The focus of this research revolves around the importance level of sialic acid in the reasoning of cases, including tumors and then evaluate the patient's response to treatment and its impact on the immune response there are a lot of evidence showing that parts Alkrbu ???????? in peptides sugary and glycoproteins play an important role in Alfalitin life and responsiveness

Optical fiber chemical sensor based surface Plasmon resonance for sensing and measuring the refractive index and concentration for Acetic acid is designed and implemented during this work. Optical grade plastic optical fibers with a diameter of 1000μm were used with a diameter core of 980μm and a cladding of 20μm, where the sensor is fabricated by a small part (10mm) of optical fiber in the middle is embedded in a resin block and then the polishing process is done, after that it is deposited with about (40nm) thickness of gold metal and the Acetic acid is placed on the sensing probe.

The Sequencing Batch Reactor system (SBR) is a major component of the municipal wastewater biological treatment system and water reclamation that provides high-quality water that could be reused in restricted plants that which require large quantities of water despite the lack of water. The research aims to investigate the performance of a pilot plant SBR unit under real operation conditions that was installed and operated in Al-Rustamiya Wastewater Treatment Plant (WWTP), Baghdad, Iraq. Results showed that the BOD5/COD ratio of the raw wastewater was within the average value at 0.66 emphasizing the organic nature of the influent flow and hence the amenability to biological treatment. The results also ensured that the treatment pro

The aim for this research is to investigate the effect of inclusion of crack incidence into the 2D numerical model of the masonry units and bonding mortar on the behavior of unreinforced masonry walls supporting a loaded reinforced concrete slab. The finite element method was implemented for the modeling and analysis of unreinforced masonry walls. In this paper, ABAQUS, FE software with implicit solver was used to model and analyze unreinforced masonry walls which are subjected to a vertical load. Detailed Micro Modeling technique was used to model the masonry units, mortar and unit-mortar interface separately. It was found that considering potential pure tensional cracks located vertically in the middle of the mortar and units show

In this work, optical system with different aperture shapes (circular, square, elliptical and triangle aperture) has been used for efficiency evaluation when the system involved moving factor in ideal case (aberration free). The optical system evaluate far moving object, therefore the image forming at image plane due to point spread function (image formula of incoherently illuminated point object). A mathematical treatment has been used to getting results by Gaussian numerical calculations method. The results show priority of circular aperture when optical system that submits of moving factor.

This study was aimed to director wheat production's technical efficiency grown under two irrigation systems(fixed and pivot sprinkler irrigation systems)using random border analysis.Samples were collected randomly from267farmers from Salah Al-Din Governorate/Iraq.The samples were divided into two groups;187farmers used a pivot sprinkler irrigation system with three categories of possession(80,60and120dunums),while the other group used a fixed sprinkler irrigation system with four categories of possession(40,30,20and10dunums).Transcendent production function was used to study the effect of production factors on wheat yield. The results indicated that the mechanization work and the amount of added irrigation water increased by 1% whil

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par