Tungsten inert gas arc welding–based shaped metal deposition is a novel additive manufacturing technology which can be used for fabricating solid dense parts by melting a cold wire on a substrate in a layer-by-layer manner via continuous DC arc heat. The shaped metal deposition method would be an alternative way to traditional manufacturing methods, especially for complex featured and large-scale solid parts manufacturing, and it is particularly used for aerospace structural components, manufacturing, and repairing of die/molds and middle-sized dense parts. This article presents the designing, constructing, and controlling of an additive manufacturing system using tungsten inert gas plus wire–based shaped metal deposition metho

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Background In recent years, there has been a notable increase in the level of attention devoted to exploring capabilities of nanoparticles, specifically gold nanoparticles AuNPs, within context of modern times. AuNPs possess distinct biophysical properties, as a novel avenue as an antibacterial agent targeting Streptococcus Mutans and Candida Albicans. The aim of this study to create a nano-platform that has the potential to be environmentally sustainable, in addition to exhibiting exceptional antimicrobial properties against Streptococcus Mutans as well as Candida Albicans. Methods this study involved utilization of Pelargonium Graveolens leaves extract as a cost effective and environmentally sustainable app

Dust storms are a natural phenomenon occurring in most areas of Iraq. In recent years, the study of this phenomenon has become important because of the danger caused by increasing desertification at the expense of the green cover as well as its impact on human health. In this study  is important to devote the remote sensing of dust storms and its detection.Through this research, the dust storms can be detected in semi-arid areas, which are difficult to distinguish between these storms and desert areas. For the distinction between the dust storm pixels in the image with those that do not contain dust storm can be applied the Normalized Difference Dust Index (NDDI) and Brightness Temperature variation (BTV). MODIS sensors that carried

In this study, Zizphus spina-christi leaf powder was applied for the adsorption of methyl orange. The effect of different operating parameters on the Batch Process adsorption was investigated such as solution pH (2-12), effect of contact time (0-60 min.), initial dye concentration (2-20 mg/L), effect of adsorbent dosage (0-4.5 g) and effect of temperature (20-50ᵒC). The results show a maximum removal rate and adsorption capacity (%R= 23.146, q_e = 2.778 mg/g) at pH = 2 and equilibrium was reached at 40 min. The pseudo- second-order kinetics were found to be best fit for the removal process (R² = 0.997). Different isotherm models (Langmuir, Freundlich, Dubini-Radushkevich,Temkin)  were applied in this stud

In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

     Background:  Chemokine (C-X-C motif) ligand (CXCL9) has an important role recruiting the T-lymphocytes and immune response after infection by inducing T-cells accumulation around the areas associated with infections. However, this role is poorly known in relation with Toxoplasma gondii infection and also in association with thyroid hormones, which the present study is focused on. Methods: Eighty-seven women were included in this study for the period between September 2021 and February 2022. Blood samples of uninfected healthy pregnant, in addition to aborted and pregnant women infected with toxoplasmosis, were collected. Sera were then obtained and stored at -10°C. Toxo-latex agglutination test was done, followed by detec