Remanufacturing contributes to achieving economical,environmental,and social sustainability,and one of its main steps is disassembly aiming to acquire a set of recyclable and reusable components from endof-life produc...Remanufacturing contributes to achieving economical,environmental,and social sustainability,and one of its main steps is disassembly aiming to acquire a set of recyclable and reusable components from endof-life products.This research considers a multi-objective multi-product disassembly sequence planning problem under uncertain circumstances to realize a trade-off among economic,environmental,and social sustainability.Firstly,a multi-objective chance-constrained programming model is formulized to achieve maximal disassembly profit and minimal noise pollution while satisfying energy consumption requirements and obeying various complex product structures.Secondly,a multi-objective group teaching optimization algorithm combining a stochastic simulation approach is particularly devised to handle the problem.In the designed approach,problem-specific encoding and decoding methods are employed to represent and produce feasible solutions.The stochastic simulation approach is utilized to assess the feasibility and performance of the obtained solutions under uncertain environments.Rank and crowding distance approaches are introduced to realize ability grouping,namely,dividing the population into two groups.Precedence preserving crossover and mutation operators are separately utilized on the two groups to achieve population evolution,and an adaptive local search method is developed to enhance exploitation.Thirdly,comparison experiments on some real-world test problems with different scales are carried out.Through dissecting the experimental results with three performance metrics,it can be observed that the devised approach outperforms its competitors by 9.39%-10.00%,11.37%-59.86%,and 2.36%-7.73%regarding performance,respectively.The experimental results demonstrate the efficiency and excellence of the devised approach in providing high-quality disassembly schemes for managers and engineers.展开更多
Faster and predictable osseointegration is crucial for the success of dental implants, especially in patients with compromised local or systemic conditions. Despite various surface modifications on the commercially av...Faster and predictable osseointegration is crucial for the success of dental implants, especially in patients with compromised local or systemic conditions. Despite various surface modifications on the commercially available Titanium (Ti) dental implants, the bioactivity of Ti is still low. Thus, to achieve both biological and therapeutic activity on titanium surfaces, surface modification techniques such as titanium nanotubes have been studied as nanotube surfaces can hold therapeutic drugs and molecules. The main aim of the present research work is to study the early osseointegration around the novel Simvastatin drug eluting nanotubular dental implant. In the present research, the titanium nanotubes were fabricated on the screw-shaped dental implant surface and the Simvastatin drug was loaded into the nanotubes using the ultrasonication dip method. In vitro and In vivo studies were carried out on the modified dental implants. In vitro cell culture study reported enhanced osteogenic activity on the drug-loaded nanotube surface implants. The in vivo animal studies were evaluated by micro-CT, histopathology, and reverse torque removal analysis methods. The test results showed faster osseointegration with the strong interface on the Simvastatin drug-loaded implant surface at 4 weeks of healing as compared to the control implants.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62173356 and 61703320)Shandong Province Outstanding Youth Innovation Team Project of Colleges and Universities(No.2020RWG011)+4 种基金Natural Science Foundation of Shandong Province(No.ZR202111110025)Science and Technology Development Fund(FDCT)Macao SAR(No.0019/2021/A)Innovation Centre for Digital Business and Capital Development of Beijing Technology and Business University(No.SZSK202208)Zhuhai Industry-University-Research Project with Hongkong and Macao(No.ZH22017002210014PWC).
文摘Remanufacturing contributes to achieving economical,environmental,and social sustainability,and one of its main steps is disassembly aiming to acquire a set of recyclable and reusable components from endof-life products.This research considers a multi-objective multi-product disassembly sequence planning problem under uncertain circumstances to realize a trade-off among economic,environmental,and social sustainability.Firstly,a multi-objective chance-constrained programming model is formulized to achieve maximal disassembly profit and minimal noise pollution while satisfying energy consumption requirements and obeying various complex product structures.Secondly,a multi-objective group teaching optimization algorithm combining a stochastic simulation approach is particularly devised to handle the problem.In the designed approach,problem-specific encoding and decoding methods are employed to represent and produce feasible solutions.The stochastic simulation approach is utilized to assess the feasibility and performance of the obtained solutions under uncertain environments.Rank and crowding distance approaches are introduced to realize ability grouping,namely,dividing the population into two groups.Precedence preserving crossover and mutation operators are separately utilized on the two groups to achieve population evolution,and an adaptive local search method is developed to enhance exploitation.Thirdly,comparison experiments on some real-world test problems with different scales are carried out.Through dissecting the experimental results with three performance metrics,it can be observed that the devised approach outperforms its competitors by 9.39%-10.00%,11.37%-59.86%,and 2.36%-7.73%regarding performance,respectively.The experimental results demonstrate the efficiency and excellence of the devised approach in providing high-quality disassembly schemes for managers and engineers.
文摘Faster and predictable osseointegration is crucial for the success of dental implants, especially in patients with compromised local or systemic conditions. Despite various surface modifications on the commercially available Titanium (Ti) dental implants, the bioactivity of Ti is still low. Thus, to achieve both biological and therapeutic activity on titanium surfaces, surface modification techniques such as titanium nanotubes have been studied as nanotube surfaces can hold therapeutic drugs and molecules. The main aim of the present research work is to study the early osseointegration around the novel Simvastatin drug eluting nanotubular dental implant. In the present research, the titanium nanotubes were fabricated on the screw-shaped dental implant surface and the Simvastatin drug was loaded into the nanotubes using the ultrasonication dip method. In vitro and In vivo studies were carried out on the modified dental implants. In vitro cell culture study reported enhanced osteogenic activity on the drug-loaded nanotube surface implants. The in vivo animal studies were evaluated by micro-CT, histopathology, and reverse torque removal analysis methods. The test results showed faster osseointegration with the strong interface on the Simvastatin drug-loaded implant surface at 4 weeks of healing as compared to the control implants.
