Antimicrobial activity of potato Rhizospheric Pseudomonas chlororaphis subsp. aureofaciens from Sétif Algeria

Aims: This study was assessed to demonstrate the antimicrobial activity in vitro of an identified fluorescent Pseudomonas strain characterized for its capacity to produce phenazine compounds. Methodology: First Pseudomonas chlororaphis subsp aureofaciens was inoculated on Nutrient Broth supplemented with Yeast Extract (NBY) and with glucose at a final concentration of 2%, after incubation the filtered culture was acidified with HCl to pH 2. The solution was extracted twice with the same volume of ethyl-acetate. The organic supernatants were combined, dried over anhydrous Na2SO4, and evaporated to dryness. The crude extract was resuspended in methanol and tested for antimicrobial activity. Antimicrobial activity was determined (i) by disc diffusion technique for bacteria and (ii) using serial dilution technique in soft PDA for fungi. Secondly the antifungal activity of the bacterial strain was tested against several phytopathogenic fungi in dual culture. Results: The studied strain has an important activity against the phytopathogenic bacteria and fungi tested. Among the tested fungi Fusarium oxysporum f. sp. albedinis is the most sensitive to the actions of this Pseudomonas, where the inhibition rate reached 77.78%. The less sensitive one was Pythium ultimum with a rate of 55.56%. While for pathogenic bacteria only Salmonella enteridis was sensitive to the tested strain. Conclusion: Pseudomonas chlororaphis subsp aureofaciens showed appreciable antagonistic activity, in vitro, against special forms of Fusarium oxysporum and the tested phytopathogenic bacteria

Bacteriocins contributing in Rhizospheric competition among Fluorescent Pseudomonads

Aims: To examine the production of bacteriocins through the study of a group of rhizospheric Pseudomonas isolates already known to produce metabolites that are antagonistic to fungi. Methodology: Fourteen rhizospheric strains of fluorescent Pseudomonads spp., were tested as well as two referenced strains Pseudomonas protogens CHA0 and Pseudomonas aureofaciens 30-84, for their ability to produce induced bacteriocins. The induction is carried out first by UV light, and secondly by mitomycin C. Results: In addition to the reference strains, six isolates were found to produce bactericidal substances after UV light induction against Pseudomonas target bacteria but also against other genera (Escherichia and Staphylococcus). Producing strains were treated with mitomycin C, and then lysed with chloroform. Analysis of the lysates by trypsin and freezing treatments, suggests that the active compounds are of high molecular weight. Conclusion: It is therefore suggested that these bacteria could be good competitors for their introduction as biocontrol agents

SIMULATION MODEL MANAGEMENT: RESOLVING THE TECHNOLOGICAL GAPS

Model management poses requirements and responsibilities that extend throughout the life cycle of a simulation model. Recent publications have identified major problems in cost and time overruns, which are traceable to deficiencies in project and sponsor management. Beginning with the division of the simulation model life cycle into seven phases, we define "model management" and develop the requirements for a Model Management System (MMS). The functional description of a MMS focuses on those phases that jointly characterize the model development effort. Recent research in simulation model development is described, and particular emphasis is given to the approach taken with the Conical Methodology

Cranberry juice vs. placebo as prophylaxis for recurrent urinary tract infection in adult women: A systematic review

Objective: To determine the effectiveness of cranberry juice consumption as prophylaxis for urinary tract infection (UTI) in women with a history of recurrent UTI. Methods: Systematic literature review using Google Scholar with search terms “cranberry juice prophylaxis.” Results: Our search resulted in three randomized-control trials (RCTs), two of which demonstrated no benefit of cranberry juice in preventing recurrent UTI. Conclusion: Because of the significant heterogeneity among published studies, there is no definitive proof that cranberry juice is effective or useless as UTI prophylaxis

Performance Enhancement of Dual-Star Induction Machines Using Neuro-Fuzzy Control and Multi-Level Inverters: A Comparative Study with PI Controllers

This paper proposes a hybrid speed control strategy for Dual-Star Induction Machines (DSIMs) supplied by Multi-Level Inverters (MLIs). The proposed approach integrates a Neuro-Fuzzy Controller (NFC) with an Indirect Field-Oriented Control (IFOC) technique, leveraging the adaptive learning capabilities of an Artificial Neural Network (ANN) to optimize the NFC parameters. This strategy achieves significant enhancements in speed regulation performance, including a 20% reduction in settling time, a 15% decrease in overshoot, and minimized steady-state error. The NFC's online adaptive learning capability enables real-time adjustments, outperforming the PI controller in handling rotor resistance variations and load disturbances. Simulation results demonstrate a 35% reduction in torque ripple and a 20% improvement in speed regulation compared to PI controllers. The NFC also exhibits faster response times during torque change and remains unaffected by 50% rotor resistance variations. Additionally, the NFC controller achieves up to 51% reduction in Total Harmonic Distortion (THD) compared to the PI controller.  Increasing the inverter voltage level from m=2 to m=7 significantly reduces electromagnetic torque ripple, demonstrating a direct correlation between higher inverter levels and improved torque ripple performance. These improvements position the NFC-based strategy as a promising solution for industrial applications requiring precise speed control, such as robotics, electric vehicles, and automation systems

Optimization of Welding Input Parameters Using PSO Technique for Minimizing HAZ Width in GMAW

In order to conceive command systems for welding equipment based on intelligence techniques similar to human thinking; it is better to use artificial intelligence methods, for example: Genetic algorithms and particle swarm optimization. Freshly, this latter has received increased attention in many research fields. This paper discuss the application of particle swarm optimization algorithm to optimize the welding process parameters and obtain a better Width of Head Affected Zone (WHAZ) in the welding machine which is gas metal arc welding. The effect of four main welding variables in the gas metal arc welding process, namely welding speed, welding voltage, nozzle-to-plate distance and wire feed speed on the WHAZ are studied. A source code is developed in MATLAB 8.3 to perform the optimization

Antagonisme de souches de Pseudomonas vis à vis de la microflore pathogène de la pomme de terre

Antagonisme de souches de Pseudomonas vis à vis de la microflore pathogène de la pomme de terre

Study of the performance of fault-tolerant multi-level inverter included in shunt active power filter

Nowadays, the large number of shunt active power filters (SAPF) is installed in many grid networks to eliminate the source currents harmonics and enhance power quality. These filters are installed in different places according to the filtration requirements. The connection between SAPF and grid network has a negative effect during the open-circuit fault of the insulated gate bipolar transistor (IGBT) switch of the SAPF. This paper proposes the application of the new diagnostic method based on the trigonometric circle and mean value variations techniques to the early detection and precise location of the open-circuit fault of the IGBT switches, and the inclusion of the modified reconfigurable inverter topology to allow the perfect continuity of the filter currents, and improve the diagnostic of the open-circuit fault. A single-sided amplitude spectrum technique (SSAS) is applied on the source currents to get the THDi% value. The obtained simulation results prove, the great success of the proposed diagnostic method, the ability of the modified reconfigurable inverter to be adapted to the grid network, the short response time between the diagnosis and the reconfiguration process is about 7 ms which is very sufficient to guarantee the rapid continuity of the shunt active power filter

Kernel Principal Components Analysis with Extreme Learning Machines for Wind Speed Prediction

International audienceNowadays, wind power and precise forecasting are of great importance for the development of modern electricalgrids. In this paper we propose a prediction system for time series based on Kernel Principal Component Analysis (KPCA) and Extreme Learning Machine (ELM). To compare the proposed approach, three dimensionality reduction techniques were used: full space (50 variables), part of space (last four variables) and classical Principal Components Analysis (PCA). These models were compared using three evaluation criteria: mean absolute error (MAE), root mean square error (RMSE), and normalized mean square error (NMSE). The results show that the reduction of the original input space affects positively the prediction output of the wind speed. Thus, It can be concluded that the non linear model (KPCA) model outperform the otherreduction techniques in terms of prediction performance