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Although authoritarian leadership (AL) behaviour is critical to organisational performance, its impact in different cultural contexts has received scant academic attention especially for managing bespoke projects which require temporary organisations to be formed. Drawing from self-determination and expectancy theories, this present research develops an integrated model to interpret the underlying impacts that the two dichotomous groups of ALs (i.e. discipline- and dominance-focused) have on project team members' task and innovative performance in China. The model developed was tested using the data collected from 316 Chinese project team members. Empirical evidence indicates that psychological empowerment acts as a ‘mediator’ via which the discipline- and dominance-focused ALs can positively and negatively affect the team members' task and innovative performance respectively. Additionally, the aforementioned indirect relationships are moderated by outcome expectancy, implying a positive interdependency between them. This research enriches an understanding of ALs and project team in terms of task completion and innovation and is useful for developing interventions to improve project team performance.

Abstract Background There are many options for the surgical treatment of pronation external rotation (PER) type IV ankle fractures, including the use of fibular plates and screws, the aim of this study was to investigate the biomechanical stability and safety of different internal fixation methods for PER type IV ankle fractures via finite element analysis. Methods A three-dimensional finite element model of the ankle joint and the whole foot of a healthy 26-years-old adult male was established and validated based on computed tomography images of his lower limb, and a computer-aided design was used to produce a PER type IV ankle fracture and plate and screw model. Four different internal fixation modes were simulated, including a (all ankle fixation—utilizing a fibular plate and screws for comprehensive stabilization of the ankle), b (inferior tibiofibular joint fixation + all ankle fixation), c (inferior tibiofibular joint fixation + unfixed anterior ankle), and d (inferior tibiofibular joint fixation + unfixed anterior and posterior ankles). The results of the four different fixation methods were compared via finite element analysis, and the von Mises stresses. The displacements of the four different fixation methods were analyzed as the output indices. Results There were no significant differences between the results of using fibular plates and screws and the displacement of fracture breaks among the four internal fixation modalities. The von Mises stress in the tibiotalar joint, median ankle, posterior ankle, and anterior ankle was minimized in the working condition of d, d, b, and d respectively. The von Mises stress in the fibular plate and screws was minimized in the working condition of a. The von Mises stress in the distal fibula was minimized in the working condition of a. However, the stress was mainly concentrated at the attachment point of the inferior tibiofibular anterior ligament, and in the working condition with inferior tibiofibular joint fixation, the stress was significantly concentrated in the inferior tibiofibular joint screw in all the fibular plates and screws. Conclusions The results of this study demonstrate the feasibility of using finite element analysis to compare the biomechanical stability and safety of four configurations of fibular plates and screws for treating PER type IV ankle fractures. All four modalities provided comparable biomechanical stability and safety, showing no significant differences. However, the current limitations of the finite element analysis methodology preclude specific clinical inferences. Further refinement of the methodology in future studies is necessary to enable reliable clinical applications.

Abstract The COVID-19 pandemic has undermined the ability of many countries to achieve the Sustainable Developments Goals (SDGs) by 2030. Here, we systematically assess the likely impacts of the pandemic on progress towards each SDG by 2030 at global, regional and national scales. In our analysis, we account for the social and economic shocks triggered by COVID-19 and their relative impacts on the SDGs. We also analyze the interconnections between SDG indicators during the pandemic to assess the indirect cascading effects of COVID-19 on the SDGs. We find that these indirect effects slowed progress much more than the direct initial disruptions. Globally, poverty eradication (SDG 1) is most affected by the pandemic. Regionally, SDG progress has been set back most in Latin America and the Caribbean, South Asia, the Middle East and North Africa and Sub-Saharan Africa. We suggest that for high and upper-middle-income countries a focus on reducing inequality (SDG 10) would be most beneficial, whereas for low-income and lower-middle-income countries industry, innovation, and infrastructure (SDG 9) are a priority in the post-COVID-19 phase.

A pipeline robot suitable for miniature pipeline detection, namely π-II, was proposed in this paper. It features six wheel-leg mobile mechanisms arranged in a staggered manner, with a monocular fisheye camera located at the center of the front end. The proposed robot can be used to capture images during detection in miniature pipes with an inner diameter of 120 mm. To efficiently identify the robot’s status within the pipeline, such as navigating in straight pipes, curved pipes, or T-shaped pipes, it is necessary to recognize and classify these specific pipeline landmarks accurately. For this purpose, the residual network model ResNet18 was employed to learn from the images of various pipeline landmarks captured by the fisheye camera. A detailed analysis of image characteristics of some common pipeline landmarks was provided, and a dataset of approximately 908 images was created in this paper. After modifying the outputs of the network model, the ResNet18 was trained according to the proposed datasets, and the final test results indicate that this modified network has a high accuracy rate in classifying various pipeline landmarks, demonstrating a promising application prospect of image detection technology based on deep learning in miniature pipelines.

Summary: Background: Racial/ethnic disparities in prostate cancer are reported in the United States (US). However, long-term trends and contributors of racial/ethnic disparities in all-cause and cause-specific death among patients with prostate cancer remain unclear. We analysed the trends and contributors of racial/ethnic disparities in prostate cancer survivors according to the cause of death in the US over 25 years. Methods: In this retrospective, population-based longitudinal cohort study, we identified patients diagnosed with first primary prostate cancer between 1995 and 2019, with follow-up until Dec 31, 2019, using population-based cancer registries’ data from the Surveillance, Epidemiology, and End Results (SEER) Program. We calculated the cumulative incidence of death for each racial/ethnic group (Black, white, Hispanic, Asian or Pacific Islander [API], and American Indian or Alaska Native [AI/AN] people), by diagnostic period and cause of death. We quantified absolute disparities using rate changes for the 5-year cumulative incidence of death between racial/ethnic groups and diagnostic periods. We estimated relative (Hazard ratios [HR]) racial/ethnic disparities and the percentage of potential factors contributed to racial/ethnic disparities using Cox regression models. Findings: Despite a decreasing trend in the cumulative risk of death across five racial/ethnic groups, AI/AN and Black patients consistently had the highest rate of death between 1995 and 2019 with an adjusted HR of 1.48 (1.40–1.58) and 1.40 (1.38–1.42) respectively. The disparities in all-cause mortality between AI/AN and white patients increased over time, with adjusted HR 1.32 (1.17–1.49) in 1995–1999 and 1.95 (1.53–2.49) in 2015–2019. Adjustment of stage at diagnosis, initial treatment, tumor grade, and household income explained 33% and 24% of the AI/AN-white and Black-white disparities in all-cause death among patients with prostate cancer. Interpretation: The enduring racial/ethnic disparities in patients with prostate cancer, call for new interventions to eliminate health disparities. Our study provides important evidence and ways to address racial/ethnic inequality. Funding: National Key R&D Program of China, National Natural Science Foundation of China, Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support, the Open Research Fund from Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Key Projects of Philosophy and Social Sciences Research, Ministry of Education of China.

Climate change is the main cause of frequent extreme weather and natural disasters. Therefore, effective climate adaptation strategies for urban rail transit (URT) should be adopted to cope with extreme precipitation events (EPEs). This study proposes a decision-making model based on climate change for drainage renovation, which consists of an optimal renovation sequence model and an optimal investment timing model. This study analyzes the inundation risk of each station and its node importance in the URT network and then uses a multi-attribute decision analysis (MADA) to determine the optimal renovation sequence. This study also uses a real options pricing approach to calculate the value of an option in order to defer the renovation project and determine the optimal investment timing. Then, the Beijing Urban Rail Transit (BURT) is taken as an example to conduct an empirical analysis of the proposed model. Considering the uncertainty of climate change and the complexity of the URT network, the model can obtain the optimal renovation sequence and the investment timing of each station, which is expected to provide a decision-making tool for urban governments to formulate an optimal plan that strengthens the prevention of flooding disasters.

Abstract Achieving the Sustainable Development Goals (SDGs) is a long-term task, which puts forward high requirements on the sustainability of related policies and actions. Using the text analysis method, we analyze the China National Sustainable Communities (CNSCs) policy implemented over 30 years and its effects on achieving SDGs. We find that the national government needs to understand the scope of sustainable development more comprehensively, the sustained actions can produce positive effects under the right goals. The SDGs selection of local governments is affected by local development levels and resource conditions, regions with better economic foundations tend to focus on SDGs on human well-being, regions with weaker foundations show priority to basic SDGs on the economic development, infrastructures and industrialization.

Residents’ willingness to cooperate can contribute to the success of urban regeneration projects worldwide. However, limited research has explored factors determining residents’ willingness to cooperate with neighborhood regeneration projects. This study aims to investigate the influence of psychological factors on urban residents’ willingness to comply with neighborhood regeneration projects. To achieve this goal, the study extends the theory of planned behavior by specifying the effects of perceived benefit, perceived risk, and perceived fairness on residents’ compliance intention toward neighborhood regeneration projects. Data from 362 local residents (i.e., homeowners) in China were analyzed using partial least squares structural equation modeling. Results show that perceived benefit, perceived risk, and perceived fairness have significant effects on the attitude, subjective norm, and perceived behavioral control, which in turn enhance residents’ compliance intention toward neighborhood regeneration projects. In addition, perceived benefit and perceived fairness also exhibit direct positive effects on residents’ compliance intention. This study develops an enriched model to examine the forming mechanisms of residents’ compliance intention under the context of neighborhood regeneration. It also provides more insights to enhance the decision-making regarding strategies of urban regeneration toward better social sustainability. Specifically, measures should be implemented to increase residents’ subjective norm, perceived behavioral control, and benefit perception. It is also recommended to foster a favorable attitude and to facilitate fairness perceptions of residents.

New Infrastructure (NI) has gradually become a new driving force for regional economic growth and an important part of the construction of new urban infrastructure in many countries, including China. Compared with traditional infrastructures, these NIs have mutually supportive functions and complex interrelationships that create interconnected networks of resources, information, and other interactions during the construction of the NIs. Therefore, it is important to analyze such correlation networks and explore their formation mechanisms in order to develop more scientific and reasonable strategies for NI investment and construction. In this study, the interdependence between NIs in Chongqing was analyzed as an example. Social network analysis (SNA) was used for the overall characteristics of the interdependency network of the NIs and an exponential random graph model (ERGM) was used to reveal the formation mechanism of this network. The results showed that information infrastructure is the key node for enhancing the effectiveness of Chongqing’s NI needs and its government should play a coordinating role. The network of related relationships is characterized by “reciprocity” and “small group”. The aggregation of NIs with such characteristics can produce an agglomeration effect. So, in the planning of NIs, the coordination among management departments should be strengthened and project locations should be reasonably arranged according to the functional interactive characteristics of the projects.

Project delivery systems (PDSs) selection is crucial to construction project management success. The matching between construction projects and PDSs is hypersensitive to project external environment. Existing studies on selecting PDSs mainly focus on owner’s and project’s characteristics and attach less attention to project environmental factors. This study, therefore, aims to formally identify key project external environmental factors affecting PDSs selection using a data-driven approach. Key factors are summarized and identified through the granular computing method based on 61 Chinese project samples. Empirical results indicate that four factors including market competitiveness, technology accessibility, material availability, and regulatory impact are critical to PDSs selection. This study extended previous research findings on PDSs selection from a perspective of project external environments. Research conclusions can be used as references underpinning construction owners selecting appropriate PDSs considering project external environmental factors.