This is the first record of a new species of cyanobacteria Westiellopsis akinetica in the Iraqi environment, Samples were collected on June 2013 and the existence of it was not documented before. We isolated and purified this species ten years ago in Iraq, but we couldn't identify accurately based on all taxonomic handbooks. This is due to the species features being different from the other documented species in the available taxonomic lectures. It resembled many species by morphological characteristics such as Fischerella muscicola, Fischerella thermalis, Westiellopsis biateralis SA16. Westiellopsis interrupta, Westiellopsis persica SA33, Westiellopsis prolifica and Symphyonema bifilamentata. Describing a new species of the Westiellops

Most pathological effects of lead on the body are due to ability of lead to bind with important cellular molecules of various tissues and organs leading to formation abnormal molecules and thus to emergence of pathological conditions. To evaluation the risk to the health status of Iraqi workers who work in the batteries industry, expression of three types of calmodulin related genes were examined. Blood samples were collected from worker working in Iraqi industry of batteries (located in Al-Waziriya), then RNAs extraction were done thereby gene expression for Calcium/Calmodulin- dependent protein kinase2 (CaMKK2), C-X-C Chemokine receptor 4 (CXCR4) and mitogen activated protein kinase kinase 6 (MAP2K6) was done for each sample by using RT-q

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The rise of edge-cloud continuum computing is a result of the growing significance of edge computing, which has become a complementary or substitute option for traditional cloud services. The convergence of networking and computers presents a notable challenge due to their distinct historical development. Task scheduling is a major challenge in the context of edge-cloud continuum computing. The selection of the execution location of tasks, is crucial in meeting the quality-of-service (QoS) requirements of applications. An efficient scheduling strategy for distributing workloads among virtual machines in the edge-cloud continuum data center is mandatory to ensure the fulfilment of QoS requirements for both customer and service provider. E

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame