Results 221 to 230 of about 63,287 (274)

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy

Advanced Intelligent Systems, EarlyView.
Hallgrimson et al. introduce a machine learning algorithm, siMILe, that takes features of single‐molecule localization microscopy localization clusters (e.g., size and sphericity) and finds the clusters that are associated with certain cell conditions (such as differential protein expression or drug treatment).
Christian Hallgrimson, Y. Lydia Li, Claire A. Shou, Ben Cardoen, John Lim, Timothy H. Wong, Ismail M. Khater, Ivan Robert Nabi, Ghassan Hamarneh   +8 more
wiley   +1 more source

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Advanced Intelligent Systems, EarlyView.
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley   +1 more source

MusicSwarm: Biologically Inspired Intelligence for Music Composition

Advanced Intelligent Systems, EarlyView.
Biologically inspired swarms of frozen foundation models self‐organize to compose complex music without fine‐tuning. By coordinating through stigmergic signals, decentralized agents dynamically evolve specialized roles and adapt to solve complex tasks.
Markus J. Buehler
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Towards Advanced Intelligent and Perceptive Soft Grippers

Advanced Intelligent Systems, EarlyView.
Implementing soft yet strong and intelligent soft grippers request innovative and creative solutions in designing soft bodies and seamlessly integrating actuated systems with hierarchical sensing. This review systematically analyses soft grippers with a deep understanding of core components, from fundamental design principles to actuation and sensing ...
Haneul Kim, Hayeon Shin, Seik Park, Changbeom Shim, Seonggun Joe   +4 more
wiley   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Evaluating the African arid corridor hypothesis: A meta‐analysis including the phylogenetic and biogeographical history of Sesamothamnus

American Journal of Botany, EarlyView.
Abstract Premise We examined the African arid corridor (AAC) disjunction pattern of vascular plants between northeastern and southwestern Africa in the context of geological and climatic events since the late Miocene. We developed a phylogenetic and biogeographical framework for the arid‐adapted genus Sesamothamnus (Pedaliaceae), a classic example of ...
John G. Zaborsky, Jeffrey P. Rose, Ricardo Kriebel, Bryan T. Drew, Emily Moriarty Lemmon, Alan R. Lemmon, Kenneth J. Sytsma   +6 more
wiley   +1 more source

Dissecting Pirtobrutinib Resistance in Mantle Cell Lymphoma Through Single‐Cell Multi‐Omics

American Journal of Hematology, EarlyView.
ABSTRACT Pirtobrutinib (PBN), a non‐covalent BTK inhibitor, has been approved by the FDA for relapsed/refractory mantle cell lymphoma (MCL); however, resistance to PBN has been observed. To dissect the molecular dynamics driving PBN resistance, we performed integrative single‐cell multi‐omic profiling (scRNA‐seq, scATAC‐seq, and scDNA‐seq) on ...
Fangfang Yan, Yang Liu, Heng‐Huan Lee, Wei Wang, Joseph McIntosh, Yijing Li, Jovanny Vargas, Yue Fei, Sairah Ahmed, Lukas M. Simon, Michael Wang   +10 more
wiley   +1 more source