The microenvironments of tissues or organs are complex architectures comprised of structural proteins including collagen. Particularly, the cornea is organized in a lattice pattern of collagen fibrils which play a significant role in its transparency. This paper introduces a transparent bioengineered corneal structure for transplantation. The structure is fabricated by inducing shear stress to a corneal stroma-derived decellularized extracellular matrix bioink based on a 3D cell printing technique. The printed structure recapitulates the native macrostructure of the cornea with aligned collagen fibrils which results in the construction of a highly matured and transparent cornea stroma analog. The level of shear stress, controlled by the various size of the printing nozzle, manipulates the arrangement of the fibrillar structure. With proper parameter selection, the printed cornea exhibits high cellular alignment capability, indicating a tissue-specific structural organization of collagen fibrils. In addition, this structural regulation enhances critical cellular events in the assembly of collagen over time. Interestingly, the collagen fibrils that remodeled along with the printing path create a lattice pattern similar to the structure of native human cornea after 4 weeks in vivo. Taken together, these results establish the possibilities and versatility of fabricating aligned collagen fibrils; this represents significant advances in corneal tissue engineering.

No abstract

No abstract

The objective of this study was to develop an edutainment robot which provides multi-sensory learning experiences to improve users' space perception and creativity. In particular, we focused on developing educational content for the study of the Korean alphabet (Hangul) using the robot. On the basis of the phonemic and modular nature of Hangul, we devised a block-shaped edutainment robot for the study of Hangul. The robot known as "HangulBot" is composed of a consonant block and a vowel block. By rotating and rearranging those blocks, a user can create different characters. To enable the robot to perceive the arrangement of the blocks and the distance between a consonant block and a vowel block, IR LEDs and photo transistors were used. The eight IR LEDs in the consonant block generate different radiation signals, and the vowel block perceives the arrangement of the blocks by receiving the signals. The distance between the two blocks is estimated by measuring the thresholding, and the corresponding sound of each arrangement is then played through a speaker installed in the vowel block. We executed two shortterm field trials with a twenty-seven month old child in June of 2011 and November of 2011 to ascertain children's initial reaction to HangulBot and how their reaction would change over time. While the results are preliminary, we noted several interesting findings. First, after several trials by the mother, the child felt comfortable with HangulBot. Second, the child intuitively followed the corresponding speech sounds which were generated by HangulBot according to the arrangement of the blocks. That is to say, the sound generated after the arranging the block intuitively induced the child to follow the sound. Third, the child's initial reaction to HangulBot was mostly block play, but after five months later, her reaction to the robot included not only block play but also active learning of the Korean alphabet. This result indicates that HangulBot could be an effective edutainment tool which improves space perception and creativity as well as linguistic abilities by stimulating both sides of the brain.

Predictive capabilities of unsteady Reynolds-averaged Navier–Stokes (URANS) techniques using the k−ω shear stress transport and Spalart–Allmaras models are assessed for the simulation of turbulent boundary layers under unsteady adverse pressure gradients by comparing their results with direct numerical simulation (DNS) results. Simulations are conducted for separating and reattaching turbulent boundary layers under periodic adverse pressure gradients. Phase-wise comparisons of the velocity, the Reynolds stress, and the skin friction coefficient obtained by URANS simulations and DNS are carried out. URANS techniques are found to qualitatively well predict the formation of the separation bubble and the phase response of the shear layer height, while they predict earlier separation and a larger recirculation bubble compared with those in DNS. Phase responses of the skin friction predicted by URANS simulations are found not to be an accurate indication of flow separation and reattachment of the turbulent boundary layer. The main causes of discrepancies among DNS and URANS results in the near-wall region are attributed to the different anisotropy of the Reynolds stress, which can be characterized by a barycentric map.