July 2023 arXiv papers — page 7

Mateusz Bocheński, Mariusz Semczuk

We report on reaching sub-Doppler temperatures of $^{40}$K in a single-chamber setup using a dispenser-based potassium source with natural (0.012$\%$ of $^{40}$K) isotopic composition. With gray molasses cooling on the $D_1$-line following a standard $D_2$-line magneto-optical trap, we obtain $3\times10^5$ atoms at $\sim$10~\textmu K. We reach densities high

S. M. Koksbang

Phenomenological models are widely used in cosmology in relation to constraining different cosmological models, with two common examples being cosmographic expansions and modeling the equation-of-state parameter of dark energy. This work presents a study of how using different phenomenological expressions for observables and physical quantities versus using

Hanbei Xie, Xiaodong Nong, Huifeng Wang, Bin Zhang

In this paper, we present a cosmology-independent method to constrain cosmological models from the latest 221 gamma-ray bursts (GRBs) sample, including 49 GRBs from Fermi catalog with the Amati relation (the $E_{\rm p}$-${E}_{\rm iso}$ correlation), which are calibrated by using a Gaussian process from the Pantheon+ type Ia supernovae (SNe Ia) sample. With 1

Jakub Liska, Mingxiang Gao, Lukas Jelinek, Erik R. Algarp

Performance limitations for implanted antennas, taking radiation efficiency as the metric, are presented. The performance limitations use a convex optimization procedure with the current density inside the implant acting as its degree of freedom. The knowledge of the limitations provides useful information in design procedure and physical insight. Ohmic loss

A. A. Zaitsev, N. Marimuthu, D. A. Artemenkov, P. I. Zarubin

The status of the study of multiple fragmentation of 950 MeV per nucleon Kr nuclei in a nuclear track emulsion aimed at determining the contributions of 2$\alpha$ decays of $^{8}$Be, the Hoyle 3$\alpha$ state, and the search for a 4$\alpha$ particle condensate state, is presented. In events with the production of few relativistic fragments of He and H, the p

Yu. M. Zinoviev

In this paper, using a frame-like gauge invariant formulation of the massive higher spin bosons and fermions, we develop a direct construction of the completely off-shell cubic vertices describing an interaction of the massless gravitino with the massive higher spin supermultiplets. To achieve the invariance under the local supersymmetry we introduce all nec

Saeid Naderiparizi, Xiaoxuan Liang, Setareh Cohan, Berend Zwartsenberg

Score-based diffusion models are a powerful class of generative models, widely utilized across diverse domains. Despite significant advancements in large-scale tasks such as text-to-image generation, their application to constrained domains has received considerably less attention. This work addresses model learning in a setting where, in addition to the tra

Ziao Wang, Yuhang Li, Junda Wu, Jaehyeon Soon

In this paper, we propose FinVis-GPT, a novel multimodal large language model (LLM) specifically designed for financial chart analysis. By leveraging the power of LLMs and incorporating instruction tuning and multimodal capabilities, FinVis-GPT is capable of interpreting financial charts and providing valuable analysis. To train FinVis-GPT, a financial task

Aitik Gupta, Joydip Dhar

Medical image segmentation is vital to the area of medical imaging because it enables professionals to more accurately examine and understand the information offered by different imaging modalities. The technique of splitting a medical image into various segments or regions of interest is known as medical image segmentation. The segmented images that are pro

Tatsuru Takakura, Yuichiro Yamazaki

In this paper, we consider the cohomology rings of some multiple weight varieties of type A, that is, symplectic torus quotients for a direct product of several coadjoint orbits of the special unitary group. Under some specific assumptions, we prove the symplectic volumes of multiple weight varieties are equal to the volumes of flow polytopes. Using differen

Kui Du, Jia-Jun Fan, Xiao-Hui Sun, Fang Wang

Krylov subspace methods for solving linear systems of equations involving skew-symmetric matrices have gained recent attention. Numerical equivalences among Krylov subspace methods for nonsingular skew-symmetric linear systems have been given in Greif et al. [SIAM J. Matrix Anal. Appl., 37 (2016), pp. 1071--1087]. In this work, we extend the results of Greif

A. Fronzetti Colladon, B. Guardabascio, F. Venturini

How does technological interdependence affect innovation? We address this question by examining the influence of neighbors' innovativeness and the structure of the innovators' network on a sector's capacity to develop new technologies. We study these two dimensions of technological interdependence by applying novel methods of text mining and network analysis

Kaushik Roy, Peyman Moghadam, Mehrtash Harandi

The performance of a lifelong learning (L3) model degrades when it is trained on a series of tasks, as the geometrical formation of the embedding space changes while learning novel concepts sequentially. The majority of existing L3 approaches operate on a fixed-curvature (e.g., zero-curvature Euclidean) space that is not necessarily suitable for modeling the

A. Savaş Arapoğlu, A. Emrah Yükselci

We examine the anisotropy originated from a first-order vacuum phase transitions through three-dimensional numerical simulations. We apply Bianchi Type-I metric to our model that has one scalar field minimally coupled to the gravity. We calculate the time evolution of the energy density for the shear scalar and the directional Hubble parameters as well as th

Huachuan Qiu, Tong Zhao, Anqi Li, Shuai Zhang

Dialogue safety remains a pervasive challenge in open-domain human-machine interaction. Existing approaches propose distinctive dialogue safety taxonomies and datasets for detecting explicitly harmful responses. However, these taxonomies may not be suitable for analyzing response safety in mental health support. In real-world interactions, a model response d

Andrea Santilli, Emanuele Rodolà

In recent years Large Language Models (LLMs) have increased the state of the art on several natural language processing tasks. However, their accessibility is often limited to paid API services, posing challenges for researchers in conducting extensive investigations. On the other hand, while some open-source models have been proposed by the community, they

Joydev Lahiri, D. N. Basu

The stellar configurations of quark stars are studied using perturbative QCD (pQCD) for the equation of state (EoS). The neutron star structures with equation of state obtained from Brussels-Montreal extended Skyrme interaction are also explored. The deconfinement phase transition from quark to hadron phase in stellar interior for matter under extreme pressu

Yohei Wakamaki

We provide the first explicit example of a cork of $\mathbf{CP}^2 \# 8\overline{\mathbf{CP}^2}$. This result gives the current smallest second Betti number of a standard simply-connected closed $4$-manifold for which an explicit cork has been found.

Ziao Wang, Jianning Wang, Junda Wu, Xiaofeng Zhang

At the beginning era of large language model, it is quite critical to generate a high-quality financial dataset to fine-tune a large language model for financial related tasks. Thus, this paper presents a carefully designed data creation pipeline for this purpose. Particularly, we initiate a dialogue between an AI investor and financial expert using ChatGPT

B. Prabadevi, N. Deepa, Nancy Victor, Thippa Reddy Gadekallu

With the advent of new technologies and endeavors for automation in almost all day-to-day activities, the recent discussions on the metaverse life have a greater expectation. Furthermore, we are in the era of the fifth industrial revolution, where machines and humans collaborate to maximize productivity with the effective utilization of human intelligence an

Guodong Ding, Fadime Sener, Shugao Ma, Angela Yao

One promising use case of AI assistants is to help with complex procedures like cooking, home repair, and assembly tasks. Can we teach the assistant to interject after the user makes a mistake? This paper targets the problem of identifying ordering mistakes in assembly procedures. We propose a system that can detect ordering mistakes by utilizing a learned k

Mihir Dhanakshirur, Felix Laumann, Junhyung Park, Mauricio Barahona

Understanding and adequately assessing the difference between a true and a learnt causal graphs is crucial for causal inference under interventions. As an extension to the graph-based structural Hamming distance and structural intervention distance, we propose a novel continuous-measured metric that considers the underlying data in addition to the graph stru

Ping Miao, Xianghong Jin, Weiliang Yao, Yue Chen

In the quest to find quantum spin liquids, layered cobalt oxides Na2Co2TeO6 and Na3Co2SbO6 have been proposed as promising candidates for approximating the Kitaev honeycomb model. Yet, their suitability has been thrown into question due to observed long-range magnetic order at low temperatures and indications of easy-plane, rather than Kitaev-type, spin anis

Erik Zimmermann, Michael Schleenvoigt, Alina Rupp, Gerrit Behner

We present a symmetrization routine that optimizes and eases the analysis of data featuring the anomalous Hall effect. This technique can be transferred to any hysteresis with (point-)symmetric behaviour. The implementation of the method is demonstrated exemplarily using intermixed longitudinal and transversal data obtained from a chromium-doped ternary topo

Enxin Song, Wenhao Chai, Guanhong Wang, Yucheng Zhang

Recently, integrating video foundation models and large language models to build a video understanding system can overcome the limitations of specific pre-defined vision tasks. Yet, existing systems can only handle videos with very few frames. For long videos, the computation complexity, memory cost, and long-term temporal connection impose additional challe

M. Bras-Amorós

We introduce a new class of numerical semigroups, which we call the class of {\it acute} semigroups and we prove that they generalize symmetric and pseudo-symmetric numerical semigroups, Arf numerical semigroups and the semigroups generated by an interval. For a numerical semigroup $\Lambda=\{\lambda_0<\lambda_1<\dots\}$ denote $\nu_i=\#\{j\mid\lambda_i-\lam

SM Zobaed, Mohsen Amini Salehi

Confidential computing has gained prominence due to the escalating volume of data-driven applications (e.g., machine learning and big data) and the acute desire for secure processing of sensitive data, particularly, across distributed environments, such as edge-to-cloud continuum. Provided that the works accomplished in this emerging area are scattered acros

Krishan Kumar Tiwari, Giuseppe Caire

We present numerical results with a focus on power transfer between two standard linear antenna arrays placed in the near field, where a much smaller active multi-antenna feeder (AMAF) space feeds a far larger passive array referred to as a reflective intelligent surface (RIS). The interest is in the regime of focal length to diameter ratio ($F/D$) less than

Junsoo Kim

Homomorphic encryption (HE) applied to a networked controller enables secure operation, but in most cases it allows for addition and multiplication over integers only, because of computation efficiency. Several related results deal with such constraints by means of re-encrypted controller output, based on which the controller can be re-constructed and operat

Tobias K. S. Ritschel, Asbjørn Thode Reenberg, Peter Emil Carstensen, Jacob Bendsen

We present and critically discuss five commonly used mathematical models of the meal glucose rate of appearance in humans. Such models are key to simulation of the metabolism in healthy people, people with diabetes, and obese people, and they are central to developing effective treatments and prevention strategies. Furthermore, we discuss important aspects o

Feng Huang, Hanshuang Chen

We investigate the extreme value statistics of a one-dimensional Brownian motion (with the diffusion constant $D$) during a time interval $\left[0, t \right]$ in the presence of a reflective boundary at the origin, starting from a positive position $x_0$. By deriving the survival probability of the Brownian particle without hitting an absorbing boundary at $

Tufan Roy, Masahito Tsujikawa, Masafumi Shirai

We investigate the suitability of nearly half-metallic ferrimagnetic quaternary Heusler alloys, CoCrMnZ (Z=Al, Ga, Si, Ge) to assess the feasibility as electrode materials of MgO-based magnetic tunnel junctions (MTJ). Low magnetic moments of these alloys originated from the anti-ferromagnetic coupling between Mn and Cr spins ensure a negligible stray field i

Elia Peruzzo, Willi Menapace, Vidit Goel, Federica Arrigoni

In the last few years, Neural Painting (NP) techniques became capable of producing extremely realistic artworks. This paper advances the state of the art in this emerging research domain by proposing the first approach for Interactive NP. Considering a setting where a user looks at a scene and tries to reproduce it on a painting, our objective is to develop

Mingliang Bai, Zhihao Zhou, Ruidong Wang, Yusheng Yang

Renewable energy is important for achieving carbon neutrality goal. With the great success of Large Language Models (LLMs) like ChatGPT in automatic content generation, LLMs are playing an increasingly important role. However, there has not been a specially designed LLM for renewable energy. Meanwhile, there has not been any dataset of renewable energy for t

Bowen Zheng, Chenxi Huang, Yuemei Luo

Three-dimensional (3D) reconstruction of head Computed Tomography (CT) images elucidates the intricate spatial relationships of tissue structures, thereby assisting in accurate diagnosis. Nonetheless, securing an optimal head CT scan without deviation is challenging in clinical settings, owing to poor positioning by technicians, patient's physical constraint

Xiaoshang Jin

In this article, we investigate the rate at which the first Dirichlet eigenvalue of geodesic balls decreases as the radius approaches infinity. We prove that if the conformal infinity of an asymptotically hyperbolic Einstein manifold is of nonnegative Yamabe type, then the two-term asymptotic of the eigenvalues is the same as that in hyperbolic space.

Huchen Shu, Wei Zhong, Jiajia Feng, Hongyang Zhao

Generally, the superconductivity was expected to be absent in magnetic systems, but this reception was disturbed by unconventional superconductors, such as cuprates, iron-based superconductors and recently discovered nickelate, since their superconductivity is proposed to be related to the electron-electron interaction mediated by the spin fluctuation. Howev

Meng-Fei Sun, Jin Li, Shuo Cao, Xiaolin Liu

Validating the accelerating expansion of the universe is an important issue for understanding the evolution of the universe. By constraining the cosmic acceleration parameter $X_H$, we can discriminate between the $\Lambda \mathrm{CDM}$ (cosmological constant plus cold dark matter) model and LTB (the Lema\^itre-Tolman-Bondi) model. In this paper, we explore

Nana Mgbechikwere Nwachukwu, Jennafer Shae Roberts, Laura N Montoya

To harness the true potential of Artificial Intelligence (AI) for societal betterment, we need to move away from prioritising corporate interests which exploit Global South workers in the digital age. The unpaid labour and societal harms which are generated by Digital Value Networks (DVNs) disproportionately affect workers in Africa, Latin America, and India

Clarissa Astuto, Jan Haskovec, Peter Markowich, Simone Portaro

We study self-regulating processes modeling biological transportation networks as presented in \cite{portaro2023}. In particular, we focus on the 1D setting for Dirichlet and Neumann boundary conditions. We prove an existence and uniqueness result under the assumption of positivity of the diffusivity $D$. We explore systematically various scenarios and gain

Wan-Qing Zhu, Wen-Yu Shan

Control and detection of antiferromagnetic topological materials are challenging since the total magnetization vanishes. Here we investigate the magneto-optical Kerr and Faraday effects in bilayer antiferromagnetic insulator MnBi$_2$Te$_4$. We find that by breaking the combined mirror symmetries with either perpendicular electric field or external magnetic m

Vikas Buchemmavari, Sivaprasad Omanakuttan, Yuan-Yu Jau, Ivan Deutsch

The Rydberg dipole-blockade has emerged as the standard mechanism to induce entanglement between neutral atom qubits. In these protocols, laser fields that couple qubit states to Rydberg states are modulated to implement entangling gates. Here we present an alternative protocol to implement entangling gates via Rydberg dressing and a microwave-field-driven s

Bartłomiej Olber, Krystian Radlak, Krystian Chachuła, Jakub Łyskawa

Object detection is essential to many perception algorithms used in modern robotics applications. Unfortunately, the existing models share a tendency to assign high confidence scores for out-of-distribution (OOD) samples. Although OOD detection has been extensively studied in recent years by the computer vision (CV) community, most proposed solutions apply o

David Kim

The soon-to-be-realized, global network of neutrino telescopes will allow new opportunities for collaboration between detectors. While each detector is distinct, they share the same underlying physical processes and detection principles. The full simulation chain for these telescopes is typically proprietary which limits the opportunity for joint studies. Th

Pooja Chandravanshi, Jaya Krishna Meka, Vardaan Mongia, Ravindra P. Singh

Linear-feedback shift register (LFSR) based pseudo-random number generator (PRNG) has applications in a plethora of fields. The issue of being linear is generally circumvented by introducing non-linearities as per the required applications, with some being adhoc but fulfilling the purpose while others with a theoretical proof. The goal of this study is to de

Jungil Kong, Jihoon Park, Beomjeong Kim, Jeongmin Kim

Single-stage text-to-speech models have been actively studied recently, and their results have outperformed two-stage pipeline systems. Although the previous single-stage model has made great progress, there is room for improvement in terms of its intermittent unnaturalness, computational efficiency, and strong dependence on phoneme conversion. In this work,

Aningi Mokhalingam, Indranil S Dalal, Shakti S Gupta

This work investigates the mechanical response of single-walled carbon nanotubes (SWCNTs) coupled through van der Waals and electrostatic forces using molecular dynamic (MD) simulations and a continuum model. In MD simulations, the covalent bond interactions between the carbon atoms are modeled using ReaxFF potential. The dynamic charges, dependent on the lo

Miao Chen, Ping Li, Avy Soffer, Xiaohua Yao

This paper is devoted to studying time decay estimates of the solution for Beam equation (higher order type wave equation) with a potential $$u_{t t}+\big(\Delta^2+V\big)u=0, \,\ u(0, x)=f(x),\ u_{t}(0, x)=g(x)$$ in dimension three, where $V$ is a real-valued and decaying potential on $\R^3$. Assume that zero is a regular point of $H:= \Delta^2+V $, we first

Satyam Kumar, Yelleti Vivek, Vadlamani Ravi, Indranil Bose

Causal Inference plays an significant role in explaining the decisions taken by statistical models and artificial intelligence models. Of late, this field started attracting the attention of researchers and practitioners alike. This paper presents a comprehensive survey of 37 papers published during 1992-2023 and concerning the application of causal inferenc

Jiaqi Tang, Xiaogang Xu, Sixing Hu, Ying-Cong Chen

Due to limited camera capacities, digital images usually have a narrower dynamic illumination range than real-world scene radiance. To resolve this problem, High Dynamic Range (HDR) reconstruction is proposed to recover the dynamic range to better represent real-world scenes. However, due to different physical imaging parameters, the tone-mapping functions b

Taejun Kim, Juhan Nam

Music is characterized by complex hierarchical structures. Developing a comprehensive model to capture these structures has been a significant challenge in the field of Music Information Retrieval (MIR). Prior research has mainly focused on addressing individual tasks for specific hierarchical levels, rather than providing a unified approach. In this paper,

Baoquan Zhang, Chuyao Luo, Demin Yu, Huiwei Lin

Equipping a deep model the abaility of few-shot learning, i.e., learning quickly from only few examples, is a core challenge for artificial intelligence. Gradient-based meta-learning approaches effectively address the challenge by learning how to learn novel tasks. Its key idea is learning a deep model in a bi-level optimization manner, where the outer-loop

Sourav Chowdhury, Suparna Roychowdhury, Indranath Chaudhuri

Currently, the world has been facing the brunt of a pandemic due to a disease called COVID-19 for the last 2 years. To study the spread of such infectious diseases it is important to not only understand their temporal evolution but also the spatial evolution. In this work, the spread of this disease has been studied with a cellular automata (CA) model to fin

Elen Vardanyan, Sona Hunanyan, Tigran Galstyan, Arshak Minasyan

This paper explores the problem of generative modeling, aiming to simulate diverse examples from an unknown distribution based on observed examples. While recent studies have focused on quantifying the statistical precision of popular algorithms, there is a lack of mathematical evaluation regarding the non-replication of observed examples and the creativity

Nabarun Deb, Young-Heon Kim, Soumik Pal, Geoffrey Schiebinger

We prove that the sequence of marginals obtained from the iterations of the Sinkhorn algorithm or the iterative proportional fitting procedure (IPFP) on joint densities, converges to an absolutely continuous curve on the $2$-Wasserstein space, as the regularization parameter $\varepsilon$ goes to zero and the number of iterations is scaled as $1/\varepsilon$

Zeyu Zhang, Lexing Zhang, Zaijin Wang, Ziyuan Jiao

Existing methods for reconstructing interactive scenes primarily focus on replacing reconstructed objects with CAD models retrieved from a limited database, resulting in significant discrepancies between the reconstructed and observed scenes. To address this issue, our work introduces a part-level reconstruction approach that reassembles objects using primit

Vu Ngoc Tu, Van Thong Huynh, Hyung-Jeong Yang, M. Zaigham Zaheer

Conversational engagement estimation is posed as a regression problem, entailing the identification of the favorable attention and involvement of the participants in the conversation. This task arises as a crucial pursuit to gain insights into human's interaction dynamics and behavior patterns within a conversation. In this research, we introduce a dilated c

Kaushik Roy, Christian Simon, Peyman Moghadam, Mehrtash Harandi

An ultimate objective in continual learning is to preserve knowledge learned in preceding tasks while learning new tasks. To mitigate forgetting prior knowledge, we propose a novel knowledge distillation technique that takes into the account the manifold structure of the latent/output space of a neural network in learning novel tasks. To achieve this, we pro

Xiaoxiao Hu, Qichao Ying, Zhenxing Qian, Sheng Li

RAW files are the initial measurement of scene radiance widely used in most cameras, and the ubiquitously-used RGB images are converted from RAW data through Image Signal Processing (ISP) pipelines. Nowadays, digital images are risky of being nefariously manipulated. Inspired by the fact that innate immunity is the first line of body defense, we propose DRAW

Sourav Chowdhury, Suparna Roychowdhury, Indranath Chaudhuri

Diabetes mellitus is a disease which is currently a huge health hazard globally. The cases of diabetes had increased by a significant amount in past decades. Also it has been predicted that it will further increase in future. Diabetes depends on various factors like obesity, physical inactivity. Also diabetes can depend on various environmental issues. In th

Yapeng Su, Tong Zhao, Zicheng Zhang

Deep learning has achieved remarkable results in fingerprint embedding, which plays a critical role in modern Automated Fingerprint Identification Systems. However, previous works including CNN-based and Transformer-based approaches fail to exploit the nonstructural data, such as topology and correlation in fingerprints, which is essential to facilitate the

Xiaojun Tang, Junsong Fan, Chuanchen Luo, Zhaoxiang Zhang

Weakly-supervised temporal action localization (WTAL) is a practical yet challenging task. Due to large-scale datasets, most existing methods use a network pretrained in other datasets to extract features, which are not suitable enough for WTAL. To address this problem, researchers design several modules for feature enhancement, which improve the performance

John Bailie, Bernd Krauskopf

The Atlantic Meridional Overturning Circulation (AMOC) distributes heat and salt into the Northern Hemisphere via a warm surface current toward the subpolar North Atlantic, where water sinks and returns southwards as a deep cold current. There is substantial evidence that the AMOC has slowed down over the last century. We introduce a conceptual box model for

Hari. K, Dawood Kothawala

We analyse several aspects of detectors with uniform acceleration $a$ and uniform rotation $\Omega$ in de Sitter ($\Lambda>0$) and anti-de Sitter ($\Lambda<0$) spacetimes, focusing particularly on the periodicity, in (Euclidean) proper time $\tau_{\rm traj}$, of geodesic interval $\tau_{\rm geod}$ between two events on the trajectory. For $\Lambda<0$, $\tau_

Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël C. -W. Phan

With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO networks is scarcely investigated in brain tumor detection. We propose a novel YOLO architecture with Reparameterized Convolution based on channel Shuffle (RCS-YOLO).

Shubham Sharma, Harleen Dahiya

The higher twist T-even transverse momentum dependent distribution (TMD) $h_3(x, {\bf p_\perp^2})$ for the proton has been examined in the light-front quark-diquark model (LFQDM). By deciphering the unintegrated quark-quark correlator for semi-inclusive deep inelastic scattering (SIDIS), we have derived explicit equations of the TMD for both the scenarios wh

Minyi Zhao, Yi Xu, Bingjia Li, Jie Wang

Scene text image super-resolution (STISR) is an important pre-processing technique for text recognition from low-resolution scene images. Nowadays, various methods have been proposed to extract text-specific information from high-resolution (HR) images to supervise STISR model training. However, due to uncontrollable factors (e.g. shooting equipment, focus,

Anju Panthi, Annapurni Subramaniam, Kaushar Vaidya, Vikrant Jadhav

Blue metal-poor stars are main-sequence stars that are bluer and brighter than typical turn-off stars in metal-poor globular clusters. They are thought to have either evolved through post-mass transfer mechanisms as field blue straggler stars or have accreted from Milky Way dwarf satellite galaxies. It has been found that a considerable fraction of blue meta

Dirk Hennig, Nikos I. Karachalios, Dionyssios Mantzavinos, Jesus Cuevas-Maraver

The question of whether features and behaviors that are characteristic to completely integrable systems persist in the transition to non-integrable settings is a central one in the field of nonlinear dispersive equations. In this work, we investigate this topic in the context of focusing nonlinear Schr\"odinger (NLS) equations. In particular, we consider non

S R Siva Prasad Kochi, M Ramakrishna

An analytical solution for high supersonic flow over a circular cylinder based on Schneider's inverse method has been presented. In the inverse method, a shock shape is assumed and the corresponding flow field and the shape of the body producing the shock are found by integrating the equations of motion using the stream function. A shock shape theorised by M

Hossein Akhlaghpasand, Vahid Shah-Mansouri

In this paper, we consider traffic offloading of integrated low earth orbit (LEO) satellite-terrestrial network. We first derive traffic offloading probability from the terrestrial network to the LEO satellite network based on the instantaneous radio signal strength. Then to overcome limited coverage and also traffic congestion of the terrestrial network, we

Hang Shen, Chaoying Zhaoa

The Kerr microcomb has a huge potential advantage as a quantum computing platform because of its large-scale and globally coherent optical modes. The micro-comb has always faced a primary problem is how to increase the controllability of frequency domain modes. In this work, based on the pump thresholds of different side modes, we establish a set of method f

Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey

Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe $\textit{causal-learn}$, an open-source Python library for causal discovery. This library focuses on bringing a comprehensive collection of causal discovery methods to both practitioners and researchers. It provides

Hiroto Arima, Yoshikazu Mizuguchi

Ongoing research explores thermal switching materials to control heat flow. Specifically, there has been interest in magneto-thermal switching (MTS) materials based on superconductors, which only exhibited switching behavior when a magnetic field was applied. However, a recent report highlighted nonvolatile MTS in commercial Sn-Pb solders, attributed to magn

Xiao Chen, James N. Fry, H. P. Cheng

Carbon nanoribbon or nanographene qubit arrays can facilitate quantum-to-quantum transduction between light, charge, and spin, making them an excellent testbed for fundamental science in quantum coherent systems and for the construction of higher-level qubit circuits. In this work, we study spin decoherence due to coupling with a surrounding nuclear spin bat

Kapil Kumar, N. K. Karn, V. P. S. Awana

The quest for room-temperature superconductors has been teasing scientists and physicists, since its inception in 1911 itself. Several assertions have already been made about room temperature superconductivity but were never verified or reproduced across the labs. The cuprates were the earliest high transition temperature superconductors, and it seems that c

Qian Zhao, Ting Sun, Kun Xue, Feng Wan

Cascaded Compton scattering and Breit-Wheeler (BW) processes play fundamental roles in high-energy astrophysical sources and laser-driven quantum electrodynamics (QED) plasmas. A thorough comprehension of the polarization transfer in these cascaded processes is essential for elucidating the polarization mechanism of high-energy cosmic gamma rays and laser-dr

Haiyue Song, Raj Dabre, Chenhui Chu, Sadao Kurohashi

Sub-word segmentation is an essential pre-processing step for Neural Machine Translation (NMT). Existing work has shown that neural sub-word segmenters are better than Byte-Pair Encoding (BPE), however, they are inefficient as they require parallel corpora, days to train and hours to decode. This paper introduces SelfSeg, a self-supervised neural sub-word se

Christian Aebi, Grant Cairns

We show that there are only two equable triangles having vertices on the Eisenstein lattice, up to Euclidean motions.

Dingyi Yang, Hongyu Chen, Xinglin Hou, Tiezheng Ge

Stylized visual captioning aims to generate image or video descriptions with specific styles, making them more attractive and emotionally appropriate. One major challenge with this task is the lack of paired stylized captions for visual content, so most existing works focus on unsupervised methods that do not rely on parallel datasets. However, these approac

Rimita Lahiri, Tiantian Feng, Rajat Hebbar, Catherine Lord

We address the problem of detecting who spoke when in child-inclusive spoken interactions i.e., automatic child-adult speaker classification. Interactions involving children are richly heterogeneous due to developmental differences. The presence of neurodiversity e.g., due to Autism, contributes additional variability. We investigate the impact of additional

Jason F. Herrmann, Devin J. Dean, Christopher J. Sarabalis, Vahid Ansari

In situ tunable photonic filters and memories are important for emerging quantum and classical optics technologies. However, most photonic devices have fixed resonances and bandwidths determined at the time of fabrication. Here we present an in situ tunable optical resonator on thin-film lithium niobate. By leveraging the linear electro-optic effect, we demo

Vidya Setlur, Andriy Kanyuka, Arjun Srinivasan

Search and information retrieval systems are becoming more expressive in interpreting user queries beyond the traditional weighted bag-of-words model of document retrieval. For example, searching for a flight status or a game score returns a dynamically generated response along with supporting, pre-authored documents contextually relevant to the query. In th

Kousik Rajesh, Mrigank Raman, Mohammed Asad Karim, Pranit Chawla

In recent times there has been a surge of multi-modal architectures based on Large Language Models, which leverage the zero shot generation capabilities of LLMs and project image embeddings into the text space and then use the auto-regressive capacity to solve tasks such as VQA, captioning, and image retrieval. We name these architectures as "bridge-architec

Haochen Shi, Xinyao Liu, Fengmao Lv, Hongtao Xue

In the era of big data, the issue of data quality has become increasingly prominent. One of the main challenges is the problem of duplicate data, which can arise from repeated entry or the merging of multiple data sources. These "dirty data" problems can significantly limit the effective application of big data. To address the issue of data deduplication, we

Kengo Aoki

A 2-distance $k$-coloring of a graph $G$ is a proper $k$-coloring such that any two vertices at distance two or less get different colors. The 2-distance chromatic number of $G$ is the minimum $k$ such that $G$ has a 2-distance $k$-coloring, denote as $\chi_2(G)$. In this paper, we show that $\chi_2(G) \leq 17$ for every planar graph $G$ with maximum degree

Samira Zare, Alex Spaeth, Sandya Suresh, and Mircea Teodorescu

Origami structures have been widely explored in robotics due to their many potential advantages. Origami robots can be very compact, as well as cheap and efficient to produce. In particular, they can be constructed in a flat format using modern manufacturing techniques. Rotational motion is essential for robotics, and a variety of origami rotational joints h

Xiao Li, Xiucui Guan, Qiao Zhang, Xinyi Yin

A network for the transportation of supplies can be described as a rooted tree with a weight of a degree of congestion for each edge. We take the sum of root-leaf distance (SRD) on a rooted tree as the whole degree of congestion of the tree. Hence, we consider the SRD interdiction problem on trees with cardinality constraint by upgrading edges (denoted by (S

Jerry Bona, Angel Duran, Dimitrios Mitsotakis

Considered here are two systems of equations modeling the two-way propagation of long-crested, long-wavelength internal waves along the interface of a two-layer system of fluids in the Benjamin-Ono and the Intermediate Long-Wave regime, respectively. These systems were previously shown to have solitary-wave solutions, decaying to zero algebraically for the B

Yi C. Huang, Fei Xue

In this paper we present a complete proof of a conjecture due to V. V. Prelov in 2010 about an information inequality for the binary entropy function.

Yuanhao Gong

Activation functions play an essential role in neural networks. They provide the non-linearity for the networks. Therefore, their properties are important for neural networks' accuracy and running performance. In this paper, we present a novel signed and truncated logarithm function as activation function. The proposed activation function has significantly b

Bojko Bakalov, Ju Wang

For any cocommutative Hopf algebra $H$ and a left $H$-module $V$, we construct an operad $\mathcal{P}^{cl}_H(V)$, which in the special case when $H$ is the algebra of polynomials in one variable reduces to the classical operad $\mathcal{P}^{cl}(V)$. Morphisms from the Lie operad to $\mathcal{P}^{cl}(V)$ correspond to Poisson vertex algebra structures on $V$.

Siyu Tong, Xiaoxue Yu, Rongpeng Li, Kun Lu

Semantic communication (SemCom) demonstrates strong superiority over conventional bit-level accurate transmission, by only attempting to recover the essential semantic information of data. In this paper, in order to tackle the non-differentiability of channels, we propose an alternate learning based SemCom system for visual transmission, named SparseSBC. Spe

Jia Li, Xiang Li

The traditional i.i.d.-based learning paradigm faces inherent challenges in addressing causal relationships, which has become increasingly evident with the rise of applications in causal representation learning. Our understanding of causality naturally requires a perspective as the creator rather than observer, as the ``what...if'' questions only hold within

Ying Liao, Santiago Coelho, Jenny Chen, Benjamin Ades-Aron

Diffusion magnetic resonance imaging offers unique in vivo sensitivity to tissue microstructure in brain white matter, which undergoes significant changes during development and is compromised in virtually every neurological disorder. Yet, the challenge is to develop biomarkers that are specific to micrometer-scale cellular features in a human MRI scan of a

Arun Niddish Mahendran, Caitlin Freeman, Alexander H. Chang, Michael McDougall

The adaptability of soft robots makes them ideal candidates to maneuver through unstructured environments. However, locomotion challenges arise due to complexities in modeling the body mechanics, actuation, and robot-environment dynamics. These factors contribute to the gap between their potential and actual autonomous field deployment. A closed-loop path pl

Qiang Gao, Jin Mo Bok, Ping Ai, Jing Liu

Superconductivity is realized by opening a gap in the superconducting state. The gap symmetry is crucial in understanding the underlying superconductivity mechanism. The magnitude and the phase are essential in fully characterizing the superconducting gap. Angle-resolved photoemission spectroscopy (ARPES) has played a key role in determining the gap symmetry

Swarnadeep Seth, Brandon Stine, Aniket Bhattacharya

We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained (CG) bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional screened Coulomb interaction for the charged amino acid beads. Our simulation studies of two different hydropathy scales (HPS1,

Albert Yu Sun, Eliott Zemour, Arushi Saxena, Udith Vaidyanathan

Machine learning practitioners often fine-tune generative pre-trained models like GPT-3 to improve model performance at specific tasks. Previous works, however, suggest that fine-tuned machine learning models memorize and emit sensitive information from the original fine-tuning dataset. Companies such as OpenAI offer fine-tuning services for their models, bu

Talat Nazir, Sergei Silvestrov

The existence and uniqueness of the common fixed point for generalized contractive mappings in order partial metric spaces is investigated. The existence of nonnegative solution of implicit nonlinear integral equations is also studied. Some examples demonstrating the validity of our main results are constructed. The presented results extend and unify various