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

Background : Gastroesophageal reflux disease (GERD) is one of chronic gastrointestinal diseases in which patient may be asymptomatic or was complained from heartburn and regurgitation or pulmonary symptoms. Aim of the study : Examine the serum level of sHLA-G in GERD patients and can be used as a biomarker for early detection of GERD disease. Materials and methods : The design of the study was a case- control prospective enrolled forty patients consulted Gastroenterology Unit- Al-Kindy Teaching Hospital, were diagnosed as GERD by their physician, and compared to second forty control healthy group form January-2023 to May-2024. Serum used for quantitative assessment of soluble HLA-G (sHLA-G) using a sandwich enzyme-linked immunosorbent a

Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as

The rapid and uncontrolled expansion of urban sprawl in Baghdad, particularly after 2003, has significantly transformed the city's landscape. This expansion stems from socio-political instability, a lack of affordable housing, and inadequate urban planning frameworks. As informal settlements encroach on agricultural lands, the city's infrastructure—including water, sanitation, and transportation systems—faces mounting pressure. This situation presents critical challenges to the sustainability of Baghdad’s public services and the quality of life for its residents. This study aims to evaluate the impact of unregulated urban sprawl on Baghdad’s public services and infrastructure, focusing on how informal growth has undermined the city'

The study aims to determine the concentrations of radon, humidity, and CO2 in residences within the Mitham Al-Tammar neighbourhood of Kufa, utilising an Airthings 2960 Wave Plus device in the living rooms of each household. The concentration of radon varied, with a minimum value of 13 ± 3.9 Bq/m³ and a maximum value of 90 ± 5.8 Bq/m³, yielding an average rate of 35.8 ± 4.889 Bq/m³. The concentrations of total VOCs in residences ranged from 69.26 ppb to 810.14 ppb, with a mean of 321.4855 ± 40.4. The humidity percentages exhibited a minimum concentration of 51.68% and a maximum of 122.97%, averaging 76.594 ± 4.298. The concentrations of volatile organic compounds and

The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems' variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.