Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

While traditional energy sources such as oil, coal, and natural gas drive economic growth, they also seriously affect people’s health and the environment. Renewable energies (RE) are presently seen as an efficient choice for attaining long-term sustainability in development. They provide an adequate response to climate change and supply sufficient electricity. The current situation in Iraq results from a decades-long scarcity of reliable electricity, which has impacted various industries, including agriculture. There are diverse prospects for using renewable energy sources to address the present power crisis. The economic and environmental impacts of renewable energy systems were investigated in this study by using the solar pumpi

Objective: To determine the effect of instructional program on infertile women's knowledge regarding
diagnostic and therapeutic intervention for infertility.
Methodology: Non-probability (purposive sample) of (100) infertile women, who visit Kamal Al-Samaraee Hospital/
fertility and IVF center. The data are collected through the use of constructed questionnaire, which included:
demographic characteristics, social status, previous medical history, reproductive status, sexual status and questions
regarding women’s knowledge about infertility. Instrument validity and reliability was determined. Data were
collected through the use of questionnaire, the application of the instructional program was done for the study group<

Forest cover in Mosul Province experienced significant changes following the 2014 occupation. These changes can be effectively analyzed using multitemporal remote sensing imagery. This study aims to evaluate the ability of multi-temporal Landsat 8 images and the Forest Canopy Density (FCD) model to detect changes in forest canopy density in a protected forest in Mosul Governorate during the period from 2014 to 2025. The remote sensing data used in this research are Landsat 8 images captured on March 21, 2014, and April 4, 2025. The method employed is FCD modeling, which produces pixel-level canopy density estimates. The results of the FCD model are then used to analyze changes in canopy density following the occupation. The findings of this

Blends of polyvinyl pyrrolidone (PVP) and polyvinyl alcohol (PVA) in equal weight ratios (50 wt.% PVP + 50 wt.% PVA) were doped with 15% of various lithium salts (Li2CO3, LiNO3, Li2SO4H2O, and LiCl) and prepared using the solution-casting method, with dimethylformamide (DMF) as the solvent. The impact of these salts on the blends was analyzed and the results showed that the energy gap was decreased by adding lithium salts Li2CO3, LiNO3 and Li2SO4.H₂O. The minimum energy gap value was 3.5 eV obtained from PVP/PVA:15% Li2CO3. The optical constants were determined in the range of 300-1100 nm. The results showed that all the optical constants for doped blends were grown with the addition of lithium salts. The FTIR study confirms the c