October 2022 arXiv papers — page 132

Anna Sokolova, Filipp Nikitin, Anna Vorontsova, Anton Konushin

Processing large indoor scenes is a challenging task, as scan registration and camera trajectory estimation methods accumulate errors across time. As a result, the quality of reconstructed scans is insufficient for some applications, such as visual-based localization and navigation, where the correct position of walls is crucial. For many indoor scenes, ther

Dimitris Chaikalis, Nikolaos Evangeliou, Anthony Tzes, Farshad Khorrami

The control problem of a multi-copter swarm, mechanically coupled through a modular lattice structure of connecting rods, is considered in this article. The system's structural elasticity is considered in deriving the system's dynamics. The devised controller is robust against the induced flexibilities, while an inherent adaptation scheme allows for the cont

Luca Bonfiglioli, Marco Toschi, Davide Silvestri, Nicola Fioraio

We present Eyecandies, a novel synthetic dataset for unsupervised anomaly detection and localization. Photo-realistic images of procedurally generated candies are rendered in a controlled environment under multiple lightning conditions, also providing depth and normal maps in an industrial conveyor scenario. We make available anomaly-free samples for model t

Amel Bourdoucen, Janne Lindqvist

Users need to configure default apps when they first start using their devices. The privacy configurations of the default apps do not always match what users think they have initially enabled. We first systematically evaluated the privacy configurations of default apps. We discovered serious issues with the documentation of the default apps. Based on these f

Shijie Wu, Xun Gong

Face recognition has made tremendous progress in recent years due to the advances in loss functions and the explosive growth in training sets size. A properly designed loss is seen as key to extract discriminative features for classification. Several margin-based losses have been proposed as alternatives of softmax loss in face recognition. However, two issu

Jiri Smetana, Artemiy Dmitriev, Chunnong Zhao, Haixing Miao

The sensitivity of laser interferometers is fundamentally limited by the quantum nature of light. Recent theoretical studies have opened a new avenue to enhance their quantum-limited sensitivity by using active parity-time-symmetric and phase-insensitive quantum amplification. These systems can enhance the signal response without introducing excess noise in

Zih-Ching Chen, Chin-Lun Fu, Chih-Ying Liu, Shang-Wen Li

In this study, we aim to explore efficient tuning methods for speech self-supervised learning. Recent studies show that self-supervised learning (SSL) can learn powerful representations for different speech tasks. However, fine-tuning pre-trained models for each downstream task is parameter-inefficient since SSL models are notoriously large with millions of

Elod P. Csirmaz, Laszlo Csirmaz

Data reconciliation in general, and filesystem synchronization in particular, lacks rigorous theoretical foundation. This paper presents, for the first time, a complete analysis of synchronization for two replicas of a theoretical filesystem. Synchronization has two main stages: identifying the conflicts, and resolving them. All existing (both theoretical an

Kanchan Meena, P. Singha Deo

Tunneling, though a physical reality, is shrouded in mystery. Wave packets cannot be constructed under the barrier and group velocity cannot be defined. The tunneling particle can be observed on either sides of the barrier but its properties under the barrier has never been probed due to several problems related to quantum measurement. We show that there are

Qingyi Si, Yuanxin Liu, Fandong Meng, Zheng Lin

Models for Visual Question Answering (VQA) often rely on the spurious correlations, i.e., the language priors, that appear in the biased samples of training set, which make them brittle against the out-of-distribution (OOD) test data. Recent methods have achieved promising progress in overcoming this problem by reducing the impact of biased samples on model

Xingyu Chen, Jianru Xue, Jianwu Fang, Yuxin Pan

In this paper, we propose a lightweight system, RDS-SLAM, based on ORB-SLAM2, which can accurately estimate poses and build semantic maps at object level for dynamic scenarios in real time using only one commonly used Intel Core i7 CPU. In RDS-SLAM, three major improvements, as well as major architectural modifications, are proposed to overcome the limitatio

Guozheng Ma, Zhen Wang, Zhecheng Yuan, Xueqian Wang

Visual reinforcement learning (RL), which makes decisions directly from high-dimensional visual inputs, has demonstrated significant potential in various domains. However, deploying visual RL techniques in the real world remains challenging due to their low sample efficiency and large generalization gaps. To tackle these obstacles, data augmentation (DA) has

Prajit Nadkarni, Narendra Varma Dasararaju

Visual search is of great assistance in reseller commerce, especially for non-tech savvy users with affinity towards regional languages. It allows resellers to accurately locate the products that they seek, unlike textual search which recommends products from head brands. Product attributes available in e-commerce have a great potential for building better v

Shitong Xu

Image captioning task has been extensively researched by previous work. However, limited experiments focus on generating captions based on non-autoregressive text decoder. Inspired by the recent success of the denoising diffusion model on image synthesis tasks, we apply denoising diffusion probabilistic models to text generation in image captioning tasks. We

Yinan Fang, Seungju Han, Stefano Chesi, Mahn-Soo Choi

We consider two-dimensional superconductor/ferromagnet/superconductor junctions and investigate the subgap modes along the junction interface. The subgap modes exhibit characteristics similar to the Yu-Shiba-Rusinov states that originate form the interplay between superconductivity and ferromagnetism in the magnetic junction. The dispersion relation of the s

Rickie Xian

Folding protein dynamics has been an area of high interest for quite some time, especially given the increased focus on the field of Biophysics. Because folding dynamics occur on such short time scales, empirical techniques developed for more "static" protein events, such as X-ray crystallography, nuclear magnetic resonance, and green fluorescent protein (GF

Wafa Labidi, Rami Ezzine, Christian Deppe, Moritz Wiese

We study a standard two-source model for common randomness (CR) generation in which Alice and Bob generate a common random variable with high probability of agreement by observing independent and identically distributed (i.i.d.) samples of correlated sources on countably infinite alphabets. The two parties are additionally allowed to communicate as little as

Andrea Campagner, Lorenzo Famiglini, Anna Carobene, Federico Cabitza

In medical settings, Individual Variation (IV) refers to variation that is due not to population differences or errors, but rather to within-subject variation, that is the intrinsic and characteristic patterns of variation pertaining to a given instance or the measurement process. While taking into account IV has been deemed critical for proper analysis of m

Ben Dixon, María Pérez-Ortiz, Jacob Bieker

Solar PV yield nowcasting is used to help anticipate peaks and troughs in demand to support grid integration. This paper compares multiple low-resource approaches to nowcasting solar PV yield, using a dataset of UK satellite imagery and solar PV energy readings over a 1 to 4-hour time range. The paper also estimates the carbon emissions generated and averted

Yitong Xia, Hao Tang, Radu Timofte, Luc Van Gool

NeRFmm is the Neural Radiance Fields (NeRF) that deal with Joint Optimization tasks, i.e., reconstructing real-world scenes and registering camera parameters simultaneously. Despite NeRFmm producing precise scene synthesis and pose estimations, it still struggles to outperform the full-annotated baseline on challenging scenes. In this work, we identify that

Jun Wu, Shuoli Qi, Yueshan Zhong

Recent efforts to identify non-cognitive predictors of academic achievement have especially focused on self-constructs, whose measurement is concerned with a specific domain (e.g., mathematics). However, other important factors, such as character and motivation, have received less attention. Additionally, the predictive accuracy of non-cognitive factors lack

Itay Kaplan

We prove a definable version of Matou\v{s}ek's $(p,q)$-theorem in NIP theories. This answers a question of Chernikov and Simon. We also prove a uniform version. The proof builds on a proof of Boxall and Kestner who proved this theorem in the distal case, utilizing the notion of locally compressible types which appeared in the work of the author with Bays and

Zijiang Zhou, Yue Zhou

It is conjectured by Golomb and Welch around half a century ago that there is no perfect Lee codes $C$ of packing radius $r$ in $\mathbb{Z}^{n}$ for $r\geq2$ and $n\geq 3$. Recently, Leung and the second author proved this conjecture for linear Lee codes with $r=2$. A natural question is whether it is possible to classify the second best, i.e., almost perfec

Jaco Ruit

We introduce a novel notion of pasting shapes for iterated Segal spaces which classify particular arrangements of composing cells in d-uple Segal spaces. Using this formalism, we then continue to prove a pasting theorem for these iterated Segal spaces.

Sebastian Chenery

It is a well-known result of C.T.C. Wall's that one may decompose a simply connected 6-manifold as a connected sum of two simpler manifolds. Recent work of Beben and Theriault on decomposing based loop spaces of highly connected Poincar\'e Duality complexes has yielded new methods for analysing the homotopy theory of manifolds. In this paper we will expand u

Shailee P Shah, Nayan Mumana, Preksha Barad, Rucha P Desai

The present study reports PIV analysis of the surface flow profile using a smartphone camera in ambient light instead of high-tech equipment like a professional camera and high-power laser/ LEDs. Additionally, it provides a stepwise method for optimizing recording speed and interrogation window size for the vortex flow generated at different rotational frequ

Hosea Wondo

We study the convergence and curvature blow up of La Nave and Tian's continuity method on a generalised Hirzebruch surface. We show that the Gromov-Hausdorff convergence is similar to that of the Kahler-Ricci flow and obtain curvature estimates. We also show that a general solution to the continuity method either exist or all times, or the scalar curvature b

Christos Baziotis, Prashant Mathur, Eva Hasler

A major open problem in neural machine translation (NMT) is the translation of idiomatic expressions, such as "under the weather". The meaning of these expressions is not composed by the meaning of their constituent words, and NMT models tend to translate them literally (i.e., word-by-word), which leads to confusing and nonsensical translations. Research on

Constantino Sánchez Romero, Vicente Garzó

The Boltzmann equation for $d$-dimensional inelastic Maxwell models is considered to determine the collisional moments of second, third and fourth degree in a granular binary mixture. These collisional moments are exactly evaluated in terms of the velocity moments of the distribution function of each species when diffusion is absent (mass flux of each specie

Xingyu Chen, Jianru Xue, Shanmin Pang

Vision-based localization in a prior map is of crucial importance for autonomous vehicles. Given a query image, the goal is to estimate the camera pose corresponding to the prior map, and the key is the registration problem of camera images within the map. While autonomous vehicles drive on the road under occlusion (e.g., car, bus, truck) and changing enviro

Vasilis Gkolemis, Theodore Dalamagas, Christos Diou

Accumulated Local Effect (ALE) is a method for accurately estimating feature effects, overcoming fundamental failure modes of previously-existed methods, such as Partial Dependence Plots. However, ALE's approximation, i.e. the method for estimating ALE from the limited samples of the training set, faces two weaknesses. First, it does not scale well in cases

Rahime Belen-Saglam, Enes Altuncu, Yang Lu, Shujun Li

The blockchain technology has been rapidly growing since Bitcoin was invented in 2008. The most common type of blockchain systems, public (permisionless) blockchain systems have some unique features that lead to a tension with European Union's General Data Protection Regulation (GDPR) and other similar data protection laws. In this paper, we report the resul

F. Zhang, L. Yin

We obtain the superfluid hydrodynamic equations of a multi-component Bose gas with short-ranged interactions at zero temperature under the local equilibrium assumption and show that the quantum pressure is generally present in the nonuniform case. Our approach can be extended to systems with long-range interactions such as dipole-dipole interactions by treat

M. Mohamed El Kordy Shehata, George Simion, Ruoyu Li, Fahd A. Mohiyaddin

The spin of an electron confined in semiconductor quantum dots is currently a promising candidate for quantum bit (qubit) implementations. Taking advantage of existing CMOS integration technologies, such devices can offer a platform for large scale quantum computation. However, a quantum mechanical framework bridging a device's physical design and operationa

Sourav Biswas, Pankaj Wahi, Anjan Kumar Gupta

Superconducting weak link (WL), acting as a Josephson junction (JJ), is one of the widely used elements in superconductor science and quantum circuits. A hysteretic JJ with robust switching between its superconducting and resistive state is an excellent candidate for single-photon detection. However, the ubiquitous fluctuations in the junction strongly influ

Romain Gautron, Dorian Baudry, Myriam Adam, Gatien N Falconnier

Identification of best performing fertilizer practices among a set of contrasting practices with field trials is challenging as crop losses are costly for farmers. To identify best management practices, an ''intuitive strategy'' would be to set multi-year field trials with equal proportion of each practice to test. Our objective was to provide an identificat

Daniel Eckhardt, Barbara Verfürth

The aim of this work is the numerical homogenization of a parabolic problem with several time and spatial scales using the heterogeneous multiscale method. We replace the actual cell problem with an alternate one, using Dirichlet boundary and initial values instead of periodic boundary and time conditions. Further, we give a detailed a priori error analysis

Arnaud Martin

Most questionnaires offer ordered responses whose order is poorly studied via belief functions. In this paper, we study the consequences of a frame of discernment consisting of ordered elements on belief functions. This leads us to redefine the power space and the union of ordered elements for the disjunctive combination. We also study distances on ordered e

Xu-Run Huang, Lie-Wen Chen

A precise and model-independent determination of the neutron distribution radius $R_{\rm n}$ and thus the neutron skin thickness $R_{\rm skin}$ of atomic nuclei is of fundamental importance in nuclear physics, particle physics and astrophysics but remains a big challenge in terrestrial labs. We argue that the nearby core-collapse supernova (CCSN) in our Gala

P. Sai Ram Aditya, Mayukha Pal

With the advancement of technology for artificial intelligence (AI) based solutions and analytics compute engines, machine learning (ML) models are getting more complex day by day. Most of these models are generally used as a black box without user interpretability. Such complex ML models make it more difficult for people to understand or trust their predict

Qu Yang, Jibin Wu, Malu Zhang, Yansong Chua

Spiking neural networks (SNNs) are shown to be more biologically plausible and energy efficient over their predecessors. However, there is a lack of an efficient and generalized training method for deep SNNs, especially for deployment on analog computing substrates. In this paper, we put forward a generalized learning rule, termed Local Tandem Learning (LTL)

R. Sundara Rajan, Rini Dominic D., T. M. Rajalaxmi, L. Packiaraj

Graph embedding is the major technique which is used to map guest graph into host graph. In architecture simulation, graph embedding is said to be one of the strongest application for the execution of parallel algorithm and simulation of various interconnection networks \cite{Pa99}. In this paper, we have embedded circulant networks into star of cycle and fo

E. R. Zinatullin, S. B. Korolev, T. Yu. Golubeva

In our work, we compare three teleportation protocols: the original protocol, the photon subtraction protocol, and the protocol with a cubic phase gate. We evaluate the fidelity of each protocol using the example of teleportation of the squeezed state and the Schrodinger's cat state. We show that, under equal conditions, the teleportation scheme with a cubic

Julien Romero, Simon Razniewski

Compiling comprehensive repositories of commonsense knowledge is a long-standing problem in AI. Many concerns revolve around the issue of reporting bias, i.e., that frequency in text sources is not a good proxy for relevance or truth. This paper explores whether children's texts hold the key to commonsense knowledge compilation, based on the hypothesis that

David Baumgartner, Ronan Bernard, Bernhard Weigand, Grazia Lamanna

Collisions between a stream of drops and a continuous jet of a different liquid are experimentally investigated. In contrast to previous studies, our work focuses on the effects of liquid miscibility and wettability on the collision outcomes. Thus, miscible and immiscible liquids providing total and partial wetting are used. We show that, as long as the jet

Erik Plauschinn

In this note we study the mass spectrum of type IIB flux compactifications. We first give a general discussion of the mass matrix for F-term vacua in four-dimensional N=1 supergravity theories and then specialize to type IIB Calabi-Yau orientifold compactifications in the presence of geometric and non-geometric fluxes. F-term vacua in this setting are in gen

Soumyajit Guin, Shalabh Bhatnagar

The infinite horizon setting is widely adopted for problems of reinforcement learning (RL). These invariably result in stationary policies that are optimal. In many situations, finite horizon control problems are of interest and for such problems, the optimal policies are time-varying in general. Another setting that has become popular in recent times is of

Jiri Horejsi

The present text is an updated version of an earlier author's book on the electroweak theory (published originally in 2002, ISBN 80-246-0639-9). It reflects the ultimate completion of the standard model by the long-awaited discovery of the Higgs boson (ten years after the first edition) and incorporates also some minor corrections of the previous text, remov

Dan Qiao, Chenchen Dai, Yuyang Ding, Juntao Li

The conventional success of textual classification relies on annotated data, and the new paradigm of pre-trained language models (PLMs) still requires a few labeled data for downstream tasks. However, in real-world applications, label noise inevitably exists in training data, damaging the effectiveness, robustness, and generalization of the models constructe

Yixiong Zou, Shanghang Zhang, Yuhua Li, Ruixuan Li

Few-shot class-incremental learning (FSCIL) is designed to incrementally recognize novel classes with only few training samples after the (pre-)training on base classes with sufficient samples, which focuses on both base-class performance and novel-class generalization. A well known modification to the base-class training is to apply a margin to the base-cla

Giovanni Angelini, Giuseppe Cavaliere, Luca Fanelli

When proxies (external instruments) used to identify target structural shocks are weak, inference in proxy-SVARs (SVAR-IVs) is nonstandard and the construction of asymptotically valid confidence sets for the impulse responses of interest requires weak-instrument robust methods. In the presence of multiple target shocks, test inversion techniques require extr

Kun Yan, Lei Ji, Chenfei Wu, Jian Liang

Panorama synthesis endeavors to craft captivating 360-degree visual landscapes, immersing users in the heart of virtual worlds. Nevertheless, contemporary panoramic synthesis techniques grapple with the challenge of semantically guiding the content generation process. Although recent breakthroughs in visual synthesis have unlocked the potential for semantic

Jungtaek Oh, Dae-Gyu Jang

We study the exact distributions of runs of a fixed length in variation which considers binary trials for which the probability of ones is geometrically varying. The random variable $E_{n,k}$ denote the number of success runs of a fixed length $k$, $1\leq k \leq n$. Theorem 3.1 gives an closed expression for the probability mass function (PMF) of the Type4 $

Baturay Saglam, Doga Gurgunoglu, Suleyman S. Kozat

We introduce a novel deep reinforcement learning (DRL) approach to jointly optimize transmit beamforming and reconfigurable intelligent surface (RIS) phase shifts in a multiuser multiple input single output (MU-MISO) system to maximize the sum downlink rate under the phase-dependent reflection amplitude model. Our approach addresses the challenge of imperfec

Timo Flesch, Andrew Saxe, Christopher Summerfield

How do humans and other animals learn new tasks? A wave of brain recording studies has investigated how neural representations change during task learning, with a focus on how tasks can be acquired and coded in ways that minimise mutual interference. We review recent work that has explored the geometry and dimensionality of neural task representations in neo

Weisong Dong

In this paper, we solve the Dirichlet problem for Monge-Amp\`ere type equations for $(n-1)$-plurisubharmonic functions on Hermitian manifolds.

Biswarup Paul, Mahatsab Mandal, Pradip Roy, Sukalyan Chattapadhyay

We have performed a systematic study of J/$\psi$ and $\psi$(2S) production in p--p collisions at different Large Hadron Collider (LHC) energies and at different rapidities using the leading order non-relativistic quantum chromodynamics model of heavy quarkonium production. We have included the contributions from hiher excited states decaying to J$\psi$ . The

ATLAS Collaboration

A search for pair-produced scalar and vector leptoquarks decaying into quarks and leptons of different generations is presented. It uses the full LHC Run 2 (2015-2018) data set of 139 fb$^{-1}$ collected with the ATLAS detector in proton-proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. Scalar leptoquarks with charge -(1/3)e as well as sca

C. Autieri, M. Cuoco, G. Cuono, S. Picozzi

We study from first principles the magnetic, electronic, orbital and structural properties of the LaMnO3 doped with gallium replacing the Mn-site. The gallium doping reduces the Jahn-Teller effect, and consequently the bandgap. Surprisingly, the system does not go towards a metallic phase because of the Mn-bandwidth reduction. The Ga-doping tends to reduce t

Dinh-Thi Nguyen, Julien Ricaud

We consider a one-dimensional, trapped, focusing Bose gas where $N$ bosons interact with each other via both a two-body interaction potential of the form $a N^{\alpha-1} U(N^\alpha(x-y))$ and an attractive three-body interaction potential of the form $-b N^{2\beta-2} W(N^\beta(x-y,x-z))$, where $a\in\mathbb{R}$, $b,\alpha>0$, $0<\beta<1$, $U, W \geq 0$, and

Luca Schmidtke, Benjamin Hou, Athanasios Vlontzos, Bernhard Kainz

Inferring 3D human pose from 2D images is a challenging and long-standing problem in the field of computer vision with many applications including motion capture, virtual reality, surveillance or gait analysis for sports and medicine. We present preliminary results for a method to estimate 3D pose from 2D video containing a single person and a static backgro

Chengwei Hu, Deqing Yang, Haoliang Jin, Zhen Chen

Continual relation extraction (CRE) aims to extract relations towards the continuous and iterative arrival of new data, of which the major challenge is the catastrophic forgetting of old tasks. In order to alleviate this critical problem for enhanced CRE performance, we propose a novel Continual Relation Extraction framework with Contrastive Learning, namely

Eric Cancès, Michael F. Herbst, Gaspard Kemlin, Antoine Levitt

Response calculations in density functional theory aim at computing the change in ground-state density induced by an external perturbation. At finite temperature these are usually performed by computing variations of orbitals, which involve the iterative solution of potentially badly-conditioned linear systems, the Sternheimer equations. Since many sets of v

Debjani Banerjee

Measurements of jet production and jet properties in pp collisions provide a test of perturbative quantum chromodynamics (pQCD) and form a baseline for similar measurements in heavy ion (A--A) collisions. In this contribution, we report recent ALICE measurements of charged-particle jet production and intra-jet properties, including mean charged-constituent m

Tim Siebert, Kai Norman Clasen, Mahdyar Ravanbakhsh, Begüm Demir

With the new generation of satellite technologies, the archives of remote sensing (RS) images are growing very fast. To make the intrinsic information of each RS image easily accessible, visual question answering (VQA) has been introduced in RS. VQA allows a user to formulate a free-form question concerning the content of RS images to extract generic informa

Sema Kazan, Cumali Yıldırım

In the present paper, we introduce screen almost semi-invariant (SASI) lightlike submanifolds of indefinite Keahler manifolds. We obtain the neccesary and sufficient condition for the induced connection to be a metric connection on SASI-lightlike submanifolds and construct an example for this manifold. Also we find some conditions for integrability of distri

Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero, Jesus Angulo

In neural networks, the property of being equivariant to transformations improves generalization when the corresponding symmetry is present in the data. In particular, scale-equivariant networks are suited to computer vision tasks where the same classes of objects appear at different scales, like in most semantic segmentation tasks. Recently, convolutional l

Yuanyang Hu, Chengxia Lei

In this paper, we study the Lotka-Volterra prey-predator models consisting of two species on finite connected graphs under Neumann condition and the condition that there is no boundary condition. We establish the global stability of the unique constant equilibrium solution of each parabolic system.

Wanfeng Zheng, Qiang Li, Xiaoyan Guo, Pengfei Wan

Text-driven image manipulation is developed since the vision-language model (CLIP) has been proposed. Previous work has adopted CLIP to design a text-image consistency-based objective to address this issue. However, these methods require either test-time optimization or image feature cluster analysis for single-mode manipulation direction. In this paper, we

Dashan Gao, Xin Yao, Qiang Yang

Federated learning (FL) has been proposed to protect data privacy and virtually assemble the isolated data silos by cooperatively training models among organizations without breaching privacy and security. However, FL faces heterogeneity from various aspects, including data space, statistical, and system heterogeneity. For example, collaborative organization

Zhongyi Ni, Feng Ji, Hang Sheng, Hui Feng

When sampling multiple signals, the correlation between the signals can be exploited to reduce the overall number of samples. In this paper, we study the sampling theory of multiple correlated signals, using correlation to sample them at the lowest sampling rate. Based on the correlation between signal sources, we model multiple continuous-time signals as co

Biswarup Paul

ALICE has measured quarkonium production in p-Pb collisions at backward ($-$4.46 $<$ $y_{\rm cms}$ $<$ $-$2.96), mid ($-$1.37 $<$ $y_{\rm cms}$ $<$ 0.43) and forward (2.03 $<$ $y_{\rm cms}$ $<$ 3.53) rapidity ($y$) regions down to zero transverse momentum ($p_{\rm T}$). The inclusive J/$\psi$ production has been studied at mid-$y$ in p-Pb interactions at $\s

Saeed Salehi

We unify Godel's First Incompleteness Theorem (1931), Tarski's Undefinability Theorem (1933), Godel-Carnap's Diagonal Lemma (1934), and Rosser's (strengthening of Godel's first) Incompleteness Theorem (1936), whose proofs resemble much and use almost the same technique.

David Baumgartner, Günter Brenn, Carole Planchette

This paper experimentally investigates the effect of viscosity on the outcomes of collisions between a regular stream of droplets and a continuous liquid jet. A broad variation of liquid viscosity of both the drop and the jet liquid is considered, keeping other material properties unchanged. To do so, only two liquid types were used: aqueous glycerol solutio

Cheng Wang, Lei Yi, Linfeng Jiang, Chao Sun

The dispersed phase in turbulence can vary from almost inviscid fluid to highly viscous fluid. By changing the viscosity of the dispersed droplet phase, we experimentally investigate how the deformability of dispersed droplets affects the global transport quantity of the turbulent emulsion. Different kinds of silicone oil are employed to result in the viscos

M. D. Gorski, S. Aalto, S. König, C. Wethers

Compact Obscured Nuclei (CONs) account for a significant fraction of the population of luminous and ultraluminous infrared galaxies (LIRGs and ULIRGs). These galaxy nuclei are compact, with radii of 10-100~pc, with large optical depths at submm and far-infrared wavelengths, and characterized by vibrationally excited HCN emission. It is not known what powers

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu

The past few years have witnessed a remarkable advance in deep learning for EEG-based sleep stage classification (SSC). However, the success of these models is attributed to possessing a massive amount of labeled data for training, limiting their applicability in real-world scenarios. In such scenarios, sleep labs can generate a massive amount of data, but l

Zhining Liu

We study the classification problem for polarized varieties with high nefvalue. We give a complete list of isomorphism classes for normal polarized varieties with high nefvalue. This generalizes classical work on the smooth case by Fujita, Beltrametti and Sommese. As a consequence we obtain that polarized varieties with slc singularities and high nefvalue, a

Peiyi Wang, Yifan Song, Tianyu Liu, Binghuai Lin

Continual relation extraction (CRE) aims to continually learn new relations from a class-incremental data stream. CRE model usually suffers from catastrophic forgetting problem, i.e., the performance of old relations seriously degrades when the model learns new relations. Most previous work attributes catastrophic forgetting to the corruption of the learned

Thomas F. Bloom, Christian Elsholtz

Any rational number can be written as the sum of distinct unit fractions. In this survey paper we review some of the many interesting questions concerning such 'Egyptian fraction' decompositions, and recent progress concerning them.

Gemma González-Torà, Markus Wittkowski, Ben Davies, Bertrand Plez

Red supergiants (RSGs) are evolved massive stars in a stage preceding core-collapse supernova. Understanding evolved-phases of these cool stars is key to understanding the cosmic matter cycle of our Universe, since they enrich the cosmos with newly formed elements. However, the physical processes that trigger mass loss in their atmospheres are still not full

Pei-Rong Han, Fan Wu, Xin-Jie Huang, Huai-Zhi Wu

Non-Hermitian (NH) extension of quantum-mechanical Hamiltonians represents one of the most significant advancements in physics. During the past two decades, numerous captivating NH phenomena have been revealed and demonstrated, but all of which can appear in both quantum and classical systems. This leads to the fundamental question: what NH signature present

Pascal Bégout, Jesús Ildefonso Díaz

This paper completes some previous studies by several authors on the finite time extinction for nonlinear Schr{\"o}dinger equation when the nonlinear damping term corresponds to the limit cases of some ``saturating non-Kerr law'' $F(|u|^2)u=\frac{a}{\varepsilon+(|u|^2)^\alpha}u,$ with $a\in\mathbb{C},$ $\varepsilon\geqslant0,$ $2\alpha=(1-m)$ and $m\in[0,1).

Zonghan Yang, Xiaoyuan Yi, Peng Li, Yang Liu

Warning: this paper contains model outputs exhibiting offensiveness and biases. Recently pre-trained language models (PLMs) have prospered in various natural language generation (NLG) tasks due to their ability to generate fairly fluent text. Nevertheless, these models are observed to capture and reproduce harmful contents in training corpora, typically toxi

Laurent Risser, Agustin Picard, Lucas Hervier, Jean-Michel Loubes

The problem of algorithmic bias in machine learning has gained a lot of attention in recent years due to its concrete and potentially hazardous implications in society. In much the same manner, biases can also alter modern industrial and safety-critical applications where machine learning are based on high dimensional inputs such as images. This issue has ho

Wentao Ding, Hao Chen, Huayu Li, Yuzhong Qu

Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years. In the generation of temporal queries, existing KGQA methods ignore the fact that some intrinsic connections between events can make them temporally related, which may limit their capability. We systematically analyze the possible

Toufik Mansour, Gökhan Yıldırım

We introduce an algorithmic approach based on generating tree method for enumerating the inversion sequences with various pattern-avoidance restrictions. For a given set of patterns, we propose an algorithm that outputs either an accurate description of the succession rules of the corresponding generating tree or an ansatz. By using this approach, we determi

David L. Donoho, Michael J. Feldman

Modern datasets are trending towards ever higher dimension. In response, recent theoretical studies of covariance estimation often assume the proportional-growth asymptotic framework, where the sample size $n$ and dimension $p$ are comparable, with $n, p \rightarrow \infty $ and $\gamma_n = p/n \rightarrow \gamma > 0$. Yet, many datasets -- perhaps most -- h

Liangdong Lu, Gaochi Zhang, Ganyu Feng, Wenzheng Ma

In this paper, we propose a sufficient condition for a family of 2-generator self-orthogonal quasi-cyclic codes with respect to Hermitian inner product. Supported in the Hermitian construction, we show algebraic constructions of good quantum codes. 30 new binary quantum codes with good parameters improving the best-known lower bounds on minimum distance in G

Heng Zhang

This paper investigates an infinite-horizon linear quadratic stochastic (LQS) optimal control problem for a class of continuous-time stochastic systems. By employing the technique of adaptive dynamic programming (ADP), we propose a novel model-free policy iteration (PI) algorithm. Without needing all information of the system coefficient matrices, the propos

Ahmet Iscen, Thomas Bird, Mathilde Caron, Alireza Fathi

We study class-incremental learning, a training setup in which new classes of data are observed over time for the model to learn from. Despite the straightforward problem formulation, the naive application of classification models to class-incremental learning results in the "catastrophic forgetting" of previously seen classes. One of the most successful exi

Mohsinul Kabir, Tasnim Ahmed, Md. Bakhtiar Hasan, Md Tahmid Rahman Laskar

Mental health research through data-driven methods has been hindered by a lack of standard typology and scarcity of adequate data. In this study, we leverage the clinical articulation of depression to build a typology for social media texts for detecting the severity of depression. It emulates the standard clinical assessment procedure Diagnostic and Statist

Felix Schuhknecht, Simon Jörz

Blockchain systems essentially consist of two levels: The network level has the responsibility of distributing an ordered stream of transactions to all nodes of the network in exactly the same way, even in the presence of a certain amount of malicious parties (byzantine fault tolerance). On the node level, each node then receives this ordered stream of trans

Mohammad Ridwan Kabir, Mohammad Ishrak Abedin, Rizvi Ahmed, Saad Bin Ashraf

Upper limb disability due to neurological disorders or other factors restricts computer interaction for affected individuals using a generic optical mouse. This work reports the findings of a comparative evaluation of Auxilio, a sensor-based wireless head-mounted Assistive Mouse Controller (AMC), that facilitates computer interaction for such individuals. Co

Oussama Jourairi, Muhammet Balcilar, Anne Lambert, François Schnitzler

End-to-end trainable models have reached the performance of traditional handcrafted compression techniques on videos and images. Since the parameters of these models are learned over large training sets, they are not optimal for any given image to be compressed. In this paper, we propose an instance-based fine-tuning of a subset of decoder's bias to improve

Zhedong Liu, Janet Van Niekerk, Haavard Rue

Evaluating the predictive performance of a statistical model is commonly done using cross-validation. Among the various methods, leave-one-out cross-validation (LOOCV) is frequently used. Originally designed for exchangeable observations, LOOCV has since been extended to other cases such as hierarchical models. However, it focuses primarily on short-range pr

Leïla Haegel, Kellie O'Neal-Ault, Quentin G. Bailey, Jay D. Tasson

An effective field theory framework, the Standard-Model Extension, is used to investigate the existence of Lorentz and CPT-violating effects during gravitational wave propagation. We implement a modified equation for the dispersion of gravitational waves, that includes isotropic, anisotropic and birefringent dispersion. Using the LIGO-Virgo-KAGRA algorithm l

Javier Videla, Ahmed Mostafa Shaaban, Elena Atroshchenko

Geometry Independent Field approximaTion (GIFT) was proposed as a generalization of Isogeometric analysis (IGA), where different types of splines are used for the parameterization of the computational domain and approximation of the unknown solution. GIFT with Non-Uniform Rational B-Splines (NUBRS) for the geometry and PHT-splines for the solution approximat

Maria Frizzarin, Giulio Visentin, Alessandro Ferragina, Elena Hayes

In April 2022, the Vistamilk SFI Research Centre organized the second edition of the "International Workshop on Spectroscopy and Chemometrics - Applications in Food and Agriculture". Within this event, a data challenge was organized among participants of the workshop. Such data competition aimed at developing a prediction model to discriminate dairy cows' di

Karolina Trokowska, Piotr Śniady

Stanley and F\'eray gave a formula for the irreducible character of the symmetric group related to a multi-rectangular Young diagram. This formula shows that the character is a polynomial in the multi-rectangular coordinates and gives an explicit combinatorial interpretation for its coefficients in terms of counting certain decorated maps (i.e., graphs drawn