The pathogenicity of S. saprophyticus was studied in mice. A group of white mice were injected transurethrally using a catheter with S. saprophyticus S67 cell suspension in a concentration reached 109 CFU/ml. concomitantly, the role of its peptidoglycan in the pathogenicity was studied by injecting another group of mice with 0.3 mg/0.2 ml of partially purified S. saprophyticus S67 peptidoglycan extract. After autopsy, kidneys and urinary bladder showed several histopathological changes both in cells and peptidoglycan injected mice, included: hydropic degeneration, glomerulus shrinkage, congestion of renal vessels, infiltration of inflammatory cells, and dekeratinization in urinary bladder.

New Azo ligands HL1 [2-Hydroxy-3-((5-mercapto-1,3,4-thiadiazol-2-yl)diazenyl)-1-naphth aldehyde] and HL2 [3-((1,5-Dimethyl-3-oxo-2-phenyl-2,3-dihydro-1H-pyrazol-4-yl)diazenyl)-2-hydroxy-1-naphthaldehyde] have been synthesized from reaction (2-hydroxy-1-naphthaldehyde) and (5-amino-1,3,4-thiadiazole-2-thiol) for HL1 and (4-amino-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one) for HL2. Then, its metal ions complexes are synthesized with the general formula; [CrHL1Cl3(H2O)], [VOHL1(SO4)] [ML1Cl(H2O)] where M = Mn(II), Co(II), Ni(II) and Cu(II), and general formula; [Cr(L2)2 ]Cl and [M(L2)2] where M = VO(II), Mn(II), Co(II), Ni(II) and Cu(II) are reported. The ligands and their metal complexes are characterized by phisco- chemical spectroscopic

Abstract:
This tribe had lived in Iraq since the first century A.D. Persia tried to
keep this tribe away from Iraq, but without result. The tribe managed to get
victory against Persia in the battle of Dhyqar.
When the Muslims had come to conquer Iraq, Rabi’a welcomed them
and takes part in that action.
That tribe helped the caliph Ali in the Jammal and Sifffen wars in order
to remain Iraq the center of the Islamic caliphates this tribe had felt very sad
and sorrowful when the caliphate become to the Umayyad . This tribe did not
give up, so this tribe did what could be done to help those who had revolted
against the Umayyad. Rabi’a did that in order to get ride of the Mudriat alsham,
and favored Rabi

Background: Periodontal diseases are inflammatory diseases affecting the supporting tissues of the teeth. One of the leading environmental factors that are closely related not only to the risk but also to the prognosis of periodontitis is smoking. This study aimed to evaluate the influence of smoking on periodontal health status and to measure the levels of matrix metalloproteinase-9 in smokers and nonsmokers chronic periodontitis patients, also it aimed to test the correlation between the levels of matrix metalloproteinase-9 and the clinical periodontal parameters. Materials and Methods: Five milliliters samples of un-stimulated whole saliva and full-mouth clinical periodontal recordings (plaque index, gingival index, bleeding on probing,

The question about the existence of correlation between the parameters A and m of the Paris function is re-examined theoretically for brittle material such as alumina ceramic (Al2O3) with different grain size. Investigation about existence of the exponential function which fit a good approximation to the majority of experimental data of crack velocity versus stress intensity factor diagram. The rate theory of crack growth was applied for data of alumina ceramics samples in region I and making use of the values of the exponential function parameters the crack growth rate theory parameters were estimated.

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).