In this research, a bimodal nanoporous Baghdadite (NB) (Ca3ZrSi2O9) was prepared by a modified sol-gel method using P123 as a surfactant. The effects of P123's contents on the structural and textural properties as well as the drug delivery behavior of NB were assessed in vitro. The usage of P123 offered a new route for the synthesis of NB. The synthesized NB samples with different amounts of P123 were studied through X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), N2 adsorption-desorption, field emission scanning electron microscopy (FESEM) equipped with energy-dispersive X-ray analysis spectroscopy (EDAX) and transmission electron microscopy (TEM). The results showed that a single-phase Baghdadite was obtained by this new method at the calcination temperature of 800?°C. It was found that an increase in P123's content up to 0.025?mol changed the morphology of NB samples from mountain-like to needle-like. The potential application of NB samples as drug delivery agents was assessed by estimating their release properties up to 240?h. This research revealed that the synthesized Baghdadite could be used as a potential nanoporous carrier with controlled release capability in bone tissue regeneration. 相似文献
Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (Vp) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R2) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.
Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer... 相似文献
This paper presents a proposal for multiobjective Invasive Weed Optimization (IWO) based on nondominated sorting of the solutions. IWO is an ecologically inspired stochastic optimization algorithm which has shown successful results for global optimization. In the present work, performance of the proposed nondominated sorting IWO (NSIWO) algorithm is evaluated through a number of well-known benchmarks for multiobjective optimization. The simulation results of the test problems show that this algorithm is comparable with other multiobjective evolutionary algorithms and is also capable of finding better spread of solutions in some cases. Next, the proposed algorithm is employed to study the Pareto improvement model in two complex electricity markets. First, the Pareto improvement solution set is obtained for a three-player oligopolistic electricity market with a nonlinear demand function. Then, the IEEE 30-bus power system with transmission constraints is considered, and the Pareto improvement solutions are found for the model with deterministic cost functions. In addition, NSIWO algorithm is used to analyze this system with stochastic cost data in a risk management problem which maximizes the expected total profit but minimizes the profit risk in the market. 相似文献
Poly(2-hydroxyethyl methacrylate) (pHEMA) as a biomaterial with excellent biocompatibility and cytocompatibility elicits a minimal immunological response from host tissue making it desirable for different biomedical applications. This article seeks to provide an in-depth overview of the properties and biomedical applications of pHEMA for bone tissue regeneration, wound healing, cancer therapy (stimuli and non-stimuli responsive systems), and ophthalmic applications (contact lenses and ocular drug delivery). As this polymer has been widely applied in ophthalmic applications, a specific consideration has been devoted to this field. Pure pHEMA does not possess antimicrobial properties and the site where the biomedical device is employed may be susceptible to microbial infections. Therefore, antimicrobial strategies such as the use of silver nanoparticles, antibiotics, and antimicrobial agents can be utilized to protect against infections. Therefore, the antimicrobial strategies besides the drug delivery applications of pHEMA were covered. With continuous research and advancement in science and technology, the outlook of pHEMA is promising as it will most certainly be utilized in more biomedical applications in the near future. The aim of this review was to bring together state-of-the-art research on pHEMA and their applications. 相似文献
THERMAL SPRAYING provides a large range ofcoatings,which increase the wear resistance ofsubstrates[1].One of the major coating families is thecermet,composed of hard ceramic particles with ametallic binder.The most commonly used cermetcoatings in industrial applications are based on eitherthe WC-Co or the Cr3C2-Ni(Cr)systems with WC-17wt%Co and Cr3C2-25wt%Ni(Cr)being typicalcompositions[2,3].Although WC-Co deposits are hardand wear resistant at ambient temperatures their rangeof ap… 相似文献
This paper encompasses the presentation of an enhanced approach with the capacity to reduce the time complexity of accessing nodes in m-dimensional matrices from \(O(n^m)\) to \(O(n\log n)\). The accomplishment of this process is attained by the serialization of nD (nD) matrices to single-dimensional arrays followed by the access of nodes accordingly. Linear representation of nD matrix data structure induces a superior parallelism of matrix calculations over dense, parallel core micro-architecture computers, including NVIDIA GPGPU Supercomputing and Intel Xeon Phi processing boards. This approach is feasibly implemented as the core of matrix data representation in Math software such as Matlab, Mathematica and Maple, in IDEs for more optimized code generation and in Parallel Computing Libraries such as CUBLAS and Magma. 相似文献
Organizations have recently become interested in applying new approaches to reduce fuel consumptions, aiming at decreasing green house gases emission due to their harmful effects on environment and human health; however, the large difference between practical and theoretical experiments grows the concern about significant changes in the transportation environment, including fuel consumptions, carbon dioxide (CO2) emissions cost and vehicles velocity, that it encourages researchers to design a near-reality and robust pollution routing problem. This paper addresses a new time window pickup-delivery pollution routing problem (TWPDPRP) to deal with uncertain input data for the first time in the literature. For this purpose, a new mixed integer linear programming (MILP) approach is presented under uncertainty by taking green house emissions into consideration. The objective of the model is to minimize not only the travel distance and number of available vehicles along with the capacity and aggregated route duration restrictions but also the amount of fuel consumptions and green house emissions along with their total costs. Moreover, a robust counterpart of the MILP is introduced by applying the recent robust optimization theory. Computational results for several test problems indicate the capability and suitability of the presented MILP model in saving costs and reducing green house gases concurrently for the TWPDPRP problem. Finally, both deterministic and robust mathematical programming are compared and contrasted by a number of nominal and realizations under these test problems to judge the robustness of the solution achieved by the presented robust optimization model. 相似文献