The aim of this research is to study the extent of the impact of government funding decisions on the financial performance of the directorate of Diyala province. The research problem was based on the financial reality of the directorate, and the data were collected from the financial divisions, planning and follow-up, implementation, and engineers of the resident engineer departments. Demonstrate the impact of government funding decisions on financial performance. Using scientific methods in estimating their financial needs through the annual estimated budget. The use of financial analysis to assess the performance of the Directorate, for the purpose of assessing the financial situation of the Directorate of research. The researc

Antibacterial activity of CNSs against Staphylococcus aureus and Escherichia coli was estimated. Higher inhibition zone of 18 mm and 20 mm were observed against S. aureus and E.coli, respectively, at a concentration of 2 mg/ml of carbon nanosphere after 24 hrs of incubation at 37 ºC. In vitro cytotoxicity experiment was performed on two parasite strains of Leishmania donovani and Leishmania tropica by using MTT assay. L. donovani revealed more sensitiv to the CNSs than L. tropica. An intermediate level of cytotoxicity of 51.31 % was observed when 2.4 mg/ml of CNSs was incubated with L. donovani, while weak cytotoxicity of 37.20 % was shown when the

Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin

water quality assessment is still being done at specific locations of major concern. The use of Geographical Information System (GIS) based water quality information system and spatial analysis with Inverse Distance Weighted interpolation enabled the mapping of water quality indicators along Tigris river in Salah Al-Din government, Iraq. Water quality indicators were monitored by taking 13 river samples from different locations along the river during Winter season year 2020. Maps of 10 water quality indicators. This meant that the specific water quality indicator and diffuse pollution characteristics in the basin were better illustrated with the variations displayed along the course of the river than conventional line graphs. Creation of

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

This study investigated the effect of essential oils extracted from peel of Citrus limon and Citrus reticulata on two species of fungui: Penicillium expansum and Fusarium proliferatum and also effect of two fungicides: Hymexazol and Benomyl against this fungi. Results showed that the essential oils of C. limon inhibited the radial growth of P. expansum and F. proliferatum at concentration 4.5 and 5%, respectively. However, the essential oil of C. reticulate inhibited this growth at concentration 5.5 and 6%, respectively. Moreover, the two fungicides inhibited radial growth of this fungi. In conclusion, there is a positive relationship between the increasing of concentration and the percentage of inhibiting of radial growth of fungi.

Thirty six bacteria were isolated from various sourcesc (soil, starch, cooked rice and other foods) and subjected to a series of primary screening tests to obtain the optimal isolation to production of amylase. The volume of producing zone by logal indicator for (Seven) isolates of the secondary screening by measuring the enzymatic activity and specific enzymatic activity. The isolate A4 was found to be the most efficient for production of amylase. Then this isolate was diagnosed through microscopic, vitek 2 system technique. in addition by gentic diagnesis through gene 16s of the genes nitrogen bases by use the polymerase chain reaction (PCR) which reached 1256 bases. In comparison to the available information at the National Center for