Group technology empowering optimization of mixed-flow precast production in off-site construction.

Faced with immense pressure to reduce environmental impact, off-site construction (OSC) is considered a sustainable alternative to conventional practices. However, challenged by component diversity and a significant surge in demand, deficient or empirical-based scheduling management struggles to effectively harness the potential of mixed-flow precast production to improve efficiency, instead resulting in environmental impacts, and falling short of expected benefits in OSC projects. Therefore, this study addresses the conflict between efficiency and environmental impact arising from the application of mixed-flow precast production by integrating multi-objective optimization and group technology. A multi-objective optimization framework is proposed, incorporating grouping technology for mixed-flow precast production scheduling and aiming to minimize carbon emissions and reduce tardiness/earliness penalty. The non-dominated sorting genetic algorithm II (NSGA-II), adjusted by adaptive population initialization strategy and group technology, is introduced to solve this problem, striking a balance between sustainability and penalty costs. Through a real-case analysis, the proposed approach demonstrates an average reduction of 37.5% in carbon emissions compared to rule-based scheduling methods, a 30.1% reduction compared to previous research methods, along with over 10% reduction in tardiness/earliness penalty. This study enhances environmental benefits and efficiency from a production scheduling perspective and establishes an automated, practical method, fostering low-cost, high-efficiency green production for construction component enterprises, particularly for small and medium-sized enterprises, thereby promoting sustainable development in the construction industry.

How does digital technology empower urban green development efficiency in the Beijing-Tianjin-Hebei region-mechanism analysis and spatial effects.

Under the strategy of "Digital China" and "Sustainable Development," the synergistic development of digital economy and green economy has become a crucial topic. Based on the panel data of 13 cities in the Beijing-Tianjin-Hebei (BTH) region from 2011 to 2019, this study investigates the direct effect, intrinsic mechanism, and spatial spillover effect of digital technology development (DTD) on urban green development efficiency (GDE). The empirical results show that (1) DTD significantly improves urban GDE in the BTH region, and it passes the endogeneity test, (2) DTD can enhance urban GDE by improving the environmental regulation intensity and technological innovation level in the BTH region; however, the industrial structure optimization weakens the promotion effect of DTD on urban GDE in the BTH region, which shows a "masking effect," (3) the kernel density estimation method and ArcGIS technology reveal the existence of "digital divide" and GDE differences among cities in the BTH region. Moreover, the spatial distribution pattern of DTD gradually forms "H-H" and "L-L" clusters in the BTH region, and (4) DTD also increases the GDE of neighboring cities through spatial spillover effects in the BTH region, and it passes the robustness test of replacing the spatial weight matrix. This study is important for the BTH region to simultaneously solve economic development and environmental problems in the context of digitalization.

Genetic diversity and biogeography of haloalkaliphilic sulphur-oxidizing bacteria belonging to the genus Thioalkalivibrio.

A group of 85 isolates of haloalkaliphilic obligately chemolithoautotrophic sulphur-oxidizing bacteria belonging to the genus Thioalkalivibrio were recently obtained from soda lakes in Mongolia, Kenya, California, Egypt and Siberia. They have been analyzed by repetitive extragenic palindromic (rep)-PCR genomic fingerprinting technique with BOX- and (GTG)5-primer set. Cluster analysis was performed using combined fingerprint profiles and a dendrogram similarity value (r) of 0.8 was used to define the same genotype. Fifty-six genotypes were found among the isolates, revealing a high genetic diversity. The strains can be divided into two major clusters, including isolates from the Asiatic (Siberia and Mongolia) and the African (Kenya and Egypt) continents, respectively. The majority (85.9%) of the genotypes were found in only one area, suggesting an endemic character of the Thioalkalivibrio strains. Furthermore, a correlation between fingerprint clustering, geographic origin and the characteristics of the lake of origin was found.