There is increasing evidence that humans are not living sustainably. There are three major drivers of the unsustainable approach: population, consumption and the growth economy. There is widespread denial about these issues, but they clearly need to be addressed if we are to achieve any of the possible sustainable futures. The first and second versions of the ‘World Scientists Warning to Humanity’ both highlight the problem of increasing human population, as do the IPCC and IPBES reports. However, all have been largely ignored. The size of an ecologically sustainable global population is considered, taking into account the implications of increasing per capita consumption. The paper then discusses the reasons why society and academia largely ignore overpopulation. The claim that discussing overpopulation is ‘anti-human’ is refuted. Causal Layered Analysis is used to examine why society ignores data that do not fit with its myths and metaphors, and how such denial is leading society towards collapse. Non-coercive solutions are then considered to reach an ecologically-sustainable human population. LinkedIn: https://www.linkedin.com/in/helenkopnina/
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This study explores the shape-morphing behavior of 4D-printed structures made from Polylactic Acid (PLA), a prominent bio-sourced shape-memory polymer. Focusing on the response of these structures to thermal stimuli, this research investigates how various printing parameters influence their morphing capabilities. The experimental approach integrates design and slicing, printing using fused deposition modeling (FDM), and a post-printing activation phase in a controlled laboratory environment. This process aims to replicate the external stimuli that induce shape morphing, highlighting the dynamic potential of 4D printing. Utilizing Taguchi’s Design of Experiments (DoE), this study examines the effects of printing speed, layer height, layer width, nozzle temperature, bed temperature, and activation temperature on the morphing behavior. The analysis includes precise measurements of deformation parameters, providing a comprehensive understanding of the morphing process. Regression models demonstrate strong correlations with observed data, suggesting their effectiveness in predicting responses based on control parameters. Additionally, finite element analysis (FEA) modeling successfully predicts the performance of these structures, validating its application as a design tool in 4D printing. This research contributes to the understanding of 4D printing dynamics and offers insights for optimizing printing processes to harness the full potential of shape-morphing materials. It sets a foundation for future research, particularly in exploring the relationship between printing parameters and the functional capabilities of 4D-printed structures.
