May 2022 arXiv papers — page 131

Zlatko Papić, Ajit C. Balram

The fractional quantum Hall (FQH) effect refers to the strongly-correlated phenomena and the associated quantum phases of matter realized in a two-dimensional gas of electrons placed in a large perpendicular magnetic field. In such systems, topology and quantum mechanics conspire to give rise to exotic physics that manifests via robust quantization of the Ha

Matteo Fael, Kay Schönwald, Matthias Steinhauser

We study the impact of third-order QCD corrections for several kinematic moments of the inclusive semileptonic $B$ decays, to first order in the $1/m_b$ expansion. We consider the first four moments of the charged-lepton energy $E_\ell$ spectrum, the total leptonic invariant mass $q^2$ and the hadronic invariant mass $M_X^2$. No experimental cuts are applied

Liangbin Xie. Xintao Wang, Honglun Zhang, Chao Dong, Ying Shan

Most of the existing video face super-resolution (VFSR) methods are trained and evaluated on VoxCeleb1, which is designed specifically for speaker identification and the frames in this dataset are of low quality. As a consequence, the VFSR models trained on this dataset can not output visual-pleasing results. In this paper, we develop an automatic and scalab

R. R. Ashurov, M. D. Shakarova

The Schrödinger equation $i \partial_t^ρu(x,t)-u_{xx}(x,t) = p(t)q(x) + f(x,t)$ ( $0<t\leq T, \, 0<ρ<1$), with the Riemann-Liouville derivative is considered. An inverse problem is investigated in which, along with $u(x,t)$, also a time-dependent factor $p(t)$ of the source function is unknown. To solve this inverse problem, we take the additional condition

Ravshan Ashurov, Yusuf Fayziev

Let $A$ be an arbitrary positive selfadjoint operator, defined in a separable Hilbert space $H$. The inverse problems of determining the right-hand side of the equation and the function $ϕ$ in the non-local boundary value problem $D_t^ρ u(t) + Au(t) = f(t)$ ($0 < ρ< 1, 0 < t \leq T$), $u(ξ) = αu(0) + ϕ$, ($α$ is a constant and $0 < ξ\leq T)$, is considered.

Felix Bock, Johannes Pardey, Lucia D. Penso, Dieter Rautenbach

The independence number $α(G)$ and the dissociation number ${\rm diss}(G)$ of a graph $G$ are the largest orders of induced subgraphs of $G$ of maximum degree at most $0$ and at most $1$, respectively. We consider possible improvements of the obvious inequality $2α(G)\geq {\rm diss}(G)$. For connected cubic graphs $G$ distinct from $K_4$, we show $5α(G)\geq

Seo Yeon Park, Cornelia Caragea

MixUp is a data augmentation strategy where additional samples are generated during training by combining random pairs of training samples and their labels. However, selecting random pairs is not potentially an optimal choice. In this work, we propose TDMixUp, a novel MixUp strategy that leverages Training Dynamics and allows more informative samples to be c

S. Goswami, L. Silva, A. Bressan, V. Grisoni

In recent observations of extremely metal-poor low-mass starburst galaxies, almost solar Fe/O ratios are reported, despite N/O ratios consistent with the low metallicity. We investigate if the peculiar Fe/O ratios can be a distinctive signature of an early enrichment produced by very massive objects dying as Pair-Instability Supernovae (PISN). We run chemica

Kumar Saurav, Rahul Vaze

We consider a single source-destination pair, where information updates arrive at the source at arbitrary time instants. For each update, its size, i.e. the service time required for complete transmission to the destination, is also arbitrary. At any time, age of information (AoI) is equal to the difference between the current time, and the arrival time of t

Yannick Minet, Simon J. Herr, Ingo Breunig, Hans Zappe

Tunable light sources are a key enabling technology for many applications such as ranging, spectroscopy, optical coherence tomography, digital imaging and interferometry. For miniaturized laser devices, whispering gallery resonator lasers are a well-suited platform, offering low thresholds and small linewidths, however, many realizations suffer from the lack

Alexander Kathan, Andreas Triantafyllopoulos, Xiangheng He, Manuel Milling

Digital health applications are becoming increasingly important for assessing and monitoring the wellbeing of people suffering from mental health conditions like depression. A common target of said applications is to predict the results of self-assessed Patient-Health-Questionnaires (PHQ), indicating current symptom severity of depressive individuals. In thi

Dennis The

In his 1910 paper, Élie Cartan gave a tour-de-force solution to the (local) equivalence problem for generic rank 2 distributions on 5-manifolds, i.e. $(2,3,5)$-distributions. From a modern perspective, these structures admit equivalent descriptions as (regular, normal) parabolic geometries modelled on a quotient of $G_2$, but this is not transparent from his

Alexandre José de Oliveira e Silva, Caius L. Selhorst, Joaquim E. R. Costa, Paulo J. A. Simões

In recent decades our understanding of solar active regions (ARs) has improved substantially due to observations made with better angular resolution and wider spectral coverage. While prior AR observations have shown that these structures were always brighter than the quiet Sun at centimeter wavelengths, recent observations at millimeter and submillimeter wa

Jeffrey W. Miller

This article establishes general conditions for posterior consistency of Bayesian finite mixture models with a prior on the number of components. That is, we provide sufficient conditions under which the posterior concentrates on neighborhoods of the true parameter values when the data are generated from a finite mixture over the assumed family of component

L. V. Gerasimov, R. R. Yusupov, A. D. Moiseevsky, I. Vybornyi

Single atoms in dipole microtraps or optical tweezers have recently become a promising platform for quantum computing and simulation. Here we report a detailed theoretical analysis of the physics underlying an implementation of a Rydberg two-qubit gate in such a system -- a cornerstone protocol in quantum computing with single atoms. We focus on a blockade-t

Gabriel R. Palma, Renato M. Coutinho, Wesley A. C. Godoy, Fernando L. Cônsoli

Many studies have shown that the protection of the host $\it{Acyrthosiphon~pisum}$ (Hemiptera, Aphididae) against the parasitoid $\it{Aphidius~ervi}$ (Hymenoptera, Braconidae) is conferred by the interaction between the secondary endosymbiont $\it{Hamiltonella~defensa}$ and the bacteriophage $\it{APSE}$ ($\it{Acyrthosiphon~pisum}$ secondary endosymbiont). Th

Yuhang Cao, Jiaqi Wang, Yiqi Lin, Dahua Lin

Learning from a few training samples is a desirable ability of an object detector, inspiring the explorations of Few-Shot Object Detection (FSOD). Most existing approaches employ a pretrain-transfer paradigm. The model is first pre-trained on base classes with abundant data and then transferred to novel classes with a few annotated samples. Despite the subst

Amar Kumar Banerjee, Indrajit Debnath

In this paper we have introduced the notion of $\mathcal{I}$-density topology in the space of reals introducing the notions of upper $\mathcal{I}$-density and lower $\mathcal{I}$-density where $\mathcal{I}$ is an ideal of subsets of the set of natural numbers. We have further studied certain separation axioms of this topology.

D. S. Smirnov, J. Holler, M. Kempf, J. Zipfel

Heterobilayers consisting of MoSe$_2$ and WSe$_2$ monolayers can host optically bright interlayer excitons with intriguing properties such as ultralong lifetimes and pronounced circular polarization of their photoluminescence due to valley polarization, which can be induced by circularly polarized excitation or applied magnetic fields. Here, we report on the

Debarun Bhattacharjya, Saurabh Sihag, Oktie Hassanzadeh, Liza Bialik

Datasets involving sequences of different types of events without meaningful time stamps are prevalent in many applications, for instance when extracted from textual corpora. We propose a family of models for such event sequences -- summary Markov models -- where the probability of observing an event type depends only on a summary of historical occurrences o

Qi Bi, Beichen Zhou, Kun Qin, Qinghao Ye

Aerial scene classification remains challenging as: 1) the size of key objects in determining the scene scheme varies greatly; 2) many objects irrelevant to the scene scheme are often flooded in the image. Hence, how to effectively perceive the region of interests (RoIs) from a variety of sizes and build more discriminative representation from such complicat

Arturo Oncevay, Duygu Ataman, Niels van Berkel, Barry Haddow

Theoretical work in morphological typology offers the possibility of measuring morphological diversity on a continuous scale. However, literature in Natural Language Processing (NLP) typically labels a whole language with a strict type of morphology, e.g. fusional or agglutinative. In this work, we propose to reduce the rigidity of such claims, by quantifyin

Anuj Kumar

We consider the problem of &#34;wall-to-wall optimal transport&#34; in which we attempt to maximize the transport of a passive temperature field between hot and cold plates. Specifically, we optimize the choice of the divergence-free velocity field in the advection-diffusion equation subject to an enstrophy constraint (which can be understood as a constraint

Cristian R. Rojas, Pawel Wachel

In this paper we establish that every (deterministic) non-autonomous, discrete-time, causal, time invariant system has a state-space representation, and discuss its minimality.

Maggie Wigness, John G. Rogers, Luis E. Navarro-Serment

When working alongside human collaborators in dynamic and unstructured environments, such as disaster recovery or military operation, fast field adaptation is necessary for an unmanned ground vehicle (UGV) to perform its duties or learn novel tasks. In these scenarios, personnel and equipment are constrained, making training with minimal human supervision a

Jesse Tanguay, Mats Persson

Spectroscopic x-ray detectors (SXDs) are poised to play a substantial role in the next generation of medical x-ray imaging. Evaluating their performance in terms of the detective quantum efficiency (DQE) requires normalization of the frequency-dependent signal-to-noise ratio (SNR) by that of an ideal SXD. We provide mathematical expressions of the SNR of ide

I. Dhiman, Marcella C. Berg, Loukas Petridis, Jeremy C Smith

Alternation in various properties of n-alkanes (CnH2n+2) as a function of carbon content (n) is termed odd-even effect. Here, we report a comprehensive molecular dynamics simulation study on n-alkane systems carried out with n ranging between 3 (propane) and 8 (octane), examining the odd-even effect in melting point, density, intramolecular conformational or

A. Beresnyak, A. L. Velikovich, J. L. Giuliani, S. L. Jackson

We describe a simple practical numerical method for simulating plasma driven within a vacuum chamber by a pulsed power generator. Typically, in this type of simulation, the vacuum region adjacent to the plasma is approximated as a highly resistive, light fluid; this involves computationally expensive solvers describing the diffusion of the magnetic field thr

Stijn Cambie, Matteo Mazzamurro

The first degree-based entropy of a graph is the Shannon entropy of its degree sequence normalized by the degree sum. In this paper, we characterize the connected graphs with given order $n$ and size $m$ that minimize the first degree-based entropy whenever $n-1 \le m \le 2n-3,$ thus extending and proving a conjecture by Yan.

Damyn M Chipman

Elliptic partial differential equations (PDEs) arise in many areas of computational sciences such as computational fluid dynamics, biophysics, engineering, geophysics and more. They are difficult to solve due to their global nature and sometimes ill-conditioned operators. We review common discretization methods for elliptic PDEs such as the finite difference

Jason Stock, Chuck Anderson

This work introduces a wavelet neural network to learn a filter-bank specialized to fit non-stationary signals and improve interpretability and performance for digital signal processing. The network uses a wavelet transform as the first layer of a neural network where the convolution is a parameterized function of the complex Morlet wavelet. Experimental res

Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou

Reinforcement learning (RL) has been shown to be effective at learning control from experience. However, RL typically requires a large amount of online interaction with the environment. This limits its applicability to real-world settings, such as in robotics, where such interaction is expensive. In this work we investigate ways to minimize online interactio

Ian Ball, Matt O. Jackson, Deniz Kattwinkel

We correct a bound in the definition of approximate truthfulness used in the body of the paper of Jackson and Sonnenschein (2007). The proof of their main theorem uses a different permutation-based definition, implicitly claiming that the permutation-version implies the bound-based version. We show that this claim holds only if the bound is loosened. The new

Daniela Di Donato

This note is a contribution to large scale geometry. More precisely, we introduce the intrinsically quasi-isometric sections in metric spaces and we investigate their properties: the Ahlfors-David regularity in large scale; following Cheeger theory, it is possible to define suitable sets in order to obtain convexity and being a vector space over $\mathbb{R}$

Yu-Shun Hsiao, Siva Kumar Sastry Hari, Michał Filipiuk, Timothy Tsai

The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort. This paper proposes a sensor frame processing rate (FPR) estimation model, Zhuyi, that quantifies the minimum safe FPR continuously in a driving scenario. Zhuyi ca

Ziteng Cui, Guo-Jun Qi, Lin Gu, Shaodi You

Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propose a novel multitask auto encoding transformation (MAET) model which is able to explore the intrinsic pattern behind illumination translation. In a self-supervision manner, the MAE

Yuning Lu, Jianzhuang Liu, Yonggang Zhang, Yajing Liu

We present prompt distribution learning for effectively adapting a pre-trained vision-language model to address downstream recognition tasks. Our method not only learns low-bias prompts from a few samples but also captures the distribution of diverse prompts to handle the varying visual representations. In this way, we provide high-quality task-related conte

Elliott Waissbluth, Hany Farid, Vibhor Sehgal, Ankit Peshin

How, in 20 short years, did we go from the promise of the internet to democratize access to knowledge and make the world more understanding and enlightened, to the litany of daily horrors that is today&#39;s internet? We are awash in disinformation consisting of lies, conspiracies, and general nonsense, all with real-world implications ranging from horrific

Aleksandra Slavkovic, Jeremy Seeman

To quantify trade-offs between increasing demand for open data sharing and concerns about sensitive information disclosure, statistical data privacy (SDP) methodology analyzes data release mechanisms which sanitize outputs based on confidential data. Two dominant frameworks exist: statistical disclosure control (SDC), and more recent, differential privacy (D

David Gesbert, Omid Esrafilian, Junting Chen, Rajeev Gangula

The use of unmanned aerial vehicles (UAV) as flying radio access network (RAN) nodes offers a promising complement to traditional fixed terrestrial deployments. More recently yet still in the context of wireless networks, drones have also been envisioned for use as radio frequency (RF) sensing and localization devices. In both cases, the advantage of using U

Kenichi N. Komagata, Valentin J. Wittwer, Thomas Südmeyer, Lukas Emmenegger

Quantum cascade laser (QCL) frequency combs have revolutionized mid-infrared (MIR) spectroscopy by their high brightness and fast temporal resolution, and are a promising technology for fully-integrated and cost-effective sensors. As for other integrated comb sources such as micro-combs and interband cascade laser, QCLs have a comb spacing of several GHz, wh

Adrián A. Budini

Quantum memory effects can be qualitatively understood as a consequence of an environment-to-system backflow of information. Here, we analyze and compare how this concept is interpreted and implemented in different approaches to quantum non-Markovianity. We study a non-operational approach, defined by the istinguishability between two system states character

Dominic P. Mulligan, Nick Spinale

Interactive theorem proving software is typically designed around a trusted proof-checking kernel, the sole system component capable of authenticating theorems. Untrusted automation procedures reside outside of the kernel, and drive it to deduce new theorems via an API. Kernel and untrusted automation are typically implemented in the same programming languag

Sreejith Gopinath, Aspen Olmsted

The rapid advancement of technology has resulted in advanced camera capabilities coming to smaller form factors with improved energy efficiency. These improvements have led to more efficient and capable cameras on mobile devices like mobile phones, tablets, and even eyeglasses. Using these unobtrusive cameras, users can capture photographs and videos of almo

Priyanka Kaswan, Sennur Ulukus

We consider a system with a source which maintains the most current version of a file, and a ring network of $n$ user nodes that wish to acquire the latest version of the file. The source gets updated with newer file versions as a point process, and forwards them to the user nodes, which further forward them to their neighbors using a memoryless gossip proto

Omid Esrafilian, Rajeev Gangula, David Gesbert

This paper considers the problem of ground user localization based on received signal strength (RSS) measurements obtained by an unmanned aerial vehicle (UAV). We treat UAV-user link channel model parameters and antenna radiation pattern of the UAV as unknowns that need to be estimated. A hybrid channel model is proposed that consists of a traditional path l

Mona Wang, Anunay Kulshrestha, Liang Wang, Prateek Mittal

Network-level adversaries have developed increasingly sophisticated techniques to surveil and control users&#39; network traffic. In this paper, we exploit our observation that many encrypted protocol connections are no longer tied to device IP address (e.g., the connection migration feature in QUIC, or IP roaming in WireGuard and Mosh), due to the need for

Tianyu Jia, En-Yu Yang, Yu-Shun Hsiao, Jonathan Cruz

Autonomous machines (e.g., vehicles, mobile robots, drones) require sophisticated 3D mapping to perceive the dynamic environment. However, maintaining a real-time 3D map is expensive both in terms of compute and memory requirements, especially for resource-constrained edge machines. Probabilistic OctoMap is a reliable and memory-efficient 3D dense map model

Swati Banerjee

Living Lab is an umbrella term used for referring to a methodology of user-centric innovation in real-life environments within a wider network of relevant stake holders. Real-life environment refers to living houses and hospitals inter wined and connected together in a way which promotes direct usability of research by the end users. It primarily consists of

Carmela Lardo, Maurizio Salaris, Santi Cassisi, Nate Bastian

Stars in massive star clusters exhibit intrinsic variations in some light elements (MPs) that are difficult to explain in a coherent formation scenario. In recent years, HST photometry has led to the characterisation of the global properties of th MPs in an unparalleled level of detail. In particular, the colour-colour diagrams known as chromosome maps have

Mathias Brossard, Guilhem Bryant, Basma El Gaabouri, Xinxin Fan

Sensitive computations are now routinely delegated to third-parties. In response, Confidential Computing technologies are being introduced to microprocessors, offering a protected processing environment, which we generically call an isolate, providing confidentiality and integrity guarantees to code and data hosted within -- even in the face of a privileged

Steve Paul, Payam Ghassemi, Souma Chowdhury

This paper presents a novel graph reinforcement learning (RL) architecture to solve multi-robot task allocation (MRTA) problems that involve tasks with deadlines and workload, and robot constraints such as work capacity. While drawing motivation from recent graph learning methods that learn to solve combinatorial optimization (CO) problems such as multi-Trav

Samantha Wu, Jim Fuller

In a substantial number of core-collapse supernovae, early-time interaction indicates a dense circumstellar medium (CSM) that may be produced by outbursts from the progenitor star. Wave-driven mass loss is a possible mechanism to produce these signatures, with previous work suggesting this mechanism is most effective for low mass ($ \sim \! 11 \, M_\odot$) S

Daniel Hopp

Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures. Currently, there are a plethora of methodologies and approaches for practitioners to choose from. However, there lacks a comprehensive comparison of these disparate approaches in terms of predictive performance and

Sherzod M. Mirakhmedov

We consider a multinomial distribution, where the number of cells increases and the cell-probabilities decreases as the number of observations grows. The probabilities of large deviations of statistics, which has form of a sum of Borel functions of cell-frequencies, are studied. Large deviation results for the power-divergence statistics and its most popular

Srijith Balakrishnan, Beatrice Cassottana, Arun Verma

Recent studies increasingly adopt simulation-based machine learning (ML) models to analyze critical infrastructure system resilience. For realistic applications, these ML models consider the component-level characteristics that influence the network response during emergencies. However, such an approach could result in a large number of features and cause ML

Saverio Mariani

In parallel to the study of proton-proton collisions, LHCb is developing a unique heavy-ion programme and is pioneering beam-gas fixed-target physics at the CERN LHC. In this document, a selection of some recent results from both programmes is presented.

Élise Bertin-Lemée, Annelies Braffort, Camille Challant, Claire Danet

This article presents an original method for Text-to-Sign Translation. It compensates data scarcity using a domain-specific parallel corpus of alignments between text and hierarchical formal descriptions of Sign Language videos in AZee. Based on the detection of similarities present in the source text, the proposed algorithm recursively exploits matches and

Xiao Ao, Danae Sánchez Villegas, Daniel Preoţiuc-Pietro, Nikolaos Aletras

Parody is a figurative device used for mimicking entities for comedic or critical purposes. Parody is intentionally humorous and often involves sarcasm. This paper explores jointly modelling these figurative tropes with the goal of improving performance of political parody detection in tweets. To this end, we present a multi-encoder model that combines three

Igor Sedlár, Johann J. Wannenburg

Kleene algebra with tests, KAT, provides a simple two-sorted algebraic framework for verifying properties of propositional while programs. Kleene algebra with domain, KAD, is a one-sorted alternative to KAT. The equational theory of KAT embeds into KAD, but KAD lacks some natural properties of KAT. For instance, not each Kleene algebra expands to a KAD, and

Anne S. M. Buckner, Kong You Liow, Clare L. Dobbs, Tim Naylor

Understanding the formation and evolution of high mass star clusters requires comparisons between theoretical and observational data to be made. Unfortunately, while the full phase space of simulated regions is available, often only partial 2D spatial and kinematic data is available for observed regions. This raises the question as to whether cluster paramet

Ameek Sidhu, A. G. G. M. Tielens, Els Peeters, Jan Cami

We present a charge distribution based model that computes the infrared spectrum of polycyclic aromatic hydrocarbon (PAH) molecules using recent measurements or quantum chemical calculations of specific PAHs. The model is applied to a sample of well-studied photodissociation regions (PDRs) with well-determined physical conditions (the radiation field strengt

Bin Shi, Xuelin Huang, Peng Wei

There is an increasing trend of research in mediation analysis for survival outcomes. Such analyses help researchers to better understand how exposure affects disease outcomes through mediators. However, due to censored observations in survival outcomes, it is not straightforward to extend mediation analysis from linear models to survival outcomes. In this a

Esma Balkir, Isar Nejadgholi, Kathleen C. Fraser, Svetlana Kiritchenko

We present a novel feature attribution method for explaining text classifiers, and analyze it in the context of hate speech detection. Although feature attribution models usually provide a single importance score for each token, we instead provide two complementary and theoretically-grounded scores -- necessity and sufficiency -- resulting in more informativ

Federico Mogavero, Jacques Laskar

The discovery of the chaotic motion of the planets in the Solar System dates back more than 30 years. Still, no analytical theory has satisfactorily addressed the origin of chaos so far. Implementing canonical perturbation theory in the computer algebra system TRIP, we systematically retrieve the secular resonances at work along the orbital solution of a for

Bo Liu

With the rapid development of mobile Internet and big data, a huge amount of data is generated in the network, but the data that users are really interested in a very small portion. To extract the information that users are interested in from the huge amount of data, the information overload problem needs to be solved. In the era of mobile internet, the user

Lucain Pouget, Timo Hasenbichler, Jakob Auer, Klaus Lichtenegger

We investigate the feasibility of deploying Deep-Q based deep reinforcement learning agents to job-shop scheduling problems in the context of modular production facilities, using discrete event simulations for the environment. These environments are comprised of a source and sink for the parts to be processed, as well as (several) workstations. The agents ar

T. Passot, P. L. Sulem, D. Laveder

A two-field Hamiltonian gyrofluid model for kinetic Alfvén waves retaining ion finite Larmor radius corrections and parallel magnetic field fluctuations is used to study direct turbulent cascades from the MHD to the sub-ion scales. For moderate energy imbalance and weak enough magnetic fluctuations, the spectrum of the transverse magnetic field and that of t

A. Bazzani, F. Capoani, M. Giovannozzi, R. Tomàs

In recent years, intense efforts have been devoted to studying how nonlinear effects can be used to shape the transverse beam distribution by means of an adiabatic crossing of nonlinear resonances. By this approach, it is possible to split the beams in the transverse plane, so that the initial single-Gaussian beam is divided into several distinct distributio

Alexandre Neves, Alberto Sardinha

A key goal of ad hoc teamwork is to develop a learning agent that cooperates with unknown teams, without resorting to any pre-coordination protocol. Despite a vast number of ad hoc teamwork algorithms in the literature, most of them cannot address the problem of learning to cooperate with a completely unknown team, unless it learns from scratch. This article

Abderrezak Belabbes, Silvana Botti, Friedhelm Bechstedt

The natural and true band profiles at heterojunctions formed by hexagonal Si$_x$Ge$_{1-x}$ alloys are investigated by a variety of methods: density functional theory for atomic geometries, approximate quasiparticle treatments for electronic structures, different band edge alignment procedures, and construction of various hexagonal unit cells to model alloys

Ali Modarressi, Mohsen Fayyaz, Yadollah Yaghoobzadeh, Mohammad Taher Pilehvar

There has been a growing interest in interpreting the underlying dynamics of Transformers. While self-attention patterns were initially deemed as the primary option, recent studies have shown that integrating other components can yield more accurate explanations. This paper introduces a novel token attribution analysis method that incorporates all the compon

James G. MacKinnon, Morten Ørregaard Nielsen, Matthew D. Webb

Methods for cluster-robust inference are routinely used in economics and many other disciplines. However, it is only recently that theoretical foundations for the use of these methods in many empirically relevant situations have been developed. In this paper, we use these theoretical results to provide a guide to empirical practice. We do not attempt to pres

Milan Ding, Juliet C. Pickering

This comment points out errors in the analysis of 61 magnetic hyperfine structure ($A$) constants of Co II energy levels by Fu et al. [JQSRT 2021, 107590]. The paper was published without full awareness of the extensive literature already available for Co II hyperfine $A$ constants at the time; 57 of 58 $A$ constants that were claimed to have been measured f

P. K. Humire, C. Henkel, A. Hernández-Gómez, S. Martín

Context: Methanol masers of Class I (collisionally-pumped) and Class II (radiatively-pumped) have been studied in great detail in our Galaxy in a variety of astrophysical environments such as shocks and star-forming regions and are helpful to analyze the properties of the dense interstellar medium. However, the study of methanol masers in external galaxies i

Katerina Koutlia, Biljana Bojovic, Zoraze Ali, Sandra Lagen

Due to the rapid technology evolution and standardization activity in the mobile communication networks, there is the need for the research community to be able to develop, test and evaluate new and/or already xisting solutions before industrial or real-network implementation. As such, it is essential to have an open-source tool that provides an alternative

Jiajun Lv, Xingxing Zuo, Kewei Hu, Jinhong Xu

Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial measurements, which are usually available in robotic applications. In this paper, we propose a novel LiDAR-IMU calibration method within the continuous-time batch-optimization framework, where the intrinsics of both sensors and the spatial-temporal extrinsics between sensors are

Jacopo Pegoraro, Michele Rossi

mmWave radars have recently gathered significant attention as a means to track human movement within indoor environments. Widely adopted Kalman filter tracking methods experience performance degradation when the underlying movement is highly non-linear or presents long-term temporal dependencies. As a solution, in this article we design a convolutional-recur

Vojtech Mrazek

Software methods introduced for automated design of approximate implementations of arithmetic circuits rely on fast and accurate evaluation of approximate candidate implementations. To accelerate the evaluation of circuit error, we propose four novel algorithms for the exact worst-case and mean absolute error analysis based on Binary Decision Diagrams. As th

J. E. Méndez-Delgado, C. Esteban, J. García-Rojas, W. J. Henney

We analyze the physical conditions and chemical composition of the photoionized Herbig-Haro object HH~514, which emerges from the proplyd 170-337 in the core of the Orion Nebula. We use high-spectral resolution spectroscopy from UVES at the Very Large Telescope and IFU-spectra from MEGARA at the Gran Telescopio de Canarias. We observe two components of HH~51

Jeremy Karam, Alison Sills

Star cluster formation in giant molecular clouds involves the local collapse of the cloud into small gas-rich subclusters, which can then subsequently collide and merge to build up the final star cluster(s). In this paper, we simulate collisions between these subclusters, using coupled smooth particle hydrodynamics for the gas and N-body dynamics for the sta

I M Tambovtsev, I S Lobanov

We have written expressions for the free energy of a cholesteric liquid crystal in an approximation using the elasticity constants K_1, K_2, K_3 and the energy variation and the corresponding energy and energy gradient along the direction of the director vector n at each lattice point for the lattice model. A feature of this lattice model is the shift of the

Jacopo Pegoraro, Jesus Omar Lacruz, Michele Rossi, Joerg Widmer

A well established method to detect and classify human movements using Millimeter-Wave ( mmWave) devices is the time-frequency analysis of the small-scale Doppler effect (termed micro-Doppler) of the different body parts, which requires a regularly spaced and dense sampling of the Channel Impulse Response ( CIR). This is currently done in the literature eith

Tanja Hernández Rodríguez, Anton Sekulic, Markus Lange-Hegermann, Björn Frahm

Development and optimization of biopharmaceutical production processes with cell cultures is cost- and time-consuming and often performed rather empirically. Efficient optimization of multiple-objectives like process time, viable cell density, number of operating steps & cultivation scales, required medium, amount of product as well as product quality depict

Manoel Horta Ribeiro, Justin Cheng, Robert West

In many online communities, community leaders (i.e., moderators and administrators) can proactively filter undesired content by requiring posts to be approved before publication. But although many communities adopt post approvals, there has been little research on its impact on community behavior. Through a longitudinal analysis of 233,402 Facebook Groups, w

James Jordon, Lukasz Szpruch, Florimond Houssiau, Mirko Bottarelli

This explainer document aims to provide an overview of the current state of the rapidly expanding work on synthetic data technologies, with a particular focus on privacy. The article is intended for a non-technical audience, though some formal definitions have been given to provide clarity to specialists. This article is intended to enable the reader to quic

Bagus Santoso, Yasuhiko Ikematsu, Shuhei Nakamura, Takanori Yasuda

In Asiacrypt 2001, Courtois proposed the first three-pass zero-knowledge identification (ID) scheme based on the MinRank problem. However, in a single round of Courtois&#39; ID scheme, the cheating probability, i.e., the success probability of the cheating prover, is 2/3 which is larger than half. Although Courtois also proposed a variant scheme which is cla

Jean-Jacques Forneron

In non-linear estimations, it is common to assess sampling uncertainty by bootstrap inference. For complex models, this can be computationally intensive. This paper combines optimization with resampling: turning stochastic optimization into a fast resampling device. Two methods are introduced: a resampled Newton-Raphson (rNR) and a resampled quasi-Newton (rq

P. Gaete, J. A. Helayël-Neto

We study some observational signatures of nonlinearities of the electromagnetic field. First to all we show the vital role played by nonlinearities in triggering a material behavior of the vacuum with $(\varepsilon > 0, μ<0)$, which corresponds to a ferrimagnetic material. Secondly, the permittivity and susceptibility induced by nonlinearities are considered

W. B. Langdon

We summarise how a 3.0 GHz 16 core AVX512 computer can interpret the equivalent of up to on average 1103370000000 GPop/s. Citations to existing publications are given. Implementation stress is placed on both parallel computing, bandwidth limits and avoiding repeated calculation. Information theory suggests in digital computing, failed disruption propagation

Vilmos Totik

We examine the uniform distribution theory of H. Weyl when there is a periodic perturbation present. As opposed to the classical setting, in this case the conditions for (mod 1) density and (mod 1) uniform distribution turn out to be different.

Lin Hao Lee

Real-time tracking of the position of a musical performance on a musical score, i.e. score following, can be useful in music practice, performance and production. Example applications of such technology include computer-aided accompaniment and automatic page turning. Score following is a challenging task, especially when considering deviations in performance

Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi

When omega-regular objectives were first proposed in model-free reinforcement learning (RL) for controlling MDPs, deterministic Rabin automata were used in an attempt to provide a direct translation from their transitions to scalar values. While these translations failed, it has turned out that it is possible to repair them by using good-for-MDPs (GFM) Büchi

K. L. Page, A. P. Beardmore, J. P. Osborne, U. Munari

On 2021 August 8, the recurrent nova RS Ophiuchi erupted again, after an interval of 15.5 yr. Regular monitoring by the Neil Gehrels Swift Observatory began promptly, on August 9.9 (0.37 day after the optical peak), and continued until the source passed behind the Sun at the start of November, 86 days later. Observations then restarted on day 197, once RS Op

Prerna Agarwal, Avani Gupta, Renuka Sindhgatta, Sampath Dechu

Recommending a sequence of activities for an ongoing case requires that the recommendations conform to the underlying business process and meet the performance goal of either completion time or process outcome. Existing work on next activity prediction can predict the future activity but cannot provide guarantees of the prediction being conformant or meeting

Guang-Xing Li, Bing-Qiu Chen

Recently studies discovered that part of the Gould Belt belongs to a 2.7 kpc-long {coherent, thin} wave consisting of a chain of clouds, where a damped undulation pattern has been identified from the spatial arrangement of the clouds. We use the proper motions of Young Stellar Objects (YSOs) anchored inside the clouds to study the kinematic structure of the

Guang-Xing Li, Ji-Xuan Zhou

The evolution of molecular interstellar clouds is a complex, multi-scale process. The power-law density exponent describes the steepness of density profiles, and it has been used to characterize the density structures of the clouds yet its usage is usually limited to spherically symmetric systems. Importing the Level-Set Method, we develop a new formalism th

Khushdeep Singh Mann, Abhishek Tomy, Anshul Paigwar, Alessandro Renzaglia

Reliably predicting future occupancy of highly dynamic urban environments is an important precursor for safe autonomous navigation. Common challenges in the prediction include forecasting the relative position of other vehicles, modelling the dynamics of vehicles subjected to different traffic conditions, and vanishing surrounding objects. To tackle these ch

Roee Shraga

This work offers a novel view on the use of human input as labels, acknowledging that humans may err. We build a behavioral profile for human annotators which is used as a feature representation of the provided input. We show that by utilizing black-box machine learning, we can take into account human behavior and calibrate their input to improve the labelin

T. An, Y. Zhang, A. Wang, X. Shu

Context. Recently, SDSS J143016.05+230344.4 (J1430+2303) was reported to be a supermassive black hole binary (SMBHB) in the final coalescence phase. It is probably the first SMBHB coalescence event observable in human history. Radio observations of J1430+2303 before and after coalescence will provide a unique diagnosis of the energetics and environment of th