The addition of the time dimension to three-dimensional (3D) printing has introduced four-dimensional (4D) printing technology, which has gained considerable attention in different fields such as medical, art, and engineering. Nowadays, bioscience has introduced some ideas which can be fulfilled by 4D printing. Blending time with variations caused by the situation has many beneficial aspects such as perceptibility and adaptability. Since 4D printing can create a dynamic structure with stimuli-responsive materials, the applications of smart materials, stimulus, and 3D printing are the effective criteria in 4D printing technology. Smart materials with their flexible properties can reshape, recolor, or change function under the effect of the internal or exterior stimuli. Thus, an attractive prospect in the medical field is the integration of the 4D printing approach along with smart materials. This research aims to show the most recent applications of 4D printing technology and smart materials in medical engineering which can show better prospective of 4D printing applications in the future. Also, it describes smart medical implants, tissue engineering, and bioprinting and how they are being used for the 4D printing approach in medical engineering applications. In this regard, a particular emphasis is dedicated to the latest progress in the innovation and development of stimuli-responsive materials that are activated and respond over time to physical, chemical, and biological stimuli and their exploitation through 3D printing methods to fabrication 4D printing smart parts such as intelligent tissue-engineered scaffolds, smart orthopedic implants, and targeted drug delivery systems. On the other hand, major challenges in this technology are explained along with some suggestions for future works to address existing limitations. It is worth noting that despite significant research that has been carried out into 4D printing, it might be more valuable if some investigation is done into 4D bio-printing applications and how this approach will be developed.

Bone shows a radial gradient architecture with the exterior densified cortical bone and the interior porous cancellous bone. However, previous studies presented uniform designs for bone scaffolds that do not mimic natural bone's gradient structure. Hence, mimicking native bone structures is still challenging in bone tissue engineering. In this study, a novel biomimetic bone scaffold with Haversian channels is designed, which approximates mimicking the native bone structure. Also, the influence of adding graphene oxide (GO) to polycaprolactone (PCL)‐based scaffolds are investigated by preparing PCL/GO composite ink containing 0.25% and 0.75% GO and then 3D printing scaffolds by an extrusion‐based machine. Scanning electron microscopy (SEM) is used for morphological analysis. SEM reveals good printability and interconnected pore structure. The contact angle test shows that wettability reinforces with the increase of GO content. The mechanical behavior of the scaffolds under compression is examined numerically and experimentally. The results indicate that incorporation of GO can affect bone scaffolds' Young's modulus and von Mises stress distribution. Moreover, the biodegradation rates accelerate in the PCL/GO scaffolds. Biological characterizations, such as cell growth, viability, and attachment, are performed utilizing osteoblast cells. Compared to pure PCL, an enhancement is observed in cell viability in the PCL/GO scaffolds.

This paper shows that using don't cares computed for area optimization during local node minimization may result in an increase in the power consumption of other nodes in a Boolean network. It then presents techniques for computing a subset of observability and satisfiability don't care conditions that can be used freely to optimize the local function of nodes. The concept of minimal variable support is then used to optimize the local function of each node for minimum power using its power relevant don't care set, that is, to reimplement the local function using a modified support that has a lower switching activity. Empirical results on a set of benchmark circuits are presented and discussed.

Countries around the world generate electricity from renewable resources to decarbonise their societies and reduce global warming. Some countries have already outlined their wishes to produce a part of their total energy consumption from renewable sources in the coming years and gradually reduce the use of nuclear energy and fossil fuel in favour of cleaner fuels. While renewable energies are significant factors in tackling climate change, the parameters that can influence their performance should be analysed in detail during the design process. One of these parameters is the foundation of an offshore wind turbine. Offshore wind turbines allow more energy to be produced than an onshore installation, and do not have any harmful effects on human beings, while their geotechnical aspects need to be clearly determined in advance. In this study, the influential parameters such as soil type, the number of bolts in the design, and the size of the structure were analysed using the finite element method for three different designs. The simulations showed that some soil properties, such as cohesion, do not influence the results, while Young’s modulus has a large influence on the designs. Additionally, the results of this study showed that the maximum stress concentrations are at the bolts and connection joints where they are too close to the steel’s yield stress. It also proves that the non-elastic behaviour of the soil does not require to be assigned for such analyses and it can be simplified only with its elastic behaviour. The embedded length affects the lateral displacement, while the number of bolts influences the structure’s resistance to external loads.