Structural design with multi-family triply periodic minimal surfaces (TPMS) is a meaningful work that can combine the advantages of different types of TPMS. However, very few methods consider the influence of the blending of different TPMS on structural performance, and the manufacturability of final structure. Therefore, this work proposes a method to design manufacturable microstructures with topology optimization (TO) based on spatially-varying TPMS. In our method, different types of TPMS are simultaneously considered in the optimization to maximize the performance of designed microstructure. The geometric and mechanical properties of the unit cells generated with TPMS, that is minimal surface lattice cell (MSLC), are analyzed to obtain the performance of different types of TPMS. In the designed microstructure, MSLCs of different types are smoothly blended with an interpolation method. To analyze the influence of deformed MSLCs on the performance of the final structure, the blending blocks are introduced to describe the connection cases between different types of MSLCs. The mechanical properties of deformed MSLCs are analyzed and applied in TO process to reduce the influence of deformed MSLCs on the performance of final structure. The infill resolution of MSLC within a given design domain is determined according to the minimal printable wall thickness of MSLC and structural stiffness. Both numerical and physical experimental results demonstrate the effectiveness of the proposed method.

The design of the light-weight infill structure is a hot research topic in additive manufacturing. In recent years, various infill structures have been proposed to reduce the amount of printing material. However, 3D models filled with them may have very different structural performances under different loading conditions. In addition, most of them are not self-supporting. To mitigate these issues, a novel light-weight infill structure based on the layer construction is proposed in this article. The layers of the proposed infill structure continuously and periodically transform between triangles and hexagons. The geometries of two adjacent layers are controlled to be self-supporting for different 3D printing technologies. The machine code (Gcode) of the filled 3D model is generated in the construction of the infill structure for 3D printers. That means 3D models filled with the proposed infill structure do not need an extra slicing process before printing, which is time consuming in some cases. Structural simulations and physical experiments demonstrate that our infill structure has comparable structural performance under different loading conditions. Furthermore, the relationship between the structural stiffness and the parameters of the infill structure is investigated, which will be helpful for non-professional users.

Major depression (MD) is a major public health problem which has a substantial impact on individuals and society. Although it is usually treated with antidepressant in primary care, these therapies accompanied with serious side effects. In the clinic of Chinese medicine, Xiao-Yao-San is the first option for MD with little side effects. Although with clear therapeutic effects, its therapeutic mechanism is obscure. In this study, by integrating leading biomedical knowledge databases, though bioinformatics analysis, we explored the potential therapeutic mechanism of Xiao-Yao-San for MD. The therapeutic mechanism analysis covers aspects of Chinese herbal medicine, chemical compound, target protein, OMIM genes, and pathways enriched. As a result, Xiao-Yao-San's 4 target proteins e.g., ADRB2R, B2AR, ADRB2, and MC4R can be matched in MD's OMIM genes which are mainly enriched in pathways of signal transduction. This research demonstrates that Xiao-Yao-San's target proteins may regulate a wide range of different pathways associated with MD.

We present a feature and parameterization approach for constructing garment surface with garment sections from human body sections. The body section is obtained from polygonal 3D human models with the horizontal cutting plane based on detecting feature points on human model. Then we make the interstice measure which converts from garment tolerance as the parameter to build garment sections from body sections. Garment Surface is constructed with garment sections by an improved angle synchronous method.