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Crowd evacuation simulation using virtual reality (VR) is significant for digital emergency response construction. However, existing evacuation simulation studies suffer from poor adaptation to complex environments, inefficient evacuations, and poor simulation effects and do not fully consider the impacts of specific disaster environments on crowd evacuation. To more realistically express the crowd evacuation results obtained under the influence of fire environments and the subjective consciousness of pedestrians in subway stations, we designed a dynamic pedestrian evacuation path planning method under multiple constraints, analysed the influences of an ‘environmental role’ and a ‘subjective initiative’ on crowd evacuation, established an improved social force model (ISFM)-based crowd evacuation simulation method in VR, developed a prototype system and conducted experimental analyses. The experimental results show that the crowd evacuation time of the ISFM is affected by the disaster severity. In simulation experiments without disaster scenarios, the improved model's crowd evacuation efficiency improved by averages of 12.53% and 15.37% over the commercial Pathfinder software and the original social force model, respectively. The method described herein can effectively support real-time VR crowd evacuation simulation under multiexit and multifloor conditions and can provide technical support for emergency evacuation learning and management decision analyses involving subway fires.

Efficient and intuitive representation of floods can improve people’s perception, which is useful for flood emergency management and decision making. However, the current methods of visualizing flood disaster scenes have the shortcomings of data redundancy and low-efficiency. The interference of the complex background can be avoided through region of interest (ROI) extraction, because the attention will be quickly attracted by a few salient visual objects. First, the characteristics of the flood disaster scene object are analysed, and the method for scene division and data organization is established. Second, the region of interest is extracted according to the time series data of the flood evolution process simulated using cellular automata, and the dynamic identification model of the objects of interest is established. Then, a dynamic scheduling queue model with service interruption is designed to optimize the rendering efficiency of flood scenes and improve the perception efficiency. Finally, a prototype visualization system was developed and the experimental results show that approximately 30% of the redundant data are reduced, and the scene rendering efficiency is increased by approximately 15%. The non-ROI visualization is weakened by using the rules of human visual cognition, which improves the perception efficiency of flood scenes.

Holographic projection technology can provide a more intuitive and efficient visualization effect for a digital twin bridge construction scene. However, pre-rendering methods in the existing research work are usually used to implement holographic visualization, which is static display. The above-mentioned methods for static display have many shortcomings, such as poor adaptability, low rendering efficiency and lack of real-time. A dynamic holographic modelling approach is proposed for the augmented visualization of digital twin scenes for bridge construction. Firstly, a dynamic segmentation algorithm with adaptive screen size was designed to high-efficiently generate holographic scenes. Secondly, a motion blur control method was designed to improve the rendering efficiency of holographic scenes according to human visual characteristics. Finally, a prototype system was developed, and the corresponding experimental analysis was completed. The experimental results show that the method proposed in this article can support adaptive screen size image segmentation and real-time generation of holographic scenes for bridge construction. The amount of scene data can be reduced to more than 30%, which significantly improves rendering efficiency and reduces glare.

Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies.

This paper introduces the fractional Fourier series on the fractional torus and proceeds to investigate several fundamental aspects. Our study includes topics such as fractional convolution, fractional approximation, fractional Fourier inversion, and the Poisson summation formula. We also explore the relationship between the decay of its fractional Fourier coefficients and the smoothness of a function. Additionally, we establish the convergence of the fractional Féjer means and Bochner–Riesz means. Finally, we demonstrate the practical applications of the fractional Fourier series, particularly in the context of solving fractional partial differential equations with periodic boundary conditions, and showcase the utility of approximation methods on the fractional torus for recovering non-stationary signals.

Over the past decade, prefabricated construction has increasingly gained popularity in addressing environmental concerns while meeting the high construction demand, particularly in developing countries. Accordingly, the concept of stakeholder engagement increasingly garnered attention as it is highly relevant for understanding and explaining the relationships among various stakeholders, like contractors, suppliers, and producers, especially within the fragmented context of prefabrication. To further the field, this study aims to provide a comprehensive qualitative and quantitative analysis for stakeholder engagement in the realm of prefabricated construction via a value-based network. This value-based network analysis is utilized to model multiple relationships between stakeholders as value exchanges, thus enabling to engage them though management with a focus. Specifically, A total of 110 values were identified and analyzed among 12 stakeholders throughout the whole lifecycle via an extensive literature review, interviews, and questionnaires directed at prefabrication practitioners in China. This data collection process garnered 194 valid responses with a 64.7% response rate. The findings show that enhancing stakeholder engagement requires improvements in both the abilities and experiences of developers, and in the collaborative relationships among key stakeholders. These improvements can be achieved by prioritizing the engagement of prefabrication consultants and encouraging the government to issue policies that support developers, producers, and consultants in fostering collaboration. This in-depth network analysis offers practical insights for decision-makers in the management of core stakeholders and value-based relationships, thereby improving stakeholder engagement. Additionally, it expands the current body of knowledge on stakeholder engagement by incorporating the value-based network analysis into the exploration of its stakeholders and relationships.

As an important technology of digital construction, real 3D models can improve the immersion and realism of virtual reality (VR) scenes. The large amount of data for real 3D scenes requires more effective rendering methods, but the current rendering optimization methods have some defects and cannot render real 3D scenes in virtual reality. In this study, the location of the viewing frustum is predicted by a Kalman filter, and eye-tracking equipment is used to recognize the region of interest (ROI) in the scene. Finally, the real 3D model of interest in the predicted frustum is rendered first. The experimental results show that the method of this study can predict the frustrum location approximately 200 ms in advance, the prediction accuracy is approximately 87%, the scene rendering efficiency is improved by 8.3%, and the motion sickness is reduced by approximately 54.5%. These studies help promote the use of real 3D models in virtual reality and ROI recognition methods. In future work, we will further improve the prediction accuracy of viewing frustums in virtual reality and the application of eye tracking in virtual geographic scenes.

Background and aimsPatients with cirrhosis commonly experience minimal hepatic encephalopathy (MHE), and alterations in neurotransmitters have been thought to be related to cognitive function. However, the relationship between alterations in peripheral and central butyrylcholinesterase (BuChE) with MHE disease progression remains unknown. As such, this study was designed to investigate potential changes in peripheral and central BuChE activity and their effects on cognitive function in the context of MHE.Materials and methodsWe enrolled 43 patients with cirrhosis secondary to hepatitis B, 20 without MHE and 23 with MHE, and 25 with healthy controls (HC). All the selected subjects underwent resting-state functional MRI, and the original images were processed to obtain the regional homogeneity (ReHo) brain maps. Thereafter, the correlation of BuChE activity with ReHo, number connection test of type A (NCT-A), and digital symbol test (DST) scores with MHE patients were analyzed using Person correlation analysis. Meanwhile, we purchased 12 Sprague-Dawley (SD) rats and divided them into an experimental group (n = 6) and a control group (n = 6). The rats in the experimental group were intraperitoneally injected with thioacetamide (TAA) to prepare MHE model rats. After modeling, we used the Morris water maze (MWM) and elevated plus maze (EPM) to assess the cognition function and exploratory behavior of all rats. The activity of serum, hippocampus, and frontal lobe tissue BuChE was detected by ELISA.ResultsBuChE activity gradually decreased among the HC, patients with cirrhosis, and MHE groups (all P < 0.01). We observed a linear correlation between serum BuChE and NCT-A and DST scores in MHE patients (all P < 0.01). We noted that BuChE activity can negatively correlate with ReHo values in the left middle temporal gyrus and left inferior temporal gyrus, and positively correlate with ReHo values in the right inferior frontal gyrus, and also found that the peripheral BuChE activity of MHE rats was significantly lower than their control counterparts, and the BuChE activity in frontal lobe extracts was significantly higher than the control rats (all P < 0.05).ConclusionThe altered activity of BuChE may contribute to cognitive impairment in MHE patients, which may be a potential biomarker of disease evolution in the context of MHE.

The BeiDou navigation satellite system (BDS) provides precise positioning, navigation, and timing (PNT) services in the Asia-Pacific Region, but the BDS-based structural health monitoring (SHM) approach (SHM) is rarely studied, especially in civil engineering. Moreover, how BDS can be applied to complete the tasks of SHM in a real project is also not fully investigated, especially working in conjunction with other techniques. This study aims to propose a BDS-based approach for SHM in civil engineering. The performance of the proposed approach is investigated through a case study—the Tianhan Grand Theater (TGT). A specific Tianhan system corresponding to BDS is proposed to complete the SHM tasks of TGT. Based on the collected data, the trusses with maximum displacement and stress are found by BDS to evaluate structural health in the construction stage. The results show that the maximum displacement and stress have certain safety reserves and meet the requirements of the specifications and regulations. Thus, BDS can satisfactorily complete the tasks of SHM for Long-span steel structures. This study gives a clear view to engineers and researchers that how to apply BDS in structural construction and provides a valuable real case for evaluating the performance of BDS in SHM.

The visualization of flood disasters in virtual reality (VR) scenes is useful for the representation and sharing of disaster knowledge and can effectively improve users’ cognitive efficiency in comprehending disaster information. However, the existing VR methods of visualizing flood disaster scenes have some shortcomings, such as low rendering efficiency and poor user experience. In this paper, a tunnel vision optimization method for VR flood scenes based on Gaussian blur is proposed. The key techniques are studied, such as region of interest (ROI) calculation and tunnel vision optimization considering the characteristics of the human visual system. A prototype system has been developed and used to carry out an experimental case analysis. The experimental results show that the number of triangles drawn in a flood VR scene is reduced by approximately 30%–40% using this method and that the average frame rate is stable at approximately 90 frames per second (fps), significantly improving the efficiency of scene rendering and reducing motion sickness.

Prefabricated construction (PC) is considered as a sustainable construction mode that can improve project performance such as quality and efficiency. Even though, Chinese governments at different levels have formulated many guidelines and incentives to help construction firms better implement PC, their implementing PC level is still low. To some extent, this is likely attributed to ineffective measures of improving PC projects' performance for construction firms lacking adequate understanding of their PC development level and corresponding influencing factors. Furthermore, there are relatively scant research works exploring the issue. Thus, this study aims to formulate a PC maturity model that can be used to evaluate the PC development level of construction firms. It is also expected that this model can identify the key factors that influence the development maturity. The model is firstly established using a four-step methodology, namely, maturity dimension determination, maturity-associated criteria identification, criteria weights calculation based on Entropy and Fuzzy Analytical Hierarchy Process (FAHP), and maturity level evaluation based on fuzzy integral. Next, three construction firms are selected as study cases to test the model's effect on mapping out PC maturity and key influencing factors. Key findings are eventually analysed to derive effective strategies for improving the maturity of construction firms, further expediting the sustainable transition of the construction sector into PC.

Large-scale crowd evacuation simulation in virtual reality is of great significance for emergency response. However, the existing large-scale crowd evacuation simulation methods are challenging to apply to the virtual reality scene. Thus, the efficiency of large-scale crowd rendering in virtual reality needs to be improved. Here we proposed a chain navigation grid for virtual reality large-scale crowd evacuation simulation. The objective of this study was to apply traditional cellular automata crowd evacuation simulation algorithms to virtual reality scenes through a chain navigation grid. Combined with the characteristics of crowd movement, we proposed the vertex raster rendering method to efficiently visualize large-scale crowds in virtual reality scenes. Finally, we constructed two evacuation scenes and carried out experimental analyses. The results show that the chain evacuation navigation grid can transform the discrete crowd movement of cellular automata into continuous crowd movement in virtual reality and can connect multiple cellular automata corresponding to multi-floors. Compared with the evacuation results of Pathfinder software, the chain evacuation navigation can add the factor of environmental familiarity. Therefore, this study improved evacuation simulation by increasing about 6% efficiency in time and computing process. Compared with the traditional crowd evacuation rendering method, the vertex raster rendering method increases the maximum number of people rendering from 2 times to 31 times.

Abstract In this article, we study some Riemann–Hilbert problems with shift on the Lyapunov curve for generalized polyanalytic functions, which are null-solutions of a class of iterated Beltrami equations. Firstly, we obtain two integral representations of these functions by using Cauchy formula associated with the Beltrami equations and explicitly constructing two weakly singular kernels. Next, we develop a theory of matrix factorization for triangular matrix functions with shift in the frame of Beltrami equations and solve the Riemann–Hilbert problems by using them and the decomposition theorem for the iterated Beltrami equations. Finally, we get explicit formulae of solutions and conditions of solvability for the Riemann–Hilbert problems.

The rapid acquisition of deposit volume information and dynamic modeling, as well as the visualization of disaster scenes, have great significance for the sharing of landslide information and the management of emergency rescue. However, existing methods have shortcomings, such as a long and costly deposit volume acquisition cycle, lack of knowledge and guidance, complex operations for scene modeling expression, and low scene rendering efficiency. Therefore, this paper focuses on the study of a three-dimensional visualization and optimization method for landslide disaster scenes guided by knowledge, and discusses key technologies such as the rapid acquisition of landslide deposit volume information based on three-dimensional reconstruction, the knowledge-guided dynamic modeling visualization of disaster scenes, and scene optimization considering visual significance. The prototype systems are developed and used in a case experiment and analysis. The experimental results show that the proposed method can quickly obtain the deposit volume, and the results are equivalent to ContextCapture, Metashape, and Pix4Dmapper software. The method realizes the dynamic visualization of the whole disaster process, provides rich information, achieves high readability, and improves the efficiency of scene rendering, with a stable average rendering frame rate of more than 80 frames/second.

In this paper, we revisit some fundamental properties of linear canonical transform (abbreviated as LCT). In particular, we prove the additive property rigorously for LCT in the higher dimensional case (abbreviated as MLCT). We also consider the Lp-theory of MLCT with 1 ≤ p ≤ 2. Specifically, the inversion theorem of MLCT by the related Gauss and Abel means is studied, and the pointwise convergence of approximate identities with respect to convolution for MLCT is also obtained. As applications, we study the Lp-type Heisenberg-Pauli-Weyl uncertainty principles and the Lp-type Donoho-Stark uncertainty principles for MLCT. [ABSTRACT FROM AUTHOR]