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- Engineering | Journal | ScienceDirect. com by Elsevier
The official journal of the and is an international open-access journal that was launched by the Chinese Academy of Engineering (CAE) in 2015 Its aims are to provide a high-level platform where cutting-edge advancements in engineering R D, current major research outputs, and key achievements can be disseminated and shared; to report progress in engineering science, discuss hot topics, areas
- Engineered non-canonical reductive TCA pathway drives high-yield . . .
The reductive tricarboxylic acid (rTCA) cycle is a crucial metabolic pathway employed in the microbial production of C4-dicarboxylic acids, especially succinic acid (SA) However, the inherent redox constraints associated with this cycle pose significant limitations on the yields of SA Here, we address this critical bottleneck by engineering a non-canonical reductive TCA (Nc-rTCA) pathway in
- ScienceDirect. com | Science, health and medical journals, full text . . .
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- Guide for authors - Engineering Structures - ISSN 0141-0296 . . .
Engineering Structures provides a forum for a broad blend of scientific and technical papers to reflect the evolving needs of the structural engineering and structural mechanics communities Particularly welcome are contributions dealing with new developments or innovative applications of structural and mechanics principles and digital technologies for the analysis and design of engineering
- Non-solvent induced phase separation of zwitterionic copolymer . . .
The development of anti-fouling loose nanofiltration (LNF) membranes capable of dye desalination for resource recovery from saline textile wastewater …
- Machine Learning to speed up Computational Fluid Dynamics engineering . . .
Computational fluid dynamics (CFD) is a valuable tool in designing built environments, enhancing comfort, health, energy efficiency, and safety in both indoor and outdoor applications Nevertheless, the time required for CFD computations still needs to be reduced for engineering studies Recent advances in machine learning (ML) techniques offer a promising avenue for developing fast-running
- Automated data processing and feature engineering for deep learning and . . .
The machine learning model design process itself is a time-consuming process requiring extensive domain knowledge To train a model for image classification, for example, the developer would usually go through the following steps: (1) Collect and fine-tune image data, (2) choose a suitable ML algorithm, (3) define acceptable parameter and hyperparameter settings, (4) train the selected model
- Semantic enrichment of BIM models for construction cost estimation in . . .
Accurate construction cost estimation is vital for ensuring profitable project execution for both owners and contractors However, traditional methods often rely on disparate engineering data, leading to inaccuracies and inconsistencies among stakeholders To address this, this paper introduces an automated system that semantically enriches Building Information Modeling (BIM) models by
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