Until today, one of the leading predominant infections is Urinary tract infection (UTI). It exerts a huge burden on health systems worldwide each year. Treating UTIs empirically with antimicrobials improves morbidity rates. This study aims to assess the prevalence of UTI-associated bacteria in adult patients and to determine their antibiotic susceptibility profile. A retrospective study was conducted for adult outpatients who visited Al-Diwaniya tertiary hospitals from January 2020 till February 2022 to review their medical and lab records in addition to sociodemographic data. A total of 256 patients’ records were included of which 204 (79.7%) belong to females and 52 (20.3%) were males with an average age of 39.22±17.10 years. The predominant organisms’ isolates were Staphylococcus spp. found in 100 records (39.1%), Escherichia coli (E. coli) demonstrated in 90 records (35.2%), and Klebsiella spp. (K. spp.) revealed in 23 records (9%). Staphylococcus spp. (Staph. spp.) showed high resistance to ampicillin (92.9%) followed by ceftazidime (87.5%), and were highly sensitive to vancomycin. The higher resistance profile of E. coli was to ampicillin (97.9%) and ceftriaxone (81.3%) while was highly susceptible to meropenem (97.9%) and amikacin (97.6%). Additionally, Klebsiella spp. was highly susceptible to nitrofurantoin (78.6%), while was completely resistant to ampicillin. This study presents Staphylococcus spp. as the most prevalent gram-positive uropathogen and E. coli as the most prevalent gram-negative bacteria with a multidrug resistance profile to commonly used antimicrobials which is an alarming situation to implement an immediate effective stewardship program.
A laboratory investigation of six different tests were conducted on silty clay soil spiked with lead in concentrations of 1500 mg/kg. A constant DC voltage gradient of 1 V/cm was applied for all these tests with duration of 7 days remediation process for each test. Different purging solutions and addition configurations, i.e. injection wells, were investigated experimentally to enhance the removal of lead from Iraqi soil during electro-kinetic remediation process. The experimental results showed that the overall removal efficiency of lead for tests conducted with distilled water, 0.1 M acetic acid, 0.2 M EDTA and 1 M ammonium citrate as the purging solutions were equal to 18 %, 37 %, 42 %, and 29 %, respectively. H
... Show MoreThe permeable reactive barrier (PRB) is one of the promising innovative in situ groundwater remediation technologies, in removing of copper from a contaminated shallow aquifer. The 1:1- mixture of waste foundry sand (WFS) and Kerbala’s sand (KS) was used for PRB. The WFS was represented the reactivity material while KS used to increase the permeability of PRB only. However, Fourier-transform infrared (FTIR) analysis proved that the carboxylic and alkyl halides groups are responsible for the sorption of copper onto WFS. Batch tests have been performed to characterize the equilibrium sorption properties of the (WFS+KS) mix in copper- containing aqueous
solutions. The sorption data for Cu+2 ions, obtained by batch experiments, have be
Thin-walled members are increasingly used in structural applications, especially in light structures like in constructions and aircraft structures because of their high strength-to-weight ratio. Perforations are often made on these structures for reducing weight and to facilitate the services and maintenance works like in aircraft wing ribs. This type of structures suffers from buckling phenomena due to its dimensions, and this suffering increases with the presence of holes in it. This study investigated experimentally and numerically the buckling behavior of aluminum alloy 6061-O thin-walled lipped channel beam with specific holes subjected to compression load. A nonlinear finite elements analysis was used to obtain the
... Show MoreIn this paper, a numerical model for fluid-structure interaction (FSI) analysis is developed for investigating the aeroelastic response of a single wind turbine blade. The Blade Element Momentum (BEM) theory was adopted to calculate the aerodynamic forces considering the effects of wind shear and tower shadow. The wind turbine blade was modeled as a rotating cantilever beam discretized using Finite Element Method (FEM) to analyze the deformation and vibration of the blade. The aeroelastic response of the blade was obtained by coupling these aerodynamic and structural models using a coupled BEM-FEM program written in MATLAB. The governing FSI equations of motion are iteratively calculated at each time step, through exchanging data between
... Show MoreAddressed the problem of the research is marked: (Performing processors for the time between Impressionism and superrealism) the concept of time and how to submit artwork. The search came in four sections: general framework for research and identified the research problem and the need for him. With an indication of the importance of his presence. Then determine the research objectives of (detection processors performing to the concept of time in works of art in each of Impressionism and superrealism. And a comparison between them to reveal similarities and differences), followed by the establishment of boundaries Find three (objectivity, the temporal and spatial) were then determine the terms related to the title. Then provide the theore
... Show MoreABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
... Show MoreIn the leaves of Olea europaea L. Olive trees an endophytic fungus was discovered. Cladosporium sp. was identified to be the fungus based on its morphological characteristics and nuclear ribosomal DNA ITS sequence analysis and was registered in NCBI as the Cladosporium genus has been registered under the number (0P939922.1) The species was not specified, and it was considered of unknown species after comparing it to global isolates. In comparison to olive leaf extract, Cladosporium sp. including total flavonoid, total phenolic, total terpenoid, and total saponins, Which were 121.9%, 198.1%, 89.13%, and 29.87 % respectively compared to its content in olive leaf extract, which was 61.54 %, 67.88 % , 17.1
... Show MoreThis paper presents thermal characteristics analysis of a modified Closed Wet Cooling Tower (CWCT) based on heat and mass transfer principles to improve the performance of this tower in Iraq. A prototype of CWCT optimized by added packing was designed, manufactured and tested for cooling capacity of 9 kW. Experiments are conducted to explore the effects of various operational and conformational parameters on the thermal performance. In the test section, spray water temperature and both dry bulb temperature and relative humidity of the air measured at intermediate points of the heat exchanger and packing. Heat exchangers consist of four rows and eight columns for an inline tubes arrangement and six rows and five columns f
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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