Isolation and identification fungi of Emericella nidulans and Aspergillus flavus from a pinkish and yellowish artificial clay, by using potato dextrose agar (PDA). Results revealed that E. nidulans was the best for degrading anthracene (92.3%) with maximum biomass production (3.7gm/l), compared to A. flavus with the rate of degradation (89%) and biomass production of (1.2gm/l), when methylene blue was used as redox indicator after incubating in a shaker incubator 120rpm at 30Co for 8days. Results indicated that E. nidulans has a high ability of anthracene degradation with the rate of (84%), while A. flavus showed the lower level with (77%) by using HPLC.

fication of benzaldehyde (C6H5CHO) and O- amino aniline O-C6H4(NH2)2 in ethanol with 8- Hydroxyquinoline (8HQ) . Formed compounds were acquired of 1:1:2 molar proportion reactions for metal ions and ligands (L) and 2(8HQ) during reaction for MCl2 .nH2O salt products complexes conformable into the forms [M(L)(8HQ)2] ,where M = Mn(II),Co(II) and Ni(II). Whole the compounds were identified during the basis of their; FT-IR and U.V spectrum, melting point, molar conduct, identify of the percentage from the metal at the complexes via flame (AAS), C, H and N content of the Schiff base (L) and metal complexes were analysis and magnetic susceptibility menstruations. A hexagonal coordinated metal complexes were proposed to the separated complexes of

rhabditid Mesorhabditis franseni Fuchs, 1933 (Family, Mesorhabditidae) and pratylenchid nematode Pratylenchus goodeyi Sher and Allen, 1953 (Family, Pratylenchidae). They were illustrated by molecular aspects. All specimens of both genera were cultured and reproduced for DNA extraction. M. franseni (IRQ.ZAh2 PP528819.1 isolate) was characterized. P. goodeyi (IRQ.ZAh5 PP535537 isolate) was also characterized. Selected specimens of these two species were molecularly characterized using the partial ITS-rRNA gene sequences. The ITS-rRNA sequence of IRQ.ZAh2 PP528819.1 isolate had a range of (98.62%-100%) sequence homology with ITS-rRNA sequence of M. franseni available in NCBI database. While, the ITS-rRNA sequence of IRQ.ZAh5 PP535537 isolate h

Background: Preoperative radiographical assessment of the maxillofacial lesions is of a great importance in guiding the surgeon during surgical procedure in reducing post-operative complications. This study highlighted the application of CBCT scan in the assessment of maxillofacial cystic and cystic like lesions as a part of advanced radiology Materials and methods: A total of 20 patients (15 males and 5 females) participated in this prospective study. CBCT scan (Kodak 9500 CBCT) with (DICOM) software utilized to perform scanning to all patients in order to assess lesion extension, morphological features and it’s relation to the adjacent vital structures. Results: In this study, the total cystic and cystic like lesions involving the

Background: The bone mineral density of the lumbar vertebra has been assessed according to the results of the Dual-Energy X-Ray Absorptiometry (DEXA). Although anemia is known to affect bone mineral density, at the present time, it is not clear which vertebra is more affected by this disease. Objective: To evaluate the effects of anemia on the bone mineral density of the lumbar vertebra in comparison with a normal subject and determine which part of the lumbar vertebra is more affected by anemia. Methods: All 205 participants in this study complained of bone pain (90 males and 105 females). 95 patients, including both sexes, suffered from anemia. Additionally, the study included 110 seemingly healthy volunteers as the control group

This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

We study in this paper the composition operator of induced by the function ?(z)=sz+t where , and We characterize the normal composition operator C? on Hardy space H2 and other related classes of operators. In addition to that we study the essential normality of C? and give some other partial results which are new to the best of our knowledge.

In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T