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 develope

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

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Periodontal disease is typically treated with mechanical debridement of the tooth surface. It may, however, be insufficient to eradicate pathogenic microorganisms on its own. Because of the microbial etiology of periodontitis, systemic or local antibiotic therapy is used as an adjunct treatment. The present study aimed to determine the effects of curcumin gel on Porphyromonas gingivalis. Eleven patients with stage II and III periodontitis were registered in the study. A double-blinded split-mouth design followed. Periodontal pockets were distributed into 2 groups; the test group received scaling and root planing along with curcumin gel, while the control group received scaling and root planing along with a placebo gel. Plaque index,

A factorial experiment (2× 3) in randomized complete block design (RCBD) with three replications was conducted to examine the effect of honeycomb selection method using three interplant distances on yield and its components of two cultivars of bean, Bronco and Strike. Interplant distances used were 75× 65 cm, 90× 78 cm, and 105× 91 cm (row× plant) represent short (high plant density), intermediate (intermediate plant density), and wide (low plant density) distance, respectively. Parameters used for selection were number of days from planting to the initiation of first flower, number of nodes formed prior to first flower, and number of main branches. Results showed significant superiority of the Bronco cultivar represented in the number

Objective: Hesperidin (HSP) is a pharmacologically active organic compound found in citrus fruits and peppermint. We synthesized a new HSP derivative by reacting it with 5-Amino-1,3,4-thiadiazole-2-thiol in acetic acid. Methods: This compound was characterized by Fourier-transform infrared, proton nuclear magnetic resonance, and electron impact mass spectra. A molecular docking study explores the predicted binding of the compound and its possible mode of action. Bioavailability, site of absorption, drug mimic, and topological polar surface was predicted using absorption, distribution, metabolism, and excretion (ADME) studies. Results: The docking study predicts that the new compound binds to the active sites of Aurora-B

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

Purpose:  the purpose of study is estimate the Risk premium, Interest rate, Inflation and FDI in the through of Coronavirus in the MENA countries.   Theoretical framework: The theoretical framework included the study of the main variables, which are risk premium, interest rate, inflation, and foreign direct investment during the Corona virus pandemic.   Design/methodology/approach:  Concentrating on “COVID-19”, as an effective factor on the Foreign direct investment (FDI), I employ data of “MENA (Middle East and Northern Africa)” countries from 2000 to 2021 to investigate the impact of COVID-19, financial and macroeconomic indicators on FDI relying on the analytic research approach of Static panel data regression, includ

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J