This study aimed to identify the primary behavioral and health risk factors associated with the likelihood of myocardial infarction (heart attack) and to construct a probabilistic predictive model using binary logistic regression among patients attending cardiac centers in Aden Governorate. The study employed a cross-sectional design utilizing primary data collected from a random sample of 51 patients across cardiac centers in Aden hospitals between October 2025 and January 2026.The model included five independent explanatory variables: age, smoking, Qat chewing, hypertension, and diabetes mellitus. The results demonstrated that the estimated model possesses overall statistical significance (p = 0.005) and an excellent goodness-of-fit according to the Hosmer–Lemeshow test (p = 0.836). Wald test results indicated that hypertension, smoking, age, and diabetes mellitus are positively and significantly associated with an increased odd of occurrence. Hypertension emerged as the most influential predictor ({Exp}(B) = 16.057, p = 0.010), followed by smoking ({Exp}(B) = 5.346, p = 0.030), age ({Exp}(B) = 1.070, p = 0.048), and diabetes ({Exp}(B) = 1.063, p = 0.020), whereas Qat chewing demonstrated no statistically significant effect. The model achieved an overall classification accuracy of 78.4% with a high diagnostic sensitivity of 94.6%. The findings conclude that the binary logistic regression model exhibits excellent fit and high diagnostic precision, highlighting hypertension and smoking as the primary risk factors driving the increased odds of heart attacks in Aden.

This study aimed to build a database of the morphometric characteristics of the Wadi Rafad watershed (Shabwah Governorate, Yemen) by analyzing a Digital Elevation Model (DEM) with a spatial resolution of 10 m. The analysis was conducted using WMS 10 and ArcGIS 10.3 software, with the assistance of Global Mapper 13, in addition to a set of topographic and geological maps and satellite imagery of the watershed. The aim was to obtain the watershed's morphometric characteristics, including its spatial, morphological, topographic, and drainage network characteristics, to provide a digital database for future use. A descriptive approach was used to describe and analyze the watershed natural characteristics, while a quantitative approach was employed for spatial data analysis and producing digital maps. This involved calculating variables and morphometric characteristics and interpreting the results. Digital maps were produced showing elevations, slopes, rock units, and the tributary network. The topographical characteristics varied due to variations in their formation and development processes, as well as the different geological factors that formed them, particularly the lithological nature, geological structures, topographic features, and climate conditions. The watershed elevation ranges between 15 and 1679 m and slope of 0.21. Its covers an area of 650.6 km² with a length, width and perimeter of 38.9 km, 16.7 km and 153.3 km, respectively. Shape factor, circularity and Elongation ratio is 0.43, 0.35 and 0.74, respectively which indicates fine texture, elongated watershed shape and natural flood-lowering potential. The watershed has a drainage network of 7th order with an average drainage density of 2.92 km/km2, stream frequency of 9.9 /km2 and the dominate drainage pattern is dendritic. It is currently in a state of equilibrium. We recommend using a high spatial resolution DEMs to study its morphometric characteristics, which can be used for watershed management and other hydrological studies in future.

This research develops a generalized analytical framework to solve non-linear integro-differential equations of order n using a modified inverse operator. The study investigates two cases to demonstrate the versatility of the proposed operator. In the first case, a first-order model with a variable coefficient q(x) = x is analyzed, where the operator effectively integrates the linear structure by incorporating an exponential integrating factor into the framework. In the second case, the study addresses a second-order model with a constant coefficient q(x) = 1. By integrating this modified operator with the Adomian Decomposition Method (ADM), a robust recursive scheme is constructed that simplifies the computational process and preserves initial conditions. To overcome symbolic execution challenges and memory exhaustion, a discrete summation algorithm is implemented for the nonlinear terms. The methodology is supported by rigorous mathematical proofs of existence, uniqueness, and convergence based on the Banach fixed-point theorem. Numerical results via Mathematica software confirm high-order precision and rapid convergence, proving the scheme’s reliability for complex physical applications.  

Let G be a finite, simple graph and let S (G) denote the subdivision graph obtained by inserting one new vertex into each edge of G. A hub set of a graph H is a vertex set D⊆V(H) such that every two non-adjacent vertices of V(H)-D are connected by a path whose internal vertices all belong to D. The minimum cardinality of a hub set of H is the hub number h(H). In this paper, we study the hub number of subdivision graphs. We first record basic structural observations for hub sets and then obtain exact formulas for subdivisions of trees, paths, cycles, and stars. We also derive general bounds for h(S(G)) in terms of the order and size of G, give Nordhaus–Gaddum-type inequalities for subdivision graphs and their complements under natural connectedness assumptions, and discuss how complete and complete bipartite source graphs lead to extremal subgraph problems. Several examples are included to illustrate the results.

This study evaluated the quality and thermal stability of local and commercial vegetable oils by analyzing fatty acid-related indicators, acid value, and cholesterol content. The findings showed that all samples' fatty acid-related values with temperature. Local oils displayed comparatively low values, with Abyani sesame oil ranging from 0.193±0.017 to 0.267±0.056% and Yemeni almond oil ranging from 0.073±0.012% at 25 °C to 0.099±0.044% at 90 °C. Commercial oils showed higher susceptibility to thermal deterioration with higher values and quicker rises, especially commercial Saudi black oil (0.829 ±0.178 to 1.040±0.241) and Somalia sesame oil (0.146  ± 0.032 to 0.324 ± 0.062 %). Local oils had lower acid values; Yemeni almond oil increased from 1.571% mg KOH/g at 30 °C to 2.149±0.150% mg KOH/g at 90 °C, while Abyani sesame oil increased from 3.330±0.245 to 5.554±0.461 mg KOH/g. Commercial oils, displayed much higher values. For instance, commercial Somalia sesame oil from 7.254±1.787 to 8.964±2.456 mg KOH/g, while Saudi black oil stayed extremely high (16.69±4.365to 16.83±2.986 mg KOH/g), indicating greater hydrolysis and the generation of free fatty acids. Tehama sesame and Abyani Sesame oils had cholesterol contents of 26.53±1.735 and 26.34±2.489 ppm, respectively, which were comparatively constant and lower than other local oils. Commercial oils showed more variety, ranging from 22.42±1.676 Indian linseed to 27.28±1.983 ppm Saudi black oil. Local Yemeni fenugreek oil 38.13±1.897 ppm. Based on these results, this study compares thermal stability and quality indicators (free fatty acids, acid value, and cholesterol) of local versus commercial vegetable oils in Yemen as reliable indicators for assessing the quality and oxidative stability of sesame seed oils, with implications for quality and consumer health awareness.

Cephalosporins are among the most widely used antibiotics around the world to combat diseases of bacterial origin. The study and appreciation of antibiotics has become essential to ensure drug's quality, safety, and therapeutic efficacy. The objective of this research is to develop an simple, sensitive and cost-effective spectrophotometric method for the estimate four types of cephalosporin drugs,  containing a thiazole ring, such as; ceftriaxone ( CFX), cefotaxime (CFT), ceftazidime (CFZ), cefepime (CFP) in pharmaceutical formulations. The proposed method are based on coupling reactions between the above mentioned drugs and 2,4-dinitrophenylhydrazine reagent in alkaline mediums, to give stable colored complexes that can be measured accurately at the maximum wavelengths (λmax) 510, 505, 500 and 496nm, for CFX, CFT, CFZ and CFP respectivly. The optimum experimental conditions have been studied. The developed methods showed good linearity, Beer's law is obeyed in the concentrations range of 2 – 30, 4 – 33, 3 – 33 and 2.5 – 17 µg/mL for CFX, CFT, CFZ and CFP respectively with high correlation coefficients. Accuracy and precision were evaluated through recovery studies and repeatability tests, the molar absorptivity (ε), Sandell’s sensitivity (s), Limit of detection (LOD) and quantification limits (LOQ) for the studied drugs were calculated. Recovery studies shows that this method is accurate and can be successfully employed for the determination of the studied cephalosporin’s in quality control laboratories.

Unplasticized Polyvinyl Chloride (uPVC) is a vital structural thermoplastic whose macroscopic mechanical responses are governed by atomistic dynamics often inaccessible via traditional experimentation. This study aims to provide molecular-level insights into the macroscopic mechanical response and viscoplastic performance of amorphous uPVC. Atomistic Molecular Dynamics Simulations (MDS) were conducted using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) package and a reparametrized  CHARMM  force field.  Amorphous simulated cells were equilibrated through a rigorous multi-stage thermal protocol within the Isothermal-Isobaric (NPT) ensemble. Uniaxial tensile tests were performed at a constant strain rate across temperatures ranging from 200 K to 350 K.

Findings revealed that increasing temperature systematically reduced yield stress and significantly diminished material stiffness. Quantitative topological analysis demonstrated that initial elastic deformation is enthalpy-driven by non-bonded intermolecular interactions, whereas large strain hardening is entropy-driven, characterized by significant chain uncoiling and segmental alignment. This research establishes a predictive framework linking microstructural dynamics to macroscopic performance. The results confirm that elevated thermal energy facilitates molecular mobility and lowers energy barriers for conformational transitions, offering a robust contribution to the fundamental understanding of yield mechanisms in glassy thermoplastics and providing valuable insights for the design of polymer components under varying thermal conditions.