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Various schedule risks beset prefabrication housing production (PHP) in Hong Kong throughout the prefabrication supply chain, from design, manufacturing, logistics, to on-site assembly. Previous research on the risks in prefabrication construction projects has mainly focused on the construction stage and has been confined to issues of completeness and accuracy without consideration of stakeholder-related risks and their cause-and-effect relationships.However, in reality, the supply chain is inseparable as precast components should be manufactured and transported to sites to fit in with the schedule of on-site assembly in seamless connection manner, and most risks are interrelated and associated with various stakeholders.This study applies social network analysis (SNA) to recognize and investigate the underlying network of stakeholder-associated risk factors in prefabrication housing construction projects.Critical risks and relationships that have important roles in structuring the entire network of PHP are identified and analyzed. BIM (Building Information Modelling)-centered strategies are proposed to facilitate stakeholder communication and mitigate critical schedule risks and interactions underlying the risk network. This study not only provides an effective method to analyze stakeholder-associated risk factors and to evaluate the effect of these risk factors from a network perspective, but also offers a new visual perspective in the promotion of the use of the Internet of things (IoT) and helps identify housing construction problems in Hong Kong.

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Transcription and pre-mRNA splicing are the key nuclear processes in eukaryotic gene expression, and identification of factors common to both processes has suggested that they are functionally coordinated. p100 protein has been shown to function as a transcriptional co-activator for several transcription factors. p100 consists of staphylococcal nuclease (SN)-like and Tudor-SN (TSN) domains of which the SN-like domains have been shown to function in transcription, but the function of TSN domain has remained elusive. Here we identified interaction between p100 and small nuclear ribonucleoproteins (snRNP) that function in pre-mRNA splicing. The TSN domain of p100 specifically interacts with components of the U5 snRNP, but also with the other spliceosomal snRNPs. In vitro splicing assays revealed that the purified p100, and specifically the TSN domain of p100, accelerates the kinetics of the spliceosome assembly, particularly the formation of complex A, and the transition from complex A to B. Consistently, the p100 protein, as well as the separated TSN domain, enhanced the kinetics of the first step of splicing in an in vitro splicing assay in dose-dependent manner. Thus our results suggest that p100 protein is a novel dual function regulator of gene expression that participates via distinct domains in both transcription and splicing.

Many studies have been conducted on the contributions of the construction industry to greenhouse gas (GHG) emissions. However, these studies focused on the embodied GHG emissions of buildings and were restricted by limited system boundaries due to a lack of detailed on and off-site process data, especially data for assembly and miscellaneous works as well as construction related human activities. This study therefore analyzed GHG emissions during the construction phase of a case study building on the basis of an extended system boundary in the context of China by utilizing detailed onsite process data. The results show that indirect emissions accounted for 97% of all GHG emissions. On-site electricity use and building materials production were the two greatest contributors to direct and indirect emissions respectively. Recombining the construction activities revealed that construction related human activities generated significant GHG emissions (385 tCO2e), which have been ignored in previous research. The findings also reveal that although some materials used during the construction process are negligible in terms of weight, such as polyamide safety nets and aluminum (<0.1%), they have a considerable impact on GHG emissions (2-3%).

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