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• A multi-class Boosting method is proposed for the multi-class imbalanced problem. • Parametrized division of exposure zone is achieved using RMS, C r , C s , and D cl , etc. • Field chloride profile data with time span of 18 years validates proposed method. • The distribution of exposure zone satisfies the Weibull distribution. The analysis of marine reinforced concrete structures using chloride profile data is a commonly used exposure zone classification method. However, chloride profile data is multi-class, unbalanced and non-parametric, which makes it difficult for the commonly used machine-learning methods to construct an appropriate classification model. To solve this problem, chloride profile is parametrized by the minimum redundancy maximum relevance algorithm and a multi-class Boosting method using F-measure as inductive bias indicator to evaluate the weight of base classifiers is put forward. The method is based on field test data of the chloride profile over a period of 18 years in Hangzhou Bay, China. The method outperforms the original Boosting method with an average F-measure improvement of 6.2 %. The results show that parametric partitioning of the exposure zone is achieved and the distribution of the exposure zone satisfies the Weibull distribution. [ABSTRACT FROM AUTHOR]

The cement manufacturing industry, a resource- and energy-intensive sector, took up more than 15% of total greenhouse gas emissions in China, thus finding a clean technology option for sustainable development is essential. CO 2 curing has emerged as a promising novel method for large-scale carbon sequestration and mechanical properties improvement of cement-based composites. Currently, a body of related works is mainly investigated in the laboratory, and understandings of the behaviors of CO 2 -cured cement-based composites are still less than complete, including, 1) the CO 2 storage potential has plenty of room for improvement due to the influence mechanism of variables factors remains unclear; 2) previous evaluations were mostly based on the subsets of individual result rather than an integrated dataset; 3) whether CO 2 curing is suitable for the manufacturing process of reinforced concrete. Therefore, this paper presents a comprehensive overview covering a wide range of parameters as well as fabrication, mechanical (compressive strength), and environmental (CO 2 uptake value) performances on the basis of a correct understanding of the differences between active and passive carbonation reactions. Notably, the influences of critical factors, including those less understood, e.g., types of curing setup (flow-able, enclosed, and others), components of binder, and aggregate/binder ratio, are also analyzed and the corresponding mechanisms discussed to achieve satisfied curing efficiency. Besides, corrosion-related challenges are also be pointed out to convince the widespread acceptance of this technology. Finally, based on this paper, limitations of existing research are identified and future scope on CO 2 curing regime is proposed. • 170 studies related to CO 2 /carbonation-cured cement-based composites are analyzed. • The differences between active/passive-carbonation together with reaction mechanisms are expounded. • Fabrication and influence factors on engineering and environmental properties are systematically reviewed. • CO 2 -cured cement-based composites exhibit excellent resistance to aggressive conditions. • The challenges and opportunities in the CO 2 curing method are innovatively discussed. [ABSTRACT FROM AUTHOR]

Porcine sapelovirus (PSV) is a ubiquitous virus in farmed pigs that is associated with SMEDI syndrome, polioencephalomyelitis, and diarrhea. However, there are few reports on the prevalence and molecular characterization of PSV in Fujian Province, Southern China. In this study, the prevalence of PSV and a poetical combinative strain PSV2020 were characterized using real-time PCR, sequencing, and bioinformatics analysis. As a result, an overall sample prevalence of 30.8% was detected in 260 fecal samples, and a farm prevalence of 76.7% was observed in 30 Fujian pig farms, from 2020 to 2022. Noteably, a high rate of PSV was found in sucking pigs. Bioinformatics analysis showed that the full-length genome of PSV2020 was 7550 bp, and the genetic evolution of its ORF region was closest to the G1 subgroup, which was isolated from Asia and America; the similarity of nucleotides and amino acids to other PSVs was 59.5~88.7% and 51.7~97.0%, respectively. However, VP1 genetic evolution analysis showed a distinct phylogenetic topology from the ORF region; PSV2020 VP1 was closer to the DIAPD5469-10 strain isolated from Italy than strains isolated from Asia and America, which comprise the G1 subgroup based on the ORF region. Amino acid discrepancy analysis illustrated that the PSV2020 VP1 gene inserted twelve additional nucleotides, corresponding to four additional amino acids (STAE) at positions 898-902 AAs. Moreover, a potential recombination signal was observed in the 2A coding region, near the 3' end of VP1, owing to recombination analysis. Additionally, 3D genetic evolutionary analysis showed that all reference strains demonstrated, to some degree, regional conservation. These results suggested that PSV was highly prevalent in Fujian pig farms, and PSV2020, a PSV-1 genotype strain, showed gene diversity and recombination in evolutionary progress. This study also laid a scientific foundation for the investigation of PSV epidemiology, molecular genetic characteristics, and vaccine development.