January 2022 arXiv papers — page 65

Matteo Castiglioni, Alessandro Nuara, Giulia Romano, Giorgio Spadaro

In online marketing, the advertisers aim to balance achieving high volumes and high profitability. The companies' business units address this tradeoff by maximizing the volumes while guaranteeing a minimum Return On Investment (ROI) level. Such a task can be naturally modeled as a combinatorial optimization problem subject to ROI and budget constraints that

Yuval Yifrach

H. Weyl proved in \cite{Weyl} that integer evaluations of polynomials are equidistributed mod 1 whenever at least one of the non-free coefficients is irrational. We use Weyl's result to prove a higher dimensional analogue of this fact. Namely, we prove that evaluations of polynomials on lattice points are equidistributed mod 1 whenever at least one of the no

Richmond Opoku-Sarkodie, Ferenc A. Bartha, Mónika Polner, Gergely Röst

SIRS models capture transmission dynamics of infectious diseases for which immunity is not lifelong. Extending these models by a W compartment for individuals with waning immunity, the boosting of the immune system upon repeated exposure may be incorporated. Previous analyses assumed identical waning rates from R to W and from W to S. This implicitly assumes

Sergey N. Pozdnyakov, Michele Ceriotti

Graph neural networks (GNN) are very popular methods in machine learning and have been applied very successfully to the prediction of the properties of molecules and materials. First-order GNNs are well known to be incomplete, i.e., there exist graphs that are distinct but appear identical when seen through the lens of the GNN. More complicated schemes have

Zhi Qiao, Xianbo Shi, Yudong Yao, Michael J. Wojcik

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, their computational cost has hindered their wider adoption.

Giovanni De Toni, Bruno Lepri, Andrea Passerini

Being able to provide counterfactual interventions - sequences of actions we would have had to take for a desirable outcome to happen - is essential to explain how to change an unfavourable decision by a black-box machine learning model (e.g., being denied a loan request). Existing solutions have mainly focused on generating feasible interventions without pr

Nazanin Hoghooghi, Sida Xing, Peter Chang, Daniel Lesko

Mid-infrared (MIR) spectrometers are invaluable tools for molecular fingerprinting and hyper-spectral imaging. Among the available spectroscopic approaches, GHz MIR dual-comb absorption spectrometers have the potential to simultaneously combine the high-speed, high spectral resolution, and broad optical bandwidth needed to accurately study complex, transient

Guillaume Bal, Simon Becker, Alexis Drouot

We study the propagation of wavepackets along curved interfaces between topological, magnetic materials. Our Hamiltonian is a massive Dirac operator with a magnetic potential. We construct semiclassical wavepackets propagating along the curved interface as adiabatic modulations of straight edge states under constant magnetic fields. While in the magnetic-fre

C. N. Murphy, L. Toledo Tude, P. R. Eastham

Solids can be cooled by driving impurity ions with lasers, allowing them to transfer heat from the lattice phonons to the electromagnetic surroundings. This exemplifies a quantum thermal machine, which uses a quantum system as a working medium to transfer heat between reservoirs. We review the derivation of the Bloch-Redfield equation for a quantum system co

Alexandros Haliassos, Rodrigo Mira, Stavros Petridis, Maja Pantic

One of the most pressing challenges for the detection of face-manipulated videos is generalising to forgery methods not seen during training while remaining effective under common corruptions such as compression. In this paper, we examine whether we can tackle this issue by harnessing videos of real talking faces, which contain rich information on natural fa

Cole Hawkins, Alec Koppel, Zheng Zhang

A fundamental challenge in Bayesian inference is efficient representation of a target distribution. Many non-parametric approaches do so by sampling a large number of points using variants of Markov Chain Monte Carlo (MCMC). We propose an MCMC variant that retains only those posterior samples which exceed a KSD threshold, which we call KSD Thinning. We estab

Giorgio Domenichini, O. Anatole von Lilienfeld

We propose to relax geometries throughout chemical compound space (CCS) using alchemical perturbation density functional theory (APDFT). APDFT refers to perturbation theory involving changes in nuclear charges within approximate solutions to Schr\"odinger's equation. We give an analytical formula to calculate the mixed second order energy derivatives with re

Vladimir Georgiev, Hideo Kubo

In this work we study the global existence for 3d semilinear wave equation with non-negative potential satisfying generic decay assumptions. In the supercritical case we establish the small data global existence result. The approach is based on appropriate conformal energy estimate in combination with Hardy inequality for conformal energy on space - like sur

Feihu Jin, Jinliang Lu, Jiajun Zhang, Chengqing Zong

Recently, prompt learning has become a new paradigm to utilize pre-trained language models (PLMs) and achieves promising results in downstream tasks with a negligible increase of parameters. The current usage of discrete and continuous prompts assumes that the prompt is fixed for a specific task and all samples in the task share the same prompt. However, a t

Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Michael Baron

Detecting relevant changes in dynamic time series data in a timely manner is crucially important for many data analysis tasks in real-world settings. Change point detection methods have the ability to discover changes in an unsupervised fashion, which represents a desirable property in the analysis of unbounded and unlabeled data streams. However, one limita

Yan Zhao, Lingjun Zhao, Zhong Liu, Dewen Hu

Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challenging task in SAR Automatic Target Recognition (SAR ATR) areas due to aircraft's extremely discrete appearance, obvious intraclass variation, small size and serious background's interference. In this paper, a single-shot detector namely Attentional Feature Refinement and Alignment Networ

Mohsen Raoufi, Heiko Hamann, Pawel Romanczuk

The tradeoff between accuracy and speed is considered fundamental to individual and collective decision-making. In this paper, we focus on collective estimation as an example of collective decision-making. The task is to estimate the average scalar intensity of a desired feature in the environment. The solution we propose consists of exploration and exploita

T. Adamantopoulos, M. Merte, D. Go, F. Freimuth

Here, we report first principles calculations and analysis of laser-induced photocurrents at the surface of a prototype Rashba system. By referring to Keldysh non-equilibrium formalism combined with the Wannier interpolation scheme we perform first-principles electronic structure calculations of a prototype BiAg$_2$ surface alloy, which is a well-known mater

Hafiz Zeeshan Iqbal Khan, Jahanzeb Rajput, Jamshed Riaz

In this paper, a reconfigurable control scheme for a generalized class of multicopters is presented to overcome single or multiple rotor failures. In a multicopter, the rotor failure heavily affects its dynamics and thus its controllability. Limited controllability leads to limited or no reconfigurability. \emph{Available Control Authority Index} has been re

Ajay Soni, Pratik Padamwar, Krishna Reddy Konda

In this paper we present a novel approach for lane detection and segmentation using generative models. Traditionally discriminative models have been employed to classify pixels semantically on a road. We model the probability distribution of lanes and road symbols by training a generative adversarial network. Based on the learned probability distribution, co

Violetta Weger, Niklas Gassner, Joachim Rosenthal

The improvements on quantum technology are threatening our daily cybersecurity, as a capable quantum computer can break all currently employed asymmetric cryptosystems. In preparation for the quantum-era the National Institute of Standards and Technology (NIST) has initiated in 2016 a standardization process for public-key encryption (PKE) schemes, key-encap

Alexander K. Dmitriev, Anton K. Vershovskii

The response of the level anti-crossing signal to a quasi-resonant radio-frequency field, which appears in a zero magnetic field at NV color centers in diamond, is investigated. It is shown that the complex structure of this response can be explained by the Autler-Townes splitting. The possibility of controlling the parameters of the level anti-crossing sign

Grahame Erskine, James Tuite

The search for the smallest possible $d$-regular graph of girth $g$ has a long history, and is usually known as the cage problem. This problem has a natural extension to hypergraphs, where we may ask for the smallest number of vertices in a $d$-regular, $r$-uniform hypergraph of given (Berge) girth $g$. We show that these two problems are in fact very closel

Satya Prakash Nayak, Daniel Neider, Rajarshi Roy, Martin Zimmermann

It is widely accepted that every system should be robust in that ``small'' violations of environment assumptions should lead to ``small'' violations of system guarantees, but it is less clear how to make this intuition mathematically precise. While significant efforts have been devoted to providing notions of robustness for Linear Temporal Logic (LTL), branc

Carsten Wiecher, Philipp Tendyra, Carsten Wolff

Various stakeholders with different backgrounds are involved in Smart City projects. These stakeholders define the project goals, e.g., based on participative approaches, market research or innovation management processes. To realize these goals often complex technical solutions must be designed and implemented. In practice, however, it is difficult to synch

Marcin Bury, Francesco Hautmann, Sergio Leal-Gomez, Ignazio Scimemi

Transverse momentum dependent (TMD) distributions match collinear parton density functions (PDF) in the limit of small transverse distances, which is accounted for by global extractions of TMD distributions. We study the influence of the collinear PDF value and uncertainties on the determination of unpolarized TMD distributions and the description of Drell-Y

Rumi Melih Pelen

In this paper, several classes of three-weight ternary linear codes from non-weakly regular dual-bent functions are constructed based on a generic construction method. Instead of the whole space, we use the subspaces $B_+(f)$ or $B_-(f)$ associated with a ternary non-weakly regular dual-bent function $f$. Unusually, we use the pre-image sets of the dual func

Mehmet Efruz Karabulut, K. Vijay-Shanker

Rapid growth of the biomedical literature has led to many advances in the biomedical text mining field. Among the vast amount of information, biomedical article abstracts are the easily accessible sources. However, the number of the structured abstracts, describing the rhetorical sections with one of Background, Objective, Method, Result and Conclusion categ

Maximilian Suppan, Christian Huber, Klaus Mathauer, Claas Abert

Within this work, we demonstrate in-situ easy-axis alignment of single-crystal magnetic particles inside a polymer matrix using fused filament fabrication. Two different magnetic materials are investigated: (i) Strontium hexaferrite inside a PA6 matrix, fill grade: 49 vol% and (ii) Samarium iron nitride inside a PA12 matrix, fill grade: 44 vol%. In the prese

Ana R. Romero Castellannos, H. E. Castellanos, C. E. Alvarez-Salazar

Homemade spectrometers are commonly used tools to analyze light sources and determine its physical characteristics. We perform an assessment of homemade spectrometers in terms of spectral resolution and accuracy in the determination of intensity, through the comparison of results with a spectroscope commonly used in the physics and chemistry labs. We found t

Gabriel Santana, Maira Valera

This research aimed to explore some new Hermite-Hadamard inequalities for strongly harmonic convex set-valued functions with modulus c > 0 introduced by G. Santana

Wanghan Lv, Kumar Vijay Mishra, Shichao Chen

Target localization based on frequency diverse array (FDA) radar has lately garnered significant research interest. A linear frequency offset (FO) across FDA antennas yields a range-angle dependent beampattern that allows for joint estimation of range and direction-of-arrival (DoA). Prior works on FDA largely focus on the one-dimensional linear array to esti

Xiaofeng Liu, Fangxu Xing, Thibault Marin, Georges El Fakhri

Lesions or organ boundaries visible through medical imaging data are often ambiguous, thus resulting in significant variations in multi-reader delineations, i.e., the source of aleatoric uncertainty. In particular, quantifying the inter-observer variability of manual annotations with Magnetic Resonance (MR) Imaging data plays a crucial role in establishing a

Miro Bilge

In the scope of this paper, the precise positioning of objects with the help of Ultra Wide Band technology is evaluated. To achieve this, a prototype module for the use with the Decawave transceiver DW1000 was implemented and added to FruityMesh, an Internet of Things (IoT) mesh network of the company M-Way Solutions. The focus of the network is low-power co

Mónica Graf, Hugo Aramberri, Pavlo Zubko, Jorge Íñiguez

Ferroelectrics subject to suitable electric boundary conditions present a steady negative capacitance response. When the ferroelectric is in a heterostructure, this behavior yields a voltage amplification in the other elements, which experience a potential difference larger than the one applied, holding promise for low-power electronics. So far research has

Bin Guo, Emil Sekerinski

Graph analytics attract much attention from both research and industry communities. Due to the linear time complexity, the $k$-core decomposition is widely used in many real-world applications such as biology, social networks, community detection, ecology, and information spreading. In many such applications, the data graphs continuously change over time. Th

Saubhik Sarkar, Chiranjib Mukhopadhyay, Abhijeet Alase, Abolfazl Bayat

Second order quantum phase transitions, with well-known features such as long-range entanglement, symmetry breaking, and gap closing, exhibit quantum enhancement for sensing at criticality. However, it is unclear which of these features are responsible for this enhancement. To address this issue, we investigate phase transitions in free-fermionic topological

V. I. Klyukhin, A. Ball, C. P. Berriaud, E. Bielert

The conceptual design study of a hadron Future Circular hadron-hadron Collider (FCC-hh) with a center-of-mass energy of the order of 100 TeV assumes using in the experimental detector the superconducting magnetic system with a central magnetic flux density of an order of 4 T. A superconducting magnet with a minimal steel yoke was proposed as an alternative t

Yigeng Peng, Tong Wu, Guanglu Yuan, Lihan Chi

High harmonic generation (HHG) from crystals in strong laser fields has been understood by the band theory of solid, which is based on the periodic boundary condition (PBC) of translational invariant. For systems having PBC of rotational invariant, in principles an analogous Bloch theorem can be developed and applied. Taking a ring-type cluster of cyclo[18]c

Li Lin, Yixin Cao, Lifu Huang, Shu'ang Li

Prediction over event sequences is critical for many real-world applications in Information Retrieval and Natural Language Processing. Future Event Generation (FEG) is a challenging task in event sequence prediction because it requires not only fluent text generation but also commonsense reasoning to maintain the logical coherence of the entire event story.

Wesley H. Holliday

In this paper, we study three representations of lattices by means of a set with a binary relation of compatibility in the tradition of Plo\v{s}\v{c}ica. The standard representations of complete ortholattices and complete perfect Heyting algebras drop out as special cases of the first representation, while the second covers arbitrary complete lattices, as we

Yu Gu, Tomasz Komorowski

In this short note, we prove a central limit theorem for a type of replica overlap of the Brownian directed polymer in a Gaussian random environment, in the low temperature regime and in all dimensions. The proof relies on a superconcentration result for the KPZ equation driven by a spatially mollified noise, which is inspired by the recent work of Chatterje

Tao Chen

When faced with changing environment, highly configurable software systems need to dynamically search for promising adaptation plan that keeps the best possible performance, e.g., higher throughput or smaller latency -- a typical planning problem for self-adaptive systems (SASs). However, given the rugged and complex search landscape with multiple local opti

Qiushi Zhang

Understanding the dynamics of the micro-sized surface bubbles produced by plasmonic heating can benefit a wide range of applications like microfluidics, catalysis, micro-patterning and photo-thermal energy conversion. Usually, surface plasmonic bubbles are generated on plasmonic nano-structures pre-deposited on the surface subject to laser heating. In our st

Masahiro Yamamoto

We define fractional derivatives $\pppa$ in Sobolev spaces based on $L^p(0,T)$ by an operator theory, and characterize the domain of $\pppa$ in subspaces of the Sobolev-Slobodecki spaces $W^{\alpha,p}(0,T)$. Moreover we define $\pppa u$ for $u\in L^p(0,T)$ in a sense of distribution. Then we discuss initial value problems for linear fractional ordinary diffe

Robin Alexander, Benjamin R. Baer, Stephen E. Fremes, Mary Charlson

The fragility index is a clinically motivated metric designed to supplement the $p$ value during hypothesis testing. The measure relies on two pillars: selecting cases to have their outcome modified and modifying the outcomes. The measure is interesting but the case selection suffers from a drawback which can hamper its interpretation. This work presents the

Hamed Khorasgani, Haiyan Wang, Hsiu-Khuern Tang, Chetan Gupta

Traditionally, the performance of multi-agent deep reinforcement learning algorithms are demonstrated and validated in gaming environments where we often have a fixed number of agents. In many industrial applications, the number of available agents can change at any given day and even when the number of agents is known ahead of time, it is common for an agen

Katja A. Salbaum, Elijah R. Shelton, Friedhelm Serwane

With a kind of magnetism, the human retina draws the eye of neuroscientist and physicist alike. It is attractive as a self-organizing system, which forms as a part of the central nervous system via biochemical and mechanical cues. The retina is also intriguing as an electro-optical device, converting photons into voltages to perform on-the-fly filtering befo

Marco Castrillón López, Álvaro Rodríguez Abella

In this work, generalized principal bundles modelled by Lie group bundle actions are investigated. In particular, the definition of equivariant connections in these bundles, associated to Lie group bundle connections, is provided, together with the analysis of their existence and their main properties. The final part gives some examples. In particular, since

G. D. Soria, K. Freindl, J. E. Prieto, A. Quesada

CoFe2O4 thin films (5 nm and 20 nm thick) were grown by oxygen assisted molecular beam epitaxy on Pt(111) at 523~K and subsequently annealed at 773 K in vacuum or oxygen. They were characterized in-situ using Auger Electron Spectroscopy, Low-Energy Electron Diffraction, Scanning Tunneling Microscopy and Conversion Electron M\"ossbauer Spectroscopy. The as-gr

Dirk Lorenz, Hinrich Mahler, Christian Meyer

We investigate the problem of optimal transport in the so-called Beckmann form, i.e. given two Radon measures on a compact set, we seek an optimal flow field which is a vector valued Radon measure on the same set that describes a flow between these two measures and minimizes a certain linear cost function. We consider $L^\alpha$ regularization of the problem

Qiushi Zhang

My thesis mostly focusses on the systems of porphyrin molecules adsorbed on single-crystalline metallic surfaces. Cyclic tetrapyrrole porphyrins play key roles in many important chemical and biological processes, such as oxygen transport in heme (iron porphyrin), electron transfer and oxidation reactions in photosynthetic chlorophyll (magnesium porphyrin). C

R. Dogra, S. Lando

We introduce a new one-variable polynomial invariant of graphs, which we call the skew characteristic polynomial. For an oriented simple graph, this is just the characteristic polynomial of its anti-symmetric adjacency matrix. For nonoriented simple graphs the definition is different, but for a certain class of graphs (namely, for intersection graphs of chor

Ningyuan Huang, Soledad Villar

Graph neural networks are designed to learn functions on graphs. Typically, the relevant target functions are invariant with respect to actions by permutations. Therefore the design of some graph neural network architectures has been inspired by graph-isomorphism algorithms. The classical Weisfeiler-Lehman algorithm (WL) -- a graph-isomorphism test based on

Andreea Bobu, Marius Wiggert, Claire Tomlin, Anca D. Dragan

Reward learning enables robots to learn adaptable behaviors from human input. Traditional methods model the reward as a linear function of hand-crafted features, but that requires specifying all the relevant features a priori, which is impossible for real-world tasks. To get around this issue, recent deep Inverse Reinforcement Learning (IRL) methods learn re

David A. Craven

This paper almost classifies the maximal subgroups of $E_7(q)$ for general $q$ a power of a prime $p$. Only four potential maximal subgroups are missing: $PSL_2(7)$ (unknown for $p\neq 2,3,7$), $PSL_2(8)$ ($p=2$) and $PSL_2(9)=A_6$ ($p\neq 2,3$). In addition, there is one issue with the precise structure with the positive-dimensional maximal subgroup of type

Sean Prudhoe, Sarah Shandera

We study families of dynamical maps generated from interactions with varying degrees of symmetry. For a family of time-independent Hamiltonians, we demonstrate the relationship between symmetry, strong-coupling, perfect entanglers, non-Markovian features, and non-time-locality. We show that by perturbing the initial environment state, effective time-local de

Hao Wang, Yun-Song Piao

In the studies on pre-recombination early dark energy (EDE), the evolution of Universe after recombination is usually regarded as ${\Lambda}CDM$-like, which corresponds that the equation of state of dark energy responsible for current accelerated expansion is $w=-1$. However, in realistic models, $w$ might be evolving. We consider the parametrizations of $w$

Xian Wang, Diego Monteiro, Lik-Hang Lee, Pan Hui

Haptic feedback in virtual reality (VR) allows users to perceive the physical properties of virtual objects (e.g., their weight and motion patterns). However, the lack of haptic sensations deteriorates users' immersion and overall experience. In this work, we designed and implemented a low-cost hardware prototype with liquid metal, VibroWeight, which can wor

Brent R. Yates

A first measurement of the $\mathrm{b}$ quark fragmentation function at the LHC is presented. Charmed meson candidates produced via semi-leptonic $\mathrm{t\overline{t}}$ decays ($\mathrm{t} \to \mathrm{b}\mathrm{W} \to$ b-jet $\ell \nu$) are used as a proxy for the parent $\mathrm{B}$ meson. Templates are generated at various values of the fragmentation sha

Rui Luo, Vikram Krishnamurthy, Erik Blasch

The paper develops a blockchain protocol for a social media network (BE-SMN) to mitigate the spread of misinformation. BE-SMN is derived based on the information transmission-time distribution by modeling the misinformation transmission as double-spend attacks on blockchain. The misinformation distribution is then incorporated into the SIR (Susceptible, Infe

Mario Martinez-Saito

We describe a chain of unidirectionally coupled adaptive excitable elements slowly driven by a stochastic process from one end and open at the other end, as a minimal toy model of unresolved irreducible uncertainty in a system performing inference through a hierarchical model. Threshold potentials adapt slowly to ensure sensitivity without being wasteful. Ac

István A. Kovács, Ferenc Iglói

In many-body systems with quenched disorder, dynamical observables can be singular not only at the critical point, but in an extended region of the paramagnetic phase as well. These Griffiths singularities are due to rare regions, which are locally in the ordered phase and contribute to a large susceptibility. Here, we study the geometrical properties of rar

Reizo Kato, Masashi Uebe, Shigeki Fujiyama, Hengbo Cui

A molecular Mott insulator $\beta$'-EtMe$_3$Sb[Pd(dmit)$_2$]$_2$ is a quantum spin liquid candidate. In 2010, it was reported that thermal conductivity of $\beta$'-EtMe$_3$Sb[Pd(dmit)$_2$]$_2$ is characterized by its large value and gapless behavior (a finite temperature-linear term). In 2019, however, two other research groups reported opposite data (much s

Augustine Denteh, Helge Liebert

We provide new insights regarding the headline result that Medicaid increased emergency department (ED) use from the Oregon experiment. We find meaningful heterogeneous impacts of Medicaid on ED use using causal machine learning methods. The individualized treatment effect distribution includes a wide range of negative and positive values, suggesting the ave

Maria Loukaki

Let $U_n$ denote the group of upper $n \times n$ unitriangular matrices over a fixed finite field $\mathbb{F}$ of order $q$. That is, $U_n$ consists of upper triangular $n \times n$ matrices having every diagonal entry equal to $1$. It is known that the degrees of all irreducible complex characters of $U_n$ are powers of $q$. It was conjectured by Lehrer tha

Minh-Quan Dao, Elwan Héry, Vincent Frémont

Recent advances in 3D object detection are made by developing the refinement stage for voxel-based Region Proposal Networks (RPN) to better strike the balance between accuracy and efficiency. A popular approach among state-of-the-art frameworks is to divide proposals, or Regions of Interest (ROI), into grids and extract features for each grid location before

G. Cubadda, S. Grassi, B. Guardabascio

Many economic variables feature changes in their conditional mean and volatility, and Time Varying Vector Autoregressive Models are often used to handle such complexity in the data. Unfortunately, when the number of series grows, they present increasing estimation and interpretation problems. This paper tries to address this issue proposing a new Multivariat

Ahmet Ilker Topuz, Madis Kiisk, Andrea Giammanco

In this study, by attempting to resolve the angular complication during the particle generation for the muon tomography applications in the GEANT4 simulations, we exhibit an unconventional methodology that is hinged on the direction limitation via the vectorial construction from the generation location to the restriction area rather than using a certain angu

Marco Tranzatto, Frank Mascarich, Lukas Bernreiter, Carolina Godinho

Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy hard to achieve. This has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response, the CERB

A. Buades, O. Martorell, M. Sánchez-Beeckman

We propose a patch-based method for the simultaneous denoising and fusion of a sequence of RAW multi-exposed images. A spatio-temporal criterion is used to select similar patches along the sequence, and a weighted principal component analysis permits to both denoise and fuse the multi exposed data. The overall strategy permits to denoise and fuse the set of

Martin Spillum Grønli, Tomáš Brauner

We investigate the thermodynamics of two-flavor quark matter in presence of nonzero isospin chemical potential and external magnetic field. It is known that at sufficiently high isospin chemical potential, charged pions undergo Bose-Einstein condensation (BEC). The condensate behaves as a superconductor, exhibiting Meissner effect in weak external magnetic f

B. Riaz, W. -F. Thi

We report the first detection in the ${\it J}_{{\it K}}$ = 1$_{0}$ - 0$_{0}$ rotational transition line of CH$_{3}$D towards three Class 0/I proto-brown dwarfs (proto-BDs) from IRAM 30 m observations. Assuming a rotational temperature of 25 K, the CH$_{3}$D abundances (relative to H$_{2}$) are in the range of (2.3--14.5) $\times$ 10$^{-7}$. The CH$_{4}$ abun

Phung Lai, NhatHai Phan, Issa Khalil, Abdallah Khreishah

This paper explores previously unknown backdoor risks in HyperNet-based personalized federated learning (HyperNetFL) through poisoning attacks. Based upon that, we propose a novel model transferring attack (called HNTroj), i.e., the first of its kind, to transfer a local backdoor infected model to all legitimate and personalized local models, which are gener

Maria Loukaki

Berkovich, Chillag and Herzog characterized all finite groups $G$ in which all the nonlinear irreducible characters of $G$ have distinct degrees. In this paper we extend this result showing that a similar characterization holds for all finite solvable groups $G$ that contain a normal subgroup $N$, such that all the irreducible characters of $G$ that do not c

Jan Glaubitz, Anne Gelb, Guohui Song

Image reconstruction based on indirect, noisy, or incomplete data remains an important yet challenging task. While methods such as compressive sensing have demonstrated high-resolution image recovery in various settings, there remain issues of robustness due to parameter tuning. Moreover, since the recovery is limited to a point estimate, it is impossible to

Sourav Mondal, Marco Ruffini

The recently proposed open-radio access network (O-RAN) architecture embraces cloudification and network function virtualization techniques to perform the base-band function processing by dis-aggregated radio units (RUs), distributed units (DUs), and centralized units (CUs). This enables the cloud-RAN vision in full, where mobile network operators (MNOs) cou

Padraic Odesse, Catherine Lovekin

Theories of stellar convective core overshoot can be examined through analysis of pulsating stars. Better accuracy can be achieved by obtaining external constraints such as those provided by observing pulsating stars in eclipsing binary systems, but this requires that the binary parameters be identified so photometric variations of the pulsating component ma

Matthias Pickem, Josef Kaufmann, Karsten Held, Jan M. Tomczak

Many metallic transition-metal oxides turn insulating when grown as films that are only a few unit-cells thick. The microscopic origins of these thickness induced metal-to-insulator transitions however remain under dispute. Here, we simulate the extreme case of a monolayer of an inconspicuous correlated metal -- the strontium vanadate SrVO$_3$ -- deposited o

Antonio Bueno, Irene Ortiz

We study rotational surfaces in Euclidean 3-space whose Gauss curvature is given as a prescribed function of its Gauss map. By means of a phase plane analysis and under mild assumptions on the prescribed function, we generalize the classification of rotational surfaces of constant Gauss curvature; exhibit examples that cannot exist in the constant Gauss curv

Pablo Valgañón, David Soriano-Paños, Alex Arenas, Jesús Gómez-Gardeñes

The analysis of contagion-diffusion processes in metapopulations is a powerful theoretical tool to study how mobility influences the spread of communicable diseases. Nevertheless, many metapopulation approaches use indistinguishable agents to alleviate analytical difficulties. Here, we address the impact that recurrent mobility patterns, and the spatial dist

Brett R. Gordon, Robert Moakler, Florian Zettelmeyer

Despite their popularity, randomized controlled trials (RCTs) are not always available for the purposes of advertising measurement. Non-experimental data is thus required. However, Facebook and other ad platforms use complex and evolving processes to select ads for users. Therefore, successful non-experimental approaches need to "undo" this selection. We ana

Anjali Nair, Qin Li, Weiran Sun

We investigate the numerical implementation of the limiting equation for the phonon transport equation in the small Knudsen number regime. The main contribution is that we derive the limiting equation that achieves the second order convergence, and provide a numerical recipe for computing the Robin coefficients. These coefficients are obtained by solving an

Fabio Di Pumpo, Alexander Friedrich, Andreas Geyer, Christian Ufrecht

Dark matter or violations of the Einstein equivalence principle influence the motion of atoms, their internal states as well as electromagnetic fields, thus causing a signature in the signal of atomic detectors. To model such new physics, we introduce dilaton fields and study the modified propagation of light used to manipulate atoms in light-pulse atom inte

Xingyu Zhou

Motivated by the wide adoption of reinforcement learning (RL) in real-world personalized services, where users' sensitive and private information needs to be protected, we study regret minimization in finite-horizon Markov decision processes (MDPs) under the constraints of differential privacy (DP). Compared to existing private RL algorithms that work only o

Hyun-Suk Lee

Dynamic scheduling is an important problem in applications from queuing to wireless networks. It addresses how to choose an item among multiple scheduling items in each timestep to achieve a long-term goal. Conventional approaches for dynamic scheduling find the optimal policy for a given specific system so that the policy from these approaches is usable onl

Marianna B. Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh

Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that existing cognitive theories of human decision making, such as the thinking fast and slow theory, can provide insights on how to advance AI systems towards some of these capabiliti

F. Nyenhuis, P. N. Terekhin, T. Menold, B. Rethfeld

Industrial use of ultrashort-pulse surface structuring would significantly increase by an effective utilization of the average laser powers available currently. However, the unexplained degradation of surfaces processed with numerous pulses at high average laser power makes this difficult. Based on a systematic experimental study, the structure formation und

P. L. Robinson

We consider $q$-analytic derivations of the $q$-Gauss summation formula for a $\, _2\phi _1$ that respect the symmetry in its upper parameters.

Tianyu Fang, Yijie Mao, Shanpu Shen, Zhencai Zhu

Rate-splitting multiple access (RSMA) has been recognized as a promising and powerful multiple access (MA) scheme, non-orthogonal transmission framework and interference management strategy for 6G. Inspired by the appealing spectral efficiency gain achieved by RSMA over conventional MA schemes in multi-user multi-antenna transmission, in this paper we introd

L. F. S. Gouveia, Gabriel Rondón, P. R. da Silva

The normal forms associated with holomorphic systems are well known in the literature. In this paper we are concerned about studying the piecewise smooth holomorphic systems (PWHS). Specifically, we classify the possible phase portraits of these systems from the known normal forms and the typical singularities of PWHS. Also, we are interested in understandin

Ajit Singh, Rupam Barman

For a positive integer $t$, let $b_{t}(n)$ denote the number of $t$-regular partitions of a nonnegative integer $n$. In a recent paper, Keith and Zanello established infinite families of congruences and self-similarity results modulo $2$ for $b_{t}(n)$ for certain values of $t$. Further, they proposed some conjectures on self-similarities of $b_t(n)$ modulo

ATLAS Collaboration

A search is made for a vector-like $T$ quark decaying into a Higgs boson and a top quark in 13 TeV proton-proton collisions using the ATLAS detector at the Large Hadron Collider with a data sample corresponding to an integrated luminosity of 139 fb$^{-1}$. The Higgs-boson and top-quark candidates are identified in the all-hadronic decay mode, where $H\to b\b

Viktor Skoupý, Georgios Lukes-Gerakopoulos

The detection of gravitational waves from Extreme mass Ratio Inspirals (EMRIs) by the future space-based gravitational-wave detectors demands the generation of accurate enough waveform templates. Since the spin of the smaller secondary body cannot be neglected for the detection and parameter estimation of EMRIs, we study its influence on the phase of the gra

Mattia Lecci, Federico Chiariotti, Matteo Drago, Andrea Zanella

Over the past few years, eXtended Reality (XR) has attracted increasing interest thanks to its extensive industrial and commercial applications, and its popularity is expected to rise exponentially over the next decade. However, the stringent Quality of Service (QoS) constraints imposed by XR's interactive nature require Network Slicing (NS) solutions to sup

Lizhong Wang, Jiping Zhang

By generalizing Frobenius' polynomial method to good partition algebra, we will develop new character theories for a finite group $G$. A uniform defining equations are derived for these kinds of character theories. The new character theories leads to various factorizations of the group determinant. We will show that these new character theories are equivalen

Christoph Lehrenfeld, Paul Stocker

In Trefftz discontinuous Galerkin methods a partial differential equation is discretized using discontinuous shape functions that are chosen to be elementwise in the kernel of the corresponding differential operator. We propose a new variant, the embedded Trefftz discontinuous Galerkin method, which is the Galerkin projection of an underlying discontinuous G

Kathrin Blagec, Jakob Kraiger, Wolfgang Frühwirt, Matthias Samwald

Publicly accessible benchmarks that allow for assessing and comparing model performances are important drivers of progress in artificial intelligence (AI). While recent advances in AI capabilities hold the potential to transform medical practice by assisting and augmenting the cognitive processes of healthcare professionals, the coverage of clinically releva

Wojciech Szewczuk, Przemysław Walczak, Jadwiga Daszyńska-Daszkiewicz, Dawid Moździerski

KIC8264293 is a fast rotating B-type pulsator observed by Kepler satellite. Its photometric variability is mainly due to pulsations in high-order g modes. Besides, we detected a weak H$\alpha$ emission. Thus, the second source of variability is the fluctuation in a disk around the star. The pulsational spectrum of KIC8264293 reveals a frequency grouping and

Klaus E. Hermann

We examine the structure of compact metal nanoparticles (NPs) forming polyhedral sections of face centered (fcc) and body centered (bcc) cubic lattices, which are confined by facets characterized by highly dense {100}, {110}, and {111} monolayers. Together with the constraint that the NPs exhibit the same point symmetry as the ideal cubic lattice, i.e. Oh, d