Technical design features for improving the way a passive elastic filament produces propulsive thrust can be understood by analyzing the deformation of sperm-templated microrobots with segmented magnetization. Magnetic nanoparticles are electrostatically self-assembled on bovine sperm cells with nonuniform surface charge, producing different categories of sperm-templated microrobots. Depending on the amount and location of the nanoparticles on each cellular segment, magnetoelastic and viscous forces determine the wave pattern of each category during flagellar motion. Passively propagating waves are induced along the length of these microrobots using external rotating magnetic fields and the resultant wave patterns are measured. The response of the microrobots to the external field reveals distinct flow fields, propulsive thrust, and frequency responses during flagellar propulsion. This work allows predictions for optimizing the design and propulsion of flexible magnetic microrobots with segmented magnetization.

Modeling the process that a listener actuates in deriving words intended by a speaker, requires setting a hypothesis on how lexical items are stored in memory. Stevens' model (2002) postulates that lexical items are stored in memory according to distinctive features, and that these features are hierarchically organized. The model highlights the importance of abrupt acoustic events, named landmarks, in the perception process. In this model, the detection of landmarks is primary in human perception, corresponding to the first phase of recognition. The temporal area around the landmark is then further processed by the listener. Based on the above model, the Speech Communication Group of the Massachusetts Institute of Technology (MIT) developed a speech recognition system -for spoken English -over a span of more than 20 years. In the current work (LaMIT project, Lexical access Model for Italian) the above model is applied to Italian. Exploring a new language will provide insight into how Stevens' approach has universal application across languages, with relevant implications for understanding how the human brain recognizes speech.