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

In this study, a theoretical scenario has been used to calculate the electronic current in sensitizer N3 molecule contact to TiO2 semiconductor for electrons in functional solar cells. It is known to play an important role on the compute the eficiency of solar cell. Some parameters of electronic current such as the transition energy, driving force energy, barrier height coupling overlapping values are determined. Transition energy is a necessary parameter to calculate the electronic current in solar cell with using wide polarity solvents Acetic acid, 2-Methoxyethanol, 1-Butanol, Methyl alcohol, chloroform, N,N-Dimethylacetamide and Ethyl alcohol via the quantum donor-acceptor system. Here, we show the results of transition energy can be var

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

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

Diabetes Mellitus is a group of metabolic diseases characterized by increasing of glucose level in plasma compared with normal value (hyperglycemia). This disease also causes elevation of lipid profile levels except HDL (High density lipoproteins) which increased relatively. The effects of the polyphenolic mixture (catechins, epicatechins, procyanidin B1, procyanidin B2 and procyanidin C1) on total cholesterol (TC), triacylglycerol (TG), high density lipoprotein (HDL) and low density lipoprotein (LDL) were studied in (30) streptozotocin-induced diabetic mice with (20-25)gm weight. Mice were given (30 mg/mL) of Polyphenolic Cocoa beans Extracts (CE) once daily for (7) days before Streptozotocin STZ injection and for (21 day) there after. A

The long-term monitoring of land movements represents the most successful application of the Global Navigation Satellite System (GNSS), particularly the Global Positioning System. However, the application of long term monitoring of land movements depends on the availability of homogenous and consistent daily position time series of stations over a period of time. Such time series can be produced very efficiently by using Precise Point Positioning and Double Difference techniques based on particular sophisticated GNSS processing softwares. Nonetheless, these rely on the availability of GNSS products which are precise satellite orbit and clock, and Earth orientation parameters. Unfortunately, several changes and modifications have been mad

The aim of this work is to provide an efficient selection technique as a part of planning process to guide the decision makers to decide the preferences of one supplier over another for purchasing lab instruments in education domain. Fuzzy Analytical Hierarchy Process has used as a multi-criteria decision process, as an industrial engineering tool with certain emphasis on the qualitative aspects required to the decision makers. While the concept of degree of possibility for each criterion is used to reach its relative weights, a specific methodology created to reach the final objective decision of supplier selection. A questionnaire form was developed and distributed to five universities located in Baghdad province with a total

This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro