The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The developed ANN mode gave a high correlation coefficient reaching 0.927 for the prediction of TDS from the model and showed high levels of TDS in Al-Hawizeh marsh that pose threats to people using the marsh for drinking and other uses. The dissolved Oxygen concentration has the highest importance of 100% in the model because the water of the marsh is fresh water, while Turbidity had the lowest importance.
This research is studying technique sculptures super - realism, search through, how the method of work, and the search for the materials used in their manufacture, and this is the first study in the field of art and the field of academic study in the country.Research consists of an introduction, And four sections, The introduction containing information on: research problem, Importance of research, Goals of the research, Limits of research, research approach, and research tools.The first section contains a technical study sculptures super -realism in contemporary sculpture, while the second section includes a search for alternative materials available in the local markets, for making sculptures super - realism, the third section dedicate
... Show MoreThe article presents the results of studying the conchological variability of the terrestrial mollusk Chondrulopsina fedtschenkoi (Ancey, 1886), known to occur in three regions of the Zaravshan Range (Central Asia): the Urgutsay Gorge, the vicinity of the Gissarak Reservoir and the Ingichka-Irmak Gorge. Conchological variability was determined based on statistical analysis. The climate of the three regions is different, and environmental factors have led to changes in the mollusk shell. The shells have changed in response to environmental factors, these are their adaptive traits for survival; the variability of conchological features is also reflected in the color of the shell, and the intensive development of the color of the shell in m
... Show MoreThe manganese doped zinc sulfide nanoparticles were synthesized by simple aqueous chemical reaction of manganese chloride, zinc acetate and thioacitamide in aqueous solution. Thioglycolic acid is used as capping agent for controlling the nanoparticle size. The main advantage of the ZnS:Mn nanoparticles of diameter ~ 2.73 nm is that the sample is prepared by using non-toxic precursors in a cost effective and eco-friendly way. The structural, morphological and chemical composition of the nanoparticles have been investigated by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) with energy dispersion spectroscopy (EDS) and Fourier transform infrared (FTIR) spectroscopy. The nanosize of the prepared nanoparticles was elucidated by Scan
... Show MoreBackground: The most crucial mechanism of genetic variation in N. meningitidis is the slipped strand mispairing, this mechanism generates Phase variation using simple sequence repeat (SSR) and is commonly used by the N. meningitidis to escape the immune system despite its function in eradicating the pathogenic and commensal bacteria. Some of simple sequence repeats (SSRs) that located within the genome works as phase variation while other SSRs have no role in generating phase variation mechanisms. Therefore, Aim: the main goal of the current in silico study was to detect the probability of SSR to enroll with phase variation for the entire N. meningitidis genome. Methods: Different criteria were used to judge SSR as
... Show MoreIntroduction and Aim: Cancers are a complex group of genetic illnesses that develop through multistep, mutagenic processes which can invade or spread throughout the body. Recent advances in cancer treatment involve oncolytic viruses to infect and destroy cancer cells. The Newcastle disease virus (NDV), an oncolytic virus has shown to have anti-cancer effects either directly by lysing cancer cells or indirectly by activating the immune system. The green fluorescent protein (GFP) has been widely used in studying the anti-tumor activity of oncolytic viruses. This study aimed to study the anticancer effect of a recombinant rNDV-GFP clone on NCI-H727 lung carcinoma cell line in vitro. Materials and Methods: The GFP gene was inserted t
... Show MoreBackground: Generally, genetic disorders are a leading cause of spontaneous abortion, neonatal death, increased morbidity and mortality in children and adults as well. They a significant health care and psychosocial burden for the patient, the family, the healthcare system and the community as a whole. Chromosomal abnormalities occur much more frequently than is generally appreciated. It is estimated that approximately 1 of 200 newborn infants had some form of chromosomal abnormality. The figure is much higher in fetuses that do not survive to term. It is estimated that in 50% of first trimester abortions, the fetus has a chromosomal abnormality. Aim of the study: This study aims to shed some light on the results of chromosomal studies per
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
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