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We introduce the open-source Python software framework pycity_scheduling for the effective development, testing, and assessment of optimisation-based power scheduling algorithms for local multi-energy systems in city districts. The framework primarily targets the elaboration of coordination concepts that can efficiently solve the power dispatch problem on the city district level. Its target users are researchers in the field of smart grid applications and the deployment of operational flexibility for local energy systems. Illustrative code examples demonstrate the capabilities of the pycity_scheduling framework and its use cases. The design principles established in pycity_scheduling allows users to access, extend, and modify the Python package without any need for commercial software or licensing concerns.

In this article a gateway module to integrate legacy laboratory devices into the network of the digital laboratory in the 21st century is introduced. The device is based on ready to buy consumer hardware that is easy to get and inexpensive. Depending on the specific requirements of the desired application (bare embedded computer, RS232 serial port connector, IP65 certified casing and connectors) the needed investment ranges from about 95 € up to 200 €. The embedded computer runs an open source Linux operating system and can in principle be used to run any kind of software needed for communicating with the laboratory device. Here the open source SiLA2 standard is used for presenting the device’s functions in the network. As an example the digital integration of a magnetic stirrer is shown and can be used as a template for other applications. A method for easy remote integration of the device to ensure an easy and consistent workflow in development, testing and usage is also presented. This incorporates a method for remote installation of SiLA2 servers on the box as well as a web frontend for administration, debugging and management of those.

Summary: Three-dimensional matrices often contain highly structured adhesive tracks that require cells to turn corners and bridge non-adhesive areas. Here, we investigate these complex processes using micropatterned cell adhesive frames. Spreading kinetics on these matrices depend strongly on initial adhesive position and are predicted by a cellular Potts model (CPM), which reflects a balance between adhesion and intracellular tension. As cells spread, new stress fibers (SFs) assemble periodically and parallel to the leading edge, with spatial intervals of ∼2.5 μm, temporal intervals of ∼15 min, and characteristic lifetimes of ∼50 min. By incorporating these rules into the CPM, we can successfully predict SF network architecture. Moreover, we observe broadly similar behavior when we culture cells on arrays of discrete collagen fibers. Our findings show that ECM geometry and initial cell position strongly determine cell spreading and that cells encode a memory of their spreading history through SF network organization. : Kassianidou et al. use adhesive micropatterns to recapitulate features of 3D extracellular matrices and to integrate live-cell imaging with mathematical modeling. They find that spreading trajectories are determined by a balance between adhesion energy, surface tension, and line tension, and that cells produce a stress fiber network that encodes the spreading history. Keywords: cell-matrix adhesion, cell shape, cell spreading, actin cytoskeleton, stress fibers, mathematical modeling, cellular Potts model, cell memory, mechanobiology, cell migration