This research study experimentally the effect of air flow rate on humidification process
parameters. Experimental data are obtained from air conditioning study unit T110D. Results obtained
from experimental test, calculations and psychometrics software are discussed. The effect of air flow rate
on steam humidification process parameters as a part of air-conditioning processes can be explained
according to obtained results. Results of the steam humidification processes (1,2) with and without
preheating with 5A and 7.5A shows decreasing in dry bulb temperature, humidity ratio, and heat add to
moist air with increasing air flow rate, but humidification load, and total energy of moist air increase with
increasing air flo

Nitrogen dioxide NO₂ is one of the most dangerous contaminant in the air, its toxic gas that cause disturbing respiratory effects, most of it emitted from industrial sources especially from the stack of power plants and oil refineries. In this study Gaussian equations modelled by Matlab program to state the effect of pollutant NO₂ gas on area around Durra refinery, this program also evaluate some elements such as wind and stability and its effect on stacks height. Data used in this study is the amount of fuel oil and fuel gas burn inside refinery at a year 2017. Hourly April month data chosen as a case study because it’s unsteady month. After evaluate emission rate of the all fuel and calculate exit velocity from

ABSTRACT Background: The Iraqi hospital witnessed numerous violence incidents against medical staff working in emergency department and range from verbal to physical violence. High frequency of these attacks urged the Iraqi doctors for migration. Aim of study: To identify the prevalence of workplace violence against medical staff and to and study the risk factors related to work place violence. Materials and methods: A descriptive cross sectional study carried out among a sample of 300 medical

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

This studies deals with investigated the potential of a Iraqi bentonite clay for the adsorption of bromo phenol red dye from contaminated water. Impulse adsorption experiments were performed. The contact time influence of initial dye concentration, temperature, pH, ionic strength, partical size adsorbent and adsorbent dosage on bromo phenol red adsorption are investigated in a series of batch adsorption experiments. Adsorption equilibrium data were analyzed and described by the Freundlich, Langmuir and temkin isotherms equations. Thermodynamic parameters inclusive the Gibbs free energy (∆G• ), enthalpy (∆H• ), and entropy (∆S• ), were also calculated. These parameters specified that adsorption of bromo phenol red onto bentonite

In this research, an organobentonite (HDTMA-BT) was prepared by modifying a jordanian bentonite (BT) with hexadecyltrimethylammonium bromide. By means of in situ free radical polymerization in THF with AIBN as the initiator, this organobentonite is used to prepare the polymethylmethacrylate-bentonite (PMA-HDTMA-BT) nanocomposite. Scanning electron microscopy (SEM), x-ray diffraction (XRD), energy dispersive spectrometer (EDS) and Fourier transform infrared (FTIR) spectroscopy were used to characterize both HDTMA-BT and PMA-HDTMA-BT. Those adsorbents were used in a batch process to remove Pb(II), Cr(III) ions, and p-chlorophenol (PCP) from aqueous solution. Investigated factors included adsorbent dosage, initial pH solution, contact time, an

The approach of green synthesis of bio-sorbent has become simple alternatives to chemical synths as they use for example plant extracts, plus green synthesis outperforms chemical methods because it is environmentally friendly besides has wide applications in environmental remediation. This paper investigates the removal of ciprofloxacin (CIP) using green tea nano zero-valent iron (GT-NZVI) in an aqueous solution. The synthesized GT-NZVI was categorized using SEM, AFM, BET, FTIR, and Zeta potentials techniques. The spherical nanoparticles were found to be nano zero-valent, with an average size of 85 nm and a surface area of 2.19m2/g. The results showed that the removal efficiency of ciprofloxacin depends on the initial pH (2.5-10),