This study aimed to evaluate the health effects of exposure to particulate matter (PM2.5 and PM10) and gaseous pollutants, including carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2), on the hematological parameters of workers exposed to charcoal grilling emissions in restaurants. Air pollutant concentrations were measured in six barbecue restaurants located in Al-Rusafa District, Baghdad, during December 2024 and January 2025. Nine measurements were recorded monthly during morning and evening peak cooking periods. Blood samples were collected from two groups: grilling workers exposed directly to charcoal smoke (n = 30) and customers from dining areas as the control group (n = 30). Hematological analyses included white blood cells (WBC), red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), platelets (PLT), and other blood indices. Statistical analyses were performed using independent t-tests and stepwise multiple linear regression analysis. The results showed that pollutant concentrations were consistently higher in grilling areas than in dining areas, especially during evening hours, due to intensive cooking activity and insufficient ventilation. PM2.5 and PM10 concentrations frequently exceeded World Health Organization (WHO) permissible limits in grilling areas, while CO, NO2, and SO2 also reached elevated levels. Significant increases (p ≤ 0.05) were observed in WBC, RBC, HGB, HCT, mean corpuscular volume (MCV), and PLT among exposed workers compared with the control group. Stepwise regression analysis demonstrated that CO2 was positively associated with WBC, HGB, RBC, MCV, and PLT, whereas PM10 and PM2.5 showed negative associations with several hematological parameters after adjustment for co-pollutants. These findings suggest that chronic exposure to indoor air pollutants generated from charcoal grilling may induce systemic inflammation, oxidative stress, and physiological adaptation to hypoxic conditions among restaurant workers.
An approximate solution of the liner system of ntegral cquations fot both fredholm(SFIEs)and Volterra(SIES)types has been derived using taylor series expansion.The solusion is essentailly
This work aim to prepare Ag/R6G/PMMA nanocomposite thin
films by In-situ plasma polymerization and study the changes in the
optical properties of fluorophore due to the presence of Ag
nanoparticles structures in the vicinity of the R6G laser dye. The
concentrations of R6G dye/MMA used are: 10-4M solutions were
prepared by dissolving the required quantity of the R6G dye in
MMAMonomer. Then Silver nanoparticles with 50 average particles
size were mixed with MMAmonomer with concentration of 0.3, 0.5,
0.7wt% to get R6G silver/MMA in liquid phase. The films were
deposited on glass substrates by dielectric barrier discharge plasma
jet. The Ag/R6G/PMMA nanocomposite thin films were
characterization by UV-Visible
Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
... Show MoreThis study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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