Urban land uses are in a dynamic state that varies over time, the city of Karbala in Iraq has experienced functional changes over the past 100 years, as the city is characterized by the presence of significant tourist and socio-economic activity represented by religious tourism, and it occur due to various reasons such as urbanization. The purpose of this study is to apply a Markov model to analyze and predict the behavior of transforming the use of land in Karbala city over time. This can include the conversion of agricultural land, or other areas into residential, commercial, industrial land uses. The process of urbanization is typically driven by population growth, economic development, based on a set of probabilities and transitions bet

The thermal properties (thermal transfer and thermal expansion coefficient) of the enhanced epoxy resin (MWCNT / x-TiO₂) were studied by weight ratios with the values (0%, 3%, 5%, 7% and 10%) and a constant ratio of 3% of MWCNT. The ultrasonic technology was used to prepare the neat and composites which were then poured into Teflon molds according to standard conditions. Thermo-analyzer sensor technology was used to measure thermal transfer (thermal conductivity, thermal flow, thermal diffusion, thermal energy and heat resistance). The thermal conductivity, flow, and thermal conductivity values were increased sequentially by increasing the weight ratio of the filler while the results of stored energy values an

A new Mannich base ligand was prepared by reacting the 2-chloro.-N-(5-mercapto-1, 3, 4-thiadazol -2-yl) acetamide and Piperidine in the presence (formaldehyde) (L) ligand. A series of ligand complexes were prepared from (L) with the metal ion Co (II), Ni (II), Cu (II), Pd (II), Pt (IV), and Au (III). Various spectroscopic techniques such as C.H.N.S, FTIR, UV-VIS, , 1HNMR, 13CNMR, Magnetic moment, and molar conductivity successfully characterize the obtained compounds. The M: L ratio was determined using the molar ratio method in solution. All prepared compounds' antibacterial and antifungal activity was studied against two types of bacteria and one type of fungi at a rate of 0.02M. The standard ΔH° f and ΔEb of the ligands an

This search study the effect of particle size of graphite on the mechanical and thermal properties of epoxy composites, where graphite adopted with particle sizes (45,53,75) ?m, respectively, and the percentages by weight (0,1,3,5,7,9)% for each size of this three particle sizes.Mechanical properties represented by the bending (three-point bending) and through which the conclusion is bending stress and modulus of elasticity, thermal properties were either through thermal conductivity tests.The results showed that the ratio(1%) is the maximum value of bending stress at the three particle size and the (45 ?m) is the maximum.Thermal conductivity result show is the maximum value at ratio (1%) of particle size(53 ?m)

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

The design of coordination compounds with solvent-responsive optical properties remains a central challenge in molecular photonics. Here, we describe the synthesis and full characterisation of a symmetrical tetradentate diamine ligand, 3,3′-((1,2-phenylenebis(azanediyl))- bis(methanylylidene))bis(pentane-2,4-dione) (H₂L), and its neutral square-planar complexes [M(L)] (M(II) = Co, Ni, Cu). The Cu(II) complex crystallised as [Cu(L)]⋅0.5 (pyrazine), adopting a nearly square-planar geometry (τ₄ = 0.06) in the solid state, as confirmed by single-crystal X-ray diffraction. In DMSO solution, UV–Vis spectra revealed reversible axial coordination of two solvent molecules, driving a transformation to a distorted octahedral geometry. Struc

Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one

In the present work a modification was made on three equations to represent the
experiment data which results for Iraqi petroleum and natural asphalt. The equations
have been developed for estimating the chemical composition and physical properties
of asphalt cement at different temperature and aging time. The standard deviations of
all equations were calculated.
The modified correlation related to the aging time and temperature with penetration
index and durability index of aged petroleum and natural asphalts were developed.
The first equation represents the relationship between the durability index with aging
time and temperature.

log_e(DI)=a₁+0.0123(2log_e T

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c