he effect of different cultural conditions on production of bioemulsifier from Serratia marcescens S10 was determined; different carbon and nitrogen sources were used such as: different oils include: edible (vegetable) oils (olive oil, sesame oil, sun flower oil and corn oil) and heavy oils (oil 150, oil 60, oil 40) as carbon sources and (NH4Cl, casein, (NH4)2SO4, peptone, tryptone, gelatin and yeast extract) as nitrogen sources were added to production media. Bioemulsifier was estimated by measuring the surface tension (S.T), emulsification activity (E.A) and emulsification index (E24%). The best results of bioemulsifier production from Serratia marcescens S10 were obtained at pH8 and incubated at 37ºC for 5days, using sesame oil

The current study was conducted on 504(Ros-308) broiler chicks during the period 28/9/2017-9/11/2018to determine the effect of heat shock in early age and additives such as ginseng in three levels on birds weight and feedconsumption. Results showed that the exposure to high temperature (38-400C) lead to significant decrease (p≤≤≤≤≤0.05 (inaverage body weight at7 day of age and significant decrease in body weight in birds expousured to high temperature inthe periods 2, 4 and 6 hours compared with control (Table 1). Significant decrease in live body weight when exposure to2hr compared with 6hr namely (138.54) and (144.21), respectively while no significant difference between 2 and 4h.Results showed no significant effect in body we

Production and characterization of methionine γ- lyase from Pseudomonas putida and its effect on cancer cell lines

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

The present research aims to design an electronic system based on cloud computing to develop electronic tasks for students of the University of Mosul. Achieving this goal required designing an electronic system that includes all theoretical information, applied procedures, instructions, orders for computer programs, and identifying its effectiveness in developing Electronic tasks for students of the University of Mosul. Accordingly, the researchers formulated three hypotheses related to the cognitive and performance aspects of the electronic tasks. To verify the research hypotheses, a sample of (91) students is intentionally chosen from the research community, represented by the students of the college of education for humanities and col

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas