Basrah Journal of Science

An (????,3)-arc ???? in projective plane ????????(2,????) of size ???? and degree three
is a set of n points such that every line in the plane meet it in less than
or equal three points, also the arc ???? is complete if it is not contained
in (????+1,3)-arc. In this paper, the classification of degree three arcs in
�
�????(2,19) is introduced in details according to their stabilizer groups.
The motivation for working in the projective plane of order 19 is
twofold. First, the size of the largest (????,3)-arc is not known. Second,
the number of (????,3)-arcs is significantly higher in the projective plane
of order 19 than it is in the projective plane of order ???? for ????<19,
giving a large number of (????,3)-arcs for the study.

This study examines the three-way repeated measurements model and
looks at the model's ANOVA. The test statistic for the hypothesis
corresponding to each model factor is defined, as is the distribution of
a sum of squares statistics. The chi-square transformation of the sum
of squares distribution was used to determine the confidence interval
for the variance of components. The application of the repeated
measurements model to an experiment is the study's practical
component.

The aim of this work is to solve the fractional order T. Regge problem
by applying a unique transformation technique called the Kamal
transform. It focuses mostly on the application of Kamal's
transformation methodology to the solution of fractional differential
equations (FDEs), especially with regard to the boundary value
fractional order T. Regge problem. Furthermore, Kamal transformation
formulas for fractional derivatives and fractional integrals are derived,
the benefits and drawbacks of the methodology are examined, and
multiple instances are shown to demonstrate the practicality of the
technique. As seen by the examples we presented, the Kamal
transformation methodology provides guaranteed solutions for FDEs,
which have a substantial impact on the field of fractional computation

This study aims to explore the application of the Rishi transform to
population growth and decay problems, which are pivotal in various
fields such as finance, physical science, chemistry, biology, and
sociology. The primary objectives are to demonstrate the effectiveness
of the Rishi transform in solving these problems and to provide several
practical applications that highlight its value and utility. The results
confirm the Rishi transform’s capability and usefulness in addressing
population growth and decay issues.

Cybersecurity has become an important priority requiring immediate
response. Threats have become a commonplace phenomenon. This
paper will examine malware, a kind of cybersecurity encompassing
harmful software that expropriates data and jeopardizes privacy and
security. We will elucidate the application of malware analysis and
machine learning methodologies for detection. Currently, fraudsters
employ polymorphic malware that utilizes strategies challenging for
conventional detection technologies to identify. Therefore, this study
will utilize a survey on machine learning algorithms that facilitate the
detection of different malware types while ensuring optimal detection
performance and accuracy.

This study discusses the development of embedded systems for plant
monitoring and irrigation systems utilizing Internet of Things (IoT)
within MATLAB environments. The IoT paradigm is designed to
connect devices via the Internet and facilitate user access to data. This
model can accurately observe environmental data in agricultural areas
and subsequently provide comparable data to the user. The model
monitors various characteristics, including temperature, humidity, and
light intensity. The infrared sensors are employed to detect the entry of
external objects into the fields; in the event of an intruder detection,
buzzers will activate for a few seconds. The motor operates in both
manual and automatic modes, contingent upon moisture sensors. The
motor is regularly alternated between the ON and OFF phases of pump
operations. The outcome is observed in web applications and
monitoring systems. The water plant processing is often conducted
manually, based on the desired water quantities for the plant. Our study
discusses automatic prototypes and systems designed for plant
irrigation based on moisture levels. This study offers a more secure
application with greater user accessibility compared to existing
solutions.

Cybersecurity is an essential topic, as most of our daily activities are
controlled by web applications. These applications become susceptible
to various threats that lead to unauthorized access to personal data.
Therefore, protecting application data has become essential.
Supervised machine learning is widely utilized in various applications,
such as spam detection; it functions as a powerful tool for automating
decision-making and producing predictions based on historical data.
This study employs supervised machine learning to classify anomalies
in a network using the NSL-KDD dataset, which is utilized to assess
intrusion detection techniques. This dataset contains no repeated items
in the training subset, making the approach impartial to any particular
items. This research utilizes approaches such as CNN, LSTM, hybrid
CNN-LSTM, RBFN, MLP, and SVM. Evaluating multiple algorithms
and analyzing their results to select the most efficient option is
typically a wise strategy. The results of the implemented models were
evaluated and compared based on detection rate, time efficiency, and
accuracy. The findings demonstrate that the CNN-LSTM hybrid model
exceeded the benchmark methods, with a detection rate of 99.61% and
an accuracy of 99.8%.

This study examined many nuclear characteristics, including the
composition, forms, and methods for altering the shapes of radioactive
radium isotope nuclei based on the deformation parameters associated
with these isotopes. The radii and deformation characteristics of these
nuclei were also analyzed. The nuclear properties of radium require
examination due to its common presence in the environment and its
classification as an alpha emitter. Radium is a threat to natural
ecosystems. The MATLAB software served as the operational tool for
acquiring the results, in which several equations were executed to yield
the desired outcomes. The results indicate that at mass number 230, β
and δ get their peak values of 0.2692 and 0.2702, respectively, whilst
at mass number 212, they achieve their lowest values of 0.0882 and
0.0704. Upon meticulous investigation, it was evident that there
existed only a minor discrepancy between the experimental and
acquired results, although the substantial differences in the outcomes.
The nuclei exhibit spherical or nearly spherical structures and forms
due of their elevated deformation parameters and near to the magic
numbers. Consequently, their forms are inherently elliptical.

This article examined the differential cross-section and the integral
cross-section (DCS & ICS) for NFx molecules (where x: 1, 2, 3). The
molecules underwent electron collisions (elastic scattering) within a
defined energy range. A theoretical model has been employed to
compute DCS and ICS at specific energies ranging from 1.5 eV to 100
eV. Overall, our DCS findings consistently aligned with measurements
from other researchers; however, theoretical investigations on these
compounds were limited.

The work describes the synthesis, characterization, and assessment of the
biological activity of two novel Schiff bases, PHMP and BPHMP. The
condensation
process
between hydralazine hydrochloride and
terephthalaldehyde, facilitated by p-toluenesulfonic acid as a catalyst,
resulted in their production. The compounds were studied by spectroscopic
techniques, including FTIR, proton nuclear magnetic resonance (1H-NMR),
carbon-13 nuclear magnetic resonance (13C-NMR), and mass spectrometry.
The antibacterial and antifungal efficacy of the Schiff base compounds
assessed against the bacteria S. aureus and E. coli, as well as the fungus C.
albicans and A. niger, yielded varying outcomes in comparison to
hydralazine hydrochloride as the standard drugs.

This study examined adropin, oxidative stress, and antioxidants in
osteoarthritis patients and a control group, as well as the relationship
between adropin and these factors. To achieve this goal, we collected
150 samples from 30–65-year-old men and women. Osteoarthritis
affected 92 people. Patients were classified by disease severity: mild,
moderate, or severe. The control group of 58 people is used for
comparison. Quantified were adropin, glutathione (GSH), uric acid
(UA), and MDA. Results show significant Adropin reduction
(p≤0.0001) in osteoarthritis patients (282 ± 158.6 ng/L) compared to
the control group (433.5 ± 119.7 ng/L). Adropin significantly reduced
severe osteoarthritis (111±24.8 ng/L) compared to moderate
(336.3±99.1 ng/L) and mild (410.3±108.4 ng/L) instances compared to
the control group (p≤0.0001). Adropin and GSH are positively
correlated in severe (r=0.446, p=0.004) and moderate (r=0.519,
p=0.0013) cases. Adropin is negatively correlated with MDA in mild
(r=-0.493, p=0.031) and severe (r=-0.542, p=0.001) instances. Adropin
negatively correlates with uric acid in moderate (r=-0.525, p=0.012)
and severe (r=-0.467, p=0.002) cases. This study supports the use of
adropin to diagnose and track osteoarthritis. We also find a link
between adropin and oxidative stress, suggesting it contributes to
disease progression.

Cancer is a significant human affliction, and hematological health is a
major issue. Leukemia cannot be effectively cured, even advancements
in treatment options. The B-cell lymphoma (BCL2) gene is crucial for
the diagnosis and treatment of leukemia, particularly in understanding
the BCL2 protein's significant regulatory role in apoptosis. This study
was conducted at Nanakaly Cancer Hospital in Arbil, Iraq, from
January 1, 2022, to June 30, 2022, utilizing cancer patient data
spanning from 2010 to 2022. Five milliliters of blood samples were
obtained from cancer patients and healthy individuals for molecular
detection. RNA was extracted from blood, followed by the synthesis
of cDNA. The quantification of cDNA was performed using a
Nanodrop spectrophotometer, and subsequently, PCR was employed
to analyze the BCL2 gene. BCL2 protein levels were significantly
diminished in the regulatory molecular tissues of a hematological
malignancy cell. There is no observable difference in expression level.
Our data indicated that reduced BCL2 expression correlates with
significant clinical characteristics, including tumor grade, stage, and
type of blood cancer. We found that BCL2 is linked to leukemia and
may be a biomarker for hematologic malignancies.