July 2023 arXiv papers — page 31

Cui-Yuan Dai, Xiang-Yu Wang, Ruo-Yu Liu, Bing Zhang

Recent LHAASO observations of the prompt emission phase of the brightest-of-all-time GRB 221009A imposes a stringent limit on the flux ratio between the TeV and MeV emissions, $F_{\rm TeV}/F_{\rm MeV}\le 2\times10^{-5}$, during the period $220 \operatorname{-}230\, {\rm s}$ after the trigger. bf This period covers the peak of the main MeV burst and is just b

Matteo Beccaria, Simone Giombi, Arkady A. Tseytlin

We present a quantum M2 brane computation of the instanton prefactor in the leading non-perturbative contribution to the ABJM 3-sphere free energy at large $N$ and fixed level $k$. Using supersymmetric localization, such instanton contribution was found earlier to take the form $F^{\rm inst}(N,k) = - ({\sin^{2} \frac{2\pi}{k}} )^{-1} \, \exp (-2\pi \sqrt\fra

Fernando Alonso-Fernandez, Josef Bigun

Periocular biometrics has been established as an independent modality due to concerns on the performance of iris or face systems in uncontrolled conditions. Periocular refers to the facial region in the eye vicinity, including eyelids, lashes and eyebrows. It is available over a wide range of acquisition distances, representing a trade-off between the whole

Dengyu Zhang, Xinyu Zhang, Zheng Zhang, Bo Zhu

Motion planning is challenging for multiple robots in cluttered environments without communication, especially in view of real-time efficiency, motion safety, distributed computation, and trajectory optimality, etc. In this paper, a reinforced potential field method is developed for distributed multi-robot motion planning, which is a synthesized design of re

Taniya Das, Mark Koch, Maya Ravichandran, Nikhil Khatri

GraphRNN is a deep learning-based architecture proposed by You et al. for learning generative models for graphs. We replicate the results of You et al. using a reproduced implementation of the GraphRNN architecture and evaluate this against baseline models using new metrics. Through an ablation study, we find that the BFS traversal suggested by You et al. to

Juan José Gálvez-Viruet, María Gómez-Rocha

The front form of Hamiltonian dynamics provides a framework within QCD in which interaction terms are invariant under 7 of 10 Poincar\'e transformations and the vacuum structure is simple. However, canonical expressions are divergent and must be regulated before attempting to define an eigenvalue problem. The renormalization group procedure for effective par

Yu. S. Tsyganov, D. Ibadullayev, A. N. Polyakov, V. B. Zlokazov

A simple routine is proposed for monitoring the efficiency value of a low pressure pentane filled multi-wire proportional chamber (MWPC) in long term experiments. The proposed algorithm utilizes a two parameter approximation for the background function. It is based on a linear approximation of the background in the energy range of 4.8 to 10.0 MeV and an expo

Shahab Saquib Sohail, Faiza Farhat, Yassine Himeur, Mohammad Nadeem

Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It has shown impressive performance in various domains, including passing exams and creative writing. However, challenges and concerns related to biases and trust persist. In this work, we present a comprehensive review of over 1

Andreu Riera-Campeny, Marc Roda-Llordes, Piotr T. Grochowski, Oriol Romero-Isart

We derive an analytical expression of a Wigner function that approximately describes the time evolution of the one-dimensional motion of a particle in a nonharmonic potential. Our method involves two exact frame transformations, accounting for both the classical dynamics of the centroid of the initial state and the rotation and squeezing about that trajector

Kouki Terashima, Kanji Tanaka, Ryogo Yamamoto, Jonathan Tay Yu Liang

In ground-view object change detection, the recently emerging mapless navigation has great potential to navigate a robot to objects distantly detected (e.g., books, cups, clothes) and acquire high-resolution object images, to identify their change states (no-change/appear/disappear). However, naively performing full journeys for every distant object requires

M. Andrés-Carcasona, A. Macquet, M. Martínez, Ll. M. Mir

We present an estimation of the noise induced by scattered light inside the main arms of the Einstein Telescope (ET) gravitational wave detector. Both ET configurations for high- and low-frequency interferometers are considered, for which we propose baffle layouts. The level of scattered light and the ET laser beam clipping losses are intimately related to t

Benjamin Joecker, Holly G. Stemp, Irene Fernández de Fuentes, Mark A. I. Johnson

Quantum nondemolition (QND) measurements are a precious resource for quantum information processing. Repetitive QND measurements can boost the fidelity of qubit preparation and measurement, even when the underlying single-shot measurements are of low fidelity. However, this fidelity boost is limited by the degree in which the physical system allows for a tru

Yiren Chen, Jianhua Guo, Shen Wang

The Giant Radio Array for Neutrino Detection (GRAND) aims to detect the radio emission from air showers triggered by ultra-high-energy particles in the atmosphere. GRANDProto300 is its pathfinder array, of which the first 100 detection units have already been produced. A custom data acquisition (DAQ) board receives, processes, and transmits radio signals. We

Sergei M. Puchinin, Fedor S. Stonyakin

We consider minimization problems with the well-known Polya-Lojasievich condition and Lipshitz-continuous gradient. Such problem occurs in different places in machine learning and related fields. Furthermore, we assume that a gradient is available with some relative inexactness. We propose some adaptive gradient-type algorithm, where the adaptivity took plac

F. Geyer, K. Schmidt, J. Kummer, M. Brüggen

Radio interferometry invariably suffers from an incomplete coverage of the spatial Fourier space, which leads to imaging artifacts. The current state-of-the-art technique is to create an image by Fourier-transforming the incomplete visibility data and to clean the systematic effects originating from incomplete data in Fourier space. Previously, we have shown

Jakub Janarek, Zbigniew Drogosz, Jacek Grela, Jeremi K. Ochab

This paper addresses the question of the brain's critical dynamics after an injury such as a stroke. It is hypothesized that the healthy brain operates near a phase transition (critical point), which provides optimal conditions for information transmission and responses to inputs. If structural damage could cause the critical point to disappear and thus make

Shengbo You, Peng-Han Lu, András Kovács, Thomas Schachinger

Over the past few years, the combination of diffuser and near-field electron ptychography has drawn more attention by its ability to recover large field of view with few diffraction patterns. In this paper, we purpose a novel design and implementation of amplitude diffuser. The amplitude diffuser introduces structures to the illumination while reducing the i

Milad Gholami, Gianni Bianchini, Antonio Vicino

This paper presents a robust secondary control strategy for frequency synchronization and active power sharing for inverter-based microgrids. The problem is addressed in a multi-agent fashion where the local controllers of the distributed generators play the role of agents, and communication is affected by time-varying delays. {The approach is fully distribu

ALICE Collaboration

Charged-particle jet yields have been measured in semicentral Pb$-$Pb collisions at center-of-mass energy per nucleon-nucleon collision $\sqrt{s_{\rm NN}} = 5.02$ TeV with the ALICE detector at the LHC. These yields are reported as a function of the jet transverse momentum, and further classified by their angle with respect to the event plane and the event s

Shanwei Ding, Guanghan Li

We consider a general curvature equation $F(\kappa)=G(X,\nu(X))$, where $\kappa$ is the principal curvature of the hypersurface $M$ with position vector $X$. It includes the classical prescribed curvature measures problem and area measures problem. However, Guan-Ren-Wang \cite{GRW} proved that the $C^2$ estimate fails usually for general function $F$. Thus,

Martin Orr

A theorem of L\"utkebohmert states that a rigid group homomorphism from the formal multiplicative group to a smooth commutative rigid group $G$, with relatively compact image, can be extended to a homomorphism from the rigid multiplicative group to $G$. In this paper, we prove a relative version of this theorem over a geometrically reduced quasi-compact quas

Ayuka Matsumi, Naoki Nishida, Misaki Kojima, Donghoon Shin

As for term rewrite systems, the dependency pair (DP, for short) framework with several kinds of DP processors is useful for proving termination of logically constrained term rewrite systems (LCTRSs, for short). However, the polynomial interpretation processor is not so effective against LCTRSs with bit-vector arithmetic (BV-LCTRSs, for short). In this paper

Nandita Pan, Supratik Banerjee, Arijit Halder

Upon quenching the forcing, a turbulent system tends to attain the state of stable equilibrium through the process of turbulent relaxation. Such relaxation in binary fluids is of surmount interest for both fundamental science understanding and industrial applications. A systematic investigation of the same has been carried out, for the first time, using dire

Kevin J Painter, Thomas Hillen, Jonathan R Potts

The employment of nonlocal PDE models to describe biological aggregation and other phenomena has gained considerable traction in recent years. For cell populations, these methods grant a means of accommodating essential elements such as cell adhesion, critical to the development and structure of tissues. For animals, they can be used to describe how the near

Hiroyuki Kaneko, Tomoka Tosaki, Kunihiko Tanaka, Yusuke Miyamoto

We present position-position-velocity (PPV) cubes of the physical and chemical properties of the molecular medium in the central 1.2 kpc region of the active galaxy NGC 613 at a PPV resolution of 0.$^{\prime\prime}$8$\times$0.$^{\prime\prime}$8$\times$10 km s$^{-1}$ (0.$^{\prime\prime}$8 = $\sim$68 pc). We used eight molecular lines obtained with ALMA. Non-L

Leonid Berlin, Andrey Galyaev, Pavel Lysenko

Three variants of the statistical complexity function, which is used as a criterion in the problem of detection of a useful signal in the signal-noise mixture, are considered. The probability distributions maximizing the considered variants of statistical complexity are obtained analytically and conclusions about the efficiency of using one or another varian

Philipp A. Guth, Karl Kunisch, Sérgio S. Rodrigues

A strategy is proposed for adaptive stabilization of linear systems, depending on an uncertain parameter. Offline, the Riccati stabilizing feedback input control operators, corresponding to parameters in a finite training set of chosen candidates for the uncertain parameter, are solved and stored in a library. A uniform partition of the infinite time interva

Simina Brânzei, Nithish Kumar, Gireeja Ranade

This paper proposes a stochastic block model with dynamics where the population grows using preferential attachment. Nodes with higher weighted degree are more likely to recruit new nodes, and nodes always recruit nodes from their own community. This model can capture how communities grow or shrink based on their collaborations with other nodes in the networ

Rupert L. Frank, Fabio Nicola, Paolo Tilli

Lieb and Carlen have shown that mixed states with minimal Wehrl entropy are coherent states. We prove that mixed states with almost minimal Wehrl entropy are almost coherent states. This is proved in a quantitative sense where both the norm and the exponent are optimal and the constant is explicit. We prove a similar bound for generalized Wehrl entropies. As

Weijun Wu, Fujun Zhou, Yongsheng Li

Diffusive limit of the Vlasov-Poisson-Boltzmann system with cutoff soft potentials $-3<\gamma<0$ in the perturbative framework around global Maxwellian still remains open. By introducing a new weighted $H_{x,v}^2$-$W_{x,v}^{2, \infty}$ approach with time decay, we solve this problem for the full range of cutoff potentials $-3<\gamma\leq 1$. The core of this

Aleks Scholz, Koraljka Muzic, Victor Almendros-Abad, Antonella Natta

We report on a search for variability in the young brown dwarf SST1624 (~M7 spectral type, M~0.05Msol), previously found to feature an expanding gaseous shell and to undergo quasi-spherical mass loss. We find no variability on timescales of 1-6hours. Specifically, on these timescales, we rule out the presence of a period with amplitude >1%. A photometric per

C. Augier, A. S. Barabash, F. Bellini, G. Benato

Neutrinoless double beta decay ($0\nu\beta\beta$) is a yet unobserved nuclear process which would demonstrate Lepton Number violation, a clear evidence of beyond Standard Model physics. The process two neutrino double beta decay ($2\nu\beta\beta)$ is allowed by the Standard Model and has been measured in numerous experiments. In this letter, we report a meas

Siyu Chen, Mengdi Wang, Zhuoran Yang

We study reinforcement learning (RL) for learning a Quantal Stackelberg Equilibrium (QSE) in an episodic Markov game with a leader-follower structure. In specific, at the outset of the game, the leader announces her policy to the follower and commits to it. The follower observes the leader's policy and, in turn, adopts a quantal response policy by solving an

ALICE Collaboration

The elliptic flow ($v_2$) of $\rm D^0$ mesons from beauty-hadron decays (non-prompt $\rm D^0$) was measured in midcentral (30-50%) Pb-Pb collisions at a centre-of-mass energy per nucleon pair $\sqrt{s_{\rm NN}}$ = 5.02 TeV with the ALICE detector at the LHC. The $\rm D^0$ mesons were reconstructed at midrapidity ($|y|<0.8$) from their hadronic decay $\mathrm

Jean-François de Kemmeter, Adam Byrne, Amy Dunne, Timoteo Carletti

Many natural or human-made systems encompassing local reactions and diffusion processes exhibit spatially distributed patterns of some relevant dynamical variable. These interactions, through self-organization and critical phenomena, give rise to power-law distributions, where emergent patterns and structures become visible across vastly different scales. Re

Ijaz Ahmed, Waqas Ahmad, M. S. Amjad, Jamil Muhammad

This study explores the possibility of discovering $H^{\pm}$ through its bosonic decays, i.e. $H^{\pm}\rightarrow W^\pm\phi$ (where $\phi$ = h or A), within the Type-I Two Higgs Doublet Model (2HDM). The main objective is to demonstrate the available parameter space after applying the recent experimental and theoretical exclusion limits. We suggest that for

A. Frasca, J. Alonso-Santiago, G. Catanzaro, A. Bragaglia

We report the discovery of a low-mass totally eclipsing system in the young (age$\simeq$28 Myr) open cluster NGC2232, during a scrutiny of their TESS light curves. The follow-up study of this detached system, TIC 43152097, is based on photometry and high-resolution spectra from the literature and purposely collected. The radial velocity of the center of mass

Xiang Huang, Zhuoyuan Li, Hongsheng Liu, Zidong Wang

Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention. However, most existing methods adopt pure data-driven black-box models, which have limited accuracy and interpretability. By combining trainable difference operators with black-box models, we propose a new hybrid architecture explicitly embedded with partial

Paolo Bernuzzi, Antonia Düx, Christian Kühn

In this work, we study early-warning signs for stochastic partial differential equations (SPDEs), where the linearization around a steady state has continuous spectrum. The studied warning sign takes the form of qualitative changes in the variance as a deterministic bifurcation threshold is approached via parameter variation. Specifically, we focus on the sc

Mara Vizzuso, Gianluca Passarelli, Giovanni Cantele, Procolo Lucignano

Recently, Digitized-Counterdiabatic (CD) Quantum Approximate Optimization Algorithm (QAOA) has been proposed to make QAOA converge to the solution of an optimization problem in fewer steps, inspired by Trotterized counterdiabatic driving in continuous-time quantum annealing. In this paper, we critically revisit this approach by focusing on the paradigmatic w

Anderson S. Chaves, Murilo Aguiar Silva, Alex Antonelli

We employed first-principles calculations to investigate the thermoelectric transport properties of the compound As$_2$Se$_3$. Early experiments and calculations have indicated that these properties are controlled by a kind of native defect called antisites. Our calculations using the linearized Boltzmann transport equation within the relaxation time approxi

Antoine Grimaldi, Laurent U Perrinet

The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiology, especially for the performance of neuromorphic hardware, such as event-based cameras. Nonetheless, many ar

Jiajun Zhu, Yanqun Tang, Chao Yang, Chi Zhang

Integrated sensing and communication (ISAC) is a significant application scenario in future wireless communication networks, and sensing capability of a waveform is always evaluated by the ambiguity function. To enhance the sensing performance of the orthogonal time frequency space (OTFS) waveform, we propose a novel time-domain interleaved cyclic-shifted P4

Catherine Spurin, Sharon Ellman, Tom Bultreys, Hamdi Tchelepi

The injection of CO$_2$ into underground reservoirs provides a long term solution for anthropogenic emissions. A variable injection method (such as ramping the flow rate up or down) provides flexibility to injection sites, and could increase trapping at the pore-scale. However, the impact of a variable injection method on the connectivity of the gas, and sub

Wenxue Li, Junyi Zhang, Gaoxiong Zeng, Yufei Liu

RDMA has been widely adopted for high-speed datacenter networks. However, native RDMA merely supports one-to-one reliable connection, which mismatches various applications with group communication patterns (e.g., one-to-many). While there are some multicast enhancements to address it, they all fail to simultaneously achieve optimal multicast forwarding and f

Zhihao Hu, Dong Xu

Recently, diffusion models like StableDiffusion have achieved impressive image generation results. However, the generation process of such diffusion models is uncontrollable, which makes it hard to generate videos with continuous and consistent content. In this work, by using the diffusion model with ControlNet, we proposed a new motion-guided video-to-video

Junpeng Jing, Jiankun Li, Pengfei Xiong, Jiangyu Liu

Correlation based stereo matching has achieved outstanding performance, which pursues cost volume between two feature maps. Unfortunately, current methods with a fixed model do not work uniformly well across various datasets, greatly limiting their real-world applicability. To tackle this issue, this paper proposes a new perspective to dynamically calculate

Wenjie Xuan, Shanshan Zhao, Yu Yao, Juhua Liu

Relying on large-scale training data with pixel-level labels, previous edge detection methods have achieved high performance. However, it is hard to manually label edges accurately, especially for large datasets, and thus the datasets inevitably contain noisy labels. This label-noise issue has been studied extensively for classification, while still remainin

G. Sommani, C. Lagunas Gualda, H. Niederhausen

Sources of astrophysical neutrinos can potentially be discovered through the detection of neutrinos in coincidence with electromagnetic counterparts. Real-time alerts generated by IceCube play an important role in this search, acting as triggers for follow-up observations with instruments sensitive to electromagnetic signals in various wavelengths. In previo

Long Liu, Bo Zhou, Zhipeng Zhao, Zening Liu

Multi-source unsupervised domain adaptation (MUDA) aims to transfer knowledge from related source domains to an unlabeled target domain. While recent MUDA methods have shown promising results, most focus on aligning the overall feature distributions across source domains, which can lead to negative effects due to redundant features within each domain. Moreov

Yifan Feng, Jiashu Han, Shihui Ying, Yue Gao

The isomorphism problem is a fundamental problem in network analysis, which involves capturing both low-order and high-order structural information. In terms of extracting low-order structural information, graph isomorphism algorithms analyze the structural equivalence to reduce the solver space dimension, which demonstrates its power in many applications, s

Mrinmoy Roy, Sarwar J. Minar, Porarthi Dhar, A T M Omor Faruq

Detection of easily missed hidden patterns with fast processing power makes machine learning (ML) indispensable to today's healthcare system. Though many ML applications have already been discovered and many are still under investigation, only a few have been adopted by current healthcare systems. As a result, there exists an enormous opportunity in healthca

Jérémy Rousseau, Christian Alaka, Emma Covili, Hippolyte Mayard

Medical radiography segmentation, and specifically dental radiography, is highly limited by the cost of labeling which requires specific expertise and labor-intensive annotations. In this work, we propose a straightforward pre-training method for semantic segmentation leveraging Denoising Diffusion Probabilistic Models (DDPM), which have shown impressive res

Mátyás Molnár

In 2018, in preparation for the Beam Energy Scan II, the STAR detector was upgraded with the Event Plane Detector (EPD). The instrument enhanced STAR's capabilities in centrality determination for fluctuation measurements, event plane resolution for flow measurements and in triggering overall. Due to its fine radial granularity, it can also be utilized to me

Rui Xu, Liqin Shi, Yinghui Ye, Haijian Sun

Relay-enabled backscatter communication (BC) is an intriguing paradigm to alleviate energy shortage and improve throughput of Internet-of-Things (IoT) devices. Most of the existing works focus on the resource allocation that considered the unequal and continuous time allocation for both source-relay and relay-destination links. However, the continuous time a

Lorenzo Agnolucci, Alberto Baldrati, Francesco Todino, Federico Becattini

Image recognition has recently witnessed a paradigm shift, where vision-language models are now used to perform few-shot classification based on textual prompts. Among these, the CLIP model has shown remarkable capabilities for zero-shot transfer by matching an image and a custom textual prompt in its latent space. This has paved the way for several works th

Pengfei Zhao, Liyou Luo, Yongquan Liu, Jensen Li

Manipulating elastic waves using a transformation approach is challenging due to the complex constitutive relationship. However, for flexural waves, approximated as scalar waves, two straightforward approaches emerge based on geometric curvature and plate thickness. Here, we develop transformation theory to establish equivalence between curved plates of diff

Henry Fraser, Jose-Miguel Bello y Villarino

This paper critically evaluates the European Commission's proposed AI Act's approach to risk management and risk acceptability for high-risk AI systems that pose risks to fundamental rights and safety. The Act aims to promote "trustworthy" AI with a proportionate regulatory burden. Its provisions on risk acceptability require residual risks from high-risk sy

Dong Lu, Zhiqiang Wang, Teng Wang, Weili Guan

Vision-language pre-training (VLP) models have shown vulnerability to adversarial examples in multimodal tasks. Furthermore, malicious adversaries can be deliberately transferred to attack other black-box models. However, existing work has mainly focused on investigating white-box attacks. In this paper, we present the first study to investigate the adversar

A. Mandilara, B. Dellen, U. Jaekel, T. Valtinos

We propose a model for data classification using isolated quantum $d$-level systems or else qudits. The procedure consists of an encoding phase where classical data are mapped on the surface of the qudit's Bloch hyper-sphere via rotation encoding, followed by a rotation of the sphere and a projective measurement. The rotation is adjustable in order to contro

Olivier Jeunen

Modern web-based platforms show ranked lists of recommendations to users, attempting to maximise user satisfaction or business metrics. Typically, the goal of such systems boils down to maximising the exposure probability for items that are deemed "reward-maximising" according to a metric of interest. This general framing comprises streaming applications, as

Ken T. Mori, Trent Brown, Steven Peters

Despite the presence of the classification task in many different benchmark datasets for perception in the automotive domain, few efforts have been undertaken to define consistent classification requirements. This work addresses the topic by proposing a structured method to generate a classification structure. First, legal categories are identified based on

Eli Belkind, Ran Dubin, Amit Dvir

With the advance in malware technology, attackers create new ways to hide their malicious code from antivirus services. One way to obfuscate an attack is to use common files as cover to hide the malicious scripts, so the malware will look like a legitimate file. Although cutting-edge Artificial Intelligence and content signature exist, evasive malware succes

Nikoleta Ilić, Katja Poppenhaeger, Desmond Dsouza, Scott J. Wolk

The magnetic activity of low-mass stars changes as they age. The primary process decreasing the stellar activity level is the angular momentum loss via magnetized stellar wind. However, processes like tidal interactions between stars and their close companions may slow down the braking effect and the subsequent decrease of the activity level. Until now, the

Ravindra Singh

Measurements of heavy-flavour tagged jets, allow for comparisons of the heavy quarks (charm and beauty) production, propagation, and hadronization across different collision systems. Comparison of measurements performed in pp with Pb--Pb collisions can help in studying the possible modification of the heavy-quark production and hadronization inside jets due

Tomislav Došlić, Luka Podrug

We study a recursively defined two-parameter family of graphs which generalize Fibonacci cubes and Pell graphs and determine their basic structural and enumerative properties. In particular, we show that all of them are induced subgraphs of hypercubes and present their canonical decompositions. Further, we compute their metric invariants and establish some H

Nobuchika Okada, Osamu Seto

We study the flavor dependent $U(1)_{B_i-L_j}$ models, where an $i$th generation of quarks and $j(\neq i)$th generation of leptons are charged. By solving the anomaly free condition for the matter sector of the SM fermions and three generations of right-handed (RH) neutrinos, we find that the $j$th generation of RH neutrino is not necessarily charged under t

Jialun Pei, Zhangjun Zhou, Yueming Jin, He Tang

High-accuracy Dichotomous Image Segmentation (DIS) aims to pinpoint category-agnostic foreground objects from natural scenes. The main challenge for DIS involves identifying the highly accurate dominant area while rendering detailed object structure. However, directly using a general encoder-decoder architecture may result in an oversupply of high-level feat

Ruowei Wang, Yu Liu, Pei Su, Jianwei Zhang

Shape generation is the practice of producing 3D shapes as various representations for 3D content creation. Previous studies on 3D shape generation have focused on shape quality and structure, without or less considering the importance of semantic information. Consequently, such generative models often fail to preserve the semantic consistency of shape struc

Yang Gou, Yinghui Ye, Guangyue Lu, Lu Lv

In this paper, we consider intelligent reflecting surface (IRS) in a non-orthogonal multiple access (NOMA)-aided Integrated Sensing and Multicast-Unicast Communication (ISMUC) system, where the multicast signal is used for sensing and communications while the unicast signal is used only for communications. Our goal is to depict whether the IRS improves the p

Kurada T S S Satyanarayana, Addada Narasimha Rao

Among the various factors affecting the firms positioning and performance in modern day markets, capital structure of the firm has its own way of expressing itself as a crucial one. With the rapid changes in technology, firms are being pushed onto a paradigm that is burdening the capital management process. Hence the study of capital structure changes gives

Haein Cho, Soon-Yi Kang, Byungchan Kim

A Known Alder-type partition inequality of level $a$, which involves the second Rogers-Ramanujan identity when the level $a$ is 2, states that the number of partitions of $n$ into parts differing by at least $d$ with the smallest part being at least $a$ is greater than or equal to that of partitions of $n$ into parts congruent to $\pm a \pmod{d+3}$, excludin

Graziano Gentili, Jasna Prezelj, Fabio Vlacci

This paper focuses on the problem of finding a continuous extension of the hypercomplex logarithm along a path. While a branch of the complex logarithm can be defined in a small open neighbourhood of a strictly negative real point, no continuous branch of the hypercomplex logarithm can be defined in any open set $A\subset \mathbb K\setminus \{0\}$ which cont

Sofia Zinzani, Francesca Baletto

It is far well accepted that the morphology of nanoparticles and nanoalloys is of paramount importance to understand their properties. Furthemore, the morphology depends on the growth mechanism with coalescence generally accepted as one the most common mechanisms both in liquid and in the gas phase. Coalescence refers when two existing seeds collide and aggr

Simon Wassing, Stefan Langer, Philipp Bekemeyer

The numerical approximation of solutions to the compressible Euler and Navier-Stokes equations is a crucial but challenging task with relevance in various fields of science and engineering. Recently, methods from deep learning have been successfully employed for solving partial differential equations by incorporating the equations into a loss function that i

Jeremy Andrea, Nicolas Chanon

Since the initial measurements of single-top quark production at the Tevatron in 2009, tremendous progress has been made at the LHC. While LHC Run 1 marked the beginning of a precision era for the single-top quark measurements in some of the main production mechanisms, LHC Run 2 witnessed the emergence and exploration of new processes associating top quark p

Callum Gray, Lekshmi Kailas, Peter G. Adams, Christopher D. P. Duffy

The plant light-harvesting pigment-protein complex LHCII is the major antenna sub-unit of PSII and is generally (though not universally) accepted to play a role in photoprotective energy dissipation under high light conditions, a process known Non-Photochemical Quenching (NPQ). The underlying mechanisms of energy trapping and dissipation within LHCII are sti

Tomoya Kinugawa, Takashi Nakamura, Hiroyuki Nakano

We focus on gravitational-wave events of binary black-hole mergers up to the third observing run with the minimum false alarm rate smaller than $10^{-5}\,{\rm yr}^{-1}$. These events tell us that the mass ratio of two black holes follows $m_2/m_1=0.723$ with the chance probability of 0.00301% for the chirp mass $M_{\rm chirp} > 18\,M_{\odot}$. We show that t

Anwitaman Datta, Chua Chiah Soon, Wangfan Gu

We propose cryptographic protocols to incorporate time provenance guarantees while meeting confidentiality and controlled sharing needs for research data. We demonstrate the efficacy of these mechanisms by developing and benchmarking a practical tool, GovernR, which furthermore takes into usability issues and is compatible with a popular open-sourced researc

Fabio Durastante, Beatrice Meini

We propose two approaches, based on Riemannian optimization, for computing a stochastic approximation of the $p$th root of a stochastic matrix $A$. In the first approach, the approximation is found in the Riemannian manifold of positive stochastic matrices. In the second approach, we introduce the Riemannian manifold of positive stochastic matrices sharing w

Gerard van der Geer, Shushi Harashita

We prove a formula for the cycle class of the supersingular locus in the Chow ring with rational coefficients of the moduli space of principally polarized abelian varieties in characteristic $p$. This formula determines this class as a monomial in the Chern classes of the Hodge bundle up to a factor that is a polynomial in $p$. This factor is known for $g\le

Ying Guo, Cheng Zhen, Pengfei Yan

Recent studies on face forgery detection have shown satisfactory performance for methods involved in training datasets, but are not ideal enough for unknown domains. This motivates many works to improve the generalization, but forgery-irrelevant information, such as image background and identity, still exists in different domain features and causes unexpecte

Longcheng Guo

We first define appropriate state representation and action space, and then design an adjustment mechanism based on the actions selected by the intelligent agent. The adjustment mechanism outputs the next state and reward value of the agent. Additionally, the adjustment mechanism calculates the error between the adjusted state and the unadjusted state. Furth

O. A. Veliev

In this paper we consider the Bloch eigenvalues and spectrum of the non-self-adjoint differential operator L generated by the differential expression of odd order n with the periodic PT-symmetric coefficients, where n>1. We study the localizations of the Bloch eigenvalues and the structure of the spectrum. Moreover, we find conditions on the norm of the coef

Yiteng Xu, Peishan Cong, Yichen Yao, Runnan Chen

Human-centric scene understanding is significant for real-world applications, but it is extremely challenging due to the existence of diverse human poses and actions, complex human-environment interactions, severe occlusions in crowds, etc. In this paper, we present a large-scale multi-modal dataset for human-centric scene understanding, dubbed HuCenLife, wh

Jingxin Zhang, Jiawei Xi, Peixing Li, Ray C. C. Cheung

Deep learning, as a highly efficient method for metasurface inverse design, commonly use simulation data to train deep neural networks (DNNs) that can map desired functionalities to proper metasurface designs. However, the assumptions and simplifications made in the simulation model may not reflect the actual behavior of a complex system, leading to suboptim

Nao Hirokawa, Aart Middeldorp

We present a new encoding of the Battle of Hercules and Hydra as a rewrite system with AC symbols. Unlike earlier term rewriting encodings, it faithfully models any strategy of Hercules to beat Hydra. To prove the termination of our encoding, we employ type introduction in connection with many-sorted semantic labeling for AC rewriting and AC-MPO, a new AC co

Yuhang Guo, Mengzhao Li, Mengchen Niu, Zhijun Liang

A comprehensive and reliable nuclear database of neutron-induced process is required by the development of Accelerator-Driven System technology. Although many excellent efforts have been made, the measurements to the fission fragment in zero degree of the beam direction is not perfect enough. Most detector can not work constantly under the strike of intense

Viktor Linders, Mark Carpenter, Jan Nordström

A stencil-adaptive SBP-SAT finite difference scheme is shown to display superconvergent behavior. Applied to the linear advection equation, it has a convergence rate $\mathcal{O}(\Delta x^4)$ in contrast to a conventional scheme, which converges at a rate $\mathcal{O}(\Delta x^3)$.

Jaka Hedžet, Michael A. Henning

Given a graph $G$ and assuming that some vertices of $G$ are infected, the $r$-neighbor bootstrap percolation rule makes an uninfected vertex $v$ infected if $v$ has at least $r$ infected neighbors. The $r$-percolation number, $m(G, r)$, of $G$ is the minimum cardinality of a set of initially infected vertices in $G$ such that after continuously performing t

Sue Sin Chong, Yi Sheng Ng, Hui-Qiong Wang, Jin-Cheng Zheng

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field,

Songbo Hu, Han Zhou, Mete Hergul, Milan Gritta

Creating high-quality annotated data for task-oriented dialog (ToD) is known to be notoriously difficult, and the challenges are amplified when the goal is to create equitable, culturally adapted, and large-scale ToD datasets for multiple languages. Therefore, the current datasets are still very scarce and suffer from limitations such as translation-based no

Luca Cavalli, Daniel Barath, Marc Pollefeys, Viktor Larsson

RANSAC and its variants are widely used for robust estimation, however, they commonly follow a greedy approach to finding the highest scoring model while ignoring other model hypotheses. In contrast, Iteratively Reweighted Least Squares (IRLS) techniques gradually approach the model by iteratively updating the weight of each correspondence based on the resid

Tetsuya Yamamoto, Hiroshi Watanabe

It is important to understand the dynamics of red blood cells (RBCs) in blood flow. This requires the formulation of coarse-grained RBC models that reproduce the hydrodynamic properties of blood accurately. One of the models that successfully reproduce the rheology and morphology of blood has been proposed by Fedosov et al. [D. A. Fedosov, B. Caswell, and G.

Danica Kosanović

For any smooth manifold $M$ of dimension $d\geq4$ we construct explicit classes in homotopy groups of spaces of embeddings of either an arc or a circle into $M$, in every degree that is a multiple of $d-3$, and show that they are detected in the Taylor tower of Goodwillie and Weiss. The classes are obtained from families of string links constructed in the $d

Tatiana Demidova, Ivan Shevchenko

Extensive numerical experiments on the long-term dynamics of planetesimals near the orbits of planets around single stars with debris disks have been carried out. The radial sizes of planetesimal clusters and the planetary chaotic zone as a function of mass parameter $\mu$ (planet-star mass ratio) have been determined numerically with a high accuracy separat

Daniel González-Iglesias, Benito Gimeno, Daniel Esperante, Pablo Martinez-Reviriego

The objective of this work is the evaluation of the risk of suffering a multipactor discharge in an S-band dielectric-assist accelerating (DAA) structure for a compact low-energy linear particle accelerator dedicated to hadrontherapy treatments. A DAA structure consists of ultra-low loss dielectric ciylinders and disks with irises which are periodically arra

Salome Kazeminia, Carsten Marr, Bastian Rieck

Multiple instance learning (MIL) is a framework for weakly supervised classification, where labels are assigned to sets of instances, i.e., bags, rather than to individual data points. This paradigm has proven effective in tasks where fine-grained annotations are unavailable or costly to obtain. However, the effectiveness of MIL drops sharply when training d

Friedrich-Karl Thielemann, Thomas Rauscher

This chapter will go through the important nuclear reactions in stellar evolution and explosions, passing through the individual stellar burning stages and also explosive burning conditions. To follow the changes in the composition of nuclear abundances requires the knowledge of the relevant nuclear reaction rates. For light nuclei (entering in early stellar

Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu

Conversational recommendation systems (CRS) aim to interactively acquire user preferences and accordingly recommend items to users. Accurately learning the dynamic user preferences is of crucial importance for CRS. Previous works learn the user preferences with pairwise relations from the interactive conversation and item knowledge, while largely ignoring th