The soil acari fauna (Cryptostigmat) in soil of Baghdad in Jadiriya area was studied in a total of 16 monthly samples through a period of 12 months (December 2009-November 2010). A new record of one genus for Iraq named (Malloconthrius sp.), and one species named Eupelops plicatus out of seven mite group Cryptostigmata which isolated from the soil. Two species were recorded during the present study as dominants named (Ceratozetes gracilis, Perlohmania dissimilis). The Cryptostigmatid mites are the most common soil inhabiting and saprophagous animals the ordinal composition of the soil acari fauna was predominantly Cryptostigmata sp disturbance of these factors generates modifications of numerical densities and the presences of mites in a

The aim of this paper is to estimate the concentrations of some heavy metals in Mohammed AL-Qassim Highway in Baghdad city for different distances by using the polynomial interpolation method for functions passing from the data, which is proposed by using the MATLAB software. The sample soil in this paper was taken from the surface layer (0-25 cm depth) at the two sides of the road with four distances (1.5, 10, 25 and 60 m) in each  side of the road. Using this method, we can find the concentrations of heavy metals in the soil at any depth and time without using the laboratory, so this method reduces the time, effort and costs of conducting laboratory analyzes.

The aim of this paper is to estimate the concentrations of some heavy metals in Mohammed AL-Qassim Highway in Baghdad city for different distances by using the polynomial interpolation method for functions passing from the data, which is proposed by using the MATLAB software. The sample soil in this paper was taken from the surface layer (0-25 cm depth) at the two sides of the road with four distances (1.5, 10, 25 and 60 m) in each  side of the road. Using this method, we can find the concentrations of heavy metals in the soil at any depth and time without using the laboratory, so this method reduces the time, effort and costs of conducting laboratory analyzes.

The present study aimed to evaluate the concentration of Malon dialdehyde (MDA) in pregnant women during different stages of pregnancy (stage of pregnancy, abortion, contraceptives and parity number).The study included (120) blood samples from normal pregnant women in age of the procreating were subdivided into three trimesters of pregnancy (40/group), and (40) samples from non-pregnant women as a control group. The results showed a significant increase in MDA in three stages of pregnancy compared with the control group. The concentration of MDA increased significantly in pregnant women with multipregnancy when compared with pregnant women for the first time, and in pregnant women whom was using contraceptions compared with p

  The research aims to measure  the efficiency of health services Quality  in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency  for two types of orientation direction, which are input and output oriented direction.

  The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).

60 cases of Bacteremia were documented at Ibn Al-Baladi hospital during 6 months (1-1-2002 to 1-7-2002), with an incidence of 5.2 were gram-negative organisms and most common one was Salmonella and Klebsiella. Incidence was significantly higher in male than female .Antimicrobial sensitivity tests revealed that isolated bacteria are with multiple drug resistance to commonly used antimicrobial agents. Salmonella showed high resistance to cephaloxin, co-trimoxazole and amoxicillin and also Klebsiella showed resistance to cephaloxin and amoxicillin.

This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th

This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there
is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated

Background: Childhood meningitis is a major
cause of morbidity and mortality, Hemophilus
influenza b (Hib) is the most common cause in
many countries, especially below 5 years and
before the development of conjugated Hib vaccine,
it is followed by Streptococcus Pneumonia, and
then N. meningitides, in addition to other
microorganisms.
Objective: To identify the causative organisms
of bacterial meningitis and to identify the factors
predisposing significantly to the incidence of
bacterial meningitis.
Method: This cross sectional , study was done in
Al-Elwia Pediatric Hospital during the period 1st
of January 2007 to 30th of June 2007.Eighty four
patients with presumptive diagnosis of meningitis<

     This paper presents an efficient system using a deep learning algorithm that recognizes daily activities and investigates the worst falling cases to save elders during daily life. This system is a physical activity recognition system based on the Internet of Medical Things (IoMT) and uses convolutional neural networks (CNNets) that learn features and classifiers automatically. The test data include the elderly who live alone. The performance of CNNets is compared against that of state-of-the-art methods, such as activity windowing, fixed sample windowing, time-weighted windowing, mutual information windowing, dynamic windowing, fixed time windowing, sequence prediction algorithm, and conditional random fields. Th