With China’s government facilitating railway projects, more railway lines inevitably pass through ecological fragile regions (EFRs). Railway construction activities in EFRs might cause detrimental impacts on the local water-soil environment (WSE), which is the basis of the local ecological system that if destroyed can induce secondary disasters. Studies on the WSE risk (WSER) during railway construction in EFRs are limited. As such, this study aims to offer preliminary insight into the WSER assessment of railway construction in EFRs. WSERs were identified firstly based on the literature review and field surveys, and thus a risk index framework for WSER assessment including 5 categories of WSERs and 16 second-order risks was established. Then a comprehensive quantitative assessment method was developed by integrating analytic hierarchy process (AHP) and matter-element analysis (MEA) to assess the overall WSERs of railway construction in EFRs. A case (i.e., the Mingan subproject of Hefei-Fuzhou railway) was selected to demonstrate and validate the developed approach. Results show that the proposed assessment approach can be applied to evaluate the WSERs during railway construction. In addition, the case study demonstrates that the risk of construction methods should be the key focus. Findings from this study enrich the knowledge body of sustainable railways and guide the project managers to conduct practical WSER assessment of railway construction.

Carbon emissions have become a focus of political and academic concern in the global community since the launch of the Kyoto Protocol. As the largest carbon emitter, China has committed to reaching the carbon peak by 2030 and carbon neutrality by 2060 in the 75th United Nations High-level Meeting. The transport sector needs to be deeply decarbonized in China to achieve this goal. Previous studies have shown that the carbon emissions of the railway sector are small compared to highways, waterways, and civil aviation. However, these studies only consider the operation stage and do not consider the carbon emissions caused by large-scale railway infrastructure construction during the construction stage. As an essential source of carbon emissions and the focus of emissions reduction, the carbon emission of railway construction projects (RCPs) is in urgent need of relevant research. Based on a systematic literature review (SLR), this paper sorts out the carbon emission factors (CEFs) related to RCPs; combines semi-structured expert interviews to clarify the carbon emissions measurement boundary of RCPs; modifies and calibrates CEFs; constructs the carbon emission measurement model of RCPs including building material production stage, building material transportation stage, and construction stage; and conducts empirical analysis to validate carbon emission factors and measurement models. This study effectively complements the theoretical research on CEFs and measurement models in the construction stage of railway engineering and contributes to guiding the construction of low-carbon railways practically.

In knowledge economy era, enterprise needs to innovate to maintain its advantages and competitiveness. Construction enterprises, being pillars of China’s economy and confronting the challenge brought by the strategy of “going out”, the call for their technology or management innovation was broadly pronounced across practical and academic fields. Social capital (SC), as a resource in a social network, is the basis for creating sustainable competitiveness and advantage for enterprises. The innovative achievements and innovation performance (IP) of enterprises are largely determined by their SC. To achieve competitiveness in the market, enterprises must carry out knowledge transfer (KT) with the other members of their networks. However, few scholars have examined weather SC has any effect on IP in construction enterprises. Using a KT perspective, this paper explored how SC affects the IP of construction enterprises. Based on the literature review and analysis, a conceptual model was constructed and validated using structural equation modeling (SEM). Through empirical analysis, the following conclusions were drawn: (1) SC has a positive impact on the IP of construction enterprises. Among them, the structural dimension (SD) and cognitive dimension (CD) have a significant positive impact on the IP of construction enterprises, while the relational dimension (RD) does not. (2) The SD, CD, and RD of construction enterprises’ SC have a positive influence on KT. (3) There are mediating effects of KT between SC and IP of construction firms, and they are partial. KT plays a partial mediating effect between SD, CD, and IP of construction firms. The research results can not only improve an understanding of effects of SC on IP of construction enterprises, but also validate the importance of KT in stimulating IP.

With digital transformation underway in various Chinese construction enterprises, each enterprise has progressed differently, and a clear direction for future digital transformation and upgrading is lacking. As such, the importance of measuring the level of digitization among Chinese construction enterprises is increasing. This paper presents a model for evaluating digital transformation maturity within construction enterprises. The model considers six aspects: digital strategy, digital business applications, digital technology capabilities, and so on. The digital maturity of enterprises is determined using the Analysis of Hierarchy (AHP)-Decision Making Experiment and Evaluation Laboratory (DEMATEL) method. Technical abbreviations are explained when first used. This study demonstrates that digital business applications are the most significant primary indicator, with a weight of 29.53%. The success of digital transformation in the construction industry is strongly influenced by the interconnection between digital technology and construction sites, as well as other factors such as new technical personnel, digital infrastructure, digital innovation, and innovation iteration ability. It is crucial to understand how digital technology and the construction industry can effectively connect in order to achieve success in this realm. This paper aims to enhance the digital transformation capabilities and efficiency of construction companies and boost their core competitiveness through targeted measures.

Background: Glucocorticoids (GCs) are often used to treat cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). The effects of GCs on the efficacy of CAR-T cell treatment in relapsed/refractory multiple myeloma (RRMM) have not been fully established. We evaluated the impact of GCs on clinical outcomes of RRMM patients treated with CAR-T cells.Methods: This study involved RRMM patients treated with CAR-T cells at our center between June 2017 and December 2020. Patients were stratified into GC-used group (GC-group) and non-GC-used group (NGC-group). CRS or ICANS was graded on the basis of the American Society of Transplantation and Cellular Therapy consensus grading system. Response status was evaluated by the IMWG Uniform Response Criteria. The duration of response (DOR), progression-free survival (PFS), and overall survival (OS) were calculated.Result: A total of 71 patients were included in this study. In the NGC group (40 patients), 34 (85%) had responses to CAR-T cell therapy, including 16 (40%) stringent complete response (sCR), seven (17.5%) complete response (CR), five (12.5%) very good partial response (VGPR), and six (15%) partial response (PR). The overall response rate (ORR) and complete response rate (CRR) in the NGC group were 85% and 57.5%. In the GC group (31 patients), 29 (93.5%) had responses, including 11 (35.5%) sCR, nine (29%) CR, two (6.4%) VGPR, and seven (22.6%) PR. Differences in ORR and CRR between the two groups were insignificant. The dose, duration, and timing of GCs did not affect ORR and CRR. At a median follow-up of 28.2 months, the median PFS was 20.4 months (95% CI, 7.9 to 32.9) while the median OS was 36.6 months (95% CI, 25.9 to 47.2) for the GC group. The median PFS and OS for the NGC group were 13.7 months (95% CI, 8.8 to 18.6) and 27.5 months (95% CI, 14.1 to 41.0). There were no significant differences in either PFS or OS between the GC group and the NGC group. Differences in median DOR for the patients with CR or better in the GC group and NGC group were not significant (p = 0.17). Earlier, prolonged use and high dose of GCs were not associated with any effects on either PFS or OS. Additionally, GCs had no effects on CAR-T cell proliferation.Conclusion: Administration of GCs, dose, timing, and duration does not influence the clinical efficacy of CAR-T cells in RRMM in this study.