Background: Restoration of the gingival margin of Class II cavities with composite resin continues to be problematic, especially where no enamel exists for bonding to the gingival margin. The aim of study is to evaluate the marginal leakage at enamel and cementum margin of class II MOD cavities using amalgam restoration and modern composite restorations Filtek™ P90, Filtek™ Z250 XT (Nano Hybrid Universal Restorative) and SDR bulk fill with different restoratives techniques. Materials and method: Eighty sound maxillary first premolar teeth were collected and divided into two main groups, enamel group and cementum group (40 teeth) for each group. The enamel group was prepared with standardized Class II MOD cavity with gingival margin (1 mm above C.E.J) on both box sides. While the cementum group with the gingival margin (1 mm below C.E.J) on both sides. The enamel and cementum groups were then subdivided into eight subgroups for each (five teeth) with 10 boxes for each group. Subgroups within the main group named according to materials and techniques that were used with it as following: Amalgam subgroup (Permite, SDI), SDR subgroup (DENTSPLY) with bulk technique, Filtek™ P90 subgroup (3M ESPE) with three incremental techniques (Oblique, Horizontal and Centripetal technique), and Filtek™ Z250XT subgroup (3M ESPE) with three incremental techniques (Oblique, Horizontal and Centripetal technique).After specimens were stored in distilled water at 37°C for 7 days. All specimens were subjected to thermocycling at (5° to 55 °C). Microleakage was evaluated by stereomicroscope (20 X). Data were analyzed statistically by Kruskal-Wallis test and Mann-Whitney U-test. Result: All experimental groups showed leakage at cementum more than enamel groups. SDR bulk fill subgroup showed the highest marginal leakage among all experimental groups followed by Filtek™ Z250 XT subgroup with horizontal technique at both enamel and cementum groups. Silorane and Filtek™ Z250 XT subgroups with oblique technique showed the least marginal leakage followed by centripetal technique at both enamel and cementum groups. Amalgam restoration subgroup shows lesser leakage than SDR bulk fills subgroup significantly at both enamel and cementum groups. While it show higher leakage than Silorane subgroup with oblique technique significantly at enamel margin only. Conclusion: The limiting factors for marginal leakage are technique and material dependent.
The current study was designed to evaluate the anti-inflammatory effect of GKB in the rat model of granulomatous inflammation. Thirty rats were distributed into five groups: The first group served as negative control group that received distilled water (DW) only without inducting inflammation, positive control group; treated with DW with the induction of inflammation and they were assigned to cotton pellet-induced granuloma, ginkgo biloba (GKB) treated group (200mg/kg/day), dexamethasone-treated group (1mg/kg), and Prednisolone treated group (5mg/kg). All the treatments were given orally for seven consecutive days. On day eight, the rats were anesthetized and the pellets together with granulation tissue were carefully removed
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Despite the global economic downturn, online e-commerce, especially the sale of counterfeit goods, continues to witness a rise in sales, and one of the important players in e-commerce is the owners of e-commerce auction sites. Although they do not have a direct role in trademark infringement, they still consider them indirectly responsible (secondary liability) for infringing on their trademarks. Thus, many cases have been filed by the owners of the original trademarks (which have been infringed by persons who have sold some of the goods and products that are imitating their marks through some electronic auctions) against the owners of those auctions. In view of the international character of the Internet, in different countries, and despit
... Show MoreThis paper discusses a comparative study to relate parametric and non-parametric mode decomposition algorithms for response-only data. Three popular mode decomposition algorithms are included in this study: the Eigensystem Realization Algorithm with the Natural Excitation Technique (NExT-ERA) for the parametric algorithm, as well as the Principal Component Analysis (PCA) and the Independent Component Analysis (ICA) for the non-parametric algorithms. A comprehensive parametric study is provided for (i) different response types, (ii) excitation types, (iii) system damping, and (iv) sensor spatial resolution to compare the mode shapes and modal coordinates of using a 10-DOF building model. The mode decomposition results are also compared using
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
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KE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9
NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among