Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time of 240 min, 5 g/L of dosage, initial concentration of 25 mg/L, and a temperature of 45 °C. The removal percentage of TEC under the optimum condition was 96%. Thermodynamic analysis indicated that the removal efficiency was slightly increased with temperature depending on the positive value of Δ𝐻°, thus indicating that the adsorption phenomenon was endothermic. The Langmuir model fitted the study (R2 = 0.998), demonstrating that the adsorption sites were homogenous. The experimental results were best matched with the second-order kinetic model, implying that chemisorption was the primary process during the adsorption process. Compared to previous research and based on the value of qmax (15.60 mg/g), the biomass was suitable for TEC removal.
Aim: To evaluate the wettability and microhardness of Zirconium (ZrO2) dental material when coated with different concentrations of Faujasite. Materials and methods: 30 circular disks produced from ZrO2, then each group is classified into 10 control groups, 10 coated groups with 3% Faujasite, and 10 coated groups with 7% faujasite by electro-spun tool to study variable properties in hardness and water contact angle of implant materials. Results: This study stated the high hardness in 7% of faujasite concentration for ZrO2, in addition, the contact angle decreased gradually until reach 0 ᵒ in 7% concentration of faujasite with ZrO2 Conclusion: Water contact angle (WCA) declined till disappeared in (7% wt.) of faujasite coated with the Z
... Show MoreIn this work, CdS/TiO2 nanotubes composite nanofilms were successfully synthesized via electrodeposition technique. TiO2 titania nanotube arrays (NTAs) are commonly used in photoelectrochemical cells as the photoelectrode due to their high surface area, excellent charge transfer between interfaces and fewer interfacial grain boundaries. The anodization technique of titanium foil was used to prepare TiO2 NTAs photoelectrode. The concentration of CdCl2 played an important role in the formation of CdS nanoparticles. Field emission scanning electron microscopy (FESEM) shows that the CdS nanoparticles were well deposited onto the outer and inner of nanotube at 40 mM of CdCl2. X-ray diffraction (XRD) and energy dispersive X-ray (EDX) analyses wer
... Show MoreStatement of the Problem. The use of orthodontic fixed appliances may adversely affect oral health leading to demineralizing lesions and the development of gingival problems. Aims of the Study. The study aimed to coat orthodontic archwires with chlorhexidine hexametaphosphate nanoparticles (CHX-HMP NPs) and to evaluate the elusion of CHX from CHX-HMP NPs. Materials and Methods. A solution of CHX-HMP nanoparticles with an overall concentration of 5 mM for both CHX and HMP was prepared, characterized (using atomic force microscope and Fourier transformation infrared spectroscopy), and used to coat orthodontic stainless steel (SSW) and NiTi archwires (NiTiW). The coated segments were characterized (using scanning electron microscopy
... Show MoreSelenium is naturally present in the human body, animals, and plants, and is one of the important elements in their growth and maintenance. Recently, the nanoform of selenium has attracted attention due to its low toxicity and a high degree of adsorption compared to its organic and inorganic forms. The current study aimed to examine the effect of Cress leaves (Lepidium sativum L.) extract in combination with selenium nanoparticles in alleviating polycystic ovary syndrome in letrozole-induced PCOS in adult female rats. Nonthermal or cold plasma was used in the synthesis of selenium nanoparticles. Subsequently, the produced nanoparticles were identified, the 30 rats were divided into 6 equal groups, the first group was healthy (negative contr
... Show MoreA batch and flow injection (FI) spectrophotometric methods are described for the determination of barbituric acid in aqueous and urine samples. The method is based on the oxidative coupling reaction of barbituric acid with 4-aminoantipyrine and potassium iodate to form purple water soluble stable product at λ 510 nm. Good linearity for both methods was obtained ranging from 2 to 60 μg mL−1, 5–100 μg mL−1 for batch and FI techniques, respectively. The limit of detection (signal/noise = 3) of 0.45 μg mL−1 for batch method and 0.48 μg mL−1 for FI analysis was obtained. The proposed methods were applied successfully for the determination of barbituric acid in tap water, river water, and urine samples with good recoveries of 99.92
... Show MoreThe study was conducted in the poultry field, College of Agriculture, Al-Muthanna University from 1/3/2018 to 6/4/2018 to determine the effect of commercial Ascomax powder produced from seaweed (Ascophyllum nodocum) on some productive performance of broilers. A total of 400, one day, Ross 308 broiler chicks were used for 35 days. The chicks were randomly distributed to 4 treatments, four replicates per treatment (25 chick / replicate). The treatments were as follows: T1: (control treatment), while T2, T3 and T4 added diet by Ascomax powder by 1, 1.5 and 2 g per 1 kg of the basal diet, respectively. The results of the study showed a significant superiority (P <0.05) for the added Ascomax powder treatments compared to the treatment of control
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for