mapsto F(-z)$. Let $K_\mathcal{B}(z,w)$ be the reproducing kernel in $\mathcal B$ and $S_{\mathcal{B}}$ be the operator of multiplication by the independent variable with maximal domain

Miriam Marqués, Miriam Pena Alvarez, Miguel Martinez-Canales, Graeme J Ackland

Through density functional theory and molecular dynamics calculations, we have analysed various metal polyhydrides to understand whether hydrogen is present in its molecular or atomic form - tetrahydrides of Ba,Sr,Ra, Cs and La; Ba$_8$H$_{46}$ and BaH$_{12}$. We show that, in experimentally reported binary barium hydrides (BaH$_x$), molecular H$_2$ and atomi

Ali Behcet Alpat, Abdullah Coban, Hakan Kaya, Giovanni Bartolini

Radiation effects analysis of instruments operative in harsh radiation environment is crucial for performance and functionality of electronic devices and components. Engineering design of instruments is usually carried out in Computer Aided Design (CAD) engineering software. Geant4-based Monte Carlo codes are extensively used for particle transport simulatio

Bohnishikha Ghosh, Anat Daniel, Bernard Gorzkowski, Radek Lapkiewicz

M.V. Berry's work [J. Phys. A: Math. Theor. 43, 415302 (2010)] highlighted the correspondence between backflow in quantum mechanics and superoscillations in waves. Superoscillations refer to situations where the local oscillation of a superposition is faster than its fastest Fourier component. This concept has been used to demonstrate backflow in transverse

Ruth H. Tichauer, Ilia Sokolovskii, Gerrit Groenhof

Transport of excitons in organic materials can be enhanced through polariton formation when the interaction strength between these excitons and the confined light modes of an optical resonator exceeds their decay rates. While the polariton lifetime is determined by the Q(uality)-factor of the optical resonator, the polariton group velocity is not. Instead, t

Jan Govaerts

Even though its classical equations of motion are then left invariant, when an action is redefined by an additive total derivative or divergence term (in time, in the case of a mechanical system) such a transformation induces nontrivial consequences for the system's canonical phase space formulation. This is even more true and then in more subtle ways for th

Chenpeng Du, Yiwei Guo, Feiyu Shen, Kai Yu

In this paper, we describe the systems developed by the SJTU X-LANCE team for LIMMITS 2023 Challenge, and we mainly focus on the winning system on naturalness for track 1. The aim of this challenge is to build a multi-speaker multi-lingual text-to-speech (TTS) system for Marathi, Hindi and Telugu. Each of the languages has a male and a female speaker in the

Silviu-Marian Udrescu, Diego Alejandro Torres, Ronald Fernando Garcia Ruiz

We propose an experimental scheme for performing sensitive, high-precision laser spectroscopy studies on fast exotic isotopes. By inducing a step-wise resonant ionization of the atoms travelling inside an electric field and subsequently detecting the ion and the corresponding electron, time- and position-sensitive measurements of the resulting particles can

Behnam Behinaein Hamgini, Hossein Najafi, Ali Bakhshali, Zhuhong Zhang

In this paper, we introduce a new nonlinear optical channel equalizer based on Transformers. By leveraging parallel computation and attending directly to the memory across a sequence of symbols, we show that Transformers can be used effectively for nonlinear compensation (NLC) in coherent long-haul transmission systems. For this application, we present an im

Sachin Vaidya, Mikael C. Rechtsman, Wladimir A. Benalcazar

Chern insulators present a topological obstruction to a smooth gauge in their Bloch wave functions that prevents the construction of exponentially-localized Wannier functions - this makes the electric polarization ill-defined. Here, we show that spatial or temporal differences in polarization within Chern insulators are well-defined and physically meaningful

André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye

The domain of an optimization problem is seen as one of its most important characteristics. In particular, the distinction between continuous and discrete optimization is rather impactful. Based on this, the optimizing algorithm, analyzing method, and more are specified. However, in practice, no problem is ever truly continuous. Whether this is caused by com

B. Sana, M. Barik, S. Lee, U. Jena

Collective behavior of spins, frustration-induced strong quantum fluctuations, and subtle interplay between competing degrees of freedom in quantum materials can lead to correlated quantum states with exotic excitations that are essential ingredients for establishing paradigmatic models and have immense potential for quantum technologies. Disorder is ubiquit

Aggelina Chatziagapi, Dimitris Samaras

In this work, we present a multimodal solution to the problem of 4D face reconstruction from monocular videos. 3D face reconstruction from 2D images is an under-constrained problem due to the ambiguity of depth. State-of-the-art methods try to solve this problem by leveraging visual information from a single image or video, whereas 3D mesh animation approach

Harel Biggie, Andrew Beathard, Christoffer Heckman

Typical algorithms for point cloud registration such as Iterative Closest Point (ICP) require a favorable initial transform estimate between two point clouds in order to perform a successful registration. State-of-the-art methods for choosing this starting condition rely on stochastic sampling or global optimization techniques such as branch and bound. In th

Alejandro Ríos-Herrejón

In this paper we obtain new results regarding the chain conditions in the Pixley-Roy hyperspaces $\mathscr{F}[X]$. For example, if $c(X)$ and $R(X)$ denote the cellularity and weak separation number of $X$ (see Section~[4]) and we define the cardinals $$c^* (X) := \sup \{c(X^{n}) : n\in \mathbb{N}\} \quad \text{and} \quad R^{*}(X) := \sup \{R(X^{n}) : n\in \

Richard P. Stanley

Let $P$ be a finite poset of width two, i.e., with no three-element antichain. We associate with $P$ a skew Young diagram $\Upsilon(P)$ and discuss some of the properties of the map $\Upsilon$. In particular, if we regard $\Upsilon(P)$ as a poset in a standard way, then the linear extensions of $P$ are in bijection with the order ideals of $\Upsilon(P)$.

Jon Aycock, Andrew Kobin

In various contexts, the zeta function of an object splits into a product of $L$-functions. We categorify this product formula for quadratic covers of objects in the following contexts: quadratic extensions of number fields, ramified double covers of algebraic curves, ramified double covers of topological spaces and Galois double covers of graphs. Our unifie

Michael Bechtel, Heechul Yun

In this paper, we present a solution to the industrial challenge put forth by ARM in 2022. We systematically analyze the effect of shared resource contention to an augmented reality head-up display (AR-HUD) case-study application of the industrial challenge on a heterogeneous multicore platform, NVIDIA Jetson Nano. We configure the AR-HUD application such th

Po-Chun Hsu, Li-Hsiang Shen, Chun-Hung Liu, Kai-Ten Feng

Terahertz (THz) communication with ultra-wide available spectrum is a promising technique that can achieve the stringent requirement of high data rate in the next-generation wireless networks, yet its severe propagation attenuation significantly hinders its implementation in practice. Finding beam directions for a large-scale antenna array to effectively ove

Ruxi Liang, Furen Deng, Zepei Yang, Chunming Li

In neutral hydrogen (HI) galaxy survey, a significant challenge is to identify and extract the HI galaxy signal from observational data contaminated by radio frequency interference (RFI). For a drift-scan survey, or more generally a survey of a spatially continuous region, in the time-ordered spectral data, the HI galaxies and RFI all appear as regions which

Li-Hsiang Shen, An-Hung Hsiao, Fang-Yu Chu, Kai-Ten Feng

Device-free human presence detection is a crucial technology for various applications, including home automation, security, and healthcare. While camera-based systems have traditionally been used for this purpose, they raise privacy concerns. To address this issue, recent research has explored the use of wireless channel state information (CSI) extracted fro

Nicholas D. Alikakos, Zhiyuan Geng

We investigate the Allen-Cahn system \begin{equation*} \Delta u-W_u(u)=0,\quad u:\mathbb{R}^2\rightarrow\mathbb{R}^2, \end{equation*} where $W\in C^2(\mathbb{R}^2,[0,+\infty))$ is a potential with three global minima. We establish the existence of an entire solution $u$ which possesses a triple junction structure. The main strategy is to study the global min

Li-Hsiang Shen, An-Hung Hsiao, Kuan-I Lu, Kai-Ten Feng

Accurate detection of human presence in indoor environments is important for various applications, such as energy management and security. In this paper, we propose a novel system for human presence detection using the channel state information (CSI) of WiFi signals. Our system named attention-enhanced deep learning for presence detection (ALPD) employs an a

Amirhossein Nazeri, Pierluigi Pisu

In this paper, we investigate the robustness of an LSTM neural network against noise injection attacks for electric load forecasting in an ideal microgrid. The performance of the LSTM model is investigated under a black-box Gaussian noise attack with different SNRs. It is assumed that attackers have just access to the input data of the LSTM model. The result

Mohammad Khodadadi, Jafar Tahmoresnezhad

With blockchain technology rapidly progress, the smart contracts have become a common tool in a number of industries including finance, healthcare, insurance and gaming. The number of smart contracts has multiplied, and at the same time, the security of smart contracts has drawn considerable attention due to the monetary losses brought on by smart contract v

Tiefeng Jiang, Tuan Pham

Given a random sample from a multivariate normal distribution whose covariance matrix is a Toeplitz matrix, we study the largest off-diagonal entry of the sample correlation matrix. Assuming the multivariate normal distribution has the covariance structure of an auto-regressive sequence, we establish a phase transition in the limiting distribution of the lar

Tyler Poppenwimer, Itay Mayrose, Niv DeMalach

There are two main life cycles in plants, annual and perennial. These life cycles are associated with different traits that determine ecosystem function. Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding their global distributional patterns. Here, we assembled an extensive data

Dmytro Sytnyk, Barbara Wohlmuth

We present an exponentially convergent numerical method to approximate the solution of the Cauchy problem for the inhomogeneous fractional differential equation with an unbounded operator coefficient and Caputo fractional derivative in time. The numerical method is based on the newly obtained solution formula that consolidates the mild solution representatio

Nestor Mirabal

Gamma-ray bursts (GRBs) have long been suspected as possible ultra-high energy cosmic ray (UHECR) accelerators. In this brief note, I report that GRB 980425/SN 1998bw falls within the region of interest (ROI) with the highest significance in an all-sky blind search for magnetically-induced effects in the arrival directions of UHECRs conducted by the Pierre A

Yuhang Li, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda

Spiking Neural Networks (SNNs) are recognized as the candidate for the next-generation neural networks due to their bio-plausibility and energy efficiency. Recently, researchers have demonstrated that SNNs are able to achieve nearly state-of-the-art performance in image recognition tasks using surrogate gradient training. However, some essential questions ex

Ewout Gelling, George Fletcher, Michael Schmidt

Graph database users today face a choice between two technology stacks: the Resource Description Framework (RDF), on one side, is a data model with built-in semantics that was originally developed by the W3C to exchange interconnected data on the Web; on the other side, Labeled Property Graphs (LPGs) are geared towards efficient graph processing and have str

Ruochu Yang, Mengxue Hou, Chad Lembke, Catherine Edwards

Underwater gliders are widely utilized for ocean sampling, surveillance, and other various oceanic applications. In the context of complex ocean environments, gliders may yield poor navigation performance due to strong ocean currents, thus requiring substantial human effort during the manual piloting process. To enhance navigation accuracy, we developed a re

A. V. Glushkov, A. V. Sabourov, L. T. Ksenofontov, K. G. Lebedev

The lateral distribution of particles in extensive air showers from cosmic rays with energy above $10^{17}$ eV registered at the Yakutsk complex array was analyzed. Experimentally measured particle densities were compared to the predictions obtained within frameworks of three ultra-high energy hadron interaction models. The cosmic ray mass composition estima

Thijs van der Horst, Tim Ophelders, Bart van der Steenhoven

We consider the problem of deciding, given a sequence of regions, if there is a choice of points, one for each region, such that the induced polyline is simple or weakly simple, meaning that it can touch but not cross itself. Specifically, we consider the case where each region is a translate of the same shape. We show that the problem is NP-hard when the sh

Logan Bishop-Van Horn, Eli Mueller, Kathryn A. Moler

We measured the local magnetic response of a niobium thin film by applying a millitesla-scale AC magnetic field using a micron-scale field coil and detecting the response with a micron-scale pickup loop in a scanning superconducting quantum interference device (SQUID) susceptometry measurement. Near the film's critical temperature, we observed a step-like no

Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu, Hai Wei

We introduce a novel feature set, which we call HDRMAX features, that when included into Video Quality Assessment (VQA) algorithms designed for Standard Dynamic Range (SDR) videos, sensitizes them to distortions of High Dynamic Range (HDR) videos that are inadequately accounted for by these algorithms. While these features are not specific to HDR, and also a

Rui Ding

In this paper, we show that the halfspace depth random variable for samples from a univariate distribution with a notion of center is distributed as a uniform distribution on the interval [0,1/2]. The simplicial depth random variable has a distribution that first-order stochastic dominates that of the halfspace depth random variable and relates to a Beta dis

Symon Serbenyuk

In this article, for modelling numeral systems, the operator approach, which is introduced in [25], is generalized for a certain case. An example of such numeral systems is introduced and considered.

Momina Sajid, Yanning Shen, Yasser Shoukry

We introduce the problem of model-extraction attacks in cyber-physical systems in which an attacker attempts to estimate (or extract) the feedback controller of the system. Extracting (or estimating) the controller provides an unmatched edge to attackers since it allows them to predict the future control actions of the system and plan their attack accordingl

Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari Morcos

Joint-embedding based learning (e.g., SimCLR, MoCo, DINO) and reconstruction-based learning (e.g., BEiT, SimMIM, MAE) are the two leading paradigms for self-supervised learning of vision transformers, but they differ substantially in their transfer performance. Here, we aim to explain these differences by analyzing the impact of these objectives on the struc

Fabricio Alcalde Bessia, Troy England, Hongzhi Sun, Leandro Stefanazzi

The \emph{MIDNA} application specific integrated circuit (ASIC) is a skipper-CCD readout chip fabricated in a 65 nm LP-CMOS process that is capable of working at cryogenic temperatures. The chip integrates four front-end channels that process the skipper-CCD signal and performs differential averaging using a dual slope integration (DSI) circuit. Each readout

H. V. Ovcharenko, O. B. Zaslavskii

If two particles move towards a black hole and collide in the vicinity of the horizon, under certain conditions their energy $E_{c.m.}$ in the center of mass frame can grow unbounded. This is the Ba\~{n}ados-Silk-West (BSW) effect. Usually, this effect is considered for extremal horizons and geodesic (or electrogedesic) trajectories. We study this effect in

Bikash Patra, Rahul Verma, Shin-Ming Huang, Bahadur Singh

Understanding the role of lattice geometry in shaping topological states and their properties is of fundamental importance to condensed matter and device physics. Here we demonstrate how an anisotropic crystal lattice drives a topological hybrid nodal line in transition metal tetraphosphides $Tm$P$_4$ ($Tm$ = Transition metal). $Tm$P$_4$ constitutes a unique

Chengzhe Sun, Shan Jia, Shuwei Hou, Siwei Lyu

Advancements in AI-synthesized human voices have created a growing threat of impersonation and disinformation, making it crucial to develop methods to detect synthetic human voices. This study proposes a new approach to identifying synthetic human voices by detecting artifacts of vocoders in audio signals. Most DeepFake audio synthesis models use a neural vo

Ionut Sebastian Mihai, Sarang Chafle, Johan Henriksson

Single-cell analysis is currently one of the most high-resolution techniques to study biology. The large complex datasets that have been generated have spurred numerous developments in computational biology, in particular the use of advanced statistics and machine learning. This review attempts to explain the deeper theoretical concepts that underpin current

Yosef Caplan, Dror Orgad

We carry out a sign-problem-free quantum Monte Carlo calculation of a bilayer model with a repulsive intra-layer Hubbard interaction and a ferromagnetic inter-layer interaction. The latter breaks the global $SU(2)$ spin rotational symmetry but preserves a $U(2)\times U(2)$ invariance under mixing of same-spin electrons between layers. We show that despite th

E. A. Jagla

We analyze a mesoscopic model of a shear stress material with a three dimensional slab geometry, under an external quasistatic deformation of a simple shear type. Relaxation is introduced in the model as a mechanism by which an unperturbed system achieves progressively mechanically more stable configurations. Although in all cases deformation occurs via loca

Jee Young Kim, William Boag, Freya Gulamali, Alifia Hasan

Private and public sector structures and norms refine how emerging technology is used in practice. In healthcare, despite a proliferation of AI adoption, the organizational governance surrounding its use and integration is often poorly understood. What the Health AI Partnership (HAIP) aims to do in this research is to better define the requirements for adequ

Ignacio Reyes-Jainaga, Francisco Förster, Alejandra M. Muñoz Arancibia, Guillermo Cabrera-Vives

In recent years, automatic classifiers of image cutouts (also called "stamps") have shown to be key for fast supernova discovery. The Vera C. Rubin Observatory will distribute about ten million alerts with their respective stamps each night, enabling the discovery of approximately one million supernovae each year. A growing source of confusion for these clas

João Chakrian, Marcelo L. Lyra, Jonas R. F. Lima

In this work we investigate the transport properties of non-relativistic quantum particles on incommensurate multilayered structures with the thicknesses $w_n$ of the layers following an extended Harper model given by $w_n = w_0 |\cos(\pi a n^{\nu})|$. For the normal incidence case, which means an one-dimensional system, we obtained that for a specific range

Roberta De Vito, Alejandra Avalos-Pacheco

Diet is a risk factor for many diseases. In nutritional epidemiology, studying reproducible dietary patterns is critical to reveal important associations with health. However, it is challenging: diverse cultural and ethnic backgrounds may critically impact eating patterns, showing heterogeneity, leading to incorrect dietary patterns and obscuring the compone

Kangming Li, Daniel Persaud, Kamal Choudhary, Brian DeCost

Extensive efforts to gather materials data have largely overlooked potential data redundancy. In this study, we present evidence of a significant degree of redundancy across multiple large datasets for various material properties, by revealing that up to 95 % of data can be safely removed from machine learning training with little impact on in-distribution p

André LeClair

In a recent article we showed that the analog of the cosmological constant in two spacetime dimensions for a wide variety of integrable quantum field theories has the form $\rho_{\rm vac} = - m^2 /2 \mathfrak{g} $ where $m$ is a physical mass and $\mathfrak{g} $ is a generalized coupling, where in the free field limit $\mathfrak{g} \to 0$, $\rho_{\rm vac}$ d

Charles Parker, Endre Süli

We construct a right inverse of the trace operator $u \mapsto (u|_{\partial T}, \partial_n u|_{\partial T})$ on the reference triangle $T$ that maps suitable piecewise polynomial data on $\partial T$ into polynomials of the same degree and is bounded in all $W^{s, q}(T)$ norms with $1 < q <\infty$ and $s \geq 2$. The analysis relies on new stability estimate

Steven Gassner, Eugene J. Mele

Nonlinear optical responses are becoming increasingly relevant for characterizing the symmetries and quantum geometry of electronic phases in materials. Here, we develop an expanded diagrammatic scheme for calculating spatially dispersive corrections to nonlinear optical conductivities, which we expect to enhance or even dominate even-order responses in mate

Avinash Kumar Paladi, Churchil Dwivedi, Prerna Rana, Nobleson K

The wideband timing technique enables the high-precision simultaneous estimation of pulsar Times of Arrival (ToAs) and Dispersion Measures (DMs) while effectively modeling frequency-dependent profile evolution. We present two novel independent methods that extend the standard wideband technique to handle simultaneous multi-band pulsar data incorporating prof

S. F. Sánchez, J. K. Barrera-Ballesteros, L. Galbany, R. García-Benito

We present the analysis performed using the pyPipe3D pipeline for the 895 galaxies that comprises the eCALIFA data release Sanchez et al. submitted, data with a significantly improved spatial resolution (1.0-1.5"/FWHM). We include a description of (i) the analysis performed by the pipeline, (ii) the adopted datamodel for the derived spatially resolved proper