Results 141 to 150 of about 12,047 (267)
Asking the 5 W's for designing next‐generation bioprocessing
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook +4 more
wiley +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Grasslands are the predominant land use type in China, which is currently encountering significant desertification issues. Consequently, restoring grassland vegetation has important implications for terrestrial carbon (C) levels and, consequently, the ...
Chuanyu Zhou +6 more
doaj
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +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
Several indices can be used to assess the impact of short-term conservation agriculture strategies on improving soil organic carbon (SOC). To find out how the SOC pools and the carbon lability influence the carbon management index (CMI) in response to ...
Aram Gorooei +6 more
doaj +1 more source
High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State
Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording +4 more
wiley +1 more source
A judicious management practice to improve the soil\u27s organic carbon level and soil fertility is essential for agricultural and environmental sustainability.
Kavyasree, V., Mini
core +1 more source
Therapeutic Applications of Stimuli‐Based Release and Engineering of Extracellular Vesicles
This review summarizes the effects of endogenous and exogenous stimuli, their effects on the natural release of extracellular vesicles, as well as their uptake and release. It also gives an overview of stimuli‐responsive EVs and their therapeutic applications. Extracellular vesicles (EVs), nano‐ to microsized lipid bilayer membrane‐bound particles, are
Gloria Kemunto, Kristen Dellinger
wiley +1 more source

