April 2024 arXiv papers — page 68

Mouhamed Amine Bouchiha, Quentin Telnoff, Souhail Bakkali, Ronan Champagnat

Large Language Models (LLMs) have witnessed rapid growth in emerging challenges and capabilities of language understanding, generation, and reasoning. Despite their remarkable performance in natural language processing-based applications, LLMs are susceptible to undesirable and erratic behaviors, including hallucinations, unreliable reasoning, and the genera

Ling Yue, Jonathan Li, Sixue Xing, Md Zabirul Islam

The clinical trial process, a critical phase in drug development, is essential for developing new treatments. The primary goal of interventional clinical trials is to evaluate the safety and efficacy of drug-based treatments for specific diseases. However, these trials are often lengthy, labor-intensive, and expensive. The duration of a clinical trial signif

Danko Radić, Leonid Y. Gorelik, Sergei I. Kulinich, Robert I. Shekhter

We suggest a nanoelectromechanical setup that generates properly entangled ancillary ("ancilla") qubits for error correction algorithms in quantum computing, demonstrated as an encoder for the three-qubit bit flip code. The setup is based on mesoscopic terminal utilizing the AC Josephson effect between voltage biased superconducting electrodes and mechanical

Seungwoo Kang, Hee-Seok Oh

A new measure to assess the centrality of vertices in an undirected and connected graph is proposed. The proposed measure, L1 centrality, can adequately handle graphs with weights assigned to vertices and edges. The study provides tools for graphical and multiscale analysis based on the L1 centrality. Specifically, the suggested analysis tools include the ta

Sota Asai, Osamu Iyama

For an abelian length category $\mathcal{A}$ with only finitely many isoclasses of simple objects, we have the wall-chamber structure and the TF equivalence on the dual real Grothendieck group $K_0(\mathcal{A})_\mathbb{R}^*=\operatorname{Hom}_\mathbb{R}(K_0(\mathcal{A})_\mathbb{R},\mathbb{R})$, which are defined by semistable subcategories and semistable tor

Stephen H. Yuwono, Run R. Li, Tianyuan Zhang, Kshitijkumar A. Surjuse

We have implemented noniterative triples corrections to the energy from coupled-cluster with single and double excitations (CCSD) within the 1-electron exact two-component (1eX2C) relativistic framework. The effectiveness of both the CCSD(T) and the completely renormalized (CR) CC(2,3) approaches are demonstrated by performing all-electron computations of th

Annie Yang

Extended reality can weave together the fabric of the past, present, and future. A two-day design hackathon was held to bring the community together through a love for history and a common goal to use technology for good. Through interviewing an influential community elder, Emile Pitre, and referencing his book Revolution to Evolution, my team developed an a

TaeHo Yoon, Jaeyeon Kim, Jaewook J. Suh, Ernest K. Ryu

Recently, accelerated algorithms using the anchoring mechanism for minimax optimization and fixed-point problems have been proposed, and matching complexity lower bounds establish their optimality. In this work, we present the surprising observation that the optimal acceleration mechanism in minimax optimization and fixed-point problems is not unique. Our ne

Ching-Yao Lai, Pedram Hassanzadeh, Aditi Sheshadri, Maike Sonnewald

We discuss the emerging advances and opportunities at the intersection of machine learning (ML) and climate physics, highlighting the use of ML techniques, including supervised, unsupervised, and equation discovery, to accelerate climate knowledge discoveries and simulations. We delineate two distinct yet complementary aspects: (1) ML for climate physics and

Chong-Xing Yue, Xin-Yang Li, Xiao-Chen Sun

We explore the possibility of detecting the couplings of axion-like particle (ALP) with leptons from their loop-level impact on the ALP couplings to electroweak (EW) gauge bosons via the signal process $e^+ e^- \to \gamma \gamma {E\mkern-10.5 mu/}$ at the Circular Electron Positron Collider (CEPC) and obtain prospective sensitivities to the ALP-lepton coupli

M. J. Taranchuk, R. J. Braun

The human tear film (TF) is thin multilayer fluid film that is critical for clear vision and ocular surface health. Its dynamics are strongly affected by a floating lipid layer and, in health, that layer slows evaporation and helps create a more uniform tear film over the ocular surface. The tear film lipid layer (LL) may have liquid crystalline characterist

Donghwan Lee, Hyunjun Na

Convergence of Q-learning has been the subject of extensive study for decades. Among the available techniques, the ordinary differential equation (ODE) method is particularly appealing as a general-purpose, off-the-shelf tool for sanity-checking the convergence of a wide range of reinforcement learning algorithms. In this paper, we develop a unified ODE-base

Yuta Sumiya, Hayaru shouno

Machine-learning models, which are known to accurately predict patterns from large datasets, are crucial in decision making. Consequently, counterfactual explanations-methods explaining predictions by introducing input perturbations-have become prominent. These perturbations often suggest ways to alter the predictions, leading to actionable recommendations.

Heather Wilber, Ethan N. Epperly, Alex H. Barnett

A direct solver is introduced for solving overdetermined linear systems involving nonuniform discrete Fourier transform matrices. Such matrices can be transformed into a Cauchy-like form that has hierarchical low rank structure. The rank structure of this matrix is explained, and it is shown that the ranks of the relevant submatrices grow only logarithmicall

Ali Nasiri-Sarvi, Vincent Quoc-Huy Trinh, Hassan Rivaz, Mahdi S. Hosseini

Representation learning from Gigapixel Whole Slide Images (WSI) poses a significant challenge in computational pathology due to the complicated nature of tissue structures and the scarcity of labeled data. Multi-instance learning methods have addressed this challenge, leveraging image patches to classify slides utilizing pretrained models using Self-Supervis

Paul Zinn-Justin

We discuss the use of methods coming from integrable systems to study problems of enumerative and algebraic combinatorics, and develop two examples: the enumeration of Alternating Sign Matrices and related combinatorial objects, and the theory of symmetric polynomials.

Dave Kleidermacher, Emmanuel Arriaga, Eric Wang, Sebastian Porst

In this paper, we explore the challenges of ensuring security and privacy for users from diverse demographic backgrounds. We propose a threat modeling approach to identify potential risks and countermeasures for product inclusion in security and privacy. We discuss various factors that can affect a user's ability to achieve a high level of security and priva

Qunwei Lin, Qian Leng, Zhicheng Ding, Chao Yan

In the pursuit of environmental sustainability, the aviation industry faces the challenge of minimizing its ecological footprint. Among the key solutions is contrail avoidance, targeting the linear ice-crystal clouds produced by aircraft exhaust. These contrails exacerbate global warming by trapping atmospheric heat, necessitating precise segmentation and co

Jordan K Kobellarz, Milos Brocic, Daniel Silver, Thiago H Silva

Early optimism saw possibilities for social media to renew democratic discourse, marked by hopes for individuals from diverse backgrounds to find opportunities to learn from and interact with others different from themselves. This optimism quickly waned as social media seemed to breed ideological homophily marked by "filter bubble" or "echo chambers." A typi

Dong Zhang

We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess these characteristics as well. This comparison inspire us to integrate the concept of temperature into ML systems grounded in the fundamental principles of thermodynamics, and establi

Md Montaser Hamid, Fatima Moussaoui, Jimena Noa Guevara, Andrew Anderson

Motivations: Explainable Artificial Intelligence (XAI) systems aim to improve users' understanding of AI, but XAI research shows many cases of different explanations serving some users well and being unhelpful to others. In non-AI systems, some software practitioners have used inclusive design approaches and sometimes their improvements turned out to be "cur

Mykhailo Havdiak, Jose I. Aliaga, Roman Iakymchuk

In this article, we propose an accuracy-assuring technique for finding a solution for unsymmetric linear systems. Such problems are related to different areas such as image processing, computer vision, and computational fluid dynamics. Parallel implementation of Krylov subspace methods speeds up finding approximate solutions for linear systems. In this conte

Lingxiao Yuan, Emma Lejeune, Harold S. Park

There has been significant recent interest in the mechanics community to design structures that can either violate reciprocity, or exhibit elastic asymmetry or odd elasticity. While these properties are highly desirable to enable mechanical metamaterials to exhibit novel wave propagation phenomena, it remains an open question as to how to design passive stru

Adam F. Kowalski, Joel C. Allred, Mats Carlsson

Optical flares have been observed from magnetically active stars for many decades; unsurprisingly, the spectra and temporal evolution are complicated. For example, the shortcomings of optically thin, static slab models have long been recognized when confronted with the observations. A less incorrect -- but equally simple -- phenomenological $T \approx 9000$

S. Mukovnikov, L. Sousa

We include the effect of the frictional force caused by interactions between cosmic strings and the particles of the background plasma in the computation of the stochastic gravitational wave background generated by cosmic string loops. Although our results show that friction leads to a partial suppression of the emission of gravitational radiation by cosmic

Z. Tumbleson, S. A. Morley, E. Hollingworth, A. Singh

A system that possesses translational symmetry but breaks orientational symmetry is known as a nematic phase. While there are many examples of nematic phases in a wide range of contexts, such as in liquid crystals, complex oxides, and superconductors, of particular interest is the magnetic analogue, where the spin, charge, and orbital degrees of freedom of t

Rajat Verma, Eunhan Ka, Satish V. Ukkusuri

The growth in availability of large-scale GPS mobility data from mobile devices has the potential to aid traditional travel demand models (TDMs) such as the four-step planning model, but those processing methods are not commonly used in practice. In this study, we show the application of trip generation and trip distribution modeling using GPS data from smar

Amir Ali Ahmadi, Grigoriy Blekherman, Pablo A. Parrilo

We prove that convex ternary quartic forms are sum-of-squares-convex (sos-convex). This result is in a meaningful sense the ``convex analogue'' a celebrated theorem of Hilbert from 1888, where he proves that nonnegative ternary quartic forms are sums of squares. We show by an appropriate construction that exploiting the structure of the Hessian matrix is cru

Andrew R. Ferdinand, Zheng Luo, Sindhu Jammi, Zachary Newman

We report on experiments generating a magneto-optical trap (MOT) of 88-strontium ($^{88}$Sr) atoms at microkelvin temperature, using integrated-photonics devices. With metasurface optics integrated on a fused-silica substrate, we generate six-beam, circularly polarized, counter-propagating MOTs on the blue broad-line, 461 nm, and red narrow-line, 689 nm, Sr

Seong Jin Lee, Will Wei Sun, Yufeng Liu

As e-commerce expands, delivering real-time personalized recommendations from vast catalogs poses a critical challenge for retail platforms. Maximizing revenue requires careful consideration of both individual customer characteristics and available item features to continuously optimize assortments over time. In this paper, we consider the dynamic assortment

Zhen Gao

We prove a multiplicity result for rectangular pegs that there is a generic class of smooth Jordan curves in which every curve admits two geometrically distinct similar inscribed rectangles with aspect angle in $(0,\frac{\pi}{2})$, based on the existence of rectangular pegs in any smooth Jordan curve, which is first proved by Greene and Lobb [GL21] and we gi

Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng

Today's LLMs are susceptible to prompt injections, jailbreaks, and other attacks that allow adversaries to overwrite a model's original instructions with their own malicious prompts. In this work, we argue that one of the primary vulnerabilities underlying these attacks is that LLMs often consider system prompts (e.g., text from an application developer) to

Shirley Wu, Shiyu Zhao, Michihiro Yasunaga, Kexin Huang

Answering real-world complex queries, such as complex product search, often requires accurate retrieval from semi-structured knowledge bases that involve blend of unstructured (e.g., textual descriptions of products) and structured (e.g., entity relations of products) information. However, many previous works studied textual and relational retrieval tasks as

Amrita Acharyya

In this work, we study type B set partitions for a given specific positive integer $k$ defined over $\langle n\rangle=\{-n, -(n-1),\cdots -1,0,1,\cdots n-1,n\}$. We found a few generating functions of type B analogue for some of the set partition statistics defined by Wachs, White and Steingrimsson for partitions over positive integers $[n] =\{1,2,\cdots n\}

Cunxi Dai, Xiaohan Liu, Roberto Shu, Ralph Hollis

In this work, we present a control framework to effectively maneuver wheelchairs with a dynamically stable mobile manipulator. Wheelchairs are a type of nonholonomic cart system, maneuvering such systems with mobile manipulators (MM) is challenging mostly due to the following reasons: 1) These systems feature nonholonomic constraints and considerably varying

H. Wang, R. Canameras, S. H. Suyu, A. Galan

We present a mass measurement for the secondary lens along the line of sight (LoS) in the multi-plane strong lens modeling of the group-scale lens CASSOWARY 31 (CSWA 31). The secondary lens at redshift $z = 1.49$ is a spiral galaxy well aligned along the LoS with the main lens at $z = 0.683$. Using the MUSE integral-field spectroscopy of this spiral galaxy,

Sam Gunn, Yael Tauman Kalai, Anand Natarajan, Agi Villanyi

We define the notion of a classical commitment scheme to quantum states, which allows a quantum prover to compute a classical commitment to a quantum state, and later open each qubit of the state in either the standard or the Hadamard basis. Our notion is a strengthening of the measurement protocol from Mahadev (STOC 2018). We construct such a commitment sch

Yuliang Xu, Timothy D. Johnson, Thomas E. Nichols, Jian Kang

Bayesian Image-on-Scalar Regression (ISR) provides flexible, uncertainty-aware neuroimaging analysis. However, applying ISR to large-scale datasets such as the UK Biobank is challenging due to intensive computational demands and the need to handle subject-specific brain masks rather than a common mask. We propose a novel Bayesian ISR model that scales effici

James Holliday, Braeden Morgan, Hugh Churchill, Khoa Luu

There has never been a more exciting time for the future of quantum computing than now. Near-term quantum computing usage is now the next XPRIZE. With that challenge in mind we have explored a new approach as a hybrid quantum-classical algorithm for solving NP-Hard optimization problems. We have focused on the classic problem of the Capacitated Vehicle Routi

Avimita Chatterjee, Subrata Das, Swaroop Ghosh

Quantum error correction (QEC) plays a crucial role in correcting noise and paving the way for fault-tolerant quantum computing. This field has seen significant advancements, with new quantum error correction codes emerging regularly to address errors effectively. Among these, topological codes, particularly surface codes, stand out for their low error thres

Renzo Cavalieri, Matthew M. Williams

This paper studies the relationship between quadratic Hodge classes on moduli spaces of pseudostable and stable curves given by the contraction morphism $\mathcal{T}.$ While Mumford relations do not hold in the pseudostable case, we show that one can express the (pullback via $\mathcal{T}$ of the) Chern classes of $\mathbb{E}\oplus \mathbb{E}^\vee$ solely in

Long Liu

We show that in the case of primary field extensions, the extension of scalars of Deligne $1$-motives admits a left adjoint, called Chow image, and a right adjoint, called Chow trace. This generalizes Chow's results on abelian varieties. Then we study the Chow trace in the framework of Voevodsky's triangulated categories of (\'etale) motives. With respect to

Gunnar Carlsson, Roy Joshua, Pablo Pelaez

In the present paper, we discuss applications of the derived completion theorems proven in our previous two papers. One of the main applications is to Riemann-Roch problems for forms of higher equivariant K-theory, which we are able to establish in great generality both for equivariant G-theory and equivariant homotopy K-theory with respect to actions of lin

Jose Ignacio Hernandez, Niek Mouter, Sander van Cranenburgh

Random utility maximisation (RUM) models are one of the cornerstones of discrete choice modelling. However, specifying the utility function of RUM models is not straightforward and has a considerable impact on the resulting interpretable outcomes and welfare measures. In this paper, we propose a new discrete choice model based on artificial neural networks (

Ruibo Wang, Baha Eddine Youcef Belmekki, Xue Zhang, Mohamed-Slim Alouini

To meet the demands of densely deploying communication and sensing devices in the next generation of wireless networks, integrated sensing and communication (ISAC) technology is employed to alleviate spectrum scarcity, while stochastic geometry (SG) serves as a tool for low-complexity performance evaluation. To assess network-level performance, there is a na

Gunnar Carlsson, Roy Joshua, Pablo Pelaez

In the mid 1980s, while working on establishing completion theorems for equivariant Algebraic K-Theory similar to the well-known completion theorems for equivariant topological K-theory, the late Robert Thomason found the strong finiteness conditions that are required in such theorems to be too restrictive. Then he made a conjecture on the existence of a com

Junjie Li, Yinzhi Wang, Xiao Liang, Hang Liu

Porting codes to GPU often requires major efforts. While several tools exist for automatically offload numerical libraries such as BLAS and LAPACK, they often prove impractical due to the high cost of mandatory data transfer. The new unified memory architecture in NVIDIA Grace-Hopper allows high bandwidth cache-coherent memory access of all memory from both

Zhixin Pan, Emma Andrews, Laura Chang, Prabhat Mishra

Data augmentation is widely used to mitigate data bias in the training dataset. However, data augmentation exposes machine learning models to privacy attacks, such as membership inference attacks. In this paper, we propose an effective combination of data augmentation and machine unlearning, which can reduce data bias while providing a provable defense again

Ankan Dash, Jingyi Gu, Guiling Wang, Nirwan Ansari

Machine learning techniques have shown remarkable accuracy in localization tasks, but their dependency on vast amounts of labeled data, particularly Channel State Information (CSI) and corresponding coordinates, remains a bottleneck. Self-supervised learning techniques alleviate the need for labeled data, a potential that remains largely untapped and underex

Dariusz Dereniowski, Przemysław Gordinowicz, Karolina Wróbel

This work generalizes the binary search problem to a $d$-dimensional domain $S_1\times\cdots\times S_d$, where $S_i=\{0, 1, \ldots,n_i-1\}$ and $d\geq 1$, in the following way. Given $(t_1,\ldots,t_d)$, the target element to be found, the result of a comparison of a selected element $(x_1,\ldots,x_d)$ is the sequence of inequalities each stating that either

Yuchen Zhang, Xiaoxiao Ma, Jia Wu, Jian Yang

Fake news is pervasive on social media, inflicting substantial harm on public discourse and societal well-being. We investigate the explicit structural information and textual features of news pieces by constructing a heterogeneous graph concerning the relations among news topics, entities, and content. Through our study, we reveal that fake news can be effe

Sthithpragya Gupta, Kunpeng Yao, Loïc Niederhauser, Aude Billard

Large Language Models (LLMs) present a promising frontier in robotic task planning by leveraging extensive human knowledge. Nevertheless, the current literature often overlooks the critical aspects of robots' adaptability and error correction. This work aims to overcome this limitation by enabling robots to modify their motions and select the most suitable t

Ying Yang, Jiguang Yao, Yang Xiao, Pak-Tik Fong

Developing quantum networks necessitates coherently connecting distant systems via remote strong coupling. Here, we demonstrate long-distance coherence in cavity magnonics operating in the linear regime. By locally setting the cavity near critical coupling with travelling photons, non-local magnon-photon coherence is established via strong coupling over a 2-

Gonzalo Garcia-Atance Fatjo

A tool to improve the effectiveness and the efficiency of public spending is proposed here. In the 19th century banknotes had a serial number. However, in modern days the use of digital transactions that do not use physical currency has opened the possibility to digitally track almost each cent of the economy. In this article a serial number or tracking numb

Tomáš Roubíček

The thermodynamical model of viscoelastic deformable solids at finite strains with Kelvin-Voigt rheology with a higher-order viscosity (using the concept of multipolar materials) is formulated in a fully Eulerian way in rates. Assumptions used in this paper allow for a physically justified free energy leading to non-negative entropy that satisfies the 3rd la

Byron Droguett, Claudio Bórquez

We explore the Casimir effect of a rough membrane within the framework of theories that break Lorentz symmetry. We consider two constant Aether vectors: one timelike and other spacelike, simultaneously. We employ an appropriate change of coordinates such that the membrane assumes a completely flat border and the remaining terms associated with the roughness

Lorenzo Ciardo

Information-processing tasks modelled by homomorphisms between relational structures can witness quantum advantage when entanglement is used as a computational resource. We prove that the occurrence of quantum advantage is determined by the same type of algebraic structure (known as a minion) that captures the polymorphism identities of CSPs and, thus, CSP c

Chih-Ying Liu, Jeya Maria Jose Valanarasu, Camila Gonzalez, Curtis Langlotz

Most deep learning models in medical imaging are trained on adult data with unclear performance on pediatric images. In this work, we aim to address this challenge in the context of automated anatomy segmentation in whole-body Computed Tomography (CT). We evaluate the performance of CT organ segmentation algorithms trained on adult data when applied to pedia

Ang Li, Chenxu Liu, Samuel Stein, In-Saeng Suh

Although there have been remarkable advances in quantum computing (QC), it remains crucial to simulate quantum programs using classical large-scale parallel computing systems to validate quantum algorithms, comprehend the impact of noise, and develop resilient quantum applications. This is particularly important for bridging the gap between near-term noisy-i

Thomas Führer, Manuel A. Sánchez

We design quasi-interpolation operators based on piecewise polynomial weight functions of degree less than or equal to $p$ that map into the space of continuous piecewise polynomials of degree less than or equal to $p+1$. We show that the operators have optimal approximation properties, i.e., of order $p+2$. This can be exploited to enhance the accuracy of f

Peiman Mohseni, Nick Duffield

Neural Processes (NPs) are meta-learning models that learn to map sets of observations to approximations of the corresponding posterior predictive distributions. By accommodating variable-sized, unstructured collections of observations and enabling probabilistic predictions at arbitrary query points, NPs provide a flexible framework for modeling functions ov

Robert Beinert, Jonas Bresch

Circle- and sphere-valued data play a significant role in inverse problems like magnetic resonance phase imaging and radar interferometry, in the analysis of directional information, and in color restoration tasks. In this paper, we aim to restore $(d-1)$-sphere-valued signals exploiting the classical anisotropic total variation on the surrounding $d$-dimens

Pei-Yun Lin, Darshan Chalise, David G. Cahill

Thermometry based on magnetic resonance has been extensively studied due to its important application in biomedical imaging. In our previous work, we showed that the spin-spin relaxation time (T2) of nuclear magnetic resonance (NMR) in water is a highly sensitive thermometer as T2 scales with the highly temperature-sensitive self-diffusion constant of water.

Zeinab Nezami, Emmanouil Chaniotakis, Evangelos Pournaras

The transformation of smart mobility is unprecedented--Autonomous, shared and electric connected vehicles, along with the urgent need to meet ambitious net-zero targets by shifting to low-carbon transport modalities result in new traffic patterns and requirements for real-time computation at large-scale, for instance, augmented reality applications. The clou

Andres Gomez-Lievano, Michail Fragkias

There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies,

Zhaohua Lu, John Toso, Girma Ayele, Philip He

In early phase drug development of combination therapy, the primary objective is to preliminarily assess whether there is additive activity from a novel agent when combined with an established monotherapy. Due to potential feasibility issues for conducting a large randomized study, uncontrolled single-arm trials have been the mainstream approach in cancer cl

Z. Dencs, A. Derekas, T. Mitnyan, M. F. Andersen

Understanding the atmospheric parameters of stars on the top of the RGB is essential to reveal the chemical composition of the Milky Way, as they can be used to probe the farthest parts of our Galaxy. Our goal is to determine the chemical composition of 21 RGB stars with $T_{\mathrm{eff}}<4200$K selected from the APOGEE-2 DR17 database using new observations

Ashton Lowenstein

We consider matrix models exhibiting open-closed string duality in two-dimensional string theories with various amounts of supersymmetry. In particular, a relationship between matrix models in the $\beta = 2$ Wigner-Dyson class and models in the $(1 + 2\Gamma, 2)$ Altland-Zirnbauer class relates the perturbative solutions of the two systems' string equations

Gunnar Carlsson, Roy Joshua

In this paper, we establish the key properties of the motivic and \'etale Becker-Gottlieb transfer including compatibility with \'etale and Betti realization and show how to obtain various splittings using the transfer.

Christopher D. Woodgate, George A. Marchant, Livia B. Pártay, Julie B. Staunton

We study the phase behaviour of the Al$_x$CrFeCoNi high-entropy alloy. Our approach is based on a perturbative analysis of the internal energy of the paramagnetic solid solution as evaluated within the Korringa-Kohn-Rostoker formulation of density functional theory, using the coherent potential approximation to average over disorder. Via application of a Lan

Alex Berke, Robert Mahari, Sandy Pentland, Kent Larson

Data generated by users on digital platforms are a crucial resource for advocates and researchers interested in uncovering digital inequities, auditing algorithms, and understanding human behavior. Yet data access is often restricted. How can researchers both effectively and ethically collect user data? This paper shares an innovative approach to crowdsourci

Reetika Joshi, Guillaume Aulanier, Alice Radcliffe, Luc Rouppe van der Voort

Solar jets are collimated plasma flows moving along magnetic field lines and accelerated at low altitude following magnetic reconnection. Several of them originate from anemone-shaped low-lying arcades and the most impulsive ones tend to be relatively wider and display untwisting motions. We aim to establish typical behaviours and observational signatures in

Omer Aydin, Enis Karaarslan, Nida Gokce Narin

Human Resources (HR) technology solutions encompass software and hardware tools designed to automate HR processes, gather, process, and analyze data, utilize it for strategic decision-making, and execute HR professionals' tasks while prioritizing security and privacy considerations. As with numerous other domains, Digital Transformation and emerging technolo

Soumen Koley, Jan Harms, Annalisa Allocca, Enrico Calloni

A system was recently implemented in the Virgo detector to cancel noise in its data produced by seismic waves directly coupling with the suspended test masses through gravitational interaction. The data from seismometers are being filtered to produce a coherent estimate of the associated gravitational noise also known as Newtonian noise. The first implementa

Alexandru Chirvasitu

We prove a number of results of the following common flavor: for a category $\mathcal{C}$ of topological or uniform spaces with all manner of other properties of common interest (separation / completeness / compactness axioms), a group (or monoid) $\mathbb{G}$ equipped with various types of topological structure (topologies, uniformities) and the correspondi

Joscelyn van der Veen, Daniel James

The ubiquity of optical coherence arising from its importance in everything from astronomy to photovoltaics means that underlying assumptions such as stationarity and ergodicity can become implicit. When these assumptions become implicit, it can appear that two different averages are independent: the finite time averaging of a detector and the ensemble avera

Robert Magnusson, Yeong H. Ko, Kyu J. Lee, Fairooz A. Simlan

We present subwavelength resonant lattices fashioned as nano- and microstructured films as a basis for a host of device concepts. Whereas the canonical physical properties are fully embodied in a one-dimensional periodic lattice, the final device constructs are often patterned in two-dimensionally-modulated films in which case we may refer to them as photoni

V. Berejnov, B. Y. Rubinstein

A new method recovers phase difference of interfering wavefronts from a pattern of interference fringes, avoiding discontinuity problem. The continuous phase is a solution of the first order differential equation of the interferogram function computed from the fringe intensity profile selected along the pathway over the interferogram.

Matěj Boxan, Alexander Krawciw, Effie Daum, Xinyuan Qiao

In this paper, we propose the FoMo (For\^et Montmorency) dataset: a comprehensive, multi-season data collection. Located in the Montmorency Forest, Quebec, Canada, our dataset will capture a rich variety of sensory data over six distinct trajectories totaling 6 kilometers, repeated through different seasons to accumulate 42 kilometers of recorded data. The b

Morteza Behrooz, Yuandong Tian, William Ngan, Yael Yungster

Generative AI has put many professional writers on the defensive; a major negotiation point of the recent Writers Guild of America's strike concerned use of AI. However, must AI threaten writers, their livelihoods or their creativity? And under what conditions, if any, might AI assistance be invited by different types of writers (from the amateur to the prof

Ryan Cumings-Menon, Pavel Zhuravlev

The U.S. Census Bureau's 2020 Disclosure Avoidance System (DAS) bases its output on noisy measurements, which are population tabulations added to realizations of mean-zero random variables. These noisy measurements are observed for a set of hierarchical geographic levels, e.g., the U.S. as a whole, states, counties, census tracts, and census blocks. The Cens

Alireza Javadian Sabet, Sarah H. Bana, Renzhe Yu, Morgan R. Frank

Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce. While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document wh

Dinh Van Tuan, Hanan Dery

We present a new method to solve the dynamical Bethe-Salpeter Equation numerically. The method allows one to investigate the effects of dynamical dielectric screening on the spectral position of excitons in transition-metal dichalcogenide monolayers. The dynamics accounts for the response of optical phonons in the materials below and on top the monolayer to

Manish Bhatt, Sahana Chennabasappa, Yue Li, Cyrus Nikolaidis

Large language models (LLMs) introduce new security risks, but there are few comprehensive evaluation suites to measure and reduce these risks. We present BenchmarkName, a novel benchmark to quantify LLM security risks and capabilities. We introduce two new areas for testing: prompt injection and code interpreter abuse. We evaluated multiple state-of-the-art

Christian Kisielowski, Petra Specht, Joerg R. Jinschek, Stig Helveg

Intensities in high-resolution phase-contrast images from electron microscopes build up discretely in time by detecting single electrons. A wave description of pulse-like coherent-inelastic interaction of an electron with matter is detailed and verified. In perspective, the interaction time of any matter wave compares with the lifetime of a virtual particle

Jyothisraj Johnson, Billy Boxer, Tarun Prakash, Carl Grace

There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physics communities. A big driver has been the release of the Python package, hls4ml, which has enabled porting models specified and trained using Python ML libraries to register transf

Shuo Li, Mike Davies, Mehrdad Yaghoobi

Hyperspectral imaging (HSI) is a key technology for earth observation, surveillance, medical imaging and diagnostics, astronomy and space exploration. The conventional technology for HSI in remote sensing applications is based on the push-broom scanning approach in which the camera records the spectral image of a stripe of the scene at a time, while the imag

Mingcheng He, Huaqing Wu, Conghao Zhou, Xuemin

Satellite-terrestrial integrated networks (STIN) are envisioned as a promising architecture for ubiquitous network connections to support diversified services. In this paper, we propose a novel resource slicing scheme with cross-cell coordination in STIN to satisfy distinct service delay requirements and efficient resource usage. To address the challenges po

Fausto Di Biase, Steven G. Krantz

Let $X$ be a complete measure space of finite measure. The Lebesgue transform of an integrable function $f$ on $X$ encodes the collection of all the mean-values of $f$ on all measurable subsets of $X$ of positive measure. In the problem of the differentiation of integrals, one seeks to recapture $f$ from its Lebesgue transform. In previous work we showed tha

Lingyao Li, Songhua Hu, Atiyya Shaw, Libby Hemphill

Understanding how urban density impacts public perceptions of urban service is important for informing livable, accessible, and equitable urban planning. Conventional methods such as surveys are limited by their sampling scope, time efficiency, and expense. On the other hand, crowdsourcing through online platforms presents an opportunity for decision-makers

Ruy Fabila-Monroy, Rosna Paul, Jenifer Viafara-Chanchi, Alexandra Weinberger

A rectilinear drawing of a graph is a drawing of the graph in the plane in which the edges are drawn as straight-line segments. The rectilinear crossing number of a graph is the minimum number of pairs of edges that cross over all rectilinear drawings of the graph. Let $n \ge r$ be positive integers. The graph $K_n^r$, is the complete $r$-partite graph on $n

M. Manav, R. Molinaro, S. Mishra, L. De Lorenzis

We explore the potential of the deep Ritz method to learn complex fracture processes such as quasistatic crack nucleation, propagation, kinking, branching, and coalescence within the unified variational framework of phase-field modeling of brittle fracture. We elucidate the challenges related to the neural-network-based approximation of the energy landscape,

Chengxu Liu, Xuan Wang, Xiangyu Xu, Ruhao Tian

Eliminating image blur produced by various kinds of motion has been a challenging problem. Dominant approaches rely heavily on model capacity to remove blurring by reconstructing residual from blurry observation in feature space. These practices not only prevent the capture of spatially variable motion in the real world but also ignore the tailored handling

Mohamed Niged Mabrouk, Daniel Floryan

When swimming animals form cohesive groups, they can reap several benefits. Our understanding of collective animal motion has traditionally been driven by models based on phenomenological behavioral rules, but more recent work has highlighted the critical importance of hydrodynamic interactions among a group of inertial swimmers. To study how hydrodynamic in

Annesh Mukhopadhyay, Xi-Wang Luo, Colby Schimelfenig, M. K. H. Ome

The momentum space Josephson effect describes the supercurrent flow between weakly coupled Bose-Einstein condensates (BECs) at two discrete momentum states. Here, we experimentally observe this exotic phenomenon using a BEC with Raman-induced spin-orbit coupling, where the tunneling between two local band minima is implemented by the momentum kick of an addi

Douglas Rebstock, Christopher Solinas, Nathan R. Sturtevant, Michael Buro

Traditional search algorithms have issues when applied to games of imperfect information where the number of possible underlying states and trajectories are very large. This challenge is particularly evident in trick-taking card games. While state sampling techniques such as Perfect Information Monte Carlo (PIMC) search has shown success in these contexts, t

Chia-Hsuan Chang, Mary M. Lucas, Yeawon Lee, Christopher C. Yang

Advances in large language models (LLMs) have encouraged their adoption in the healthcare domain where vital clinical information is often contained in unstructured notes. Cancer staging status is available in clinical reports, but it requires natural language processing to extract the status from the unstructured text. With the advance in clinical-oriented

Mostafa ElAraby, Ali Harakeh, Liam Paull

Semantic segmentation plays a crucial role in enabling comprehensive scene understanding for robotic systems. However, generating annotations is challenging, requiring labels for every pixel in an image. In scenarios like autonomous driving, there's a need to progressively incorporate new classes as the operating environment of the deployed agent becomes mor

Liang Wang, Luis Carvalho

Model evaluation is of crucial importance in modern statistics application. The construction of ROC and calculation of AUC have been widely used for binary classification evaluation. Recent research generalizing the ROC/AUC analysis to multi-class classification has problems in at least one of the four areas: 1. failure to provide sensible plots 2. being sen

Yan Ju, Chengzhe Sun, Shan Jia, Shuwei Hou

Deepfakes, as AI-generated media, have increasingly threatened media integrity and personal privacy with realistic yet fake digital content. In this work, we introduce an open-source and user-friendly online platform, DeepFake-O-Meter v2.0, that integrates state-of-the-art methods for detecting Deepfake images, videos, and audio. Built upon DeepFake-O-Meter