Forty soil samples were collected from different regions in Baghdad city. Among 52 isolate, only 38 isolates (73.1 %) belong to Bacillus spp. All bacterial isolates have been submitted to the cultural, microscopical, biochemical examination and VITEK 2 System, Bacillus cereus was predominantly found 21 (55.3%) followed by Bacillus subtilis 11 (28.9%), then Bacillus amyloliquefaciens was 6 (15.8%). Bacillus cereus (B1) and Bacillus subtilis (B16) isolates were with the highest level with the antibacterial activity when selected. Extracellular proteins were extracted and purified with ammonium sulfate (80%) saturation, then submitted to Sepharose-6B gel filtration column. SDS-polyacrylamide gel electrophoresis was used to determine the molecular weights of proteins, and one band appeared to each of Bacillus cereus and Bacillus subtilis with molecular weight 68 and 50 KDa respectively. The results revealed that higher effect of antibacterial activity on Gram positive bacteria, and moderate on Gram negative bacteria except P.aeruginosa with no effect. The antibiofilm effect of the extract found higher effective against S.pyogens, moderate effect against each of (S.aureus, E.coli, S. marcescens, K. spp) and no effect against P.aeruginosa. The results of cytotoxicity showed that the purified extract was a higher cytotoxic effect on breast cancer MCF7 cells at 1000µg/ml concentration, while the crude extract had a higher cytotoxic effect on breast cancer MCF7 cells at 100µg/ml concentration.
Magic squares is n×n matrix with positive integer entries as well as the sum of rows, columns and mains diagonal have the same magic constant, one of the most oldest magic square was discovered in china. In this paper the history of magic square is displayed and some definition of its kind is given the prove of two theorems about properties of magic square is introduced.
The single index support vector regression model (SI-SVR) is a useful regression technique used to alleviate the problem of high-dimensionality. In this paper, we propose a robust variable selection technique for the SI-SVR model by using vital method to identify and minimize the effects of outliers in the data set. The effectiveness of the proposed robust variable selection of the SI-SVR model is explored by using various simulation examples. Furthermore, the suggested method is tested by analyzing a real data set which highlights the utility of the proposed methodology.
Published 05/05/2019 Stachys babylonica (Lamiaceae). A new species from the mountainous, Kurdistan Iraq, is described and illustrated. Its distinguishing characters are discussed. It is distinguished from the closely related species S. kotschyi by having elliptic-rhombic (vs. ovate or ovalelliptic) leaves, (30-35 x 10-16 mm) (vs. 25-47 x 14-21mm), lower leaves petioles longer ± 16mm (vs. C.7mm), the median leaves petiole ± 7mm (vs. subsessile – sessile), calyx is narrowly tubular appressed (vs. infundibular – campanulate ± spreading), bracteoles are well developed as long as or longer than calyx (vs. shorter than calyx or absent), teeth of calyx are narrowly lanceolate (vs. broadly lanceolate and spreading). This new species to science is represented only by two specimens: the holotype & the isotype #12125.Specimen #12125 has been mistakenly identified as S. tomentosa Rech. f. by Rechinger[1]. Rechinger used only morphological characters in his identification. To clear the ambiguity, Pollen grain study was done and the results of this study were tabulated in Hamodie's work[2]. Specimen #50059 mentioned by Al-Zubaedy[3] as collected by Ali Haloob in 2010 from Piera Magron Mt belongs to S. kotschyi was also mistakenly identified as S. babylonica. The consideration of specimens belongs to S. kotschyi Boiss. as S. babylonica Hamodie & Wilcock made errors on conclusions by Al-Zubaedy[3] on molecular & P.G and morphological studies and reconsideration on these issues are needed. All the indicators so far gathered, approve that plants of this new species were most likely vanished from Piera Magron Mt. in Sulaimaniya sometime after 1948.
Accepted 17 Oct. 2017 In this research work a data stream clustering method done by extracting regions of interest from the frames of video clips (UCSD pedestrian dataset (ped1 and ped2 datasets) video clips, and VIRAT VIDEO dataset video clips). In extraction process, the HARRIS or FAST detector applied on the frames of video clips to extract list of pairs of interest points. From these pairs a list of features such as: distance, direction, x-coordinate, y-coordinate obtained to use as an input to the clustering method based on seed based region-growing technique. From these clusters, a regions of interest extracted according the pairs coordinates of each cluster. Finally, from these regions a set of geometrical complex moments obtained and then used in anomaly detection system. The results indicated that using HARRIS detector achieved detection rates are 7.88%, 51.30%, and 56.67% with false alarms are 19.39%, 32.61%, and 60 % by using Ped1, Ped2, and VIRAT datasets respectively. For the case of using FAST detector, the best detection rates are 6.67%, 44.78%, 53.33% with false alarm rates are 33.33%, 41.74%, 70% by using the datasets respectively.
