April 2023 arXiv papers — page 128

Yoon Chan Taak, Tommaso Treu

Strong lensed quasi-stellar objects (QSOs) are valuable probes of the universe in numerous aspects. Two of these applications, reverberation mapping and measuring time delays for determining cosmological parameters, require the source QSOs to be variable with sufficient amplitude. In this paper, we forecast the number of strong lensed QSOs with sufficient va

Adam Humeniuk, Christopher Ramsey

In this paper it is shown that the lattice of C*-covers of an operator algebra does not contain enough information to distinguish operator algebras up to completely isometric isomorphism. In addition, four natural equivalences of the lattice of C*-covers are developed and proven to be distinct. The lattice of C*-covers of direct sums and tensor products are

Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes

Few-shot-based facial recognition systems have gained increasing attention due to their scalability and ability to work with a few face images during the model deployment phase. However, the power of facial recognition systems enables entities with moderate resources to canvas the Internet and build well-performed facial recognition models without people's a

Alexander Kozachinskiy

In this note, we establish the hardness of approximation of the problem of computing the minimal size of a $\delta$-sufficient reason for decision trees.

Can Li, Xiaoqian Jiang, Kai Zhang

Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for a donor and ensuring transplant equity among different subpopulations. The current MELD scoring system evaluates a patient's mortality risk if not receiving an organ within 90 day

Andrew W. Mayo, Courtney D. Dressing, Andrew Vanderburg, Charles D. Fortenbach

K2-136 is a late-K dwarf ($0.742\pm0.039$ M$_\odot$) in the Hyades open cluster with three known, transiting planets and an age of $650\pm70$ Myr. Analyzing K2 photometry, we found that planets K2-136b, c, and d have periods of $8.0$, $17.3$, and $25.6$ days and radii of $1.014\pm0.050$ R$_\oplus$, $3.00\pm0.13$ R$_\oplus$, and $1.565\pm0.077$ R$_\oplus$, re

Daniel Bragg

We show that if $K$ is an arbitrary field and $G$ is a finite group then there exists a curve over $K$ with automorphism group $G$. We also give a positive solution to the weak inverse Galois problem for function fields over an arbitrary field. Finally, we reduce the inverse Galois problem for function fields over an arbitrary field $K$ to the case of $K(T)$

Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny

Video generation remains a challenging task due to spatiotemporal complexity and the requirement of synthesizing diverse motions with temporal consistency. Previous works attempt to generate videos in arbitrary lengths either in an autoregressive manner or regarding time as a continuous signal. However, they struggle to synthesize detailed and diverse motion

A. G. Sreejith, Luca Fossati, P. E. Cubillos, S Ambily

We present here the signal-to-noise (S/N) calculator developed for the Colorado Ultraviolet Transit Experiment (CUTE) mission. CUTE is a 6U CubeSat operating in the near-ultraviolet (NUV) observing exoplanetary transits to study their upper atmospheres. CUTE was launched into a low-Earth orbit in September 2021 and it is currently gathering scientific data.

Federica Milinanni, Pierre Nyquist

To sample from a given target distribution, Markov chain Monte Carlo (MCMC) sampling relies on constructing an ergodic Markov chain with the target distribution as its invariant measure. For any MCMC method, an important question is how to evaluate its efficiency. One approach is to consider the associated empirical measure and how fast it converges to the s

Manon Revel, Niclas Boehmer, Rachael Colley, Markus Brill

As the world's democratic institutions are challenged by dissatisfied citizens, political scientists and also computer scientists have proposed and analyzed various (innovative) methods to select representative bodies, a crucial task in every democracy. However, a unified framework to analyze and compare different selection mechanisms is missing, resulting i

Ernesto Pini, Giacomo Mazzamuto, Francesco Riboli, Diederik S. Wiersma

Transport processes underpin a multitude of phenomena, ranging from the propagation of atoms on lattices, to the mobility patterns of microorganisms and earthquakes, to name a few. The dynamics of these processes is very rich and key to understanding the complex nature of the underlying physics, but the way in which we classify them is often too simplistic t

Devan Walton

This paper presents a cognitive tutor powered by Davinci 003 API that generates and evaluates personalized questions for students on any topic they choose. The tutor adapts to the student's level of understanding and fosters knowledge transfer by generating questions that relate the topic to different domains. This solution has the potential to improve stude

Vinitha Ranganeni, Noah Ponto, Maya Cakmak

Mobile manipulator platforms, like the Stretch RE1 robot, make the promise of in-home robotic assistance feasible. For people with severe physical limitations, like those with quadriplegia, the ability to tele-operate these robots themselves means that they can perform physical tasks they cannot otherwise do themselves, thereby increasing their level of inde

Vinayak M. Kumar

We initiate the study of generalized AC0 circuits comprised of negations and arbitrary unbounded fan-in gates that only need to be constant over inputs of Hamming weight $\ge k$, which we denote GC0$(k)$. The gate set of this class includes biased LTFs like the $k$-$OR$ (output $1$ iff $\ge k$ bits are 1) and $k$-$AND$ (output $0$ iff $\ge k$ bits are 0), an

Viswanath Chadalapaka, Derek Nguyen, JoonWon Choi, Shaunak Joshi

In this paper, we study the problem of claim verification in the context of claims about fictional stories in a low-shot learning setting. To this end, we generate two synthetic datasets and then develop an end-to-end pipeline and model that is tested on both benchmarks. To test the efficacy of our pipeline and the difficulty of benchmarks, we compare our mo

Vitor Alcantara Batista, Alexandre Gonçalves Evsukoff

The combined growth of available data and their unstructured nature has received increased interest in natural language processing (NLP) techniques to make value of these data assets since this format is not suitable for statistical analysis. This work presents a systematic literature review of state-of-the-art advances using transformer-based methods on ele

Satish Kumar, Ivan Arevalo, ASM Iftekhar, B S Manjunath

Methane (CH$_4$) is the chief contributor to global climate change. Recent Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) has been very useful in quantitative mapping of methane emissions. Existing methods for analyzing this data are sensitive to local terrain conditions, often require manual inspection from domain experts, prone

Markus Rothgaenger, Andrew Melnik, Helge Ritter

In this paper, we compare methods for estimating the complexity of two-dimensional shapes and introduce a method that exploits reconstruction loss of Variational Autoencoders with different sizes of latent vectors. Although complexity of a shape is not a well defined attribute, different aspects of it can be estimated. We demonstrate that our methods capture

Luca Asselle, Gabriele Benedetti, Massimiliano Berti

We construct an infinite-dimensional family of smooth integrable magnetic systems on the two-torus which are Zoll, meaning that all the unit-speed magnetic geodesics are periodic. The metric and the magnetic field of such systems are arbitrarily close to the flat metric and to a given constant magnetic field. This extends to the magnetic setting a famous res

Arthur Chakwizira, Ante Zhu, Thomas Foo, Carl-Fredrik Westin

The dependence of the diffusion MRI signal on the diffusion time carries signatures of restricted diffusion and exchange. Here we seek to highlight these signatures in the human brain by performing experiments using free gradient waveforms that are selectively sensitive to the two effects. We examine six healthy volunteers using both strong and ultra-strong

Erjen Lefeber, Marcus Greiff, Anders Robertsson

We propose an observer for rotational dynamics subject to directional and gyroscopic measurements, which simultaneously estimates the gyroscopic biases and attitude rates. We show uniform almost global asymptotic and local exponential stability of the resulting error dynamics, implying robustness against bounded disturbances. This robustness is quantified wi

Jon Lasa-Alonso, Iker Gómez-Viloria, Álvaro Nodar, Aitzol García-Etxarri

Researchers routinely characterize optical samples by computing the scattering cross-section. However, the experimental determination of this magnitude requires the measurement and integration of the components of the scattered field in all directions. Here, we propose a method to determine the scattering cross-section and global polarization state of radiat

Houri Ziaeepour

$SU(\infty)$-QGR is a quantum approach to Universe and gravity. Its main assumption is infinite mutually commuting observables in the Universe, leading to representation of $SU(\infty)$ by its Hilbert spaces and those of its subsystems. The Universe as a whole is static, topological, and characterized by two continuous parameters. Nonetheless, quantum fluctu

Aykut İşleyen, Nathan van de Wouw, Ömür Arslan

Differential drive robots that can be modeled as a kinematic unicycle are a standard mobile base platform for many service and logistics robots. Safe and smooth autonomous motion around obstacles is a crucial skill for unicycle robots to perform diverse tasks in complex environments. A classical control approach for unicycle control is feedback linearization

Kamil Fedorowicz, Robert Prosser, Anupam Sengupta

Using experiments and numerical simulations, we demonstrate that the curvature of microscale conduits allow programming of liquid crystal (LC) flows. Focusing on a nematic LC flowing through U- and L-shaped channels of rectangular cross-section, our results reveal that curved flow paths can trigger gradients of flow-induced director field in the transverse d

Abdullah Alali, Tariq Alkhalifah

In salt provinces, full-waveform inversion (FWI) is most likely to fail when starting with a poor initial model that lacks the salt information. Conventionally, salt bodies are included in the FWI starting model by interpreting the salt boundaries from seismic images, which is time-consuming and prone to error. Studies show that FWI can improve the interpret

Yanbing Xue, Bo Liu, Weizhi Du, Jayanth Korlimarla

In this paper, we study multiple problems from sponsored product optimization in ad system, including position-based de-biasing, click-conversion multi-task learning, and calibration on predicted click-through-rate (pCTR). We propose a practical machine learning framework that provides the solutions to such problems without structural change to existing mach

Hend Al-Khalifa, Malak Mashaabi, Ghadi Al-Yahya, Raghad Alnashwan

This paper introduces the Saudi Privacy Policy Dataset, a diverse compilation of Arabic privacy policies from various sectors in Saudi Arabia, annotated according to the 10 principles of the Personal Data Protection Law (PDPL); the PDPL was established to be compatible with General Data Protection Regulation (GDPR); one of the most comprehensive data regulat

Yuri Uno, Tetsuya Hashimoto, Tomotsugu Goto, Simon C. -C. Ho

The Search for Extra-Terrestrial Intelligence (SETI) has been conducted for over sixty years, yet no technosignatures have been identified. Previous studies have focused on stars in our galaxy, with few searches in the extragalactic Universe despite a larger volume being available. Civilizations capable of harvesting energy from a star or a galaxy are classi

Joshua Ortiz, Alyssa Vellucci, Justin Koeln, Justin Ruths

We show that hybrid zonotopes offer an equivalent representation of feed-forward fully connected neural networks with ReLU activation functions. Our approach demonstrates that the complexity of binary variables is equal to the total number of neurons in the network and hence grows linearly in the size of the network. We demonstrate the utility of the hybrid

Siddharth Suresh, Kushin Mukherjee, Xizheng Yu, Wei-Chun Huang

Neural network models of language have long been used as a tool for developing hypotheses about conceptual representation in the mind and brain. For many years, such use involved extracting vector-space representations of words and using distances among these to predict or understand human behavior in various semantic tasks. Contemporary large language model

Mykhailo Tataryn, Mykola Stetsko

We consider black hole solutions with electric and magnetic sources in the four-dimensional Einstein-Born-Infeld-AdS theory with spherical, planar and hyperbolic horizon geometries. Exact analytical solutions for the metric function, electric and magnetic fields were obtained and they recover the RN-AdS black hole in the limit beta goes to infinity for spher

Yuly Billig

In this paper we solve the problem of finding in a given weighted hypergraph a subhypergraph with a maximum possible density. We introduce the notion of a support matrix and prove that the density of an optimal subhypergraph is equal to $|A^T A|$ for an optimal support matrix $A$. Alternatively, the maximum density of a subhypergraph is equal to the solution

Saikat Das, Satoshi Sugimoto, Varun Kumar Kushwaha, Yusuke Kozuka

Magnetization switching using spin-orbit torque offers a promising route to developing non-volatile memory technologies. The prerequisite, however, is the charge-to-spin current conversion, which has been achieved traditionally by harnessing the spin-orbit interaction in heavy metals, topological insulators, and heterointerfaces hosting a high-mobility two-d

Temuujin Bayaraa, Vsevolod Ivanov, Liang Z. Tan, Sinéad M. Griffin

Using first-principles calculations we investigate the intrinsic origins of the anomalous Hall effect (AHE) and the anomalous Nernst effect (ANE) in antiperovskite ferrimagnet Mn4N. We predict that the AHE is significantly enhanced under both compressive and tensile strain, however, the ANE generally decreases under epitaxial strain, except for 1% compressiv

M. Karrer, K. Wurster, J. Linek, M. Meichsner

Using a $30\,\mathrm{keV}$ focused He ion beam (He-FIB) with a wide range of irradiation doses $D=100$ to $1000\,\mathrm{ions/nm}$ we fabricated Josephson and resistive barriers within microbridges of epitaxially grown single crystalline YBCO thin films and investigated the change of their electric transport properties with time. One set of samples (#1A) was

N. Hüttner, S. Blien, P. Steger, A. N. Loh

Carbon nanotubes are excellent nano-electromechanical systems, combining high resonance frequency, low mass, and large zero-point motion. At cryogenic temperatures they display high mechanical quality factors. Equally they are outstanding single electron devices with well-known quantum levels and have been proposed for the implementation of charge or spin qu

L. B. Bezrukov, I. S. Karpikov, V. V. Sinev

We provide the indication of high flux of $^{40}$K geo-antineutrino and geo-neutrino ($^{40}$K-geo-($\bar{\nu} + \nu$)) with Borexino Phase III data. This result was obtained by introducing a new source of single events, namely $^{40}$K-geo-($\bar{\nu} + \nu$) scattering on electrons, in multivariate fit analysis of Borexino Phase III data. Simultaneously we

Madeline Bumpus, Xufeng Caesar Dai, Auguste H. Gezalyan, Sam Munoz

The Hilbert metric is a projective metric defined on a convex body which generalizes the Cayley-Klein model of hyperbolic geometry to any convex set. In this paper we analyze Hilbert Voronoi diagrams in the Dynamic setting. In addition we introduce dynamic visualization software for Voronoi diagrams in the Hilbert metric on user specified convex polygons.

Sasikarn Khwanmuang, Pakkapon Phongthawee, Patsorn Sangkloy, Supasorn Suwajanakorn

Our paper seeks to transfer the hairstyle of a reference image to an input photo for virtual hair try-on. We target a variety of challenges scenarios, such as transforming a long hairstyle with bangs to a pixie cut, which requires removing the existing hair and inferring how the forehead would look, or transferring partially visible hair from a hat-wearing p

Fiona Young

If $\mathcal{C}$ is a minor-closed class of matroids, then the class $\widetilde{\mathcal{C}}'_k$ of $k$-polymatroids whose $k$-natural matroids are in $\mathcal{C}$ is also minor-closed. We investigate the following question: When $\mathcal{C}$ is the class of binary matroids, what are the excluded minors for $\widetilde{\mathcal{C}}'_k$? When $k = 1$, $\wi

Yunxiang Li, Hua-Chieh Shao, Xiao Liang, Liyuan Chen

Recently, the diffusion model has emerged as a superior generative model that can produce high quality and realistic images. However, for medical image translation, the existing diffusion models are deficient in accurately retaining structural information since the structure details of source domain images are lost during the forward diffusion process and ca

Wei Zheng, Ting Tian, Xueqin Wang

For many tasks of data analysis, we may only have the information of the explanatory variable and the evaluation of the response values are quite expensive. While it is impractical or too costly to obtain the responses of all units, a natural remedy is to judiciously select a good sample of units, for which the responses are to be evaluated. In this paper, w

Bo Liu, Fan Li

Post-treatment confounding is a common problem in causal inference, including special cases of noncompliance, truncation by death, surrogate endpoint, etc. Principal stratification (Frangakis and Rubin 2002) is a general framework for defining and estimating causal effects in the presence of post-treatment confounding. A prominent special case is the instrum

Md. Tanvir Rouf Shawon, G. M. Shahariar, Faisal Muhammad Shah, Mohammad Shafiul Alam

This paper investigates the potential of semi-supervised Generative Adversarial Networks (GANs) to fine-tune pretrained language models in order to classify Bengali fake reviews from real reviews with a few annotated data. With the rise of social media and e-commerce, the ability to detect fake or deceptive reviews is becoming increasingly important in order

Jonathan Francis, Nariaki Kitamura, Felix Labelle, Xiaopeng Lu

Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Robotics. Whereas many approaches and previous survey pursuits have characterised one or two of these dimensions, there has not been a holistic a

Jacob Carlson, Tom Bryan, Melissa Dell

Thousands of users consult digital archives daily, but the information they can access is unrepresentative of the diversity of documentary history. The sequence-to-sequence architecture typically used for optical character recognition (OCR) - which jointly learns a vision and language model - is poorly extensible to low-resource document collections, as lear

Gowtham Senthil, Siva Vignesh Krishnan, Annamalai Lakshmanan, Florence Kissling

With the advent of new technologies, Augmented Reality (AR) has become an effective tool in remote collaboration. Narrow field-of-view (FoV) and motion blur can offer an unpleasant experience with limited cognition for remote viewers of AR headsets. In this article, we propose a two-stage pipeline to tackle this issue and ensure a stable viewing experience w

Miguel Cruz, Samuel Lepe

This work is devoted to the thermodynamics description of a phantom scenario proposed previously by the authors. The presence of negative chemical potential is unavoidable if we allege for a well defined thermodynamics framework since the cosmological model passages from phantom stage at present time to a future de Sitter evolution. As noted earlier in other

Mykhailo Tataryn, Mykola Stetsko

A three-dimensional slowly rotating black hole solution in the presence of negative cosmological constant in the Einstein-power-Maxwell theory is studied. It is shown that in the small rotation limit the electric field, diagonal metric function and thermodynamic properties in the small rotation limit are the same as for static case, whereas the small rotatio

Tsun-Hsuan Wang, Wei Xiao, Makram Chahine, Alexander Amini

Modern end-to-end learning systems can learn to explicitly infer control from perception. However, it is difficult to guarantee stability and robustness for these systems since they are often exposed to unstructured, high-dimensional, and complex observation spaces (e.g., autonomous driving from a stream of pixel inputs). We propose to leverage control Lyapu

Matthew Steinberg, Sebastian Feld, Alexander Jahn

Holographic quantum-error correcting codes are models of bulk/boundary dualities such as the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, where a higher-dimensional bulk geometry is associated with the code's logical degrees of freedom. Previous discrete holographic codes based on tensor networks have reproduced the general code properties

Rian Koots, Jesús Pérez-Ríos

We present Python Quasi-classical atom-molecule scattering (PyQCAMS), a new Python package for atom-molecule scattering within the quasi-classical trajectory approach. The input consists of mass, collision energy, impact parameter, and pair-wise interactions to choose between Buckingham, generalized Lennard-Jones, and Morse potentials. As the output, the cod

Geoffrey Ramseyer, Ashish Goel

Prior work studies the question of ``fairly'' ordering transactions in a replicated state machine. Each of $n$ replicas receives transactions in a possibly different order, and the system must aggregate the observed orderings into a single order. We argue that this problem is best viewed through the lens of social choice theory, in which (in the preference a

Lawrence Rudnick, William D. Cotton

Polarized synchrotron emission from multiple Faraday depths can be separated by calculating the complex Fourier transform of the Stokes' parameters as a function of the wavelength squared, known as Faraday Synthesis. As commonly implemented, the transform introduces an additional term $\lambda_0^2$, which broadens the real and imaginary spectra, but not the

Pei-Gen Yan, James F. Babb

Using a quantum-mechanical close-coupling method, we calculate cross sections for fine structure excitation and relaxation of Si and S atoms in collisions with atomic hydrogen. Rate coefficients are calculated over a range of temperatures for astrophysical applications. We determine the temperature-dependent critical densities for the relaxation of Si and S

Aakash Ashok Naik, Christina Ertural, Nidal Dhamrait, Philipp Benner

An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post

Adrian Celaya, Beatrice Riviere, David Fuentes

Accurate medical imaging segmentation is critical for precise and effective medical interventions. However, despite the success of convolutional neural networks (CNNs) in medical image segmentation, they still face challenges in handling fine-scale features and variations in image scales. These challenges are particularly evident in complex and challenging s

Blake VanBerlo, Brian Li, Alexander Wong, Jesse Hoey

Self-supervised pretraining has been observed to improve performance in supervised learning tasks in medical imaging. This study investigates the utility of self-supervised pretraining prior to conducting supervised fine-tuning for the downstream task of lung sliding classification in M-mode lung ultrasound images. We propose a novel pairwise relationship th

Daoping Yu, Vytaras Brazauskas, Ricardas Zitikis

To accommodate numerous practical scenarios, in this paper we extend statistical inference for smoothed quantile estimators from finite domains to infinite domains. We accomplish the task with the help of a newly designed truncation methodology for discrete loss distributions with infinite domains. A simulation study illustrates the methodology in the case o

Lorenzo Sarnataro, Douglas Stryker

We prove the optimal $C^{1,1}$ regularity for minimizers of the prescribed mean curvature functional over isotopy classes. As an application, we find an embedded sphere of prescribed mean curvature in the round 3-sphere for an open dense set of prescribing functions with $L^{\infty}$ norm at most 0.547.

Daniel Campos, ChengXiang Zhai

Sequence-to-sequence language models can be used to produce abstractive summaries which are coherent, relevant, and concise. Still, model sizes can make deployment in latency-sensitive or web-scale implementations difficult. This paper studies the relationship between model size, structured pruning, inference efficiency, and summarization accuracy on widely

Zheyuan Zhang, Bin Wang, Lanhong Yao, Ugur Demir

Most statistical learning algorithms rely on an over-simplified assumption, that is, the train and test data are independent and identically distributed. In real-world scenarios, however, it is common for models to encounter data from new and different domains to which they were not exposed to during training. This is often the case in medical imaging applic

S. Ben-Ami, E. O. Ofek, D. Polishook, A. Franckowiak

The Large Array Survey Telescope (LAST) is designed to survey the variable and transient sky at high temporal cadence. The array is comprised of 48 F/2.2 telescopes of 27.9cm aperture, coupled to full-frame backside-illuminated cooled CMOS detectors with $3.76$$\mu$m pixels, resulting in a pixel scale of $1.25\mathrm{arcsec}$. A single telescope with a field

Ruairí McConville, Eoin Ó Colgáin

We decompose Pantheon+ Type Ia supernovae (SN) in hemispheres on the sky finding angular variations up to $4$ km/s/Mpc in the Hubble constant $H_0$ both in the SH0ES redshift range $0.0233 < z < 0.15$ and in extended redshift ranges. The variations are driven largely by variations in absolute magnitude from SN in Cepheid hosts, but are reinforced by SN in th

Qiushi Zhang, Dongchuan Mo, Jiya Janowitz, Dan Ringle

Understanding the nucleation and growth dynamics of the surface bubbles generated on a heated surface can benefit a wide range of modern technologies, such as the cooling systems of electronics, refrigeration cycles, nuclear reactors and metal industries, etc. Usually, these studies are conducted in the terrestrial environment. As space exploration and econo

Saif R. Kazi, Kaarthik Sundar, Anatoly Zlotnik

We present a dynamic model for the optimal control problem (OCP) of hydrogen blending into natural gas pipeline networks subject to inequality constraints. The dynamic model is derived using the first principles partial differential equations (PDEs) for the transport of heterogeneous gas mixtures through long distance pipes. Hydrogen concentration is tracked

Pu Li, Xiaobai Liu

This paper presents an unsupervised approach that leverages raw aerial videos to learn to estimate planar homographic transformation between consecutive video frames. Previous learning-based estimators work on pairs of images to estimate their planar homographic transformations but suffer from severe over-fitting issues, especially when applying over aerial

Pu Li, Marie Roch, Holger Klinck, Erica Fleishman

Whistle contour extraction aims to derive animal whistles from time-frequency spectrograms as polylines. For toothed whales, whistle extraction results can serve as the basis for analyzing animal abundance, species identity, and social activities. During the last few decades, as long-term recording systems have become affordable, automated whistle extraction

Sohini Roychowdhury

Semantic segmentation for medical 3D image stacks enables accurate volumetric reconstructions, computer-aided diagnostics and follow up treatment planning. In this work, we present a novel variant of the Unet model called the NUMSnet that transmits pixel neighborhood features across scans through nested layers to achieve accurate multi-class semantic segment

Baidyanath Kundu, Vassil Vassilev, Wim Lavrijsen

The simplicity of Python and the power of C++ force stark choices on a scientific software stack. There have been multiple developments to mitigate language boundaries by implementing language bindings, but the impedance mismatch between the static nature of C++ and the dynamic one of Python hinders their implementation; examples include the use of user-defi

J. Harry Caufield, Harshad Hegde, Vincent Emonet, Nomi L. Harris

Creating knowledge bases and ontologies is a time consuming task that relies on a manual curation. AI/NLP approaches can assist expert curators in populating these knowledge bases, but current approaches rely on extensive training data, and are not able to populate arbitrary complex nested knowledge schemas. Here we present Structured Prompt Interrogation an

S. Bhuvaneswari, R. Muthuganesan, R. Radha

The characterization of quantum resources in dynamical systems is one of the most important problems to be addressed in quantum information theory. In this article, we investigate the behaviors of quantum correlations and teleportation technique in a graphene sheet comprising of disordered electrons in a two-dimensional honeycomb lattice. We use three differ

Sergey Avvakumov, Alexander Nabutovsky

We prove the following result: For each closed $n$-dimensional manifold $M$ in a (finite or infinite-dimensional) Banach space $B$, and each positive real $m\leq n$ there exists a pseudomanifold $W^{n+1}\subset B$ such that $\partial W^{n+1}=M^n$ and ${\rm HC}_m(W^{n+1})\leq c(m){\rm HC}_m(M^n)$. Here ${\rm HC}_m(X)$ denotes the $m$-dimensional Hausdorff con

Toni Hache, Lukas Koerber, Tobias Hula, Kilian Lenz

We use a pure spin current originating from the spin Hall effect to generate a spin-orbit torque (SOT) strongly reducing the effective damping in an adjacent ferromagnet. Due to additional microwave excitation, large spin-wave amplitudes are achieved exceeding the threshold for 4-magnon scattering, thus resulting in additional spin-wave signals at discrete f

Andrei Tokovinin

Results of a large program of spectroscopic monitoring of nearby solar-type stellar hierarchical systems using the CHIRON echelle spectrograph at the 1.5 m telescope are summarized. Ten papers of this series contain 102 spectroscopic orbits and substantially contribute to the knowledge of periods and eccentricties, providing input for the study of their form

Fredrik Warg, Anders Thorsén, Victoria Vu, Carl Bergenhem

Various types of vehicle automation is increasingly used in a variety of environments including road vehicles such as cars or automated shuttles, confined areas such as mines or harbours, or in agriculture and forestry. In many use cases, the benefits are greater if several automated vehicles (AVs) cooperate to aid each other reach their goals more efficient

Weihan Wang, Bharat Joshi, Nathaniel Burgdorfer, Konstantinos Batsos

This paper addresses real-time dense 3D reconstruction for a resource-constrained Autonomous Underwater Vehicle (AUV). Underwater vision-guided operations are among the most challenging as they combine 3D motion in the presence of external forces, limited visibility, and absence of global positioning. Obstacle avoidance and effective path planning require on

Clayton D. Moss, Shayne A. Sorenson, Jeremy A. Johnson

We present a numerical study on plasma generation of THz radiation utilizing multiple light pulses of various wavelengths in an optical scheme that is readily achievable in a tabletop environment. To achieve coherent THz emission it is necessary to carefully consider all the wavelengths involved in a multi-pulse setup. Previous theoretical work has explored

Sweta Mahaju, Jeffrey C. Carver, Gary L. Bradshaw

Context: Software development is human-centric and vulnerable to human error. Human errors are errors in the human thought process. To ensure software quality, practitioners must understand how to manage these human errors. Organizations often change the requirements engineering process to prevent human errors from occurring or to mitigate the harm caused wh

Dan Arnon

Two recent papers by Kawarabayashi, Thomas and Wollan, "A New Proof of the Flat Wall Theorem" (arXiv:1207.6927) and "Quickly Excluding a Non-Planar Graph" (arXiv:2010.12397) provide major improvements over Robertson and Seymour's original proof of the structure theorem for finite graphs that exclude a given graph. The first paper redefines the notion of a fl

Jane Lange, Arsen Vasilyan

We give the first agnostic, efficient, proper learning algorithm for monotone Boolean functions. Given $2^{\tilde{O}(\sqrt{n}/\varepsilon)}$ uniformly random examples of an unknown function $f:\{\pm 1\}^n \rightarrow \{\pm 1\}$, our algorithm outputs a hypothesis $g:\{\pm 1\}^n \rightarrow \{\pm 1\}$ that is monotone and $(\mathrm{opt} + \varepsilon)$-close

Jennifer Rogers and, Anamaria Crisan

Automated Machine Learning (AutoML) technology can lower barriers in data work yet still requires human intervention to be functional. However, the complex and collaborative process resulting from humans and machines trading off work makes it difficult to trace what was done, by whom (or what), and when. In this research, we construct a taxonomy of data work

Hamish Innes, Shang-Min Tsai, Raymond T. Pierrehumbert

Hycean worlds are a proposed subset of sub-Neptune exoplanets with substantial water inventories, liquid surface oceans and extended hydrogen-dominated atmospheres that could be favourable for habitability. In this work, we aim to quantitatively define the inner edge of the Hycean habitable zone using a 1D radiative-convective model. As a limiting case, we m

Zehua Zeng, Hongwu Du

In recent years, single cell RNA sequencing has become a widely used technique to study cellular diversity and function. However, accurately annotating cell types from single cell data has been a challenging task, as it requires extensive knowledge of cell biology and gene function. The emergence of large language models such as ChatGPT and New Bing in 2023

Amartya Saha

The isomorphism between the (extended) BMS$_4$ algebra and the $1+2$D Carrollian conformal algebra hints towards a co-dimension one formalism of flat holography with the field theory residing on the null-boundary of the asymptotically flat space-time enjoying a $1+2$D Carrollian conformal symmetry. Motivated by this fact, we study the general symmetry proper

Zhangyi Cheng, Xiang Zhang, Lei Yu, Jianzhuang Liu

This paper aims at demystifying a single motion-blurred image with events and revealing temporally continuous scene dynamics encrypted behind motion blurs. To achieve this end, an Implicit Video Function (IVF) is learned to represent a single motion blurred image with concurrent events, enabling the latent sharp image restoration of arbitrary timestamps in t

Bernhard Heim, Markus Neuhauser, Robert Troeger

The zeros of D'Arcais polynomials, also known as Nekrasov--Okounkov polynomials, dictate the vanishing of the Fourier coefficients of powers of the Dedekind functions. These polynomials satisfy difference equations of hereditary type with non-constant coefficients. We relate the D'Arcais polynomials to polynomials satisying a Volterra difference equation of

Wenjie Qu, Youqi Li, Binghui Wang

Image segmentation is an important problem in many safety-critical applications. Recent studies show that modern image segmentation models are vulnerable to adversarial perturbations, while existing attack methods mainly follow the idea of attacking image classification models. We argue that image segmentation and classification have inherent differences, an

Shamak Dutta, Nils Wilde, Stephen L. Smith

We consider a general form of the sensor scheduling problem for state estimation of linear dynamical systems, which involves selecting sensors that minimize the trace of the Kalman filter error covariance (weighted by a positive semidefinite matrix) subject to polyhedral constraints on the selected sensors. This general form captures several well-studied pro

Pietropaolo Frisoni

We outline an algorithm to compute numerically the black-to-white hole transition amplitude, using the loop quantum gravity covariant formulation and the Lorentzian Engle-Pereira-Rovelli-Livine model. We apply the algorithm to calculate the crossing time of the transition in the deep quantum regime, comparing our result with previous analytical estimates of

David Alexandre, Hsueh-Ming Hang, Wen-Hsiao Peng

Typical video compression systems consist of two main modules: motion coding and residual coding. This general architecture is adopted by classical coding schemes (such as international standards H.265 and H.266) and deep learning-based coding schemes. We propose a novel B-frame coding architecture based on two-layer Conditional Augmented Normalization Flows

Chenyu You, Weicheng Dai, Yifei Min, Lawrence Staib

Medical data often exhibits long-tail distributions with heavy class imbalance, which naturally leads to difficulty in classifying the minority classes (i.e., boundary regions or rare objects). Recent work has significantly improved semi-supervised medical image segmentation in long-tailed scenarios by equipping them with unsupervised contrastive criteria. H

Martin Gubri, Maxime Cordy, Yves Le Traon

Transferability is the property of adversarial examples to be misclassified by other models than the surrogate model for which they were crafted. Previous research has shown that early stopping the training of the surrogate model substantially increases transferability. A common hypothesis to explain this is that deep neural networks (DNNs) first learn robus

Haimin Hu, Kensuke Nakamura, Kai-Chieh Hsu, Naomi Ehrich Leonard

We present a multi-agent decision-making framework for the emergent coordination of autonomous agents whose intents are initially undecided. Dynamic non-cooperative games have been used to encode multi-agent interaction, but ambiguity arising from factors such as goal preference or the presence of multiple equilibria may lead to coordination issues, ranging

Mariano Rodríguez-Arias Fernández, Javier Cabello Sánchez, Juan Antonio Fernández Torvisco

In this paper we present an algorithm to fit data via exponentials when the error is measured using the max-norm. We prove the necesssary results to show that the algorithm will converge to the best approximation no matter the dataset.

Giuseppe De Nittis, Danilo Polo

This work is concerned with the notion of {eigenstates} for $C^*$-algebras. After reviewing some basic and structural results, we explore the possibility of reinterpreting certain typical concepts of quantum mechanics (\eg dynamical equilibrium states, ground states, gapped states, Fermi surfaces) in terms of (algebraic) eigenstates.

Alex Lazarian, Siyao Xu, Yue Hu

Propagation of cosmic rays (CRs) in turbulent and magnetized astrophysical media is a long-standing problem that requires both understanding of the properties of turbulent magnetic fields and their interaction with energetic particles. This review focuses on selected recent theoretical findings made based on the progress in understanding and simulating magne

Lucy D'Agostino McGowan, Travis Gerke, Malcolm Barrett

This paper introduces a collection of four data sets, similar to Anscombe's Quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four data sets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the fourth involves