Additive manufacturing (AM) or 3D printing has been hailed as the third industrial revolution as it has caused a paradigm shift in the way objects have been manufactured. Conventionally, converting a raw material to a fully finished and assembled, usable product comprises several steps which can be eliminated by using this process as functional products can be created directly from the raw material at a fraction of the time originally consumed. Thus, AM has found applications in several sectors including automotive, aerospace, printed electronics, and healthcare. AM is increasingly being used in the healthcare sector, given its potential to fabricate patient-specific customized implants with required accuracy and precision. Implantable heart valves, rib cages, and bones are some of the examples where AM technologies are used. A vast variety of materials including ceramics, metals, polymers, and composites have been processed to fabricate intricate implants using 3D printing. The applications of AM in dentistry include maxillofacial implants, dentures, and other prosthetic aids. It may also be used in surgical training and planning, as anatomical models can be created at ease using AM. This article gives an overview of the AM process and reviews in detail the applications of 3D printing in dentistry. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 2058-2064, 2018.
Mineral trioxide aggregate (MTA) can provide bioactivity to poly‐caprolactone (PCL), which is an inert polymer used to print scaffolds. However, testing all combinations of scaffold characteristics (e.g., composition, pore size, and distribution) to optimize properties of scaffolds is time‐consuming and costly. The Taguchi's methods can identify characteristics that have major influences on the properties of complex designs, hence decreasing the number of combinations to be tested. The objective was to assess the potential of Taguchi's methods as a predictive tool for the optimization of bioactive scaffold printed using electro‐hydro dynamic jetting. A three‐level approach assessed the influence of PCL/MTA proportion, pore size, fiber dimension and number of layers in pH, degradation rate, porosity, yield strength, and Young's modulus. Data were analyzed using Tukey's honest significant difference test, analysis of mean and signal‐to‐noise ratio (S/N) test. Cytocompatibility and differentiation potential were assessed for 5 and 30 days using dental pulp stem cells and analyzed with one‐way analysis of variance (proliferation) or Mann–Whitney (qPCR). The S/N ratio and analysis of mean showed that fiber diameter and composition were the most influential characteristics in all properties. The experimental data confirmed that the addition of MTA to PCL increased the pH and scaffold degradation. Only PCL and PCL with 4% MTA allowed cell proliferation. The latter increased the genetic expression of ALP, COL‐1, OCN, and MSX‐1. The theoretical predictions were confirmed by the experiments. The Taguchi's identified the inputs that can be disregarded to optimize 3D printed meshed bioactive scaffolds.
Additive Manufacturing or 3D Printing as it is commonly known is increasingly being used in the manufacturing of tissue engineering scaffold. The process allows for just in time production and customization. Hence, optimizing and varying the morphology of the tissue engineering scaffold in accordance to the application is one of the advantages of 3D printing. This paper aims to optimize the surface scaffold morphology by varying the dimensional parameters such as pore size, fibre diameter, orientation of fibres on scaffold and number of layers on the scaffold. The paper makes use of Taguchi’s Design of Experiments to understand and analyse the relationship between the different parameters that influence the morphological and mechanical characteristics of the scaffold.
Nowadays, the development of big data is getting faster and faster, and the related research on motion sensing recognition and complex systems under the background of big data is gradually being valued. At present, there are relatively few related researches on vertical Baduanjin in the academic circles; research in this direction can make further breakthroughs in motion sensor recognition. In order to carry out related action recognition research on the lifting action of vertical Baduanjin, this paper uses sensor technology to collect the motion video image of vertical Baduanjin based on the background of big data and uses action recognition technology and related algorithms to obtain the action. Recognize the video image to obtain the data, get the acceleration, angular velocity, and EMG data, and count the end time and duration according to the change of the action. According to the data table and graph change trend compiled at the end of the experiment, we can see the following: after the data is preprocessed, the acceleration signal change range is limited to [−1, 1], and the acceleration change has a clear directionality; and, after 15 lifts of the detected object, its angular velocity in X-axis direction is basically negative. However, when the ninth lift is performed, the angular velocity of the movement in X-axis direction is 36.09, the largest of all angular velocities. When performing the 15th lifting action, the angular velocity of this action in Z-axis direction is −26.05, which is the smallest of all angular velocities. The longest duration of the left muscle discharge during the lifting action of the subject is 15.24 for the tibial anterior muscle and 8.91 for the external oblique muscle with the shortest duration. The longest discharge duration of the right muscle is also the tibial anterior muscle with 12.15, and the shortest duration is the erector spinae with 8.79.
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