Abstract Background: The daily usage of maxillofacial prostheses causes them to mechanically deteriorate with time. This study was aimed to evaluate the reinforcement of VST50F maxillofacial silicone by using yttrium oxide (Y2O3) nanoparticles (NPs) to resist aging and mechanical deterioration. Materials and Method: Y2O3 NPs (30–45nm) were loaded into VST50F maxillofacial silicone in two weight percentages (1 and 1.5 wt%), which were predetermined in a pilot study as the best rates for improving tear strength with minimum increase in hardness values. A total of 120 specimens were prepared and divided into the control and experimental groups (with 1 and 1.5 wt% Y2O3 addition). Each group included 40 specimens, 10 specimens for each paramet
... Show Moreتعتبر المعادلات التفاضلية الموجية من اهم المواضيع التي تمثل على سبيل المثال الحركة الموجية للاهتزازات الأرضية . ومن هنا فان ايجاد حلول تقريبيه لمثل هذه المعادلات بدقة وسرعه عالية وبشكل اسرع من الحلول التحليلية والمعقدة , اصبح ممكنا من خلال استخدام الذكاء الاصطناعي واساليب التعلم الالي. في هذا البحث هناك ثلاثة أهداف الأول هو تحويل مشكلة القيمة الأولية للمعادلة الموجية إلى شكلها القانوني وإيجاد حلها ا
... Show MoreThe performance of asphalt pavements is crucial due to heavy traffic loads from civil and industrial developments. Various additives and modifiers are used in flexible roads to improve their resistance to deterioration caused by climatic changes. From this context, modifying the asphalt binder with polymers is popular in asphalt pavement construction. The present research investigates the effect of Polyethylene (PE) polymers in powder form on the characteristics of asphalt mixtures since these polymers are composed of hydrocarbons. It is similar to asphalt binders, making them very effective in enhancing the performance of neat asphalt produced from the oil refinery. To confirm this, two types of PE, High-Density PE (HDPE) and Low-Density P
... Show MoreThe present work involves studying the effect of electrolyte composition [@1= 0.5 wt.% NH4F / 5% H2O / 5% Glycerol (GLY)/ 90% Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH4F / 5% H2O / 95% Ethylene Glycol (EG)] on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. T
... Show MoreThe present work involves studying the effect of electrolyte composition [@1= 0.5 wt.% NH4F / 5% H2O / 5% Glycerol (GLY)/ 90% Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH4F / 5% H2O / 95% Ethylene Glycol (EG)] on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. The photoelectrochemical response of TNTAs was evaluated
... Show MoreThe two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo
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