A field experiment was conducted in Al-Yusufiya district - Al-Mahmoudiya district, Baghdad province during the winter season 2021, to study improving the efficiency and management of water use and the productivity of lettuce under different irrigation systems. The Nested-Factorial Experiments design was used, where the main plots include the first factor, irrigation levels (I1) 50%, (I2) 75%, (I3) 100, (I4) 125%, (I5) 150% ETpan. After depleting 35% of the available water and in terms of climatic data from the American Evaporative Basin, Class A. Then the main factor is divided into three replicates, and the coefficients of the second factor are distributed randomly within each replicate, which includes the irrigation system: surface drip i

The agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO₂ concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1

     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

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

PM3 and Unrestricted Hartree Fock (UHF) quantum mechanical methods are carried out for the estimation of reaction path for the breakage of (R-O) bond rupture energies, for twelve ampicillin ester prodrugs derivatives, at their calculated equilibrium geometries, in addition to some physical properties such as heat of formation, total energy, dipole moment and the energy difference of EHOMO and ELUMO (ΔEHOMO-LUMO) energy levels, using the Gaussian-03 program. Comparisons were done between the total energies of the reactants, products, activation energies and transition states. The results show non possible use of some substituted organic groups as a carrier linkage for acidic ampicillin drug, whereas others show possible use as a carrier

      Quantum mechanical computations is conducted using DFT (Density Functional Theory) and PM3 (Parameterized Model 3), also, using DFT of (B3LYP) with a 6-311++G (d, p) with G09 application. These molecular three components include structure, electronic charge density and energetic characteristics of chosen phytomedicine compounds. The impact of functional groups on physical characteristics were studied using myricetin, linebacker, and flavone because of their chemical structures. For phytomedicine compounds, we utilized quantum mechanical simulations to estimate bond length, energy, vibration(vib.) modes, charge density and mechanical properties (cruelty, strength, stiffness, for the measurements of the lengths and energy of the