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.
Recently, interface management has been regarded as the key to the success of prefabricated building projects (PBPs) due to its capabilities to manage numerous interfaces caused by PBPs’ inherent geographical and organizational fragmentation. However, the factors influencing the interface management of PBPs are largely unknown and poorly studied. To compensate for this gap, this study aimed to investigate the critical factors influencing interface management in PBPs with quantitative and qualitative methods. Twenty-seven critical factors influencing the interface management of PBPs were identified through a literature review, questionnaire survey, and face-to-face interviews with professionals in the construction industry. A questionnaire survey was sent out to developers, designers, manufacturers, contractors, and consultants in China, and 66 completed questionnaires were received. Results showed the top five critical factors influencing the interface management of PBPs were (1) accuracy of design, (2) timeliness of information communication, (3) timeliness of component production and supply, (4) standardization of design, and (5) definition of work content and scope. The 27 influencing factors of PBPs were further categorized into seven groups via exploratory factor analysis, namely: (1) information communication, (2) trust and cooperation, (3) technical and management capability, (4) organizational integration, (5) standardization, (6) technical environment, and (7) contractual management. Improving these issues will contribute to the successful implementation of PBPs. Finally, combined with relevant literature and expert interviews, the impact of these seven clusters on the interface management of PBPs was discussed. The findings may contribute to deepening the understanding of interface management, reducing unnecessary conflicts and difficulties, and promoting the sustainable development of prefabricated building (PB).
PurposeThe coordinated development of the urbanization and construction industry is crucial for the sustainable development of cities. However, the coupling relationship and coordination mechanism between them remain unclear. To bridge this gap, this study attempts to explore the level of coupling coordination between new urbanization and construction industry development and investigate the critical driving factors influencing their coupling coordination degree.Design/methodology/approachBy referring to the existing literature, two index systems were established to evaluate the development level of the new urbanization and construction industry. The spatiotemporal characteristics of the coupled coordinated development of the new urbanization and construction industry in China from 2014 to 2020 were investigated using the coupling coordination model. The Markov chain and geographic detector were adopted to understand the transition probability and driving factors of the coupling coordination degree.FindingsThe results indicate that the coupling degree of China's new urbanization and construction industry is high, and the two systems exhibit obvious interaction phenomena. However, the construction industry in most provinces lags behind the new urbanization. A positive interactive relationship and coordination mechanism has not been established between the two systems. Furthermore, the coupling contribution degree of the driving factors from high to low is as follows: market size > labor resource concentration > government investment ability > economic development level > industrial structure > production efficiency > technology level. Accordingly, a driving mechanism including market, policy, economic, and production technology drivers was developed.Originality/valueThis study contributes to the existing body of knowledge by providing a set of scientific analysis methods to address the deficiency of coordination mechanism research on new urbanization and the construction industry. The results also provide a theoretical basis for decision makers to develop differentiated sustainable development policies.
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.
Actively responding to climate change and accelerating the realization of carbon emission reduction are the common goals of global sustainable development. Hydrogen energy, as a “zero carbon emission” secondary energy, is playing an increasingly important role on the world energy stage. Hydrogen energy infrastructure (focusing on hydrogen refueling stations) is a key infrastructure in the transition to a hydrogen economy. However, the indicators that influence the location selection of hydrogen refueling stations (HRSs) are specific and have complex relationships, and current research still lacks a comprehensive analysis of its location selection decision-making indicators. Based on this research gap, this study proposes a hybrid fuzzy decision-making approach to determine the relationship and degree of influence between indicators. Firstly, this study identified 18 decision indicators that influence location selection from four dimensions: policy, economy, society, and environment. Subsequently, semi-structured interviews were used to initially assess the relationship between indicators. Finally, by using interpretive structural modeling and the fuzzy decision-making trial and evaluation laboratory (ISM-FDEMATEL), a 7-level structural model is established, which clarifies the complex relationship between indicators and the individual attributes of each indicator. The research results show that the indicators of the policy dimension have a more significant influencing degree than the other three dimensions and have a greater influence on the entire indicator system; the indicators of the economic dimension have a higher influencing degree and are easily influenced by other indicators. These findings will benefit policymakers and practitioners to prioritize and manage their resources effectively and efficiently and provide a valuable reference for advancing the sustainable development of the infrastructure for hydrogen energy.
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