Results 141 to 150 of about 114,074 (272)

Dynamic, Unconstrained Optimization of Secreted Enzyme Production in Fed‐Batch Fermentation Using Reinforcement Learning

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Reinforcement learning (RL) has been used to control a wide range of dynamic processes, especially ones that are too complex to model well or have stochastic environmental perturbations. Fed‐batch fermentations are subject to changes in starting cell growth rates and process variations that can affect cell growth and secreted target production.
Sai Harish Uthravalli, Sakib Ferdous, J. Michael Hess, Nigel F. Reuel   +3 more
wiley   +1 more source

Sparse Bayesian learning using hierarchical synthesis prior for STAP

IET Radar, Sonar & Navigation
Space–time adaptive processing (STAP) can effectively detect moving targets in the background of ground clutter, but the performance will drop sharply when the training samples are limited.
Junxiang Cao, Tong Wang, Weichen Cui
doaj   +1 more source

Advances in causal discovery methods for ecological time series

Biological Reviews, EarlyView.
ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki, Masato Yamamichi, Yutaka Osada, Masayuki Ushio, Kohei Nakajima, Hiroshi Masuya, Shohei Shimizu   +6 more
wiley   +1 more source

FASD and Intellectual Disability Equivalence: A Meta‐Analysis of Suggestibility During Forensic Interviews

Behavioral Sciences &the Law, EarlyView.
ABSTRACT Intellectual disability (ID) equivalence describes conditions in which individuals function cognitively and adaptively at levels comparable to ID without meeting IQ‐based diagnostic criteria. Fetal alcohol spectrum disorder (FASD) is characterised by impaired executive and adaptive functioning despite IQs often above the ID threshold ...
David J. Gilbert, Stephen Ikechukwu Azumara, Jacqueline M. Wheatcroft, Karen Steele, Penny Cook, Raja Mukherjee, Gisli Gudjonsson, Natalie Novick Brown   +7 more
wiley   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

Carbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao, Fei Wang, Qixuan Cai, Aike Xi, Kangkang Wang, Khaixien Leu, Rufan Zhang   +6 more
wiley   +1 more source

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Bayesian Optimization of Solvent‐Free Thermal Amidation via Reactive Extrusion

Chemistry – A European Journal, EarlyView.
Thermal amidation between a carboxylic acid and an amine was successfully conducted in an extruder in the absence of solvent, coupling agent, or catalyst, relying on an adapted Bayesian Optimization protocol. Active pharmaceutical ingredient moclobemide was synthesized on a larger scale, achieving excellent yield and low Process Mass Intensity (PMI ...
Matthieu Lavayssiere, Xavier Bantreil, Frédéric Lamaty   +2 more
wiley   +1 more source

Clinical Model‐Informed Precision Dosing Consult Service for Accelerating Personalized Medication in Pediatric Patients

Clinical Pharmacology &Therapeutics, EarlyView.
Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who
Zachary L. Taylor, Takanobu Nadai, Kei Irie, Wen Rui Tan, Sanjana Parikh, Anhar Hosawi, Matthijs W. van Hoogdalem, Ronaldo Morales Junior, Sonya Tang Girdwood, Abbie D. Leino, Kana Mizuno, Alexander A. Vinks, Tomoyuki Mizuno   +12 more
wiley   +1 more source

AI‐Enabled Precision Dosing in Pediatrics: Enhancing Model‐Informed Decision Making

Clinical Pharmacology &Therapeutics, EarlyView.
Ensuring safe and effective pharmacotherapy for children remains a central challenge in clinical pharmacology, yet rapid advances in AI have not translated into clinical practice. This Perspective highlights how AI‐enabled approaches can enhance model‐informed decision making for precision dosing.
Kei Irie, Tomoyuki Mizuno
wiley   +1 more source