Abstract Conventional continuous plants use fixed‐capacity equipment, resulting in high capital risk and suboptimal performance under fluctuating demands. To address these, this study proposes an integrated framework for modular process design and supervisory control capable of adapting to demand uncertainty for long‐term economic viability.
T. Asrav, M. Alvarado‐Morales, G. Sin
wiley +1 more source
Machine learning driven many‐objective moving horizon scheduling optimization
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
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 +6 more
wiley +1 more source
Does Medicare Advantage funding disparity affect managed care insurers' profitability? Evidence from Puerto Rico. [PDF]
Rivera-Rodríguez SA +2 more
europepmc +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
The impact of big data capabilities and business model innovation on new venture performance. [PDF]
Xiong X.
europepmc +1 more source
When Biology Meets Medicine: A Perspective on Foundation Models
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu +3 more
wiley +1 more source
Current Standards of Monitoring Models in Healthcare Settings
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay +5 more
wiley +1 more source
Distress, resilience, and self-repair: a topic modeling analysis of Chinese doctoral students' self-disclosure on Xiaohongshu. [PDF]
Yin Q.
europepmc +1 more source
Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects
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

