Eimeriosis is a major problem affecting ruminants worldwide. The disease is primarily caused by Eimeria species, which are specialized for each host and grow in the small and large intestine of animals. The losses due to subclinical infections (especially weight loss) and clinical disease (diarrhea) make the species of this genus a very significant economic concern. Therefore, this study was conducted in some areas of Wasit Province. A total of 180 fecal samples from goats, of both sexes and covering different age groups and months, were collected. All fecal samples were examined microscopically, and 75 positive fecal samples were taken for molecular examination and further analyzed using conventional PCR, sequencing and phylogeneti

The present study was conducted in the Tigris River within Baghdad (University of Baghdad campus). The study included some physicochemical parameters and qualitative of epiphytic algae on the host plant (Ceratophyllum demersum) during summer season 2013. The results revealed that the study area was alkaline, hard and oxygenated water. A total of 105 taxa of epiphytic algae was identified. Bacillariophyceae diatoms composed 44.7% of the total and were represented by 42.4% of the order Pennales and 1.9 %of the order Centrales. Chlorophyceae composed 32.3%, followed by Cyanophyceae composed 22.8 % of the total. The total number of epiphytic algae was fluctuated among the study period. Most of the identified algae were benthos type and a few

The pharmacist's role in the community is currently directed towards providing drug information and patient care rather than drug compounding and dispensing. Patient counseling is an essential skill for pharmacists. So as to improve the pharmacist role in the community and enhance the patient's education and counseling skills, many continuing education programs are established. The aim of this study is to assess the perceptions and tendency of community pharmacists in Iraq regarding patients counseling and continuing pharmacists’ educational programs.

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i