This paper deals with the accurate modelling of unreinforced masonry (URM) behaviour using a 3D mesoscale description consisting of quadratic solid elements for masonry units combined with zero-thickness interface elements, the latter representing in a unified way the mortar and brick–mortar interfaces. A new constitutive model for the unified joint interfaces under cyclic loading is proposed. The model is based upon the combination of plasticity and damage. A multi-surface yield criterion in the stress domain governs the development of permanent plastic strains. Both strength and stiffness degradation are captured through the evolution of an anisotropic damage tensor, which is coupled to the plastic work produced. The restitution of normal stiffness in compression is taken into account by employing two separate damage variables for tension and compression in the normal direction. A simplified plastic yield surface is considered and the coupling of plasticity and damage is implemented in an efficient step by step approach for increased robustness. The computational cost of simulations performed using the mesoscale masonry description is reduced by employing a partitioning framework for parallel computation, which enables the application of the model at structural scale. Numerical results are compared against experimental data on realistic masonry components and structures subjected to monotonic and cyclic loading to show the ability of the proposed strategy to accurately capture the behaviour of URM under different types of loading

Tracking small laboratory animals such as flies, fish, and worms is used for phenotyping in neuroscience, genetics, disease modelling, and drug discovery. An imaging system with sufficient throughput and spatiotemporal resolution would be capable of imaging a large number of animals, estimating their pose, and quantifying detailed behavioural differences at a scale where hundreds of treatments could be tested simultaneously. Here we report an array of six 12-megapixel cameras that record all the wells of a 96-well plate with sufficient resolution to estimate the pose of C. elegans worms and to extract high-dimensional phenotypic fingerprints. We use the system to study behavioural variability across wild isolates, the sensitisation of worms to repeated blue light stimulation, the phenotypes of worm disease models, and worms’ behavioural responses to drug treatment. Because the system is compatible with standard multiwell plates, it makes computational ethological approaches accessible in existing high-throughput pipelines.

This paper presents an accurate and efficient computational strategy for the 3-dimensional simulation of heterogeneous structures with unreinforced masonry components. A mesoscale modelling approach is employed for the unreinforced masonry parts, whereas other material components are modelled independently with continuous meshes. The generally nonmatching meshes of the distinct domains are coupled with the use of a mesh tying method.The physical interaction between the components is captured with the use of zero-thickness cohesive interface elements. This strategy enables the optimisation of the individual meshes leading to increased computational efficiency. Furthermore, the elimination of the mesh compatibility requirement allows the 3-dimensional modelling of complex heterogeneous structures, ensuring accurate representation of each component's nonlinear behaviour and their interaction. Numerical examples, including a comparative analysis on the elastic and nonlinear response of a masonry bridge considering arch-backfill interaction and the nonlinear simulation of a multileaf wall, are presented to show the unique features of the proposed strategy and its predictive power in comparison with experimental and numerical results found in the literature. KEYWORDS coupling element, heterogeneous structures, mesh tying, mesoscale masonry model, nonlinear analysis 1950

Novel invertebrate-killing compounds are required in agriculture and medicine to overcome resistance to existing treatments. Because insecticides and anthelmintics are discovered in phenotypic screens, a crucial step in the discovery process is determining the mode of action of hits. Visible whole-organism symptoms are combined with molecular and physiological data to determine mode of action. However, manual symptomology is laborious and requires symptoms that are strong enough to see by eye. Here, we use high-throughput imaging and quantitative phenotyping to measure Caenorhabditis elegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. We also classify compounds within each mode of action to discover substructure that is not captured in broad mode-of-action labels. High-throughput imaging and automated phenotyping could therefore accelerate mode-of-action discovery in invertebratetargeting compound development and help to refine mode-ofaction categories.