Toxic dyes are commonly discharged into waste waters and dyes are extensively used in the textile industry so it is necessary to find out efficient and eco-friendly method for treating waste waters resulting from industrial effluences. To achieve this aim the fungus Trichoderma sp. is employed into two lines: first line was self – immobilized fungal pellets in (Czapek – Dox medium) to adsorbs two dyes crystal violet, congo red by concentrations 0.01, 0.02, 0.03, 0.04, 0.05, 0.06 mg/L to both dyes, PH 2, room temperature with shaker in ( hrs.2,hrs.4,hrs.24) , by Uv- Visible spectrum . the removal efficiency of 0.05 mg/L crystal violet by Trichoderma sp was 96%. but there was no removal by congo red. The second line was immobilizing fungal mycelium to Graphain oxide free – standing aerogel to increase efficiency of adsorption. The decolorization of toxic dyes solution was detected by the change in the adsorption Uv- Visible spectrum and scanning microscopy analysis which revealed that there was dye adsorption on fungal mycelium surface. After treatment of crystal violet with 20 mg Graphain oxide -fungi aerogel in the condition PH 2, room temperature with shaker in time (hrs.2 ,hrs.4 , hrs.24 ) removal percentage to crystal violet was increasing with to raise concentrations the dye crystal violet until reaching the maximum removal percentage 97% in hrs.4 in 0.05mg/L concentrate , and it increased the efficiency of other concentrations . In contrast, according to congo red there was no color removal in any concentration within treatment time since congo red surface carries both negative and positive charges and causes electrostatic attraction, therefor, the adsorption reduced or does not occur.Trichoderma sp. is considered a selective removal to basic dyes and could be employed to remove dyes from industrial effluents.
The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
... Show MoreThe Corrosion protection effectiveness of Alimina(Al2O3,50nm)and Zinc oxide (ZnO,30nm) nanoparticales were studied on carbon steel and 316 stainless steel alloys in saline water (3.5%NaCl)at four temperatures: (20,30,40,50 OC)using three electrodes potentiostat. An average corrosion protection efficiencies of 65 %and 80% was achieved using Al2O3 NP's on carbon steel and stainless steel samples respectively, and it seems that no effect of rising temperature on the performances of the coated layers. While ZnO NP'S showed protection efficiency around 65% for the two alloys and little effected by temperature rising on the performanes of the coated layers. The morphology of the coated spesiemses was examined by Atomic force microscope.
: Cigarette smoking is a lifestyle behavior that causes significant adverse health effects. Cigarette smoke contains chemicals, many of which are lead to the production of reactive oxygen species (ROS), which can lead to apoptosis and autophagy. To estimate the association of Cigarette smoking with the autophagy and immunity, technology of real time polymerase chain reaction (RTPCR) for gene expression of (LC3A, LC3B, LC3C, myd88) was used. Enzyme-linked immunosorbent assay (ELISA) technique was utilized to measurement the amount of TNF-α protein. The ratios of LC3A/LC3B and LC3B/LC3C were calculated to estimate the autophagy flux. The results indicate the expression of LC3B, LC3C and Myd88 genes in smokers is increased significantly (p
... Show MoreTwenty five vaginal swabs from outpatients' healthy women were collected from Kamal Al-Samarai Hospital, Baghdad, to isolate and identify of Lactobacillus acidophilus. Three isolates were diagnosed as L. acidophilus which represents 15% of the total number of lactic acid bacterial (LAB) isolates; other LAB types represent 65% (20 isolates).The ability of L. acidophilus to produce surlactin was detected after measuring its biological activity to inhibit the adhesion of biofilm formed by Pseudomonas aeruginosa to surfaces using test tube method. It was found that all isolates were able to produce surlactin but the activity of surlactin was varying in each isolate. Surlactin produced by isolates 1 and 13 was the most effective. Biological appl
... Show MoreObjective Neutrophils own an arsenal of dischargeable chemicals that enable them to handle bacterial challenges, manipulating innate immune response and actual participation in acquired immunity. The reactive oxygen species (ROS) are one of the most important chemicals that neutrophils discharge to eradicate pathogens. Despite their beneficial role, the ROS were strongly correlated to periodontal tissue destruction. Lowdensity neutrophils (LDN) have been recognized for producing enhanced quantities of ROS. However, the potential role of ROS produced by LDN in periodontitis is unknown. The aim of the study was to investigate the impact of ROS produced by LDN in periodontal diseases.
In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
... Show MoreBackground: The bone mineral density of the lumbar vertebra has been assessed according to the results of the Dual-Energy X-Ray Absorptiometry (DEXA). Although anemia is known to affect bone mineral density, at the present time, it is not clear which vertebra is more affected by this disease. Objective: To evaluate the effects of anemia on the bone mineral density of the lumbar vertebra in comparison with a normal subject and determine which part of the lumbar vertebra is more affected by anemia. Methods: All 205 participants in this study complained of bone pain (90 males and 105 females). 95 patients, including both sexes, suffered from anemia. Additionally, the study included 110 seemingly healthy volunteers as the control group
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