Porous Silicon (PSi) has been produced in this work by using Photochemical (PC) etching process by using a hydrofluoric acid (HF) solution. The irradiation has been achieved using quartz- tungsten halogen lamp. The influence of various irradiation times on the properties of PSi اmaterial such as layer thickness, etching rate and porosity was investigated in this work too.
The XRD has been studied to determine the crystal structure and the crystalline size of PSi material

    The fauna of bees (Hymenoptera, Apoidea) from different regions of Iraq is surveyed in this study; there were 16 species, 13 genera that belong to four families which are collected in this investigation.

    Also, all the species that are recorded for Iraq in previous investigations are revised; totally there are 110 species, 32 genera belonging to  five families: Apidae, Andernidae, Colletidae, Halictidae and Megachilidae were listed.

Abstract:Porous Silicon (PSi) has been produced in this work by using Photochemical (PC) etching process by using a hydrofluoric acid (HF) solution. The irradiation has been achieved using quartz- tungsten halogen lamp. The influence of various irradiation times on the properties of PSi اmaterial such as layer thickness, etching rate and porosity was investigated in this work too. The XRD has been studied to determine the crystal structure and the crystalline size of PSi material

The hydroisomerization of n-decane was studied on SAPO-11 catalyst. Catalyst of 0.25wt.%Pt/SAPO-11 was prepared locally and used in the present work. The hydroconversion performed in a continuous fixed-bed laboratory reaction unit. Experiments of n-decane isomerization were performed in a temperature range of 200 to 275°C,LHSV range of 0.5-2 h^-1, and hydrogen to decane mole ratio of 2.1-8.2. The results show that the n-decane conversion increases with increasing temperature and  decreasing LHSV , the maximum conversion 56.77 % was achieved at temperature 275°C and LHSV of 0.5 h^-1. The kinetic of n-decane isomerization was also studied and the reaction was first order. The kinetic analysis also showed that the

The hydroisomerization of n-decane was studied on SAPO-11 catalyst. Catalyst of 0.25wt.%Pt/SAPO-11 was prepared locally and used in the present work. The hydroconversion performed in a continuous fixed-bed laboratory reaction unit. Experiments of n-decane isomerization were performed in a temperature range of 200 to 275°C,LHSV range of 0.5-2 h-1, and hydrogen to decane mole ratio of 2.1-8.2. The results show that the n-decane conversion increases with increasing temperature and  decreasing LHSV , the maximum conversion 56.77 % was achieved at temperature 275°C and LHSV of 0.5 h-1. The kinetic of n-decane isomerization was also studied and the reaction was first order. The kinetic analysis also showed that the activation energy eq

Firstly, in this study, a brief updated description and applications of different solar collectors used in renewable energy systems for supplying electric and thermal energy was presented. Secondly, an attempt was made to utilize tilting orientation of solar collector for maximizing collector energy with time in respect to horizontal orientation. For energy calculation, global solar radiation was used since they are directly related.  For that purpose, field measurements of half-hourly radiation on two flat panels of tilting and horizontal orientations were carried out throughout 8-month period under local climate of Baghdad. Then, energy gain and radiation level averages were calculated based on the field radiation

The histological structure of Pycnonotus leucotis was investigated to fill the dearth of information on the histology of mid-brain from available literature and help understand its brain. The brain is wide and short and its length 1.5 cm, and it consists of three regions. The middle region is the mesencephalon. The mesencephalon was divided into optic tectum and tegmentum. The optic tectum consists of six main layers, while the tegmentum contains nuclei of cranial nerves.

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