Author: "Berend, A." - Searchworks@Jio Institute Digital Library Search Results

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29,233 results on '"Berend, A."'

1. Exceptional Points for Density Modulo 1

Author: Berend, Daniel, Boshernitzan, Michael D., Kolesnik, Grigori, and Kumar, Rishi
Subjects: Mathematics - Number Theory, 1B05, 11J71, 11K06, 11K55
Abstract: It is well known that almost every dilation of a sequence of real numbers, that diverges to $\infty$, is dense modulo~1. This paper studies the exceptional set of points -- those for which the dilation is not dense. Specifically, we consider the Hausdorff and modified box dimensions of the set of exceptional points. In particular, we show that the dimension of this set may be any number between 0 and 1. Similar results are obtained for two ``natural'' subsets of the set of exceptional points. Furthermore, the paper calculates the dimension of several sets of points, defined by certain constraints on their binary expansion.
Published: 2024

2. Correlations for aerodynamic force coefficients of non-spherical particles in compressible flows

Author: Gorges, Christian, Chéron, Victor, Chopra, Anjali, Denner, Fabian, and van Wachem, Berend
Subjects: Physics - Fluid Dynamics
Abstract: This study presents particle-resolved direct numerical simulations using three-dimensional body-fitted hexahedral grids to investigate the aerodynamic force and torque coefficients of non-spherical particles in compressible flows. The simulations focus on three particle shapes: a prolate spheroid, an oblate spheroid, and a rod-like particle, across a range of Mach numbers (0.3 to 2.0), angles of attack (0\degree to 90\degree), and particle Reynolds numbers (100 to 300). Results show that particle shape significantly impacts the aerodynamic forces on a particle in a compressible flow, with oblate spheroids exhibiting the highest drag, lift, and torque values. Correlations for these aerodynamic coefficients of the particles in a compressible flow are developed and validated. These correlations advance multiphase flow modeling by improving the accuracy of point-particle simulations for non-spherical particles in compressible flows.
Published: 2024

3. SWAP-less Implementation of Quantum Algorithms

Author: Klaver, Berend, Rombouts, Stefan, Fellner, Michael, Messinger, Anette, Ender, Kilian, Ludwig, Katharina, and Lechner, Wolfgang
Subjects: Quantum Physics
Abstract: We present a formalism based on tracking the flow of parity quantum information to implement algorithms on devices with limited connectivity without qubit overhead, SWAP operations or shuttling. Instead, we leverage the fact that entangling gates not only manipulate quantum states but can also be exploited to transport quantum information. We demonstrate the effectiveness of this method by applying it to the quantum Fourier transform (QFT) and the Quantum Approximate Optimization Algorithm (QAOA) with $n$ qubits. This improves upon all state-of-the-art implementations of the QFT on a linear nearest-neighbor architecture, resulting in a total circuit depth of ${5n-3}$ and requiring ${n^2-1}$ CNOT gates. For the QAOA, our method outperforms SWAP networks, which are currently the most efficient implementation of the QAOA on a linear architecture. We further demonstrate the potential to balance qubit count against circuit depth by implementing the QAOA on twice the number of qubits using bi-linear connectivity, which approximately halves the circuit depth., Comment: 10 pages, 5 figures
Published: 2024

4. A holistic platform for accelerating sorbent-based carbon capture

Author: Charalambous, Charithea, Moubarak, Elias, Schilling, Johannes, Sanchez Fernandez, Eva, Wang, Jin-Yu, Herraiz, Laura, Mcilwaine, Fergus, Peh, Shing Bo, Garvin, Matthew, Jablonka, Kevin Maik, Moosavi, Seyed Mohamad, Van Herck, Joren, Ozturk, Aysu Yurdusen, Pourghaderi, Alireza, Song, Ah-Young, Mouchaham, Georges, Serre, Christian, Reimer, Jeffrey A, Bardow, André, Smit, Berend, and Garcia, Susana
Subjects: Built Environment and Design, Environmental Management, Environmental Sciences, Generic health relevance, Climate Action, General Science & Technology
Abstract: Reducing carbon dioxide (CO2) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO2 from various sources and deliver it to different sinks1,2. The quest for optimal solutions for specific source-sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design3 and engineers on optimizing processes4,5, which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant's lifetime, is typically one of the final steps6. Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.
Published: 2024

5. Exact expressions for the maximal probability that all $k$-wise independent bits are 1

Author: Berend, Daniel, Ernst, Philip A., Kontorovich, Aryeh, and Kumar, Rishi
Subjects: Mathematics - Probability
Abstract: Let $M(n, k, p)$ denote the maximum probability of the event $X_1 = X_2 = \cdots = X_n=1$ under a $k$-wise independent distribution whose marginals are Bernoulli random variables with mean $p$. A long-standing question is to calculate $M(n, k, p)$ for all values of $n,k,p$. This question has been partially addressed by several authors, primarily with the goal of answering asymptotic questions. The present paper focuses on obtaining exact expressions for this probability. To this end, we provide closed-form formulas of $M(n,k,p)$ for $p$ near 0 as well as $p$ near 1.
Published: 2024

6. Integrated feature analysis for deep learning interpretation and class activation maps

Author: Li, Yanli, Hassanzadeh, Tahereh, Shamonin, Denis P., Reijnierse, Monique, Mil, Annette H. M. van der Helm-van, and Stoel, Berend C.
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: Understanding the decisions of deep learning (DL) models is essential for the acceptance of DL to risk-sensitive applications. Although methods, like class activation maps (CAMs), give a glimpse into the black box, they do miss some crucial information, thereby limiting its interpretability and merely providing the considered locations of objects. To provide more insight into the models and the influence of datasets, we propose an integrated feature analysis method, which consists of feature distribution analysis and feature decomposition, to look closer into the intermediate features extracted by DL models. This integrated feature analysis could provide information on overfitting, confounders, outliers in datasets, model redundancies and principal features extracted by the models, and provide distribution information to form a common intensity scale, which are missing in current CAM algorithms. The integrated feature analysis was applied to eight different datasets for general validation: photographs of handwritten digits, two datasets of natural images and five medical datasets, including skin photography, ultrasound, CT, X-rays and MRIs. The method was evaluated by calculating the consistency between the CAMs average class activation levels and the logits of the model. Based on the eight datasets, the correlation coefficients through our method were all very close to 100%, and based on the feature decomposition, 5%-25% of features could generate equally informative saliency maps and obtain the same model performances as using all features. This proves the reliability of the integrated feature analysis. As the proposed methods rely on very few assumptions, this is a step towards better model interpretation and a useful extension to existing CAM algorithms. Codes: https://github.com/YanliLi27/IFA, Comment: 13 pages, 11 figures, code available: https://github.com/YanliLi27/IFA This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Published: 2024

7. Simultaneous visibility in the integer lattice

Author: Berend, Daniel, Kumar, Rishi, and Pollington, Andrew
Subjects: Mathematics - Number Theory, Primary: 11P21, 11N36, Secondary: 37A44
Abstract: Two lattice points are visible from one another if there is no lattice point on the open line segment joining them. Let $S$ be a finite subset of $\mathbb{Z}^k$. The asymptotic density of the set of lattice points, visible from all points of $S$, was studied by several authors. Our main result is an improved upper bound on the error term. We also find the Schnirelmann density of the set of visible points from some sets S. Finally, we discuss these questions from the point of view of ergodic theory., Comment: Published in Journal of Number Theory
Published: 2024

8. Physically consistent immersed boundary method: a framework for predicting hydrodynamic forces on particles with coarse meshes

Author: Hausmann, Max, Elmestikawy, Hani, and van Wachem, Berend
Subjects: Physics - Fluid Dynamics, Physics - Computational Physics
Abstract: In the present paper, a fluid-particle coupling method is directly derived from the Navier-Stokes equations (NSE) by applying the concept of volume-filtering, yielding a physically consistent methodology to incorporate solid wall boundary conditions in the volume-filtered flow solution, thereby allowing to solve the governing flow equations on non-body conforming meshes. The resulting methodology possesses similarities with a continuous forcing immersed boundary method (IBM) and is, therefore, termed physically consistent IBM (PC-IBM). Based on the recent findings of arXiv:2402.05842v1, the closures arising in the volume-filtered NSE are closed by suitable models or even expressed analytically. The PC-IBM is fully compatible with the large eddy simulation framework, as the volume-filtered NSE converge to the filtered NSE away from solid boundaries. The potential of the PC-IBM is demonstrated by means of different particle-laden flow applications, including a dense packing of fixed particles and periodic settling of 500 particles. The new methodology turns out to be capable of accurately predicting the fluid forces on particles with relatively coarse mesh resolutions. For the flow around isolated spheres, a spatial resolution of six fluid mesh cells per diameter is sufficient to predict the drag force with less than 10% deviation from highly resolved simulation for the investigated particle Reynolds numbers ranging from 10 to 250.
Published: 2024

9. Intertwining and propagation of mixtures for generalized KMP models and harmonic models

Author: Giardinà, Cristian, Redig, Frank, and van Tol, Berend
Subjects: Mathematics - Probability, Condensed Matter - Statistical Mechanics, Mathematical Physics
Abstract: We study a class of stochastic models of mass transport on discrete vertex set $V$. For these models, a one-parameter family of homogeneous product measures $\otimes_{i\in V} \nu_\theta$ is reversible. We prove that the set of mixtures of inhomogeneous product measures with equilibrium marginals, i.e., the set of measures of the form \[ \int\Big(\bigotimes_{i\in V} \nu_{\theta_i}\Big) \,\Xi(\prod_{i\in V}d\theta_i) \] is left invariant by the dynamics in the course of time, and the ``mixing measure'' $\Xi$ evolves according to a Markov process which we then call ``the hidden parameter model''. This generalizes results from [7] to a larger class of models and on more general graphs. The class of models includes discrete and continuous generalized KMP models, as well as discrete and continuous harmonic models. The results imply that in all these models, the non-equilibrium steady state of their reservoir driven version is a mixture of product measures where the mixing measure is in turn the stationary state of the corresponding ``hidden parameter model''. For the boundary-driven harmonic models on the chain $\{1,\ldots, N\}$ with nearest neighbor edges, we recover that the stationary measure of the hidden parameter model is the joint distribution of the ordered Dirichlet distribution (cf. [3]), with a purely probabilistic proof based on a spatial Markov property of the hidden parameter model., Comment: 30 pages
Published: 2024

10. Drag, lift, and torque correlations for axi-symmetric rod-like non-spherical particles in linear wall-bounded shear flow

Author: Chéron, Victor and van Wachem, Berend
Subjects: Physics - Fluid Dynamics
Abstract: This paper presents novel correlations to predict the drag, lift, and torque coefficients of axi-symmetric non-spherical rod-like particles in a wall-bounded linear shear flow. The particle position and orientation relative to the wall are varied to systematically investigate the influence of the wall on the hydrodynamic forces. The newly derived correlations for drag, lift, and torque on the particle depend on various parameters, including the particle Reynolds number, the orientation angle between the major axis of the particle and the main local flow direction, the aspect ratio of the particle, and the dimensionless distance from the particle centre to the wall. The coefficients of the correlations are determined through a fitting process utilizing the data generated from our previous study on the interaction forces between a locally uniform flow and an axi-symmetric non-spherical rod-like particles, as well as from data of novel direct numerical simulations (DNS) performed in this work of flow past axi-symmetric rod-like particles near a wall. The proposed correlations exhibit a good agreement compared to the DNS results, with median errors of 2.89%, 5.37%, and 11.00%, and correlation coefficients of 0.99, 0.99, and 0.96 for the correlations accounting for changes in drag, lift, and torque coefficients due to the wall-bounded linear shear flow profile, respectively. These correlations can be used in large-scale simulations using an Eulerian-Lagrangian or a CFD/DEM framework to predict the behaviour of axi-symmetric rod-like non-spherical particles in wall-bounded flows, shear flows, as well as uniform flows.
Published: 2024

11. A semi-analytical transient undisturbed velocity correction scheme for wall-bounded two-way coupled Euler-Lagrange simulations

Author: Chandran, Akshay, Evrard, Fabien, and van Wachem, Berend
Subjects: Physics - Fluid Dynamics, Physics - Computational Physics
Abstract: In the present paper, we model the velocity disturbance generated by a regularized forcing near a planar wall, which, along with the temporal nature of the forcing, provides an estimate of the unsteady velocity disturbance of the particle near a planar wall. We use the analytical solution for a singular in-time transient Stokeslet near a planar wall (Felderhof, 2009) and derive the corresponding time-persistent Stokeslets. The velocity disturbance due to a regularized forcing is then obtained numerically via a discrete convolution with the regularization kernel. The resulting Green's functions for parallel and perpendicular regularized forcing to the wall are stored as pre-computed temporal correction maps. By storing the time-dependent particle force on the fluid as fictitious particles, we estimate the unsteady velocity disturbance generated by the particle as a scalar product between the stored forces and the pre-computed Green's functions. Since the model depends on the analytical Green's function solution of the singular Stokeslet near a planar wall, the obtained velocity disturbance exactly satisfies the no-slip condition and does not require any fitted parameters to account for the rapid decay of the disturbance near the wall. The numerical evaluation of the convolution integral makes the present method suitable for arbitrary regularization kernels. Additionally, the generation of parallel and perpendicular correction maps enables to estimate the velocity disturbance due to particle motion in arbitrary directions relative to the local flow. The convergence of the method is studied on a fixed particle near a planar wall, and verification tests are performed on a settling particle parallel to a wall and a free-falling particle perpendicular to the wall., Comment: 40 pages
Published: 2024

12. Undisturbed velocity recovery with transient and weak inertia effects in volume-filtered simulations of particle-laden flows

Author: Evrard, Fabien, Chandran, Akshay, Cortez, Ricardo, and van Wachem, Berend
Subjects: Physics - Computational Physics, Physics - Fluid Dynamics
Abstract: In volume-filtered Euler-Lagrange simulations of particle-laden flows, the fluid forces acting on a particle are estimated using reduced models, which rely on the knowledge of the local undisturbed flow for that particle. Since the two-way coupling between the particle and the fluid creates a local flow perturbation, the filtered fluid velocity interpolated to the particle location must be corrected prior to estimating the fluid forces, so as to subtract the contribution of this perturbation and recover the local undisturbed flow with good accuracy. In this manuscript, we present a new model for estimating a particle's self-induced flow disturbance that accounts for its transient development and for inertial effects related to finite particle Reynolds numbers. The model also does not require the direction of the momentum feedback to align with the direction of the particle's relative velocity, allowing force contributions other than the steady drag force to be considered. It is based upon the linearization of the volume-filtered equations governing the particle's self-induced flow disturbance, such that their solution can be expressed as a linear combination of regularized transient Stokeslet contributions. Tested on a range of numerical cases, the model is shown to consistently estimate the particle's self-induced flow disturbance with high accuracy both in steady and highly transient flow environments, as well as for finite particle Reynolds numbers.
Published: 2024

13. TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters

Author: Lavington, Jonathan Wilder, Zhang, Ke, Lioutas, Vasileios, Niedoba, Matthew, Liu, Yunpeng, Green, Dylan, Naderiparizi, Saeid, Liang, Xiaoxuan, Dabiri, Setareh, Ścibior, Adam, Zwartsenberg, Berend, and Wood, Frank
Subjects: Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems, Computer Science - Robotics
Abstract: The training, testing, and deployment, of autonomous vehicles requires realistic and efficient simulators. Moreover, because of the high variability between different problems presented in different autonomous systems, these simulators need to be easy to use, and easy to modify. To address these problems we introduce TorchDriveSim and its benchmark extension TorchDriveEnv. TorchDriveEnv is a lightweight reinforcement learning benchmark programmed entirely in Python, which can be modified to test a number of different factors in learned vehicle behavior, including the effect of varying kinematic models, agent types, and traffic control patterns. Most importantly unlike many replay based simulation approaches, TorchDriveEnv is fully integrated with a state of the art behavioral simulation API. This allows users to train and evaluate driving models alongside data driven Non-Playable Characters (NPC) whose initializations and driving behavior are reactive, realistic, and diverse. We illustrate the efficiency and simplicity of TorchDriveEnv by evaluating common reinforcement learning baselines in both training and validation environments. Our experiments show that TorchDriveEnv is easy to use, but difficult to solve.
Published: 2024

14. Semantically Consistent Video Inpainting with Conditional Diffusion Models

Author: Green, Dylan, Harvey, William, Naderiparizi, Saeid, Niedoba, Matthew, Liu, Yunpeng, Liang, Xiaoxuan, Lavington, Jonathan, Zhang, Ke, Lioutas, Vasileios, Dabiri, Setareh, Scibior, Adam, Zwartsenberg, Berend, and Wood, Frank
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information across frames. While such approaches have led to significant progress on standard benchmarks, they struggle with tasks that require the synthesis of novel content that is not present in other frames. In this paper we reframe video inpainting as a conditional generative modeling problem and present a framework for solving such problems with conditional video diffusion models. We highlight the advantages of using a generative approach for this task, showing that our method is capable of generating diverse, high-quality inpaintings and synthesizing new content that is spatially, temporally, and semantically consistent with the provided context.
Published: 2024

15. Ferroelectric modulation of quantum emitters in monolayer WS$_2$

Author: Lee, Sung-Joon, Chuang, Hsun-Jen, Yeats, Andrew, McCreary, Kathleen M., O'Hara, Dante J., and Jonker, Berend T.
Subjects: Condensed Matter - Materials Science
Abstract: Quantum photonics promises significant advances in secure communications, metrology, sensing and information processing/computation. Single photon sources are fundamental to this endeavor. However, the lack of high quality single photon sources remains a significant obstacle. We present here a new paradigm for the control of single photon emitters (SPEs) and single photon purity by integrating monolayer WS$_2$ with the organic ferroelectric polymer poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)). We demonstrate that the ferroelectric domains in the P(VDF-TrFE) film control the purity of single photon emission from the adjacent WS$_2$. By switching the ferroelectric polarization, we reversibly tune the single photon purity between the semi-classical and quantum light regimes, with single photon purities as high as 94%. This provides another avenue for modulating and encoding quantum photonic information, complementing more complex approaches. This novel multidimensional heterostructure introduces a new avenue for control of quantum emitters by combining the nonvolatile ferroic properties of a ferroelectric with the radiative properties of the zero-dimensional atomic scale emitters embedded in the two-dimensional WS$_2$ semiconductor monolayer.
Published: 2024

16. Fault-tolerant quantum computing with the parity code and noise-biased qubits

Author: Messinger, Anette, Torggler, Valentin, Klaver, Berend, Fellner, Michael, and Lechner, Wolfgang
Subjects: Quantum Physics
Abstract: We present a fault-tolerant universal quantum computing architecture based on a code concatenation of noise-biased qubits and the parity architecture. The parity architecture can be understood as a LDPC code tailored specifically to obtain any desired logical connectivity from nearest neighbor physical interactions. The code layout can be dynamically adjusted to algorithmic requirements on-the-fly. This allows reaching arbitrary code distances and thereby exponential suppression of errors with a universal set of fault-tolerant gates. In addition to the previously explored tool-sets for concatenated cat codes, our approach features parallelizable interactions between arbitrary sets of qubits by directly addressing the parity qubits in the code. The proposed scheme enables codes with less physical qubit overhead compared to the repetition code with the same code distances, while requiring only weight-3 and weight-4 stabilizers and nearest neighbor 2D square-lattice connectivity., Comment: 8 pages
Published: 2024

17. Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case Study

Author: van Dam, Tim, van der Heijden, Frank, de Bekker, Philippe, Nieuwschepen, Berend, Otten, Marc, and Izadi, Maliheh
Subjects: Computer Science - Computation and Language
Abstract: Language model-based code completion models have quickly grown in use, helping thousands of developers write code in many different programming languages. However, research on code completion models typically focuses on imperative languages such as Python and JavaScript, which results in a lack of representation for functional programming languages. Consequently, these models often perform poorly on functional languages such as Haskell. To investigate whether this can be alleviated, we evaluate the performance of two language models for code, CodeGPT and UniXcoder, on the functional programming language Haskell. We fine-tune and evaluate the models on Haskell functions sourced from a publicly accessible Haskell dataset on HuggingFace. Additionally, we manually evaluate the models using our novel translated HumanEval dataset. Our automatic evaluation shows that knowledge of imperative programming languages in the pre-training of LLMs may not transfer well to functional languages, but that code completion on functional languages is feasible. Consequently, this shows the need for more high-quality Haskell datasets. A manual evaluation on HumanEval-Haskell indicates CodeGPT frequently generates empty predictions and extra comments, while UniXcoder more often produces incomplete or incorrect predictions. Finally, we release HumanEval-Haskell, along with the fine-tuned models and all code required to reproduce our experiments on GitHub (https://github.com/AISE-TUDelft/HaskellCCEval)., Comment: To appear in the First Special Event on AI Foundation Models and Software Engineering (FORGE 2024)
Published: 2024

18. Nearest Neighbour Score Estimators for Diffusion Generative Models

Author: Niedoba, Matthew, Green, Dylan, Naderiparizi, Saeid, Lioutas, Vasileios, Lavington, Jonathan Wilder, Liang, Xiaoxuan, Liu, Yunpeng, Zhang, Ke, Dabiri, Setareh, Ścibior, Adam, Zwartsenberg, Berend, and Wood, Frank
Subjects: Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract: Score function estimation is the cornerstone of both training and sampling from diffusion generative models. Despite this fact, the most commonly used estimators are either biased neural network approximations or high variance Monte Carlo estimators based on the conditional score. We introduce a novel nearest neighbour score function estimator which utilizes multiple samples from the training set to dramatically decrease estimator variance. We leverage our low variance estimator in two compelling applications. Training consistency models with our estimator, we report a significant increase in both convergence speed and sample quality. In diffusion models, we show that our estimator can replace a learned network for probability-flow ODE integration, opening promising new avenues of future research., Comment: 25 pages, 9 figures. To be published in ICML 2024
Published: 2024

19. Study and derivation of closures in the volume-filtered framework for particle-laden flows

Author: Hausmann, Max, Chéron, Victor, Evrard, Fabien, and van Wachem, Berend
Subjects: Physics - Fluid Dynamics
Abstract: The volume-filtering of the Navier-Stokes equations allows to consider the effect that particles have on the fluid without further assumptions, but closures arise of which the implications are not fully understood. In the present paper, we carefully study every closure in the volume-filtered fluid momentum equation and investigate their impact on the momentum and energy transfer dependent on the filtering characteristics. We provide an analytical expression for the viscous closure that arises because filter and spatial derivative in the viscous term do not commute. An analytical expression for the regularization of the particle momentum source of a single sphere in the Stokes regime is derived. Furthermore, we propose a model for the subfilter stress tensor, which originates from filtering the advective term. The model for the subfilter stress tensor is shown to agree well with the subfilter stress tensor for small filter widths relative to the size of the particle. We show that the subfilter stress tensor requires modeling and should not be neglected. For small filter widths, we find that the commonly applied Gaussian regularization of the particle momentum source is a poor approximation of the spatial distribution of the particle momentum source, but for larger filter widths the spatial distribution approaches a Gaussian. Furthermore, we propose a modified advective term in the volume-filtered momentum equation that consistently circumvents the common stability issues observed at locally small fluid volume fractions and identify inconsistencies in previous studies of the phase-averaged kinetic energy of the volume-filtered fluid velocity. Finally, we propose a generally applicable form of the volume-filtered momentum equation and its closures based on clear and well-founded assumptions and propose guidelines for point-particle simulations based on the new findings.
Published: 2024

20. Discovery of isoquinoline sulfonamides as allosteric gyrase inhibitors with activity against fluoroquinolone-resistant bacteria

Author: Bakker, Alexander T., Kotsogianni, Ioli, Avalos, Mariana, Punt, Jeroen M., Liu, Bing, Piermarini, Diana, Gagestein, Berend, Slingerland, Cornelis J., Zhang, Le, Willemse, Joost J., Ghimire, Leela B., van den Berg, Richard J. H. B. N., Janssen, Antonius P. A., Ottenhoff, Tom H. M., van Boeckel, Constant A. A., van Wezel, Gilles P., Ghilarov, Dmitry, Martin, Nathaniel I., and van der Stelt, Mario
Published: 2024
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21. Predictors of adherence to exercise interventions in people with schizophrenia

Author: Schwaiger, Rebecca, Maurus, Isabel, Lembeck, Moritz, Papazova, Irina, Greska, David, Muenz, Susanne, Sykorova, Eliska, Thieme, Cristina E., Vogel, Bob O., Mohnke, Sebastian, Huppertz, Charlotte, Roeh, Astrid, Keller-Varady, Katriona, Malchow, Berend, Walter, Henrik, Wolfarth, Bernd, Wölwer, Wolfgang, Henkel, Karsten, Hirjak, Dusan, Schmitt, Andrea, Hasan, Alkomiet, Meyer-Lindenberg, Andreas, Falkai, Peter, and Roell, Lukas
Published: 2024
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22. Effect of present state bias on minimal important change estimates: a simulation study

Author: Terluin, Berend, Fromy, Piper, Trigg, Andrew, Terwee, Caroline B., and Bjorner, Jakob B.
Published: 2024
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23. Standardizing designed and emergent quantitative features in microphysiological systems

Author: Nahon, Dennis M., Moerkens, Renée, Aydogmus, Hande, Lendemeijer, Bas, Martínez-Silgado, Adriana, Stein, Jeroen M., Dostanić, Milica, Frimat, Jean-Philippe, Gontan, Cristina, de Graaf, Mees N. S., Hu, Michel, Kasi, Dhanesh G., Koch, Lena S., Le, Kieu T. T., Lim, Sangho, Middelkamp, Heleen H. T., Mooiweer, Joram, Motreuil-Ragot, Paul, Niggl, Eva, Pleguezuelos-Manzano, Cayetano, Puschhof, Jens, Revyn, Nele, Rivera-Arbelaez, José M., Slager, Jelle, Windt, Laura M., Zakharova, Mariia, van Meer, Berend J., Orlova, Valeria V., de Vrij, Femke M. S., Withoff, Sebo, Mastrangeli, Massimo, van der Meer, Andries D., and Mummery, Christine L.
Published: 2024
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24. Process Chain for Condition-Based Regeneration

Author: Nuebel, Nicolas, Seume, Joerg R., Denkena, Berend, Seume, Joerg R., editor, Denkena, Berend, editor, and Gilge, Philipp, editor
Published: 2025
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25. Simulation-Based Process Design of Recontouring Technologies

Author: Böß, Volker, Denkena, Berend, Friebe, Sven, Hein, Markus, Seume, Joerg R., editor, Denkena, Berend, editor, and Gilge, Philipp, editor
Published: 2025
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26. Dexterous Regeneration Cell

Author: Denkena, Berend, Schumacher, Tim, Hein, Markus, Seume, Joerg R., editor, Denkena, Berend, editor, and Gilge, Philipp, editor
Published: 2025
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27. Simulating interfacial flows: a farewell to planes

Author: Evrard, Fabien, Chiodi, Robert, van Wachem, Berend, and Desjardins, Olivier
Subjects: Physics - Computational Physics, Physics - Fluid Dynamics
Abstract: Over the past decades, the volume-of-fluid (VOF) method has been the method of choice for simulating atomization processes, owing to its unique ability to discretely conserve mass. Current state-of-the-art VOF methods, however, rely on the piecewise-linear interface calculation (PLIC) to represent the interface used when calculating advection fluxes. This renders the estimated curvature of the transported interface zeroth-order accurate at best, adversely impacting the simulation of surface-tension-driven flows. In the past few years, there have been several attempts at using piecewise-parabolic interface approximations instead of piecewise-linear ones for computing advection fluxes, albeit all limited to two-dimensional cases or not inherently mass conservative. In this contribution, we present our most recent work on three-dimensional piecewise-parabolic interface reconstruction and apply it in the context of the VOF method. As a result of increasing the order of the interface representation, the reconstruction of the interface and the estimation of its curvature now become a single step instead of two separate ones. The performance of this new approach is assessed both in terms of accuracy and stability and compared to the classical PLIC-VOF approach on a range of canonical test-cases and cases of surface-tension-driven instabilities.
Published: 2024

28. Seg-metrics: a Python package to compute segmentation metrics

Author: Jia, Jingnan, Staring, Marius, and Stoel, Berend C.
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: In response to a concerning trend of selectively emphasizing metrics in medical image segmentation (MIS) studies, we introduce \texttt{seg-metrics}, an open-source Python package for standardized MIS model evaluation. Unlike existing packages, \texttt{seg-metrics} offers user-friendly interfaces for various overlap-based and distance-based metrics, providing a comprehensive solution. \texttt{seg-metrics} supports multiple file formats and is easily installable through the Python Package Index (PyPI). With a focus on speed and convenience, \texttt{seg-metrics} stands as a valuable tool for efficient MIS model assessment.
Published: 2024

29. A novel class of functionals for perturbative algebraic quantum field theory

Author: Hawkins, Eli, Rejzner, Kasia, and Visser, Berend
Subjects: Mathematical Physics, 81T20
Abstract: Perturbative Algebraic Quantum Field Theory (pAQFT) is based upon formal power series valued in spaces of functionals. This is usually done with microcausal functionals, which are defined using microlocal analysis and motivated by propagation of singularities. In this paper, we prove that the class of microcausal functionals is not closed under the Peierls (Poisson) bracket by showing that a Peierls bracket of regular functionals can fail to be smooth. Consequently, microcausal functionals are not a suitable basis for pAQFT. To remedy these issues, we introduce the class of equicausal functionals. We show that this class contains the local functionals and that it closes under the star-product and Peierls bracket. Furthermore, we prove the time-slice axiom for equicausal functionals, using a chain homotopy. The class of microcausal functionals is not closed under this chain homotopy, which strongly suggests that the class of microcausal functionals does not fulfill the time slice axiom., Comment: 45 pages, 2 figures, submitted to Communications in Mathematical Physics
Published: 2023

30. On the zeros of odd weight Eisenstein series

Author: van Ittersum, Jan-Willem and Ringeling, Berend
Subjects: Mathematics - Number Theory
Abstract: We count the number of zeros of the holomorphic odd weight Eisenstein series in all $\mathrm{SL}_2(\mathbb{Z})$-translates of the standard fundamental domain., Comment: 22 pages, 2 figures, 2 tables
Published: 2023

31. Future-proof ship pipe routing: navigating the energy transition

Author: Markhorst, Berend, Berkhout, Joost, Zocca, Alessandro, Pruyn, Jeroen, and van der Mei, Rob
Subjects: Mathematics - Optimization and Control
Abstract: The maritime industry must prepare for the energy transition from fossil fuels to sustainable alternatives. Making ships future-proof is necessary given their long lifetime, but it is also complex because the future fuel type is uncertain. Within this uncertainty, one typically overlooks pipe routing, although it is a crucial driver for design time and costs. Therefore, we propose a mathematical approach for modeling uncertainty in pipe routing with deterministic, stochastic, and robust optimization. All three models are based on state-of-the-art integer linear optimization models for the Stochastic Steiner Forest Problem and adjusted to the maritime domain using specific constraints for pipe routing. We compare the models using both artificial and realistic instances and show that considering uncertainty using stochastic optimization and robust optimization leads to cost reductions of up to 22% in our experiments.
Published: 2023

32. Modelling the influence of tool wear on shape errors in milling using a hybrid soft-sensor

Author: Denkena, Berend, Wichmann, Marcel, Rokicki, Markus, and Stürenburg, Lukas
Published: 2024
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33. New smart twisting active rotor (STAR): pretest predictions

Author: van der Wall, Berend G., Lim, Joon W., Riemenschneider, Johannes, Kalow, Steffen, Wilke, Gunther A., Boyd, Jr., D. Douglas, Bailly, Joelle, Delrieux, Yves, Cafarelli, Italo, Tanabe, Yasutada, Sugawara, Hideaki, Jung, Sung N., Hong, Seong H., Kim, Do-Hyung, Kang, Hee J., Barakos, George, and Steininger, Rinaldo
Published: 2024
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34. Influence of grain concentrations gradients on the profiling behaviour of bronze bonded diamond grinding wheels

Author: Denkena, Berend, Bergmann, Benjamin, Raffalt, Daniel, and Tontsch, Maximilian
Published: 2024
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35. Effects of CSR-Related Media Coverage on Corporate Reputation

Author: Ennenbach, Sabrina and Barkela, Berend
Published: 2024
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36. A prognostic neural epigenetic signature in high-grade glioma

Author: Drexler, Richard, Khatri, Robin, Sauvigny, Thomas, Mohme, Malte, Maire, Cecile L., Ryba, Alice, Zghaibeh, Yahya, Dührsen, Lasse, Salviano-Silva, Amanda, Lamszus, Katrin, Westphal, Manfred, Gempt, Jens, Wefers, Annika K., Neumann, Julia E., Bode, Helena, Hausmann, Fabian, Huber, Tobias B., Bonn, Stefan, Jütten, Kerstin, Delev, Daniel, Weber, Katharina J., Harter, Patrick N., Onken, Julia, Vajkoczy, Peter, Capper, David, Wiestler, Benedikt, Weller, Michael, Snijder, Berend, Buck, Alicia, Weiss, Tobias, Göller, Pauline C., Sahm, Felix, Menstel, Joelle Aline, Zimmer, David Niklas, Keough, Michael B., Ni, Lijun, Monje, Michelle, Silverbush, Dana, Hovestadt, Volker, Suvà, Mario L., Krishna, Saritha, Hervey-Jumper, Shawn L., Schüller, Ulrich, Heiland, Dieter H., Hänzelmann, Sonja, and Ricklefs, Franz L.
Published: 2024
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37. Clinical Outcomes of Integrase Strand Transfer Inhibitors Containing Antiretroviral Therapy in HIV-2: A Narrative Review

Author: Boschloo, Wendy J. and van Welzen, Berend J.
Published: 2024
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38. Nephropathie bei Diabetes

Author: Merker, Ludwig, Ebert, Thomas, Schleicher, Erwin, Guthoff, Martina, and Isermann, Berend
Published: 2024
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39. A novel process chain for the automated repair of leading edges in aircraft engines

Author: Kenneweg, Robert, Heide, Klaas Maximilian, Böß, Volker, Denkena, Berend, and Westermann, Hans-Henrik
Published: 2024
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40. Underlying Neural Mechanisms of Cognitive Improvement in Fronto-striatal Response Inhibition in People Living with HIV Switching Off Efavirenz: A Randomized Controlled BOLD fMRI Trial

Author: Oomen, Patrick G. A., Hakkers, Charlotte S., Arends, Joop E., van der Berk, Guido E. L., Pas, Pascal, Hoepelman, Andy I. M., van Welzen, Berend J., and du Plessis, Stefan
Published: 2024
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41. Experimental and numerical investigation to elucidate the fluid flow through packed beds with structured particle packings

Author: Patil, Shirin, Gorges, Christian, López-Bonilla, Joel, Stelter, Moritz, Beyrau, Frank, and van Wachem, Berend
Subjects: Physics - Fluid Dynamics
Abstract: The present paper presents an experimental and numerical investigation of the dispersion of the gaseous jet flow and co-flow for the simple unit cell (SUC) and body centered cubic (BCC) configuration of particles in packed beds. The experimental setup is built in such a way, that suitable and simplified boundary conditions are imposed for the corresponding numerical framework. The SUC and BCC particle beds consist of 3D-printed spheres. The flow velocities are analysed directly at the exit of the particle bed, for both beds for particle Reynolds numbers of 200, 300, and 400. Stereo particle image velocimetry (SPIV) is experimentally arranged in such a way, that the velocities over the entire region at the exit of the packed bed are obtained instantaneously. The numerical method consists of a state-of-the-art IBM with AMR. The paper presents the pore jet structure and velocity field exiting each pore for the SUC and BCC packed particle beds. The numerical and experimental studies show a good agreement for the SUC configuration for all flow velocities. For the BCC configuration, some differences can be observed in the pore jet flow structure between the simulations and the experiments, but the general flow velocity distribution shows a good overall agreement. The axial velocity is generally higher for the pores located near the centre of the packed bed than for the pores near the wall. In addition, the axial velocities are observed to increase near the peripheral pores of the packed bed. This behaviour is predominant for the BCC configuration as compared to the SUC configuration. It is shown that both the experiments and the simulations can be used to study the complex fluid structures inside a packed bed reactor.
Published: 2023
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42. A Diffusion-Model of Joint Interactive Navigation

Author: Niedoba, Matthew, Lavington, Jonathan Wilder, Liu, Yunpeng, Lioutas, Vasileios, Sefas, Justice, Liang, Xiaoxuan, Green, Dylan, Dabiri, Setareh, Zwartsenberg, Berend, Scibior, Adam, and Wood, Frank
Subjects: Computer Science - Machine Learning, Computer Science - Robotics
Abstract: Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in simulation ensures realism but the rarity of safety critical events makes large scale collection of driving scenarios expensive. In this paper, we present DJINN - a diffusion based method of generating traffic scenarios. Our approach jointly diffuses the trajectories of all agents, conditioned on a flexible set of state observations from the past, present, or future. On popular trajectory forecasting datasets, we report state of the art performance on joint trajectory metrics. In addition, we demonstrate how DJINN flexibly enables direct test-time sampling from a variety of valuable conditional distributions including goal-based sampling, behavior-class sampling, and scenario editing., Comment: 10 pages, 4 figures. Accepted to NeurIPS 2023
Published: 2023

43. Discovery of interlayer plasmon polaron in graphene/WS$_2$ heterostructures

Author: Ulstrup, Søren, Veld, Yann in 't, Miwa, Jill A., Jones, Alfred J. H., McCreary, Kathleen M., Robinson, Jeremy T., Jonker, Berend T., Singh, Simranjeet, Koch, Roland J., Rotenberg, Eli, Bostwick, Aaron, Jozwiak, Chris, Rösner, Malte, and Katoch, Jyoti
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract: Harnessing electronic excitations involving coherent coupling to bosonic modes is essential for the design and control of emergent phenomena in quantum materials [1]. In situations where charge carriers induce a lattice distortion due to the electron-phonon interaction, the conducting states get "dressed". This leads to the formation of polaronic quasiparticles that dramatically impact charge transport, surface reactivity, thermoelectric and optical properties, as observed in a variety of crystals and interfaces composed of polar materials [2-6]. Similarly, when oscillations of the charge density couple to conduction electrons the more elusive plasmon polaron emerges [7], which has been detected in electron-doped semiconductors [8-10]. However, the exploration of polaronic effects on low energy excitations is still in its infancy in two-dimensional (2D) materials. Here, we present the discovery of an interlayer plasmon polaron in heterostructures composed of graphene on top of SL WS$_2$. By using micro-focused angle-resolved photoemission spectroscopy (microARPES) during in situ doping of the top graphene layer, we observe a strong quasiparticle peak accompanied by several carrier density-dependent shake-off replicas around the SL WS$_2$ conduction band minimum (CBM). Our results are explained by an effective many-body model in terms of a coupling between SL WS$_2$ conduction electrons and graphene plasmon modes. It is important to take into account the presence of such interlayer collective modes, as they have profound consequences for the electronic and optical properties of heterostructures that are routinely explored in many device architectures involving 2D transition metal dichalcogenides (TMDs) [11-15]., Comment: 25 pages, 9 figures including Supporting Information
Published: 2023

44. Microstructure-based prediction of hydrodynamic forces in stationary particle assemblies

Author: van Wachem, Berend, Elmestikawy, Hani, and Chéron, Victor
Subjects: Physics - Fluid Dynamics, Physics - Computational Physics
Abstract: In the work, we derive novel hydrodynamic force models to describe the interaction of a flow with particles in an assembly when only an averaged resolution of the flow is available. These force models are able to predict the average drag on the particle assembly, as well as the deviations from the average drag force and the lift force for each individual particle in the assembly. To achieve this, PR-DNS of various particle assemblies and flow regimes are carried out, varying the particle volume fraction up to 0.6, and the mean particle flow Reynolds number up to 300. To characterize the structure of the particles in the assembly, a Voronoi tessellation is carried out, and a number of scalars, vectors and tensors are defined based upon this tessellation. The microstructure informed hydrodynamic force models are based on symbolic regressions of these quantities derived from the Voronoi tessellation, the global particle volume fraction of the particle assembly and the flow regime represented by the Reynolds number, and the forces on the individual particles in the assembly. The resulting hydrodynamic force models are single expressions can be directly employed in a Lagrangian particle tracking (LPT) or computational fluid dynamics/discrete element model (CFD/DEM) framework. By comparing the results of the newly proposed hydrodynamic force models with an averaged force model, as is usually adopted in Lagrangian particle tracking simulations, we show that a significant increase in accuracy can be achieved, without significantly increasing the cost of the simulation.
Published: 2023
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45. Layer-wise Feedback Propagation

Author: Weber, Leander, Berend, Jim, Binder, Alexander, Wiegand, Thomas, Samek, Wojciech, and Lapuschkin, Sebastian
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, 68T05
Abstract: In this paper, we present Layer-wise Feedback Propagation (LFP), a novel training approach for neural-network-like predictors that utilizes explainability, specifically Layer-wise Relevance Propagation(LRP), to assign rewards to individual connections based on their respective contributions to solving a given task. This differs from traditional gradient descent, which updates parameters towards anestimated loss minimum. LFP distributes a reward signal throughout the model without the need for gradient computations. It then strengthens structures that receive positive feedback while reducingthe influence of structures that receive negative feedback. We establish the convergence of LFP theoretically and empirically, and demonstrate its effectiveness in achieving comparable performance to gradient descent on various models and datasets. Notably, LFP overcomes certain limitations associated with gradient-based methods, such as reliance on meaningful derivatives. We further investigate how the different LRP-rules can be extended to LFP, what their effects are on training, as well as potential applications, such as training models with no meaningful derivatives, e.g., step-function activated Spiking Neural Networks (SNNs), or for transfer learning, to efficiently utilize existing knowledge.
Published: 2023

46. Nature of the current-induced insulator-to-metal transition in Ca$_2$RuO$_4$ as revealed by transport-ARPES

Author: Suen, Cissy T, Marković, Igor, Zonno, Marta, Heinsdorf, Niclas, Zhdanovich, Sergey, Jo, Na-Hyun, Schmid, Michael, Hansmann, Philipp, Puphal, Pascal, Fürsich, Katrin, Zimmerman, Valentin, Smit, Steef, Au-Yeung, Christine, Zwartsenberg, Berend, Krautloher, Maximilian, Elfimov, Ilya S, Koch, Roland, Gorovikov, Sergey, Jozwiak, Chris, Bostwick, Aaron, Franz, Marcel, Rotenberg, Eli, Keimer, Bernhard, and Damascelli, Andrea
Subjects: Condensed Matter - Strongly Correlated Electrons
Abstract: The Mott insulator Ca$_2$RuO$_4$ exhibits a rare insulator-to-metal transition (IMT) induced by DC current. While structural changes associated with this transition have been tracked by neutron diffraction, Raman scattering, and x-ray spectroscopy, work on elucidating the response of the electronic degrees of freedom is still in progress. Here we unveil the current-induced modifications of the electronic states of Ca$_2$RuO$_4$ by employing angle-resolved photoemission spectroscopy (ARPES) in conjunction with four-probe transport. Two main effects emerge: a clear reduction of the Mott gap and a modification in the dispersion of the Ru-bands. The changes in dispersion occur exclusively along the $XM$ high-symmetry direction, parallel to the $b$-axis where the greatest in-plane lattice change occurs. These experimental observations, together with dynamical mean-field theory (DMFT) calculations simulated from the current-induced structural distortions, indicate the intimate interplay of lattice and orbital-dependent electronic response in the current-driven IMT. Furthermore, based on a free energy analysis, we demonstrate that the current-induced phase, albeit thermodynamically equivalent, is electronically distinct from the high-temperature zero-current metallic phase. Our results provide insight into the elusive nature of the current-induced IMT of Ca$_2$RuO$_4$ and advance the challenging, yet powerful, technique of transport-ARPES., Comment: 10 pages, 5 figures
Published: 2023
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47. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements.

Author: Scholz, Markus, Horn, Katrin, Pott, Janne, Wuttke, Matthias, Kühnapfel, Andreas, Nasr, M, Kirsten, Holger, Li, Yong, Hoppmann, Anselm, Gorski, Mathias, Ghasemi, Sahar, Li, Man, Tin, Adrienne, Chai, Jin-Fang, Cocca, Massimiliano, Wang, Judy, Nutile, Teresa, Akiyama, Masato, Åsvold, Bjørn, Bansal, Nisha, Biggs, Mary, Boutin, Thibaud, Brenner, Hermann, Brumpton, Ben, Burkhardt, Ralph, Cai, Jianwen, Campbell, Archie, Campbell, Harry, Chalmers, John, Chasman, Daniel, Chee, Miao, Chen, Xu, Cheng, Ching-Yu, Cifkova, Renata, Daviglus, Martha, Delgado, Graciela, Dittrich, Katalin, Edwards, Todd, Endlich, Karlhans, Michael Gaziano, J, Giri, Ayush, Giulianini, Franco, Gordon, Scott, Gudbjartsson, Daniel, Hallan, Stein, Hamet, Pavel, Hartman, Catharina, Hayward, Caroline, Heid, Iris, Hellwege, Jacklyn, Holleczek, Bernd, Holm, Hilma, Hutri-Kähönen, Nina, Hveem, Kristian, Isermann, Berend, Jonas, Jost, Joshi, Peter, Kamatani, Yoichiro, Kanai, Masahiro, Kastarinen, Mika, Khor, Chiea, Kiess, Wieland, Kleber, Marcus, Körner, Antje, Kovacs, Peter, Krajcoviechova, Alena, Kramer, Holly, Krämer, Bernhard, Kuokkanen, Mikko, Kähönen, Mika, Lange, Leslie, Lash, James, Lehtimäki, Terho, Li, Hengtong, Lin, Bridget, Liu, Jianjun, Loeffler, Markus, Lyytikäinen, Leo-Pekka, Magnusson, Patrik, Martin, Nicholas, Matsuda, Koichi, Milaneschi, Yuri, Mishra, Pashupati, Mononen, Nina, Montgomery, Grant, Mook-Kanamori, Dennis, Mychaleckyj, Josyf, März, Winfried, Nauck, Matthias, Nikus, Kjell, Nolte, Ilja, Noordam, Raymond, Okada, Yukinori, Olafsson, Isleifur, Oldehinkel, Albertine, Penninx, Brenda, Perola, Markus, Pirastu, Nicola, and Polasek, Ozren
Subjects: Humans, Male, Female, Androgens, Genome-Wide Association Study, Kidney, Chromosomes, Human, X, Response Elements, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Tetraspanins
Abstract: X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.
Published: 2024

48. Observation of interlayer plasmon polaron in graphene/WS2 heterostructures

Author: Ulstrup, Søren, in ’t Veld, Yann, Miwa, Jill A, Jones, Alfred JH, McCreary, Kathleen M, Robinson, Jeremy T, Jonker, Berend T, Singh, Simranjeet, Koch, Roland J, Rotenberg, Eli, Bostwick, Aaron, Jozwiak, Chris, Rösner, Malte, and Katoch, Jyoti
Subjects: Quantum Physics, Physical Sciences, Condensed Matter Physics
Abstract: Harnessing electronic excitations involving coherent coupling to bosonic modes is essential for the design and control of emergent phenomena in quantum materials. In situations where charge carriers induce a lattice distortion due to the electron-phonon interaction, the conducting states get "dressed", which leads to the formation of polaronic quasiparticles. The exploration of polaronic effects on low-energy excitations is in its infancy in two-dimensional materials. Here, we present the discovery of an interlayer plasmon polaron in heterostructures composed of graphene on top of single-layer WS2. By using micro-focused angle-resolved photoemission spectroscopy during in situ doping of the top graphene layer, we observe a strong quasiparticle peak accompanied by several carrier density-dependent shake-off replicas around the single-layer WS2 conduction band minimum. Our results are explained by an effective many-body model in terms of a coupling between single-layer WS2 conduction electrons and an interlayer plasmon mode. It is important to take into account the presence of such interlayer collective modes, as they have profound consequences for the electronic and optical properties of heterostructures that are routinely explored in many device architectures involving 2D transition metal dichalcogenides.
Published: 2024

49. Precise test of lepton flavour universality in Wpps=13TeV-boson decays into muons and electrons in Wpps=13TeV collisions at Wpps=13TeV with the ATLAS detector

Author: Aad, G., Aakvaag, E., Abbott, B., Abdelhameed, S., Abeling, K., Abicht, N. J., Abidi, S. H., Aboelela, M., Aboulhorma, A., Abramowicz, H., Abreu, H., Abulaiti, Y., Acharya, B. S., Ackermann, A., Bourdarios, C. Adam, Adamczyk, L., Addepalli, S. V., Addison, M. J., Adelman, J., Adiguzel, A., Adye, T., Affolder, A. A., Afik, Y., Agaras, M. N., Agarwala, J., Aggarwal, A., Agheorghiesei, C., Ahmad, A., Ahmadov, F., Ahmed, W. S., Ahuja, S., Ai, X., Aielli, G., Aikot, A., Tamlihat, M. Ait, Aitbenchikh, B., Akbiyik, M., Åkesson, T. P. A., Akimov, A. V., Akiyama, D., Akolkar, N. N., Aktas, S., Khoury, K. Al, Alberghi, G. L., Albert, J., Albicocco, P., Albouy, G. L., Alderweireldt, S., Alegria, Z. L., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexopoulos, T., Alfonsi, F., Algren, M., Alhroob, M., Ali, B., Ali, H. M. J., Ali, S., Alibocus, S. W., Aliev, M., Alimonti, G., Alkakhi, W., Allaire, C., Allbrooke, B. M. M., Allen, J. F., Flores, C. A. Allendes, Allport, P. P., Aloisio, A., Alonso, F., Alpigiani, C., Alsolami, Z. M. K., Estevez, M. Alvarez, Fernandez, A. Alvarez, Cardoso, M. Alves, Alviggi, M. G., Aly, M., Coutinho, Y. Amaral, Ambler, A., Amelung, C., Amerl, M., Ames, C. G., Amidei, D., Amirie, K. J., Santos, S. P. Amor Dos, Amos, K. R., An, S., Ananiev, V., Anastopoulos, C., Andeen, T., Anders, J. K., Andrean, S. Y., Andreazza, A., Angelidakis, S., Angerami, A., Anisenkov, A. V., Annovi, A., Antel, C., Antipov, E., Antonelli, M., Anulli, F., Aoki, M., Aoki, T., Aparo, M. A., Bella, L. Aperio, Appelt, C., Apyan, A., Val, S. J. Arbiol, Arcangeletti, C., Arce, A. T. H., Arena, E., Arguin, J.-F., Argyropoulos, S., Arling, J.-H., Arnaez, O., Arnold, H., Artoni, G., Asada, H., Asai, K., Asai, S., Asbah, N. A., Ashby Pickering, R. A., Assamagan, K., Astalos, R., Astrand, K. S. V., Atashi, S., Atkin, R. J., Atkinson, M., Atmani, H., Atmasiddha, P. A., Augsten, K., Auricchio, S., Auriol, A. D., Austrup, V. A., Avolio, G., Axiotis, K., Azuelos, G., Babal, D., Bachacou, H., Bachas, K., Bachiu, A., Backman, F., Badea, A., Baer, T. M., Bagnaia, P., Bahmani, M., Bahner, D., Bai, K., Baines, J. T., Baines, L., Baker, O. K., Bakos, E., Gupta, D. Bakshi, Balakrishnan, V., Balasubramanian, R., Baldin, E. M., Balek, P., Ballabene, E., Balli, F., Baltes, L. M., Balunas, W. K., Balz, J., Bamwidhi, I., Banas, E., Bandieramonte, M., Bandyopadhyay, A., Bansal, S., Barak, L., Barakat, M., Barberio, E. L., Barberis, D., Barbero, M., Barel, M. Z., Barends, K. N., Barillari, T., Barisits, M.-S., Barklow, T., Baron, P., Moreno, D. A. Baron, Baroncelli, A., Barone, G., Barr, A. J., Barr, J. D., Barreiro, F., da Costa, J. Barreiro Guimarães, Barron, U., Teixeira, M. G. Barros, Barsov, S., Bartels, F., Bartoldus, R., Barton, A. E., Bartos, P., Basan, A., Baselga, M., Bassalat, A., Basso, M. J., Bate, R., Bates, R. L., Batlamous, S., Batool, B., Battaglia, M., Battulga, D., Bauce, M., Bauer, M., Bauer, P., Hurrell, L. T. Bazzano, Beacham, J. B., Beau, T., Beaucamp, J. Y., Beauchemin, P. H., Bechtle, P., Beck, H. P., Becker, K., Beddall, A. J., Bednyakov, V. A., Bee, C. P., Beemster, L. J., Beermann, T. A., Begalli, M., Begel, M., Behera, A., Behr, J. K., Beirer, J. F., Beisiegel, F., Belfkir, M., Bella, G., Bellagamba, L., Bellerive, A., Bellos, P., Beloborodov, K., Benchekroun, D., Bendebba, F., Benhammou, Y., Benkendorfer, K. C., Beresford, L., Beretta, M., Kuutmann, E. Bergeaas, Berger, N., Bergmann, B., Beringer, J., Bernardi, G., Bernius, C., Bernlochner, F. U., Bernon, F., Guardia, A. Berrocal, Berry, T., Berta, P., Berthold, A., Bethke, S., Betti, A., Bevan, A. J., Bhalla, N. K., Bhatta, S., Bhattacharya, D. S., Bhattarai, P., Bhide, K. D., Bhopatkar, V. S., Bianchi, R. M., Bianco, G., Biebel, O., Bielski, R., Biglietti, M., Billingsley, C. S., Bindi, M., Bingul, A., Bini, C., Biondini, A., Bird, G. A., Birman, M., Biros, M., Biryukov, S., Bisanz, T., Bisceglie, E., Biswal, J. P., Biswas, D., Bloch, I., Blue, A., Blumenschein, U., Blumenthal, J., Bobrovnikov, V. S., Boehler, M., Boehm, B., Bogavac, D., Bogdanchikov, A. G., Bohm, C., Boisvert, V., Bokan, P., Bold, T., Bomben, M., Bona, M., Boonekamp, M., Booth, C. D., Borbély, A. G., Bordulev, I. S., Borecka-Bielska, H. M., Borissov, G., Bortoletto, D., Boscherini, D., Bosman, M., Sola, J. D. Bossio, Bouaouda, K., Bouchhar, N., Boudet, L., Boudreau, J., Bouhova-Thacker, E. V., Boumediene, D., Bouquet, R., Boveia, A., Boyd, J., Boye, D., Boyko, I. R., Bozianu, L., Bracinik, J., Brahimi, N., Brandt, G., Brandt, O., Braren, F., Brau, B., Brau, J. E., Brener, R., Brenner, L., Brenner, R., Bressler, S., Britton, D., Britzger, D., Brock, I., Brock, R., Brooijmans, G., Brost, E., Brown, L. M., Bruce, L. E., Bruckler, T. L., de Renstrom, P. A. Bruckman, Brüers, B., Bruni, A., Bruni, G., Bruschi, M., Bruscino, N., Buanes, T., Buat, Q., Buchin, D., Buckley, A. G., Bulekov, O., Bullard, B. A., Burdin, S., Burgard, C. D., Burger, A. M., Burghgrave, B., Burlayenko, O., Burr, J. T. P., Burzynski, J. C., Busch, E. L., Büscher, V., Bussey, P. J., Butler, J. M., Buttar, C. M., Butterworth, J. M., Buttinger, W., Vazquez, C. J. Buxo, Buzykaev, A. R., Urbán, S. Cabrera, Cadamuro, L., Caforio, D., Cai, H., Cai, Y., Cai, Y., Cairo, V. M. M., Cakir, O., Calace, N., Calafiura, P., Calderini, G., Calfayan, P., Callea, G., Caloba, L. P., Calvet, D., Calvet, S., Calvetti, M., Toro, R. Camacho, Camarda, S., Munoz, D. Camarero, Camarri, P., Camerlingo, M. T., Cameron, D., Camincher, C., Campanelli, M., Camplani, A., Canale, V., Canbay, A. C., Canonero, E., Cantero, J., Cao, Y., Capocasa, F., Capua, M., Carbone, A., Cardarelli, R., Cardenas, J. C. J., Carducci, G., Carli, T., Carlino, G., Carlotto, J. I., Carlson, B. T., Carlson, E. 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Published: 2024
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50. Measurements of the production cross-section for a Z boson in association with b- or c-jets in proton–proton collisions at s=13 TeV with the ATLAS detector

Author: Aad, G., Aakvaag, E., Abbott, B., Abdelhameed, S., Abeling, K., Abicht, N. J., Abidi, S. H., Aboelela, M., Aboulhorma, A., Abramowicz, H., Abreu, H., Abulaiti, Y., Acharya, B. S., Ackermann, A., Bourdarios, C. Adam, Adamczyk, L., Addepalli, S. V., Addison, M. J., Adelman, J., Adiguzel, A., Adye, T., Affolder, A. A., Afik, Y., Agaras, M. N., Agarwala, J., Aggarwal, A., Agheorghiesei, C., Ahmad, A., Ahmadov, F., Ahmed, W. S., Ahuja, S., Ai, X., Aielli, G., Aikot, A., Tamlihat, M. Ait, Aitbenchikh, B., Akbiyik, M., Åkesson, T. P. A., Akimov, A. V., Akiyama, D., Akolkar, N. N., Aktas, S., Khoury, K. Al, Alberghi, G. L., Albert, J., Albicocco, P., Albouy, G. L., Alderweireldt, S., Alegria, Z. L., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexopoulos, T., Alfonsi, F., Algren, M., Alhroob, M., Ali, B., Ali, H. M. J., Ali, S., Alibocus, S. W., Aliev, M., Alimonti, G., Alkakhi, W., Allaire, C., Allbrooke, B. M. M., Allen, J. F., Flores, C. A. Allendes, Allport, P. P., Aloisio, A., Alonso, F., Alpigiani, C., Alsolami, Z. M. K., Estevez, M. Alvarez, Fernandez, A. Alvarez, Cardoso, M. Alves, Alviggi, M. G., Aly, M., Coutinho, Y. Amaral, Ambler, A., Amelung, C., Amerl, M., Ames, C. G., Amidei, D., Amirie, K. J., Santos, S. P. Amor Dos, Amos, K. R., An, S., Ananiev, V., Anastopoulos, C., Andeen, T., Anders, J. K., Andrean, S. Y., Andreazza, A., Angelidakis, S., Angerami, A., Anisenkov, A. V., Annovi, A., Antel, C., Antipov, E., Antonelli, M., Anulli, F., Aoki, M., Aoki, T., Aparo, M. A., Bella, L. Aperio, Appelt, C., Apyan, A., Val, S. J. Arbiol, Arcangeletti, C., Arce, A. T. H., Arena, E., Arguin, J-F., Argyropoulos, S., Arling, J.-H., Arnaez, O., Arnold, H., Artoni, G., Asada, H., Asai, K., Asai, S., Asbah, N. A., Pickering, R. A. Ashby, Assamagan, K., Astalos, R., Astrand, K. S. V., Atashi, S., Atkin, R. J., Atkinson, M., Atmani, H., Atmasiddha, P. A., Augsten, K., Auricchio, S., Auriol, A. D., Austrup, V. 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Published: 2024
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