July 2022 arXiv papers — page 38

Peng Chen, Xixi Lin, Lixin Yan

In this paper, we study the $L^p$-boundedness of the commutator $[b, S_R^\delta(H)](f) = bS_R^\delta(H) f - S_R^\delta(H)(bf)$ of a BMO function $b$ and the Bochner-Riesz means $S_R^\delta(H)$ for Hermite operator $H=-\Delta +|x|^2$ on $\mathbb{R}^n$, $n\geq2$. We show that if $\delta>\delta(q)=n(1/q -1/2)- 1/2$, the commutator $[b,S_R^\delta(H)]$ is bounded

N. Gopalswamy, S. Yashiro, S. Akiyama, H. Xie

We report on the solar and interplanetary (IP) causes of the third largest geomagnetic storm (2018 August 26) in solar cycle 24. The underlying coronal mass ejection (CME) originating from a quiescent filament region becomes a 440 km/s magnetic cloud (MC) at 1 au after ~5 days. The prolonged CME acceleration (for about 24 hrs) coincides with the time profile

Todd Schmid

It came to the attention of myself and the coauthors of (S., Rozowski, Silva, Rot, 2022) that a number of process calculi can be obtained by algebraically presenting the branching structure of the transition systems they specify. Labelled transition systems, for example, branch into sets of transitions, terms in the free semilattice generated by the transiti

B. G. Palm, F. M. Bayer, R. J. Cintra

In this paper, we propose five prediction intervals for the beta autoregressive moving average model. This model is suitable for modeling and forecasting variables that assume values in the interval $(0,1)$. Two of the proposed prediction intervals are based on approximations considering the normal distribution and the quantile function of the beta distribut

Shadikur Rahman, Umme Ayman Koana, Maleknaz Nayebi

Background: Code reviewing is an essential part of software development to ensure software quality. However, the abundance of review tasks and the intensity of the workload for reviewers negatively impact the quality of the reviews. The short review text is often unactionable, which needs further interaction between the reviewer and the developer. The proble

O. A. Acevedo, B. M. Pimentel

We study quantum electrodynamics (QED) in the light-front dynamical form by using null-plane causal perturbation theory. We establish the equivalence with instant dynamics for the scattering processes, whose normalization allows to construct the instantaneous terms of the usual null-plane QED Lagrangian density. Then we study vacuum polarization and normaliz

R. V. R. Pandya

In this paper, we propose generalized attention mechanism (GAM) by first suggesting a new interpretation for self-attention mechanism of Vaswani et al. . Following the interpretation, we provide description for different variants of attention mechanism which together form GAM. Further, we propose a new relative position representation within the framework of

Clayton Barnes, Krzysztof Burdzy, Alex Forney, Zach Dingels

Simulations support the conjecture that the dimension of the trace of Brownian earthworm is strictly greater than 3/2.

Oiwi Parker Jones, Brendan Shillingford

In contrast to the older writing system of the 19th century, modern Hawaiian orthography employs characters for long vowels and glottal stops. These extra characters account for about one-third of the phonemes in Hawaiian, so including them makes a big difference to reading comprehension and pronunciation. However, transliterating between older and newer tex

Jiaxi Nie, Erlang Surya, Ji Zeng

A convex geometric graph $G$ is said to be packable if there exist edge-disjoint copies of $G$ in the complete convex geometric graph $K_n$ covering all but $o(n^2)$ edges. We prove that every convex geometric graph with cyclic chromatic number at most $4$ is packable. With a similar definition of packability for ordered graphs, we prove that every ordered g

Nirmalya Thakur, Chia Y. Han

Falls, highly common in the constantly increasing global aging population, can have a variety of negative effects on their health, well-being, and quality of life, including restricting their capabilities to conduct Activities of Daily Living (ADLs), which are crucial for one's sustenance. Timely assistance during falls is highly necessary, which involves tr

Huandong Chen, Batyr Ilyas, Boyang Zhao, Emre Ergecen

Electron-lattice coupling effects in low dimensional materials give rise to charge density wave (CDW) order and phase transitions. These phenomena are critical ingredients for superconductivity and predominantly occur in metallic model systems such as doped cuprates, transition metal dichalcogenides, and more recently, in Kagome lattice materials. However, C

Nikhil Ghosh, Mikhail Belkin

In this work we establish an algorithm and distribution independent non-asymptotic trade-off between the model size, excess test loss, and training loss of linear predictors. Specifically, we show that models that perform well on the test data (have low excess loss) are either "classical" -- have training loss close to the noise level, or are "modern" -- hav

Qi Wu, David Bauer, Michael J. Doyle, Kwan-Liu Ma

Neural networks have shown great potential in compressing volume data for visualization. However, due to the high cost of training and inference, such volumetric neural representations have thus far only been applied to offline data processing and non-interactive rendering. In this paper, we demonstrate that by simultaneously leveraging modern GPU tensor cor

Gabriel P. L. M. Fernandes, Alexandre C. Ricardo, Fernando R. Cardoso, Celso J. Villas-Boas

In this paper we describe one of the most promising platforms for the construction of a universal quantum computer, which consists of a chain of $N$ ions trapped in a harmonic potential, whose internal states work out as qubits, and are coupled to collective vibrational modes of the chain. From such coupling, it is possible to build interactions between diff

Roumen Anguelov, Jean Lubuma

We consider a dynamical system, defined by a system of autonomous differential equations, on $\Omega\subset\mathbb{R}^n$. By using Mickens' rule on the nonlocal approximation of nonlinear terms, we construct an implicit Nonstandard Finite Difference (NSFD) scheme that, under an existence and uniqueness condition, is an explicit time reversible scheme. Apart

Wei-Sheng Lai, YiChang Shih, Lun-Cheng Chu, Xiaotong Wu

Motion blur of fast-moving subjects is a longstanding problem in photography and very common on mobile phones due to limited light collection efficiency, particularly in low-light conditions. While we have witnessed great progress in image deblurring in recent years, most methods require significant computational power and have limitations in processing high

Kamal R. Joshi, Sunil Ghimire, Makariy A. Tanatar, Amlan Datta

Niobium thin films on silicon substrate used in the fabrication of superconducting qubits have been characterized using scanning and transmission electron microscopy, electrical transport, magnetization, quasiparticle spectroscopy, and real-space real-time magneto-optical imaging. We study niobium films to provide an example of a comprehensive analytical set

Youheng Zhang

This paper reviews the historical development of AI and representative philosophical thinking from the perspective of the research paradigm. Additionally, it considers the methodology and applications of AI from a philosophical perspective and anticipates its continued advancement. In the history of AI, Symbolism and connectionism are the two main paradigms

Oğuzhan Ersoy, Jérémie Decouchant, Satwik Prabhu Kimble, Stefanie Roos

Payment channel networks (PCNs) enhance the scalability of blockchains by allowing parties to conduct transactions off-chain, i.e, without broadcasting every transaction to all blockchain participants. To conduct transactions, a sender and a receiver can either establish a direct payment channel with a funding blockchain transaction or leverage existing chan

Amr S. Abdelfattah, Tamer Abdelkader, EI-Sayed M. EI-Horbaty

The Mobile intermittent wireless connectivity limits the evolution of the mobile landscape, such that this progress coupled with the ubiquitous nature of the Internet and the web services. The web service Reliability achieves the low overhead communication and retrieves the appropriate state response from the web service consumption. This paper discusses and

Amr S. Abdelfattah, Tamer Abdelkader, EI-Sayed M. EI-Horbaty

The evolution of the mobile landscape is coupled with the ubiquitous nature of the Internet with its intermittent wireless connectivity and the web services. Achieving the web service reliability results in low communication overhead and retrieving the appropriate response. The Middleware Approach (MA) is highly tended to achieve the web service reliability.

Luke Conaboy, Ilian T. Iliev, Anastasia Fialkov, Keri L. Dixon

Supersonic relative motion between baryons and dark matter due to the decoupling of baryons from the primordial plasma after recombination affects the growth of the first small-scale structures. Large box sizes (greater than a few hundred Mpc) are required to sample the full range of scales pertinent to the relative velocity, while the effect of the relative

Sudeshna Patra, Neal J. Evans, Kee-Tae Kim, Mark Heyer

We have mapped HCN and HCO$^{+}$ (J = 1 $\to$ 0) line emission toward a sample of seven star-forming regions (with 12 + log[O/H] range from 8.34 to 8.69) in the outer Milky Way (Galactocentric distance > 9.5 kpc), using the 14-meter radio telescope of the Taeduk Radio Astronomy Observatory (TRAO). We compare these two molecular lines with other conventional

Florin Boenkost, Félix Foutel-Rodier, Emmanuel Schertzer

Building on the spinal decomposition technique in Foutel-Rodier and Schertzer (2022) we prove a Yaglom limit law for the rescaled size of a nearly critical branching process in varying environment conditional on survival. In addition, our spinal approach allows us toprove convergence of the genealogical structure of the population at a fixed time horizon --

Amlan Banaji, Jonathan M. Fraser

We study the dimension theory of limit sets of iterated function systems consisting of a countably infinite number of conformal contractions. Our focus is on the Assouad type dimensions, which give information about the local structure of sets. Under natural separation conditions, we prove a formula for the Assouad dimension and prove sharp bounds for the As

Martin Ukrop, Lydia Kraus, Vashek Matyas

Flawed TLS certificates are not uncommon on the Internet. While they signal a potential issue, in most cases they have benign causes (e.g., misconfiguration or even deliberate deployment). This adds fuzziness to the decision on whether to trust a connection or not. Little is known about perceptions of flawed certificates by IT professionals, even though thei

Hossein A. Rahmani, Mohammadmehdi Naghiaei, Ali Tourani, Yashar Deldjoo

Recommending appropriate travel destinations to consumers based on contextual information such as their check-in time and location is a primary objective of Point-of-Interest (POI) recommender systems. However, the issue of contextual bias (i.e., how much consumers prefer one situation over another) has received little attention from the research community.

Amr S. Abdelfattah, Tamer Abdelkader, EI-Sayed M. EI-Horbaty

The intermittent wireless connectivity in Mobiles limits the spread of mobile applications usage over the web, such that the web services are the independent protocol that used to achieve the mobile connectivity with the cloud services. Achieving the web service reliability results in two aspects. The first is low communication overhead and retrieving the ap

Roger Casals, Eugene Gorsky, Mikhail Gorsky, Ian Le

We show the existence of cluster $\mathcal{A}$-structures and cluster Poisson structures on any braid variety, for any simple Lie group. The construction is achieved via weave calculus and a tropicalization of Lusztig's coordinates. Several explicit seeds are provided and the quiver and cluster variables are readily computable. We prove that these upper clus

Jakub Mojsiejuk, Sławomir Ziętek, Krzysztof Grochot, Witold Skowroński

We present cmtj - a comprehensive simulation package that allows large-scale macrospin simulations for a variety of multilayer spintronics devices. Apart from conventional static simulations, such as magnetoresistance and magnetisation hysteresis loops, cmtj implements a mathematical model of dynamic experimental techniques commonly used for spintronics devi

Seyed Ehsan Marjani Bajestani, Giovanni Beltrame

Event-based cameras (ECs) are bio-inspired sensors that asynchronously report brightness changes for each pixel. Due to their high dynamic range, pixel bandwidth, temporal resolution, low power consumption, and computational simplicity, they are beneficial for vision-based projects in challenging lighting conditions and they can detect fast movements with th

Bowen Xie

We consider multi-component matching systems in heavy traffic consisting of $K\geq 2$ distinct perishable components which arrive randomly over time at high speed at the assemble-to-order station, and they wait in their respective queues according to their categories until matched or their ``patience" runs out. An instantaneous match occurs if all categories

Amr S. Abdelfattah

The evolution of decentralized microservice-based systems is challenging. These challenges are classified into static and dynamic categories. Regarding the static perspective, documenting and visualizing the fluid application topology is something few have been able to accomplish. Building an architecture map of services design is a complicated task in its i

Jan Koniarik, Daniel Dlhopolcek, Martin Ukrop

Due to the pandemic of COVID-19, many university courses had to abruptly transform to enable remote teaching. Adjusting courses on embedded systems and micro-controllers was extra challenging since interaction with real hardware is their integral part. We start by comparing our experience with four basic alternatives of teaching embedded systems: 1) interact

Emma Riese, Madeleine Lorås, Martin Ukrop, Tomáš Effenberger

Teaching assistants (TAs) are heavily used in computer science courses as a way to handle high enrollment and still being able to offer students individual tutoring and detailed assessments. TAs are themselves students who take on this additional role in parallel with their own studies at the same institution. Previous research has shown that being a TA can

Patrick Cabau, Fernand Pelletier

We introduce three notions of partial bihamiltonian structures ($\operatorname{PQ}$, $\operatorname{PN}$ et $\operatorname{P\Omega}$) in the convenient setting defined by Fr\"{o}licher, Kriegl and Michor. We study geometrical objects linked with these structures and give examples in finite and infinite dimensions.

Peter Achten, Elena Machkasova

This volume contains the papers, accepted after post-reviewing, based on presentations submitted to TFPIE 2021 and TFPIE 2022 that took place online, in collaboration with LambdaDays 2021/22 in Krak\'ow, Poland. TFPIE stands for Trends in Functional Programming in Education, where authors present research and experiences in teaching concepts of functional pr

C. Moore, C. M. Adhikari, T. Das, L. Resch

The optical properties of monocrystalline, intrinsic silicon are of interest for technological applications as well as fundamental studies of atom-surface interactions. For an enhanced understanding, it is of great interest to explore analytic models which are able to fit the experimentally determined dielectric function $\epsilon(T_\Delta, \omega)$, over a

Zhenling Yang, Huacheng Song, Qiunan Wu

Recall that most of the current image style transfer methods require the user to give an image of a particular style and then extract that styling feature and texture to generate the style of an image, but there are still some problems: the user may not have a reference style image, or it may be difficult to summarise the desired style in mind with just one

Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan

We present a non-asymptotic lower bound on the eigenspectrum of the design matrix generated by any linear bandit algorithm with sub-linear regret when the action set has well-behaved curvature. Specifically, we show that the minimum eigenvalue of the expected design matrix grows as $\Omega(\sqrt{n})$ whenever the expected cumulative regret of the algorithm i

Prem Kant, Urban Larsson, Ravi K. Rai, Akshay V. Upasany

A class of discrete Bidding Combinatorial Games that generalize alternating normal play was introduced by Kant, Larsson, Rai, and Upasany (2022). The major questions concerning optimal outcomes were resolved. By generalizing standard game comparison techniques from alternating normal play, we propose an algorithmic play-solution to the problem of game compar

Graham Coop

A common sample descriptor in human genomics studies is that of 'genetic ancestry group', with terms such as 'European genetic ancestry' or 'East Asian genetic ancestry' frequently used in publications to describe the genetics of groups of individuals based on the analysis of their genotypes. In this Perspective, I argue that these terms are imprecise and po

Chongyang Deng, Ming-Jun Lai

We first extend the construction of generalized barycentric coordinates (GBC) based on the vertices on the boundary of a polygon $\Omega$ to a new kind of GBCs based on vertices inside the $\Omega$ of interest. For clarity, the standard GBCs are called boundary GBCs while the new GBCs are called interior GBCs. Then we present an analysis on these two kinds o

Itai Benjamini, Maksim Zhukovskii

In this paper we find an integer $h=h(n)$ such that the minimum number of variables of a first order sentence that distinguishes between two independent uniformly distributed random graphs of size $n$ with the asymptotically largest possible probability $\frac{1}{4}-o(1)$ belongs to $\{h,h+1,h+2,h+3\}$. We also prove that the minimum (random) $k$ such that t

Simon Axelrod, Eugene Shakhnovich, Rafael Gomez-Bombarelli

Molecular photoswitches are the foundation of light-activated drugs. A key photoswitch is azobenzene, which exhibits trans-cis isomerism in response to light. The thermal half-life of the cis isomer is of crucial importance, since it controls the duration of the light-induced biological effect. Here we introduce a computational tool for predicting the therma

Nathaniel Clause, Woojin Kim, Facundo Mémoli

In addition to inherent computational challenges, the absence of a canonical method for quantifying `persistence' in multi-parameter persistent homology remains a hurdle in its application. One of the best known quantifications of persistence for multi-parameter persistent homology is the rank invariant, which has recently evolved into the generalized rank i

Joel Therrien, Jiguo Cao

Random forests are a sensible non-parametric model to predict competing risk data according to some covariates. However, there are currently no packages that can adequately handle large datasets ($n > 100,000$). We introduce a new R package, largeRCRF, using the random competing risks forest theory developed by Ishwaran et al. (2014). We verify our package's

Aleksandr V. Mosenkov, Pavel A. Usachev, Zacory Shakespear, Jacob Guerrette

In this first paper in a series we present a study of the global dust emission distribution in nearby edge-on spiral galaxies. Our sample consists of 16 angularly large and 13 less spatially resolved galaxies selected from the DustPedia sample. To explore the dust emission distribution, we exploit the Herschel photometry in the range 100-500 $\mu$m. We emplo

Lucas Bouck, Ricardo H. Nochetto, Vladimir Yushutin

We develop a Q-tensor model of nematic liquid crystals occupying a stationary surface which represents a fluidic material film in space. In addition to the evolution due to Landau--de\,Gennes energy the model includes a tangent viscous incompressible flow along the surface. A thermodynamically consistent coupling of a two-dimensional flow and a three-dimensi

Swarup N. Ghosh, Alexander J. Izzo

It is shown that a uniform algebra can have a nonzero bounded point derivation while having no nontrivial Gleason parts. Conversely, a uniform algebra can have a nontrivial Gleason part while having no nonzero, even possibly unbounded, point derivations.

Michael J. McGuffin, Ryan Servera, Marie Forest

It is common to advise against using 3D to visualize abstract data such as networks, however Ware and Mitchell's 2008 study showed that path tracing in a network is less error prone in 3D than in 2D. It is unclear, however, if 3D retains its advantage when the 2D presentation of a network is improved using edge-routing, and when simple interaction techniques

S. Spor

The anomalous $ZZ\gamma$ and $Z\gamma\gamma$ neutral triple gauge couplings occurred by dimension-eight operators are investigated through the process $\mu^+\mu^-\,\rightarrow\,\mu^+\gamma^*\mu^-\,\rightarrow\,\mu^+ Z(\nu\bar{\nu})\mu^-$ at the muon collider with $\sqrt{s}=3$, $6$, $10$ and $14$ TeV. The charged lepton pseudo-rapidity, the charged lepton tra

Juan Carlos D'Olivo Saez, José Arnulfo Herrera Lara, Ismael Romero, Oscar Alfredo Sampayo

Knowledge of the composition of the Earth's interior is highly relevant to many geophysical and geochemical problems. Neutrino oscillations are modified in a non-trivial way by the matter effects and can provide valuable and unique information not only on the density but also on the chemical and isotopic composition of the deep regions of the planet. In this

Michael Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette

Practising and honing skills forms a fundamental component of how humans learn, yet artificial agents are rarely specifically trained to perform them. Instead, they are usually trained end-to-end, with the hope being that useful skills will be implicitly learned in order to maximise discounted return of some extrinsic reward function. In this paper, we inves

Jingkai Yan, Robert Colgan, John Wright, Zsuzsa Márka

Gravitational wave astronomy is a vibrant field that leverages both classic and modern data processing techniques for the understanding of the universe. Various approaches have been proposed for improving the efficiency of the detection scheme, with hierarchical matched filtering being an important strategy. Meanwhile, deep learning methods have recently dem

Nicolas Legendre, Khanh Dao Duc, Nina Miolane

Recent advances in variational autoencoders (VAEs) have enabled learning latent manifolds as compact Lie groups, such as $SO(d)$. Since this approach assumes that data lies on a subspace that is homeomorphic to the Lie group itself, we here investigate how this assumption holds in the context of images that are generated by projecting a $d$-dimensional volum

Gregory Holste, Evangelos K. Oikonomou, Bobak J. Mortazavi, Zhangyang Wang

Advances in self-supervised learning (SSL) have shown that self-supervised pretraining on medical imaging data can provide a strong initialization for downstream supervised classification and segmentation. Given the difficulty of obtaining expert labels for medical image recognition tasks, such an "in-domain" SSL initialization is often desirable due to its

H. El Moumni, J. Khalloufi, K. Masmar

The purpose of the current letter is to give some relevant clarification on the validity of the laws of thermodynamics and the stability of the horizon by scalar field scattering formalism. On the one side, the connection between the energy of the absorbed particle and the change of the enthalpy of the black hole appears to resolve the violation of the secon

Yunan Yang, Denis Silantyev, Russel Caflisch

We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in [Caflisch, R., Silantyev, D. and Yang, Y., 2021. Journal of Computational Physics, 439, p.110404], which was restricted to the case of Maxwell molecules, for wh

Shraddha Pathak, Ankur A. Kulkarni

During an epidemic, the information available to individuals in the society deeply influences their belief of the epidemic spread, and consequently the preventive measures they take to stay safe from the infection. In this paper, we develop a scalable framework for ascertaining the optimal information disclosure a government must make to individuals in a net

Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis

Deep Learning models have become dominant in tackling financial time-series analysis problems, overturning conventional machine learning and statistical methods. Most often, a model trained for one market or security cannot be directly applied to another market or security due to differences inherent in the market conditions. In addition, as the market evolv

Safwan Alfattani, Animesh Yadav, Halim Yanikomeroglu, Abbas Yongacoglu

In the future, urban regions will encounter a massive number of capacity-hungry devices. Relying solely on terrestrial networks for serving all UEs will be a cost-ineffective approach. Consequently, with the anticipated supply and demand mismatch, several UEs will be unsupported. To offer service to the left-out UEs, we employ an energy-efficient and cost-ef

Matthias Bachfischer, Renata Borovica-Gajic, Benjamin I. P. Rubinstein

While early empirical evidence has supported the case for learned index structures as having favourable average-case performance, little is known about their worst-case performance. By contrast, classical structures are known to achieve optimal worst-case behaviour. This work evaluates the robustness of learned index structures in the presence of adversarial

Yun-Jin Zhang, A-Li Luo, Bi-Wei Jiang, Wen Hou

We identify 20 F-type Herbig stars and provide a list of 22 pre-main-sequence candidates from LAMOST DR8. The effective temperature, distance, extinction, stellar luminosity, mass, and radius are derived for each Herbig star based on optical spectra, photometry, Gaia EDR3 parallaxes, and pre-main-sequence evolutionary tracks. According to spectral energy dis

Wolfgang Weingarten

Experimental data on N-doped superconducting (sc) cavities are further analyzed which contribute to confirm a recently proposed model explaining the increase of the Q-value versus the accelerating gradient.

Susmita Sarkar, Nayan Sarkar, Farook Rahaman, Y Aditya

The wormhole solution could be found by solving the Einstein field equations with violating the null energy condition (NEC). We represent wormhole solutions in $\kappa(R,T)$ gravity in two different ways. At first, we find the shape function by considering a redshift function and linear equation of state (EoS). The solution represents a wormhole for the real

K. D. Leka, Eric L. Wagner, Ana Belén Griñón-Marín, Véronique Bommier

The problem of bias, meaning over- or underestimation, of the component perpendicular to the line-of-sight, Bperp, in vector magnetic field maps is discussed. Previous works on this topic have illustrated that the problem exists; here we perform novel investigations to quantify the bias, fully understand its source(s), and provide mitigation strategies. Firs

Fernando Manrique de Lara, Esteban Ferrer

We propose to accelerate a high order discontinuous Galerkin solver using neural networks. We include a corrective forcing to a low polynomial order simulation to enhance its accuracy. The forcing is obtained by training a deep fully connected neural network, using a high polynomial order simulation but only for a short time frame. With this corrective forci

Carolina A. Mosquera, Andrea Olivo

We prove that the Fourier transform of self-similar measures on the complex plane has fast decay outside of a very sparse set of frequencies, with quantitative estimates, extending the results obtained in the real line, first by R. Kaufman, and later, with quantitative bounds, by the first author and P. Shmerkin. Also we derive several applications concernin

Andrew Hundt, William Agnew, Vicky Zeng, Severin Kacianka

Stereotypes, bias, and discrimination have been extensively documented in Machine Learning (ML) methods such as Computer Vision (CV) [18, 80], Natural Language Processing (NLP) [6], or both, in the case of large image and caption models such as OpenAI CLIP [14]. In this paper, we evaluate how ML bias manifests in robots that physically and autonomously act w

Jose Cruz, Maria Grossinho, Daniel Sevcovic, Cyril Izuchukwu Udeani

The purpose of this review paper is to present our recent results on nonlinear and nonlocal mathematical models arising from modern financial mathematics. It is based on our four papers written jointly by J. Cruz, M. Grossinho, D. Sevcovic, and C. Udeani, as well as parts of PhD thesis by J. Cruz. We investigated linear and nonlinear partial integro-differen

S. A. Hosseini, N. Darabiha, D. Thevenin

A hybrid lattice Boltzmann/finite-difference solver for low Mach thermo-compressible flows developed in earlier works is extended to more realistic and challenging configurations involving turbulence and complex geometries in the present article. The major novelty here as compared to previous contributions is the application of a more robust collision operat

Vatsalya Chaubey, Siddhartha S. Borkotoky

We propose application-layer coding schemes to recover lost data in delay-sensitive uplink (sensor-to-gateway) communications in the Internet of Things. Built on an approach that combines retransmissions and forward erasure correction, the proposed schemes' salient features include low computational complexity and the ability to exploit sporadic receiver fee

Michal Karwatowski, Marcin Pietron

Lemmatization is the process of grouping together the inflected forms of a word so they can be analysed as a single item, identified by the word's lemma, or dictionary form. In computational linguistics, lemmatisation is the algorithmic process of determining the lemma of a word based on its intended meaning. Unlike stemming, lemmatisation depends on correct

John Sipple, Abdou Youssef

The need for explainable AI (XAI) is well established but relatively little has been published outside of the supervised learning paradigm. This paper focuses on a principled approach to applying explainability and interpretability to the task of unsupervised anomaly detection. We argue that explainability is principally an algorithmic task and interpretabil

Sona Pavlikova, Daniel Sevcovic

The purpose of this paper is to analyze the Moore-Penrose pseudo-inversion of symmetric real matrices with application in the graph theory. We introduce a novel concept of positively and negatively pseudo-inverse matrices and graphs. We also give sufficient conditions on the elements of a block symmetric matrix yielding an explicit form of its Moore-Penrose

Daesoo Lee

Fake news detection has become a major task to solve as there has been an increasing number of fake news on the internet in recent years. Although many classification models have been proposed based on statistical learning methods showing good results, reasoning behind the classification performances may not be enough. In the self-supervised learning studies

Oliver Dukes, David Richardson, Eric Tchetgen Tchetgen

We consider studies where multiple measures on an outcome variable are collected over time, but some subjects drop out before the end of follow up. Analyses of such data often proceed under either a 'last observation carried forward' or 'missing at random' assumption. We consider two alternative strategies for identification; the first is closely related to

M. C. Rahn, K. Kummer, A. Hariki, K. -H. Ahn

Effective models focused on pertinent low-energy degrees of freedom have substantially contributed to our qualitative understanding of quantum materials. An iconic example, the Kondo model, was key to demonstrating that the rich phase diagrams of correlated metals originate from the interplay of localized and itinerant electrons. Modern electronic structure

Qinghua Tao, Francesco Tonin, Panagiotis Patrinos, Johan A. K. Suykens

Multi-view Spectral Clustering (MvSC) attracts increasing attention due to diverse data sources. However, most existing works are prohibited in out-of-sample predictions and overlook model interpretability and exploration of clustering results. In this paper, a new method for MvSC is proposed via a shared latent space from the Restricted Kernel Machine frame

Haojing Yan, Zhiyuan Ma, Chenxiaoji Ling, Cheng Cheng

On July 13, 2022, NASA released to the whole world the data obtained by the James Webb Space Telescope (JWST) Early Release Observations (ERO). These are the first set of science-grade data from this long-awaited facility, marking the beginning of a new era in astronomy. In the study of the early universe, JWST will allow us to push far beyond z ~ 11, the re

Gianluca Cubadda, Alain Hecq, Elisa Voisin

This paper proposes methods to investigate whether the bubble patterns observed in individual series are common to various series. We detect the non-linear dynamics using the recent mixed causal and noncausal models. Both a likelihood ratio test and information criteria are investigated, the former having better performances in our Monte Carlo simulations. I

Rodrigo Capucha, Da Huang, Tomás Lopes, Rui Santos

We discuss two models which are part of a class providing a common explanation for lepton flavor universality violation in $b \to s l^+ l^- $ decays, the dark matter (DM) problem and the muon $(g-2)$ anomaly. The $B$ meson decays and the muon $(g-2)$ anomalies are explained by additional one-loop diagrams with DM candidates. The models have one extra fermion

Meng Yao, Da Wang, Qiang-Hua Wang

We design a novel formalism of determinant quantum Monte Carlo method for the half-filled Hubbard model with on-site Hubbard interaction $U$ and nearest neighbor density-density interaction $V$ on the square lattice. The formalism is free of sign problem for $|U|\ge 4|V|$, and is achieved by introducing discrete auxiliary fields on the nearest-neighbor bonds

Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi

In recent years there has been significant progress in the field of 3D learning on classification, detection and segmentation problems. The vast majority of the existing studies focus on canonical closed-set conditions, neglecting the intrinsic open nature of the real-world. This limits the abilities of robots and autonomous systems involved in safety-critic

Chen Wei, Shenghan Ren, Kaitai Guo, Haihong Hu

The Resolution of feature maps is critical for medical image segmentation. Most of the existing Transformer-based networks for medical image segmentation are U-Net-like architecture that contains an encoder that utilizes a sequence of Transformer blocks to convert the input medical image from high-resolution representation into low-resolution feature maps an

Swapnali Khamaru, Rajaraman Ganesh, Meghraj Sengupta

Ion resonance instability of toroidal electron plasmas in a tight aspect ratio axisymmetric toroidal device is reported for ${Ar}^+$ ions of different initial density values using a high fidelity 3D3V PIC solver. Stability of a recently discovered quiescent quasi-steady state (QQS) of a toroidal electron plasma obtained from "seed" solution as a result of en

Mostafa Behtouei, Luigi Faillace, Mauro Migliorati, Luigi Palumbo

New high-gradient accelerating RF cavities are nowadays developed in several national laboratories for high-energy physics applications. Ultra high gradients, up to the order of GV/m, can be achieved by using ultra compact accelerating structures in the sub-THz regime. Nevertheless, the experimental setup for measuring the main RF parameters for such compact

Zheng Feng, Mattia Prosperi, Jiang Bian

Estimating treatment effects, especially individualized treatment effects (ITE), using observational data is challenging due to the complex situations of confounding bias. Existing approaches for estimating treatment effects from longitudinal observational data are usually built upon a strong assumption of "unconfoundedness", which is hard to fulfill in real

Antoine Caradot, Cuipo Jiang, Zongzhu Lin

Given a vertex operator algebra V , one can attach a graded Poisson algebra called the C2-algebra R(V). The associate Poisson scheme provides an important invariant for V and has been studied by Arakawa as the associated variety. In this article, we define and examine the cohomological variety of a vertex algebra, a notion cohomologically dual to that of the

Riccardo Torchio, Maximilian Nolte, Sebastian Schöps, Albert E. Ruehli

This contribution investigates the connection between Isogeometric Analysis (IgA) and the Partial Element Equivalent Circuit (PEEC) method for electrostatic problems. We demonstrate that using the spline-based geometry concepts from IgA allows for extracting circuit elements without a meshing step. Moreover, the proposed IgA-PEEC method converges for complex

Qi Fan, Wenjie Pei, Yu-Wing Tai, Chi-Keung Tang

Existing few-shot segmentation methods have achieved great progress based on the support-query matching framework. But they still heavily suffer from the limited coverage of intra-class variations from the few-shot supports provided. Motivated by the simple Gestalt principle that pixels belonging to the same object are more similar than those to different ob

David Zuehlke, Taylor Yow, Daniel Posada, Joseph Nicolich

This work utilizes a particle swarm optimizer (PSO) for initial orbit determination for a chief and deputy scenario in the circular restricted three-body problem (CR3BP). The PSO is used to minimize the difference between actual and estimated observations and knowledge of the chief's position with known CR3BP dynamics to determine the deputy's initial state.

Aman Goel, Qianhui Men, Edmond S. L. Ho

Synthesizing multi-character interactions is a challenging task due to the complex and varied interactions between the characters. In particular, precise spatiotemporal alignment between characters is required in generating close interactions such as dancing and fighting. Existing work in generating multi-character interactions focuses on generating a single

Yang Ling, Zhengxin Chen, Jiang Wu

This paper constructs the mapping relation from density of states (DOS) to UV-vis spectra by using an ab initio perspective. Taking BiOIO3 semiconductor photocatalyst as an example, the experimental verification was also carried out. The optical response of the material considers the superposition benefits of all possible transitions. Directly using the diff

Song Li, Song Ke, Chenxing Yang, Jun Chen

Gonadotrophin-releasing hormone receptor (GnRH1R) is a promising therapeutic target for the treatment of uterine diseases. To date, several GnRH1R antagonists are available in clinical investigation without satisfying multiple property constraints. To fill this gap, we aim to develop a deep learning-based framework to facilitate the effective and efficient d

D Reshma, Sudharani R, Suresh N

The study investigates the impact of downsizing layoffs on the profitability of construction industries listed in BSE India. In India, construction industries have adopted downsizing long back in the organization to improve the firms performance. For the purpose of the study, Secondary data of 15 Construction companies listed in BSE India have been considere

Hanzhao Wang, Xiaocheng Li, Kalyan Talluri

A number of products are sold in the following sequence: First a focal product is shown, and if the customer purchases, one or more ancillary products are displayed for purchase. A prominent example is the sale of an airline ticket, where first the flight is shown, and when chosen, a number of ancillaries such as cabin or hold bag options, seat selection, in

Fanghua Lin, Yannick Sire, Juncheng Wei, Yifu Zhou

We study a simplified Ericksen-Leslie system modeling the flow of nematic liquid crystals with partially free boundary conditions. It is a coupled system between the Navier-Stokes equation for the fluid velocity with a transported heat flow of harmonic maps, and both of these parabolic equations are critical for analysis in two dimensions. The boundary condi