<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Due to its importance in physics and applied mathematics, the non-linear Sturm-Liouville problems
witnessed massive attention since 1960. A powerful Mathematical technique called the Newton-Kantorovich
method is applied in this work to one of the non-linear Sturm-Liouville problems. To the best of the authors’
knowledge, this technique of Newton-Kantorovich has never been applied before to solve the non-linear
Sturm-Liouville problems under consideration. Accordingly, the purpose of this work is to show that this
important specific kind of non-linear Sturm-Liouville differential equations problems can be solved by
applying the well-known Newton-Kantorovich method. Also, to show the efficiency of appl

Two molecular imprinted polymer (MIP) membranes for Levofloxacin (LEV) were prepared based on PVC matrix. The imprinted polymers were prepared by polymerization of styrene (STY) as monomer, N,N methylene di acrylamide as a cross linker ,benzoyl peroxide (BPO) as an initiator and levofloxacin as a template. Di methyl adepate (DMA) and acetophenone (AOPH) were used as plasticizers , the molecular imprinted membranes and the non molecular imprinted membranes were prepared.  The slopes and detection limits of the liquid electrodes ranged from -21.96 – -19.38 mV/decade and 2×10^-4M- 4×10^-4M, and Its response time was around 1 minute, respectively. The liquid  electrodes were packed with 0.1 M standar

ABSTRACT

Critical buckling temperature of angle-ply laminated plate is developed using a higher-order displacement field. This displacement field used by Mantari et al based on a constant ‘‘m’’, which is determined to give results closest to the three dimensions elasticity (3-D) theory. Equations of motion based on higher-order theory angle ply plates are derived through Hamilton^, s principle, and solved using Navier-type solution to obtain critical buckling temperature for simply supported laminated plates. Changing (α₂/ α₁) ratios, number of layers, aspect ratios, E₁/E₂ ratios for thick and thin plates and their effect on thermal

In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets

This paper aims to introduce certain new kinds of ideals on pseudo-BG-Algebra (P-BG-A), such as pseudo-closed ideal (P-CI), pseudo-completely closed ideal (P-CCI), and pseudo-n-ideal (P-n-I). Firstly, a (P-n-I) is defined and its pertinent properties are explored. Some important properties have been proven, for example, any pseudo-ideal is a (P-n-I), but the opposite is not generally true, an example was given of the opposite direction. Also, every pseudo-subalgebra of a (P-BG-A) is a pseudo ideal and it is a (P-n-I). Secondly, (P-CI) and a (P-CCI) ideal are defined. After that, we prove that every pseudo-subalgebra of a (P-BG-A) is a (P-CI) and the converse is true. The relationship between (P-BG-A) and pseudo-BH-algebra is demonstrated un

Metalloendo peptidase is a neutral endopeptidase that cleaves peptides at the amino side of hydrophobic residues and inactivates several peptide hormones, including atrial natriuretic factor, giucagon, enkephalin, substance p, neurotensin, oxytocin, and bradykinin. It is also a major enzyme for the degradation of beta-amyloid. This study aimed to measure enzyme activity and compare it with other biochemical changes in sera patients with diabetic nephropathy. The study included 35 pathological samples of people with diabetic nephropathy, 24 samples from males and 11 samples from females, as well as the same number of healthy people as a comparison group of 15 males, 20 females, with the ages of both groups of patients with diabetic nephropat

This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimi

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic