When the number of confirmed coronavirus disease cases rose in Iraq in the middle of February 2021, the Iraqi government performed a closure approach to constrain mobility and factory operations and enforce social distancing. In this research, the concentrations of air components (PM_2.5, PM₁₀, nitrogen dioxide (NO₂) and ozone (O₃)), which represent herein the degree of air quality index, were recorded, drawn and evaluated over central (Baghdad, the capital), northern (Kirkuk Province) and southern (Basra Province) Iraq before and during the closure. The experimental duration of this research was 6 months (from 1 January 2021 to 30 June 2021), which

Reducing costs and protecting the environment surrounding economic unity has become the concern of many economic units and shifting their ideas towards preserving resources and protecting the environment by adopting strategies and techniques that take into account when applied reducing production costs and protecting the environment, including these strategies and techniques, the technical costs of the product life cycle and the strategy of cleaner production, as the application of the two concepts in local economic units helps to try to keep up with the countries that work to keep up with the success of their economic units by following the concepts that have been successful in  Developed countries by maintaining the sustainabilit

This work studied the electrical and thermal surface conductivity enhancement of polymethylmethacrylate (PMMA) clouded by double-walled carbon nanotubes (DWCNTs) and multi-walled carbon nanotube (MWCNTs) by using pulsed Nd:YAG laser. Variable input factors are considered as the laser energy (or the relevant power), pulse duration and pulse repetition rate. Results indicated that the DWCNTs increased the PMMA’s surface electrical conductivity from 10-15 S/m to 0.813×103 S/m while the MWCNTs raised it to 0.14×103 S/m. Hence, the DWCNTs achieved an increase of almost 6 times than that for the MWCNTs. Moreover, the former increased the thermal conductivity of the surface by 8 times and the later by 5 times.

Message in the tune of readers and denial to those who say infidelity tunes

In the present study, the effects of brake pad particles of lung and liver histological sections were evaluated for (60) adult male mice. The animals were divided into three groups ( A,B,C) according to the periods of exposure (4, 8, and 12) weeks respectively exposed to brake pad particles in addition to the control groups (F) exposed to fresh air only. A special inhalation chamber designed locally has been used to expose the animals. The exposure to brake pad particles was (2.228) µg/m³ for 30 min/day, 5 days/week for (4,8and12) weeks respectively.

The examination in group (A) of the histological sections of the lung showed the thickness of interalveolar septa.  Also, a congestion of alveolar capillary was marked indicat

The present study combines UV-Vis spectrophotometry and dispersive liquid-liquid microextraction (DLLME) for the preconcentration and determination of trace level clidinium bromide (Clid) in pharmaceutical preparation and real samples. The method is based on ion-pair formation between Clid and bromocresol green in aqueous solution using citrate buffer (pH = 3). The colored product was first extracted using a mixture of 800 µL acetonitrile and 300 µL chloroform solvents. Then, a spectrophotometric measurement of sediment phase was performed at λ = 420 nm. The important parameters affecting the efficiency of DLLME were optimized. Under the optimum conditions, the calibration graphs of standard -1 (Std.), drug, urine and serum were ranged

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c