Hydatidosis is a zoonotic, helminthes parasitic disease that cause veterinary and human problems due to economic burden. Amis of the current study was to estimate the prevalence rate of hydatidosis infecting different organs of sheep slaughtered in street. In addition, investigate the relationship between age, gender and the infected rates in some Baghdad areas during a period from may to end of July 2018.A total of 188 sheep was examined for detection of Hydatid cyst in different organs using macroscopic and microscopic examination The overall prevalence rate of 47.9% was recorded. The results indicate non significant differences according to age and gender, the highest rate 57% was observed in sheep more than one year old compare

Background: Infection with sexually
transmitted diseases is broad and includes
bacterial, viral and protozoa infection.
Large number of infected people goes
untreated because of symptomatic or
unrecognized infections.
Patients and methods: Forty five
patients was complaining from infertility
(primary or secondary), consulting
Kammal El-Sammari Hospital for
infertility from May - 2008 to February -
2009. Control group consisted of twenty
fertile women that consulting private clinic
for checking. Four swabs were taken from
each woman in two groups. Two swabs
were taken from posterior fornix of the
vagina (High vaginal swab) and the last
two were taken from endocervical canal.
First swab

A total of 47 species belonging to 46 genera, 34 subfamilies, 23 families and 7 orders of predator and parasitoid insects were collected and identified. The survey was conducted throughout the program held by the General Directorate of Agriculture-Duhok, in cooperating with the College of Agricultural Engineering Sciences in Duhok Province, Kurdistan Region, Iraq from May 2013 to April 2014.
The species hosts, collecting date, locality and distributions are given. The current checklist also included some species previously collected by other researchers in Duhok Province.

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect