Abstract:

Investment in human capital of renewable energy can be relied upon to get to achieve the goals of development is important for Iraq through the intellectual community cards creative able to innovate and develop what is so is study the effect of human investment on economic growth through the adoption of the index of national income as a function of variables independent ( human capital, physical capital) and this is built on the premise that the relationship direct correlation between economic growth and human investment, and it can measure the return on human investment, which is an incentive to increase human capital through education and the development of the economy in general have shown th

Back ground : The transforming growth factor beta (TGFB) signaling pathway is involved in many cellular processes in both the adult organism and the developing embryo including cell growth, cell differentiation, apoptosis. The interaction between implant material and surrounding tissues is believed to play a fundamental role in implant success and illustrates different expression of growth factors by different cells that involved in the formation of peri-implant tissue. The aim of this study was to localize expression of TGF B by newly formed bone tissue around surface-conditioned implants with placental collagen at different time intervals: 3 ,7,14,28, and 56 days . Materials and Methods: Commercially pure Titanium (CPTi) implants coated w

ABCTRACT

Care research examining the relationship between the variables of search presidents (employee training and organizational commitment) to determine the effect of the training of employees in organizations in achieving organizational commitment of employees towards their organizations and by the fact that training is one of the most important activities adopted by the administration and by which can benefit realized for workers and for the organization .ttjsd problem Search lack of training considered as a factor of the important factors in the development of staff skills and development work in many Iraqi companies, including vegetable oils company (where to look), which in turn raises the relevance and commitment

Electrocoagulation process was employed for the treatment of river water flows in Iraq. In this study, a batch Electrocoagulation process was used to treat river water taken from Al - Qadisiyah water treatment plant. electrolysis time, voltage and inter-electrode spacing were the most important parameters to study . A statistical model was developed using the RSM model. The optimum condition after studying the parameter effect the process was 1 cm separating, 30 volts . The RSM model shows the ideal condition of removal for both the TSS and turbidity at 1 cm, 20 volts and 55 min.

This systematic review aimed to analyse available evidence to answer two focused questions about the efficacy of erythritol powder air‐polishing (EPAP) (i) as an adjunctive during active periodontal therapy (APT) and (ii) as an alternative to hand/ultrasonic instrumentation during supportive periodontal therapy (SPT). Additionally, microbiological outcomes and patient's comfort/perceptions were assessed as secondary outcomes.

The extraction process of chlorophyll from dehydrated and pulverized alfalfa plant were studied by percolation method. Two  solvent systems were used for the extraction namely; Ethanol-water and Hexane-Toluene systems . The effect of circulation rate, solvent concentration, and solvent volume to solid weight ratio were studied. In  both ethanol water, and Hexane-Toluene systems it appears that solvent concentration is the most effective variable.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve