Biofilm formation is one of the biggest challenges of scientists. Role of heavy metals in forming biofilm is not clear enough. Here, the effect of lead on biofilm formation by Bacillus spp. isolated from soil in terms of biofilm formation and remove was studied. In present study, 10 isolates of Bacillus spp were isolated from soil. The ability of all isolates to form biofilm was evaluated. The effect of lead on biofilm formation was studied by adding lead (pb) before forming biofilm. In another experiment the lead was added after biofilm formation to study the effect of lead on biofilm remove. The current study, showed the ability of all studied isolates to form biofilm. Maximum biofilm formation by Bacillus spp isolate number 8 (B8) follow

The electrochemical behavior of Al-17%Si alloy is investigated in 3.5wt% NaCl solution. Many alloys with addition of the different wt% magnesium metal of  1wt%, 2%, 3wt% ,4.5wt% ,and 9wt% were prepared by gravity die casting . The microstructures of prepared alloys were examined by optical and SEM microscopes. Corrosion behavior was investigated by using potentiostat instrument under static potentials test and corrosion current was recorded to determine corrosion resistance of all prepared samples. It was found that the addition of Mg metal improves the corrosion resistance of Al-17%Si alloy in 3.5%NaCl solution. The alloy containing 1%Mg shows less corrosion rate than the others while the alloys containing 4.5%Mg, 9%Mg content have

In this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.

A mercury porosimeter has been used to measure the intrusion volume of the three types mercury positive lead acid-battery plates. The intrusion volumes were used to calculate the pore diameter, pore volume, pore area, and pore size distribution. The variation of the pore area in positive lead acid-battery plates as well as of the pore volume has the following sequence. Paste positive > Uncured positive > Cured positive

A mercury porosimeter has been used to measure the intrusion volume of the three types mercury positive lead acid-battery plates. The intrusion volumes were used to calculate the pore diameter, pore volume, pore area, and pore size distribution. The variation of the pore area in positive lead acid-battery plates as well as of the pore volume has the following sequence. Paste positive > Uncured positive > Cured positive

This study aimed at isolating uropathogenic Escherichia coli from urinary tract infections (UTIs) of human and cattle to examine the molecular diversity and phylogenetic relationship of the isolates. A total of 100 urine samples were collected from UTIs of human and cattle. The isolates identification was done using routine diagnostic methods and confirmed by Vitek2. Antimicrobial susceptibility was tested against 10 antimicrobials. Random amplified polymorphic DNA (RAPD)-polymerase chain reaction (PCR) was applied to identify the genetic diversity among E. coli isolates from human and animal origin by using five different octamer primers. The gelJ software for the phylogenetic analysis created Dendrograms. Out of 50 human urine samples, E.

This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Reg

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in