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Artificial meat is an eco-friendly alternative to real meat that is marketed to have a similar taste and feel. The mechanical properties of artificial meat significantly influence our perception of taste, but how precisely the mechanics of artificial meat compare to real meat remains insufficiently understood. Here we perform mechanical tension, compression, and shear tests on isotropic artificial meat (Tofurky® Plant-Based Deli Slices), anisotropic artificial meat (Daring™ Chick'n Pieces) and anisotropic real meat (chicken) and analyze the data using constitutive neural networks and automated model discovery. Our study shows that, when deformed by 10%, artificial and real chicken display similar maximum stresses of 21.0 kPa and 21.8 kPa in tension, -7.2 kPa and -16.4 kPa in compression, and 2.4 kPa and 0.9 kPa in shear, while the maximum stresses for tofurky were 28.5 kPa, -38.3 kP, and 5.5 kPa. To discover the mechanics that best explain these data, we consulted two constitutive neural networks of Ogden and Valanis–Landel type. Both networks robustly discover models and parameters to explain the complex nonlinear behavior of artificial and real meat for individual tension, compression, and shear tests, and for all three tests combined. When constrained to the classical neo Hooke, Blatz Ko, and Mooney Rivlin models, both networks discover shear moduli of 94.4 kPa for tofurky, 35.7 kPa for artificial chick'n, and 21.4 kPa for real chicken. Our results suggests that artificial chicken succeeds in reproducing the mechanical properties of real chicken across all loading modes, while tofurky does not, and is about three times stiffer. Strikingly, all three meat products display shear softening and their resistance to shear is about an order of magnitude lower than their resistance to tension and compression. We anticipate our study to inspire more quantitative, mechanistic comparisons of artificial and real meat. Our automated-model-discovery based approach has the potential to inform the design of more authentic meat substitutes with an improved perception of taste, with the ultimate goal to reduce environmental impact, improve animal welfare, and mitigate climate change, while still offering the familiar taste and texture of traditional meat. Our source code, data, and examples are available at https://github.com/LivingMatterLab/CANNs. [Display omitted] [ABSTRACT FROM AUTHOR]

Plantar soft tissue stiffening in diabetes leads to a risk of developing ulcers. There are relatively few studies providing methods for quantifying the mechanical properties of skin and fat in the plantar tissue of diabetic patients. Previous studies used linear or non-linear single layer deformable models or linear multi-layer models. This study aimed to investigate the mechanical properties of plantar soft tissue using multi-layer, non-linear models to estimate more accurate mechanical properties in the plantar tissues of diabetic patients. Ten healthy young (HY) subjects, ten healthy old (HO) subjects, and ten old diabetic patients (DB) volunteered for the study. Indentation tests were performed at two sites in the heel. The subjects underwent computed tomography (CT) to measure the respective thicknesses of the skin and fat at the indentation sites. Subject-specific finite element models were created to estimate the parameters of the first-order Ogden forms of the skin and fat. The initial shear modulus for the fat layer μ F in DB, HO, and HY were 4.68 MPa (±0.87), 2.71 MPa (±1.25), and 2.27 MPa (±0.87), respectively. The initial shear modulus for the skin layer (μ S) in DB, HO, and HY were 5.86 MPa (±2.51), 7.05 MPa (±1.94), and 14.58 MPa (±1.98), respectively. The DB had stiffer fat tissue than the normal subjects in the same age group but had the same soft skin. These aspects can cause different mechanical stress conditions in a diabetic foot than in a normal foot under the same mechanical loading, making the diabetic foot vulnerable to the initiation of mechanical breakdowns such as ulcers. [ABSTRACT FROM AUTHOR]