A large number of researchers had attempted to identify the pattern of the functional relationship between fertility from a side and economic and social characteristics of the population from another, with the strength of effect of each. So, this research aims to monitor and analyze changes in the level of fertility temporally and spatially in recent decades, in addition to estimating fertility levels in Iraq for the period (1977-2011) and then make forecasting to the level of fertility in Iraq at the national level (except for the Kurdistan region), and for the period of (2012-2031). To achieve this goal has been the use of the Lee-Carter model to estimate fertility rates and predictable as well. As this is the form often has been familiar

The neutron, proton, and matter densities of the ground state of the proton-rich ²³Al and ²⁷P exotic nuclei were analyzed using the binary cluster model (BCM). Two density parameterizations were used in BCM calculations namely; Gaussian (GS) and harmonic oscillator (HO) parameterizations. According to the calculated results, it found that the BCM gives a good description of the nuclear structure for above proton-rich exotic nuclei. The elastic form factors of the unstable ²³Al and ²⁷P exotic nuclei and those of their stable isotopes ²⁷Al and ³¹P are studied by the plane-wave Born approximation. The main difference between the elastic form factors of unstable nuclei and the

Fiscal policy is one of the important economic tools that affect economic development in general and human development in particular through its tools (public revenues, public expenditures, and the general budget).

It was hoped that the effects of fiscal policy during the study period (2004-2007) will positively reflect on human development indicators (health, education, income) by raising these indicators on the ground. After 2003, public revenues in Iraq increased due to increased revenues. However, despite this increase in public budgets, the actual impact on human development and its indicators was not equivalent to this increase in financial revenues. QR The value of the general budget allocations ha

It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

The catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor

using  active  carbon  prepared  from  date  stones  as  catalyst  by  ferric  and  zinc  chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account