M. domestica is the most important insect that transmit pathogens for diseases in the world. The use of nanotechnology is eco-friendly method in control pests. The study aims to investigate the feasibility of bio-manufacturing nanocapsules of fungal secondary metabolites in order to improve the efficiency of metabolite and assess their inhibitory effect on the acetylcholine esterase enzyme in housefly larvae. An equal mixture of organic solvents, ethyl acetate and dichloromethane, was used to extract the metabolic products of the fungus M. anisopliae, (PEG4000) and chitosan was used in the preparation of nanocapsules. The results of the DLS granular size assay showed that the size of the extract particles and the size of the chitosan and (PEG 4000) nanocapsules were 610, 217 and 188 nm, respectively. The SEM images showed that the diameter of the extract and the nanocapsules chitosan and polyethylene glycol 4000 reached a rate 547.5, 17.8 and 26.2 nm, respectively. The FTIR showed that the extract of the second products of the fungus contains functional groups like: alkynes and alkenes, amines, carboxyl and aromatic groups, while the presence of groups of phenols, alcohol, amines, alkenes, and alkyl halides was recorded for nanocapsules of chitosan and PEG. The results showed that the extract of fungal metabolic and nanocapsules has an inhibitory effect on acetylcholinesterase enzyme and reached the highest inhibition rate 53.2 ,36.3,18.2% when treated with nanocapsules PEG at a concentration 500 ppm, extract of fungal metabolites at a concentration 50,000 ppm, chitosan nanocapsules at a concentration 500 ppm respectively. It is clear that acetylcholinesterase inhibition is one of the mechanisms of fungi metabolic action and the nanocapsules prepared from them.
In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
... Show MoreIn 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
... Show MoreIn this research, deposition of titanium oxide (TiO2) and vanadium oxide (V2O5) thin film in different mixing percentage (0, 25 ,50, 75 and100)% on the substrate of glass .The coating thickness was ( 50 nm ).
In this research contact angle was measured and the effect of weather conditions. Results showed that the value of the contact angle of the prepared films reached its highest value at 50% (TiO2+V2O5) was 160º.
The results showed that the optical transmittance of TiO2 and V2O5 thin film decrease with increasing the deposition angle and decrease with increasing V2O5 pro
... Show MoreThis paper presents experimental results regarding the behaviours of eight simply supported partially prestressed concrete beams with internally unbonded tendons, focusing particularly on the effect of three different variables: concrete compressive strength,
Polyacetal was synthesized from the reaction of PVA with para-methyoxy benzaldehyde. Polymer metal complexwas prepared by reaction with Cu, polymer blend with Chitosan was prepared through the technique of solution casting method.All prepared compounds have been characterized through FT-IR, DSC, SEM as well as the Biological activity. The FT-IR results indicated the formation of polyacetal. The DSC results indicated the thermal stability regarding prepared polymer, polymermetal complex and Chitosan polymer blends. Antibacterial potential related to synthesized polyacetal, its metal complex andChitosan blend against four types of bacteria namely, Staphylococcus aureas, Psedomonas aeruginosa, Bacillus subtilis, Escherichia coli was examined a
... Show MoreThis paper introduces an experimental study on the behavior of confined concrete filled aluminum tubular (CFT) column to improve strength design, ductility and durability of concrete composite structures under concentrically loaded in compression to failure. To achieve this: seven column specimens with same concrete diameter 100mm and without steel reinforcement have been examined through experimental testing, which are used to study the effects of the thickness of the aluminum tube encased concrete ( thickness : 0mm, 2mm, 3mm, 4mm and 5mm with same length of column 450mm), length of column (thickness 5mm and length of column 700mm) and durability (thickness 5mm and length of column 450mm) on the structural behavior of &
... Show MoreDynamic Thermal Management (DTM) emerged as a solution to address the reliability challenges with thermal hotspots and unbalanced temperatures. DTM efficiency is highly affected by the accuracy of the temperature information presented to the DTM manager. This work aims to investigate the effect of inaccuracy caused by the deep sub-micron (DSM) noise during the transmission of temperature information to the manager on DTM efficiency. A simulation framework has been developed and results show up to 38% DTM performance degradation and 18% unattended cycles in emergency temperature under DSM noise. The finding highlights the importance of further research in providing reliable on-chip data transmission in DTM application.
This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).