Iraqi Journal of Science

In people with a hereditary predisposition, gluten consumption causes celiac
disease, a multifactorial autoimmune condition. The ensuing small intestine
inflammatory process develops specific antibodies and causes various gastrointestinal
and extra-intestinal symptoms with varying degrees of severity. Evaluation of the
blood iron profile at various histological celiac disease severity in Iraqi patients was
the goal of the current study. Seventy-five Iraqi patients with celiac disease, with a
mean age of 18.68± 11.13 years, were the study's participants. These people tested
positive for celiac antibodies and experienced gastrointestinal symptoms. Based on
the disease histological severity, they were divided into two groups: marsh (III a, b,
c) group and marsh (0, I) group. For comparison purposes, 46 people who appeared
to be in good health and matched in age and gender to the patients utilized in the study
were also included. The levels of iron, transferrin, hemoglobin, ferritin, total iron
binding capacity, unsaturated iron binding capacity, and the percentage of transferrin
that is saturated with iron were all measured. In comparison to the other patient groups
under study, celiac patients (marsh III) group, and particularly those of group (marsh
III c), showed a substantial drop (p<0.05) in iron, the percentage of transferrin
saturating with iron, the levels of each ferritin and of hemoglobin. The total iron
binding capacity and the unsaturated iron binding capacity showed a significant
elevation (p<0.05) in (marsh III c) patients’ group, meanwhile non-significant
differences (p> 0.05) were found in transferrin concentration. Moreover, significant
differences (p< 0.05) were obtained in the iron profile between celiac patients who
followed strict gluten free diet and those patients with gluten contained diet.

Thalassemia is a genetic disease identified by a defect in the production of one or
more globin chains. This study was aimed at determining the possibility of using
"serum kidney injury molecule-1 (KIM-1)" and "N-acetyl-β-D-glucosaminidase
(NAG)" in the diagnosis of early renal damage in thalassemia patients. Serum
biomarkers (CBC, urea, creatinine, KIM-1, and NAG) were determined in 45 patients
with major thalassemia with an age range of 4-45 years who attended Baquba General
Hospital. A significant increase in S.KIM-1 and S.NAG levels in patients compared
with controls. The level of KIM was positively correlated with that of urea and
creatinine in comparison with control. Also, the level of NAG was strongly positively
correlated with the level of KIM-1 (p = 0.000) and had a moderately positive
correlation with urea and creatinine (p = 0.000). According to ROC, KIM-1 had a
sensitivity of 95.56% and a specificity of 88.89%, while NAG had a sensitivity of
100% and a specificity of 75.6%. This study concluded that S.KIM-1 and S.NAG are
highly promising biomarkers for the detection of "acute kidney injury" in an early
stage before elevated urea and creatinine in thalassemia patients.

The consumption of synthetic, non-biodegradable polymer plastics has drawn
attention to growing environmental concerns, prompting the development of other
materials, particularly bio-based materials. Biopolymer-based biocomposite materials
are plasticized to improve their ductility. In this study, five distinct weight ratios of
biopolymers (PA/EOO), 90 wt.%, 80 wt.%, 70 wt.%, 60 wt.%, and 50 wt.% were
employed as plasticizers for poly-lactic acid (PA) in a fluid molding process. The
mechanical, thermal stability, and morphological characteristics of the blends were
each examined using a viscometer measurement (R.V.), tensile properties (TP), a
scanning electron microscope (SEM), and a thermogravimetric analyzer (TGA). All
composite materials (PA/EOO) mixtures show notable improvements in mechanical
properties and excellent thermal stability when compared to pure PA. The maximum
PA/EOO elongation at break was around 213 % when the PA/EOO mix was 80 wt %.
Attractive morphological results from composite materials (PA/EOO) blends showed
that EOO was compatible with PA and that the resulting composite material
(PA/EOO) was thought to be an ecologically beneficial mixture because it contained
vegetable oil.

In this work, biosynthesized nanoparticles (Cr2O3) NPs were extracted by licorice
root and proven by AFM technique to have a particle diameter of 14.99 nm. These
particles were superimposed on polypropylene, and nanocomposites were synthesizes
and diagnosed using different techniques, such as FT-IR, SEM, EDS, XRD, TG, DTA,
and DSC. To identify the shapes, sizes, and nature of the particles of nanocomposites
synthesized in an environmentally friendly way using the mentioned techniques,
inhibitory actions of microorganisms were studied using several types of bacteria and
fungi. To identify the protective role of environmentally friendly nanoparticles, the
antimicrobial activity of the synthesized nanoparticles was characterized by green
methods. Antioxidant activity was calculated by DPPH, and acceptable results were
obtained for scavenging free radicals.

This work demonstrated a simple and environmentally friendly method for
synthesizing silica-supported copper nanocubes (CuNCs/SiO2). The copper
nanocubes, with a size of 15  5 nm, were synthesized using green reagents and
conditions. Ascorbic acid, water, and di-n-butyl sulfide were employed as reducing
agent, solvent, and stabilizing ligand, respectively. The designed nanoscale catalyst
was utilized for the esterification of acetic acid to methyl acetate at room temperature.
The catalyst exhibited high efficiency, converting 80% of the reactant to the desired
product (methyl acetate) after 24 hours of reaction at room temperature. The size and
shape of copper nanocubes were characterized by transmission electron microscopy
(TEM) and X-ray diffraction to characterize the formation of copper nanocubes, while
the esterification product was characterized using gas chromatography-mass
spectrometry.

Diabetes is associated with endothelial dysfunction, which impairs blood
vesselscapacity to maintain vascular tone. Apelin is an adipocyte-produced relaxing
factor that has endothelium-dependent and nitric oxide (NO)-mediated vasorelaxant
effects. The current study investigated how streptozotocin (STZ)-induced type one
diabetes modulates the mechanisms involved in aortic vascular response to apelin,
focusing on the role of potassium channels and endothelial derived relaxing factors
(EDRF). In this study, precontracted rat thoracic aortic segments were pre-incubated
with the NO inhibitor, cyclooxygenase (COX) inhibitor and potassium channels
blockers including: non-selective calcium-activated potassium channel, big
conductance calcium-activated potassium channels (BKca), intermediate conductance
calcium activated potassium channels (IKca), delayed inward rectifier potassium
channels (Kir), adenosine triphosphates-sensitive potassium channels (KATP) and
voltage sensitive potassium channels (Kv) blockers, then cumulative concentrations
of apelin were applied to each group in both non-diabetic and diabetic conditions. The
statistical analysis between diabetic and non-diabetic groups revealed that endothelial
impairment induced by diabetes in rat thoracic aorta remarkably attenuated the
vascular responses to apelin. An important new finding in this study was that almost
all potassium channels blockers noticeably P<0.001 increased apelin efficacy with
relatively no changes in the peptide potency. However, in diabetic aortic segments,
the non-selective Kca, BKca blockers, NO inhibitor and COX inhibitor reversed
vascular responses to apelin, but Kir, KATP and Kv blockers significantly reduced
vascular responses to apelin in comparison to control rats. It is worth noting that
diabetes did not only alter the peptide potency in these experimental groups but also
significantly increased the maximum responses when Kca and BKca blockers
preincubated. In conclusion, our findings shed light on the mechanisms behind
diabetes-induced aortic artery hypo-reactivity to apelin which involve the inhibition
of endothelial NO synthase activities and decreased contribution of Kca, BKca, IKca,
Kv, Kir and KATP channels.

Klebsiella pneumoniae is among the most frequent microorganisms isolated from
infections of burn wounds. This cross-sectional study aimed to investigate the
distribution of multi-drug resistant (MDR) K. pneumoniae in two burn hospitals and
the antibiotic resistance profile in different burn regions of the same patient. It was
performed in two hospitals (Al-Zahraa and Al-Karama) in Al-Kut, Iraq, between
January and May 2022. Totally, 100 burn swabs were collected from 40 patients of
both genders suffering from burn wound infections, with ages ranging between 3 and
50 years. Klebsiella pneumoniae were isolated and identified using conventional
methods followed by VITEK®2 system and confirmed via polymerase chain reaction
targeting the gapA gene. Then, the antimicrobial susceptibility pattern was studied by
the VITEK®2 system. Of the 100 burn wound swabs, 20 isolates were K. pneumoniae.
Fifty five percent (11 out of 20) of K. pneumoniae isolated in the current study were
MDR and 35% of the isolates had the extended spectrum beta-lactamase (ESBL)
which is the main antibiotic resistance mechanism. Furthermore, the bacteria isolated
from different burned areas of the same patient showed variable pattern of antibiotic
susceptibility. To conclude, K. pneumoniae contaminating the burn wards in the Iraqi
hospitals are mostly MDR, against which tigecycline is the most effective antibiotic.

Acute lymphoblastic leukemia (ALL) is a blood cancer where high numbers of
abnormal, immature lymphocytes called blasts start over-multiplying in the bone
marrow. The lymphocyte cells and interleukins are crucial for controlling the immune
response in tumor microenvironment. Many of the single nucleotide polymorphisms
(SNPs) of some interleukin genes may change protein synthesis or function and
regulate the immune response. A lot of these changes have been connected to a high
risk of developing cancer. Aim of this study was to investigate the potential
association between IL-12 (+1188 A/C) (rs3212227) and IL-18 (–607 A/C)
(rs1946518) polymorphism with serum levels of interferon-γ (IFN-γ) and tumor
necrosis factor-α (TNF-α) and their genotypes association with the susceptibility to
ALL disease in Iraqi patients. The study included 59 ALL patients and 30 healthy
controls. The detection of IL-12 and IL-18 SNP genes was determined by ARMSPCR
methods and serum levels of IFN-γ and TNF-α were determined by utilizing
enzyme linked immuno-sorbent assay (ELISA) kits. Results observed no significant
association of IL-12 and IL-18 polymorphism with serum IFN-γ and TNF-α level.
Genotyping frequencies of IL-12 (+1188A/C) CA, AA and CA+AA genotypes
showed a strong association with the development of ALL disease, IL-18 genotypes
showed no significant association with the disease progression.

This study aimed to evaluate the association of single nucleotide polymorphisms
(SNP rs-9939609) of the fat mass and obesity-associated (FTO) gene with body
mass index (BMI) and some biochemical markers in obese patients. The fat and
mass obesity (FTO) gene variant specific single nucleotide polymorphism (SNP rs-
9939609) with the T to A missense mutation may have a powerful association with
obesity. This case-control study included 106 obese patients (57 males and 49
females) and 80 healthy control (40 males and 40 females). DNA was extracted from
whole blood, and then the tetra-primer amplification refractory mutation system -
polymerase chain reactions (ARMS.PCR) technique was used to limit the single
nucleotide gene polymorphisms (rs9939609) of the FTO gene. Lipid profile,
glycated hemoglobin (HbA1C), fasting blood sugar, insulin and FTO concentrations
were measured by standard methods. In this study, the A allele in the rs9939609 was
at a higher frequency of 35 (33.1%) in the obese patients and at a significant p-value
= 0.039 compared with control 15 (18.7%). It significantly increased in the additive
model and allele frequency (p= 0.003, 0.002 respectively). The rs9939608 SNP
showed a significant association with increased BMI, insulin and homeostatic model
assessment-insulin resistance (HOMO-IR) with p-values of 0.001, 0.001 and 0.028
respectively. After making adjustments for age and sex, lower levels of high-density
lipoprotein (HDL) were observed in the AA and TA genotypes compared to the TT
genotype (p = 0.004). While, no significant differences were recorded between the
rs9939608 SNP and HbA1C, total cholesterol (TC), triglyceride (TG), very lowdensity
lipoprotein (VLDL), and low-density lipoprotein (LDL) in obese patients

The deposition process and investigation of the physical properties of tungsten
trioxide (WO3) thin films before and after gamma irradiation are presented in this
paper. The WO3 thin films were deposited, using the pulse laser deposition technique,
on glass substrates at laser energies of 600mJ and 800mJ. After deposition, the
samples were gamma irradiated with Co60. The structural and optical properties of
polycrystalline WO3 thin films are presented and discussed before and after 5kGy
gamma irradiation at the two laser energies. X-ray diffraction spectra revealed that all
the films consisted of WO3 crystallized in the triclinic form; the dislocation density
and lattice strain increased with the absorbed dosage of gamma irradiation. The optical
constants, the average diameter and the surface roughness of the WO3 films were
calculated before and after gamma irradiation and for the two laser energies. It was
found that the WO3 thin films conductivity increased by γ-irradiated and with the
increase of the laser energy.

The study of neutron-rich nuclei's form factors, root-mean-square radius (rms), and
nuclear density distributions is the focus of this work for the nuclei (22N,23 O and 24F).
With the use of a strong short-range effect and a strong tensor force, the nucleons
distribution function of the two oscillating harmonic particles in a two-frequency shell
model operates with two different parameters: the first (bcore), for the inner (core)
orbits, and the second (bvalence) for the outer (halo) orbits. This work demonstrated the
existence of neutron halo nuclei for the nuclei (22N, 23O and 24F) in the (2s1/2) shell.
The computed density distribution of neutron, proton and matter for these nuclei
displayed the long tail performance. Using the Borne approximation of the plane
wave, the elastic form factor of the electron scattering from the alien nucleus was
calculated, this form factor is independent of the neutrons that make up the halo, but
rather it results from a difference in the proton density distribution of the last proton
in the nuclei. Fortran 95 power station program was used to the neutron, proton and
matter density, elastic electron scattering form factor, and rms radii. The calculated
outcomes for these exotic nuclei were in good agreement with the experimental data.

The beam transport system is an essential part of any accelerator. This research
investigates how a charged particle beam extracted from a plasma source behaves as
it passes through a virtual beam transport system consisting of a series of C-bending
magnets. This is done by analyzing the equations of motion of charged particles
through this system. In addition, the study investigates the effect of the free drift
space regions between these magnets and studies the behavior of charged particles
beam passing through the suggested system for both horizontal and vertical planes
using a computer program designed for this purpose. The results indicate many
focusing regions along the beam path (beam envelop) for both the horizontal and
vertical planes. The presence of free drift regions between the magnets strongly
affects the beam envelop for both horizontal and vertical planes.

This research aims to study the structural properties of cadmium telluride (CdTe)
core QDs and cadmium telluride/ cadmium selenium (CdTe/CdSe) core-shell QDs at
pH 12. The QDs were prepared using aqueous synthesis by reflux process. The
structural properties of the QDs were studied using X-ray diffraction (XRD), Field
Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray
spectroscopy (EDX), and Transmission Electron Microscopy (TEM). The results of
the XRD analysis for CdTe QDs and CdTe/CdSe QDs showed that they have three
diffraction peaks in the directions (111), (220), and (331) with a slight shift in the
diffraction peaks of CdTe/CdSe QDs, which indicates the successful packing of
selenium atoms around CdTe. FESEM results confirmed that CdTe and CdTe/CdSe
QDs possess quantum spherical NPs with diameters ranging from 27 nm to 41 nm.
The EDX results confirm corrections of added concentrations The histogram images
of the TEM analysis show that the diameters of CdTe and CdTe/CdSe are 7nm and 9
nm, respectively.

Naturally occurring radioactivity was evaluated in the reservoir rock, surface soil
samples, and oil production waste at the East Baghdad South (EBS) Oil Field. The
radioactivity of uranium-238 (and radium-226), thorium-232, and potassium-40 were
calculated in core samples from four geological formations: Al-Zubair, Al-Khasib,
Tanuma, and Hartha Formations, which represent the oil reservoirs in the study area
in addition to the natural GR and SGR logs for the oil well in EBS were calculated.
The radioactivity of the above-mentioned nuclides was also measured for surface soil
samples and waste samples from the site of the oil production industry at the EBS
oilfield. The measurements included all the stages of oil production from the
collection of crude oil from the wells stage to the storage of the manufactured oil. It
also included measurements of radioactivity in samples for some sites outside the
industry and near the oil wells in the region. Total radioactivity was measured in
count/second and the exposure dose rates were also measured at all the above sites.
Relatively high concentrations of uranium-238 and radium-226 were found in rock
core samples of some geological units within the oil reservoir formations which will
certainly move with the oil to the surface and collect with waste (such as sludge) when
oil is produced. Although, some sites have higher Ra-226, Th-232, and K-40, in the
sludge samples and oily soil, such as in the 1st separator stage, water separation
(Desalter) stage, and near the waste pit, these locations are acceptable if they are
compared with other oilfields worldwide. The gamma absorbed doses calculated
inside the EBS oil industry were higher than the global average of (59) nGy/h where
Ra-226 is the main contributor in these doses, on the other hand, external hazard index
(Hex) values less than unity so they are acceptable according to UNSCEAR. Radiation
dose values in some places in the study area exceed the values recommended by ICRP,
UNSCEAR, and IAEA (1 mSv/y) for the public but less than the values recommended
for workers (20 mSv/y). generally, the site of EBS- oilfield does not show radioactive
contamination or significant radioactive hazards, as it is a new facility, and safety
instructions are still strictly applied, and the removal of waste immediately before its
spread by the activity of the workers in the facility.

At the Subba oil field, wellbore stability is the main concern while drilling. The
wellbore's instability causes several issues, including: (inefficient hole cleaning, tight
hole, stuck pipe, mud losses, caving, bad cementing, and well kick or blowout). This
increases Non-Productive Time (NPT) and well-drilling costs; hence the operator's
main goal is to create a drilling program that reduces these problems and therefore
reduce drilling cost. The study aims to build a 1D mechanical earth model to predict
the wellbore failure and design optimum mud weight to improve the drilling
efficiency for future wells. The model includes pore pressure, stress state, and rock
mechanical parameters (such as UCS, angle of friction, Young-Modulus, and Poisson-
Ratio). To achieve this aim, the study utilised offset well data including log data
(Gama-Ray Logs (GR), Caliper Logs (CALI), Density Logs (RHOZ), and
Compressional Sonic (DTCO) and Shear Sonic (DTSM)), Core tests, Mini-frac field
tests, Drilling Reports, Mud Reports, and Mud Log Reports (master log) to estimate
and calibrate the profiles of formation pore pressure, rock mechanical properties, and
in-situ stresses.
The 1D mechanical earth model was built using the Excel program for three wells
data set, where all the necessary parameters to create the model was calculated,
calibrated for the calculated variables with core data and pressure test points, and
finally the safe mud window was detected.
The results showed that the Eaton Slowness method to predict pore pressure perfectly
matches the pressure test points. The most common fault regimes in the Subba oilfield
are normal and strike-slip faults. The Modified Lade criteria showed a compatible
match with drilling events and calliper log in predicting the failure zones, so it is the
best criterion in determining minimum and maximum mud weight. Based on the
results of this study and in comparison with the mud window used in drilling
operations in the field, it is necessary to change the mud window used in drilling and
adopt the safe MWW of this study in drilling new wells in this field and the area
adjacent to the field.

This research is concerned with the set of functions in ordered Banach algebra
values that links up between functional analysis and measure theory. We generalized
the concept of integration by using the measure space (ℵ, Γ, ℳ) and the measurable
function θ: ℵ
→ ???? where ???? is an ordered Banach algebra by using the integration
of a simple measurable function with values in an ordered Banach algebra space
(represented by an indicator function that has values in an ordered Banach algebra)
and the integral of a non-negative measurable function that has values in an ordered
Banach algebra. The aim of this research is to define the integration of functions by
using the measure ℳ in the ordered Banach algebra space. This study generalized the
definition of integration for the measurable function with values in the ordered
Banach algebra space.

In this work, the concept of the paracompact map has been generalized to other
new types of maps, in addition to the fact that the paracompact map has been linked
to these new maps. Accordingly, we will separate these new types of maps into two
classes, the first class is called a strong form which implies a paracompact map under
certain conditions. While the other class is called a weaker form of a paracompact
map, whereas the paracompact map implies them. Finally, the composition operations
of paracompact maps are studied.

In this article, the Laplace transformation method in connection with the
variational iteration method will be used to solve approximately fuzzy random
ordinary differential equations. After that, the sequence of approximated closed form
iterated solutions is derived based on the general Lagrange multiplier evaluated using
the well-known convolution theorem of the Laplace transformation method. In
addition, two examples are given and solved to illustrate the reliability, efficiency and
applicability of the proposed method, they are simulated using computer programs
with two different generations of stochastic processes, namely the Wiener process or
Brownian motion, which are 1000 and 10000, respectively

The peristaltic flow of Walter's B fluid through an asymmetric channel is analyzed.
The constitutive equation for the balance of mass, momentum, trapped phenomena,
and velocity distribution is modeled. Consideration of low Reynolds number and long
wavelength assumption are used in the flow analysis to get an exact solution by using
the perturbation method. The impact of impotent parameters on stream function and
axial velocity has been gained. The set of figures is graphically analyzed of these
parameters

Suppose that ???? is a finite group and ???? is a non-empty subset of ???? such that
???? ∉ ???? and ????−1 ⊆ ????. Suppose that ????????????(????, ????) is the Cayley graph whose vertices are
all elements of ???? and two vertices ???? and ???? are adjacent if and only if ????????−1 ∈ ????. In
this paper,we introduce the generalized Cayley graph denoted by ????????????????(????, ????) that is
a graph with vertex set consists of all column matrices ???????? which all components are
in ???? and two vertices ???????? and ???????? are adjacent if and only if ????????[(????????)−1]???? ∈ ????(????),
where ????????
−1 is a column matrix that each entry is the inverse of similar entry of ????????
and ????(????) is ???? × ???? matrix with all entries in ???? , [????−1]???? is the transpose of ????−1
and ???? ≥ 1. We aim to determine the structure of ????????????????(G, ????) when G is the dihedral
group of order 2n and | S |= 3 for every ???? ≥ 2, n ≥ 3.

In the past years, there was an attempt to add one column to the e-abacus diagram,
then another work followed by other researchers by adding several columns to the
same diagram. At that time, a question remained, is it possible to add a row and later
several rows on the same diagram? Or is this not an easy thing except under certain
conditions? In this research, we will know when we can take these steps.

The analysis of observed data at different time points is prominent to single
problems when the scientist studied random sampling data over time restricts the
applicability of many traditional statistical methods that require random sampling.
The analysis of this data is usually mentioned to the stochastic process, in a special
case, if it relates to time, then it is called time series [1]. The aim of our study is to
focus on the case of observations that are made at certain times of the year, specifically
in the autumn season, in equal periods of time, and we estimate the effect of
interference on wheat prices n order to obtain the best predictive model and the best
order of this model for the overall effect on the price of wheat for the coming years.

One of the most effective mathematical concepts for developing a clear picture of
topological cluster proximity spaces is the follower points and the takeoff points.
These are utilized in current study to construct three sets called the cluster outer set,
the cluster disputed set and the cluster brim set denoted by ???????????? , ???????? (????), ???????? (????),
respectively. These three sets have divided the space into three separate pairs. On the
other hand, the most important results, properties, and relationships between the sets
were highlighted and studied.

In this paper we introduce a generalization of local module. The notion of 2-Local
module can be considered a new concept (generalization of local modules). Let T be
a ring with identity. 2-maximal submodule can define as, any submodule B1 of B is
called 2-maximal if (B/B1) is a 2-regular module. 2-Local module means every
submodule A of a T-module B where
????
????
is a unique 2-maximal submodule. Almost
any unique maximal submodule of a T-module ???? gives 2-local module. Also, we can
present a generalization of local module by, if ???? is a fully prime module over the ring
???? and every submodule B1 of a T-module B is a unique almost max-submodule, this
means ???? is a 2-local. Every semi-maximal submodule ????1 over chained module ???? is
maximal (2-maximal submodule) and hence ???? is 2-local module. Some properties
and examples of 2-Local module are given. Finally some implications of 3-local
module have been presented.

A submodule N is called rational in M if HomR(
M
N
, E(M))=0, where E(M) is the
injective hull of M. Rational submodules have been studied and discussed by many
authors such as H.H. Storrer, H. Khabazian, E. Ghashghaei, A. Hajikarimi and A.R.
Naghipour, M.S. Abbas and M.A. Ahmed. The main objective of this paper is to give
a new class of submodules named P-rational submodules. This class is contained
properly in the class of rational submodules. Several properties of this concept are
introduced. The relationships between this class of submodules and some other related
concepts are discussed such as essential and quasi-invertible submodules. Other
characterizations of the P-rational submodule analogous to those which is known in
the concept of the rational submodule are given.

This paper introduces the Right Truncated Inverse Gompertz Distribution
(RTIGD) with two parameters δ and ϑ with some of its properties as; (Survival-
Function, Hazard-Function, cumulative distribution function, probability density
function, r-th moment, mean, variance, Moment Generating Function, Median, and
Mode. In addition, we propose a new hybrid algorithm, namely the firefly Algorithm
with Cuckoo Search Algorithm (FA_CSA) to estimate the parameters based on the
survival functions of RTIGD. Simulation is utilized to compare the proposed
algorithm with traditional methods, for example, the Maximum Likelihood Estimator
and moment method and the standard algorithms Firefly Algorithm and Cuckoo
Search. In most cases, the results demonstrate that the proposed algorithm (FA_CSA)
provides an accurate estimation for the survival function since it has less mean squared
error than the other estimation methods.

Linear programming currently occupies a prominent position in various fields
and has wide applications, as its importance lies in being a means of studying the
behavior of a large number of systems as well. It is also the simplest and easiest type
of model that can be created to address industrial, commercial, military and other
dilemmas. Through which to obtain the optimal quantitative value. In this research,
we deal with the post optimality solution, or what is known as sensitivity analysis
using the principle of shadow prices. The scientific solution to any problem is not a
complete solution once the optimal solution is reached. Any change in the values of
the model constants or what is known as the inputs of the model will change the
problem of linear programming and will affect the optimal solution. Therefore, we
need a method that helps to stand on the impact of changing these constants on the
optimal solution that has been reached. General concepts about the binary model and
some related theories have also been addressed. By analyzing the sensitivity, we rely
on real data for a company that transports crude oil and its derivatives. The
mathematical model is formulated for it and the optimal solution is reached using
the software. Ready-made sop WINQSB and then calculate the shadow price values
for the binding constraints, in addition, linear programming under the fuzzy
environment is reviewed, and a new method based on the prime numbers is used to
solve the fuzzy parameters model.

In this paper, a solution to one of the Bicriteria Machine Scheduling Problems
(BCMSP) is proposed. This problem focuses on the maximum early jobs time and
range of lateness jobs time on a single machine (1//(???????????????? , ???????? )). First, we derive a
subproblem 1//(???????????????? + ???????? ) from the main problem which is a special case for the
suggested problem. Secondly, both exact complete enumeration and Branch and
Bound (BAB) with two new lower bounds with some heuristic methods to solve the
problems are proposed. The results prove the accuracy of BAB to solve the problem
for ???? ≤ 110 jobs in a reasonable time. In addition, the accuracy of the suggested
heuristic methods is compared with the results of the exact methods.

A general treatment function with an epidemic model that involves the delay in the
treatment period has been proposed and studied in this work. This model contains
two compartments, namely susceptible denoted by ????(????) and infected denoted by ????(????).
The existence of all the fixed points has been determined. The system has two
equilibrium points, namely the uninfected equilibrium point (UIEP) and the endemic
equilibrium point (EEP). The conditions for local stability and Hopf bifurcation have
been discussed. The stability of the periodic solutions and the direction of the Hopf
bifurcation properties have been studied analytically and numerically.

Let R be a commutative ring containing a unit, and let M be a left R-module. We
define a proper sub-module N of an R-module M to be a weakly 2-prime sub-module
if whenever 0 ≠ ???????? ∈ ????, ???? ∈ ????, ???? ∈ ????, then either ???? ∈ ???? or ????2 ∈ [????: ????]. This
concept is an expansion of the idea of a weakly 2-prime ideal, where an ideal P of R
is said to be a weakly 2-prime ideal if for all ????, ???? ∈ ????, 0 ≠ ???????? ∈ ???? implies ????2 ∈ ????
or ????2 ∈ ????. Several characteristics of sub-modules that are weakly 2-prime are taken
into account.

Diabetes mellitus (DM), a chronic, clinically heterogeneous condition, is becoming
increasingly common all over the world. Insulin deficiency, resistance to insulin's
actions on the body's surface, or both may lead to pancreatic beta-cell degeneration.
Diabetes makes people more prone to its consequences, the most prevalent of which
is diabetic retinopathy (DR). Deep learning algorithms surpass traditional
classification models for illness diagnosis on photos of medical problems. Deep
transfer learning models for medical DR detection were evaluated using the APTOS
2019 dataset. Deep transfer learning algorithms for medical diabetic retinopathy (DR)
detection are being evaluated. MobileNet Convolutional Neural Networks (CNN)
architecture is used to detect the DR in binary class classification tasks, which
leverages pre-trained weights collected during the training process using the
ImageNet database. Cohen Kappa, F1 score, recall, accuracy, and precision are some
of the performance indicators used. According to the data, the given model is the most
effective in terms of accuracy and training time for handling our challenges. Overall,
MobileNet is a good pick. The following metrics were found to be accurate: 0.9455,
precise: 0.94651, recall: 0.9455, F1 score: 0.94556, and Cohen Kappa score: 0.89083.
This method might aid medical personnel in the early detection of diabetic
retinopathy.

Nowadays, smart parking systems (SPS) represent one of the active research areas
of intelligent transport systems (ITS). It is an interesting topic and attractive to
researchers due to the difficult challenges that are needed to solve it. It enhances city
life and plays an important role in reducing gas emissions, air pollution, and traffic
congestion while improving the time override for drivers to easily allocate vacant
parking lots. In this paper, we discuss and dedicate a review of how computer visionbased
approaches can assist in providing wellness solutions for the occupancy of
smart parking lots. In addition, we provide an overview of the most common standard
datasets and some well-known applications of vacant smart parking lots.

Cloud computing is one of the emerging technologies that expands the boundaries
of the internet by using centralized servers to maintain data and resources. It allows
users and consumers to use various applications provided by the cloud provider, but
one of the major issues is task scheduling. Task scheduling is employed for the
purpose of mapping the requests of users to the appropriate resources available. This
paper provides a detailed survey of the available scheduling techniques for cloud
environments based on six common metaheuristic algorithms. Those algorithms are
the Cuckoo Search Algorithm (CSA), Chicken Swarm Optimization (CSO), Genetic
Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), and
Grey Wolf Optimization (GWO). The literature is analyzed from three perspectives:
task type, objectives to be optimized, simulation environment, and quality of service
performance metrics. In addition, the research gaps and future directions for future
investigation are presented

In Parallel programming, a programmer needs to understand hardware
environment, programming paradigm and primitives available in the programming
language. Most of the time, parallel programmes are written for a specific architecture
and cannot typically adapt to other architectures Particularly, programs written for
shared memory architectures are unsuitable for distributed or hybrid architectures.
This paper proposes Adaptive Design Pattern for Parallel Programming to improve
adaptability, flexibility with achieving performance on different architectures.
Molecular Dynamics (MD) simulation is required to scale to various architectures
from simple machine to cluster of workstations. In this study, MD Simulation
experimented using both pure benchmark code and code based on adaptive design
patterns. Redesigned MD Simulation with Adaptive Design Pattern claims parallel
efficiency from 56% to 90% for different number of processing elements used. The
solution demonstrates adaptability to different architectures and scalability to use with
large number of atoms and long duration simulation.

Object detection algorithms play an important role in detecting people in
surveillance videos. In recent years, with the rapid development of deep learning, the
performance of object detection has improved by leaps and bounds, and the scheme
of object detection by the YOLOV7 algorithm has also been born. Traditional object
detection methods often fail to achieve a balance between speed and accuracy. To
address these issues, in this research, an improved YOLOv7 algorithm performance
is proposed to get the best speed-to-accuracy balance compared to state-of-the-art
object detection within recorded videos using an effective compression method. This
method calculates the difference between frames of video, and by using the zero
difference approach by removing the duplicate frames from the recorded video and
choosing only the meaningful frames based on many variables, including frame size,
frame details, and the distance of the frames, influence the choice of a
meaningful frame, and this will reduce the size of the video by eliminating the frames
comparable to those chosen.
Additionally, any other datasets or pre-trained weights have not been used;
YOLOv7 has been exclusively trained on the MS COCO dataset from scratch. In order
to ensure the effectiveness of this approach, numerous detection systems are used in
this work. Additionally, positive performance results to reduce the processing time
required for object detection have been attained.

Complex detection in protein-protein interaction (PPI) networks is one of the major
issues facing scientific study in biological networks. In PPINs, proteins are distributed
differently as groups (complexes). These groups can be identified as having a great
internal density in the number of edges inside the groups while having the least
possible number of edges between these groups. The most common methods for
finding such complexes are evolutionary algorithms (EAs), which have been used
widely in literature for this objective. Despite the reliability of these complicated
detection models, they are mostly based on topological (graph) qualities, and the
biological implications of the PPI networks have been rarely explored. In this
research, EA with mutation-based gene ontology is developed, particularly in the
mutation part where the functional annotation of the protein has been considered using
gene ontology structure. The experimental results prove the reliability of the proposed
method using standard validation measures. It also outperforms the state-of-the-art
method in terms of the prediction ability and quality of the complexes found

Negation is a linguistic phenomenon that can cause sentences to have their
meanings reversed. It frequently inverts affirmative sentences into negative ones,
affecting the polarity; therefore, the sentiment of the text also changes accordingly.
Negation can be expressed differently, making it somewhat challenging to detect. As
a result, detecting negation is critical for Sentiment Analysis (SA) system
development and improvement and will increase classifier accuracy, but it also poses
a significant conceptual and technical challenge. This paper aims to survey and gather
the most recent research related to detecting negation in SA. Many researchers have
worked and performed methods, including algorithmic, machine, and deep learning
approaches such as Decision Tree (DT), Support Vector Machines (SVM), K-Nearest
Neighbor (KNN), Naive Bayesian (NB), Logistic Regression (LR), Artificial Neural
Networks (ANNs), Recurrent Neural Networks (RNNs), Bidirectional Long Short-
Term Memory (BiLSTM), and other hybrid methods such as rule-based and machine
learning, lexicon and machine learning, machine learning, and deep learning. It
addresses and tries to identify the gaps in the current studies, laying the foundation
for future studies in this field.

Path planning is a challenging navigation problem that can be handled using
multi-objective methods. This paper presents a three-stage multi-objective pathplanning
method. The first stage is to locate the best or near-best solution path and
avoid detected obstacles using a hybrid of the red fox–gray wolf optimizer (RFO–
GWO), which finds a route from the start position to the target position. In the
second step, a mutation operation using an evolutionary algorithm is utilized to
enhance the length, integrity, and smoothness of the route generated by the RFO–
GWO algorithm. The final step of the suggested method is refined further using a
multiphase technique. By integrating the real sizes of the mobile robots and the size
of the barriers and phrasing the issue as a traveling object in the available area, the
suggested path-planning method resembles the actual world. The simulation results
indicate that this strategy creates the most viable path even in complicated
surroundings, overcoming the disadvantages of traditional approaches. Furthermore,
when compared to prior path-planning methods, the simulation’s outcomes indicate
that the suggested RFO–GWO method is effective in terms of the route, and the
strategy is extremely competitive. The results showed a significant improvement,
where the total percentage convergence time (in seconds) for RFO–GWO for the
three maps was 15%, 12%, and 10%, respectively, whereas it was 35%, 41%, and
43% seconds in GWO and 34%, 35%, and 37% seconds in RFO. There was also a
significant improvement in the number of nodes for RFO-GWO (2%, 3%, and 2%)
compared to GWO nodes (64%, 65%, and 62%), and RFO nodes (32%, 30%, and
35%) for the same three maps. Subsequently, the smoothness of the path formed by
the recommended approach was enhanced using the evolutionary algorithm (EA),
where the total percentage length of the path in the worst scenario for GWO was
28% and for RFO was 26% in units, but after improvement with the RFO-GWO
with EA, it became 22% in units.

Data generated from the internet and modern applications is extensive and rapidly
expanding. So, all modern applications must successfully perform tasks using this
massive data. Therefore, one of the significant factors for the success of any
application is understanding and extracting meaningful information using digital
analytics tools to positively impact the application's performance and deal with
challenges that can be encountered. On the other hand, cloud computing is simply an
environment comprising a collection of high-performance services from various
vendors. These services can frequently access and process massive amounts of data
faster than a traditional computer. One of these services is cloud analytics, which
applies cloud-based analytic algorithms against data in a private or public cloud to get
the desired outcome. This paper differentiates between several analytics
methodologies to create highly consistent, logical, and information-rich summaries.
This research has discussed and analyzed many studies related to this field. Therefore,
the results of this paper can be utilized to determine the advantages of these methods,
which will help future researchers in their research for a more organized and thorough
analysis when dealing with such applications. In addition, this paper attempts to
discover new directions and propose new guidelines in this evolving field.

Human skin detection is the process of classifying the image pixels or regions as
skin or non-skin. Skin detection has many applications, such as face tracking, skin
diseases, nudity recognition, hand gestures, video surveillance, web content filtering,
and pornographic content filtering. Skin detection is a challenging problem due to skin
color variation, the human race, aging, gender, makeup, complex backgrounds, etc.
This paper suggests detecting the skin region in the image and finding the location of
the skin based on a convolutional neural network. In this proposal, the proposed CNN
will be modified by adding two layers before the first layer of CNN and after the last
layer of CNN. The main purpose of these layers is to prepare the input image by using
a sliding window, which inputs an indexed small part of the image into the CNN. The
network classifies each part as skin or non-skin and then sends the result into the
second suggested layer. After processing all the image pixels, the non-skin blocks are
mapped to the original image as black regions. The final image contains the skin
regions with black in the background. The contribution of the proposed method is the
ability to detect the skin from any part of the human body, unlike previous works,
which focused on one part of the body. The input image is processed as blocks instead
of the entire image as in the previous works, and then in the output, the original image
is reconstructed. This method works well with most of the challenges that face the
detection of skin, and finally, the designed network facilitates the localization and
segmentation of the skin region almost accurately, while the previous networks
focused on the classification of the image as skin or non-skin. The accuracy of the
detection of skin when testing with images different from the training images was
95.4%.

This study investigates instantaneous and continuous sources as point, line, and
area sources. Gaussian concentration in the case of the puff model with an
instantaneous point source inhomogeneous longitudinal diffusion is investigated. The
concentration is calculated using different dispersion parameters to get the proposed
normalized concentration of the puff model at ground level around the centerline,
which is compared with observed data by the Copenhagen experiment and previous
work [1].
Also, the continuous point source is used to get the Gaussian plume model in three
dimensions using dispersion parameters to compare with the observed concentration
data measured by the Egyptian Atomic Energy Authority for Iodine-135 (I135) in an
unstable condition

In this study, the first kind Bessel function was used to solve Kepler equation for
an elliptical orbiting satellite. It is a classical method that gives a direct solution for
calculation of the eccentric anomaly. It was solved for one period from (M=0-360)°
with an eccentricity of (e=0-1) and the number of terms from (N=1-10). Also, the error
in the representation of the first kind Bessel function was calculated. The results
indicated that for eccentricity of (0.1-0.4) and (N = 1-10), the values of eccentric
anomaly gave a good result as compared with the exact solution. Besides, the obtained
eccentric anomaly values were unaffected by increasing the number of terms (N = 6-
10) for eccentricities (0.8 and 0.9). The Bessel function's solution appeared to be close
to the exact solution for eccentricity of 1 and more than 10 number of terms. Finally,
the representation of the first kind Bessel function J1(x) was closer to the exact
representation only for eccentricity 0.5 and (N=1-10).

The main goal of this work is to put a simple model of the spectral energy
distribution of binary stars called WW Cha. This model is built up on the extracted
data from various telescopes and archives for the target WW Cha stars and then
analyzing them using a python environment. The result of the fitting proposes that
there are two protoplanetary disks around the WW Cha star, with different physical
properties for each disk, such as the size of the inner disk being 10 AU, while the size
of the outer disk being 300 AU. The shape of the outer disk is a flaring disk not a flat
disk according to the value of the power law for the surface density (1.5). The
emission in the disk is caused by small amorphous olivine grains ranging in size from
0.1 to 3000 micrometers.

The present work aimed to examine the nature and degree of the cross-correlations
among three different ionospheric indices: these are Optimum Working Frequency
(OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF).
VOCAP and ASASPS models were adopted to determine the datasets of the selected
ionospheric indices. The determination was made for different transceiver stations that
provide certain HF connection links during the minimum and maximum years of solar
cycle 24, 2009 and 2014, respectively. Matlab program was implemented to produce
the geodesic parameters for the selected transceiver stations. The determination was
made for different path lengths (500, 1000, 1500, and 2000) Km and bearings (0o, 45o,
90o ........ 315o). Different correlation methods were used to examine the best
determination coefficient values between the tested parameters. A third-order
polynomial equation was set as the best correlation method that gave a better
description for the correlation among the tested parameters. The proposed
mathematical correlation equations were used to predict the seasonal values of the
(HPF, OWF and BUF) parameters. The proposed equations were verified by
comparing their values with the observed datasets during the study years. Also, the
predicted values were tested using different statistical methods, which gave good
results for all tested cases.

The earth's surface comprises different kinds of land cover, water resources, and
soil, which create environmental factors for varied animals, plants, and humans.
Knowing the significant effects of land cover is crucial for long-term development,
climate change modeling, and preserving ecosystems. In this research, the Google
Earth Engine platform and freely available Landsat imagery were used to investigate
the impact of the expansion and degradation in urbanized areas, watersheds, and
vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land
cover indices such as the Normalized Difference Vegetation Index, Normalized
Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI,
and NDBI) were determined to examine the effects of land cover changes. In addition,
the land surface temperature was calculated to assess urbanization expansion's impact
on Baghdad's climate warming. The results showed a drastic decrease in vegetative
cover and green land, on the other hand, a significant expansion in urbanized areas.
Hence, from 2004 to 2021, the urbanized areas and open land rose by 37% and 3%,
respectively, while the vegetative cover decreased by 41%. The maximum land
surface temperature has risen 4° C, and the minimum land surface temperature has
risen 2.5°C.