This study depicts the removal of Manganese ions (Mn²⁺) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm², time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis

Background: Periodontal diseases are inflammatory disorders caused by the accumulation of oral biofilm and the host response to this accumulation which characterized by exaggerated leukocytes and neutrophils attraction to the sites of inflammation by chemoattractants which are a very important part of the pathogenesis of periodontal diseases. This study aimed to determine and compare the clinical periodontal parameters and the leukocyte cell types in the peripheral blood between patients with gingivitis and periodontitis with different severities compared to healthy controls. Materials and methods: This study included 150 male subjects aged between 35-50 years. They were divided into three groups: gingivitis group (n=30), periodontitis p

This study was performd on 50 urine specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of maltase in patients (6.40±2.17) I.U/ml and activity rate of maltase in normal (0.44±0.20)I.U/ml. The results of the study reveal that maltase activity of type 2 diabetes patient's urine shows significant increase (P<0.01) compare to normal.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.

Aim of the study:  Role of p110-beta as well as and CDK 1  in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.

Type of the study: is a retrospective study

Methods: This retr

The removal of fluoride ions from aqueous solution onto algal biomass as biosorbent in batch and continuous fluidized bed systems was studied. Batch system was used to study the effects of process parameters such as, pH (2-3.5), influent fluoride ions concentration (10- 50 mg/l), algal biomass dose (0–1.5 g/ 200 ml solution), to determine the best operating conditions. These conditions were pH=2.5, influent fluoride ions concentration= 10 mg/l, and algal biomass dose=3.5 mg/l. While, in continuous fluidized bed system, different operating conditions were used; flow rate (0.667- 0.800 l/min), bed depth (8-15 cm) corresponded to bed weight of (80- 150 g). The results show that the breakthrough time increases with the inc

Background Chromobacterium violaceum is a rare but potentially pathogenic bacterium that can infect humans and animals. Limited information is available about its occurrence in poultry. This study aimed to isolate and identify C. violaceum from diarrheic chickens and to evaluate its immunological impact in a mouse model. Methods Fifty chicken diarrhea fecal samples were cultured and typed by biochemical tests, Vitek 2 Compact System, and 16S rRNA gene PCR sequencing. Killed bacterial antigens were prepared and administered to mice to measure immune responses (IgG and IL-6 levels by ELI