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Clarifying the relationship between building carbon emissions and economic development can help sustainable construction in the field of construction, and this paper provides a constructive suggestion for ensuring economic development while realizing energy efficiency and emission reduction in buildings.

The study focuses on the building sector and firstly analyzes the complex relationship between economic agglomeration (EA) and carbon emission intensity (CEI) of commercial buildings at the city level through the spatial Durbin model and the threshold effect model, and then discusses the regional heterogeneity of this complex relationship from the dimensions of economic density and climate zones, respectively, and finally analyzes in depth the intrinsic influencing mechanism of EA on the CEI of commercial buildings.

The authors found that (1) there is an inverted U-shaped nonlinear relationship between EA and CEI of commercial buildings, and the inflection point of the EA level is 2.42, i.e. 1.125 bn RMB/km². (2) Significant regional differences exist in the inverted U-shaped relationship for cities with different economic densities and cities in different climate zones. (3) EA mainly affects the CEI of commercial buildings through externalities such as commercial building size and tertiary industry share, of which commercial building size is the most important factor hindering the decoupling of urban economic development from the CEI of commercial buildings.

This paper discusses for the first time the relationship between economic development and carbon emissions at the city level and clarifies the spatial differences and influencing mechanism of this relationship, providing a fuller reference for policymakers to develop differentiated building energy efficiency and emission reduction strategies.

The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap between the main bridge and the approach bridge. For long-span railway bridges, it must also be coordinated with rail expansion joint (REJ), which is necessary to accommodate the expansion and contraction of, and reducing longitudinal stress in, the rails. The main aim of this study is to present analysis of recent developments in the research and application of BEJs in high-speed railway (HSR) long-span bridges in China, and to propose a performance-based integral design method for BEJs used with REJs, from both theoretical and engineering perspectives.

The study first presents a summary on the application and maintenance of BEJs in HSR long-span bridges in China representing an overview of their state of development. Results of a survey of typical BEJ faults were analyzed, and field testing was conducted on a railway cable-stayed bridge in order to obtain information on the major mechanical characteristics of its BEJ under train load. Based on the above, a performance-based integral design method for BEJs with maximum expansion range 1600 mm (±800 mm), was proposed, covering all stages from overall conceptual design to consideration of detailed structural design issues. The performance of the novel BEJ design thus derived was then verified via theoretical analysis under different scenarios, full-scale model testing, and field testing and commissioning.

Two major types of BEJs, deck-type and through-type, are used in HSR long-span bridges in China. Typical BEJ faults were found to mainly include skewness of steel sleepers at the bridge gap, abnormally large longitudinal frictional resistance, and flexural deformation of the scissor mechanisms. These faults influence BEJ functioning, and thus adversely affect track quality and train running performance at the beam end. Due to their simple and integral structure, deck-type BEJs with expansion range 1200 mm (± 600 mm) or less have been favored as a solution offering improved operational conditions, and have emerged as a standard design. However, when the expansion range exceeds the above-mentioned value, special design work becomes necessary. Therefore, based on engineering practice, a performance-based integral design method for BEJs used with REJs was proposed, taking into account four major categories of performance requirements, i.e., mechanical characteristics, train running quality, durability and insulation performance. Overall BEJ design must mainly consider component strength and the overall stiffness of BEJ; the latter factor in particular has a decisive influence on train running performance at the beam end. Detailed BEJ structural design must stress minimization of the frictional resistance of its sliding surface. The static and dynamic performance of the newly-designed BEJ with expansion range 1600 mm have been confirmed to be satisfactory, via numerical simulation, full-scale model testing, and field testing and commissioning.

This research provides a broad overview of the status of BEJs with large expansion range in HSR long-span bridges in China, along with novel insights into their design.

Integrating artificial intelligence and quantitative investment has given birth to various agricultural futures price prediction models suitable for nonlinear and non-stationary data. However, traditional models have limitations in testing the spatial transmission relationship in time series, and the actual prediction effect is restricted by the inability to obtain the prices of other variable factors in the future.

To explore the impact of spatiotemporal factors on agricultural prices and achieve the best prediction effect, the authors innovatively propose a price prediction method for China's soybean and palm oil futures prices. First, an improved Granger Causality Test was adopted to explore the spatial transmission relationship in the data; second, the Seasonal and Trend decomposition using Loess model (STL) was employed to decompose the price; then, the Apriori algorithm was applied to test the time spillover effect between data, and CRITIC was used to extract essential features; finally, the N-Beats model was selected as the prediction model for futures prices.

Using the Apriori and STL algorithms, the authors found a spillover effect in agricultural prices, and past trends and seasonal data will impact future prices. Using the improved Granger causality test method to analyze the unidirectional causality relationship between the prices, the authors obtained a spatial effect among the agricultural product prices. By comparison, the N-Beats model based on the spatiotemporal factors shows excellent prediction effects on different prices.

This paper addressed the problem that traditional models can only predict the current prices of different agricultural products on the same date, and traditional spatial models cannot test the characteristics of time series. This result is beneficial to the sustainable development of agriculture and provides necessary numerical and technical support to ensure national agricultural security.

China has recently introduced a new audit law that aims to increase the scope of audit supervision and raise the standards for preventing risks in auditing national public projects. This paper presents a systematic research study on the causes of audit risks in national public projects and discusses the process by which these causes contribute to the emergence of such risks. Furthermore, the paper investigates the core risk sources in various types of national construction project audit. This paper aims to provide theoretical support for auditors of national construction projects in risk avoidance when conducting audits.

In this study, the authors carefully selected five national public audit projects from China and performed a comprehensive analysis of 85 relevant audit documentation. The textual analysis was conducted using Nvivo12 software, and the grounded theory approach was adopted for generalization purposes.

Based on the research results, the findings suggest that there are five key causes contributing to the audit risk of national construction projects: professional competence, risk awareness, management capacity, level of attention and deliberate fraud. The most critical factor identified is management capability, with 59.93% of the data supporting this view. This conclusion was based on an analysis of state-owned enterprises, administrative organs and public institutions. Building upon this, a framework titled “the mechanism of audit risk factors with management capability as the core” was constructed.

This paper employs qualitative analysis methods to examine national construction projects in China, contributing new literature to the theoretical study of audit risk management. The article also provides practical recommendations for auditors on how to mitigate audit risks and improve the quality of audit services in national project governance.