Background: The healing period for bone–implant contact takes 3–6 months or even longer. Application of Escherichia coli-derived recombinant human bone morphogenetic protein-2 (ErhBMP-2) to implant surfaces has been of great interest on osseointegration due to its osteoinductive potential. The objective of this study was to evaluate the effect of ErhBMP-2 on implant stability. Materials and methods: A total of 48 dental implants were inserted in 15 patients. Twenty four implants coated with 0.5 mg/ml ErhBMP-2 (study group). The other 24 implants were uncoated (control group). Each patient was received at least two dental implants at the same session. Both groups were followed with repeated implant stability measurements by me

This study aims to observe the effect of melatonin implantation and exposure to different light colors and their interaction on productive in local Iraqi chicken. This study was conducted at the poultry farm of the Department of Animal Production/College of Agriculture/University of Baghdad/Abu Ghraib, on 252 birds (180 females and 72 males). The birds were divided into three sections (white, red and green) each section contains two lines, one of which has been planted melatonin under the skin of the neck of birds and the other has not been planted hormone. The results of the study showed significant improvement in productive traits such as egg proportion rate, egg weight, cumulative eggs number, egg mass and feed conversion rate. That the

Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

The influence and hazard of fire flame are one of the most important parameters that affecting the durability and strength of structural members. This research studied the influence of fire flame on the behavior of reinforced concrete beams affected by repeated load. Nine self- compacted reinforced concrete beams were castellated, all have the same geometric layout (0.15x0.15x1.00) m, reinforcement details and compressive strength (50 Mpa). To estimate the effect of fire flame disaster, four temperatures were adopted (200, 300, 400 and 500) oC and two method of cooling were used (graduated and sudden). In the first cooling method, graduated, the tested beams were leaved to cool in air while in the second method, sudden, water splash was use

The objective of this study is to determine the efficacy of class V Er:YAG laser (2940 nm) cavity preparation and conventional bur cavity preparation regarding Intrapulpal temperature rise during cavity preparation in extracted human premolar teeth. Twenty non carious premolar teeth extracted for orthodontic purposes were used and class V cavity preparation was applied both buccal and lingual sides for each tooth .Samples were equally grouped into two major groups according to cavity depth (1mm and 2mm). Each major group was further subdivided into two subgroupsof ten teeth for each (twenty cavities for each subgroup). TwinlightEr:YAG laser (2940 nm) with 500mJ pulse energy, P.R.R of 10 Hz and 63.69 J/cm2 energy density was used. The ana

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i