Wasit Journal for Pure Sciences

In this study, a new two-parameter lifetime distribution called the Odd Chen–Gamma distribution is
proposed. The probability density function, cumulative distribution function, reliability function, and several
important statistical properties of this distribution are derived. Bayesian analysis is performed using two prior
functions for the unknown shape parameter: the exponential (informative) prior and a hypothetical prior. The Bayesian
estimator of the shape parameter is obtained under two asymmetric loss functions, namely the De-Groot and the Al
Bayyati loss function. A simulation study is conducted to evaluate the performance of the Bayesian estimators by
examining their mean squared errors under different parameter values and various sample sizes. All numerical
computations and simulations were performed using MATLAB 2024b.

Our work included studying some subclasses of functions (univalent - multivalent) that are close to
convex. which is divide into two parts. First part, we discussed the properties of parameter estimates, the
implication relation, distortion theorem, and the radius of convexity of functions a subclass of univalent. Second
part of this article, we discuss the same properties for subclasses of multivalent functions defined using the Salagen
operator in the unit disc.

This paper presents a truncated series of Fermat polynomials as a quick and effective way to solve
fractional differential equations numerically. The suggested method converts the fractional differential equation
with its beginning conditions into a set of algebraic equations. This transformation is achieved by using the Galerkin
spectral technique in conjunction with the matrix of operations for fractional-order derivatives according to Caputo's
definition of Fermat polynomials. The precision, efficiency, and stability of the suggested approach are illustrated
through a series of numerical examples. The results also show excellent compatibility with exact solutions even
when the exact solution is non-polynomial. In addition, comparisons with previously reported methods confirm the
higher performance and reliability of the current strategy.

The rapid digitalization of educational environments has led to the large-scale generation of student
related data from online learning platforms, intelligent tutoring systems, and virtual classrooms. While such data
enable advanced predictive analytics and personalized learning, they also raise critical concerns related to data
privacy, fairness, and ethical use. To address these challenges, this paper proposes an Adaptive Federated Learning
(AFL) framework for fair and privacy-preserving educational analytics. Unlike conventional centralized learning
approaches, the proposed framework allows multiple educational institutions to collaboratively train predictive
models without sharing raw student data. Moreover, AFL incorporates a fairness-aware adaptive aggregation
mechanism that dynamically adjusts client contributions based on both local predictive performance and fairness
indicators. This strategy improves model robustness and reduces demographic bias under heterogeneous and
potentially adversarial data distributions. The effectiveness of the proposed framework is evaluated on three publicly
available educational datasets—Student Performance, Predict Students’ Dropout and Academic Success, and the
Open University Learning Analytics Dataset (OULAD)—under both normal and label-flipping attack scenarios.
Experimental results demonstrate that AFL achieves performance comparable to centralized models while
consistently improving fairness and resilience against adversarial behavior. These findings highlight the potential of
AFL as a trustworthy and ethically aligned solution for decentralized educational data analytics.

Proteus mirabilis is an opportunistic pathogen implicated in urinary tract infections, with virulence
largely attributed to factors such as ZapA, a metalloprotease, and UreR, a regulator of urease activity.
Lipopolysaccharides [LPS] are a vital ingredient of the outing Gram-negative bacteria membranes, functioning in
both structural integrity and pathogenesis. However, the role of endogenous LPS for expressing the genes of virulence
factors in P. mirabilis remains unclear. This study objected to assess the LPS extract from P. mirabilis on the
expression of ZapA and UreR genes within P. mirabilis cells. LPS was isolated from cultured P. mirabilis using a hot
phenol-water extraction method and applied to fresh bacterial cultures on different levels. Entire RNA was obscure,
and expressing the ZapA and UreR quantified via qRT-PCR, with 16S rRNA used as the internal control. Comparative
analysis between treated and untreated groups had achieved to investigate the LPS exposure on the target genes.
Exposure to extracted LPS significantly led to an upregulation of ZapA andUreR genes expression. These findings
suggest LPS may act as an autocrine or paracrine signaling molecule modulating virulence gene expression in P.
mirabilis. The results demonstrate that LPS derived from P. mirabilis can modulate the core virulence-associating
gene expression, ZapA and UreR, potentially influencing the pathogenicity of P. mirabilis.

Aging-related decline in hematopoietic and platelet function is a hallmark of DNA repair deficiency
syndromes, yet the impact of metabolic and pharmacological interventions on platelet biology in this context remains
unclear. This study addresses this gap by investigating whether dietary restriction (DR) and myostatin/activin
blockade through soluble Activin Receptor Type IIB (sActRIIB) can modulate platelet activation markers—GPIbα
and P-Selectin—in a progeroid mouse model (Ercc1Δ/-). While DNA repair-deficient mice exhibited significantly
reduced GPIbα expression compared to wild-type controls, sActRIIB treatment showed a modest, though non
significant, improvement. In contrast, DR alone or combined with sActRIIB had negligible effects. P-Selectin levels
remained unchanged between mutant and control mice; however, sActRIIB treatment significantly suppressed its
expression, indicating a potential anti-inflammatory effect. These findings suggest that myostatin/activin pathway
inhibition may offer a partial therapeutic benefit in modulating platelet activation in progeroid models, whereas
dietary restriction appears insufficient. It is important to conduct further studies to investigate specific, combinatorial
application in the restoration of platelet homeostasis in DNA repair-deficient aging diseases.

Pseudomonas aeruginosa is an important Gram-negative opportunistic pathogen responsible for a
large fraction of nosocomial infections, usually associated with high morbidity and mortality. Its remarkable
plasticity, innate resistance mechanisms, and ability to efficiently form a biofilm also explain its viability and the
ongoing difficulty in treatment. This work was developed to characterize clinical P. aeruginosa isolates on the basis
of its clinical distribution between the infection types and biofilm-forming capacity, to profile the profile of key
virulence genes (lasB, toxA, algD, pvdA) and to characterize the susceptibility of isolates to antibiotics. The total P.
aeruginosa isolates obtained from the clinical sources (respiratory tract infections, burns, wounds, surgical site
infections, and catheter-associated infections) were 94, and collected from [Al Zahra Teaching Hospital in Kut]
during the period of [January 1, 2025 to July 30, 2025]. The isolates clearly showed moderate- to strong biofilm
formation with 81.9% of isolates being of high production. In addition, a significant amount of virulence genes was
detected, specifically lasB (86.2%), toxA (79.8%), algD (73.4%) and pvdA (69.1%). The antibiotic susceptibility
testing (n=94) revealed heterogeneous resistance; the most resistant antibiotic was Cefotaxime (46.7%) and the
second was Aztreonam (30.7%). Polymyxin B (4.0%) continued to be very effective. These observations illustrate
the extensive pathogenicity of P. aeruginosa and the strong necessity of ongoing surveillance and for developing
new antibiotic resistance targets for this antimicrobial multi-drug-resistant organism.

Drug–drug interactions (DDIs) are a major source of adverse drug events (ADEs) that are potentially
preventable in the healthcare system worldwide. The present literature lacks a comparative and rigorous synthesis.
The objective of our study was to systematically identify, appraise and synthesize evidence on the prevalence,
severity, types, and management outcomes of DDIs occurring between the private clinic and hospital settings, and
the factors that contribute to the occurrence of DDIs at the patient and system levels are the objective of our study .
PubMed, Scopus, Web of Science and Google Scholar were used for literature search from January 2015 to May
2026. Direct or indirect comparative data on DDIs in private clinic versus hospital outpatient or inpatient setting
was required for eligibility. Using the Newcastle–Ottawa Scale (NOS) as well as Cochrane RoB 2.0, risk of bias
was determined. Narrative synthesis and data extraction in tables were conducted. Forty-two studies (n ≈ 2.1 million
patient records) were included. The prevalence of DDI varied from 10.3%–67.4% in settings. The rates of clinically
severe DDIs were significantly higher in hospital than in private clinics (mean 28.4% vs. 15.7%) due to the higher
prevalence of multimorbidity and older age of inpatients. The detection rate for DDI, pharmacist interventions and
integration of CDSS were much lower at private clinics. The conclusion reported that the DDI are common,
clinically important, and occur in unique ways in both settings. Patient complexity results in higher severity DDIs in
hospitals, while structural limitations in private clinics result in under-detection. The need for targeted
pharmacovigilance,

In this study, a sustainable and environmentally benign methodology was developed for the synthesis
of titanium dioxide (TiO₂) nanoparticles utilizing Solanum melongena (eggplant) extract as a natural reducing and
stabilizing agent. The proposed biosynthetic route was intentionally designed to substitute conventional chemical
pathways that commonly involve hazardous precursors and high-energy consumption. The synthesized TiO₂
nanomaterials were subjected to comprehensive structural and morphological characterization through X-ray
diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and Fourier-transform infrared
spectroscopy (FTIR). XRD patterns verified the formation of a highly crystalline anatase phase with an estimated
mean crystallite size of approximately 13.6 nm. The FE-SEM micrographs revealed nearly spherical to quasi-spherical
morphologies with an average particle diameter of about 29 nm, indicating that the bio mediated process enabled
controlled nucleation and moderate particle-size homogeneity. The FTIR spectra exhibited characteristic Ti–O–Ti
stretching vibrations together with residual phytochemical functional groups originating from the eggplant extract,
confirming their involvement as surface-capping species that enhanced nanoparticle stability. In addition to the
structural investigation, the electrical sensing performance of the TiO₂ nanomaterials toward DNA molecules was
evaluated at ambient temperature. A comparative analysis between uncalcined and calcined (400 °C) TiO₂ samples
demonstrated a pronounced improvement in sensitivity following calcination. The thermally treated TiO₂ displayed
enhanced electrical conductivity, increased surface activity, and improved crystallinity, achieving DNA-sensing
sensitivities in the range of 45–70%, compared with 12–18% for the uncalcined samples. The observed enhancement
is attributed to the generation of oxygen vacancies and the phase transformation from amorphous to anatase, which
collectively facilitated more efficient charge transfer across the TiO₂–biomolecule interface.