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Analysis of Bacterial Resistance Patterns in Mahmoudiyah Hospital: A Retrospective Study in Baghdad
No full textAntibiotic resistance represents a critical threat to global public health, undermining the efficacy of antimicrobial therapy and complicating clinical management of bacterial infections. This retrospective study investigated the epidemiological profile and antimicrobial resistance patterns of bacterial pathogens isolated from clinical specimens at Mahmoudiyah Hospital in Baghdad during 2024. A total of 753 infection-suspected samples were analyzed using the VITEK 2 compact system and standard biochemical methods for identification and susceptibility testing. The most frequently isolated pathogens were Escherichia coli (10.1%), Klebsiella pneumoniae (8.5%), and Pseudomonas aeruginosa (7.7%), with Staphylococcus aureus (6.9%) also representing a significant proportion of isolates. Resistance profiles revealed alarming trends, including high methicillin resistance in S. aureus (MRSA prevalence: 77.5%) and widespread resistance among Gram-negative bacteria to commonly used antibiotics such as ampicillin, ciprofloxacin, and ceftriaxone. Notably, E. coli exhibited resistance patterns suggestive of extended-spectrum beta-lactamase (ESBL) production, while Acinetobacter baumannii showed complete resistance to colistin, a last-resort antibiotic. Further analysis of resistance patterns showed concerning rates of resistance to first-line agents: over 90% of E. coli isolates were resistant to ampicillin, while K. pneumoniae and P. aeruginosa displayed reduced susceptibility to fluoroquinolones and third-generation cephalosporins. Additionally, a substantial proportion of Gram-positive isolates, including Enterococcus faecalis, demonstrated high-level resistance to penicillin and ciprofloxacin. These findings underscore the urgent need for enhanced antimicrobial stewardship, robust infection control measures, and continuous surveillance to combat the escalating challenge of multidrug-resistant infections in hospital settings
The Potential Utilization of DNA Repair Protein XRCC1 as a Predictive Biomarker for Radiotherapy Response in Iraqi Women with Breast Cancer
No full textThis study sought to elucidate whether the XRCC1 protein could serve as a predictive biomarker for treatment response in breast cancer (BC) women undergoing radiotherapy (RT). Between July 2024 and January 2025, 180 blood samples from 60 newly diagnosed BC patients, aged 34–56 years, before and after RT at the Al-Amal National Hospital for Cancer Management and the Baghdad Center for Nuclear Medicine and Radiotherapy, as well as 60 age- and sex-matched controls (30 RT workers and 30 healthy women), were tested. A made-on-request enzyme immunoassay measured XRCC1 levels. Serum XRCC1 levels in BC patients significantly increased after RT, followed by RT workers, compared to pre-RT patients and healthy controls (438.42±105.18 vs 348.58±104.56 vs 53.36±13.97 vs 93.71±27.56 pg/ml, P<0.001). In BC patients receiving RT, XRCC1 levels were higher in the 15-fraction and 30-fraction groups than the 20- and 25-fraction groups (449.95±105.48 vs 538.59±4.63 vs 336.18±3.01 vs 368.12±80.16 pg/ml, P<0.05). XRCC1 levels were elevated significantly with RT doses of ≥ 50 Gy and 45 Gy (570.33±45.07 and 472.47±66.92 pg/ml). RT at 6 and 10 MV did not significantly affect BC patients (449.39±101.35 vs. 428.83±109.11 pg/ml, P>0.05). The XRCC1 ROC curve showed a high AUC (0.801, 95% CI= 0.70-0.88) with 74.5% sensitivity and 89.7% specificity. Additionally, XRCC1 predicted RT response with 81% accuracy (95% CI= 71.48-88.52). In BC patients and RT workers, high XRCC1 levels were linked to RT parameters, suggesting that XRCC1 may predict RT responsiveness and DNA repair efficacy. XRCC1 may also predict radiation-induced DNA damage in RT workers and encourage greater radiation protection
Clinical-Epidemiological Study of Measles Trends from 2019-2023 in Iraq
No full text
Measles, a highly contagious viral infection, which belongs to the Morbilivirus genus, Paramyxoviridae family. Remains a significant public health challenge worldwide, despite the availability of an effective vaccine. The objective is to determine the outcome of measles cases in Iraq and determine of measles trend from 2019-2023. The study is an epidemiological retrospective cross-sectional study that included information on Measles disease from 2019/January/1st to 2023/December/31st. The duration of data collection continued for the period from 2024/October/17th to 2025/February /28th. The data of the whole Iraq was collected from: Iraqi Ministry of Health\ Department of Public Health\ Communicable Disease Control Center from section of epidemiological surveillance that locates in Baghdad Governorate and obtains the information from health departments in the Iraq. The study included 3,873 laboratory-confirmed measles cases out of over 20,000 suspected cases. Descriptive statistics were applied, and inferential tests including the independent t-test, ANOVA, and chi-square test were used for data analysis via SPSS software (version 29.0), with a significance level set at p < 0.05. The clinical information show that the highest number of patients were from hospitals with 80.17% of patients, in contrast to primary health centers with 19.83%, the clinical methods of diagnosis had the highest ratio of result than others methods with 55.38%,) 15607 patients had diagnosed at hospital Lab 2.13% with positive result ,while 97.87% of the patients had negative result , The most of the cases had ELISA IgM test with 99.95% and the rest cases had Tissue Culture with 0.05%.Its reappearance the outbreak of measles has been facilitated by dwindling vaccination rates, inadequate healthcare systems, and the dissemination of false information. Its prevalence is 4104,728,199,633 and 14571 cases for the years (2019-2023) respectively, in Iraq. Regard to outcome of measles cases 99.94 % was cured.
Effects of Heat Transfer and Concentration on Peristaltic Ree-Eyring Fluid Flow in a Symmetric Channel with Square and Triangular Boundaries
No full textThis article aims to investigate the effects of heat transfer analysis, Ree-Eyring fluid concentration, magnetic field, porous media, and MHD on the peristaltic transport of Ree-Eyring fluid in a rotating frame within a symmetric channel that experiences triangular and square boundary in three dimensions. The governing equations are written, which are continuity, motion, heat, and concentration equations with help of conservation of mass, Newton\u27s second law, and conservation of energy, respectively. We then simplified the equations using the long wave length hypothesis and the Renold number approximation. This approximation led to the development of nonlinear differential equations. The exact solution of the Ree-Eyring particle concentration, temperature, velocity, and stream function are calculated. Using the MATHMETICA program, we have graphically clarified the flow quantities for different parameters. We have also graphically explained the trapping phenomenon. In this analysis, we observed that highlighting the concentration of fluid leads to a decrease in axial velocity and secondary velocity. The increase in the magnetic field resulted in an increase in axial velocity, but a decrease in secondary velocity. We observed an increase in trapping phenomena as the concentration of fluid increase and it decrease as the magnetic field increase
A Studying the effect of Depth of Cut on Electric Spark Machining parameters
No full textSeveral machining parameters impact the process\u27s quality. These parameters may include variables such as the type of polarity, the kind of workpiece, the types of dielectric materials, methods for dielectric flow, and the selection of operational parameters, among other factors. This paper includes optimization studies designed to provide insights into the influence of these factors and the strategies utilized to achieve optimal performance. The study revealed that the depth of cut consistently increased with higher pulse time and current values. Additionally, the optimization of process parameters for the EDM process using a copper electrode was explored. Metal removal using electro discharge Machining (EDM) is primarily achieved through melting. The reported experimental results indicate an absence of melting, even during short pulses with a discharge duration of 5 seconds, despite their sensitivity to temperature variations. This is because short pulses do not provide sufficient time for the metal to heat up effectively (equivalent to approximately 45 minutes), leading to minimal or no melting. In the EDM parameters used, the depth of cut increased with higher voltage levels (140 V to 240 V), current (Ip) values (12 A, 24 A, 50 A), pulse-on time (Ton) durations (100 ms, 200 ms, 400 ms), and pulse-off time (Toff) intervals (3 ms, 6.5 ms, 12 ms). The increase in voltage (140 V to 240 V) and current (Ip: 12 A to 50 A) significantly contributed to the enhanced depth of cut. The ET system utilized for these parameters also showed a consistent increase in the depth of cut with rising voltage and current. Testing confirmed that these parameters positively influenced the depth of cut while simultaneously improving their combined effect. Four parameters—voltage (140 V, 240 V), current (Ip: 12 A), and pulse rates—were evaluated, revealing that as voltage and current increased, the depth of cut and overall performance improved, with gradual adjustments in pulse rates enhancing the process further
Ant Colony Optimization With Lagrangian Relaxation For Cloud Computing Offloading Optimization
No full textThis research introduces a new optimization method that combines Ant Colony Optimization (ACO) with Lagrangian relaxation to improve the efficiency of cloud computing offloading. The objective is to enhance the distribution of computing activities and data transfer between mobile devices and cloud servers in order to decrease latency and energy consumption. The ACO method is used to effectively explore the solution space, while Lagrangian relaxation is performed to address the equality requirements of the optimization problem. The experimental findings confirm the efficacy of the suggested methodology in obtaining substantial enhancements in performance when compared to conventional methods
Key Performance Indicators of Sustainability for Iraqi Public Buildings
No full textDue to the importance of Sustainable Construction, a comprehensive assessment of the Sustainability of the built environment is required. Studying the sustainability performance indicators of current buildings is a crucial first step in evaluating a building\u27s sustainability. This study aims to understand the main performance of sustainability indicators for public buildings in Iraq as a result of relying on these buildings intensively for the development and welfare of society in Iraq. Based on previous studies, sustainability indicators were collected and identified, and 71 indicators were obtained, distributed among a group of categories within the three dimensions of environmental, social, and economic sustainability. The relative importance of the indicators was determined by organizing a questionnaire that was distributed to a group of engineers with experience in sustainable buildings, and relied on 103 forms in the analysis. The results of the survey were analyzed using a statistics program (SPSS-V-26) to give priority to the indicators identified using the relative importance index(RII) to point out the relative importance of environmental, social, and economic indicators. The Pareto principle was also applied to reduce the number of indicators and choose the most relatively important ones.14 key performance indicators for the sustainability of public buildings were obtained.
Enhanced Intrusion Detection Using RNA Encoding and Frequent Pattern Mining on CICIDS2017 Dataset
No full textIntrusion Detection System is a security system that serves as a shield to the infrastructure in place. Over the years, IDS technology has expanded significantly in order to meet the demands of new computer crime. Starting from the middle of the eighties to the current century, efforts have been made to improve its ability to identify attacks without compromising the performance of the network. This paper proposes a new method for a misuse IDS model based on RNA encoding and Frequent Pattern Mining for improving pattern extraction and classification, where Frequent Pattern Mining can deal with large amounts of data, therefore fast extractions of patterns and can detect intrusion in real-time. In this work, the characteristic patterns related to the malicious activity are identified using the CICIDS2017 dataset containing different types of network attacks. The proposed system comprises four stages: Data Selection and Preprocessing, RNA encoding, Frequent Pattern Mining and lastly classification. The experiments showed that the proposed IDS model has high accuracy and lower computational complexity as well as better scalability to be applied to real-time network intrusion detection.
Design and implementation of an automated eye care system GUI
No full textUsing a structured questionnaire sent to medical practitioners at Ibn Al-Haytham Eye Hospital, this study looks at user needs for a computerized Eye Care Management System (ECMS). The outcomes underline the requirement of automation in sophisticated image processing for disease identification, patient management, and appointment scheduling. Important needs found include easy user interfaces and safe data storage. These results led to the development of a prototype ECMS containing an interactive hospital interface with automatic Diabetic Macular Eedema (DME) identification.
This work shows how user-driven needs could direct the creation of sensible and quick eye care treatments. The information used in this study came from Ibn Al-Haytham Eye Hospital, therefore guaranteeing the practical relevance and legitimacy of the study. The created Python code was used for automated analysis and disease diagnosis to handle this actual data. The Eye Care Management System\u27s user interface then was developed and put into use depending on the processed data and the needs found by means of the questionnaire
The influence of weld joint integrity on Fatigue properties in carbon steel
No full textPresent research is mainly studying the influence of formation weld inclusions on the fatigue life to failure using mild steel compact tension specimen of 6mm thickness with weld position normal to the notch tip where crack is supposed to initiate and propagate toward the weld line which is about 3-to 5 mm away from the notch. The weld was conducted using shield metal arc welding method while the filler weld type used is E6010 Fatigue tests for all the prepared specimens were implemented under a constant load amplitude of 6 KN with loading frequency around 80 HZ, Different numbers of stress ratio were used during tests as explained later on. All tests give a confirmed results that fatigue life improved as stress ratio decreased while the number of fatigue cycle to failure were suddenly decrease when the crack tip hit the spherical weld inclusion which is considered as harmful defect on the weld joint. Scanning electron machine was massively used to investigate the fractur surfaces features and to show the shape and position of the inclusions