This study was aimed to assess the efficiency of N.oleander to remove heavy metals such as Copper (Cu) from wastewater. A toxicity test was conducted outdoor for 65-day to estimate the ability of N.oleander to tolerate Cu in synthetic wastewater. Based on a previous range-finding test, five concentrations were used in this test (0, 50, 100, 300, 510 mg/l). The results showed that maximum values of removal efficiency was found 99.9% on day-49 for the treatment 50 mg/l. Minimum removal efficiency was 94% day-65 for the treatment of 510 mg/l. Water concentration was within the permissible limits of river conservation and were 0.164 at day-35 for the 50 mg/l treatment, decreased thereafter until the end of the observation, and 0.12 at day-65 for the treatment 100 mg/l. the concentrations of water samples exceeded the permissible limits for 300 and 510 mg/l throughout the observation. Bioaccumulation factor (BAF) for N.oleaner was found to be greater than one for all the treatments. Higher translocation factor (TF) were 1.65, 1.73, 2.61 and 2.34 mg/l for 50, 100, 300 and 510 mg/l, respectively. This study revealed that N.oleander can tolerate and treat Cu concentration in wastewater.
This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.
Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed
... Show MoreThis paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
... Show MoreThe present research aims at recognizing the difficulties and problems which hamper teachers and educators alike when using the internet for educational purposes.It discusses the benefits of the internet as a source of information or publication and as a communicative tool.Arandom sample of (30) teachers working at schools in Baghdad / Second Risafa,was selected.Three of the sample members use the internet for student project plans via internet centers, whereas 16 of them use it for chatting, emailing and research purposes.The rest of the sample have limited knowledge of the internet. The researcher used the interviewing method to gather data from
... Show MoreCutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production. This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and
... Show MoreA mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 25
... Show MoreThis study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed that these isolates are biological surfactant producers. The bet
... Show MoreCatalytic microwave-assisted pyrolysis of biomass is gaining popularity as an alternative to fossil fuels due to health, environmental, climate, and economic issues. This study conducted a catalytic pyrolysis process of the Albizia plant's branches using an Iraqi clay catalyst (bentonite) focusing on the variables including the biomass-particle size, experimental time, microwave power level, and the catalyst-to-biomass ratio. The physical and chemical properties of the resulting biofuel were analyzed presented by HHV, acidity, density, viscosity, GC-MS, FTIR for bio-oil and SEM, EDX, BET, HHV, FTIR for biochar. The study revealed that addition of bentonite as a catalyst led to enhanced production of biogas produced from 5% to 45% an
... Show MoreThis paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).