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Abstract Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and effective model selection, and in the power of integrating huge metagenomics databases. These results demonstrate a new avenue to improve deep learning protein structure prediction through advanced MSA construction and provide additional evidence that optimization of input information to deep learning-based structure prediction methods must be considered with as much care as the design of the predictor itself.
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Building material stock analysis is critical for effective circular economy strategies: a comprehensive review
Abstract Buildings account for the largest share of accumulated materials and waste globally. Tracking the material composition, quantity and location of these materials, known as building material stock analysis (MSA), is a first step in enabling the reuse or repurposing of materials, key strategies of the circular economy. While the number of building MSAs is growing, there is a need to coalesce methods, data and scope. Therefore, in this work, we reviewed and evaluated 62 journal and conference articles on MSA of buildings from different angles including scope, boundaries, archetype classification, material intensity determination, approaches (i.e. bottom-up, top-down, remote sensing) and quantity of materials to identify barriers, gaps and opportunities in this area along with its implications for decision-making, policy and regulations. We cataloged the three major approaches of MSAs and discuss their advantages and shortcomings. We also created a comprehensive directory of building archetypes, references and materials for future researchers. As expected, most of the studies estimated that concrete had the largest mass compared with other materials; however, mass-based distribution of materials showed significant variations in different building stocks across the world. Also, embedded plastics and their types remain under-represented in current studies. A major barrier to MSA is related to a lack of information on physical attributes and geographic information system, design and construction data. Policy makers can play a role in mitigating data barriers through instituting regulations that enforce the reporting of building-related data during the permitting process. Furthermore, outcomes of building MSA can help policy makers when considering incentives for design and construction that utilize these abundant building materials.
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- PAR ID:
- 10369383
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research: Infrastructure and Sustainability
- Volume:
- 2
- Issue:
- 3
- ISSN:
- 2634-4505
- Page Range / eLocation ID:
- Article No. 032001
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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