In recent years, biopolymers are getting wide attention with the perspective of developing high‐performance biocomposites with low environmental impact owing to their unique and useful features such as abundant availability, renewability, eco‐friendliness and lightweight. Biopolymer composites are expected to replace many conventional materials in optical, biological, and engineering applications as the investment and research on these materials increase substantially. The desired properties of biopolymer composites can be achieved by blending an appropriate biopolymer with suitable additives, which pave the way for polymer‐filler interaction. A variety of parameters such as chemical composition, degradation kinetics and mechanical properties of biopolymer composites can be tailored according to the application needs. The interfacial interactions between the biopolymer and the nanofiller have a significant effect on the mechanical properties of biopolymer composites. The present review is focused on the recent advances in the mechanical properties of various biopolymer composites. In the first part of this review, the unfamiliar mechanical characterization techniques such as fatigue test, nanoindentation and nondestructive testing of biopolymer composites have been discussed. In the later part, the various popular processing techniques of biocomposite fabrication have been discussed. In addition, in the conclusion section, few challenges associated with the processing and mechanical performance of biopolymer composites have been described.
School-aged children with autism spectrum disorders (ASDs) have delayed gestural development, in comparison with age-matched typically developing children. In this study, an intervention program taught children with low-functioning ASD gestural comprehension and production using video modelling (VM) by a computer-generated robot animation. Six to 12-year-old children with ASD (N = 20; IQ < 70) were taught to recognize 20 gestures produced by the robot animation (phase I), to imitate these gestures (phase II) and to produce them in appropriate social contexts (phase III). Across the three phases, significant differences were found between the results of the pretest and the immediate and follow-up posttests; the results of both posttests were comparable, after controlling for the children's motor and visual memory skills. The children generalized their acquired gestural skills to a novel setting with a human researcher. These results suggest that VM by a robot animation is effective in teaching children with low-functioning ASD to recognize and produce gestures.
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