Iraqi Journal of Science

The development of two-dimensional chromatography systems is crucial in many
scientific fields as it provides improved separation efficiency and selectivity of
complex mixtures. By separating compounds based on two independent properties,
these systems can offer a more detailed understanding of sample composition. This
increased level of detail is particularly useful in industries such as pharmaceuticals,
environmental analysis, and proteomics, where complex mixtures with similar
properties need to be differentiated. A new chromatography system with two
dimensions was developed to separate and quantify specific flavonoids in German
wine samples. The first dimension used a homemade hydrophilic interaction liquid
chromatographic column, while the second dimension used a reversed-phase liquid
chromatographic column. This 2D ZIC-HILIC x RP technique was able to address
the problem of peak overlapping that commonly occurs in one-dimensional liquid
chromatography, especially for natural products. The study presents analytical and
statistical data for both techniques, and suggests that the use of two-dimensional
chromatography can improve the resolution of conventional one-dimensional liquid
chromatography. In a conventional ZIC-HILIC-HPLC system, apigenin and
naringenin were detected together but were successfully separated and measured
using a 2DLC system. The limits of detection (LOD) for apigenin and naringenin
were found to be 0.0705 μg/mL and 0.1300 μg/mL, respectively, while the limits of
quantification (LOQ) were 0.2136 μg/mL and 0.3939 μg/mL, respectively. The
recovery rate for both compounds was over 99%, with a relative standard deviation
(RSD) of less than 1.5%. The linearity range for both compounds was between
0.005 μg/mL to 10 μg/mL, and the correlation coefficient (r2) was determined to be
0.9998. For hesperidin and rutin, the LOD and LOQ were found to be 0.0336 μg/mL
and 0.1018 μg/mL, and 0.0120 μg/mL and 0.0363 μg/mL, respectively. The
linearity range for both compounds was between 0.005 μg/mL to 12 μg/mL, and the
correlation coefficient (r2) was determined to be 0.9999.

This work includes the synthesis of new ester compounds containing two 1,3,4-
oxadiazole rings, 15a-c and 16a-c. This was done over seven steps, starting with pacetamido-
phenol 1 and 2-mercaptobenzoimidazole 2. The structure of the products
was determined using FT-IR, 1H NMR, and mass spectroscopy. The evaluation of
the antimicrobial activities of some prepared compounds was achieved against four
types of bacteria (two types of gram-positive bacteria; Staphylococcus aureus and
Bacillus subtilis, and two types of gram-negative bacteria, Pseudomonas aeruginosa
and E. Coli), as well as against one types of fungus (C. albino). The results show
moderate activit against the study bacteria, and the theoretical analysis of the
toxicity demonstrates non-toxicity with acute oral human toxicity. Also, the toxicity
of these compounds in rats was weak. A molecular modelling study explains that
these compounds possess good binding with lung cancer proteins.

In this contribution, new derivatives of bicyclic fused rings with a bridgehead
nitrogen atom were synthesized from the imidazo[1,2-a]pyridine derivatives C1 by
reacting two moles of 2-aminopyridine and 4-aminoacetophenone with iodine in a
one-pot reaction. This compound (C1) was then condensed with 2-
nitrobenzaldehyde and 2,4-dichlorobenzaldehyde to form new derivatives of Schiff
bases (C2 and C3). These Schiff bases were then cyclized to synthesize thiazolidin-
4-one derivatives (C4 and C5), tetrazole derivatives (C6 and C7), and aza-β-lactam
derivatives (C8 and C9) through the reactions with thioglycolic acid, sodium azide,
and 1-naphthylisocyanate, respectively. FT-IR, 1H NMR, and 13C NMR
spectroscopy were used to characterize these new compounds. In the second part of
this work, the antioxidants of these compounds were measured, and results ranged
from good to medium.

Green synthesis methods have emerged as favorable techniques for the synthesis of
nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and nontoxicity.
In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using
the aqueous extract of Laurus nobilis leaves as a natural capping agent. The
synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich
Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive
characterization of NiO-NPs was performed using various techniques such as atomic
force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD),
Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy
(SEM). Additionally, operational parameters including adsorbent weight, adsorption
duration, temperature, pH value, and initial BS dye concentration were optimized for
the adsorption process. Isotherm analysis indicated a better fit of the Langmuir model
with equilibrium experimental data than the Freundlich model. The kinetic study
revealed that the Pseudo-second-order (PSO) model was more suitable to represent the
adsorption process compared to the Pseudo-first-order (PFO) kinetic model.
Thermodynamic analysis encompassing the changes in Gibbs free energy (ΔG˚),
enthalpy (ΔH˚), and entropy (ΔS˚) unveiled that the adsorption of BS dye onto NiONPs
was a spontaneous endothermic process with an increase in the randomness.

Spiro-isatin derivatives have been the subject of extensive research due to their
diverse pharmacological properties and potential therapeutic applications. These
molecules are characterized by a spirocyclic structure that includes an isatin moiety
and one or more heterocyclic rings, resulting in a unique and versatile molecular
architecture. In this work, a series of new spiro-isatin derivatives B1-12 were
synthesized over two steps. The first step included a condensation reaction between
isatin and various aromatic amines, affording the corresponding Schiff bases A1-12
in high yields (up to 96%). In the second step, A1-12 underwent a reaction with
glycine, resulting in the formation of B1-12 with yields varying between 65 and
92%. The structures of the compounds were confirmed by FT-IR and 1H NMR
spectroscopy. A few of the produced compounds were examined for antibacterial
and antioxidant properties.

In this research investigation, a total of eighteen diverse tetra- and penta-lateral
cyclic compounds were synthesized. These included 1,3,4-thiadiazole, thiazolidin-4-
one (via an alternative method), 1,2,4-triazole, carbothioamide, thiazole-4-one,
azetidin-2-one, and oxazole. The synthesis procedure entailed a sequence of
reactions. The thiazolidine-4-one 1 was obtained by reaction p-aminobenzoic acid
with thiosemicarbazide, followed by treatment with p-tolualdehyde to produce
Schiff base 2. Reaction Schiff base 2 with mercaptoacetic acid in dry benzene was
carried out to produce thiazolidine-4-one 3. In another synthesis pathway, the
esterification of p-nitro benzoic acid with ethanol in the presence of sulfuric acid
was obtained to formation of compound 4. Compound 4 was subsequently reacted
with thiosemicarbazide, yielding compound 5. Cyclization of compound 5 was then
achieved using 4% sodium hydroxide solution. This formed the 1,2,4-triazole
heterocycle, designated compound 6. Thiosemicarbazone 7-9 were prepared by
reaction of thiosemicarbazide with different aldehydes. Additionally, 2-substituted-
1,3-thiazolidine-4-one derivatives 10-12 were synthesized through the reaction of
thiosemicarbazone with chloroacetic acid in the presence of anhydrous sodium
acetate. The Oxazole derivative 15 was obtained through a series of reactions
starting with the reaction of p-amino benzoic acid with ethyl chloroacetate, resulting
in compound 13. Compound 13 was then treated with urea to obtain compound 14,
followed by a reaction with 4-phenyl phenacyl bromide to yield the final product,
the Oxazole derivative 15. The 2-aminooxadiazole derivative 16 was synthesized by
reaction urea with 4-bromoacetophenone which was reacted with 4-
bromobenzaldehyde to produce Schiff base derivative 17. Finally, β-lactam 18 is
obtained through reaction Schiff base with chloroacetyl chloride in the presence of
triethyl amine. FT-IR, 1H-NMR, and 13C-NMR spectroscopy were used to confirm
their proposed structures. Moreover, the antibacterial and antifungal activities of
certain synthesized compounds, specifically 2,3,6,11,13,15,17, and 18, were
assessed against Staphylococcus aureus, Escherichia coli, and Candida albicans,
demonstrating encouraging outcomes.Keywords: Antibacterial, antifungal activity,
oxadaizole, heterocyclic derivatives, Oxazole.

Anise is an aromatic plant which is used in traditional medicine and
pharmaceutical industry. The main components of anise seed are anise alcohol, panisaldehyde,
estragol, acetophenone, limonene and pinene, while the volatile oil
found in anise is anethole. The antioxidant, antimicrobial, anticonvulsant and
analgesic properties of anise seeds and oil have been confirmed by various studies.
The current study was designed to study the effects of oral administration of anise
oil on the reproductive capacity of adult male mice by examining certain
physiological parameters such as measuring the serum testosterone level, counting
the number of sperm, sperm motility and abnormal sperm morphology. A total of 36
male mice were used and randomly divided into three equal groups. Group1
received corn oil (control), T1 received anise oil in a dose of 0.043 gm/kg B.wt ,
and T2 received anise oil in a dose of 0.086 gm/kg B.Wt orally. The above
mentioned parameters were examined at the end of three weeks of administration for
six animals of each group. As well as, the examinations were repeated at the end of
six weeks of administration for the rest of the animals. The results exhibited that
treatment with anise oil led to a significant increase in the level of testosterone,
sperm count and motility. Furthermore, abnormal morphology of the sperms
decreased significantly. In conclusion, it can be said that the administered doses of
anise oil could have led to improve the fertility in male mice.

Chronic Kidney Disease (CKD) has been raised as a public health state
worldwide and is associated with increased cardiovascular morbidity and mortality.
The aim of the study was to assess serum lipid profile levels, renal function and
glucose in CKD patients undergoing hemodialysis. A total of 50 patients (23 males
and 27 females) with CKD attending the hemodialysis at Kidney Unit in Al-Ramadi
Teaching Hospital, Anbar Iraq and of ages ranging between 20 -85 years, were
sustained for this research. The patients were classified into three categories with
their mean age of 65.71±1.98 years. Eleven healthy adults were also recruited in this
study with mean age of 37.00±15.56 years as control group. The study included
measuring biochemical markers such as glucose, total cholesterol(TC), triglycerides
(TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein
cholesterol (LDL-C), very-low-density lipoprotein (VLDL) , creatinine and urea by
using automated chemistry analyzer by Abbott/USA. The outcomes of this study
showed that the urea and creatinine levels increased significantly, whereas HDL-C
level significantly decreased in the patients as compared with control group.
However, TC and LDL-C showed slightly lower levels which were within the
normal limits in the control group. While TG, VLDL and glucose levels showed
non-significant changes in CKD patients as compared with control (P ≤ 0.05). In
addition, all parameters revealed no significant changes in males as compared with
females group (P ≤ 0.05). Depending on age, only creatinine level showed
significant change in 20-40 years age group as compared with 61-85years age group
(p <0.05). Finally, abnormal lipid metabolism may probably be an independent risk
factor for the progression of renal disease.

In this research, silver nanoparticles (AgNPs) were manufactured using aqueous
extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was
investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was
assessed by MTT assay. AgNPs showed inhibition effect at the following
concentrations 12.5, 25, 50, 100 and 200 μg/ml versus MCF-7 cell line, and all
treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at
the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%,
while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells
viability to 75.77%.

Urinary tract infections (UTIs) are the most common infections caused mainly by
Escherichia coli and the O-antigen and FimH & PapGII adhesion genes are among
the most important virulence factors. The aim of this study was to investigate the
prevalence of some O-antigen in uropathogenic E. coli (UPEC) and molecular
characterization of the adhesion genes FimH & PapGII63. E. coli isolates (50.4%
from total number of samples) were collected from urinary tract infection patients
from July to October in 2021 and identified using molecular and biochemical tests.
Sevenantigenic types of uropathogenic E. coli were investigated, as well as the
presence of FimH & PapGII genes in uropathogenic E. coli strains. The results
indicated that the majority of UPEC belonged to serotypes O1, O2, O4, O6, O7,
O18ac and O75 in varying proportions, where the O1 serotype was the most
predominant, followed by O2, O6, O75, O7, O4 and O18ac respectively. The results
of molecular tests showed the presence of the FimH gene in 52 isolates with a
percentage of 82.50% and the presence of the PapGII gene in 19 isolates with a
percentage of 30.15%. From the results we can conclude that the serotypes O1 and
O2 had the most virulence role due to presence of the adhesion genes FimH and
PapGII.

Pregnancy and delivery are physiological conditions that are marked by abrupt
alterations to hormones, immunological and molecular characters. The current study
aimed to evaluate oxytocin (OT), prolactin (PRL), cortisol and insulin growth
factor-2 (IGF-2) levels as physiological biomarkers; programmed cell death protein-
1 (PD-1), programmed cell death ligand-1 (PD-L1),interleukin-6 (IL-6) as
immunological biomarkers, and single nucleotide polymorphisms (SNPs; rs53576
and rs2254298) of oxytocin receptor gene OXTR as molecular factors in samples of
Iraqi women undergoing caesarean section (CS) and normal delivery (ND). Blood
samples were collected from 96 pregnant women at term with ages ranging between
16-43 years. Regarding the physiological biomarkers, the study findings indicated
that the change in OT, cortisol and IGF-2 between CS and ND groups was not
significant, While the PRL level indicated a highly significant (P≤0.001) decrease in
the CS group, especially in comparison with the ND group. Immunological
biomarkers demonstrated a significant (P≤05) elevation for PD-1 as well as for PDL1
in the CS group as compared to the ND group. However, PD-1/PD-L1 ratio
revealed a high significant (P≤0.001) rise in CS compared with ND. The IL-6 results
revealed a significant (P≤0.001) reduction in the CS groups compared to the ND
group. And regarding the SNP of OXTR (rs53576), the findings revealed no notable
association in genotypes CC, TC and TT between both groups. In addition, the
mutant C allele and the wild T allele revealed no significant association between CS
and ND groups [OR=1.26 (0.68-2.3%)]. The SNP results of OXTR (rs2254298)
showed a high positive association (P≤0.001) in genotypes GG, AG and AA
between CS and ND groups. Also, the mutant G allele and the wild A allele revealed
high significance (P≤0.001) between both groups [OR=5.3 (2.8-9.76%)].

The main aim of our study was to determine if the ACE2 rs2106809 and AGT
rs699 polymorphisms increase the risk and severity of Covid-19 infection in Iraqi
patients. This case-control study included 102 patients (mean age 52.66±18.82
years) and 92 healthy (mean age 37.88±14.19 years). The patients were grouped
based on severity: hospitalized (n = 57) and non-hospitalized (n = 45). Demographic
and comorbidity data was also collected. Genotype distribution of two selected
SNPs ACE2 gene rs2106809 and AGT rs699 polymorphisms was performed by
allele-specific PCR (AS-PCR) and sanger sequencing. The ACE2 rs2106809 C allele
was associated to an increased risk of Covid-19 infection and the severity in males
but not in the females (C vs. T OR = 3.04 p=0.01 and C vs. T OR = 4.9, p = 0.03,
respectively). While AGT rs699 TC genotype was associated with 2.96 folds higher
risk of Covid-19 infection (TC vs.TT, CC OR =2.96, 95%CI = 1.12–6.44; p = 0.02).
The AGT rs699 was not associated with the severity of infection. Among
outpatients, benign conditions were associated with a lower risk, however older age
males and comorbidities increased the risk. We concluded that the genetic variant of
rs2106809 ACE2 in males was significant with a risk of infection and severe clinical
course because it could be located on the X-chromosome, and at the same time AGT
rs699 polymorphism had an impact on the increased risk of Covid-19 but had no
relation with the severity of Covid-19.

The risk of breast cancer development is believed to be attributed to the alterations
of a number of key biological components. Within this context, elevated levels of
some chemokines that act as growth factors and can promote cancer development.
The current study was designed to evaluate CXCL3 (a chemokine C-X-C Motif
Ligand 3) and leptin (a peptide hormone synthesized by adipose tissue with cytokine
activity) serum of Iraqi breast cancer patients in comparison to healthy controls. A
total of 90 participants consisted of 60 patients diagnosed with breast cancer and 30
healthy women as control group were enrolled into this case-control study. Venous
blood samples were collected from all participants to evaluate CXCL3 and leptin
serum levels using ELISA. The results demonstrated significantly (P≤0.001) higher
mean levels of CXCL3 and leptin in breast cancer patients (1.19±0.10 ng/mL and
130.44± 3.72pg/mL) compared to those of their healthy counterparts (0.430±
0.02\ng/mL and 57.1± 3.2pg/mL respectively). Interestingly, vast majority of the
assessed breast cancer cases (up to 95-98%) showed to have elevated serum levels of
both of the assessed potential biomarkers (CXCL3 and leptin). The present study
results suggest an association of both CXCL3 and leptin in breast cancer
pathogenicity. This supports the possibility of utilizing these potential biomarkers for
breast cancer early detection and diagnosis.

Female reproductive aging is a normal phase of life that eventually leads to
menopause and reproductive senescence. The current experimental investigation
was intended to study zinc supplementation effects on early embryonic development
and neonates in 26-28 weeks old female mice. In this investigation, 80 mature
female mice were used that were divided into two groups of forty each. Two control
groups received distilled water, while two Zn groups were given 0.115 mg/kg/day
Zn orally daily during 2-3 estrous cycles. The female mice were all mated with adult
males. Twenty female mice from both the control and Zn groups were euthanized by
CO2 gas inhalation, and then a longitudinal incision in the abdomen of each female
mouse was performed and uterine horns and oviducts were detached from the body
in order to obtain two-cell embryos. On the other hand, 20 pregnant mice from each
group were permitted to complete their pregnancy until birth and then their neonates
were collected for macroscopic examination. The findings showed that the Zn
supplementation significantly (P≤0.01) improved the mean embryonic development
and the quality of 2-cell stage embryo grade A. Whereas, it decreased the mean
embryonic development of 2-cell stage embryo grade D in aged female mice
significantly (P≤0.01) in comparison with aged control groups. Also, the count and
quality of neonates from Zn-treated aged female mice enhanced significantly
(P≤0.01) as compared to non-treated aged female mice. It was concluded from these
findings that the Zn can improve embryonic development and neonate count and
quality in aged mice.

Staphylococcus haemolyticus is one of the most frequently isolated coagulasenegative
staphylococci. The ability to form biofilm is considered as one of the most
important virulence factors of coagulase negative staphylococci. There is only
limited knowledge of the nature of S. haemolyticus biofilms. This study was aimed
at evaluating the ability of S. haemolyticus strains to produce biofilm in the presence
of copper oxide nanoparticles (CuONPs). The biological synthesis of nanoparticles
is an environmentally friendly approach for large-scale production of nanoparticles.
Copper oxide nanoparticles were produced in the current study from the S.
haemolyticus viable cell filtrate. UV-visible (UV-Vis) spectroscopy, X-ray
diffraction (XRD), atomic force microscope (AFM), field emission scanning
electron microscope (FE-SEM), energy-dispersive X-ray spectroscopy (EDX) and
zeta potential (ZP) analysis were used to analyze the newly synthesized CuONPs.
Our findings revealed that at minimum inhibitory concentration (MIC), CuONPs
showed remarkable inhibition on the biofilms produced by multidrug resistant
(MDR) S. haemolyticus isolates.

The primary objective of this study was to measure the expression profile of the
signal transducer activator transcription 1 (STAT1) in the circulatory leukocytes of
non-pregnant/pregnant ewes and test the possibility that it could be useful for
detecting early pregnancy. Whole blood was collected from 20 ewes (control) and
another 5 samples were taken on days (15, 25, 35, and 50). Also, blood was
collected from 30 ewes on day 15 post insemination (PI) and another 10 samples
were taken on days (25, 35, and 50) PI. Total RNA was isolated from peripheral
blood leukocytes (PBLs), and STAT1 expression levels were determined by
quantitative real-time PCR (qRT-PCR). Gene expression for STAT1 mRNA was 5.8-
fold and 5.1 times higher in gravid as opposed to non-gravid ewes. The reliable cutoff
point > 1.45 was established using the receiver operating characteristic (ROC)
curve, and the accuracy (Acc) for detecting pregnancy was 82%, 93%, 70% and
60%, and the sensitivity (Se) was 83%, 80%, 60% and 33% and Specificity (Sp)
95% on days 15, 25, 35 and 50, respectively. The mRNA expression was lower in
ewes that control non-pregnant than pregnant ewes on days 15 and 25. So The best
period to detect pregnancy was 15-25 days PI.

Burn infections are a serious concern for patients with burn injuries, as they can
lead to significant morbidity and mortality. The present study was designed to
evaluate the chitosan activity against five pathogens collected from burn infections
(Escherichia coli ZE15, Acinetobacter bummani ZA2, Klebsiella pneumonia ZK3 and
Pseudomonas aeruginosa ZP17, Staphylococcus aureus ZS2). Chitosan was produced
in solid-state fermentation using corn meal supplemented with 2% of shrimp shell
chitin. The degree of deacetylation of chitosan was 79.5% and the FT-IR spectrum
(4000 to 400) cm-1 gave IR spectra similar to that of the commercial chitosan. The
produced chitosan showed a significant inhibitory ability from the concentration of
10 mg/ml to 2 mg/ml. The M.I.C. and S.I.C were varied between the isolates; for P.
aeruginosa ZP17 and Staph. aureus ZS2, the M.I.C and S.I.C were 1.6 mg/ml and of
1.4 mg/ml respectively, while for E. coli ZE15, Kl. pneumonia ZK3 and A. bumannii
ZA2 were 1.4 mg/ml and 1.2 mg/ml. Furthermore, this study showed an the important
role of the produced chitosan as an antibiofilm agent to reduce the biofilm formation
for the tested isolates. However, the strongest antibiofilm activity was against E. coli
Z.E15 with 55.2%. Moreover, four potential formulas containing chitosan with
concentration of 1.6 mg/ml were tested. A formula containing polyvinyl alcohol,
vaseline and chitosan to create a cream showed the best results in comparison with
the four-formula used in this study. This formula was added to pads of thick cellulosic
filter paper to treat a mouse model with full thickness cutaneous burn to assess the
benefits of treating with a chitosan dressing. The healing process was examined and
results showed a signs of remodeling stage by day four and a scar tissue formation by
day nine

This paper used argon plasma jets to prepare CuO nanostructures. Several
techniques, including UV–Vis spectroscopy, X-ray diffraction (XRD), X-ray energy
dispersive spectroscopy (EDS), and scanning electron microscopy (SEM), were used
for the characterization of the prepared CuO nanoparticles. UV–Vis spectroscopy
analysis confirmed that the CuO nanostructures have an energy band gap of 2.7 eV.
The XRD analysis showed that the CuO nanostructures have an average crystallite
size of 36 nm. Furthermore, the results of the EDX examination demonstrated the
creation of CuO nanostructures of high purity. The scanning electron microscope was
used to analyze the surface morphology, showing a high agglomeration rate.
According to SEM analysis, the average diameter of CuO nanoparticles was 10 nm.

In this work, aluminium-doped zinc oxide (AZO) nanostructure at 0.3 wt% and 0.5
wt% Al was synthesized using the pulse-laser ablation technique in liquid(PLAL)
using pulsed Nd: YAG laser of a fundamental wavelength of (1064 nm). The process
was done in the absence and presence of an external magnetic field. The deposited
AZO nanostructures by drop-casting on etched-Si wafers were examined by different
techniques. The XRD test illustrates enhancing the crystallinity of the prepared thin
films by applying an external magnetic field. The FESEM images displayed the
change of nanostructure to nano-sheets of high surface area after using a 77.2 mT
permanent magnet placed behind the target during the ablation process. The gas sensor
based on the AZO nanostructures has higher sensitivity against NO2 than H2S.
Increasing the Al ratio from 0.3 wt% to 0.5 wt% changed the properties of the
prepared samples to have small porosity and small surface area, which negatively
affected the properties of the sensor

Mineralogical and geotechnical properties used to analyse the swelling potentials
of Al-Hartha City. According to mineralogy, montmorillonite is a dominated clay
mineral (33.61%) followed by montmorillonite-chlorite (33.34%), kaolinite (9.18%)
and illite (5.38%). While calcite, Quartz, Feldspar, and dolomite are non-clay minerals
that are also present. According to geotechnical analysis, the percent of clay range
between 9-42% with an average of 25.5%, silt 55-80% with an average of 67.5% and
sand 0-17% with an average of 8.5%. While liquid limits and plasticity index are,
respectively, 10–25% with an average of 17.5% and 35%–51% with an average of
43%. According to the unified soil classification system (USCS), these soils are
mainly low plasticity lean clay soils (CL) and 10% classified as medium stiff elastic
silt (MH). According to activity values, soils are primarily inactive-(70%), normally
active-(20%), active-(10%), and their consistency is plastic. according to an
assessment of soil expansivity based on index properties and activity, a significant
amount of the soil is expansive. Additionally, there is an agreement between the
results of the mineralogical tests performed on these soils and the results of the
measures of soil expansivity obtained from the evaluation of the swelling of the soil
based on assessments of its index properties.

The Kumait oil field is located in the Maysan Governorate southeastern Iraq, which
was studied and interpreted by using 2D and 3D seismic data provided by the Oil
Exploration Company using Petrel software. The study concerned the Mishrif
Formation belongs to the Cretaceous Age. The reflector was detected based on
synthetic seismograms and well logs for Kt-1 well. Structural maps (two-way time,
velocity, and depth) were derived from seismic reflection interpretations to show
several structural features, such as four isolated irregular enclosures representing the
Kumait structure plunging NW-SE and demonstrating that the Kumait oil field is
influenced by the Najd fault system trending NW-SE. The stratigraphic interpretation
used the variance attribute to delineate the edge of the fault, which extended from the
Mishrif Formation with a depth of 3090m and used the Direct Hydrocarbon Indicators
(DHI) to identify the stratigraphic features in the research region and the extraction of
seismic attributes. The applied seismic attributes, such as the instantaneous phase,
show dim spots, flat spots, and mounds and is followed by down-lap; the
instantaneous frequency, which offers low-frequency areas indicating a high
probability of hydrocarbon accumulation; and the RMS amplitude, which shows high
amplitude in the seismic data that conforms to the structure and confirms the presence
of hydrocarbon.

Nine earthquakes inside Mesopotamia Plain from 2016 to 2018 were analyzed.
Three seismic networks have been relied on to relocate these events and know their
responsible fault. These networks are; Mesopotamian Seismological Center, Al-
Refaei Seismic Array and Iranian Seismological Center. The results showed that the
root mean square (RMS) values for all relocated events ranged between 0.002-0.997.
The results of the error ellipse ranged from 0.24 - 4.17 km with longitude and 0.76 -
8.24 km with latitude. The new locations of these events are on or near the Ramadi-
Musaiyib Fault. This means that the Ramadi-Musaiyib Fault, which belongs to the
Najd fault system, is currently in reactivation.

This paper emphasizes on examining the impact of a magnetic field, and porous
medium on the non-Newtonian Jeffery nanofluid flows due to metachronal waves
induced by ciliated structures that covering the inner walls of the symmetric channel.
The governing equations namely continuity, motion, energy and nanoparticles
concentration are formulated with suitable boundary conditions and simplified
depending on the assumption of long wavelength and low Reynolds number. The
simplified equations are solved by using Mathematica program. Further, these
analytical solutions for velocity profile, temperature, concentration profiles and
streamlines are graphically elucidated and discussed in detail. we concluded that the
Hartman number and permeability parameter have opposite effect on the flow
characteristics. Moreover, the Jeffery parameter????1 has an increasing impact on the
velocity profile whereas the dimensionless eccentricity of ellipse parameter ????
decreases the velocity profile of the fluid.

This study is concerned with analyzing the peristaltic flow of Bingham fluid through
an irregular tube with a short wavelength “relative to channel width” and using the
governing equations of Bingham fluid in the Navier-Stokes equations in the
Cartesian coordinate system. Significant results of the problem were obtained and
analyzed using the Wolfram-Mathematica Computational Notebook.

This paper constructs and generalizes the numerical Runge-Kutta-Mohammed
(RKM) method for solving twelve-order ordinary differential equations (ODEs). The
novel contribution of this study is the development and generalization of the
numerical RKM methods for solving ODEs of the order of less than a tenth. The
algebraic order conditions (OCs) for the proposed RKM method are derived up to
order thirteen using Taylor expansion. Then, the constructed method has been derived
from these order conditions. However, the proposed numerical RKM method has been
evaluated at some implementations and compared to an existing Runge-Kutta (RK)
method to determine the method's viability. Moreover, this comparison demonstrates
the proposed direct method is more efficient than the classical method in terms of
efficiency and accuracy. Also, numerical implementations are used to prove the
efficiency and time complexity of function evaluations. This direct RKM method is a
suggested technique for solving ODEs of twelve orders which has great features like
a direct and efficient method. Consequently, the proposed method requires less time
complexity of computation than other methods

The present paper shows a numerical comparison by using the number of the
following criteria: mean squared, root mean Square, mean absolute, and relative mean
squared error values between the methods, namely maximum likelihood and
Bayesian estimators for the two parameters of the exponentiated exponential
distribution. In estimating the maximum likelihood, The equations cannot be solved
directly, Then Newton-Raphson method is used. Because of Bayes estimators under
scale invariant squared and weighted composite linear-exponential loss functions the
ratios cannot be simplified in a closed form. So, we use Lindley approximation.
MATLAB program is used to display the results

In this paper, we introduce and discuss an extended subclass〖 Ą〗_p^*(λ,α,γ) of
meromorphic multivalent functions involving Ruscheweyh derivative operator.
Coefficients inequality, distortion theorems, closure theorem for this subclass are
obtained.

Fixed point theory is not only essential in mathematics but also to a vast array of
applications. In this approach, we provide some fixed point theorems for fuzzy
normed space. The triangle property of a fuzzy norm is introduced first. This property
is used to demonstrate some fixed point solutions for self-mappings in fuzzy normed
space. To demonstrate the importance of the obtained results, an application for the
existence of a solution to the ordinary differential equation and the Fredholm integral
equation is constructed.

In this article, two issues related to the design of the experiment are investigated;
namely the inspection times and optimal censoring. In the first issue, we study four
different approaches to determine the inspection times, namely; pre-specified, equally
spaced, optimally spaced, and equal probability using two optimality criteria. In the
second issue, we identify the optimal censoring scheme by finding the expected
numbers of removals or proportions that attain a specific optimality criterion using
two optimality criteria considered. Numerical comparisons using the Monte Carlo
simulations are provided of the inspection times, optimum control schemes issues for
different parameters and different sample sizes. Statistical measures such as bias and
root mean square error for both pre-specified and equal space methods are calculated
and the inspection times for different values of the censoring percentage h are
obtained.

Many researchers discussed distributive modules and their properties. In this work,
the distributive property will be studied over semimodules. Some of the results
obtained in homomorphisms of distributive modules are generalized. Some conditions
were needed like concept subtractive, i-regular, k-regular, and k-cyclic, to get good
results. The relationship between the distributive semimodule over the local semiring
and the hollow semimodule was obtained, and the relationship between the
distributive semimodule and the homomorphisms distributed over the intersection
process or the inverse image distributed over the addition

Let ???? be a commutative ring with 1 and ???? be a left unitary R-module. In this paper,
we give a generalization for the notions of compressible (retractable) module. As well
as, we study closed (St-closed) compressible and closed (St-closed) retractable.
Furthermore, some of their advantages, properties, categorizations and instances have
been given. Finally, we study the relation between them.

The Gumbel max distribution is one of the most important statistical distributions
because it has many applications, especially in the field of water research and the
prediction of earthquakes and volcanoes. This work includes a comparison of
several Shrinkage Bayesian methods, namely the Shrinkage Bayesian Square Loss
Function, Shrinkage Bayesian Lenix Function, and Shrinkage Bayesian Unix
Function to estimate the distribution parameter. The research also includes several
simulated experiments according to the sample size change and the real value of the
distribution parameter. The number of experiments is 15 simulated experiments
based on the difference sample size and true distribution parameter values. The
results of the simulation experiments are compared depending on each of the
absolute least difference criteria (????????????????) and the mean squared error (????????????). The
comparison results show that the estimation method is affected by the sample size,
and the real value of the distribution parameter. The best estimation method is the
Shrinkage Bayesian Lenix Function. The Bayesian methods can be applied to other
statistical distributions such that the Lindley Weibull distribution and logistics
distribution.

An R-module M is called polyform if every essential submodule of M is rational.
The main goal of this paper is to give a new class of modules named P-polyform
modules. This class of modules are contained properly in the class of polyform
modules. Several properties of this concept are introduced and compared with those
which is known in the concept of polyform modules. Another characterization of the
definition of P-polyform modules is given as an analogue to that in the concept of
polyform modules. So we proved that a module M is P-polyform if and only if
HomR (
K
N
, M)= 0, for each essential submodule N of M, which is pure in M, and a
submodule K of M, with NKM. The relationships between this class of modules
and some other related concepts are discussed such as monoform, QI-monoform,
monoform, essentially quasi-Dedekind, essentially prime, purely quasi-Dedekind,
ESQD and St-polyform modules. Furthermore, purely St-polyform is defined and its
relationship with the P-polyform module is studied.

Estimation for the reliability of a parallel redundant system with independent stress
and strength Burr distribution (type ???? ) probability density functions is considered.
Estimation of the reliability parameters is conducted according to the non-Bayesian
estimation methods, namely the maximum likelihood and shrinkage methods. The
Bayesian estimation is also considered using the Jeffery and Gamma priors with
squared error, quadratic and weighted loss functions. Finally, the reliability estimate
is calculated and the best method for estimation for each case is given using the mean
squared error criteria.

In this work, the right coprime factor for balancing and truncating unstable systems
is extended to parameter-varying multidimensional systems employing recent works
on coprime factor model reduction of one-dimensional uncertain systems. Since the
balanced truncation method cannot be applied directly to unstable systems, state
feedback gains should be computed and incorporated in order to stabilize the given
system and to be able to apply the balanced truncation technique via defining the socalled
stable coprime factor, as coprime factorization overcomes the stability
condition required for model reduction. Parameter-dependent state feedback and
parameter-dependent Gramians are considered in this work yielding less conservative
techniques. In addition, the Gramians are defined as block diagonal matrices, which
are partitioned according to the structure of the multidimensional systems. The
application to a simulation example demonstrates the applicability and validity of the
proposed reduction approach leading to small error bounds between the full and the
reduced models.

Medical diagnosis is the process of identifying the presence of a specific disease.
Medical images play an important and major role in helping the doctor and specialist
in the process of diagnosing the patient's condition. As a result of the technological
development taking place in the fields of artificial intelligence, which processes data
quickly and efficiently by responding to various conditions and situations, providing
a great deal of flexibility and accuracy, it is widely used in helping to diagnose
diseases. Fuzzy logic was used to find the number of cells in medical images, where
the increase or decrease in the number of cells beyond the normal limit indicates the
presence of a specific disorder or disease.
This paper aims to use fuzzy logic and the Image J system to determine the appropriate
mechanism and method for counting cells according to their size in the medical image,
where a set of basic steps are implemented on the image by using the Image J system.
This includes converting to mask, outlining, filling holes, watershedding, setting
measurements, and analyzing particles. After that, using fuzzy logic to determine the
best appropriate methods for counting cells in medical images based on size, enter a
single random value for size, and cells smaller than that value are ignored. The area
and perimeter of cells are accounted for.

Binary relations or interactions among bio-entities, such as proteins, set up the
essential part of any living biological system. Protein-protein interactions are usually
structured in a graph data structure called "protein-protein interaction networks"
(PPINs). Analysis of PPINs into complexes tries to lay out the significant
knowledge needed to answer many unresolved questions, including how cells are
organized and how proteins work. However, complex detection problems fall under
the category of non-deterministic polynomial-time hard (NP-Hard) problems due to
their computational complexity. To accommodate such combinatorial explosions,
evolutionary algorithms (EAs) are proven effective alternatives to heuristics in
solving NP-hard problems. The main aim of this study is to make a close
examination of the performance of the EAs where modularity and modularity
density are selected as two different objective functions. Topology-based modularity
and topology-based modularity density are designed to examine the detection ability
of the EAs and to compare their performance. To conduct the experiments, two
yeast Saccharomyces cerevisiae PPINs are used and evaluated under nine evaluation
metrics. The results reveal the potential impact of the topology-based modularity
density to outperform the counterpart modularity functions in almost all evaluation
metrics.

Many questions and answers about Islamic law are scattered on the internet and
have been explained repeatedly by various sites. One solution is presented by the
website www.piss-ktb.com, which creates a web-based source of information in the
form of Frequently Asked Questions (FAQ). However, web-based FAQs have a
weakness: users still have to browse through the available questions one by one
according to the questions they want to know the answers to. Browsing through
thousands of FAQs is inefficient and exhausting.
Thus, a chatbot system can become a better alternative to the FAQ website. Still,
chatbots are difficult to use because most of their conversations are hard to understand.
A single character error will cause the system to misunderstand its meaning. In reality,
users expect a chatbot that can understand everyday language. Thus, it is necessary to
develop a chatbot system that can understand various common sentence combinations
in everyday language and understand the meaning of words. In addition, it should be
able to predict answers automatically to various kinds of questions and requests, even
though the initial training data is relatively low. Therefore, this study aims to develop
a system that can provide answers automatically based on user commands in natural
language using Global Vectors for Word Representations (GloVe), Convolutional
Neural Networks (CNN), and Transfer Learning techniques. The result shows that the
use of transfer learning and the Nadam optimizer can improve the system’s
performance.

The field of cloud-based electronic government (CBEG) is still expanding. Some
conflicting results have been published regarding the factors influencing the adoption
of CBEG. The paper aims to review the literature and understand the status of CBEG
and the factors behind its adoption. Specific keywords related to the topic were used
to extract articles from reliable databases. An extensive review was done on a total of
41 articles published between 2016 and August 2022. The findings showed that there
has been an increase in the number of articles related to CBEG, specifically in the
public sector. The review also showed that the quantitative approach outperformed
other approaches. The Technology Organization Environment (TOE) framework and
Diffusion of Innovation (DOI) were used in the majority of the reviewed papers.
Structural equation modeling (SEM) was applied intensively in the reviewed papers.
The most important factors for CBEG adoption are top-level management support,
security, compatibility, relative advantage, complexity, and privacy. Future studies are
recommended to expand the scope of inclusion criteria, conduct more empirical
studies on CBEG, and deploy mediators and moderators. Empirically, combining more
theories can explain more about the adoption of CBEG. The findings help decisionmakers
better understand the predictors of the successful adoption of CBEG.

The shear wave sonic (S-wave) log data is essential for identifying the reservoir's
geomechanical properties, which is an important factor for the drilling, completion,
and optimization processes, where obtaining S-wave requires capital investment and
reduces the cost. In this paper, we used the multi-layer perceptron (MLPR) and the
gradient boosting regression (GBR) to predict the missing S-Wave log data for the
Volve Oil Field in the North Sea. Prescriptive and predictive analysis were carried
out in series to achieve a high blind data accuracy rate of 0.943 and 0.982 for the
multi-layer perceptron regression and the gradient boosting regression, respectively.
It was observed that the gradient-boosting algorithm achieved higher accuracy than
the MLPR algorithm for the limited dataset. It was also found that hierarchical
clustering can reveal information regarding the feature's importance similar to the
relevant AI tools, which makes hierarchical clustering a faster tool in eliminating the
nonimportant inputs from the dataset while the use of artificial intelligence tools
showed a significant effect in predicting the missing values of the sonic wave log
and the neutron porosity log in an efficient way by selecting the relevant important
features.

An accumulation of aberrant cells called a brain tumor is the outcome of
unregulated cell division. Brain cancers can be found using magnetic resonance
imaging (MRI). The exponential growth of deep learning networks has allowed us to
tackle complex tasks, even in fields as complicated as medicine. However, using these
models requires a large corpus of data for the networks to be highly generalizable and
have high performance. This dearth of training data makes it critical to explore
methods such as data augmentation. In this sense, data augmentation methods are
widely used in strategies to train networks, and with small data sets being vital in
medicine due to the limited access to data, this work aims to identify the best
classification system by considering the prediction accuracy in this vein. Data
augmentation is performed on the database and fed into the three convolutional neural
network (CNN) models. A comparison line is drawn between the three models based
on accuracy and performance on the Inception v3 models, Mobile Net V2, and
Squeeze Net network for brain tumor detection and classifying 350 brain MR images.
The statistical methods were modified in order to evaluate these algorithms. With
0.992% accuracy, 0.993% recall, 0.989% precision, and 0.994% F1 score, the Squeeze
Net model performed the best. The Mobile Net V2 model, which had an accuracy of
0.964%, came next. When the research's findings were compared to those of related
studies in the literature, they revealed better success rates than those of the majority
of investigations.

Credit card fraud has become an increasing problem due to the growing reliance
on electronic payment systems and technological advances that have improved fraud
techniques. Numerous financial institutions are looking for the best ways to leverage
technological advancements to provide better services to their end users, and
researchers used various protection methods to provide security and privacy for
credit cards. Therefore, it is necessary to identify the challenges and the proposed
solutions to address them. This review provides an overview of the most recent
research on the detection of fraudulent credit card transactions to protect those
transactions from tampering or improper use, which includes imbalance classes,
concept drift, and verification latency problems using machine learning and deep
learning. It also provides valuable information for academic and industrial
researchers and opens new avenues for research aimed at developing robust fraud
detection systems.

The importance of a survey of Arabic root extraction algorithms is that it can
provide a comprehensive overview of the current state of the field and the various
approaches used for this task. This can be helpful for academics and professionals
working on Arabic natural language processing projects, since it enables them to
comprehend the advantages and disadvantages of several approaches and select the
one that is best suited to the task at hand. A survey can also help to pinpoint areas that
require more research and can serve as a springboard for fresh studies in this area. In
general, a survey can enhance the study of Arabic root extraction and improve the
quality of Arabic natural language processing tools. Researchers can use this survey
to compare the performance of several algorithms and select the best one for their
particular application. In this survey, the majority of the root extraction algorithms for
the Arabic language were studied with a focus on identifying their advantages and
disadvantages, as well as their accuracy. The algorithms were classified into various
approaches. The importance of root extraction in Arabic is explored, along with its
uses and applications. Also, the issues that still require research and improvement in
order to improve the efficiency of algorithms were highlighted. For instance, one issue
that the algorithms encounter is the absence of a unified list that encompasses all roots,
patterns, and affixes. Additionally, more rules are needed to regulate the process of
root extraction.

Doubts arise about the originality of a document when noticing a change in its
writing style. This evidence to plagiarism has made the intrinsic approach for
detecting plagiarism uncover the plagiarized passages through the analysis of the
writing style for the suspicious document where a reference corpus to compare with
is absent.
The proposed work aims at discovering the deviations in document writing style
through applying several steps: Firstly, the entire document is segmented into
disjointed segments wherein each corresponds to a paragraph in the original
document. For the entire document and for each segment, center vectors comprising
average ???????? − ???????????? weight of their word ???? − ???????????????????? are constructed. Second, the
degree of closeness is calculated through applying Cosine similarity to measure for
each segment, the deviation of its center vector from the center vector of the entire
document. Additionally, word n-gram length will be investigated to show its effect on
the proposed system performance wherein, center vectors are computed considering
word n-grams for different values of n (n= 1, 2, and 3).
Performance evaluation of the proposed method was accomplished through the use of
Precision, Recall, F-measure, Granularity, and Plagdet as evaluation measures.
Moreover, PAN-PC-09 and PAN-PC-11 were used for detecting intrinsic plagiarism
as evaluation corpora. It is shown that the proposed approach has achieved results that
are comparable to the state-of-the-art methods. Positive impact was observed through
discovering deviations in document writing style by computing weight vectors
dissimilarity rather than calculating the difference between the word n-grams that
exist in segments and their corresponding word n-grams in the suspicious document.
Furthermore, when considering the length of word n-gram, better results were
recorded for system performance when word bi-grams was used compared to word
uni-grams and word tri-grams.

Many authors investigated the problem of the early visibility of the new crescent
moon after the conjunction and proposed many criteria addressing this issue in the
literature. This article presented a proposed criterion for early crescent moon sighting
based on a deep-learned pattern recognizer artificial neural network (ANN)
performance. Moon sight datasets were collected from various sources and used to
learn the ANN. The new criterion relied on the crescent width and the arc of vision
from the edge of the crescent bright limb. The result of that criterion was a control
value indicating the moon's visibility condition, which separated the datasets into four
regions: invisible, telescope only, probably visible, and certainly visible. This
criterion was used on the dataset for ANN learning to compare its efficiency with the
actual moon visibility events.

This research aims to investigate the color distribution of a huge sample of 613654
galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift
of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at
redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been
extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have
been produced and analysed using a Matlab code for the main sample as well as all
five subsamples. Then a bimodal Gaussian fit to color distributions of data that have
been carried out using minimum chi-square in Microsoft Office Excel. The results
showed that the color distributions of the main sample and all subsamples are bimodal.
This indicates that the color distribution is an ideal tool to differentiate between young
and old galaxies. The young and blue star-forming galaxies are represented by one of
the two peaks, while the old and red non-star-forming galaxies are represented by the
other peaks of the color distribution.