Background/Objectives: Given the complex nature of Anterior Cruciate Ligament (ACL) injury, it is important to analyze its etiology with suitable approaches in order to formulate intervention strategies for effective prevention. The present study employs system thinking techniques to develop a Causal Loop Diagram (CLD) Model for investigating the risk factors for ACL Injury (CLD-ACLI), through a Group Model Building approach. Methods: A two-stage procedure was applied involving a comprehensive literature review followed by several systems thinking group-modeling co-creation workshops with stakeholders. Results: Based on input from experts and stakeholders, combined with the latest scientific findings, the derived CLD-ACLI model revealed a series of interesting complex nonlinear interrelationships causal loops between the likelihood of ACL injury and the number of risk factors. Particularly, the interaction among institutional, psychological, neurocognitive, neuromuscular, malalignment factors, and trauma history seem to affect neuromuscular control, which subsequently may alter the biomechanics of landing, predisposing the ACL to injury. Further, according to the proposed CLD-ACLI model, the risk for injury may increase further if specific environmental and anatomical factors affect the shear forces imposed on the ACL. Conclusions: The proposed CLD-ACLI model constitutes a rigorous useful conceptual presentation agreed upon among experts on the dynamic interactions among potential intrinsic and extrinsic risk factors for ACL injury. The presented causal loop model constitutes a vital step for developing a validated quantitative system dynamics simulation model for evaluating ACL injury-prevention strategies prior to implementation.

It is essential to systematically consider social, economic, and natural endowments in managing and allocating water resources. However, few studies have comprehensively quantitatively evaluated the allocation of regional water resources from a socio-hydrology perspective and provided recommendations. To explore this research gap, we have constructed a tightly coupled framework that integrates system dynamics models and optimization algorithms to carry out an innovative redistribution of water resources in Shaanxi Province. The system dynamics model simulation results showed that the error was almost always within 10% over the research period, indicating robust simulation capability and laying a solid foundation for subsequent model coupling. The coupled model achieves convergence in approximately 30 generations by formulating the optimization problem with four individual objectives. Optimizing four objectives concurrently results in convergence around the 150th generation. The optimized Pareto solution sets visually demonstrate the trade-offs between different objectives. In the optimized water allocation schedule, the water consumption in Yulin exhibits a change of 1.22 ×108m3, reflecting the most significant optimization effects on agricultural and domestic water allocation. The results indicated that the comprehensive Gini coefficient typically ranged between 0.2 and 0.3. Over the period from the year 2010-2021, the Gini coefficient exhibited a declining trend, signifying a positive trajectory in water resource allocation throughout the research period and a high level of fairness. The annual total green WF of grain in Weinan was the highest at 14.26 ×108m3, followed by Xianyang at 9.52 ×108m3, and the lowest in Tongchuan at 0.54 ×108m3. The annual average amount of blue WF of grain is the highest in Hanzhong, at 11.33 ×108m3, followed by Weinan at 9.60 ×108m3, and the lowest in Tongchuan at 0.14 ×108m3. The coupled framework proposed in this study exhibits significant innovation, scalability, and practical efficiency. It can inspire future research and decision-making and holds the potential for application in other regions.

Marginal cost curves (MCCs) are popular decision-support tools for assessing and ranking the cost-effectiveness of different options in environmental policy and management. However, conventional MCC approaches have been criticized for lack of transparency and disregard for complexity; not accounting for interaction effects between measures; ignoring ancillary benefits and costs; and not considering intertemporal dynamics. In this paper, we present an approach to address these challenges using a system dynamics (SD)-based model for producing dynamic MCCs. We describe the approach by applying it to evaluate efforts to address water scarcity in a hypothetical, but representative, Swedish city. Our results show that the approach effectively addresses all four documented limitations of conventional MCC methods. They also show that combining MCCs with behavior-over-time graphs and causal-loop diagrams can lead to new policy insights and support a more inclusive decision-making process.

Research focusing solely on the carrying capacity of a single aspect of water resources, water environment, or water ecology is no longer sufficient to support the sustainable development and management of basin water systems. The study of basin carrying capacity should expand towards a comprehensive and holistic direction. Therefore, this study constructed an evaluation index system for carrying capacity based on water resources, water environment, and water ecology (\"Three Waters\"). Utilizing the entropy weight-TOPSIS method, System Comprehensive Index Evaluation, and ArcGIS tools, the comprehensive evaluation index of the \"Three Waters\" System Carrying Capacity (TWSCC) in the Yellow River Basin (YRB) from 2005 to 2020 was calculated. The evaluation index analyzed the spatiotemporal variation characteristics of subsystem carrying capacity and performed early warning identification and analysis of TWSCC. Four differentiated developmental pathways were designed based on the current status of basin carrying capacity. Leveraging System Dynamics (SD) modeling, the dynamic simulation, and emulation of carrying capacity trends in the YRB from 2020 to 2035 were conducted. The research findings indicate that from 2005 to 2020, the TWSCC levels across the nine provinces in the YRB consistently exhibited varying degrees of overload. The alert levels mostly remained in \"Heavy warning\" or \"Medium warning\" states. By 2035, TWSCC under the four development paths improved from 2020 levels, with the Green Environmental Protection-Oriented scheme reaching a safe carrying capacity. In summary, this paper offers theoretical and methodological support for developing basin-carrying capacity and the integrated governance of \"Three Waters.\"

This article explores the influence of safety culture (as a subset of organizational culture) on the safety performance of a post-combustion carbon capture facility. After determining the controlling variables of safety culture, a system dynamics model was built to assess how those variables contribute to the safety performance of the facility. The focus on safety culture arises for avoiding major disasters that could significantly impact a company\'s ability to continue, as well as minor but disruptive incidents occurring during routine operations (i.e. when there is no system upset). This paper describes the complex relationship between cultural norms, leadership practices, communication patterns, and safety conduct with an emphasis on management and personnel commitment to safety, open communication, safety investments, and productivity pressure. Insights from this study contribute to the development of strategies for enhancing the safety performance of carbon capture operations, thereby promoting the integrity and reliability of these essential elements of energy networks. This paper focuses on the visible aspect of safety culture as manifested in organismal practices. We proposed a system dynamics model to devise strategies to reconcile the profitability while preventing accidents.

A dynamic model has been developed to simulate aspects of feedlot lamb growth and body composition, including energy and protein requirements, growth rate, composition of gain, and body mass. Model inputs include initial body mass (kg), standard final mass (kg), age (days), and dietary energy concentration (Mcal·kg-1). The model was assessed as a decision support tool using a dataset of 564 individual measures of final body mass and diet energy. The simulations provide graphical and numerical descriptions of nutrient requirements, composition of gain, and estimates of animal performance over time. The model is accurate and precise, with a root mean squared error of 7.79% of the observed final body mass and a coefficient of determination of 0.89 when simulating the same variable. The model can be used as a reliable decision support tool to estimate final body mass and the days on feed required to reach a certain final mass with precision and accuracy. Moreover, the dynamic model can also serve as a learning tool to illustrate practical principles of animal nutrition, nutrient requirement relationships, and body composition changes. This model holds the potential to enhance livestock management practices and assist producers in making informed decisions about feedlot lamb production.

Measuring the impact of project portfolio synergy (PPSI) is crucial for making informed decisions to improve the strategic realization of a project portfolio. However, the literature has failed to measure PPSI effectively from the perspective of project element flow and to explore the differences in synergy relationships between homogeneous and heterogeneous projects. Consequently, this study proposes a framework for measuring PPSI from the perspective of project element flow. First, based on analyzing the synergistic relationship between projects, the corresponding project element datum quantity is determined according to the different types of element flow forms. Second, the synergy degree between homogeneous and heterogeneous projects is quantified through project similarity and correlation. Third, a dynamic measurement model is constructed using System Dynamics to solve the complex interactive feedback and dynamics in the PPSI measurement system. Finally, the framework is demonstrated and validated by a numerical example of project management in Xi\'an, Shaanxi Province. The results indicate that the model can effectively measure PPSI and identify the key factors generating it. In implementing the portfolio, managers must focus on sharing and integrating newly developed technologies and information, thus facilitating the generation of PPSI. This study extends the boundary of project portfolio synergy theory and contributes to the literature on measuring PPSI by focusing on the elements flow within portfolios. Additionally, the model provides an effective tool for managers to forecast PPSI and determine appropriate optimization strategies.

Improving our knowledge of future dynamics of ecosystem services (ESs) in the face of climate change and human activities provides a crucial foundation to navigate complex environmental challenges, which are essential to attaining sustainable development particularly in urban regions. However, an existing dearth persists in thoroughly forecasting the intricate interplay of trade-offs and synergies, as well as ecosystem services bundling under distinct future scenarios. This study adopts an integrated research framework to understand the spatiotemporal dynamics of ESs in the Changsha-Zhuzhou-Xiangtan Urban Agglomeration (CZTUA) under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (i.e., SSP126, SSP245 and SSP585). Our future scenarios suggest that the core urban area of CZTUA is projected to expand at the cost of forests and croplands by 2050. Furthermore, human-induced urbanization, particularly the high-intensity LUCC along the Xiangjiang river, significantly impacts ESs, resulting in lower ESs values. The trade-off effects between ESs are primarily observed between WY (water yield) and other ESs. Ecosystem service bundles (ESB) previously dominated by WY have significantly transitioned to CS (carbon storage)-HQ (habitat quality) bundle, especially in the urban core of CZTUA, which serves as an early warning of potential challenges related to water resources. Our study utilizes the latest climate and land use change predictions to evaluate ecosystems in urban agglomerations, and adopts a layered zoning strategy based on ESs, which provides decision-makers with reproducible tools to explore ecosystem changes.

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

Under the impetus of the new industrial revolution, how to realize intelligent manufacturing transformation of traditional pharmaceutical manufacturing enterprises has realistic urgency. The study starts from the perspective of complex adaptive system, constructs a system dynamics model of the evolution mechanism of intelligent manufacturing transformation of pharmaceutical manufacturing enterprises based on technological adaptation and evolutionary adaptation, and analyzes it by simulation using Vensim PLE software. The results of the study show that pharmaceutical manufacturing enterprises utilize technological affordances to provide support to realize network product-based manufacturing capability and smart product-based manufacturing capability through technological innovation capability and institutional optimization capability; the technological affordances environment promotes the realization of intelligent manufacturing transformation of pharmaceutical manufacturing enterprises to present a stage transformation law. The study enriches and extends the research paradigm of intelligent manufacturing transformation, and provides a reference for pharmaceutical manufacturing enterprises to realize intelligent manufacturing transformation.