An important class of tasks that are underexplored in current human computation systems are complex tasks with global constraints. One example of such a task is itinerary planning, where solutions consist of a sequence of activities that meet requirements specified by the requester. In this paper, we focus on the crowdsourcing of such plans as a case study of constraint-based human computation tasks and introduce a collaborative planning system called Mobi that illustrates a novel crowdware paradigm. Mobi presents a single interface that enables crowd participants to view the current solution context and make appropriate contributions based on current needs. We conduct experiments that explain how Mobi enables a crowd to effectively and collaboratively resolve global constraints, and discuss how the design principles behind Mobi can more generally facilitate a crowd to tackle problems involving global constraints.

Development of new approaches to biomimetically reconstruct vasculature networks remains challenging in regenerative medicine. We introduce a particle-based artificial stem cell spheroid (ASSP) technology that recapitulates paracrine functions of three-dimensional (3D) SSPs for vasculature regeneration. Specifically, we used a facile method to induce the aggregation of stem cells into 3D spheroids, which benefited from hypoxia microenvironment–driven and enhanced secretion of proangiogenic bioactive factors. Furthermore, we artificially reconstructed 3D spheroids (i.e., ASSP) by integration of SSP-secreted factors into micro-/nanoparticles with cell membrane–derived surface coatings. The easily controllable sizes of the ASSP particles provided superior revascularization effects on the ischemic tissues in hindlimb ischemia models through local administration of ASSP microparticles and in myocardial infarction models via the systemic delivery of ASSP nanoparticles. The strategy offers a promising therapeutic option for ischemic tissue regeneration and addresses issues faced by the bottlenecked development in the delivery of stem cell therapies.

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A coupled multiphase model based on computational fluid dynamics (CFD) and discrete element method (DEM) is developed to numerically investigate the extrusion-based 3D printing process of discontinuous carbon fibre-reinforced polymer composites. Short carbon fibres are modelled as rigid bodies by clumping discrete spheres in DEM, while polymer matrix is treated as an incompressible Newtonian fluid in CFD. A fluid-particle interaction model is adopted to couple DEM and CFD and represent the dynamic fibre/matrix interaction. Collisions between fibres are considered naturally in DEM by using the Hertz-Mindlin contact law. The coupled CFD-DEM is validated, both qualitatively and quantitatively, against X-ray microtomography (μCT) experimental results for the T300/PA6 composite. Parametric study on various fibre lengths, fibre volume fraction and resin viscosity using the CFD-DEM model shows that the nozzle clogging tends to occur when the fibre length and/or the fibre volume fraction are increased. Use of a polymer matrix with a lower viscosity can be effective to eliminate the clogging issue when printing composites with relatively short fibres. The fibre length is dominating when long fibres are used and the clogging is largely independent on the viscosity of the polymer matrix. Finally, a potential solution of using a cone sleeve insert located above the shrinking region to address the nozzle clogging issue is proposed and numerically assessed.