Effects of Strontium incorporation to Mg-Zn-Ca biodegradable bulk metallic glass investigated by molecular dynamics simulation and density functional theory calculation.

Molecular dynamics (MD) simulation and density functional theory (DFT) calculations were used to predict the material properties and explore the improvement on the surface corrosion resistance for the Mg66Zn30Ca3Sr1 bulk metallic glass (BMG). The Mg66Zn30Ca4 BMG was also investigated to realize the influence of the addition of Sr element on the material behaviors of Mg66Zn30Ca4. The Mg-Zn-Ca-Sr parameters of the next nearest-neighbor modified embedded atom method (2NN MEAM) potential were first determined by the guaranteed convergence particle swarm optimization (GCPSO) method based on the reference data from the density functional theory (DFT) calculation. Besides, using the 2NN MEAM parameters of the Mg-Zn-Ca-Sr system, the structures of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1 were predicted by the simulated-annealing basin-hopping (SABH) method. The local atomic arrangements of the predicted BMG structures are almost the same as those measured in some related experiments from a comparison with the calculated and experimental X-ray diffraction (XRD) profiles. Furthermore, the HA index analysis shows that the fractions of icosahedra-like local structures are about 72.20% and 72.73% for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1, respectively, indicating that these two BMG structures are entirely amorphous. The uniaxial tensile MD simulation was conducted to obtain the stress-strain relationship as well as the related mechanical properties of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1. Consequently, the predicted Young's moduli of both BMGs are about 46.4 GPa, which are very close to the experimental values of 48.8 ± 0.2 and 49.1 ± 0.1 GPa for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1, respectively. However, the predicted strengths of Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1 are about 850 and 900 MPa, both are slightly higher than the measured experimental values about 747 ± 22 and 848 ± 21 MPa for Mg66Zn30Ca4 and Mg66Zn30Ca3Sr1. Regarding the thermal properties, the predicted melting temperature of Mg66Zn30Ca3Sr1 by the square displacement (SD) profile is about 620 K, which is very close to the experimental melting temperature of about 613 K. The self-diffusion coefficients of Mg, Zn, Ca, and Sr elements were also calculated for temperatures near their melting points by means of the Einstein equation. The methodology can determine the diffusion barriers for different elements by utilizing these diffusion coefficients resulting in a fact that the diffusion barriers of Ca and Sr elements of Mg66Zn30Ca3Sr1 are relatively high. For the electronic properties predicted by the DFT calculation, the projected density of states (PDOS) profiles of surface Mg, Zn, Ca, and Sr elements clearly show that the addition of Sr into Mg66Zn30Ca4 effectively reduces the s and p orbital states of surface Mg and Zn elements near the Fermi level, particularly the p orbits, which suppresses the electron transfer as well as increases the surface corrosion resistance of Mg66Zn30Ca4. Consequently, this study has provided excellent 2NN MEAM parameters for the Mg, Zn, Ca, and Sr system by the GCPSO method to predict real BMG structures as well as by means of the DFT calculation to explore the electronic properties. Eventually, through our developed numerical processes the material properties of BMGs with different compositions can be predicted accurately for the new BMG design.

Speech-generating devices: effectiveness of interface design-a comparative study of autism spectrum disorders.

BACKGROUND: We analyzed the efficacy of the interface design of speech generating devices on three non-verbal adolescents with autism spectrum disorder (ASD), in hopes of improving their on-campus communication and cognitive disability. The intervention program was created based on their social and communication needs in school. Two operating interfaces were designed and compared: the Hierarchical Relating Menu and the Pie Abbreviation-Expansion Menu. METHODS: The experiment used the ABCACB multiple-treatment reversal design. The test items included: (1) accuracy of operating identification; (2) interface operation in response to questions; (3) degree of independent completion. Each of these three items improved with both intervention interfaces. RESULTS: The children were able to operate the interfaces skillfully and respond to questions accurately, which evidenced the effectiveness of the interfaces. CONCLUSIONS: We conclude that both interfaces are efficacious enough to help nonverbal children with ASD at different levels.

Applied Cliplets-based half-dynamic videos as intervention learning materials to attract the attention of adolescents with autism spectrum disorder to improve their perceptions and judgments of the facial expressions and emotions of others.

BACKGROUND: Autism spectrum disorders (ASD) are characterized by a reduced ability to understand the emotional expressions on other people's faces. Increasing evidence indicates that children with ASD might not recognize or understand crucial nonverbal behaviors, which likely causes them to ignore nonverbal gestures and social cues, like facial expressions, that usually aid social interaction. OBJECTIVE: In this study, we used software technology to create half-static and dynamic video materials to teach adolescents with ASD how to become aware of six basic facial expressions observed in real situations. METHODS: This intervention system provides a half-way point via a dynamic video of a specific element within a static-surrounding frame to strengthen the ability of the six adolescents with ASD to attract their attention on the relevant dynamic facial expressions and ignore irrelevant ones. RESULTS: Using a multiple baseline design across participants, we found that the intervention learning system provided a simple yet effective way for adolescents with ASD to attract their attention on the nonverbal facial cues; the intervention helped them better understand and judge others' facial emotions. CONCLUSION: We conclude that the limited amount of information with structured and specific close-up visual social cues helped the participants improve judgments of the emotional meaning of the facial expressions of others.

Augmented reality-based self-facial modeling to promote the emotional expression and social skills of adolescents with autism spectrum disorders.

Autism spectrum disorders (ASD) are characterized by a reduced ability to understand the emotions of other people; this ability involves recognizing facial expressions. This study assessed the possibility of enabling three adolescents with ASD to become aware of facial expressions observed in situations in a school setting simulated using augmented reality (AR) technology. The AR system provided three-dimensional (3-D) animations of six basic facial expressions overlaid on participant faces to facilitate practicing emotional judgments and social skills. Based on the multiple baseline design across subjects, the data indicated that AR intervention can improve the appropriate recognition and response to facial emotional expressions seen in the situational task.