Urban renewal is an ideal approach to promoting the value of the urban fabric and improving the sustainability of the urban environment. This study, which shows the continuity of research on sustainable urban renewal, aimed to identify sustainable urban renewal literature based on a library analysis of scientific research since 2000. A total of 3971 scientific papers from the SCIE (Science Citation Index Expanded) and SSCI (Social Sciences Citation Index) databases were reviewed to examine how research concerning “sustainable urban renewal” has emerged and developed in the past 20 years. The h-indices and impact factors of the most relevant journals in urban renewal and sustainable development since 2000 were analyzed. The most frequently cited articles were analyzed using analysis of social networks (VOSviewer). The results revealed potential future focuses of research and guidelines that link urban renewal and sustainability: the engagement of all stakeholders in the decision-making process; the involvement of residents in projects; the development of cooperation between towns and cities; the preservation and reuse of built and industrial heritage while respecting environmental law; and, finally, the search for new financing techniques. These potential future research topics were analyzed in four research areas so that sustainable development can easily be integrated into an urban renewal project.

The increasing developmental potentiality for the construction industry brings the huge challenge to make up the limitation of traditional construction project management mode when adapting to the Sustainable Development Goals (SDGs). Due to the high energy and resource consumption for the construction projects, there are a large number of uncertainties and disturbances in achieving resilient urban infrastructure. Studying construction project resilience (CPR) is imperative. However, prior studies preferred to measure resilience by systemic indicators, which are complex and unfriendly. Studying CPR from the perspective of employee behavior (EB) remains rare. Hence, this study proposed a social network analysis (SNA) methodology to overcome the research gap. Firstly, six EBs are identified by the systematic literature review (SLR). Then, the critical employees (CEs) and their interrelationships are investigated to form the social network. Six SNA parameters including density, degree centrality, betweenness centrality, efficiency, constraint, and cliques are selected to model the EBs, namely PMT cohesion, the identity of the project culture, formal behavior between employees, collaboration efficacy, informal social constraints, and reciprocity and mutual trust. Finally, the value of CPR is obtained and the strategies for improving the CPR are proposed from four characteristics: robustness, redundancy, rapidity, and resourcefulness. The findings provided a simple and effective techniques to measure the CPR and could benefit the project manager to improve the CPR by exerting accurate strategies to the EBs in poor performance.

For current territory development planning in China, city center accessibility (CCA) has gained increasing attention for evaluating the expansion of urban areas. How should CCA and its differences between the automobile and public transit (PT) modes be measured? We analyzed CCA from travel time and travel cost perspectives using the travel data obtained from the Baidu Map at a 100 m × 100 m resolution. The GWR was then examined to explore the correlation between the explanatory variables and the CCA differences. Automobile-based CCA shows a concentric structure and varies with time, while PT-based CCA has an apparent linear expansion along the metro lines and fluctuates less. When measuring by travel cost instead of travel time, CCA gaps between the two modes are lessened, and the automobile’s advantage is no longer evident. The distance from the metro stations has a significant positive effect on CCA differences, and the positive effect concentrates in the 3.6 km range (measured by travel time) and 2.8 km range (measured by travel cost) around the metro stations. Our study highlights the importance of multiple perspectives when comparing the accessibility of different transport modes, and the results also provide implications for policy-makers.

In this study, BM-Fe (black sesame melanin-iron complex) was prepared and characterized. The results showed that the carboxyl hydroxyl group of BSM (black sesame melanin) participated in the chelation of iron ions. EDS (energy dispersive spectroscopy) and XPS (X-ray photoelectron spectroscopy) results confirmed the presence of iron ions in BM-Fe. The results of DLS (dynamic light scattering) showed that the average particle sizes of BSM and BM-Fe were 844.9 nm and 294.3 nm, respectively, indicating that the structure of BM-Fe with a smaller particle size was formed after the binding of iron ions with the active group on BSM. Finally, the in vitro iron dissolution, iron ion identification, in vitro iron ion reduction, antioxidant activity, cytotoxicity and moisture resistance properties of BM-Fe and FST (ferrous sulfate tablets, a commonly used iron supplement) were comprehensively compared. The results showed that BSM combined with iron instead of physically mixing, and BM-Fe was easily reduced in the gastrointestinal environment. BM-Fe had good bioavailability and retained the excellent characteristics (such as oxidation resistance and biocompatibility) of BSM, and had the potential to be applied in the treatment of iron-deficiency-related diseases. In summary, BM-Fe prepared in this study not only retained the excellent characteristics of BSM but also had a good effect on iron supplementation, high bioavailability and low side effects. Comprehensive analysis showed that the performance of BM-Fe prepared in this study was similar to or even better than that of the control (FST). Thus, BM-Fe is expected to become a new comprehensive multi-functional iron supplement and has a broad developmental prospect.

As an important reference indicator for transmissions, it is necessary to conduct offline testing of PRND shifting force. By studying the shift force of PRND(Parking, Reverse, Neutral, and Drive), a fault prediction method for PRND shift force based on BP neural network is proposed to improve the offline detection efficiency of PRND shift force. Based on the data obtained from the offline detection platform, a dataset for network training is obtained after processing; Build a PRND shift force fault prediction model, design and train a BP neural network, and after error backpropagation, the next layer gradient determines the gradient of the current layer to obtain the prediction network; Bringing the dataset into the network for simulation and comparing the simulation results, it was found that the network can achieve ideal results.