In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

Microbial lipases today occupy a place of prominence among biocatalysts owing to their ability to catalyze awide variety of reactions in aqueous and non- aqueous media, A.baumannii were isolated from different clinical specimens from hospitalized patients from Baghdad hospitals and were detected by biochemical tests and API20E system. The percentage of isolation was (16.6%), A. baumannii is an increasingly multidrug – resistant (MDR), it showed high level of resistant to Ceftriaxon, Colistin, Piperacillin, Co-trimoxazol, Tertracycline, Carbenicillin, Amoxicillin, Penicillin G, Gentamicin and Ceftazidim , wherease the isolates were highly sensitive to Imipenem, Ciprofloxacin, Meropenem, Amikacin, and Cefotaxime.

An electrolytic process for the removal of Zn(II) from aqueous solution using a parallel amalgamated copper screens cathode operated in the flow through mode is proposed. The current-potential curves recorded at a rotating amalgamated copper disc electrode were used to determine diffusion coefficient of Zn(II). The performance of electrolytic reactor was investigated by using different flow rates at initial zinc ion concentration(48 mg/L). Taking into account the residential Zn(II) concentration, the best results were obtained for cathode potential of (-1.35 V vs. SCE) at flow rate (320 L/h). Zinc ion concentration was found to decrease from 48 mg/L to 1 mg/L during 120 min. of electrolysis. The experimental data are well correlate

In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficiency of cadmium b

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

     The ferric oxide nanoparticles (Fe₂O₃) which are deposited at interface which is related to hole collecting buffer layer [poly(3,4-ethyl-enedioxythiophene): poly(styrene-sulfonate) (PEDOT: PSS)] as well as regioregular poly(3-hexyl-thiophene): Zinc oxide nanoparticles (P3HT): (ZnO) active layer have been considerable increasing the performance of solar cell. Also, the solar cell devices have been fabricated with a weight ratio of 1:0.7, 1:0.8, 1:0.9 and 1:1 of P3HT and ZnO, respectively. In addition, photo physical characteristics regarding such devices with different value of the weight ratio were examined. This work is indicating that the absorption spectrum related to blend will be broad

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN