Results 101 to 110 of about 406,470 (199)

MULTIVARIATE POINT PROCESSES

open access: yes, 1972
Cox, D. R., Lewis, P. A. W.
openaire   +2 more sources

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

open access: yesAdvanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira   +13 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova   +4 more
wiley   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios   +4 more
wiley   +1 more source

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

open access: yesAdvanced Intelligent Systems, EarlyView.
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov   +8 more
wiley   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan   +6 more
wiley   +1 more source

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