The present study was conducted to estimate the antimicrobial activity and the potential biological control of the killer toxin produced byD. hanseniiDSMZ70238 against several pathogenic microorganisms. In this study, the effects of NaCl, pH, and temperature, killer toxin production, and antimicrobial activity were studied. The results showed that the optimum inhibitory effect of killer toxin was at 8% NaCl, and the diameters of clear zones were 20, 22, 22, 21, 14, and 13 mm forStaphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Streptococcus pyogenes, Candida albicans,andCandida neoformans, respectively. The largest inhibition zones were

The adsorption of Malonic acid, Succinic acid, Adipic acid, and Azelaic acid from their aqueous solutions on zinc oxide surface were investigated. The adsorption efficiency was investigated using various factors such as adsorbent amount, contact time, initial concentration, and temperature. Optimum conditions for acids removal from its aqueous solutions were found to be adsorbent dose (0.2 g), equilibrium contact time (40 minutes), initial acids concentration (0.005 M). Variation of temperature as a function of adsorption efficiency showed that increasing the temperature would result in decreasing the adsorption ability. Kinetic modeling by applying the pseudo-second order model can provide a better fit of the data with a greater correla

Seeds, beans, leaves, fruit peel and seeds of five plants (Ferula assa-foetida, Coffea robusta, Olea europaea, Punica granatum and Vitis vinifera, respectively) were extracted with four solvents (distilled water, 80% methanol, 80% acetone and a mixed solvent that included methanol, ethanol, acetone and n-butanol at proportions 7:1:1:1). Such manipulation yielded 20 extracts, which were phytochemically analyzed for total polyphenols (TP) and flavonoids (TF). The DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity (RSA) and DPP-4 (dipeptidyl peptidase-4) relative inhibition activity (RIA) were also assessed for each extract. The results revealed that mixed solvent extract of V.

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

In this study, the effect of glass fiber reinforced polymer (GFRP) section and compressive strength of concrete in composite beams under static and low velocity impact loads was examined. Modeling was performed and the obtained results were compared with the test results and their compatibility was evaluated.‎ Experimental tests of four composite beams were carried out, where two of them are control specimen with 20 MPa compressive strength of concrete deck slab and 50 MPa for other. Bending characteristics were affected by the strength of concrete under impact loading case, as it increased maximum impact force and damping time at a ratio of 59% and reduced the damping ratio by 47% compared to the reference hybrid beam. Under stat