Results 181 to 190 of about 35,296 (265)

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

A highly energy-efficient multi-core neuromorphic architecture for training deep spiking neural networks. [PDF]

Nat Commun
Li M, Zhou H, Xu X, Zhong Z, Quan P, Zhu X, Lin Y, Lin W, Li X, Wang D, Zhang J, Ma Y, Cui X, Wang W, Meng Q, Ma Z, Li G, Cui X, Tian Y.   +18 more
europepmc   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

Advanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh, Anton Bolyachkin, Hajime Nakamura, Tadakatsu Ohkubo, Hossein Sepehri‐Amin   +4 more
wiley   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Toward cardiac electrophysiology digital twins with an efficient open source scalable solver on GPU clusters. [PDF]

Sci Rep
Berg LA, Oliveira RS, Camps J, de Lima LMR, de Oliveira Campos J, Wang ZJ, Doste R, Bueno-Orovio A, Dos Santos RW, Rodriguez B.   +9 more
europepmc   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

AmberTorchPB: A Unified Framework for Poisson-Boltzmann-Based Reaction Field Energy Calculation via Tensor Computation. [PDF]

J Chem Theory Comput
Wu Y, Wang Q, Jiang R, Luo R.
europepmc   +1 more source

Holographic Mapping of Orbital Angular Momentum using a Terahertz Diffractive Optical Neural Network

Advanced Intelligent Discovery, EarlyView.
A compact six‐layer diffractive optical neural network enables direct recognition and spatial mapping of terahertz (THz) orbital angular momentum (OAM) beams. Fabricated by 3D printing, the system distinguishes nine OAM modes and their superpositions with high fidelity, good efficiency, and low crosstalk, offering a scalable solution for THz ...
Wei Jia, Miguel Gomez, Steve Blair, Berardi Sensale‐Rodriguez   +3 more
wiley   +1 more source

Fast segmentation with the NextBrain histological atlas. [PDF]

Imaging Neurosci (Camb)
Puonti O, Nolan J, Dicamillo R, Balbastre Y, Casamitjana A, Mancini M, Robinson E, Peter L, Annunziata R, Althonayan J, Crampsie S, Blackburn E, Billot B, Atzeni A, Schmidt P, Hughes J, Augustinack JC, Edlow BL, Zöllei L, Thomas DL, Kliemann D, Bocchetta M, Strand C, Holton JL, Jaunmuktane Z, Iglesias JE.   +25 more
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source