Diabetes is a common, metabolic disease, that results in a high level of blood sugar. Patients diagnosed with diabetes suffer from a body that cannot effectively use the insulin or cannot produce a sufficient amount of insulin. Providing a method of detection via symptoms that can be noticed by the patient can prompt the patient to seek medical assistance more promptly and in turn to be correctly diagnosed and treated. This paper proposed a solution for the problem using machine learning techniques. We applied eight algorithms on a data set of 521 subjects. The results are compared to each

The unsteady flow field variations between healthy and diseased three-dimensional rigid posterior cerebral artery are numerically investigated. The Computational hemodynamic simulations have been known to provide valuable clinical information to researchers and surgeons that proved to be crucial for the assessment of medical risks, pre-surgical conditioning and treatment planning. The wall shear stress (WSS) and wall pressure are the most important hemodynamic variables, and both are used to give accurate description about the health status of the artery. The results showed that at the

Numerical simulations of blood flow in arteries are important in the understanding and diagnosis of many cardiovascular diseases, such as atherosclerosis and arterial stenosis. More realistic mathematical models representing blood rheology offer a better understanding of these diseases. In this study, blood is considered an Oldroyd-B fluid with a shear-thinning property and a shear rate-dependent relaxation time that is adopted by fitting experimental data. The Quemada model is used to represent the shear-thinning property with hematocrit variation. The stabilized finite element method is used

Due to the dispersive porous nature of its material, carbon–carbon supercapacitors have a current–voltage relationship which is modeled by a fractional-order differential equation of the form i(t)=Cα[Formula presented] where α≤1 is a dispersion coefficient and Cα is a pseudo-capacitance not measurable in Farads. Hence, the energy stored in a capacitor, known to equal CV2/2 where C is the capacitance in Farad and V is the voltage applied, does not apply to a supercapacitor. In a recent work (Allagui et al., 2016), a fractional-order energy equation that enables the quantification of the energy

Swarm intelligence represents a meta-heuristic approach to solve a wide variety of problems. Searching for similar patterns of genes is becoming very essential to predict the expression of genes under various conditions. Firefly clustering inspired by the behaviour of fireflies helps in grouping genes that behave alike. Contrasting hard clustering methodology, fuzzy clustering assigns membership values for every gene and predicts the possibility of belonging to every cluster. To distinguish highly expressed and suppressed genes, the research in this paper proposes an efficient fuzzy-firefly

This paper is dedicated to develop a fractional order model of the rate of change of cancerous blood cells in Chronic Myeloid Leukaemia using fractional-order differential equations as well as tackling the factors that affect this rate and compare between them. The simulated cases (using MATLAB) prove that the proposed model is doable in terms of the variables positions in the equations and its effect on the overall population. Also, the effect of the Pactional order is investigated through three parameters sets and it has shown strong influence on the dynamic response. © 2017 IEEE.

Worldwide, the phenomenal antimicrobial resistance with its consequences of fatal diseases has been alerted; it is because the morbidity and mortality at a shocking rate. Therefore, there is an urgent quest of innovative antimicrobials agents; it is that communicable disease is a worldwide trouble as of the growth and wideness of drug-resistant pathogens. As for the aim of the research, it is widely investigative to the prevalence of Gram-negative pathogens of E. coli and K. pneumoniae in different age groups, gender along with the identification of ESBL-producing pathogens and antimicrobial

The novelty of the present work looks in the synthesis of aqueous dispersed selenium nanoparticles (Se NPs) using gamma rays with the aid of various natural macromolecules such as citrus pectin (CP), sodium alginate (Alg), chitosan (CS) and aqueous extract of fermented fenugreek powder (AEFFP) using Pleurotus ostreatus for investigating their impact in vitro toward carcinoma cell. The synthesized Se NPs were characterized by XRD, UV–Vis., DLS, HRTEM, SEM, EDX and FTIR. Nucleation and growth mechanisms were also discussed. The factorial design was applied to examine the importance of multiple

The purposes of this work are to evaluate the antimicrobial, antibiofilm, anticancer, and antioxidant abilities of anisotropic zinc oxide nanoparticles (ZnO NPs) synthesized by a cost-effective and eco-friendly sol–gel method. The synthesized ZnO NPs were entirely characterized by UV-Vis, XRD, FTIR, HRTEM, zeta potential, SEM mapping, BET surface analyzer, and EDX elemental analysis. Antimicrobial and antibiofilm activities of ZnO NPs were investigated against multidrug-resistant (MDR) bacteria and yeast causing serious diseases like urinary tract infection (UTI). The anticancer activity was

Substitutions of cations were considered to be the main way for improving the performance of ferrite nanocrystalline structures. In this paper, non-magnetic and magnetic ions were conducted to substitute cobalt spinel ferrite nanoparticles CoFe2O4 NPs (CFO NPs). The studied Co1−xMxFe2O4; M = Zn, Cu, and Mn; x = 0.00, and 0.50) samples were synthesized through a cost-effective sol–gel technique. The outstanding properties of the samples are addressed using XRD, FTIR, the inductively coupled plasma optical emission spectrometer (ICP-OES), Raman analyses, HR-TEM, BET surface area analyzer, the