April 2023 arXiv papers — page 145

Titas Chanda, Marcello Dalmonte, Maciej Lewenstein, Jakub Zakrzewski

The presence of gauge symmetry in 1+1D is known to be redundant, since it does not imply the existence of dynamical gauge bosons. As a consequence, in the continuum, the Abelian-Higgs model, the theory of bosonic matter interacting with photons, just possesses a single phase, as the higher dimensional Higgs and Coulomb phases are connected via non-perturbati

Simone Angarano, Mauro Martini, Alessandro Navone, Marcello Chiaberge

In recent years, precision agriculture has gradually oriented farming closer to automation processes to support all the activities related to field management. Service robotics plays a predominant role in this evolution by deploying autonomous agents that can navigate fields while performing tasks such as monitoring, spraying, and harvesting without human in

David Dudal, Philipe De Fabritiis, Marcelo S. Guimaraes, Giovani Peruzzo

A study of the Bell-CHSH inequality in gauge field theories is presented. By using the Kugo-Ojima analysis of the BRST charge cohomology in Fock space, the Bell-CHSH inequality is formulated in a manifestly BRST invariant way. The examples of the free four-dimensional Maxwell theory and the Abelian Higgs model are scrutinized. The inequality is probed by usi

Michael Dyck, Alistair Weld, Julian Klodmann, Alexander Kirst

During brain tumour resection, localising cancerous tissue and delineating healthy and pathological borders is challenging, even for experienced neurosurgeons and neuroradiologists. Intraoperative imaging is commonly employed for determining and updating surgical plans in the operating room. Ultrasound (US) has presented itself a suitable tool for this task,

Ioana Ciotir, Reika Fukuizumi, Dan Goreac

This paper is concerned with the existence and uniqueness of the solution for the stochastic fast logarithmic equation with Stratonovich multiplicative noise in $\mathbb{R}^{d}$ for $d\geqslant 3$. It provides an answer to a critical case (morally speaking, corresponding to the porous media operator $\Delta X^m$ for $m=0$) left as an open problem in the pape

Malte Jahn

Time series of counts are frequently analyzed using generalized integer-valued autoregressive models with conditional heteroskedasticity (INGARCH). These models employ response functions to map a vector of past observations and past conditional expectations to the conditional expectation of the present observation. In this paper, it is shown how INGARCH mode

Shunsuke Nishimura, Taku Kobayashi, Daichi Sasaki, Takeyuki Tsuji

Various techniques have been applied to visualize superconducting vortices, providing clues to their electromagnetic response. Here, we present a wide-field, quantitative imaging of the stray field of the vortices in a superconducting thin film using perfectly aligned diamond quantum sensors. Our analysis, which mitigates the influence of the sensor inhomoge

Samuel Ducros

The objective of this internship is to propose an innovative method that uses unlabelled data, i.e. data that will allow the AI to automatically learn to predict the correct outcome. To reach this stage, the steps to be followed can be defined as follows: (1) consult the state of the art and position ourself against it, (2) come up with ideas for development

Aditya Kasliwal, Pratinav Seth, Sriya Rallabandi, Sanchit Singhal

Thermal imaging has numerous advantages over regular visible-range imaging since it performs well in low-light circumstances. Super-Resolution approaches can broaden their usefulness by replicating accurate high-resolution thermal pictures using measurements from low-cost, low-resolution thermal sensors. Because of the spectral range mismatch between the ima

Carlos Areces, Raul Fervari, Andrés R. Saravia, Fernando R. Velázquez-Quesada

We introduce a novel semantics for a multi-agent epistemic operator of knowing how, based on an indistinguishability relation between plans. Our proposal is, arguably, closer to the standard presentation of knowing that modalities in classical epistemic logic. We study the relationship between this new semantics and previous approaches, showing that our sett

Ismael Akray

In 1859, Ernst E. Kummer \cite{erns} introduced the concept prime ideal and after that in 1983 this concept was generalized to prime submodules by R. McCasland \cite{mcca}. In this article, by considering complexes as a generalization of modules, I introduce the concept prime subcomplex and study some properties analogous to that of prime submodules.

Yarno Merckx, Pablo Correa, Krijn D. de Vries, Kumiko Kotera

We present a phenomenological framework for starburst-driven neutrino production via proton-proton collisions and apply it to (ultra)luminous infrared galaxies (U/LIRGs) in the Great Observatories All-Sky LIRG Survey (GOALS). The framework relates the infrared luminosity of a GOALS galaxy, derived from consistently available Herschel Space Observatory data,

Jimmy Lin, David Alfonso-Hermelo, Vitor Jeronymo, Ehsan Kamalloo

The advent of multilingual language models has generated a resurgence of interest in cross-lingual information retrieval (CLIR), which is the task of searching documents in one language with queries from another. However, the rapid pace of progress has led to a confusing panoply of methods and reproducibility has lagged behind the state of the art. In this c

Juan Molina, Jinyi Shangguan, Ran Wang, Luis C. Ho

We present new NOrthern Extended Millimeter Array (NOEMA) observations of the CO(2--1) emission in eight of the brightest Palomar-Green quasars at $z \lesssim 0.5$ to investigate the role of active galactic nuclei (AGN) feedback in luminous quasars detected at low redshifts. We detect CO(2--1) emission in three objects, from which we derive CO luminosities,

Rajesh Biswas, Asaad Daher, Arpan Das, Wojciech Florkowski

We present a new derivation of Israel-Stewart-like relativistic second-order dissipative spin hydrodynamic equations using the entropy current approach. In our analysis, we consider a general energy-momentum tensor with symmetric and anti-symmetric parts. Moreover, the spin tensor, which is not separately conserved, has a simple phenomenological form that is

Adaku Uchendu, Jooyoung Lee, Hua Shen, Thai Le

Advances in Large Language Models (e.g., GPT-4, LLaMA) have improved the generation of coherent sentences resembling human writing on a large scale, resulting in the creation of so-called deepfake texts. However, this progress poses security and privacy concerns, necessitating effective solutions for distinguishing deepfake texts from human-written ones. Alt

Hanchen Wang, Marco Madami, Jilei Chen, Hao Jia

We report the experimental observation of the spin-wave moir\'e edge and cavity modes using Brillouin light scattering spectro-microscopy in a nanostructured magnetic moir\'e lattice consisting of two twisted triangle antidot lattices based on an yttrium iron garnet thin film. Spin-wave moir\'e edge modes are detected at an optimal twist angle and with a sel

Jamie Hathaway, Alireza Rastegarpanah, Rustam Stolkin

This paper addresses the problem of robotic cutting during disassembly of products for materials separation and recycling. Waste handling applications differ from milling in manufacturing processes, as they engender considerable variety and uncertainty in the parameters (e.g. hardness) of materials which the robot must cut. To address this challenge, we prop

Jeffrey Diller, Roland Roeder

We prove an equidistribution result for iterated preimages of curves by a large class of rational maps $f:\mathbb{CP}^2\dashrightarrow\mathbb{CP}^2$ that cannot be birationally conjugated to algebraically stable maps. The maps, which include recent examples with transcendental first dynamical degree, are distinguished by the fact that they have constant Jaco

Marc Jayson Baucas, Petros Spachos

Device monitoring services have increased in popularity with the evolution of recent technology and the continuously increased number of Internet of Things (IoT) devices. Among the popular services are the ones that use device location information. However, these services run into privacy issues due to the nature of data collection and transmission. In this

Manuel Zahn, Douglas P. Perrin

Annotation and labeling of images are some of the biggest challenges in applying deep learning to medical data. Current processes are time and cost-intensive and, therefore, a limiting factor for the wide adoption of the technology. Additionally validating that measured performance improvements are significant is important to select the best model. In this p

Takayuki Ishizaki, Taku Nishino, Aranya Chakrabortty

We study the equilibrium-independent (EI) passivity of a nonlinear power system composed of two-axis generator models. The model of our interest consists of a feedback inter-connection of linear and nonlinear subsystems, called mechanical and electromagnetic subsystems. We mathematically prove the following three facts by analyzing the nonlinear electromagne

Jona Bühler, Peter Stoffer

The translation of experimental limits on the neutron electric dipole moment into constraints on heavy $CP$-violating physics beyond the Standard Model requires knowledge about non-perturbative matrix elements of effective operators, which ideally should be computed in lattice QCD. However, this necessitates a matching calculation as an interface to the effe

Shu-Min Wu, Xiao-Wei Fan, Rui-Di Wang, Hao-Yu Wu

Previous studies have shown that the Hawking effect always destroys quantum correlations and the fidelity of quantum teleportation in the Schwarzschild black hole. Here, we investigate the fidelity of quantum teleportation of Dirac fields between users in Schwarzschild spacetime. We find that, with the increase of the Hawking temperature, the fidelity of qua

Rebekka Garreis, Chuyao Tong, Jocelyn Terle, Max Josef Ruckriegel

Bilayer graphene is a promising platform for electrically controllable qubits in a two-dimensional material. Of particular interest is the ability to encode quantum information in the so-called valley degree of freedom, a two-fold orbital degeneracy that arises from the symmetry of the hexagonal crystal structure. The use of valleys could be advantageous, as

Xinwei Liu, Kiran Raja, Renfang Wang, Hong Qiu

Latent fingerprints are among the most important and widely used evidence in crime scenes, digital forensics and law enforcement worldwide. Despite the number of advancements reported in recent works, we note that significant open issues such as independent benchmarking and lack of large-scale evaluation databases for improving the algorithms are inadequatel

Giuseppe Ancona, Mattia Cavicchi, Robert Laterveer, Giulia Saccà

We show that the hyper-K\"ahler varieties of OG10-type constructed by Laza-Sacc\`a-Voisin (LSV) verify the Lefschetz standard conjecture. This is an application of a more general result, stating that certain Lagrangian fibrations verify this conjecture. The main technical assumption of this general result is that the Lagrangian fibration satisfies the hypoth

Takahiro Ohno, Kazuki Tokuda, Ayu Konishi, Takeru Matsumoto

The nature of molecular clouds and their statistical behavior in subsolar metallicity environments are not fully explored yet. We analyzed data from an unbiased CO($J$ = 2-1) survey at the spatial resolution of ~2 pc in the northern region of the Small Magellanic Cloud with the Atacama Compact Array to characterize the CO cloud properties. A cloud-decomposit

Francesco Marchetti, Emma Perracchione, Anna Volpara, Anna Maria Massone

Variably scaled kernels and mapped bases constructed via the so-called fake nodes approach are two different strategies to provide adaptive bases for function interpolation. In this paper, we focus on kernel-based interpolation and we present what we call mapped variably scaled kernels, which take advantage of both strategies. We present some theoretical ana

T. Cecil, C. Albert, A. J. Anderson, P. S. Barry

Line Intensity Mapping (LIM) is a new observational technique that uses low-resolution observations of line emission to efficiently trace the large-scale structure of the Universe out to high redshift. Common mm/sub-mm emission lines are accessible from ground-based observatories, and the requirements on the detectors for LIM at mm-wavelengths are well match

Chunyu Guo, Glenn Wagner, Carsten Putzke, Dong Chen

Spontaneously broken symmetries are at the heart of many phenomena of quantum matter and physics more generally. However, determining the exact symmetries broken can be challenging due to imperfections such as strain, in particular when multiple electronic orders form complex interactions. This is exemplified by charge order in some kagome systems, which are

Hanrong Ye, Dan Xu

This report serves as a supplementary document for TaskPrompter, detailing its implementation on a new joint 2D-3D multi-task learning benchmark based on Cityscapes-3D. TaskPrompter presents an innovative multi-task prompting framework that unifies the learning of (i) task-generic representations, (ii) task-specific representations, and (iii) cross-task inte

Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik

The quantitative structure-activity relationship (QSAR) regression model is a commonly used technique for predicting biological activities of compounds using their molecular descriptors. Predictions from QSAR models can help, for example, to optimize molecular structure; prioritize compounds for further experimental testing; and estimate their toxicity. In a

Mohamed Amine Chatti, Mouadh Guesmi, Laura Vorgerd, Thao Ngo

Despite the acknowledgment that the perception of explanations may vary considerably between end-users, explainable recommender systems (RS) have traditionally followed a one-size-fits-all model, whereby the same explanation level of detail is provided to each user, without taking into consideration individual user's context, i.e., goals and personal charact

Mareike Berger, Pieter Rein ten Wolde

Initiating replication synchronously at multiple origins of replication allows the bacterium Escherichia coli to divide even faster than the time it takes to replicate the entire chromosome in nutrient-rich environments. What mechanisms give rise to synchronous replication initiation remains however poorly understood. Via mathematical modelling, we identify

Zhuofan Zong, Dongzhi Jiang, Guanglu Song, Zeyue Xue

In this paper, we propose a new paradigm, named Historical Object Prediction (HoP) for multi-view 3D detection to leverage temporal information more effectively. The HoP approach is straightforward: given the current timestamp t, we generate a pseudo Bird's-Eye View (BEV) feature of timestamp t-k from its adjacent frames and utilize this feature to predict t

Vlad Dedu, Anton Poluektov

Measurement of $CP$-violating observables in semileptonic decays is a sensitive null-test of the Standard Model: any $CP$ violation would be an unambiguous sign of New Physics effects. The model-independent technique to measure parity and $CP$-odd observables in the $B\to D^{\ast}\mu\nu$ decays is proposed, which effectively cancels out parity-even terms in

Felix Finster

The linearized field equations for causal fermion systems in Minkowski space are analyzed systematically using methods of functional analysis and Fourier analysis. Taking into account a direction-dependent local phase freedom, we find a multitude of homogeneous solutions. The time evolution of the inhomogeneous equations is studied. It leads to the dynamical

Tsuyoshi Baba, Kosuke Nishida, Kyosuke Nishida

Automatic image editing has great demands because of its numerous applications, and the use of natural language instructions is essential to achieving flexible and intuitive editing as the user imagines. A pioneering work in text-driven image editing, StyleCLIP, finds an edit direction in the CLIP space and then edits the image by mapping the direction to th

Jian Huang, Deng-Gao Lai, Jie-Qiao Liao

Quantum squeezing is an important resource in modern quantum technologies, such as quantum precision measurement and continuous-variable quantum information processing. The generation of squeezed states of mechanical modes is a significant task in cavity optomechanics. Motivated by recent interest in multimode optomechanics, it becomes an interesting topic t

Jihan Yang, Runyu Ding, Weipeng Deng, Zhe Wang

We propose a lightweight and scalable Regional Point-Language Contrastive learning framework, namely \textbf{RegionPLC}, for open-world 3D scene understanding, aiming to identify and recognize open-set objects and categories. Specifically, based on our empirical studies, we introduce a 3D-aware SFusion strategy that fuses 3D vision-language pairs derived fro

Pengwan Yang, Cees G. M. Snoek, Yuki M. Asano

In this paper we address the task of finding representative subsets of points in a 3D point cloud by means of a point-wise ordering. Only a few works have tried to address this challenging vision problem, all with the help of hard to obtain point and cloud labels. Different from these works, we introduce the task of point-wise ordering in 3D point clouds thr

Haihong He, Xiaoxia Wang

We prove two single-parameter q-supercongruences which were recently conjectured by Guo, and establish their further extensions with one more parameter. Crucial ingredients in the proof are the terminating form of q-binomial theorem and a Karlsson-Minton type summation formula due to Gasper. Incidentally, an assertion of Wang, Li and Tang is also verified by

Jiaxu Xing, Giovanni Cioffi, Javier Hidalgo-Carrió, Davide Scaramuzza

Drones have the potential to revolutionize power line inspection by increasing productivity, reducing inspection time, improving data quality, and eliminating the risks for human operators. Current state-of-the-art systems for power line inspection have two shortcomings: (i) control is decoupled from perception and needs accurate information about the locati

Yanis Labrak, Adrien Bazoge, Richard Dufour, Mickael Rouvier

In recent years, pre-trained language models (PLMs) achieve the best performance on a wide range of natural language processing (NLP) tasks. While the first models were trained on general domain data, specialized ones have emerged to more effectively treat specific domains. In this paper, we propose an original study of PLMs in the medical domain on French l

Guang-Yong Chen, Yong-Hang Yu, Min Gan, C. L. Philip Chen

Random functional-linked types of neural networks (RFLNNs), e.g., the extreme learning machine (ELM) and broad learning system (BLS), which avoid suffering from a time-consuming training process, offer an alternative way of learning in deep structure. The RFLNNs have achieved excellent performance in various classification and regression tasks, however, the

Andrew James Murray, Joshua Rogers

New (e, 2e) differential cross section measurements from krypton are presented in the perpendicular plane, where the incident electron beam is orthogonal to the scattered and ejected electrons that map out a detection plane. New data were obtained at incident energies from 30 eV to 120 eV above the ionization potential (IP), the experiment being configured t

Anirban Chakraborty, Sarani Bhattacharya, Sayandeep Saha, Debdeep Mukhopadhyay

In this paper, we analyse the results and claims presented in the paper \emph{`Are Randomized Caches Truly Random? Formal Analysis of Randomized Partitioned Caches'}, presented at HPCA conference 2023. In addition, we also analyse the applicability of `Bucket and Ball' analytical model presented in MIRAGE (Usenix Security 2021) for its security estimation. W

Aryan, Bowen Li, Sebastian Scherer, Yun-Jou Lin

Indoor relocalization is vital for both robotic tasks like autonomous exploration and civil applications such as navigation with a cell phone in a shopping mall. Some previous approaches adopt geometrical information such as key-point features or local textures to carry out indoor relocalization, but they either easily fail in an environment with visually si

Manolis Katsaragakis, Christos Baloukas, Lazaros Papadopoulos, Verena Kantere

The Intel Optane DC Persistent Memory (DCPM) is an attractive novel technology for building storage systems for data intensive HPC applications, as it provides lower cost per byte, low standby power and larger capacities than DRAM, with comparable latency. This work provides an in-depth evaluation of the energy consumption of the Optane DCPM, using well-esta

L. Vorabbi, D. Maltoni, S. Santi

Binary Neural Networks (BNNs) can significantly accelerate the inference time of a neural network by replacing its expensive floating-point arithmetic with bitwise operations. Most existing solutions, however, do not fully optimize data flow through the BNN layers, and intermediate conversions from 1 to 16/32 bits often further hinder efficiency. We propose

Daniel John Mannion, Anthony Joseph Kenyon

Bio-inspired computing has focused on neuron and synapses with great success. However, the connections between these, the dendrites, also play an important role. In this paper, we investigate the motivation for replicating dendritic computation and present a framework to guide future attempts in their construction. The framework identifies key properties of

Jérôme Rutinowski, Hazem Youssef, Sven Franke, Irfan Fachrudin Priyanta

This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, barrels) over a network of, in this example, six RGB cameras. This framework, makes use of multiple sensors, data pipelines and data annotation procedures, and is described in detail

Chenfeng Zhu, Dachun Yang, Wen Yuan

Let $X$ be a ball Banach function space on $\mathbb{R}^n$. In this article, under some mild assumptions about both $X$ and the boundedness of the Hardy--Littlewood maximal operator on both $X$ and the associate space of its convexification, the authors successfully recover the homogeneous ball Banach Sobolev semi-norm $\|\,|\nabla f|\,\|_X$ via the functiona

Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, Dacheng Tao

Deep generative models have demonstrated successful applications in learning non-linear data distributions through a number of latent variables and these models use a nonlinear function (generator) to map latent samples into the data space. On the other hand, the nonlinearity of the generator implies that the latent space shows an unsatisfactory projection o

Aleksandr Safin, Daniel Duckworth, Mehdi S. M. Sajjadi

The Scene Representation Transformer (SRT) is a recent method to render novel views at interactive rates. Since SRT uses camera poses with respect to an arbitrarily chosen reference camera, it is not invariant to the order of the input views. As a result, SRT is not directly applicable to large-scale scenes where the reference frame would need to be changed

Xiang Wang, Shiwei Zhang, Zhiwu Qing, Changxin Gao

Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they generally suffer from two limitations: i) the matching procedure between local frames tends to be inaccurate due to the lack of guidance to force long-range temporal perception; ii) exp

Johannes Carmesin, Jan Kurkofka

We offer a new structural basis for the theory of 3-connected graphs, providing a unique decomposition of every such graph into parts that are either quasi 4-connected, wheels, or thickened $K_{3,m}$'s. Our construction is explicit, canonical, and has the following applications: we obtain a new theorem characterising all finite Cayley graphs as either essent

Nikita Samarin, Shayna Kothari, Zaina Siyed, Oscar Bjorkman

The California Consumer Privacy Act (CCPA) provides California residents with a range of enhanced privacy protections and rights. Our research investigated the extent to which Android app developers comply with the provisions of the CCPA that require them to provide consumers with accurate privacy notices and respond to "verifiable consumer requests" (VCRs)

Mariam Kamal, Josu Arteche

This paper investigates economic convergence in terms of real income per capita among the autonomous regions of Spain. In order to converge, the series should cointegrate. This necessary condition is checked using two testing strategies recently proposed for fractional cointegration, finding no evidence of cointegration, which rules out the possibility of co

Rachid Caich

Let $\varepsilon >0$. Let $f$ be a Steinhaus or Rademacher random multiplicative function. We prove that we have almost surely, as $x \to +\infty$, $$ \sum_{n \leqslant x} f(n) \ll \sqrt{x} (\log_2 x)^{\frac{3}{4}+ \varepsilon}. $$

Tomislav Piskor, Peter Pinski, Thilo Mast, Vladimir V. Rybkin

In this work, we propose a multi-scale protocol for routine theoretical studies of chemical reaction mechanisms. The initial reaction paths of our investigated systems are sampled using the Nudged-Elastic Band (NEB) method driven by a cheap electronic structure method. Forces recalculated at the more accurate electronic structure theory for a set of points o

Longfei Yin, Ziang Liu, Bhavani Shankar M. R., Mohammad Alaee-Kerahroodi

Extreme crowding of electromagnetic spectrum in recent years has led to the challenges in designing sensing and communications systems. Both systems require a broad range of bandwidth, thus resulting in competing interests in exploiting the spectrum. Efficient spectrum and hardware utilization have led to the emergence of integrated sensing and communication

Syed Masood A. S. Bukhari, Behnam Pourhassan, Houcine Aounallah, Li-Gang Wang

Thermodynamic Riemannian geometry provides great insights into the microscopic structure of black holes (BHs). One such example is the Ruppeiner geometry which is the metric space comprising the second derivatives of entropy with respect to other extensive variables of the system. Reissner-Nordstr\"om black holes (RNBHs) are known to be endowed with a flat R

Hai-Jun Li, Ying-Quan Peng, Wei Chao, Yu-Feng Zhou

The supermassive black holes (SMBHs) are ubiquitous in the center of galaxies, although the origin of their massive seeds is still unknown. In this paper, we investigate the SMBHs formation from the QCD axion bubbles. In this case, the primordial black holes (PBHs) are considered as the seeds of SMBHs, which are generated from the QCD axion bubbles due to an

Peter J. Haine, Tim Holzschuh, Sebastian Wolf

This paper has two main goals. First, we prove nonabelian refinements of basechange theorems in \'etale cohomology (i.e., prove analogues of the classical statements for sheaves of spaces). Second, we apply these theorems to prove a number of results about the \'etale homotopy type. Specifically, we prove nonabelian refinements of the smooth basechange theor

Sizhong Zhou, Hongxia Liu

A spanning subgraph $F$ of $G$ is called a path factor if every component of $F$ is a path of order at least 2. Let $k\geq2$ be an integer. A $P_{\geq k}$-factor of $G$ means a path factor in which every component has at least $k$ vertices. A graph $G$ is called a $P_{\geq k}$-factor avoidable graph if for any $e\in E(G)$, $G$ has a $P_{\geq k}$-factor avoid

Vladimir Gorchakov

In this paper we study a specific class of actions of a $2$-torus $\mathbb{Z}_2^k$ on manifolds, namely, the actions of complexity one in general position. We describe the orbit space of equivariantly formal $2$-torus actions of complexity one in general position and restricted complexity one actions in the case of small covers. It is observed that the orbit

Zhao Xu, Daniel Onoro Rubio, Giuseppe Serra, Mathias Niepert

Deep latent generative models have attracted increasing attention due to the capacity of combining the strengths of deep learning and probabilistic models in an elegant way. The data representations learned with the models are often continuous and dense. However in many applications, sparse representations are expected, such as learning sparse high dimension

Mikhail Piotrovich, Stanislava Buliga, Tinatin Natsvlishvili

We estimated the spin values of the supermassive black holes (SMBHs) of the active galactic nuclei (AGN) for a large set of Narrow Line Seyfert 1 (NLS1) galaxies assuming the inclination angle between the line of sight and the axis of the accretion disk to be approximately 45 degrees. We found that for these objects the spin values are on average less than f

Timm Hess, Eli Verwimp, Gido M. van de Ven, Tinne Tuytelaars

Continual learning research has shown that neural networks suffer from catastrophic forgetting "at the output level", but it is debated whether this is also the case at the level of learned representations. Multiple recent studies ascribe representations a certain level of innate robustness against forgetting -- that they only forget minimally in comparison

Sijie Wang, Qiyu Kang, Rui She, Wei Wang

LiDAR relocalization plays a crucial role in many fields, including robotics, autonomous driving, and computer vision. LiDAR-based retrieval from a database typically incurs high computation storage costs and can lead to globally inaccurate pose estimations if the database is too sparse. On the other hand, pose regression methods take images or point clouds

Sergio Abriola, Santiago Cifuentes, Nina Pardal, Edwin Pin

Repairing inconsistent knowledge bases is a task that has been assessed, with great advances over several decades, from within the knowledge representation and reasoning and the database theory communities. As information becomes more complex and interconnected, new types of repositories, representation languages and semantics are developed in order to be ab

Maurus Item, Juan Gómez-Luna, Yuxin Guo, Geraldo F. Oliveira

Processing-in-memory (PIM) promises to alleviate the data movement bottleneck in modern computing systems. However, current real-world PIM systems have the inherent disadvantage that their hardware is more constrained than in conventional processors (CPU, GPU), due to the difficulty and cost of building processing elements near or inside the memory. As a res

Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc Van Gool

Autonomous driving requires a structured understanding of the surrounding road network to navigate. One of the most common and useful representation of such an understanding is done in the form of BEV lane graphs. In this work, we use the video stream from an onboard camera for online extraction of the surrounding's lane graph. Using video, instead of a sing

Giovanni Grieco, Giovanni Iacovelli, Daniele Pugliese, Domenico Striccoli

Sixth-Generation (6G) networks are set to provide reliable, widespread, and ultra-low-latency mobile broadband communications for a variety of industries. In this regard, the Internet of Drones (IoD) represents a key component for the development of 3D networks, which envisions the integration of terrestrial and non-terrestrial infrastructures. The recent em

Anne-Maria Visuri, Jeffrey Mohan, Shun Uchino, Meng-Zi Huang

We study the current-voltage characteristics of a superconducting junction with particle losses at the contacts. We adopt the Keldysh formalism to compute the steady-state current for varying transmission of the contact. In the low transmission regime, the dissipation leads to an enhancement of the current at low bias, a nonmonotonic dependence of current on

Michalis Pachilakis, Savino Dambra, Iskander Sanchez-Rola, Leyla Bilge

In the past decade, global warming made several headlines and turned the attention of the whole world to it. Carbon footprint is the main factor that drives greenhouse emissions up and results in the temperature increase of the planet with dire consequences. While the attention of the public is turned to reducing carbon emissions by transportation, food cons

Eric Rozan, Sebastian Bouzat, Marcelo N Kuperman

Lately, concepts such as lockdown, quarantine, and social distancing have become very relevant since they have been associated with essential measures in the prevention and mitigation of COVID-19. While some conclusions about the effectiveness of these measures could be drawn from field observations, many mathematical models aimed to provide some clues. Howe

Christian Malacaria, Jeremy Heyl, Victor Doroshenko, Sergey S. Tsygankov

Accreting X-ray pulsars (XRPs) are presumably ideal targets for polarization measurements, as their high magnetic field strength is expected to polarize the emission up to a polarization degree of ~80%. However, such expectations are being challenged by recent observations of XRPs with the Imaging X-ray Polarimeter Explorer (IXPE). Here we report on the resu

Wlodzimierz Bryc, Yizao Wang

We consider Motzkin paths of length $L$, not fixed at zero at both end points, with constant weights on the edges and general weights on the end points. We investigate, as the length $L$ tends to infinity, the limit behaviors of (a) boundary measures induced by the weights on both end points and (b) the segments of the sampled Motzkin path viewed as a proces

E. A. Bespalov, I. Yu. Mogilnykh, K. V. Vorob'ev

We study nowhere-zero integer eigenvectors of the block graphs of Steiner triple systems and the Johnson graphs. For the first eigenvalue we obtain the minimums of $L_{\infty}$-norm for several infinite series of Johnson graphs, including J(n,3) as well as general upper and lower bounds. The minimization of $L_{\infty}$-norm for nowhere-zero integer eigenvec

Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin Vechev

Stabilizer simulation can efficiently simulate an important class of quantum circuits consisting exclusively of Clifford gates. However, all existing extensions of this simulation to arbitrary quantum circuits including non-Clifford gates suffer from an exponential runtime. To address this challenge, we present a novel approach for efficient stabilizer simul

Ziqian Hua, Zhiyuan Li, Mengfei Zhang, Zhuo Chen

Elemental abundances are key to our understanding of star formation and evolution in the Galactic center. Previous work on this topic has been based on infrared (IR) observations, but X-ray observations have the potential of constraining the abundance of heavy elements, mainly through their K-shell emission lines. Using 5.7 Ms Chandra observations, we provid

Masoud Taherijam, Saiedeh Marashi, Alireza Tondro, Hamidreza Abdolvand

One of the main degradation mechanisms of the zirconium alloys used in nuclear reactors is hydrogen embrittlement and hydride formation. The formation of zirconium hydrides is accompanied by a transformation strain, the effects of which on the development of localized deformation zones are not well-understood. This study uses a crystal plasticity finite elem

Anna Vizziello, Maurizio Magarini, Pietro Savazzi, Laura Galluccio

The Internet of Medical Things (IoMT) paradigm will enable next generation healthcare by enhancing human abilities, supporting continuous body monitoring and restoring lost physiological functions due to serious impairments. This paper presents intra-body communication solutions that interconnect implantable devices for application to the nervous system, cha

Zhao Xu, Carolin Lawrence, Ammar Shaker, Raman Siarheyeu

Quantifying predictive uncertainty of neural networks has recently attracted increasing attention. In this work, we focus on measuring uncertainty of graph neural networks (GNNs) for the task of node classification. Most existing GNNs model message passing among nodes. The messages are often deterministic. Questions naturally arise: Does there exist uncertai

Maolin Luo, Xiang Zhang

Clinical evidence encompasses the associations and impacts between patients, interventions (such as drugs or physiotherapy), problems, and outcomes. The goal of recommending clinical evidence is to provide medical practitioners with relevant information to support their decision-making processes and to generate new evidence. Our specific task focuses on reco

Deepawali Sharma, Vedika Gupta, Vivek Kumar Singh

The increase in abusive content on online social media platforms is impacting the social life of online users. Use of offensive and hate speech has been making so-cial media toxic. Homophobia and transphobia constitute offensive comments against LGBT+ community. It becomes imperative to detect and handle these comments, to timely flag or issue a warning to u

Stefano Peluchetti

The dynamic Schr\"odinger bridge problem seeks a stochastic process that defines a transport between two target probability measures, while optimally satisfying the criteria of being closest, in terms of Kullback-Leibler divergence, to a reference process. We propose a novel sampling-based iterative algorithm, the iterated diffusion bridge mixture (IDBM) pro

Yukang Cao, Yan-Pei Cao, Kai Han, Ying Shan

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by recent methods on text-guided 3D common object generation, generating high-quality human avatars remains an open challenge due to the complexity of the human body's shape, pose, and ap

Felix Agner, Pauline Kergus, Anders Rantzer, Sophie Tarbouriech

This paper aims at coordinating interconnected agents where the control input of each agent is limited by the control input of others. In that sense, the systems have to share a limited resource over a network. Such problems can arise in different areas and it is here motivated by a simplified district heating example. When the shared resource is insufficien

Xiong Fan

We prove a general approximate quantization rule $ \int_{L_{E}}^{R_{E}}k_0(x)$ $dx=(N+\frac{1}{2})\pi $ or $ \oint k_0(x)$ $dx=(2N+1)\pi $ (including both forward and backward processes) for the bound states in the potential well of the $n$th-order Schr\"{o}dinger equations $ e^{-i\pi n/2}{{}\frac{d^n\Psi(x)}{d x^n} } =[E-{} V(x)]\Psi(x) ,$ where ${} k_0(x)=

Ankit Yadav, Shubham Chandel, Sushant Chatufale, Anil Bandhakavi

Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual hate speech analysis dataset for English, Hindi, Arabic, French, German and Spanish languages for multiple domains across hate speech - Abuse, Racism, Sexism, Religious Hate and Extremism. To the bes

S. P. Behera, D. K. Mishra, P. K. Netrakanti, R. Sehgal

We present an analysis on the sensitivity to the active-sterile neutrino mixing with Germanium (Ge) and Silicon (Si) detectors in the context of the proposed coherent elastic neutrino-nucleus experiment in India. The study has been carried out with 3 (active) $+$ 1 (sterile) neutrino oscillation model. It is observed that the measurements that can be carried

Şenay Bulut, Pınar İnselöz

The present paper deals with the generalized symmetric metric connection defined on para-Sasaki-like manifolds. We derive a relation between the Levi-Civita connection and the generalized symmetric metric conneciton on the considered manifold. We investigate the curvature tensor, the Ricci tensor and scalar curvature tensor with respect to the generalized sy

Soumyadip Sarkar

Reinforcement learning (RL) is a subfield of machine learning that has been used in many fields, such as robotics, gaming, and autonomous systems. There has been growing interest in using RL for quantitative trading, where the goal is to make trades that generate profits in financial markets. This paper presents the use of RL for quantitative trading and rep

Sicong Pan, Hao Hu, Hui Wei, Nils Dengler

Existing view planning systems either adopt an iterative paradigm using next-best views (NBV) or a one-shot pipeline relying on the set-covering view-planning (SCVP) network. However, neither of these methods can concurrently guarantee both high-quality and high-efficiency reconstruction of 3D unknown objects. To tackle this challenge, we introduce a crucial

Jaya Chaturvedi, Sumithra Velupillai, Robert Stewart, Angus Roberts

Pain is a common reason for accessing healthcare resources and is a growing area of research, especially in its overlap with mental health. Mental health electronic health records are a good data source to study this overlap. However, much information on pain is held in the free text of these records, where mentions of pain present a unique natural language

Xiong-Bin Yan, Zhi-Qin John Xu, Zheng Ma

The use of Physics-informed neural networks (PINNs) has shown promise in solving forward and inverse problems of fractional diffusion equations. However, due to the fact that automatic differentiation is not applicable for fractional derivatives, solving fractional diffusion equations using PINNs requires addressing additional challenges. To address this iss