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With recent advances in material synthesis and additive manufacturing, material systems can be designed to achieve prescribed mechanical responses. An important class of such problems is the inverse design of elastic networks that attain a target configuration under loading, with applications in robotics, aerospace, and shape-morphing structures. This work presents a framework that formulates inverse design directly within the learned family of constitutive behaviors. Given a collection of stress–strain responses, we construct a constitutive prior, defined as a low-dimensional latent representation of admissible material laws learned directly from these responses. Spatially varying latent variables are then optimized subject to the governing equilibrium equations so that the deformed network matches a target configuration. The constitutive prior is represented using an energy-based, partially input-convex neural network that enforces the constitutive constraints by construction. To improve robustness in the resulting nonconvex optimization problem, the framework combines homotopy-continuation-based optimization with correspondence-free point cloud matching, allowing the target and optimized geometries to have different discretizations. The proposed approach is demonstrated on several inverse design problems for nonlinear elastic networks, and quantitative comparisons with alternative optimization strategies show improved robustness and optimization performance.
In psychology there is a plethora of different measures and constructs. However, the literature also shows that many of these measures overlap and may even sometimes be redundant. Recognizing such overlap in measures is essential for consolidation and for moving the field forward. Accordingly, we suggest a role herein of the General Factor of Personality (GFP), which emerges from the correlations between specific personality dimensions and reflects a mix of desirable traits (e.g. being sociable, honest, and emotionally stable). It is argued and shown that the GFP is highly correlated with a wide range of psychological traits. We further postulate that this phenomenon provides a parsimonious way of looking at the overlap between many trait measures. This idea is discussed in light of the ongoing debate on the GFP in which some scholars suggest the general factor is substantive and relevant for understanding personality, whereas others consider it to solely reflect a measurement artifact. Irrespective of whether the substantive, artifact, or a mixed explanation of the GFP is adopted, overlooking the presence of a common general factor in psychological measures may, respectively, either impede the development of unifying theories of human behavior, or otherwise compromise measurement validity.
Suicide claims more than 720,000 lives each year. Reducing suicide requires targeted policy interventions, underscoring the need to identify potential protective factors. Although greenspace has been proposed as a protective factor, empirical findings remain inconsistent. A comparative analysis that accounts for spatial scale, greenspace diversity, and contextual differences is therefore needed to investigate whether the relationship between greenspace and suicide varies across countries and to better understand how social and environmental inequalities shape suicide risk.Specifically, we examined four measures of urban greenspace: regional park count, regional park area proportion, local park proximity, and average park size. Using suicide data from 2019 to 2023, we performed a cross-sectional ecological study across all urban counties in the U.S. and all urban local authorities in England & Wales to study the associations between greenspace and suicide rates. By comparing two national contexts at similar administrative levels, we investigated whether the associations differ across social contexts and how these relationships change before and after adjusting for socioeconomic disadvantage.In the U.S., park availability stood out as a strong protective factor, with counties having at least one open park exhibiting an estimated 19% lower suicide rate (incidence rate ratio (IRR) = 0.81). In England & Wales, significant nonlinear association between suicide and park counts was detected, suggesting potential heterogeneity across local authorities, particularly those with a large number of parks. These findings underscore the need for context-specific approaches to urban greenspace planning and public health interventions.
This study proposes a novel discrete hygro-thermo-mechanical model for concrete under freeze-thaw cycles (FTCs) within the framework of the Multi-physics Lattice Discrete Particle Model. The evolution of ice content and its hysteretic behavior are simulated using a modified liquid-solid interfacial energy function. The non-uniform local eigenstrains induced by temperature variation and ice formation govern the FTC-induced cracking behavior; accordingly, these eigenstrains are incorporated into the mechanical constitutive model via a one-way coupling scheme. Notably, the model successfully captures cracking patterns, which initiate at the surface and propagate inwards over hundreds of FTCs. It also accurately predicts the associated degradation in both tensile and compressive strength. Therefore, this study finds that an external compressive load exerts a complex influence on FTC-induced degradation. Specifically, a moderate compressive load equal to 50% of the material’s compressive strength increases the residual strength by approximately 1.5 MPa after 50 FTCs. This beneficial effect arises because the applied external load restrains frost-heaving deformation and thereby suppresses the initiation of FTC-induced micro-cracks. In contrast, when the external load exceeds 70% of the compressive strength, degradation is significantly accelerated.
Scuffing is a catastrophic surface failure mode of surfaces in lubricated sliding interfaces, characterized by sudden increases in friction, interfacial temperature, vibration, and noise. Despite decades of study, its underlying mechanisms remain incompletely resolved due to the complex interplay of adhesion, thermal effects, tribochemistry, plastic deformation, and lubricant failure. This review consolidates current understanding of scuffing through an interdisciplinary lens, examining key contributing factors including material adhesion, flash temperatures, surface roughness and directionality, lubricant degradation and desorption, tribochemical film dynamics, and stick–slip behavior. By integrating theoretical, computational, and experimental perspectives, this work surveys proposed scuffing criteria, failure precursors, and mitigation strategies. Scuffing mechanics modeling was one of the foci of Professor Johnson’s work; this paper follows his footprint toward the understanding, modeling, and prevention of scuffing in high-performance tribological systems.
