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This paper comprehensively investigates the lack of youth involvement in the intricate tapestry of urban policymaking in the Jordanian context. It attempts to present and illustrate the obstacles, challenges, hindrances and complexities facing engaging youth in urban planning in Jordan. Participants aged 18–24 were the primary focus of the investigation, as Jordan's population is predominantly youthful, with approximately 70% of the population under the age of 30.

The research methodology adopted in this study is a mixed-methods approach, which integrates both qualitative and quantitative data collection and analytical techniques to provide a comprehensive and nuanced understanding of the research problem.

Youth involvement in Jordan's urban policymaking is limited and inconsistent. Most notably, the prevalence of adultism emerges as the predominant and most substantive impediment, exerting a considerable influence on constraining the agency of young Jordanians in shaping urban policy.

Detailed examples can be developed to offer discerning elucidations relevant to each frame of reference.

A total of 12 discernible barriers emerged from a systematic deductive thematic analysis of primary data.

This comprehensive inquiry highlights the pervasive gaps in support for youth participation in urban policymaking within the administrative framework and across Jordanian society. Subsequent quantitative analysis was employed to strengthen the external validity of the research findings, thereby enhancing the generalizability of the qualitative insights. By employing Jordan as a case study, this paper significantly contributes to the expanding corpus of scholarly work on planning processes and practices within the Global South and the Arab world.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.

Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.

Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.

This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.

Appendix A outlines the general structure of a FIDIC based contract and introduces the documents require to form a functional contract. The main documents are the Contract Agreement, the Particular Conditions Parts A (Contract Data) and B (Special Provisions), the General Conditions, the Employer’s Requirements, and the Schedules (including the Schedule of Payments). The minimum requirements for each of the main documents are outlined. Appendix A also includes an overview of the Employer’s main risks and the Contractor’s corresponding entitlements.

Clause 7 deals with the quality of the Contractor’s work, the Engineer’s verification thereof, remedies if the Contractor’s work is not in accordance with the Contract and some additional provisions on ownership and royalties. The quality assurance systems referred to in Sub-Clause 4.9 [Quality Management and Compliance Verification Systems] must be aligned with the provisions of this Clause; some elements of this Clause may be replaced in full by the QM Systems envisaged in Sub-Clause 4.9.

This Clause outlines the procedures for adding or omitting work, as well as other situations where the price to be paid by the Employer is to be adjusted. Variations may be initiated either directly by instructions from the Engineer or by a Request for Proposal where the Contractor is to prepare and submit a proposal which then forms basis for the Variation procedure. See Sub-Clause 13.3 [Variation Procedure]. Variations may have an impact on the Contract Price as well as on the Time for Completion and other elements of the Contract, see Sub-Clause 13.3 [Variation Procedure].

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.

With around 40% of global waste attributed to the built environment sector, architects play a significant role in how resources are consumed, produced and wasted. UK architectural educators have made good progress to embed climate emergency issues in design curricula but the challenges of resource use and waste, and the opportunities afforded by circular economy design principles are less well-considered. The purpose of this paper is to provide new insights on how to introduce circular design principles to early-stage architectural design students within university curricula.

The study described took an experimental approach to designing design project briefs across several interlinked studio design projects for 1st-year Architecture students. Structured as a case study, each section describes the project, learning objectives, teaching methods and project reflections informed by a qualitative assessment of student development, outputs and feedback gathered through a questionnaire and focus group.

Introducing circular design early is highly beneficial to the development of knowledge on sustainability issues, critical design thinking and creative solution generation. Examples of beneficial teaching approaches include building systems thinking, facilitating collaboration, supporting learning-through-making, using simple analogies and referencing best-practice examples.

This research builds on limited existing circular design literature for built environment fields and through practical insights fills a significant knowledge gap on ways to introduce a complex and dynamic topic such as the circular economy to early-stage architectural design students as they develop fundamental discipline-specific knowledge, skills and competences.

This paper analyzes the ways in which accounting enables operations managers to enter and perform multiple roles in their interplay with organizational groups on the shop floor and in management, and the associated negotiations that operations managers have with “the self.”

Using field-based studies in a mining organization, the study draws on Goffman’s backstage–frontstage metaphor to analyze how operations managers enter and perform several roles with the aid of accounting.

The findings show that accounting legitimizes operations managers when they cross organizational boundaries, as accounting gives them an “entry ticket” that legitimizes their presence with the group. Accounting further allows operations managers to embrace more than one role by “putting on a mask” to become an outsider or insider in relation to a group. In performing their roles, operations managers exhibit varying attributes and knowledge. Accounting can thereby be withheld from, or shared with, organizational groups. The illusion of accounting as deterministic presented frontstage is not necessarily negotiated that way backstage. Rather, alternatives discussed backstage often become silenced in the frontstage performance. The study concludes that operations managers cross boundaries, embrace roles and exert agency as they navigate with accounting, enrolling it into their performance simultaneously as they backstage reflect upon accounting and its role for their everyday work.

This study relies on the frontstage/backstage metaphor to visualize the discrepancies in how accounting is enrolled into role performances and how seemingly categorical fronts do not necessarily share that dominant position backstage.