Kirkuk Journal of Science

Natural stones are widely used for paving, crushing, building, and dimensioning purposes worldwide. There are plenty of natural stone resources in the Sulaimaniyah governorate of north-eastern Iraq that can be used for a range of architectural and ornamental purposes. The aim of this study is to evaluate the suitability of dolomitic limestone from the Serki and Sehkaniyan formations for use as dimension stone based on their physical and mechanical properties. In this study, 21 samples of the Serki and Sehkaniyan dolomitic limestone rock were collected in outcropped rock units within the quarry sites. The physical testing of rocks includes assessments of total porosity, water absorption, saturation coefficient, apparent specific gravity, and bulk density. Based on Iraqi standard specification 1989, 1387 and American standards 2004, C568, all tested characteristics were classified as having very high density, and the rock units were frost-resistant. The uniaxial compressive strength (UCS) of the rock samples indicated a strength range of 60 to 80 MPa, these values are higher than the strength in the parallel orientation tested samples which are 43 to 56 MPa. Based on different classifications and standards, the majority of the tested samples were rated as strong to very strong, while only a few were considered moderately strong. Notably, there are significant relation between the UCS values and the physical parameters of the rock units, also strong relation with the point load index were observed in both perpendicular and parallel testing modes, yielding R² values of 0.85 and 0.76, respectively. Excavatability assessment shows most samples need hard ripping or blasting due to high strength and wide fractures. Standard excavation tools may not be effective for these rocks. The results reveal that the Serki and Sehkaniyan formations examined are of high quality and suitable for use as dimension stone for both exterior and interior applications, as well as for paving and construction materials.

Fractional-order differential equations are fundamental in diverse
scientific and engineering fields, including population dynamics, optimal
control, and physics. This paper presents a non-polynomial spline
method for their numerical solution, establishing a linear system of
algebraic equations in the representation of three-term recurrence
equations, which is solved using an elimination algorithm. The maximum
error estimations and the order of convergence for each example
demonstrate the success and core contribution of the method and
its performance is demonstrated through numerical and graphical
examples. There is a thorough explanation of a mathematical procedure
provided, as well as graphical and numerical examples solution for
several examples. Results confirm that the proposed approach achieves
superior accuracy and reliability compared to existing techniques.

This simulation work, based on the design of an 850 nm InGaAs/AlGaAs quantum well (QWs) vertical cavity surface emitting laser (VCSEL), presents significant challenges, particularly due to the limitations of device bandwidth at higher temperatures. We propose a comprehensive modelling approach to optimize the dynamic performance of a VCSEL structure with an oxide aperture diameter of 6 µm, specifically to achieve higher bandwidth at lower bias currents. The MATLAB simulation evaluates the variation of critical parameters, such as threshold current, differential efficiency, output power, and small-signal modulation, across a wide operating temperature range. Our findings indicate that in static analysis, the threshold current exhibits a positive temperature dependence, increasing with rising temperature, while both differential efficiency and optical output power decrease. Dynamic analysis reveals that although the 3-dB modulation bandwidth reduces with temperature, the VCSEL maintains high-speed performance exceeding 36 GHz at 20 °C and 24 GHz at 120 °C under a bias current of 14 mA. The temperature dependence of the modulation current efficiency factor (MCEF) provides insight into optimizing VCSEL structures for reliable high-speed operation over broad thermal conditions.

Sixty samples were taken from the covers and displays of phones,
and 2 samples from the headphones of biology students in the College
of Science, Salahaddin University. Fungal genera were diagnosed
phenotypically based on the color and shape of the colony from the
front and reverse sides in the Petri dish, and diagnosed microscopically.
Twenty-one fungal genera belonging to 29 species were isolated. The
highest genera of fungal isolates were Aspergillus spp. Four new
genera, Kutilakesopsis sp., Myrothecium verrucaria, and Thanatephorus
Cucumis, and two new species, Dreschlera bisepta and Tritrachium
oryzae, were recorded for the first time from mobile phones of biology
students in the College of Science, Salahaddin University-Erbil. In
addition, yeast was identified on CHROM Agar based on the formation
of a colony color, such as Candida albicans, C. glabrata, and C.
parapsilosis. The sensitivity test by the Agar Well Diffusion Method
was performed for six species of Aspergillus against four sterilized
agents: Dettol, Ethanol (%70%), Sanitizer, and Wet wipes on Sabouraud
Dextrose Agar (SDA). Compared to the control, Aspergillus species
were shown to be fairly sensitive to each of the tested sterilizing agents
based on the zone of inhibition of growth, except that the sanitizer was
resistant to all species of Aspergillus. This means it is necessary to
sterilize a phone with sterilizing agents, as it can be a source of disease
transmission.

This study focuses on the Fredholm integro-differential equations and is frequently found in areas of applied mathematics, physics, and engineering fields. To address these systems and obtain exact of solutions under suitable conditions, we propose a novel analytical approach. We choose the Haar wavelet colocation method for processing due to its simplicity, effectiveness, and ability to handle non-smooth solutions. The integral terms in these equations are determined using the trapezoidal rule, which effectively strikes a balance between accuracy and computational efficiency. These results are compared with analytical solutions. The comparisons show that the suggested strategy yields highly accurate results and offers a solid framework for solving the Fredholm integro-differential equations.

Toll-like receptors (TLRs) are essential to initiate an immune
response to ward an infection. The current study sought to examine
the correlation between Single Nucleotide Polymorphisms (SNPs) and
the expression of the TLR4 gene (896A/G) concerning the risk and
prognosis of acute leukemia in Erbil Province, as well as to evaluate the
influence of bacterial infections on serum TLR4 levels and associated
gene polymorphisms in patients diagnosed with acute leukemia.
Serum TLR4 levels were markedly elevated in patients with acute
leukemia, particularly in those with ALL. Post-treatment study revealed
a substantial reduction in TLR4 levels in AML; however, the decrease
was not statistically significant in ALL. Additionally, bacterial infection
before and after chemotherapy exhibited no significant correlation with
TLR4 expression. Gene polymorphism analysis indicated no significant
connection between the TLR4 (A/G) genotype allele and leukemia
risk. Serum levels of TLR4 were elevated in acute leukemia patients,
particularly in ALL, and diminished following treatment in AML. The
infection state exhibited negligible impact, and no substantial correlation
was identified between TLR4, genotypes, and disease risk, but the A
allele may merit additional investigation.

In this paper, we analyze sales data for two selected items from
a supermarket and apply polynomial regression models to uncover
insights into their sales trends. By fitting a polynomial curve to the data,
we aim to understand how such pricing affects the number of sales
of these items. This analysis compares the effectiveness of various
regression models in predicting the price of products in different contexts.
The linear regression model is the most effective for predicting the price
of tomato paste, as it gives the data a better fit, with almost identical
MSE and SEE, indicating similar prediction accuracy and errors. The
linear regression model is the most effective for predicting the dependent
variable, which is the number of sales (tomato paste) items, highlighting
that the price of the item (independent variable) is statistically significant
and provides a clear relationship with the dependent variable. In the
context of sales, the number of oil items as the dependent variable
prediction, the quadratic model is the most effective for explaining the
price of oil items with both independent variables (price of power one
and price of power two) being statistically significant, suggesting that the
quadratic model best captures the connection between the two variables.