In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex optimization problem that guarantees the global optimal solution. The convex optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Background: Transnational networks such as Communities of Practice (CoPs) are flourishing, yet their role in diffusing health systems reforms has been seldom investigated. Over the past decade, performance-based financing (PBF) has rapidly spread in Africa. This study explores how, through the PBF Community of Practice’ s attributes, structure, and strategies, PBF diffusion was fostered in sub-Saharan Africa (SSA). Methods: Informed by the diffusion entrepreneurs’ (DEs) framework dimensions, we used a mixed methods convergent design to investigate how the attributes, structure, and strategies of this community fostered the diffusion of PBF. The quantitative strand of work included firstly a semantic discourse analysis of textual data extracted from CoP’ s online discussion forum (n = 1346 posts). Secondly, the relational data extracted from these 1346 forum posts was examined using social network analysis (SNA). We confronted these quantitative results with a thematic analysis of qualitative interviews (n = 40) and data extracted from the CoP’ s key documentation (n = 17). Results: CoP members’ attributes included: representation systems anchored in clinical and economic sciences, strong expectations that the CoP would boost professional visibility and career, and significant health systems knowledge and social resources. The CoP’ s core group, dominated by high-income country (HIC) members, critically matched PBF principles to major health systems issues in Africa. The broad consensus in online PBF thematic discussions created a strong sense of community, a breeding ground for emulation among CoP members. The CoP also sought to produce and promote experiential knowledge exchanges about PBF amongst African practitioners. Findings from network analyses showed that the promoted Africa-driven community was led by HIC members, although their prominence tended to decrease with time. Conclusion: This empirical research highlighted some of the constituting features, structure, and strategies of policy networks in influencing health policy diffusion. Despite good intentions to disrupt the established governance landscape, influential actors coming from HICs continued to drive the framing, and shaped health systems policy experimentation, emulation, and learning in African countries. Beyond mere knowledge exchange platforms, CoP can act as meaningful transnational policy networks pursuing the diffusion of health systems reforms, such as PBF.

Numerous algorithms have recently been invented with varying strengths and weaknesses, none of which is the best for all cases. Herein, a hybrid optimization method known as a PSOHHO optimization algorithm is presented. There are two methods for combining algorithms: parallel and sequential. We adopted the parallel method and optimized the algorithm's performance. We cover the weaknesses of one algorithm with the strengths of another algorithm using a new method of combination. In this method, using several formulas, the top populations are exchanged between the two algorithms, and a new population is created. With this ability, the strengths of an algorithm can be used to compensate for the weaknesses of the other algorithm. In this method, no changes are made to the algorithms. The main goal is to use existing algorithms. This method aims to attain the optimal solution in the shortest time possible. Two algorithms of particle swarm optimization (PSO) and Harris Hawks optimization (HHO) were used to present this method and five truss samples were considered to confirm the performance of this method. Based on the results, this method has rapid convergence speed and acceptable results compared to the other methods. It also yields better results than its basic algorithms.