The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.
Type 2 diabetes mellitus (T2DM) is a chronic disorder that is a serious health concern all over the globe, it is linked to Interleukin-10 (IL-10) single nucleotide polymorphisms (SNPs) at the promoter region. On the other hand, diabetes influences the cellular and humoral immunity predisposing the patient to a variety of opportunistic parasites one of them is Toxoplasma gondii (T. gondii), which may infect any nucleated cell, including pancreatic cells. The purpose of this research was to explore the association of IL-10 genetic polymorphisms with T2DM and latent toxoplasmosis among Iraqi patients with T2DM. Fifty-five and fifty-eight venous blood samples were taken from T2DM patients and age-matched non-diabetic person
... Show MoreThe present study evaluates the effects of Ginkgo biloba extract as monotherapy on the glycemic status, insulin resistance (IR), body mass index (BMI), and visceral adiposity index (VAI), in addition to the inflammatory markers, oxidative status and leptin level in patients with metabolic syndrome in comparison with metformin.
The study is a randomized, double-blind pilot study conducted during the period May to September, 2020. Fifty patients were recruited in the study and they were allocated into two groups (25 per each group): Ginkgo biloba and Metformin groups, they received (120 mg Ginkgo biloba extract/ capsule) and (500 mg Metformin/ capsule) respectively; orally as a single dose for 90 days. Blood samples were taken at z
... Show Moreالمستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة
Objectives: To report the Cesarean section rate in Al-
Batool Maternity Teaching Hospital and to identify
how many of them were done for maternal and fetal
condition.
Design: A statistical cross sectional study.
Setting: The study was conducted at Al-Batool
Maternity Teaching Hospital (13000 deliveries per
year).
Participants: The patients group consists of 4556
patients admitted for delivery (vaginal and abdominal)
during a period of four months commencing from
January 2003.
Main outcome measures: calculation of all live
births, calculation of cesarean section rate, percentage
of the primary cesarean sections and the repeat
cesarean sections and listing the indications of the
operation acc
Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T
... Show MoreThis study aimed to identify the perceived mental image of volunteering, and its relationship to volunteer motivation among a sample of Al-Quds Open University students, as well as to identify the differences in the perceived mental image of volunteering due to variables (gender, year of study, place of residence, college). The researcher has used relational descriptive approach. The researcher has used two questionnaires, the first was used to measure the perceptive mental image of volunteering, and the second to measure the motivation towards volunteering, and the study population may consist of all students of Al-Quds Open University Hebron Branch during the first semester of the academic year 2021/2020 and their number (3462)Male and
... Show MoreThe percentage of fatty acids, quantity of tocopherols, tocotrienols, carotens and physiochemical characteristics of crude red palm oil have been evaluated, in addition to specific chemical detection of active compounds unsaponifiable matters. Results of Gas Liquid Chromatography showed:- The major fatty acids in red palm oil is palmitic (44.36%) then oleic (39.65%), linolenic (10.55%), stearic (3.56%), myristic (1.22%), arachdonic (0.24%) and palmotic (0.19%). Red palm oil contains ? – ?- ?- ? – Tocopherols with concentration 258 , 121 , 259, 109 m/kg oil , ? – ?- ?- ? – Tocotrienol with concentration 462.77 , 571.03, 619.18, 509.07 m/kg oil respectively. Total tocopherols & tocotrienols 2909.05 m/kg oil and
... Show MoreThe present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag
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