The aim of this study was to investigate the hybrid effects of ZrO 2 nanoparticles (nano-ZrO 2 ) and aluminum borate whiskers (ABWs) on flexural strength and surface hardness of denture base resin, polymethyl methacrylate (PMMA). Both nano-ZrO 2 and ABWs were modified by silane coupling agent (Z6030) before being mixed with PMMA. Various amounts of silanized nano-ZrO 2 and ABWs were mixed with PMMA to prepare ZrO 2 -ABW/PMMA composites. Flexural strength and surface hardness were evaluated using threepoint bending test and Vickers hardness test respectively. Fractured surfaces were also observed by scanning electron microscopy (SEM). The mechanical behaviors of silanized ZrO 2 -ABW/PMMA composites were significantly improved. Flexural strength reached a maximum value of 108.01±5.54 MPa when 2 wt% of nano-ZrO 2 was mixed with ABWs at a ZrO 2 /ABW ratio of 1:2, amounting to an increase of 52% when compared with pure PMMA. Surface hardness achieved a maximum value of 22.50±0.86 MPa when 3 wt% of nano-ZrO 2 was mixed with ABWs at the same ZrO 2 /ABW ratio, which was an increase of 27% when compared with pure PMMA.

The preparation of CaSiO 3-PMMA nanocomposite denture matrix was reported. We investigated the optimal amount of CaSiO 3 nano-particles modified by silane coupling agent (Z-6030) on strengthen flexural strength and surface hardness (Knoop hardness) of the nano-CaSiO 3 /PMMA composite materials. The results indicated that the 1.5% CaSiO 3 nano-particles could enable the nanocomposite to have the maximum flexural strength (90.50±4.86) MPa(increasing nearly 40% contrast to the blank group), while 2.0% CaSiO 3 nano-particles made the nanocomposite to have a maximum Knoop hardness(24.59±0.98) MPa (augmenting with 24% compared with the blank group). Furthermore, the fracture surface was investigated by scanning electron microscope (SEM), which revealed that the silane coupling agent (Z-6030) affected the dispersion of the CaSiO 3 nanoparticles in PMMA matrix, and the fracture surface of the 1.5% group is regular with obvious ductile dimple pattern demonstrating typical ductile fracture.

Top-N frequent itemsets mining gets the interesting results by appointing the quantity of the most frequent itemsets. It is an important data mining application. This article proposed a Top-N frequent itemsets mining algorithm based on greedy method. The obtained Top-N itemsets are stored in a static doubly linked list. Join two frequent itemsets which have the highest support in the not joined Top-N itemsets. The frequent itemsets have the higher support that can be generated early. We can adjust the border support quickly. According to the analysis and experiments, this new algorithm demonstrates better performance than Apriori and NApriori on the time and space performance.

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