In this study, a new class of polymeric nanocomposites was synthesized and characterized.  One mole of dimethyl adipate and two moles of thiosemicarbazide in ethanol first reacted to form the compound [C1]. Compound [C1] then reacted with sodium hydroxide to produce compounds [C2]. Hydrazine hydrate reacted with compound [C2] to generate compound [C3]. Compound [C4] was synthesized from compound [C3] and maleic anhydride. A polymer [C5] is formed by the reaction of the compound [C4] with ammonium persulfate as an initiator. This polymer was then combined with nano: ZnNPs, AgNPs, SiNPs, or IONPs using a hotplate stirrer for 3 hours to produce nanocomposites [C6-C9]. FTIR, 1H-NMR, and Field Emission Scanning Electron Microscope (FESEM) were

Functionalized-multi wall carbon nanotubes (F-MWCNTs) and functionalized-single wall carbon nanotubes (F-SWCNTs) were well enhanced using CoO Nanoparticles. The sensor device consisted of a film of sensitive material (F-MWCNTs/CoONPs) and (F-SWCNTs/CoO NPs) deposited by drop- casting on an n-type porous silicon substrate. The two sensors perform high sensitivity to NO₂ gas at room temperatures. The analysis indicated that the (F-MWCNTs/CoONPs) have a better performance than (F-SWCNTs/CoONPs). The F-SWCNTs/CoONPs gas sensor shows high sensitivity (19.1 %) at RT with response time 17 sec, while F-MWCNTs/CoONPs gas sensor show better sensitivity (39 %) at RT with response time 13 sec. The device shows a very reproducible sensor p

One of the most difficult tasks in modern medical societies is the process of identifying a cure for many infectious diseases caused by drug-resistant microbes. Therefore, it has become necessary to discover new compounds that work in this regard. The currently prepared Schiff base, derived from thiazole, has a biological activity against bacteria and biofilms and its activity increases when it is associated with copper, zinc and platinum ions and forms metal complexes. This study highlights the synthesis and evaluation of novel biological compounds as inhibitors of bacterial growth and biofilms. A three newly complexes are resulting from the reaction of a new Schiff base ligand (LC) with metal ions (Zn, Cu, Pt). The new ligand (LC)

Regression models are among the most important tools in scientific research and data analysis. Among these models, fuzzy regression models stand out as a modern form that addresses issues of uncertain data that do not conform to the assumptions of traditional models. In this study, we present fuzzy regression models with a focus on fuzzy linear quantitative models, in addition to fuzzy support vector machine (SVM) models. Generally, linear models are considered less effective compared to non-linear models, and to address this issue, hybrid models combining both types have been introduced. The concept of hybrid models has been generalized to fuzzy models in this paper, where we introduce a hybrid model that combines both linear and non-linea

Four metal compounds mixed ligand of azo dye ligand (L) and metformin.(Met) were produced at aquatic ethanol for (1:1:1) (M:L:Met). The prepared compounds were identified by utilizing atomic absorption flame, FT.IR and UV–Vis spectrum manners as well as conductivity mensuration. These compounds was assayed of the gained datum the octahedral geometry was proposed into whole prepared complexes.Also in this research was studied represented examining the antibacterial and antifungal impact of the azo dye ligand (L), metformin.(Met) and (Co,Ni, Cu and Cd complexes) on four types of pathogenic, clinically isolated bacteria that are resistant to antibiotic, like Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneu

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti