The plant Zizyphus spina-christa grows wildly in the middle and southern of Iraq locally named Nabag. In this study the antibacterial activity of several different plant extract (alcoholic hot and cold extract 80%, aqueous hot and cold extract) was tested against some gram negative bacteria that related to Enterobacteriacea as follow; Pseudomonas aeruginosa, Escherchia coli Proteus mirabilis, Serratia mercesence,. Aeromonas sp, Klebsiella pneumoniae ,Shigella sp, Salmonella enteritidis (134), S. typhi(97), S. typhimurium (300) , S. typhi, . The results showed that efficient method of extract was alcoholic hot extract from other extract methods that are used in this study. The detection of active compound in crude extracts of the leaves show

The genetic toxicity of aqueous and alcoholic extracts of seeds of Peganum harmala L. was evaluated on the onion roots ,using  concentrations 10,25,50,100 and 200 % w/v of extracts and periods of exposure 24,48 and 74 hours. The results indicated that the Peganum harmala significantly decreased root growth rate of onion root at all concentrations and treatment periods in comparison to the control ,  the growth of the root decreased when increasing the extract concentration.The EC50value  of aqueous extracts was 50% and for alcohol extract was 25% ,thus the alcohol extract was most effective in the growth rate of the roots from the aqueous extract. The results also indicated that the mitotic index of Allium cepa was signifi

Objectives: To study the prevalence of rs1799964 (-1031 T/C) and rs361525 (- 238 G/A) SNPs and their effect on the disease activity, severity, and cytokines production in newly diagnosed Iraqi rheumatoid arthritis patients. Patients and Methods: sixty-three patients were diagnosed by a specialist physician while attending the rheumatology unit and twenty control participated. The inflammatory markers were measured and PCR amplification and sequencing were performed to demonstrate TNF-α SNPs. Results: Regarding (-1031 C/T) SNP, the TT genotype and allele C were significantly present in the controls, and the CT genotype was distributed significantly in the patients. The TT genotype was mostly distributed in the mild-moder

Exponential distribution is one of most common distributions in studies and scientific researches with wide application in the fields of reliability, engineering and in analyzing survival function therefore the researcher has carried on extended studies in the characteristics of this distribution.

In this research, estimation of survival function for truncated exponential distribution in the maximum likelihood  methods and Bayes first and second method, least square method and Jackknife dependent in the first place on the maximum likelihood method, then on Bayes first method then comparing then using simulation, thus to accomplish this task, different size samples have been adopted by the searcher us

This research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri

Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a