Phytoplankton community is a model for of monitoring  aquatic systems and interpreting the environmental change in aquatic systems. The present study aimed to forecast environmental parameters that drive the change of phytoplankton community structure in the lake. The present study was carried out in Baghdad Tourist Island Lake (BTIL) for the period From October 2021 to May 2022. The study included the quality and quantity of phytoplankton, moreover, the highest and lowest value of the physical and chemical parameters were (Water temperature (13-30 °C), Light penetration (94-275cm), electric conductivity (837-1128 µS/cm), salinity (0.5-0.7 ‰), pH (7-8.2), total alkalinity (126-226 mg CaCO3/L), total Hardness (297-395 mg CaCO3/L

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, S

Background: coronavirus 19 is a beta-coronavirus, enveloped and roughly spherical with approximately 60 to 140 nm in diameter with positive-sense single-stranded RNA genome.

Objectives: Measurement of interleukin 6 (IL6) level in a group of patients with confirmed Covid19 infection and its correlation with many hematological and  biochemical parameters , mainly lymphocyte , neutrophil  count and their ratio , platelet count , serum ferritin , C reactive protein as well as D-dimer level

Subjects and Methods: This study was conducted on 60 PCR positive patients variably affected by COVID-19 , cases collected sequentially from June till November 20

BACKGROUND: Hepatocyte growth factor (HGF) is a proangiogenic factor that exerts different effects over stem cell survival growth, apoptosis, and adhesion. Its impact on leukemogenesis has been established by many studies. AIM: This study aimed to determine the effect of plasma HGF activity on acute myeloid leukemia (AML) patients at presentation and after remission. PATIENTS AND METHODS: This was a cross-sectional prospective study of 30 newly-diagnosed, adult, and AML patients. All patients received the 7+3 treatment protocol. Patients’ clinical data were taken at presentation, and patients were followed up for 6 months to evaluate the clinical status. Plasma HGF levels were estimated by ELISA based methods in the pa

Abstract

  The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable.                                                                                  &nb