Ciencias de la vida

Projection-Based Reconstruction for Achieving High-Order Accuracy from Low-Order DGSEM Simulations

- High-order discontinuous Galerkin spectral element methods (DGSEM) based on Legendre-Gauss-Lobatto (LGL) nodes provide accurate and efficient discretizations for conservation laws. However, their...

Digital Humanism and Evolutionary Design

- This paper examines the two concepts of digital humanism and evolutionary design. The aim is to identify and highlight potential common structures, synergies, and challenges. How should and can...

High-Order Invariant-Domain Preserving Continuous Finite Elements via Graph-Poisson Convex Limiting

- We develop a high-order invariant-domain preserving continuous finite element method for nonlinear scalar conservation laws. The method combines a residual-viscosity high-order discretization with a...

Node-Level Performance and Energy Characterization of Flagship Science Applications on SuperMUC-NG Phase 2

- We present a systematic performance and energy-efficiency characterization of five flagship scientific workloads on SuperMUC-NG phase 2, the 28 PetaFLOPs system at the Leibniz Supercomputing Center...

SPADE: Structure-Prior Adaptive Decision Estimation

- Physical-structure priors such as conservation laws, Hamiltonian forms, and symmetries can improve scientific machine learning when correct, but can degrade predictions when misspecified. Existing...

Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks

- Deep Learning (DL) has advanced various fields by extracting complex patterns from large datasets. However, the computational demands of DL models pose environmental and resource challenges. Deep...

Mass Conservation as an Inductive Bias for Self-Organized Criticality in NCA Reservoirs

- Self-organized criticality (SOC), a dynamical regime associated with maximal information processing, offers a promising foundation for reservoir computing. Recent work has shown that neural cellular...

EnerInfer: Energy-Aware On-Device LLM Inference

- On-device LLM inference is increasingly attractive for privacy-preserving, reliable, and cost-effective deployment, yet its energy and thermal costs remain a critical bottleneck. Existing systems...

Decentralized Operations of Decarbonized Chemical Plants with Renewable-driven Transmission Systems

- Electrification of ethane cracking offers a promising pathway to industrial decarbonization, provided that the electricity is sourced from renewable energy. However, integrating electrified chemical...

PHOEBI: An Open-World Benchmark for Bacterial Identification in Phase-Contrast Microscopy

- Optical microscopy enables rapid, label-free imaging of live bacteria and is the standard instrument for species identification across clinical, environmental, and industrial microbiology. Yet field...

Locally conservative redistribution limiting and applications to the approximation of conservation equations, Part II

- A non-intrusive, discretization and PDE agnostic limiting technique is introduced. The method is conservative and can be applied to high-order approximations including spectral methods. It can be...

Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding

- Vector-scalar comparison is a fundamental computation primitive that compares each element in a vector against a single scalar value. It is widely used in various data-intensive workloads from...

Architecture for Health Initiative (Arch4Health): Computational Challenges in Health-Related Applications and the Role of Computer Architecture in Addressing Them

- Recent biotechnological advances enable high-throughput, low-cost, and accurate biological data generation. This wealth of data enables unique opportunities for advancing healthcare. Despite these...

A phase-field model for microbiologically influenced corrosion

- A phase-field-based reaction-diffusion corrosion model is developed to predict microbially influenced corrosion (MIC) in metal alloys, with a focus on anaerobic conditions and sulfate-reducing...

Federated Learning for Global Carbon Emission Forecasting: A Hybrid Time-Series Approach with Statistical and Neural Models

- Climate change, primarily driven by carbon dioxide (CO2) emissions, requires accurate forecasting tools to support effective mitigation policies and sustainable development strategies. Existing...

Physics-Informed Predictive Control for Integrated Electric-Vehicle Thermal Management: An Open, Real-Data-Anchored Benchmark

- Thermal management in a battery-electric vehicle (BEV) is a coupled, vehicle-level problem: the battery pack, the passenger cabin, the heat pump, and cabin air quality compete for shared actuation...

NeutronSparse: Coordinating Heterogeneous Engines for Sparse Matrix Multiplication on NPUs

- Sparse matrix-matrix multiplication (SpMM) is a fundamental data operation for large-scale sparse data processing. With NPUs increasingly deployed in data centers for their performance and energy...

SPiralRoll: A Novel Adjustable-Stiffness Underactuated 3-DoF Joint with Torsion Springs for Rolling Robots

- Compliant mechanisms are important in robotics because they can improve adaptability, safety, and energy efficiency while reducing hardware complexity. This paper presents SPiralRoll, a novel...

Dynamics, stability, and energy efficiency of an energy-recycling rimless wheel with spring-clutch legs

- This paper proposes an energy-recycling rimless wheel with spring-clutch legs. The proposed mechanism uses a lockable clutch to store part of the impact-induced elastic energy after foot contact and...

The Language-Energy Divide: Measuring Energy Costs of Multilingual LLM Inference

- Large language models (LLMs) are increasingly deployed in multilingual settings, yet the energy costs of serving these models across different languages remain poorly understood. We present a...

CoSA: Correlation-Guided Change Attention with Learnable Residual Gating for Remote Sensing Change Detection

- Remote sensing change detection (CD) from bi-temporal imagery is critical for applications such as urban monitoring, disaster assessment, and environmental management, yet robust localization remains...