Wearable and implantable devices require conductive, stretchable and biocompatible materials. However, obtaining composites that simultaneously fulfil these requirements is challenging due to a trade-off between conductivity and stretchability. Here, we report on Ag-Au nanocomposites composed of ultralong gold-coated silver nanowires in an elastomeric block-copolymer matrix. Owing to the high aspect ratio and percolation network of the Ag-Au nanowires, the nanocomposites exhibit an optimized conductivity of 41,850 S cm (maximum of 72,600 S cm). Phase separation in the Ag-Au nanocomposite during the solvent-drying process generates a microstructure that yields an optimized stretchability of 266% (maximum of 840%). The thick gold sheath deposited on the silver nanowire surface prevents oxidation and silver ion leaching, making the composite biocompatible and highly conductive. Using the nanocomposite, we successfully fabricate wearable and implantable soft bioelectronic devices that can be conformally integrated with human skin and swine heart for continuous electrophysiological recording, and electrical and thermal stimulation.

It is often claimed that point-light displays provide sufficient information to easily recognize properties of the actor and action being performed. We examined this claim by obtaining estimates of human efficiency in the categorization of movement. We began by recording a database of three-dimensional human arm movements from 13 males and 13 females that contained multiple repetitions of knocking, waving and lifting movements done both in an angry and a neutral style. Point-light displays of each individual for all of the six different combinations were presented to participants who were asked to judge the gender of the model in Experiment 1 and the affect in Experiment 2. To obtain estimates of efficiency, results of human performance were compared to the output of automatic pattern classifiers based on artificial neural networks designed and trained to perform the same classification task on the same movements. Efficiency was expressed as the squared ratio of human sensitivity (d') to neural network sensitivity (d'). Average results for gender recognition showed a proportion correct of 0.51 and an efficiency of 0.27%. Results for affect recognition showed a proportion correct of 0.71 and an efficiency of 32.5%. These results are discussed in the context of how different cues inform the recognition of movement style.

The combination of transcricothyroid membrane ultrasonography and ultrasonographic lung-sliding evaluation could be useful in confirming endotracheal intubation in the ED.

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Interface engineering of evaporative emulsion droplets containing block copolymers (BCPs) provides an effective route to generate nonspherical particles. Here, we demonstrate the impact of length-controlled nanorods (NRs) on the interfacial properties of BCP emulsions to produce anisotropic BCP particles. A series of lamellae- and cylinder-forming polystyrene-b-poly­(4-vinylpyridine) (PS-b-P4VP) and a series of NRs with different lengths (l) are coassembled, and selective arrangement of the NRs on the P4VP domain at the particle surface enables the production of striped football (prolate) and convex lens-shaped (oblate) particles. In particular, the ratio of the NR length to the size of the NR-hosting domain (l/L), which is varied from 0.07 to 3.60, is the key parameter in determining the location of the NRs in the BCP particles as well as the final particle shape. The oblate particles are generated only in the range of 0.36 ≤ l/L ≤ 0.96, whereas the prolate particles are produced for much wider range of l/L ≥ 0.83 without upper limit. This difference is attributed to larger entropic penalty for the NRs confined within the P4VP cylinders than the entropic penalty for those within the lamellae. To better understand and support our experimental observations, we performed dissipative particle dynamics simulation and calculated the free energy for the NR/BCP assembly within the emulsion droplets.