Twelve storm dust samples were collected from three cities in Iraq. The samples were collected in the same time during big storms which hit Iraq in summer, 2012 and 2013.  The deposited dust on 4 by 4 nylon sheet on surfaces of selected buildings in cities of Baghdad, Fallujah and Al-Ramadi were collected. Each sample was put in sealed Marinilli beaker and kept for 4 weeks to reach the equilibrium state between radium and its short half-life daughters. Gamma spectrometry system based on HPGe was used for analysis of natural and artificial radionuclides in the dust. The activities of natural radionuclides were found to be ranged between 13-19 Bq/kg, 9-14 Bq/kg and 200-240 Bq/kg for Ra-226, Th-232 and K-40 respectively, while Cs-137 w

Research targeted availability of moral anxiety among secondary school students. The research sample consisted of 500 students from the (fifth grade secondary school) scientific and literary branches.
The researcher prepared a measure of moral anxiety which is in its final form of (36) items. The researcher analyzed the data statistically, significant results showed that the sample of the research they have a moral anxiety .
From these results the researcher came up with a number of recommendations and proposals.

Present research is aimed knowing of smart thinking for secondary schools' students. and discover statistically significant differences in Smart Thinking due to the couple variables of (Gender – Branch)
For the purpose of verification of the aims of the research, the researcher has prepared a smart thinking scale, the scale has been applied on sample of secondary schools' students for both Branches (Scientific & Literary One).It was contingent (500) student male and female were chosen stratified random method.
After data analyze the reached results: The Preparatory fourth grade students have smart thinking. Female smart thinking enjoy a much higher degree than males. and Scientific branch students enjoy thinking and much high

Background: Cancer is a lethal disease that results from a multifactorial process. Progression into carcinogenesis and an abnormal cell proliferation can occur due to the micro and macro environment as well as genetic mutations and modifications. In this review, cancer and the microbiota – mainly bacteria that inhabit the tumour tissue – have been discussed. The positive and negative impacts of the commensal bacteria on tumours being protective or carcinogenic agents, respectively, and their strategies have also been described. Methods: Related published articles written in English language were searched from Google Scholar, PubMed, Mendeley suggestions, as well as Google search using a combination of the keywords ‘Microbiota, commens

This study uses the performance of the discretionary estimation models by using a sample of listed companies in the Netherlands and Germany. The actual accounting framework provides a wide opportunity for managers to influence data in financial reporting. The corporate reporting strategy, the way managers use their discretionary accounting, has a significant effect on the company's financial reporting. The authors contribute to the literature through enhancement to these models to accomplish better effects of identifying earnings management as well as to present evidence that is particular to the Dutch and German setting.

For this, we followed the methodology of Dechow, Sloan, and Sweeney (1995) and Chan

A plastic tubes used as absorber of active flat plate solar collector (FPSC) for heating water were studied numerically and experimentally. The set-up is located in Babylon (republic of Iraq) 43.8⁰ East longitude and 32.3⁰ North latitude with titled of 45⁰ toward the south direction.  The study involved three dimensions mathematical model for flat coil plastic absorber which solved by FLUENT-ANSYS-R.18 program. Experiments were conducted at outdoor conditions for clear days on January and February 2018 with various water volume flow rates namely (500, 750, 1000, 1250, and 1500 Liter per hour LPH) on each month for Reynolds number range of (1 x 10⁴ to 5 x 10⁴) th

Non thermal argon plasma needle at atmospheric pressure was constructed. The experimental set up was based on simple and low cost electric components that generate electrical field sufficiently high at the electrodes to ionize various gases which flow at atmospheric pressure. A high AC power supply was used with 9.6kV peak to peak and 33kHz frequency. The plasma was generated using two electrodes. The voltage and current discharge waveform were measured. The temperature of Ar gas plasma jet at different gas flow rate and distances from the plasma electrode was also recorded. It was found that the temperature increased with increasing frequency to reach the maximum value at 15 kHz, and that the current leading the voltage, which demonstra

This search study the effect of particle size of graphite on the mechanical and thermal properties of epoxy composites, where graphite adopted with particle sizes (45,53,75) ?m, respectively, and the percentages by weight (0,1,3,5,7,9)% for each size of this three particle sizes.Mechanical properties represented by the bending (three-point bending) and through which the conclusion is bending stress and modulus of elasticity, thermal properties were either through thermal conductivity tests.The results showed that the ratio(1%) is the maximum value of bending stress at the three particle size and the (45 ?m) is the maximum.Thermal conductivity result show is the maximum value at ratio (1%) of particle size(53 ?m)

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea