November 2022 arXiv papers — page 43

Nicolas Raymond, Maxime Caru, Hakima Laribi, Mehdi Mitiche

Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects following their treatments. The existing measures offered to patients during their follow-up visits to the hospital are rather standardized for all childhood cancer survivors and not n

Bjoern Kiefer, Stefan Prüger, Oliver Rheinbach, Friederike Röver

We consider the swelling of hydrogels as an example of a chemo-mechanical problem with strong coupling between the mechanical balance relations and the mass diffusion. The problem is cast into a minimization formulation using a time-explicit approach for the dependency of the dissipation potential on the deformation and the swelling volume fraction to obtain

A. Di Piazza, L. Willingale, J. D. Zuegel

This Multi-Petawatt Physics Prioritization (MP3) Workshop Report captures the outcomes from a community-initiated workshop held April 20-22, 2022 at Sorbonne University in Paris, France. The MP3 workshop aimed at developing science questions to guide research and future experiments in four areas identified by corresponding MP3 working groups: high-field phys

Aalok Misra, Gopal Yadav

Relevant to top-down ${\cal M}$-theory dual of large-$N$ thermal QCD-like theories at intermediate coupling, induced by the $G_2$ structure supported by the closed $M_7$ - a warped product of the ${\cal M}$-theory circle and a non-K\"{a}hler six-fold which is the warped product of the thermal circle with a non-Einsteinian deformation of $T^{1,1}$ - we obtain

Emmanuel Hartman, Emery Pierson, Martin Bauer, Nicolas Charon

We present Basis Restricted Elastic Shape Analysis (BaRe-ESA), a novel Riemannian framework for human body scan representation, interpolation and extrapolation. BaRe-ESA operates directly on unregistered meshes, i.e., without the need to establish prior point to point correspondences or to assume a consistent mesh structure. Our method relies on a latent spa

Xianzhe Xu, Yiqi Jiang, Weihua Chen, Yilun Huang

In this report, we present a fast and accurate object detection method dubbed DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO series. DAMO-YOLO is extended from YOLO with some new technologies, including Neural Architecture Search (NAS), efficient Reparameterized Generalized-FPN (RepGFPN), a lightweight head with AlignedOTA label

Shuming Ma, Hongyu Wang, Shaohan Huang, Wenhui Wang

Large Transformers have achieved state-of-the-art performance across many tasks. Most open-source libraries on scaling Transformers focus on improving training or inference with better parallelization. In this work, we present TorchScale, an open-source toolkit that allows researchers and developers to scale up Transformers efficiently and effectively. Torch

Jackson Melchert, Yuchen Mei, Kalhan Koul, Qiaoyi Liu

While coarse-grained reconfigurable arrays (CGRAs) have emerged as promising programmable accelerator architectures, pipelining applications running on CGRAs is required to ensure high maximum clock frequencies. Current CGRA compilers either lack pipelining techniques resulting in low performance or perform exhaustive pipelining resulting in high energy and

Mark S. Veillette, James M. Kurdzo, Phillip M. Stepanian, Joseph McDonald

Radial velocity estimates provided by Doppler weather radar are critical measurements used by operational forecasters for the detection and monitoring of life-impacting storms. The sampling methods used to produce these measurements are inherently susceptible to aliasing, which produces ambiguous velocity values in regions with high winds, and needs to be co

Giovanni Brigati, Jean Dolbeault, Nikita Simonov

We consider Gagliardo-Nirenberg inequalities on the sphere which interpolate between the Poincar\'e inequality and the Sobolev inequality, and include the logarithmic Sobolev inequality as a special case. We establish explicit stability results in the subcritical regime using spectral decomposition techniques, and entropy and carr\'e du champ methods applied

Michael Reefe, Shobita Satyapal, Remington O. Sexton, Nathan J. Secrest

Local low metallicity dwarf galaxies are relics of the early universe and hold clues into the origins of supermassive black holes (SMBHs). In recent work, coronal lines have been used to unveil a population of candidate accreting black holes in dwarf galaxies with gas phase metallicities and stellar masses well below the host galaxies of any previously known

Jacek Wojtkiewicz, Krzysztof Wohlfeld, Andrzej M. Oleś

Using the reflection positivity method we provide the rigorous proof of the existence of long range magnetic order for the XY model on the honeycomb lattice for large spins $S\ge 2$. This stays in contrast with the result obtained using the {\it same} method but on the square lattice -- which gives a stable long-range order for spins $S\ge 1$. We suggest tha

Alessio Caminata, Han-Bom Moon, Luca Schaffler

We consider the scheme $X_{r,d,n}$ parametrizing $n$ ordered points in projective space $\mathbb{P}^r$ that lie on a common hypersurface of degree $d$. We show that this scheme has a determinantal structure and we prove that it is irreducible, Cohen-Macaulay, and normal. Moreover, we give an algebraic and geometric description of the singular locus of $X_{r,

Nishant Gupta, Nemani V. Suryanarayana

Generalising the chiral boundary conditions of $\mathbb{R}^{1,3}$ gravity for AdS$_4$ gravity, we derive chiral locally AdS$_4$ solutions in the Newman-Unti gauge consistent with a variational principle whose asymptotic symmetry algebra we show, to be an infinite-dimensional chiral extension of $\mathfrak{so}(2,3)$. This symmetry algebra coincides with the c

Jeeho Ahn, Seabin Lee, Changjoo Nam

We present a coordination method for multiple mobile manipulators to sort objects in clutter. We consider the object rearrangement problem in which the objects must be sorted into different groups in a particular order. In clutter, the order constraints could not be easily satisfied since some objects occlude other objects so the occluded ones are not direct

Dubing Chen, Chenyi Jiang, Haofeng Zhang

Attribute-based Zero-Shot Learning (ZSL) has revolutionized the ability of models to recognize new classes not seen during training. However, with the advancement of large-scale models, the expectations have risen. Beyond merely achieving zero-shot generalization, there is a growing demand for universal models that can continually evolve in expert domains us

Marco Avella-Medina, Richard A. Davis, Gennady Samorodnitsky

We propose kernel PCA as a method for analyzing the dependence structure of multivariate extremes and demonstrate that it can be a powerful tool for clustering and dimension reduction. Our work provides some theoretical insight into the preimages obtained by kernel PCA, demonstrating that under certain conditions they can effectively identify clusters in the

Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak, Ajmal Mian

Black-box adversarial attacks present a realistic threat to action recognition systems. Existing black-box attacks follow either a query-based approach where an attack is optimized by querying the target model, or a transfer-based approach where attacks are generated using a substitute model. While these methods can achieve decent fooling rates, the former t

Yuanyuan Tian

Rapidly growing social networks and other graph data have created a high demand for graph technologies in the market. A plethora of graph databases, systems, and solutions have emerged, as a result. On the other hand, graph has long been a well studied area in the database research community. Despite the numerous surveys on various graph research topics, the

Marcos Barrios

Let $IET(\mathbb{S}^{1})$ be the group of interval exchange transformation of $\mathbb{S}^{1}$ and $\mathcal{AC}_{+}(\mathbb{S}^{1})$ be the group of absolutely continuous preserving orientation bijection with inverse absolutely continuous. We denote by $\mathcal{ACI}$ the group generated by $IET(\mathbb{S}^{1})$ and $\mathcal{AC}_{+}(\mathbb{S}^{1})$. Given

Debasish Borah, Pritam Das, Dibyendu Nanda

We study the possibility of probing the radiative Dirac seesaw model with dark sector particles going inside the loop, popularly referred to as the Dirac scotogenic model via measurements of effective relativistic degrees of freedom ${\rm \Delta{N_{eff}}}$ at cosmic microwave background (CMB) experiments. The loop suppression and additional free parameters i

Laura Olivera-Nieto, Helena X. Ren, Alison M. W. Mitchell, Vincent Marandon

Identification of Cherenkov light generated by muons has been suggested as a promising way to dramatically improve the background rejection power of Imaging Atmospheric Cherenkov Telescope (IACT) arrays at high energies. However, muon identification remains a challenging task, for which efficient algorithms are still being developed. We present an approach i

Hannah Fang, Iona Xia, Jian Ge, Kevin Willis

We report discoveries of 165 new quasar Ca II absorbers from the Sloan Digital Sky Survey (SDSS) Data Release 7 and 12. Our Ca II rest frame equivalent width distribution supports the weak and strong subpopulations, split at ${W}^{\lambda3934}_{0}=0.7${\AA}. Comparison of both populations' dust depletion shows clear consistency for weak absorber association

Lukas Schumacher, Paul-Christian Bürkner, Andreas Voss, Ullrich Köthe

Mathematical models of cognition are often memoryless and ignore potential fluctuations of their parameters. However, human cognition is inherently dynamic. Thus, we propose to augment mechanistic cognitive models with a temporal dimension and estimate the resulting dynamics from a superstatistics perspective. Such a model entails a hierarchy between a low-l

Elisabetta Nocerino, Ola K. Forslund, Hiroya Sakurai, Nami Matsubara

In this work we present systematic set of measurements carried out by muon spin rotation/relaxation ($\mu^+$SR) and neutron powder diffraction (NPD) on the solid solution Na$_{\rm x}$Ca$_{1- \rm x}$Cr$_2$O$_4$. This study investigates Na-ion dynamics in the quasi-1D (Q1D) diffusion channels created by the honeycomb-like arrangement of CrO$_6$ octahedra, in t

Javier Reyes, Giancarlo Urzúa

We construct the first exotic $\mathbb C \mathbb P^2 \# 4 \overline{\mathbb C \mathbb P^2}$ by means of rational blowdowns. Similarly, we construct the first exotic $3\mathbb C \mathbb P^2 \# b^- \overline{\mathbb C \mathbb P^2}$ for $b^-=9,8,7$ . All of them are minimal and symplectic, as they are produced from projective surfaces $W$ with Wahl singularitie

Mauricio Chacón-Tirado, María de J. López, Ivon Vidal-Escobar

We present a property equivalent to the property of being semi-Kelley. Using this equivalence we prove that being semi-Kelley is a hereditary property for atriodic continua. We prove that semi-Kelley remainders are atriodic, moreover, we prove that semi-Kelley continua are semi-Kelley remainders for chainable continua, circularly chainable continua, and arc

Paul A. Cassak, M. Hasan Barbhuiya, H. Arthur Weldon

In weakly collisional and collisionless magnetized plasmas, the pressure-strain interaction describes the rate of conversion between bulk flow and thermal energy density. In this study, we derive an analytical expression for the pressure-strain interaction in a coordinate system with an axis aligned with the local magnetic field. The result is eight groups o

Paul A. Cassak, M. Hasan Barbhuiya

The pressure-strain interaction describes the rate per unit volume that energy is converted between bulk flow and thermal energy in neutral fluids or plasmas. The term has been written as a sum of the pressure dilatation and the collisionless analogue of viscous heating referred to as ${\rm Pi-D}$, which isolates the power density due to compressible and inc

M. Hasan Barbhuiya, Paul A. Cassak

How energy is converted into thermal energy in weakly collisional and collisionless plasma processes such as magnetic reconnection and plasma turbulence has recently been the subject of intense scrutiny. The pressure-strain interaction has emerged as an important piece, as it describes the rate of conversion between bulk flow and thermal energy density. In t

Charles Fefferman, Ary Shaviv

For a set $E\subset\mathbb{R}^n$ that contains the origin we consider $I^m(E)$ -- the set of all $m^{\text{th}}$ degree Taylor approximations (at the origin) of $C^m$ functions on $\mathbb{R}^n$ that vanish on $E$. This set is a proper ideal in $\mathcal{P}^m(\mathbb{R}^n)$ -- the ring of all $m^{\text{th}}$ degree Taylor approximations of $C^m$ functions on

James Daniell, Kazuma Kobayashi, Ayodeji Alajo, Syed Bahauddin Alam

The accurate and efficient modeling of nuclear reactor transients is crucial for ensuring safe and optimal reactor operation. Traditional physics-based models, while valuable, can be computationally intensive and may not fully capture the complexities of real-world reactor behavior. This paper introduces a novel hybrid digital twin-focused multi-stage deep l

Stefano Marseglia, Harry Smit

We provide an algorithm that, given any order $O$ in a quaternion algebra over a global field, computes representatives of all right equivalence classes of right $O$-ideals, including the non-invertible ones. The theory is developed for a more general kind of algebras.

Subhash Singha

We report the measurements of global spin polarization of hyperons ($P_{\Lambda}$) from FAIR, RHIC and LHC energies. The $P_{\Lambda}$ continue to follow an increasing trend at $\sqrt{s_{\mathrm NN}}$ < 7.7 GeV indicating that enormous vorticity prevail even in hadronic dominant region. New measurements of local spin polarization ($P_{z,2}$) from isobar coll

Anish Agashe, Mustapha Ishak

It is well-known that spacetime averaging is an operation that does not commute with building the Einstein tensor. In the framework of Macroscopic gravity (MG), a covariant averaging procedure, this non-commutativity gives averaged field equations with an additional correction term known as back-reaction. It is important to explore whether such a term, even

Yongda Zhu, Hai-Xia Ma, Xiao-Bo Dong, Yang Huang

Aiming at discriminating different gravitational potential models of the Milky Way, we perform tests based on the kinematic data powered by the Gaia DR2 astrometry, over a large range of $(R,z)$ locations. Invoking the complete form of Jeans equations that admit three integrals of motion, we use the independent $R$- and $z$-directional equations as two discr

Jan Nienhaus

In the 1930s, H. Hopf conjectured that a closed, even-dimensional manifold of positive sectional curvature has positive Euler characteristic. We show this under the additional assumption of an isometric $T^4$-action on the manifold, improving from previous theorems of Kennard, Wiemeler and Wilking assuming a $T^5$-action. More specifically, this is achieved

Jan Graffelman, Jan de Leeuw

The graphical representation of the correlation matrix by means of different multivariate statistical methods is reviewed, a comparison of the different procedures is presented with the use of an example data set, and an improved representation with better fit is proposed. Principal component analysis is widely used for making pictures of correlation structu

Christopher Mayero, Joseph Akeyo Omolo

We considered the anti-Jaynes-Cummings (AJC) interaction of a two-level atom in an initial ground state interacting with a field mode in an initial squeezed coherent state at arbitrary values of squeeze parameter r and provided the Jaynes-Cummings (JC) interaction as a comparison. We analysed the degree of entanglement (DEM) measured by the von Neumann entro

Atta Muhammad, Rajat Srivastava, Nikos Koutroumanis, Dionisis Semitekolos

The development of nanocomposites relies on structure-property relations, which necessitate multiscale modeling approaches. This study presents a modelling framework that exploits mesoscopic models to predict the thermal and mechanical properties of nanocomposites starting from their molecular structure. In detail, mesoscopic models of polypropylene (PP) and

Dunja Pucher, Franz Rendl

We consider semidefinite relaxations of Stable-Set and Coloring, which are based on quadratic 0-1 optimization. Information about the stability number and the chromatic number is hidden in the objective function. This leads to simplified relaxations which depend mostly on the number of vertices of the graph. We also propose tightenings of the relaxations whi

Lorenza Nanni, Daniel Thomas, James Trayford, Claudia Maraston

Strengthening the synergy between simulations and observations is essential to test galaxy formation and evolution theories. To achieve this goal, in the first paper of this series, we presented a method to generate mock SDSS-IV/MaNGA integral-field spectroscopic galaxy observations from cosmological simulations. In this second paper, we build the iMaNGA cat

Gyula Lakos

We consider the elliptical range theorems for the Davis--Wielandt shell, the numerical range, and the conformal range in terms of and related to their quadratic representations. The emphasis is on exposing a variety of elementary approaches.

Christopher Gaul, Santiago Cuesta-Lopez

Organic semiconductors are promising materials for cheap, scalable and sustainable electronics, light-emitting diodes and photovoltaics. For organic photovoltaic cells, it is a challenge to find compounds with suitable properties in the vast chemical compound space. For example, the ionization energy should fit to the optical spectrum of sun light, and the e

Thomas Heimburg

The Fluid Mosaic Model by Singer & Nicolson proposes that biological membranes consist of a fluid lipid layer into which integral proteins are embedded. The lipid membrane acts as a two-dimensional liquid in which the proteins can diffuse and interact. Until today, this view seems very reasonable and is the predominant picture in the literature. However, the

Bogdan Ganchev, Daniel R. Mayerson

Four-dimensional supersymmetric black holes are static and so have all vanishing multipoles. Nevertheless, it is possible to define finite multipole ratios for these black holes, by taking the ratio of (finite) multipoles of supersymmetric multicentered geometries and then taking the black hole scaling limit of the multipole ratios within these geometries. A

Siyu Jiang, Fa Peng Huang, Xiao Wang

The bubble wall velocity is essential for the spectra of phase-transition gravitational waves, electroweak baryogenesis and the dynamical dark matter mechanism. We perform detailed calculations of the bubble wall velocity in the well-motivated inert doublet model using the microphysical approach with some recent new methods.

Alexander Wood, Artur Lozovoi, Zi-Huai Zhang, Sachin Sharma

The silicon-vacancy (SiV) center in diamond is typically found in three stable charge states, SiV0, SiV- and SiV2-, but studying the processes leading to their formation is challenging, especially at room temperature, due to their starkly different photo-luminescence rates. Here, we use confocal fluorescence microscopy to activate and probe charge interconve

Chris Barrett, Willem Heijltjes, Guy McCusker

The Functional Machine Calculus (FMC), recently introduced by the authors, is a generalization of the lambda-calculus which may faithfully encode the effects of higher-order mutable store, I/O and probabilistic/non-deterministic input. Significantly, it remains confluent and can be simply typed in the presence of these effects. In this paper, we explore the

Luke Pebody

It is a well-known conjecture, sometimes attributed to Frankl, that for any family of sets which is closed under the union operation, there is some element which is contained in at least half of the sets. Gilmer was the first to prove a constant bound, showing that there is some element contained in at least 1\% of the sets. They state in their paper that th

ATLAS Collaboration

This paper presents a search for dark matter, $\chi$, using events with a single top quark and an energetic $W$ boson. The analysis is based on proton-proton collision data collected with the ATLAS experiment at $\sqrt{s}=$ 13 TeV during LHC Run 2 (2015-2018), corresponding to an integrated luminosity of 139 fb$^{-1}$. The search considers final states with

Vinícius S. Borges, Marcio Eisencraft

In this paper, we use Lyapunov exponents to analyze how the dynamical properties of the H\'enon map change as a function of the coefficients of a linear filter inserted in its feedback loop. We show that the generated orbits can be chaotic or not, depending on the filter coefficients. The dynamics of the system presents complex behavior, including cascades o

Jakub Žádník, Markku Mäkitalo, Pekka Jääskeläinen

Latency-critical computer vision systems, such as autonomous driving or drone control, require fast image or video compression when offloading neural network inference to a remote computer. To ensure low latency on a near-sensor edge device, we propose the use of lightweight encoders with constant bitrate and pruned encoding configurations, namely, ASTC and

A. Bris, N. G. Gracia, V. Mateu

In this work we present the computation of so-called oriented event-shape distributions for massive quarks up to $\mathcal{O}(\alpha_s)$, along with the total oriented cross section in which one does not look at the geometric properties of the momentum distribution for particles in the final state. We consider the vector and axial-vector currents, and for th

Peng Li, Pengfei Qiu, Qing Xu, Jun Luo

Today solid-state cooling technologies below liquid nitrogen boiling temperature (77 K), crucial to quantum information technology and probing quantum state of matter, are greatly limited due to the lack of good thermoelectric and/or thermomagnetic materials. Here, we report the discovery of colossal Nernst power factor of 3800$\times$10$^{-4}$ W m$^{-1}$ K$

Renaud Raquépas

We state and prove a generalization of Kingman's ergodic theorem on a measure-preserving dynamical system $(X,\mathcal{F},\mu,T)$ where the $\mu$-almost sure subadditivity condition $f_{n+m} \leq f_n + f_m \circ T^{n}$ is relaxed to a $\mu$-almost sure, "gapped", almost subadditivity condition of the form $f_{n+\sigma_m+m} \leq f_n +\rho_n + f_m \circ T^{n+\

Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu M. Gavrila

Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has proven to be an effective technique to significantly improve the student's performance for various tasks including object detection. As such, KD techniques mostly rely on guidance at

Clint Harris

Many treatment variables used in empirical applications nest multiple unobserved versions of a treatment. I show that instrumental variable (IV) estimands for the effect of a composite treatment are IV-specific weighted averages of effects of unobserved component treatments. Differences between IVs in unobserved component compliance produce differences in IV

Juyang Weng

This is a theoretical paper, as a companion paper of the plenary talk for the same conference ISAIC 2022. In contrast to the author's plenary talk in the same conference, conscious learning (Weng, 2022b; Weng, 2022c) which develops a single network for a life (many tasks), "Deep Learning" trains multiple networks for each task. Although "Deep Learning" may u

Grégoire Petit, Adrian Popescu, Hugo Schindler, David Picard

Exemplar-free class-incremental learning is very challenging due to the negative effect of catastrophic forgetting. A balance between stability and plasticity of the incremental process is needed in order to obtain good accuracy for past as well as new classes. Existing exemplar-free class-incremental methods focus either on successive fine tuning of the mod

Jacob Butt, Nicos Georgiou, Enrico Scalas

We study three non-equivalent queueing models in continuous time that each generalise the classical M/M/1 queue in a different way. Inter-event times in all models are Mittag-Leffler distributed, which is a heavy tail distribution with no moments. For each of the models we answer the question of the queue being at zero infinitely often (the `recurrence' or `

Seyed Mojtaba Marvasti-Zadeh, Devin Goodsman, Nilanjan Ray, Nadir Erbilgin

Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner. In this paper, we propose interpretable class activation mapping for tree crown detection (Crown-CAM) that overcomes inaccurate localization & computational complexity of previous meth

Arpan Hait, Subhendra Mohanty, Suraj Prakash

The memory effect in gravitational wave (GW) signals is the phenomenon, wherein the relative position of two inertial GW detectors undergoes a permanent displacement owing to the passage of GWs through them. Measurement of the memory signal is an important target for future observations as it establishes a connection between observations with field-theoretic

Ted Loch-Temzelides

We establish the existence of fixed points for set-valued maps defined on metric spaces and satisfying a pointwise or a local version of Banach's contraction property. As an application, we demonstrate the existence of Nash equilibrium in a general class of strategic games played on metric spaces of strategies.

Łukasz Augustyniak, Kamil Tagowski, Albert Sawczyn, Denis Janiak

The availability of compute and data to train larger and larger language models increases the demand for robust methods of benchmarking the true progress of LM training. Recent years witnessed significant progress in standardized benchmarking for English. Benchmarks such as GLUE, SuperGLUE, or KILT have become de facto standard tools to compare large languag

Wang-Wei Yu, Shao-Jiang Wang

The current LIGO-Virgo observing run has been pushing the sensitivity limit to touch the stochastic gravitational-wave backgrounds (SGWBs). However, no significant detection has been reported to date for any single dominated source of SGWBs with a single broken-power-law (BPL) spectrum. Nevertheless, it could equally well escape from existing Bayesian search

Adrian Gonzalez Casanova, Charline Smadi, Anton Wakolbinger

Consider a population of $N$ individuals, each of them carrying a type in $\mathbb N_0$. The population evolves according to a Moran dynamics with selection and mutation, where an individual of type $k$ has the same selective advantage over all individuals with type $k' > k$, and type $k$ mutates to type $k+1$ at a constant rate. This model is thus a variati

Tian Yu Liu, Aditya Golatkar, Stefano Soatto, Alessandro Achille

We propose a lightweight continual learning method which incorporates information from specialized datasets incrementally, by integrating it along the vector field of "generalist" models. The tangent plane to the specialist model acts as a generalist guide and avoids the kind of over-fitting that leads to catastrophic forgetting, while exploiting the convexi

Erika Arai, Hiroshi Ohki, Shinji Takeda, Masaaki Tomii

In usual (non-stochastic) tensor network calculations, the truncated singular value decomposition (SVD) is often used for approximating a tensor, and it causes systematic errors. By introducing stochastic noise in the approximation, however, one can avoid such systematic errors at the expense of statistical errors which can be straightforwardly controlled. T

Jiwoong Kim, Kajetan M. Fijalkowski, Johannes Kleinlein, Claus Schumacher

The search for topological superconductivity has motivated investigations into materials that combine topological and superconducting properties. The half-Heusler compound YPtBi appears to be such a material, however experiments have thus far been limited to bulk single crystals, drastically limiting the scope of available experiments. This has made it impos

Matteo Dalla Riva, Riccardo Molinarolo, Paolo Musolino

In this paper we study the existence and the analytic dependence upon domain perturbation of the solutions of a nonlinear nonautonomous transmission problem for the Laplace equation. The problem is defined in a pair of sets consisting of a perforated domain and an inclusion whose shape is determined by a suitable diffeomorphism $\phi$. First we analyse the c

Kaspar Hageman, Álvaro Feal, Julien Gamba, Aniketh Girish

The ability to identify the author responsible for a given software object is critical for many research studies and for enhancing software transparency and accountability. However, as opposed to other application markets like iOS, attribution in the Android ecosystem is known to be hard. Prior research has leveraged market metadata and signing certificates

Pei-Gen Yan, James F. Babb

Fine-structure transitions can be involved in various processes including photon absorption, charge transfer and inelastic collision between ions, electrons and neutral atoms. We present fine-structure excitation and relaxation cross sections for the collisions of the first few members of the carbon isoelectronic sequence (C, N$^+$ and O$^{2+}$) with atomic

Mohammadali Sharifshazileh, Giacomo Indiveri

Typical bio-signal processing front-ends are designed to maximize the quality of the recorded data, to allow faithful reproduction of the signal for monitoring and off-line processing. This leads to designs that have relatively large area and power consumption figures. However, wearable devices for always-on biomedical applications do not necessarily require

John Gliksberg, Antoine Capra, Alexandre Louvet, Pedro Javier Garcia

Coupling regular topologies with optimised routing algorithms is key in pushing the performance of interconnection networks of supercomputers.In this paper we present Dmodc, a fast deterministic routing algorithm for Parallel Generalised Fat-Trees (PGFTs) which minimises congestion risk even under massive network degradation caused by equipment failure.Dmodc

Tomohiro Hirano, Ryo Jinnai, Alexis Akira Toda

We present a general equilibrium macro-finance model with a positive feedback loop between capital investment and land price. As leverage is relaxed beyond a critical value, through the financial accelerator, a phase transition occurs from balanced growth where land prices reflect fundamentals (present value of rents) to unbalanced growth where land prices g

Peng Chen, Hong Jian Zhao, Sergey Prosandeev, Sergey Artyukhin

The microscopic origin of the electric Dzyaloshinskii-Moriya interaction (eDMI) is unveiled and discussed by analytical analysis and first-principles based calculations. As similar to the magnetic Dzyaloshinskii-Moriya interaction (mDMI), eDMI also originates from electron-mediated effect and more specifically from certain electron hoppings that are being ac

Lorena Poenaru-Olaru, Luis Cruz, Arie van Deursen, Jan S. Rellermeyer

As machine learning models increasingly replace traditional business logic in the production system, their lifecycle management is becoming a significant concern. Once deployed into production, the machine learning models are constantly evaluated on new streaming data. Given the continuous data flow, shifting data, also known as concept drift, is ubiquitous

Jin Wang, Hui Xiao, Shuwen Zhong, Yinhao Xiao

Software vulnerabilities can pose severe harms to a computing system. They can lead to system crash, privacy leakage, or even physical damage. Correctly identifying vulnerabilities among enormous software codes in a timely manner is so far the essential prerequisite to patch them. Unfortantely, the current vulnerability identification methods, either the cla

Oahidul Islam, Sumaya Akter Shikha

Internet of Things (IoT)-based applications must be integrated with wireless communication technologies for this make application data easily accessible. The wireless communication system is a crucial component of IoT infrastructure, serving as a bridge for bidirectional connection for data gathering and control message delivery. In this article, a modified

Jennifer C. White, Ryan Cotterell

Recent work has shown that despite their impressive capabilities, text-to-image diffusion models such as DALL-E 2 (Ramesh et al., 2022) can display strange behaviours when a prompt contains a word with multiple possible meanings, often generating images containing both senses of the word (Rassin et al., 2022). In this work we seek to put forward a possible e

Fernando Fernandes dos Santos, Angeliki Kritikakou, Josie Esteban Rodriguez Condia, Juan David Guerrero Balaguera

The reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic Processing Units (GPUs) is a challenging problem since the hardware architecture is highly complex and the software frameworks are composed of many layers of abstraction. While software-level fault injection is a common and fast way to evaluate the reliability of complex applicatio

Erik Bauer, Barnabas Gavin Cangan, Robert K. Katzschmann

In a future with autonomous robots, visual and spatial perception is of utmost importance for robotic systems. Particularly for aerial robotics, there are many applications where utilizing visual perception is necessary for any real-world scenarios. Robotic aerial grasping using drones promises fast pick-and-place solutions with a large increase in mobility

Audrey Duran, Gaspard Dussert, Olivier Rouvière, Tristan Jaouen

Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent results in the detection of prostate cancer (PCa). However, characterizing prostate lesions aggressiveness in mp-MRI sequences is impossible in clinical practice, and biopsy remains the reference to determine the Gleason score (GS). In this work, we propose a novel end-to-end multi-class

Xinyuan An, Xiaowei Cui, Sihao Zhao, Gang Liu

In real-world applications for automatic guided vehicle (AGV) navigation, the positioning system based on the time-of-flight (TOF) measurements between anchors and tags is confronted with the problem of insufficient measurements caused by blockages to radio signals or lasers, etc. Mounting multiple tags at different positions of the AGV to collect more TOFs

Zhen Hao Gan, Yangwei You, Meng Yee, Chuah

Tactile sensors have been introduced to a wide range of robotic tasks such as robot manipulation to mimic the sense of human touch. However, there has only been a few works that integrate tactile sensing into robot navigation. This paper describes a navigation system which allows robots to operate in crowded human-dense environments and behave with socially

Sifeng He, Yue He, Minlong Lu, Chen Jiang

Video copy localization aims to precisely localize all the copied segments within a pair of untrimmed videos in video retrieval applications. Previous methods typically start from frame-to-frame similarity matrix generated by cosine similarity between frame-level features of the input video pair, and then detect and refine the boundaries of copied segments o

Lluís Hernández-Mulà, Andreas M. Läuchli

We present an algorithm to solve very large one-dimensional disordered and interacting few-particle systems. Our approach exploits the localized nature of the eigenfunctions in real space to achieve a linear scaling with the total system size $L$. This allows us to solve for all eigenfunctions of single-particle systems with different types of disorder up to

Pierre-Henri Chavanis

We derive an approximate analytical expression of the maximum mass of relativistic self-gravitating Bose-Einstein condensates with repulsive or attractive $|\varphi|^4$ self-interaction. This expression interpolates between the general relativistic maximum mass of noninteracting bosons stars, the general relativistic maximum mass of bosons stars with a repul

Leonid Shirkov, Michał Tomza

The isotropic and anisotropic coefficients $C^{l,m}_n$ of the long-range spherical expansion $\sim 1/R^n$ ($R$ -- the intermolecular distance) of the dispersion and inductions intermolecular energies are calculated using the first principles for the complexes containing an aromatic molecule (benzene, pyridine, furan, and pyrrole) and alkali-metal (Li, Na, K,

Mengmi Zhang, Elisa Pavarino, Xiao Liu, Giorgia Dellaferrera

As AI becomes increasingly embedded in daily life, ascertaining whether an agent is human is critical. We systematically benchmark AI's ability to imitate humans in three language tasks (image captioning, word association, conversation) and three vision tasks (color estimation, object detection, attention prediction), collecting data from 636 humans and 37 A

Michele Gentili, Leonardo Martini, Marialuisa Sponziello, Luca Becchetti

Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechanisms and guiding the quest for therapeutic targets. This is all the more important, since experimental investigation of potential gene candidates is an expensive task, thus not alwa

Evgenia Koumpia, M. Koutoulaki, W. -J. de Wit, R. D. Oudmaijer

With steady observational advances, the formation of massive stars is being understood in more detail. Numerical models are converging on a scenario where accretion discs play a key role. Direct observational evidence of such discs at a few au scales is scarce, due to the rarity of such objects and the observational challenges, including the lack of adequate

Weijie Zheng, Benjamin Doerr

The NSGA-II is one of the most prominent algorithms to solve multi-objective optimization problems. Despite numerous successful applications, several studies have shown that the NSGA-II is less effective for larger numbers of objectives. In this work, we use mathematical runtime analyses to rigorously demonstrate and quantify this phenomenon. We show that ev

Michel de Lara

In his monograph \emph{Conjugate Duality and Optimization}, Rockafellar puts forward a ``perturbation + duality'' method to obtain a dual problem for an original minimization problem. First, one embeds the minimization problem into a family of perturbed problems (thus giving a so-called perturbation function); the perturbation of the original function to be

Melissa Dancy, Charles Henderson, Nanah Apkarian, Estrella Johnson

A survey of 722 physics faculty conducted in 2008 found that many physics instructors had knowledge of research-based instructional strategies (RBISs), were interested in using more, but often discontinued use after trying. Considerable effort has been made during the decade following 2008 to develop and disseminate RBISs in physics as well as change the cul

Mario Döbler, Robert A. Marsden, Bin Yang

Since experiencing domain shifts during test-time is inevitable in practice, test-time adaption (TTA) continues to adapt the model after deployment. Recently, the area of continual and gradual test-time adaptation (TTA) emerged. In contrast to standard TTA, continual TTA considers not only a single domain shift, but a sequence of shifts. Gradual TTA further

R. Cumming, T. Thomas

Quantum computing is an important developing technology with the potential to revolutionise the landscape of scientific and business problems that can be practically addressed. The widespread excitement derives from the potential for a fault tolerant quantum computer to solve previously intractable problems. Such a machine is not expected to be available unt

Frédéric Vella, Flavien Clastres-Babou, Nadine Vigouroux, Philippe Truillet

We describe a co-design approach to design the online WebSoKeyTo used to design AAC. This co-design was carried out between a team of therapists and a team of human-computer interaction researchers. Our approach begins with the use and evaluation of an existing SoKeyTo AAC design application. This step was essential in the awareness and definition of the nee

Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich

We propose a multi-explanation graph attention network (MEGAN). Unlike existing graph explainability methods, our network can produce node and edge attributional explanations along multiple channels, the number of which is independent of task specifications. This proves crucial to improve the interpretability of graph regression predictions, as explanations