This work has been done with using of epoxy resin mixed with Granite powder were weighted by percent volume (5,10,15, and 20)%and then mixed with epoxy polymer to compose polymer composite. Hand lay-up technique is used in fabrication of the composite samples. Hardness test was carried out for the proper samples in both normal condition and after immersion in HCL (1 M and 2 M) solutions for periods ranging up to 10 weeks. After comparing the results between the polymer and their composite, the hardness increased with increasing Granite weight percent, it was found that Hardness were greater for the composites before immersion compared with their values after immersion.

In this work gold nanoparticles (AuNPs), were prepared. Chemical method (Seed-Growth) was used to prepare it, then doping AuNPs with porous silicon (PS), used silicon wafer p-type to produce (PS) the processes doping achieved by electrochemical etching, the solution etching consist of HF, ethanol and AuNPs suspension, the result UV-visible absorption for AuNPs suspension showed the single peak located at ~(530 – 521) nm that related to SPR, the single peak is confirmed that the NPs present in the suspension is spherical shape and non-aggregated. X-ray diffraction analysis indicated growth AuNPs with PS. compare the PS layer without AuNPs and with AuNPs doped for electrical properties and sensitivity properties we found AuNPs:PS is more

Nanofluids (dispersion of nanoparticles in a base fluid) have been suggested as promising agents in subsurface industries including enhanced oil recovery. Nanoparticles can easily pass through small pore throats in reservoirs formations; however, physicochemical interactions between nanoparticles and between nanoparticles and rocks can cause a significant retention of nanoparticles. This study investigated the transport, attach, and retention of silica nanoparticles in core plugs. The hydrophilic silica nanoparticles were injected into limestone core as nanofluid of different nanoparticles size (5 nm, and 20 nm), concentration (0.005 – 0.1 wt% SiO2), and base fluid salinity (0 – 3 wt% NaCl) at different temperatures (23, and 50 °C). D

The direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li

The primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most

Conjugated Linoleic Acid (CLA) is an essential polyunsaturated omega fatty acid that occurs naturally in vegetable oils. It also plays an important role in preserving meat for longer periods by preventing oxidation of other fats. Thus, it can be used in the production of functional foods with high biological value and low cholesterol levels by adding poultry diets. Objective: The aim of the present study was to evaluate the effect of adding CLA to broiler diets on production performance and fatty acid content in the meat. Methodology: One-day-old Ross-308 chicks were randomly distributed into four dietary treatment groups: control (0 g CLA kgG1 diet; A1), 0.5 g CLA kgG1 diet (A2), 0.75 g CLA kgG1 diet (A3) and 1 g CLA kgG1 diet (A4). Diets

This paper highlights the main features of conjunctive adverbials and their occurrence in English academic prose. It accounts for the semantic roles of conjunctive adverbials, forms in which they are used, their positions within a sentence, and their frequency of occurrence in different registers with special reference to academic prose. It also tries to investigate possible differences in men's and women's use of conjunctive adverbials.
Keyword: conjunctive adverbials, linking adverbials, stance adverbials, circumstance adverbials, academic prose

The study employs Critical Discourse Analysis (CDA) to analyze how technological discourses are influenced by AI-generate d English texts. The research marries Fairclough’s three-dimensional discourse analysis, Van Dijk’s socio-cognitive approach, and Corpus-Assisted Discourse Studies (CADS) in the use of mixed-methods research, integrating primarily qualitative analysis with quantitative corpus-based data, to perform a thorough analysis of twenty AI-produced English texts. The findings identify the sophisticated linguistic mechanisms through which AI language employs modality, nominalization, passive voice, and interdiscursive blending to normalize and legitimize dominant contemporary ideologies. These mechanisms serve to legitimize te

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp