This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manufacture eco-friendly wood-plastic composites suitable for structural use, addressing environmental concerns by recycling wood waste. This research aims to contribute to sustainability by creating materials for decorative elements or secondary roofing, minimizing the environmental impact of wood waste, and promoting eco-friendly alternatives for daily use.
Explain in this study, thickness has an inverse relationship with electrical resistivity and a linear relationship with Grain boundary scattering. According to the (Fuchs-Sondheier, Mayadas-Shatzkces) model, grain boundary scattering leads To an Increase in electrical Resistivity. The surface scattering Coefficient of Ag, which Fuchs-Sondheier and Mayadas-Shatzkces measured at , Ag's grain boundary reflection coefficient , which Mayadas-Shatzkces measured at , If the concentration of material has an effect on metal's electrical properties, According to this silver is a good electrical conductor and is used frequently in electrical and electronic circuits.
Dental clinicians and professionals need an affordable, nontoxic, and effective disinfectant against infectious microorganisms when dealing with the contaminated dental impressions. This study evaluated the efficiency of hypochlorous acid (HOCl) as an antimicrobial disinfectant by spraying technique for the alginate impression materials, compared with sodium hypochlorite, and its effect on dimensional stability and reproduction of details. HOCl with a concentration of 200 ppm for 5 and 10 min was compared with the control group (no treatment) as a negative control and with sodium hypochlorite (% 0.5) as a positive control. Candida albicans, Staphylococcus aureus, and Pseudomonas aeruginosa were selected to assess the antimicrobi
... Show MoreThis research aims to investigate the effect of four types of nanomaterial on the Marshall properties and durability of warm mix asphalt (WMA). These types are; nano silica(NS), nano carbonate calcium (NCC), nano clay(NC), and nanoplatelets (NP). For each type of Nanomaterial, three contents are tried as following; NS(1%, 3%, and 5%), NCC(2%, 4%, and 6%), NC(3%, 5%, and 7%), and NP (2%, 4%, and 6%) by weight of asphalt cement. Following Marhsall mix design method, the optimum asphalt cement content is determined, thereafter the optimum dosage for each nanomaterial is obtained based on the highest Marshall stability value. The durability of the control mix (no nanomaterial) and modified mixtures have been compared based on moisture damage, r
... Show MoreThis investigation was undertaken to evaluate the effectiveness of using Hydrated lime as a (partial substitute) by weight of filler (lime stone powder) with five consecutive percentage namely (1.0, 1.5, 2.0, 2.5, 3.0) % by means of aggregate treatment, by introducing dry lime on dry and 2–3% Saturated surface aggregate on both wearing and binder coarse. Marshall design method, indirect tensile test and permanent deformation under repeated loading of Pneumatic repeated load system at full range of temperature (20, 40, 60) C0 were examined The study revealed that the use of 2.0% and 1.5 % of dry and wet replacement extend the pavement characteristics by improving the Marshall properties and increasing the TSR%. Finally, increase permanent
... Show MoreWith the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
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