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Curl Constraint-Preserving Reconstruction and the Guidance it Gives for Mimetic Scheme Design

Communications on Applied Mathematics and Computation 2023年第1期5卷 235-294页

作者： Dinshaw S.Balsara Roger Käppeli Walter Boscheri Michael Dumbser Physics and ACMS Departments University of Notre DameNotre DameINUSA Seminar for Applied Mathematics(SAM) Department of MathematicsETH ZürichCH-8092 ZurichSwitzerland Department of Mathematics and Computer Science University of FerraraFerraraItaly Laboratory of Applied Mathematics Department of CivilEnvironmental and Mechanical EngineeringUniversity of TrentoTrentoItaly

Several important PDE systems,like magnetohydrodynamics and computational electrodynamics,are known to support involutions where the divergence of a vector field evolves in divergence-free or divergence constraint-preserving ***,new classes of PDE systems have emerged for hyperelasticity,compressible multiphase flows,so-called firstorder reductions of the Einstein field equations,or a novel first-order hyperbolic reformulation of Schrödinger’s equation,to name a few,where the involution in the PDE supports curl-free or curl constraint-preserving evolution of a vector *** study the problem of curl constraint-preserving reconstruction as it pertains to the design of mimetic finite volume(FV)WENO-like schemes for PDEs that support a curl-preserving involution.(Some insights into discontinuous Galerkin(DG)schemes are also drawn,though that is not the prime focus of this paper.)This is done for two-and three-dimensional structured mesh problems where we deliver closed form expressions for the *** importance of multidimensional Riemann solvers in facilitating the design of such schemes is also *** two dimensions,a von Neumann analysis of structure-preserving WENOlike schemes that mimetically satisfy the curl constraints,is also *** shows the tremendous value of higher order WENO-like schemes in minimizing dissipation and dispersion for this class of *** results are also presented to show that the edge-centered curl-preserving(ECCP)schemes meet their design *** paper is the first paper that invents non-linearly hybridized curl-preserving reconstruction and integrates it with higher order Godunov *** its very design,this paper is,therefore,intended to be forward-looking and to set the stage for future work on curl involution-constrained PDEs.

关键词： PDEs Numerical schemes Mimetic

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A Data-driven Exploration and Prediction of Deep Brain Stimulation Effects on Gait in Parkinson's Disease

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IEEE Journal of Biomedical and Health Informatics 2024年 PP卷 1-13页

作者： Amprimo, Gianluca Mei, Zhongke Ferraris, Claudia Olmo, Gabriella Ravi, Deepak K. Department of Control and Computer engineering Politecnico di Torino Torino Italy Laboratory for Movement Biomechanics ETH Zürich Zurich Switzerland CNR-IEIIT Torino Italy

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an established treatment for motor impairment due to Parkinson's disease (PD) progression. While treated subjects mostly experience significant amelioration of symptoms, some still report adverse effects. In particular, changes in gait patterns due to the electrical stimulation have shown mixed results across studies, with overall gait velocity improvement described as the core positive outcome. This retrospective study investigates changes in the gait parameters of 50 PD patients before and 6 months after STN-DBS, by exploiting a purely data-driven approach. First, unsupervised learning identifies clusters of subjects with similar variations in the gait parameters after STN-DBS. This analysis highlights two dominant clusters (Silhouette score: 0.45, Dunn index: 0.18), with one of them associated to a worsening in walking. Then, supervised machine learning models (i.e., Support Vector Machine and Ensemble Boosting models) are trained using pre-surgery gait parameters, clinical scores, and demographic information to predict the two gait change clusters. In a Leave-One-Subject-Out validation, the best model achieves balanced accuracy 80.05 $\pm$ 3.52 %, denoting moderate predictability of both clusters. Moreover, feature importance analysis reveals the variability in the step width and in the step length asymmetry during the preoperative gait test as promising biomarkers to predict gait response to STN-DBS. Authors

关键词： Unsupervised learning

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Combating Distribution Shift for Accurate Time Series Forecasting via Hypernetworks

arXiv

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arXiv 2022年

作者： Duan, Wenying He, Xiaoxi Zhou, Lu Thiele, Lothar Rao, Hong School of Mathematics and Computer Sciences Nanchang University Nanchang China Computer Engineering and Networks Laboratory ETH Zurich Zurich Switzerland Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong Computer Engineering and Networks Laboratory Zurich Switzerland Zurich Switzerland School of Software Nanchang University Nanchang China

Time series forecasting has widespread applications in urban life ranging from air quality monitoring to traffic analysis. However, accurate time series forecasting is challenging because real-world time series suffer from the distribution shift problem, where their statistical properties change over time. Despite extensive solutions to distribution shifts in domain adaptation or generalization, they fail to function effectively in unknown, constantly-changing distribution shifts, which are common in time series. In this paper, we propose Hyper Time-Series Forecasting (HTSF), a hypernetwork-based framework for accurate time series forecasting under distribution shift. HTSF jointly learns the time-varying distributions and the corresponding forecasting models in an end-to-end fashion. Specifically, HTSF exploits the hyper layers to learn the best characterization of the distribution shifts, generating the model parameters for the main layers to make accurate predictions. We implement HTSF as an extensible framework that can incorporate diverse time series forecasting models such as RNNs and Transformers. Extensive experiments on 9 benchmarks demonstrate that HTSF achieves state-of-the-art performances. © 2022, CC BY.

关键词： Time series

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Automatic Energy-Hotspot Detection and Elimination in Real-Time Deeply Embedded Systems 42

Automatic Energy-Hotspot Detection and Elimination in Real-T...

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42nd IEEE Real-Time Systems Symposium, RTSS 2021

作者： Shekarisaz, Mohsen Thiele, Lothar Kargahi, Mehdi School of Electrical and Computer Engineering University of Tehran Tehran Iran Computer Engineering and Networks Laboratory ETH Zürich Zürich Switzerland

ISBN: (纸本)9781665428026

Today’s deeply embedded systems, with real-time interactions to the environment, are largely battery-operated, and peripheral modules like LTE, WiFi, and GPS are among the most energy-hungry components of them. These components are often under the direct control of an embedded software. Some pieces of the software program are called energy hotspots if they can be transformed towards better system energy consumption while leaving it logically- and temporally-correct. This paper focuses on three such energy hotspots from the peripheral module perspective. The root causes of the hotspots in the software program are misplaced driver calls: Early acquiring or late releasing of the module causes it to waste energy in the active state, having unnecessary distance between the use operations causes extra tail energy overhead, and unaccounted releasing and re-acquiring of the module causes more energy consumption in comparison to leaving the module unreleased. We provide static analysis methods for the detection and elimination of such energy hotspots automatically with regard to some relations between temporal requirements of the real-time embedded software, the time and energy specifications of the module, and the extreme (worst-case/best-case) execution times of specific pieces of the software program. Our simulation results show about 4.7 to 20 percent of energy reductions after elimination of the energy hotspots of the test programs using our proposed method. © 2021 IEEE

关键词： Real time systems

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Photo-induced macro/mesoscopic scale ion displacement in mixed-halide perovskites:ring structures and ionic plasma oscillations

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Light(Science & Applications) 2022年第10期11卷 2388-2398页

作者： Xiaoxiao Sun Yong Zhang Weikun Ge Laboratory for Thin Films and Photovoltaics Empa-Swiss Federal Laboratories for Materials Science and Technology8600 DuebendorfSwitzerland Department of Information Technology and Electrical Engineering ETH Zurich8093 ZurichSwitzerland Institute of Ion Beam Physics and Materials Research Helmholtz-Zentrum Dresden-RossendorfDresden 01328Germany Department of Electrical and Computer Engineering The University of North Carolina at CharlotteCharlotteNC 28223USA Department of Physics Tsinghua UniversityBeijing 10084People's Republic of China

Contrary to the common belief that the light-induced halide ion segregation in a mixed halide alloy occurs within the illuminated area,we find that the Br ions released by light are expelled from the illuminated area,which generates a macro/mesoscopic size anion ring surrounding the illuminated area,exhibiting a photoluminescence *** intriguing phenomenon can be explained as resulting from two counter-balancing effects:the outward diffusion of the light-induced free Br ions and the Coulombic force between the anion deficit and surplus *** after removing the illumination,the macro/mesoscopic scale ion displacement results in a built-in voltage of about 0.4 V between the ring and the ***,the displaced anions return to the illuminated area,and the restoring force leads to a damped ultra-low-frequency oscillatory ion motion,with a period of about 20-30 h and lasting over 100 *** finding may be the first observation of an ionic plasma oscillation in *** understanding and controlling the"ion segregation"demonstrate that it is possible to turn this commonly viewed"adverse phenomenon"into novel electronic applications,such as ionic patterning,self-destructive memory,and energy storage.

关键词： mixed removing return

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Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model

arXiv

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arXiv 2025年

作者： An, Zhaochong Sun, Guolei Liu, Yun Li, Runjia Han, Junlin Konukoglu, Ender Belongie, Serge Department of Computer Science University of Copenhagen Denmark Computer Vision Laboratory ETH Zurich Switzerland College of Computer Science Nankai University China Department of Engineering Science University of Oxford United Kingdom

Generalized few-shot 3D point cloud segmentation (GFS-PCS) adapts models to new classes with few support samples while retaining base class segmentation. Existing GFS-PCS methods enhance prototypes via interacting with support or query features but remain limited by sparse knowledge from few-shot samples. Meanwhile, 3D vision-language models (3D VLMs), generalizing across open-world novel classes, contain rich but noisy novel class knowledge. In this work, we introduce a GFS-PCS framework that synergizes dense but noisy pseudo-labels from 3D VLMs with precise yet sparse few-shot samples to maximize the strengths of both, named GFS-VL. Specifically, we present a prototype-guided pseudo-label selection to filter low-quality regions, followed by an adaptive infilling strategy that combines knowledge from pseudo-label contexts and few-shot samples to adaptively label the filtered, unlabeled areas. Additionally, we design a novel-base mix strategy to embed few-shot samples into training scenes, preserving essential context for improved novel class learning. Moreover, recognizing the limited diversity in current GFS-PCS benchmarks, we introduce two challenging benchmarks with diverse novel classes for comprehensive generalization evaluation. Experiments validate the effectiveness of our framework across models and datasets. Our approach and benchmarks provide a solid foundation for advancing GFS-PCS in the real world. The code is at here. © 2025, CC BY-NC-SA.

关键词： Visual languages

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Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion

arXiv

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arXiv 2025年

作者： Wu, Jiqing Berg, Ingrid Li, Yawei Konukoglu, Ender Koelzer, Viktor H. Department of Biomedical Engineering University of Basel Switzerland Department of Pathology and Molecular Pathology University Hospital University of Zurich Switzerland Computer Vision Lab ETH Zurich Switzerland Integrated System Laboratory ETH Zurich Switzerland Institute of Medical Genetics and Pathology University Hospital Basel Switzerland

Holistic 3D modeling of molecularly defined brain structures is crucial for understanding complex brain functions. Emerging tissue profiling technologies enable the construction of a comprehensive atlas of the mammalian brain with sub-cellular resolution and spatially resolved gene expression data. However, such tera-scale volumetric datasets present significant computational challenges in understanding complex brain functions within their native 3D spatial context. Here, we propose the novel generative approach Tera-MIND, which can simulate Tera-scale Mouse braINs in 3D using a patch-based and boundary-aware Diffusion model. Taking spatial transcriptomic data as the conditional input, we generate virtual mouse brains with comprehensive cellular morphological detail at teravoxel scale. Through the lens of 3D gene-gene self-attention, we identify spatial molecular interactions for key transcriptomic pathways in the murine brain, exemplified by glutamatergic and dopaminergic neuronal systems. Importantly, these in-silico biological findings are consistent and reproducible across three tera-scale virtual mouse brains. Therefore, Tera-MIND showcases a promising path toward efficient and generative simulations of whole organ systems for biomedical research. Project website: https://***/*** © 2025, CC BY.

关键词： Mammals

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Gate-defined two-dimensional hole and electron systems in an undoped InSb quantum well

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Physical Review Research 2023年第1期5卷 013117-013117页

作者： Zijin Lei Erik Cheah Filip Krizek Rüdiger Schott Thomas Bähler Peter Märki Werner Wegscheider Mansour Shayegan Thomas Ihn Klaus Ensslin Solid State Physics Laboratory ETH Zurich CH-8093 Zurich Switzerland IBM Research Europe - Zurich Säumerstrasse 4 8803 Rüschlikon Switzerland ETH Zurich Quantum Center CH-8093 Zurich Switzerland Department of Electrical and Computer Engineering Princeton University Princeton New Jersey 08544 USA

Quantum transport measurements are performed in gate-defined, high-quality, two-dimensional hole and electron systems in an undoped InSb quantum well. For both polarities, the carrier systems show tunable spin-orbit interaction as extracted from weak antilocalization measurements. The effective mass of InSb holes strongly increases with carrier density as determined from the temperature dependence of Shubnikov–de Haas oscillations. Coincidence measurements in a tilted magnetic field are performed to estimate the spin susceptibility of the InSb two-dimensional hole system. The g factor of the two-dimensional hole system decreases rapidly with increasing carrier density.

关键词： Quantum Hall effect Quantum transport Spin-orbit coupling Quantum wells Epitaxy Lithography Shubnikov-de Haas effect

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Design and Experimental Investigation of Trikarenos: A Fault-Tolerant 28nm RISC-V-based SoC

arXiv

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arXiv 2024年

作者： Rogenmoser, Michael Wiese, Philip Forlin, Bruno Endres Gürkaynak, Frank K. Rech, Paolo Menicucci, Alessandra Ottavi, Marco Benini, Luca The Integrated Systems Laboratory ETH Zurich Switzerland The Computer Architecture for Embedded Systems The University of Twente Netherlands The Department of Industrial Engineering The University of Trento Italy The Department of Space Engineering The Delft University of Technology Netherlands The Computer Architecture for Embedded Systems The University of Twente Netherlands The Department of Electronic Engineering The University of Rome Tor Vergata Italy The Integrated Systems Laboratory ETH Zurich Switzerland The Department of Electrical Electronic and Information Engineering The University of Bologna Italy

We present a fault-tolerant by-design RISC-V SoC and experimentally assess it under atmospheric neutrons and 200 MeV protons. The dedicated ECC and Triple-Core Lockstep countermeasures correct most errors, guaranteein... 详细信息

关键词： Fault tolerance

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ICT: In-field calibration transfer for air qality sensor deployments

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Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2019年第1期3卷 1–19页

作者： Cheng, Yun He, Xiaoxi Zhou, Zimu Thiele, Lothar ETH Zurich Computer Engineering and Networks Laboratory Zurich Switzerland

Recent years have witnessed a growing interest in urban air pollution monitoring, where hundreds of low-cost air quality sensors are deployed city-wide. To guarantee data accuracy and consistency, these sensors need periodic calibration after deployment. Since access to ground truth references is often limited in large-scale deployments, it is diJJicult to conduct city-wide post-deployment sensor calibration. In this work we propose In-field Calibration Transfer (ICT), a calibration scheme that transfers the calibration parameters of source sensors (with access to references) to target sensors (without access to references). On observing that (i) the distributions of ground truth in both source and target locations are similar and (ii) the transformation is approximately linear, ICT derives the transformation based on the similarity of distributions with a novel optimization formulation. The performance of ICT is further improved by exploiting spatial prediction of air quality levels and multi-source fusion. Experiments show that ICT is able to calibrate the target sensors as if they had direct access to the references. © 2019 Association for Computing Machinery.

关键词： Air quality

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