This systematic review examines the intersection of systems thinking and learning theory in addressing rural–urban challenges in light of increasing global urbanization. We explore how different dimensions of systems thinking—ontological...
In this paper, the Adaptive Calibration Model (ACM) and Active Inference Theory (AIT) are related to future-proofing startups. ACM encompasses the allocation of energy by the stress response system to alternative options for action, depending upon in...
World models is a construct that is used to represent internal models of the world. It is an important construct for human-artificial intelligence systems, because both natural and artificial agents can have world models. The term, natural agents, en...
Social learning, especially triple-loop social learning involving institutional and governance changes, has great potential to address urban water issues such as flooding, drought, and pollution. It facilitates urban transition and the adoption of mo...
More and more, the evaluation of complex projects is being related to the capacity of the project to deal with crucial social, economic, and environmental issues that society is responsible for and with the activation of systemic changes. Within this...
Diversification of flood risk management strategies (FRMS) in response to climate change relies on the adaptive capacities of institutions. Although adaptive capacities enable flexibility and adjustment, more empirical research is needed to better gr...
The title of this article signals increasing collaboration across boundaries aimed at understanding and solving complex scientific and societal problems. The article is a reflective analysis of five intersecting keywords in discussions of sustainabil...
Peri-urban interfaces tend to ensure water supply relying on their surrounding’ resources, generating water disputes when asking for collaboration. The urban-rural matrix of the Marina Baja county in southern Spain is characterized by inland ir...
Construction firms struggle to implement sustainable practices, delivering triple bottom line benefits despite growing environmental pressures. While research examines isolated sustainability drivers, the understanding of how organizational factors i...
Triple-negative breast cancer (TNBC) poses a major clinical challenge due to its aggressive progression and limited treatment options, making early diagnosis and prognosis critical. MicroRNAs (miRNAs) are crucial post-transcriptional regulators that...
This paper focuses on the triple-junction gallium arsenide solar array of a MEO (Medium Earth Orbit) satellite that has been in orbit for 7 years. Through a combination of theoretical and data-driven methods, it conducts research on anti-radiation de...
Deep neural networks must address the dual challenge of delivering high-accuracy predictions and providing user-friendly explanations. While deep models are widely used in the field of time series modeling, deciphering the core principles that govern...