The aim of this research is analysis the effect of the changes in (GDA, g, inflation) at average and standard economic curriculum in composition of the models, depending on SPSS program in analysis, and according to available date from central bank of Iraq and during the period from 2003 to 2018 and by using OLS and estimate of the equation and the results showed a statistical significance relation in incorporeal level 5% and the R² value equal  to 92.1 refer to the changes in independent variables explain 92% of changes of unemployment and the independent variables effect are very limit depend on estimated parameters in the model and respectively (0.986,0.229,-0.060), the research recommended necessity to active the inve

This study was conducted to evaluate the efficacy of Saccharomyces cerevesiae as a growth promoting agent in tomato. Soaking the seeds in yeast suspension at 5 g/L for 12h increased germination percentage, root length, root fresh and dry weight, plant height, foliage fresh and dry weight, attained 88.5% ; 8.1 cm ; 84.3 mg ; 7.03 mg ; 10.75 cm ; 839 mg and 37.75 mg compared with 80% ; 5.33 cm ; 39 mg ; 4.8 mg ; 7.35 cm ; 608 mg and 25.5 mg in seedlings grown from non treated seeds respectively. Similar results were obtained with seedling from seeds soaked in S. cerevesiae filtrate for 12 hrs. with values of 77.5% ; 6.875 cm ; 91.5 mg ; 7.5 mg ; 9.5 cm ; 777 mg and 40.35 mg compared to 66% ; 5.8 cm ; 57.7 mg ; 5.03 mg ; 5.9 cm ; 493 mg

Clinical index is needed to predict the outcome of pregnancy after in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET) for infertile patients. Growth differentiation factor-8 (GDF-8), also known as myostatin, is one of transforming growth factor-â superfamily localized in antral follicles in normal and PCOS ovaries but its function in female reproductive system is still unknown. Aim of the study is to assess the correlation between levels of GDF8 in follicular fluid (FF) with outcomes of in vitro fertilization (IVF/ICSI) in women with and without PCOS. A prospective case control study was performed enrolling (40) patients with PCOS and (40) non-PCOS women (male infertility) undergoing IVF/ICSI. The collect

In the present study, thin films of organic semiconductors Nickel PhthalocyanineTetrasulfonic Acid Tetrasodium Salt (NiPcTs) and inorganic semiconductor (CdS) prepared from the mixing of liquids for thesetwomaterials with different size ratios by the spin coating method on pre-patterned (Fluorine-doped Tin Oxide) FTO coated glass substrates and then the manufacture of solar cells. The properties of solar cells the study through the optical properties (absorption spectra, absorption coefficient, power gap) and electrical characteristics (continuous onductivity, Hall Effect and cell efficiency measurements) and Was obtainedThe efficiency of a multiple solar cell ranging from (0.16-13.2 %)

Low-level microbial activity due to the production of organic acids is a recognized problem during the initial phase of food waste composting. Increasing such activity levels by adjusting the pH values during the initial composting phase is the primary objective to be investigated. In this study, sodium acetate (NaoAc) was introduced as an amendment to an in-vessel composting system. NaoAc was added when the pH of the compost mixture reached a low level (pH < 5), the addition increased pH to 5.8. This had a positive effect on the degradation of organic materials i.e. the formation of methane gas compared to the results without NaoAc addition.

The results also proved that anaerobic-aerobic in-vessel composting could reduce the

     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

Light is an important factor that influences the growth and photosynthetic efficiency of microalgae; however, little is known about how light intensity together with the wavelength affect the photosynthetic capacity and growth of marine microalgae. In the present study, the growth of the marine green microalga Dunaliella parva was studied and optimized under different light intensities (25 ~ 70 μmol m^-2 s^-1) and qualities (blue, green, and red) in comparison with white light at 40 μmol m^-2 s^-1 as a control. The growth was monitored by counting the cell number, pigment content, Chl a, Chl b, and carotenoids concentrations. The optimal growth and highest photosyntheti