The current research dealt with the development of sciences and arts over the course of human history, and the development of sciences with their natural and human trends are important areas in developing the knowledge and application base for industrial product design and design in its various fields. Bionic science is one of the sciences that works on applying biological methods and systems found in nature to study and design engineering systems and modern technology, and for industrial products to be highly efficient, durable and resistant to natural variables in daily life for use. The transfer of technology between life forms and industrial products is desirable because the processes of development at the level of science in general

T he article deals with the linguistic, cultural, sociolinguistic, functional and stylistic characteristics of the translation of gluttonic discourse text structures within the framework of the Arabic-Russian combination, as well as with the difficulties encountered in interpretation and translation and related to different conditions under which speech is generated in Arabic and Russian-speaking areas.

In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

Background. To identify the most common retention protocols practiced by Iraqi orthodontists using a specially designed e-survey. Furthermore, this study aimed to assess the effect of sociodemographic factors on the participant’s choice. Methods. Two hundred and twenty-five questionnaires with 23 multiple choice questions were sent to members of the Iraqi Orthodontic Society. The questionnaire was organized into four sections representing information about sociodemographic status of the orthodontists, factors affecting the selection of the retention system, commonly used retainers in the upper arch and lower arch, and duration of the retention system. The chi-square test was used to test the significant association between differe

Although the number of implants has increased gradually and consistently over the years to around one million per year globally, there is still far more potential for advancement in the field of dental implantology which is typically growing quickly. This study investigates the effect of nanofiller reinforcement high-performance polymer matrix to enhance mechanical and physical characteristics. Calcium silicate (CS)/Polyetherketoneketone (PEKK) biomedical composite (G0 as a control group) is reinforced with different weight percentages (G1-G4) of tellurium dioxide nanoparticles (TeO₂NPs) ( n = 5). This research uses ethanol as a binder for mixing various weight percentages (wt%) of TeO₂NPs w

Intestinal mucositis is referring to inflammatory or ulcerative lesions of the oral or gastrointestinal tract; one of the main reasons is treatment with cancer chemotherapy. The prodrug Irinotecan is converted by carboxylesterase to the active metabolite SN-38, conjugated by UGT enzyme to SN-38G and then deconjugated by ?-glucoronidase produced by intestinal bacterial flora to produce SN-38. Irinotecan induces intestinal mucositis and diarrhea due to increased concentration of its active metabolite (SN-38).To evaluate the protective effect of carvone, I.P injection of (75mg/kg/day) of irinotecan for 4 days to induce intestinal mucositis, carvone administered to mice orally for 6 days starting from day 1. Results showed that carvone (50mg

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback