May 2022 arXiv papers — page 57

Andri Darmawan, Edi Suprayoga, Ahmad R. T. Nugraha, Abdullah A. AlShaikhi

We investigate thermoelectric (TE) properties of two-dimensional materials possessing two Dirac bands (a Dirac band) and a nonlinear band within the three-(two-)band model using linearized Boltzmann transport theory and relaxation time approximation. In the three-band model, we find that combinations of Dirac bands with a heavy nonlinear band, either a parab

Antonino Miceli, Kazutomo Yoshii, Ian T. Foster

In order to take full advantage of the U.S. Department of Energy's billion-dollar investments into the next-generation research infrastructure (e.g., exascale, light sources, colliders), advances are required not only in detector technology but also in computing and specifically AI. Let us consider an example from X-ray science. Nanoscale X-ray imaging is a

Matthew Dawes

We exhibit algorithms for calculating Tits' buildings and orbits of vectors in a lattice $L$ for certain subgroups of $\operatorname{O}(L)$. We discuss how these algorithms can be applied to understand the configuration of boundary components in the Baily-Borel compactification of orthogonal modular varieties and to improve the performance of computer arithm

Yu-ki Suzuki, Seiji Terashima

We consider a perturbation of the Einstein gravity with the Neumann boundary condition, which is regarded as an end of the world brane (ETW brane) of the AdS/BCFT correspondence, in the AdSd+1 spaectime where d is larger than 2. We obtain the mode expansion of the perturbations explicitly for the tensionless ETW brane case. We also show that the energy-momen

Yang Li, Gonzalo Mateos

As the most popular sport around the globe, the game of football has recently intrigued much research interest to explore and distill useful and appealing information from the sport. Network science and graph-centric methods have been previously applied to study the importance of football players and teams. In this paper, for the first time we study the macr

P. Mark Kayll, Craig E. Larson

We leverage an algorithm of Deming [R.W. Deming, Independence numbers of graphs -- an extension of the Koenig-Egervary theorem, Discrete Math., 27(1979), no. 1, 23--33; MR534950] to decompose a matchable graph into subgraphs with a precise structure: they are either spanning even subdivisions of blossom pairs, spanning even subdivisions of the complete graph

M. T. Rushton, C. C. Popescu, C. Inman, G. Natale

We present an axi-symmetric model for the ultraviolet (UV)-to-submillimetre (submm) images of the nearly face-on spiral galaxy NGC 628. It was calculated using a radiative transfer (RT) code, accounting for the absorption and re-emission of starlight by dust in the interstellar medium of this galaxy. The code incorporates emission from Polycyclic Aromatic Hy

Ji Liu, Peiyi Li, Huiyang Zhou

Despite rapid advances in quantum computing technologies, the qubit connectivity limitation remains to be a critical challenge. Both near-term NISQ quantum computers and relatively long-term scalable quantum architectures do not offer full connectivity. As a result, quantum circuits may not be directly executed on quantum hardware, and a quantum compiler nee

Dong Wei, Ying Sun, Ping Chai, Adrian Low

Automatic segmentation of myocardium in Late Gadolinium Enhanced (LGE) Cardiac MR (CMR) images is often difficult due to the intensity heterogeneity resulting from accumulation of contrast agent in infarcted areas. In this paper, we propose an automatic segmentation framework that fully utilizes shared information between corresponding cine and LGE images of

Matias von Bell, Martha Yip

The polytopes $\mathcal{U}_{I,\bar{J}}$ were introduced by Ceballos, Padrol, and Sarmiento to provide a geometric approach to the study of $(I,\bar{J})$-Tamari lattices. They observed a connection between certain $\mathcal{U}_{I,\bar{J}}$ and acyclic root polytopes, and wondered if M\'esz\'aros' subdivision algebra can be used to subdivide all $\mathcal{U}_{

Kaijian Li, Shansan Gong, Kenny Q. Zhu

Natural Language Inference Generation task is to generate a text hypothesis given a text premise and a logical relation between the two. This task can be used in data augmentation and controllable text generation in practice. In this paper, we propose language models with prompt and dynamic demonstration (LM-PDD) to tackle this problem in few-shot settings.

Gabriel Machado, Keiller Nogueira, Matheus Barros Pereira, Jefersson Alex dos Santos

In some scenarios, a single input image may not be enough to allow the object classification. In those cases, it is crucial to explore the complementary information extracted from images presenting the same object from multiple perspectives (or views) in order to enhance the general scene understanding and, consequently, increase the performance. However, th

Davide Giambastiani, Cosimo Tommasi, Federica Bianco, Filippo Fabbri

The electronic and optical properties of graphene can be precisely tuned by generating deterministic arrangements of strain features. In this paper, we report the formation of widespread and controlled buckling delamination of monolayer graphene deposited on hexagonal boron-nitride promoted by a significant squeezing of the graphene flake and induced by poly

Levent Aksoy, Debapriya Basu Roy, Malik Imran, Patrick Karl

This brief addresses the problem of implementing very large constant multiplications by a single variable under the shift-adds architecture using a minimum number of adders/subtractors. Due to the intrinsic complexity of the problem, we introduce an approximate algorithm, called T\~OLL, which partitions the very large constants into smaller ones. To reduce t

Murilo H. Oliveira, Gerard Higgins, Chi Zhang, Ana Predojević

We propose a scheme to dissipatively produce steady-state entanglement in a two-qubit system, via an interaction with a bosonic mode. The system is driven into a stationary entangled state, while we compensate the mode dissipation by injecting energy via a coherent pump field. We also present a scheme which allows us to adiabatically transfer all the populat

Alex Nguyen, Golrokh Akhgar, David L. Cortie, Abdulhakim Bake

The surface area of Bi2Te3 thin films was increased by introducing nanoscale porosity. Temperature dependent resistivity and magnetotransport measurements were conducted both on as-grown and porous samples (23 and 70 nm). The longitudinal resistivity of the porous samples became more metallic, indicating the increased surface area resulted in transport that

Chan Ching Ting, Mathew Bowles, Ibrahim Idewu

With the rapid development of Internet technology and the comprehensive popularity of Internet applications, online activities have gradually become an indispensable part of people's daily life. The original recommendation learning algorithm is mainly based on user-microvideo interaction for learning, modeling the user-micro-video connection relationship, wh

Ahmad Nickabadi, Maryam Saeedi Fard, Nastaran Moradzadeh Farid, Najmeh Mohammadbagheri

Generating random photo-realistic images has experienced tremendous growth during the past few years due to the advances of the deep convolutional neural networks and generative models. Among different domains, face photos have received a great deal of attention and a large number of face generation and manipulation models have been proposed. Semantic facial

Patrizio Giovannotti

Transformers, currently the state-of-the-art in natural language understanding (NLU) tasks, are prone to generate uncalibrated predictions or extreme probabilities, making the process of taking different decisions based on their output relatively difficult. In this paper we propose to build several inductive Venn--ABERS predictors (IVAP), which are guarantee

Roberto Paoletti

Suppose that a compact $r$-dimensional torus $T^r$ acts in a holomorphic and Hamiltonian manner on polarized complex $d$-dimensional projective manifold $M$, with nowhere vanishing moment map $\Phi$. Assuming that $\Phi$ is transverse to the ray through a given weight $\boldsymbol{\nu}$, associated to these data there is a complex $(d-r+1)$-dimensional polar

Joachim Jelisiejew

The thesis concerns Hilbert schemes of points and apart from mathematical results, contains small open problems and history sections, see the introduction for more details. The thesis has not been edited since 2017, see first page for more information. It is shared "as is" (in the language of GPL) solely due/thanks to several people who decided to refer to i

Zhiyu Fan, Xiang Gao, Martin Mirchev, Abhik Roychoudhury

Large language models such as Codex, have shown the capability to produce code for many programming tasks. However, the success rate of existing models is low, especially for complex programming tasks. One of the reasons is that language models lack awareness of program semantics, resulting in incorrect programs, or even programs which do not compile. In thi

John L Simons

Let $f$ be a permutation from $\mathbb{N}_0$ onto $\mathbb{N}_0$. Let $x\in\mathbb{N}_0$ and consider a (finite or infinite) sequence $s= (x,f(x),f^2(x),\cdots)$. We call $s$ a permutation sequence. Let $D$ be the set of elements of $s$. If $D$ is a finite set then the sequence $s$ is a cycle, and if $D$ is an infinite set the sequence $s$ is a divergent tra

Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad Enamul Hoque Chowdhury, Serkan Kiranyaz

Diabetic sensorimotor polyneuropathy (DSPN) is one of the prevalent forms of neuropathy affected by diabetic patients that involves alterations in biomechanical changes in human gait. In literature, for the last 50 years, researchers are trying to observe the biomechanical changes due to DSPN by studying muscle electromyography (EMG), and ground reaction for

Tamir Tassa, Lihi Dery, Arthur Zamarin

Electronic voting systems have significant advantages in comparison with physical voting systems. One of the main challenges in e-voting systems is to secure the voting process: namely, to certify that the computed results are consistent with the cast ballots and that the voters' privacy is preserved. We propose herein a secure voting protocol for elections

Rohit Pachlor, Deepti Shrimankar, Kapil Kumar Nagwanshi, Manish Paliwal

Balanced energy consumption is a major research concern in sensor networks. If some sensor nodes spent energy rapidly compared to other sensor groups, then the energy consumption is not evenly distributed and the lifetime of the network is adversely affected. In cluster-based communication protocol, cluster-head nodes rapidly dissipate their energy compared

Zhengyi Liu, Zhili Zhang, Wei Wu

Camouflaged object detection intends to discover the concealed objects hidden in the surroundings. Existing methods follow the bio-inspired framework, which first locates the object and second refines the boundary. We argue that the discovery of camouflaged objects depends on the recurrent search for the object and the boundary. The recurrent processing make

Jiayu Lin, Yuan-Gen Wang, Wenzhi Tang, Aifeng Li

Image inpainting has achieved great advances by simultaneously leveraging image structure and texture features. However, due to lack of effective multi-feature fusion techniques, existing image inpainting methods still show limited improvement. In this paper, we design a deep multi-feature co-learning network for image inpainting, which includes Soft-gating

Robin M. Schmidt, Telmo Pires, Stephan Peitz, Jonas Lööf

Non-autoregressive approaches aim to improve the inference speed of translation models by only requiring a single forward pass to generate the output sequence instead of iteratively producing each predicted token. Consequently, their translation quality still tends to be inferior to their autoregressive counterparts due to several issues involving output tok

Wolfgang Altmannshofer, Cecile Caillol, Mogens Dam, Stefania Xella

Charged lepton flavor violation is an unambiguous signature for New Physics. Here we present a summary of the theoretical and experimental status of the search for charged lepton flavor violation in heavy particle decays, in particular in the decays of the Z and Higgs bosons, and of the top quark. Decays of beyond-Standard-Model particles such as a Z' or an

Vinh Nguyen, Olivier Bodenreider

The construction and maintenance process of the UMLS (Unified Medical Language System) Metathesaurus is time-consuming, costly, and error-prone as it relies on (1) the lexical and semantic processing for suggesting synonymous terms, and (2) the expertise of UMLS editors for curating the suggestions. For improving the UMLS Metathesaurus construction process,

Lisbeth Danyeli Delgado Ordoñez, John H. Castillo, Alexander Holguín-Villa

A binary $[n,k]$-linear code $\mathcal{C}$ is a $k$-dimensional subspace of $\mathbb{F}_2^n$. For $\boldsymbol{x}\in \mathbb{F}_2^n$, the set $\boldsymbol{x}+\mathcal{C}$ is a coset of $\mathcal{C}$. In this work we study a partial ordering on the set of cosets of a binary linear code $\mathcal{C}$ of length $n$ and we construct a graph using the orphan stru

V. Fanaskov, I. Oseledets

A plentitude of applications in scientific computing requires the approximation of mappings between Banach spaces. Recently introduced Fourier Neural Operator (FNO) and Deep Operator Network (DeepONet) can provide this functionality. For both of these neural operators, the input function is sampled on a given grid (uniform for FNO), and the output function i

Dong Wei, Ying Sun, Sim-Heng Ong, Ping Chai

Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can directly visualize nonviable myocardium with hyperenhanced intensities with respect to normal myocardium. For heart attack patients, it is crucial to facilitate the decision of appropriate therapy by analyzing and quantifying their LGE CMR images. To achieve accurate quantification, LGE CMR

Zechen Liang, Yuan-Gen Wang, Wei Lu, Xiaochun Cao

Semi-Supervised Learning (SSL) has advanced classification tasks by inputting both labeled and unlabeled data to train a model jointly. However, existing SSL methods only consider the unlabeled data whose predictions are beyond a fixed threshold (e.g., 0.95), ignoring the valuable information from those less than 0.95. We argue that these discarded data have

Ivan Klianev

We present an algorithm for synchronous deterministic Byzantine consensus, tolerant to links failures and links asynchrony. It cares for a class of networks with specific needs, where both safety and liveness are essential, and timely irrevocable consensus has priority over highest throughput. The algorithm operates with redundant delivery of messages via in

Yanzhao Zhang, Dingkun Long, Guangwei Xu, Pengjun Xie

Deep pre-trained language models (e,g. BERT) are effective at large-scale text retrieval task. Existing text retrieval systems with state-of-the-art performance usually adopt a retrieve-then-reranking architecture due to the high computational cost of pre-trained language models and the large corpus size. Under such a multi-stage architecture, previous studi

Zhen Qin, Xueqiang Yan, Mengchu Zhou, Shuiguang Deng

Federated learning (FL) enables collaborative training of machine learning models without sharing training data. Traditional FL heavily relies on a trusted centralized server. Although decentralized FL eliminates the central dependence, it may worsen the other inherit problems faced by FL such as poisoning attacks and data representation leakage due to insuf

Qianqian Guo, Changchang Xi

Under semi-weak and weak compatibility of bimodules, we establish sufficient and necessary conditions of Gorenstein-projective modules over rings of Morita contexts with one bimodule homomorphism zero. This generalises and extends results on triangular matrix Artin algebras and on Artin algebras of Morita contexts with two bimodule homomorphisms zero in the

Luciano Petruzziello

We explore the interplay between the equivalence principle and a generalization of the Heisenberg uncertainty relations known as extended uncertainty principle, that comprises the effects of spacetime curvature at large distances. Specifically, we observe that, when the modified uncertainty relations hold, the weak formulation of the equivalence principle is

Xiaomei Li, Manqi Ruan, Mingrui Zhao

The CP-violating phase $\phi_s$, the \Bs decay width ($\Gamma_s$), and the \Bs decay width difference ($\Delta\Gamma_s$) are sensitive probes to new physics and can constrain the heavy quark expansion theory. The potential for the measurement at future $Z$ factories is studied in this manuscript. It is found that operating at Tera-$Z$ mode, the expected prec

Shiyu Xu, Scott Moore, Akansel Cosgun

In this paper, we present the implementation details of a Virtual Reality (VR)-based teleoperation interface for moving a robotic manipulator. We propose an iterative human-in-the-loop design where the user sets the next task-space waypoint for the robot's end effector and executes the action on the physical robot before setting the next waypoints. Informati

Hideaki Yamamoto, F. Paul Spitzner, Taiki Takemuro, Victor Buendía

Brain functions require both segregated processing of information in specialized circuits, as well as integration across circuits to perform high-level information processing. One possible way to implement these seemingly opposing demands is by flexibly switching between synchronous and less synchronous states. Understanding how complex synchronization patte

Qiao-Qiao Lv, Jin-Min Liang, Zhi-Xi Wang, Shao-Ming Fei

Quantum nonlocality is a kind of significant quantum correlation that is stronger than quantum entanglement and EPR steering. The standard tripartite nonlocality can be detected by the violation of the Mermin inequality. By using local filtering operations, we give a tight upper bound on the maximal expected value of the Mermin operators. By detailed example

Tanmoy Paul

In the present work, we examine the following points in the context of the recently proposed curvature coupling helical magnetogenesis scenario \cite{Bamba:2021wyx} -- (1) whether the model is consistent with the predictions of perturbative quantum field theory (QFT), and (2) whether the curvature perturbation induced by the generated electromagnetic (EM) fi

Boris Mocialov, Graham Turner, Helen Hastie

Traditionally, sign language resources have been collected in controlled settings for specific tasks involving supervised sign classification or linguistic studies accompanied by specific annotation type. To date, very few who explored signing videos found online on social media platforms as well as the use of unsupervised methods applied to such resources.

Pavel Pascacio, Joaquín Torres-Sospedra, Sven Casteleyn, Elena Simona Lohan

In daily life, mobile and wearable devices with high computing power, together with anchors deployed in indoor environments, form a common solution for the increasing demands for indoor location-based services. Within the technologies and methods currently in use for indoor localization, the approaches that rely on Bluetooth Low Energy (BLE) anchors, Receive

Bishal Santra, Ravi Ghadia, Manish Gupta, Pawan Goyal

In the field of Natural Language Processing, there are many tasks that can be tackled effectively using the cross-entropy (CE) loss function. However, the task of dialog generation poses unique challenges for CE loss. This is because CE loss assumes that, for any given input, the only possible output is the one available as the ground truth in the training d

T. Wang, M. Zhang, L. F. Wei

We propose a frequency-mixed effect of Terahertz (THz) and Gigahertz (GHz) electromagnetic waves in the cryogenic system of electrons floating on liquid helium surface. The THz wave is near-resonant with the transition frequency between the lowest two levels of surface state electrons. The GHz wave does not excite the transitions but generates a GHz-varying

Ildar Rakhmatulin

This manuscript presents a not typical implementation of the cycle generative adversarial networks (Cycle-GAN) method for eye-tracking tasks.

M. Reza Shaebani, Matthieu Piel, Franziska Lautenschläger

Migrating cells exhibit various motility patterns, resulting from different migration mechanisms, cell properties, or cell-environment interactions. The complexity of cell dynamics is reflected, e.g., in the diversity of the observed forms of velocity autocorrelation function -- that has been widely served as a measure of diffusivity and spreading -- . By an

Venkatasubbareddy K, Sankaranarayanan Ayyadurai

In this paper, we study the average behaviour of the coefficients of triple product L-functions and some related L-functions corresponding to normalized primitive holomorphic cusp form $f(z)$ of weight $k$ for the full modular group $SL(2,\ \mathbb{Z}).$ Here we call $f(z)$ a primitive cusp form if it is an eighenfunction of all Hecke operators simultaneousl

Adarsh Ghimire, Xiaoxiong Zhang, Sajid Javed, Jorge Dias

Person-tracking robots have many applications, such as in security, elderly care, and socializing robots. Such a task is particularly challenging when the person is moving in a Uniform crowd. Also, despite significant progress of trackers reported in the literature, state-of-the-art trackers have hardly addressed person following in such scenarios. In this w

Thomas Debris-Alazard, Léo Ducas, Nicolas Resch, Jean-Pierre Tillich

In this article we revisit smoothing bounds in parallel between lattices $and$ codes. Initially introduced by Micciancio and Regev, these bounds were instantiated with Gaussian distributions and were crucial for arguing the security of many lattice-based cryptosystems. Unencumbered by direct application concerns, we provide a systematic study of how these bo

Kharanshu Solanki

This paper examines the incommensurability thesis - one of the most important and controversial ideas to emerge from the simultaneous work of Kuhn and Feyerabend. In the first half, I discuss three aspects of incommensurability - methodological incommensurability (the view that each paradigm supplies different standards of evaluation), observational incommen

Wei Ju, Junwei Yang, Meng Qu, Weiping Song

This paper studies semi-supervised graph classification, which is an important problem with various applications in social network analysis and bioinformatics. This problem is typically solved by using graph neural networks (GNNs), which yet rely on a large number of labeled graphs for training and are unable to leverage unlabeled graphs. We address the limi

L. Mancini, M. Esposito, E. Covino, J. Southworth

Aim: We aim to refine the orbital and physical parameters and determine the sky-projected planet orbital obliquity of five eccentric transiting planetary systems: HAT-P-15, HAT-P-17, HAT-P-21, HAT-P-26, and HAT-P-29. Each of the systems hosts a hot Jupiter, except for HAT-P-26 which hosts a Neptune-mass planet. Methods: We observed transit events of these pl

Dong Wei, Ying Sun, Sim-Heng Ong, Ping Chai

Automatic segmentation of the left ventricle (LV) in late gadolinium enhanced (LGE) cardiac MR (CMR) images is difficult due to the intensity heterogeneity arising from accumulation of contrast agent in infarcted myocardium. In this paper, we present a comprehensive framework for automatic 3D segmentation of the LV in LGE CMR images. Given myocardial contour

C. Macci, B. Pacchiarotti

The main results in this paper concern large deviations for families of non-Gaussian processes obtained as suitable perturbations of continuous centered multivariate Gaussian processes which satisfy a large deviation principle. We present some corollaries and, as a consequence, we obtain logarithmic asymptotic estimates for exit probabilities from suitable h

Jiawei Mao, Xuesong Yin, Yuanqi Chang, Honggu Zhou

This paper explores improvements to the masked image modeling (MIM) paradigm. The MIM paradigm enables the model to learn the main object features of the image by masking the input image and predicting the masked part by the unmasked part. We found the following three main directions for MIM to be improved. First, since both encoders and decoders contribute

Mike Pols, Tobias Hilpert, Ivo Filot, Adri C. T. van Duin

The commercialization of perovskite solar cells is hindered by the poor long-term stability of the metal halide perovskite (MHP) light absorbing layer. Solution processing, the common fabrication method for MHPs, produces polycrystalline films with a wide variety of defects, such as point defects, surfaces, and grain boundaries. Although the optoelectronic e

Yan Lyu, Takumi Doi, Tetsuo Hatsuda, Yoichi Ikeda

First results on the interaction between the $\phi$-meson and the nucleon ($N$) are presented based on the ($2+1$)-flavor lattice QCD simulations with nearly physical quark masses. Using the HAL QCD method, the spacetime correlation of the $N$-$\phi$ system in the spin 3/2 channel is converted into the $N$-$\phi$ scattering phase shift through the interactio

Fabian Langkabel, Annika Bande

In this work, we investigate the capability of known quantum-computing algorithms for fault-tolerant quantum computing to simulate the laser-driven electron dynamics in small molecules such as lithium hydride. These computations are executed on a quantum-computer simulator. Results are compared with the time-dependent full configuration interaction method (T

Tatyana Yakhno, Anatoly Sanin, Vladimir Yakhno

In the modern world, the focus of natural science research thought has shifted mainly to the molecular level, including the study of water. Water is considered as a mixture of interacting H2O molecules and their clusters based on the data of molecular dynamics, neutron and X-ray scattering. In this case, a huge layer of information is lost related to the com

Michael C. Burkhart, Gabriel Ruiz

Within the field of causal inference, we consider the problem of estimating heterogeneous treatment effects from data. We propose and validate a novel approach for learning feature representations to aid the estimation of the conditional average treatment effect or CATE. Our method focuses on an intermediate layer in a neural network trained to predict the o

Jaan Masso, Amaresh K Tiwari

We study the productivity implications of R&D, capital accumulation, and innovation output for entrants and incumbents in Estonia. First, in contrast to developed economies, a small percentage of firm engage in formal R&D, but a much larger percentage innovate. Second, while we find no difference in the R&D elasticity of productivity for the entrants and inc

Soma Kontar, Andras Horvath

Deep neural networks were applied with success in a myriad of applications, but in safety critical use cases adversarial attacks still pose a significant threat. These attacks were demonstrated on various classification and detection tasks and are usually considered general in a sense that arbitrary network outputs can be generated by them. In this paper we

Ruili Feng, Jie Xiao, Kecheng Zheng, Deli Zhao

Human can extrapolate well, generalize daily knowledge into unseen scenarios, raise and answer counterfactual questions. To imitate this ability via generative models, previous works have extensively studied explicitly encoding Structural Causal Models (SCMs) into architectures of generator networks. This methodology, however, limits the flexibility of the g

Marc Schmitt

The realization that AI-driven decision-making is indispensable in today's fast-paced and ultra-competitive marketplace has raised interest in industrial machine learning (ML) applications significantly. The current demand for analytics experts vastly exceeds the supply. One solution to this problem is to increase the user-friendliness of ML frameworks to ma

Ping-Yen Hsieh, Shun-Lin Fang, Yu-Siang Lin, Wen-Hsien Huang

The emerging applications of silicon photonics in free space, such as LiDARs and quantum photonics, urge versatile emission shaping beyond the capabilities of conventional grating couplers. A platform that offers arbitrary shaping of free-space emission while maintaining the CMOS compatibility and monolithic integration is in pressing need. Here we demonstra

Tao Huang, Shan You, Fei Wang, Chen Qian

Unlike existing knowledge distillation methods focus on the baseline settings, where the teacher models and training strategies are not that strong and competing as state-of-the-art approaches, this paper presents a method dubbed DIST to distill better from a stronger teacher. We empirically find that the discrepancy of predictions between the student and a

Marc Schmitt

Artificial intelligence (AI) and machine learning (ML) have become vital to remain competitive for financial services companies around the globe. The two models currently competing for the pole position in credit risk management are deep learning (DL) and gradient boosting machines (GBM). This paper benchmarked those two algorithms in the context of credit s

D. A. Nesterenko, K. Blaum, P. Delahaye, S. Eliseev

$^{180m}$Ta is a naturally abundant quasi-stable nuclide and the longest-lived nuclear isomer known to date. It is of interest for, among others, the search for dark matter, for the development of a gamma laser and for astrophysics. So far, its excitation energy has not been measured directly but has been based on an evaluation of available nuclear reaction

X. Li, M. W. Ahmed, A. Banu, C. Bartram

Differential cross sections for Compton scattering from the proton have been measured at scattering angles of $55^\circ$, $90^\circ$, and $125^\circ$ in the laboratory frame using quasimonoenergetic linearly (circularly) polarized photon beams with a weighted mean energy value of 83.4\,MeV (81.3\,MeV). These measurements were performed at the High Intensity

Rujiang Li, Pengfei Li, Yongtao Jia, Ying Liu

Three-dimensional (3D) topological materials exhibit much richer phenomena than their lower-dimensional counterparts. Here, we propose self-localized topological states (i.e., topological solitons) in a 3D nonlinear photonic Chern insulator. Despite being in the bulk and self-localized in all 3D, the topological solitons at high-symmetry points K and K' rota

Miljenko Cemeljic, Hai Yang, Feng Yuan, Hsien Shang

Episodic ejections of blobs (episodic jets) are widely observed in black hole sources and usually associated with flares. In this paper, by performing and analyzing three dimensional general relativity magnetohydrodynamical numerical simulations of accretion flows, we investigate their physical mechanisms. We find that magnetic reconnection occurs in the acc

Xueying Zhang, Kai Shen, Chi Zhang, Xiaochuan Fan

In this paper, we proposed an automatic Scenario-based Multi-product Advertising Copywriting Generation system (SMPACG) for E-Commerce, which has been deployed on a leading Chinese e-commerce platform. The proposed SMPACG consists of two main components: 1) an automatic multi-product combination selection module, which itself is consisted of a topic predicti

Tuong Do, Huy Tran, Erman Tjiputra, Quang D. Tran

Extracting discriminative features plays a crucial role in the fine-grained visual classification task. Most of the existing methods focus on developing attention or augmentation mechanisms to achieve this goal. However, addressing the ambiguity in the top-k prediction classes is not fully investigated. In this paper, we introduce a Self Assessment Classifie

Xin Deng, WenYu Zhang, Qing Ding, XinMing Zhang

In point cloud analysis, point-based methods have rapidly developed in recent years. These methods have recently focused on concise MLP structures, such as PointNeXt, which have demonstrated competitiveness with Convolutional and Transformer structures. However, standard MLPs are limited in their ability to extract local features effectively. To address this

Xi Tong, Yi Wang, Hui-Yu Zhu

We study the impact of a binary companion on black hole superradiance at orbital frequencies away from the gravitational-collider-physics (GCP) resonance bands. A superradiant state can couple to a strongly absorptive state via the tidal perturbation of the companion, thereby acquiring a suppressed superradiance rate. Below a critical binary separation, this

Richard M. Talman

The upper limit on (time reversal symmetry T-violating) permanent hadron electric dipole moments (EDMs) is the PSI neutron EDM value; $d_n = (0.0\pm1.1_{\rm stat}\pm0.2_{\rm sys}\times10^{-26})\,e$\,cm. This paper describes an experiment to be performed at a BNL-proposed CLIP project which is to be capable of producing intense polarized beams of protons, $p$

M. Umar Farooq, M. Safdar

Noether theorem establishes an interesting connection between symmetries of the action integral and conservation laws of a dynamical system. The aim of the present work is to classify the damped harmonic oscillator problem with respect to Noether symmetries and to construct corresponding conservation laws for all over-damped, under damped and critical damped

Y. Baraud, H. Halconruy, G. Maillard

We solve the problem of estimating the distribution of presumed i.i.d. observations for the total variation loss. Our approach is based on density models and is versatile enough to cope with many different ones, including some density models for which the Maximum Likelihood Estimator (MLE for short) does not exist. We mainly illustrate the properties of our

Hajime Sotani

Since the eigenfrequency of gravitational waves from cold neutron stars becomes a complex number, where the real and imaginary parts respectively correspond to an oscillation frequency and damping rate, one has to somehow solve the eigenvalue problem concerning the eigenvalue in two-dimensional parameter space. To avoid this bother, one sometimes adopts an a

Yusuf Can Sevil, Tugba Ozkal Yildiz

Empirical distribution functions (EDFs) based on ranked set sampling (RSS) and its modifications have been examined by many authors. In these studies, the proposed estimators have been investigated for infinite population setting. However, developing EDF estimators in finite population setting would be more valuable for areas such as environmental, ecologica

Andrea Di Primio, Maurizio Grasselli, Luca Scarpa

We investigate a stochastic version of the Allen-Cahn-Navier-Stokes system in a smooth two- or three-dimensional domain with random initial data. The system consists of a Navier-Stokes equation coupled with a convective Allen-Cahn equation, with two independent sources of randomness given by general multiplicative-type Wiener noises. In particular, the Allen

Bo Li, Fangxiao Wang, Yu Zhou

We study the maximin share (MMS) fair allocation of $m$ indivisible chores to $n$ agents who have costs for completing the assigned chores. It is known that exact MMS fairness cannot be guaranteed, and so far the best-known approximation for additive cost functions is $\frac{13}{11}$ by Huang and Segal-Halevi [EC, 2023]; however, beyond additivity, very litt

Nithin V. Sabu, Abhishek K. Gupta, Neeraj Varshney, Anshuman Jindal

Molecular communication is a promising solution to enable intra-body communications among nanomachines. However, malicious and non-cooperative receivers can degrade the performance, compromising these systems' security. Analyzing the communication and security performance of these systems requires accurate channel models. However, such models are not present

Wei-Qi Peng, Yong Chen

In this work, we mainly consider the Cauchy problem for the reverse space-time nonlocal Hirota equation with the initial data rapidly decaying in the solitonless sector. Start from the Lax pair, we first construct the basis Riemann-Hilbert problem for the reverse space-time nonlocal Hirota equation. Furthermore, using the approach of Deift-Zhou nonlinear ste

Kurt Micallef, Albert Gatt, Marc Tanti, Lonneke van der Plas

Multilingual language models such as mBERT have seen impressive cross-lingual transfer to a variety of languages, but many languages remain excluded from these models. In this paper, we analyse the effect of pre-training with monolingual data for a low-resource language that is not included in mBERT -- Maltese -- with a range of pre-training set ups. We cond

Philipp Gubler, Naoki Yamamoto, Di-Lun Yang

We investigate polarized gravitational waves generated by chiral fermions in the early Universe. In particular, we focus on the contribution from left-handed neutrinos in thermal equilibrium with finite temperature and chemical potential in the radiation dominated era. We compute the correlation functions of gravitational fields pertinent to the Stokes param

Daniel Kvak

Melanoma is considered to be the most aggressive form of skin cancer. Due to the similar shape of malignant and benign cancerous lesions, doctors spend considerably more time when diagnosing these findings. At present, the evaluation of malignancy is performed primarily by invasive histological examination of the suspicious lesion. Developing an accurate cla

Bowen Liu, Qinglong Zhou

In this paper, we consider the elliptic relative equilibria of the restricted $4$-body problems, where the three primaries form an Euler collinear configuration and the four bodies span $\mathbf{R}^2$. We obtain the symplectic reduction to the general restricted $N$-body problem. By analyzing the relationship between this restricted $4$-body problems and the

Michael Timothy Bennett

Artificial general intelligence (AGI) may herald our extinction, according to AI safety research. Yet claims regarding AGI must rely upon mathematical formalisms -- theoretical agents we may analyse or attempt to build. AIXI appears to be the only such formalism supported by proof that its behaviour is optimal, a consequence of its use of compression as a pr

Irina Basieva, Andrei Khrennikov

Our aim is to make a step towards clarification of foundations for the notion of entanglement (both physical and mathematical) by representing it in the conditional probability framework. In Schr\"odinger's words, this is entanglement of knowledge which can be extracted via conditional measurements. In particular, quantum probabilities are interpreted as con

Rouven Frassek

Taking inspiration from the harmonic process with reservoirs introduced by Giardin\`a, Kurchan and the author in arXiv:1904.01048, we propose integrable boundary conditions for its trigonometric deformation which is known as the q-Hahn process. Following the formalism established by Mangazeev and Lu in arXiv:1903.00274 using the stochastic R-matrix, we argue

Yangkai Du, Tengfei Ma, Lingfei Wu, Yiming Wu

Towards real-world information extraction scenario, research of relation extraction is advancing to document-level relation extraction(DocRE). Existing approaches for DocRE aim to extract relation by encoding various information sources in the long context by novel model architectures. However, the inherent long-tailed distribution problem of DocRE is overlo

Cheongho Han, Doeon Kim, Andrew Gould, Andrzej Udalski

With the aim of finding short-term planetary signals, we investigated the data collected from the high-cadence microlensing surveys. From this investigation, we found four planetary systems with low planet-to-host mass ratios, including OGLE-2017-BLG-1691L, KMT-2021-BLG-0320L, KMT-2021-BLG-1303L, and KMT-2021-BLG-1554L. Despite the short durations, ranging f

Takashi Kikkawa, Eiji Saitoh

The spin Seebeck effect (SSE) refers to the generation of a spin current as a result of a temperature gradient in a magnetic material, which can be detected electrically via the inverse spin Hall effect in a metallic contact. Since the discovery of SSE in 2008, intensive studies on SSE have been conducted to elucidate its origin. SSEs appear in a wide range

Hanyue Chen, Song Xi Chen, Mu Mu

We provide a review on the "optimal fingerprinting" approach as summarized in Allen and Tett (1999) from a point view of statistical inference in light of the recent criticism of McKitrick (2021). Our review finds that the "optimal fingerprinting" approach would survive much of McKitrick (2021)'s criticism under two conditions: (i) the null simulation of the