This work focused on anthropogenic influences of the trace metals distribution in the soils of Kirkuk city. Sequential extraction technique was used to determine the distribution of the chemical fractions of Ag, Cd, Co, Cu, Ni, Pb, Zn, As, Cr and V in soil of Kirkuk city. This area is affected mainly by burning oil trash. Results show that these heavy metals were primarily restricted to surface horizons and mostly associated with the residual fraction (28.8 – 50%). The remnant fractions (13.8 – 33.1%) linked to the organic matter, 7.9 – 27.2% was bound to Fe-Mn oxide, 0.7 – 27.9 was bound to carbonate. Only a small amount of the total metals in the soil is exchangeable (0.5 – 4.2%) and water soluble (0 – 4.1%) fractions.

The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

                 The research deals with the concept of a New Urbanism as an urban development strategy in the suburbs of cities or in its centers that are affected by pedestrian-oriented design and the possibility of walking, as well as integrating economic classes through the diversity of housing and its costs, and this works to facilitate access to jobs and services while providing more diverse neighborhoods and reducing the use of cars , As designing separate houses in the suburbs and increasing car trips poses a threat to the environment and the quality of urban life, and thus the new urban provides a good strategy for developing

To assess the total hip replacement patients’ knowledge of home – care regarding pain management, medication therapy, wound care, mobility limitation and complications may occur in the post hip replacement surgery, and to assess relationship between some variables such as, age level of education, sex & marital status with home- care knowledge. A descriptive study was used to assess the hip-replacement patient home-knowledge, a purposive sampling of (60) hip-replaced –patients were selected from Gazy Alhariri Hospital  (central of surgical profession ) and Alwasity Hospital ( plastic surgery) , the questionnaire  obtains two parts , part one, which included socio-demographical characteristics of the samp

Objective: study aims to identify the diabetes type2 clients self management skills toward dietary pattern
, and find out the relationship between variables which are (Age, gender, educational level, duration of DM
diagnosis, and monthly income) with diabetes type 2 clients self management skills toward dietary pattern
Methodology: descriptive study was carried out through the present investigation from January 2nd
2011to September 2nd 2011 in order to achieve the objectives of the present study. A non probability
(purposive) sample, (200) cases which consists of clients who were attending Al-Nasiriyha diabetic center.
Including (118) males and (82) females. The data were collected by utilization of the study instrument

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Phlebotomus papatasi sand fly is the main vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Iraq. The aim of this study was to assess and predict the effects of climate change on the distribution of the cutaneous leishmaniasis (CL) cases and the main vector presently and in the future. Data of the CL cases were collected for the period (2000-2018) in addition to sand fly (SF) abundance. Geographic information system, R studio and MaxEnt (Maximum entropy niche model) software were used for analysis and predict effect of (elevation, population, Bio1-19, and Bio28-35) on CL cases distribution and SF occurrence. HadGEM2-ES model with two climate change scenarios, RCP 4.5 and RCP 8.5 were used for future projections 2050. The results showed th