Pseudomonas aeruginosa is an opportunistic pathogen responsible for serious infections. At least three different exopolysaccharides, alginate, polysaccharide synthesis locus (Psl), and pellicle exopolysaccharide (Pel) make up the biofilm matrix in P. aeruginosa . The effect of temperature on the biofilm formation and gene expression was examined by microtiter plate and real-time quantitative polymerase chain reaction (qRT-PCR). To be able to determine the effect of temperature on biofilm formation and gene expression of P. aeruginosa, 303 clinical and environmental samples were collected. Pseudomonas aeruginosa was isolated from 61 (20.1%) and 48 (15.8%) of the clinical and environmental samples, respectively. The ability of clinical and environmental P. aeruginosa isolates to develop biofilm was observed in 86.9% and 85.42% of the isolates, respectively, distributed into strong, moderate, and weak biofilm producers. Moreover, gene expression for pslA, pelA and algD genes was estimated for clinical and environmental isolates, the clinical P. aeruginosa isolates showed the highest biofilm production and the highest gene expression of pslA, pelA and algD genes as compared to environmental isolates when temperature changed. In summary, both clinical and environmental isolates formed biofilm and carried psl A, pel A and alg D genes regardless of the intensity of the biofilm. Also, 37°C represented the best temperature for biofilm production.
This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p
... Show MoreThe objective of this research work is to evaluate the quality of central concrete plant of Al-Rasheed Company by using Six Sigma approach which is a measure of quality that strives for near elimination of defects using the statistical methods to improve outputs that are critical to customers. The fundamental objective of Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction to reach delighting customers, and then suggesting an improvement system to improve the production of concrete in Al-Rasheed State Contracting Construction Company.
A field survey includes two parts (open and close questionnaire) that aimed to get the data and information required f
This paper describes DC motor speed control based on optimal Linear Quadratic Regulator (LQR) technique. Controller's objective is to maintain the speed of rotation of the motor shaft with a particular step response.The controller is modeled in MATLAB environment, the simulation results show that the proposed controller gives better performance and less settling time when compared with the traditional PID controller.
A many risk challenge in (settings hospital) are multi- bacteria are antibiotic-resistant. Some type strains that ability adhesion surface-attached bio-film census. Fifteen MRSA isolates were considered as high biofilm producers Moreover all MRSA isolates; M3, M5, M7 and M11 produced biofilms but the thickest biofilm seen M7strain. The MIC values of N. sativa oil against clinical isolates of MRSA were between (0.25, 0.5, 0.75, 1.0) μg/ml While MRSAcin (50, 75, 100, 125) µg\ ml. All biofilms treated with MRSAcin and Nigella sativa developed a presence of live cells after cultured on plate agar with inhibition zone between MIC (18 – 15) and (14- 11)mm respectively.Yet, results showed that MRSA supernatant developed a inhibitory ef
... Show MoreThe ongoing COVID‐19 pandemic caused by SARS‐CoV‐2 is associated with high morbidity and mortality. This zoonotic virus has emerged in Wuhan of China in December 2019 from bats and pangolins probably and continuing the human‐to‐human transmission globally since last two years. As there is no efficient approved treatment, a number of vaccines were developed at an unprecedented speed to counter the pandemic. Moreover, vaccine hesitancy is observed that may be another possible reason for this never ending pandemic. In the meantime, several variants and mutations were identified and causing multiple waves globally. Now the safety and efficacy of these vaccines are debatable and recommended to d
Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
... Show MoreThe successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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