Publications by authors named "Emad A A Ismail"

A novel mathematical model which explores the transmission dynamics of infectious diseases integrating nonlinear incidence and quarantine measures is presented in this study. Five different compartments: susceptible, latent, infectious, quarantined and recovered individuals presents total population. Saturation effects in disease transmission are modeled through a nonlinear infection rate while quarantine and recovery processes are explicitly incorporated.

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Objective: Amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, poses a significant challenge for targeted treatment development. Accurate prediction of its progression is crucial for this endeavor.

Methods: This study investigated deep learning methods for ALS progression prediction using the publicly available PRO-ACT dataset.

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Mathematical modeling is an effective tool for understanding and predicting certain endemic diseases. Toxoplasmosis gondii (T. gondii) is an endemic disease that is transmitted to human by contact with infected cats.

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Nanoparticles show superior potential for enhancing thermal properties compared to conventional particle-liquid suspensions. This investigation delves into magnetohydrodynamics (MHD) drift, heat, and mass transfer effects within a Jeffery nanoparticle liquid. The study includes transference equations that consider the influences of thermophoresis and Brownian motion on particle deposition.

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Despite significant advancements in worldwide vaccination, the coronavirus 2019 pandemic has disrupted primary care and vaccination programs. This study aimed to assess parents' attitudes toward compulsory childhood vaccination and the determinants of vaccination acceptance in Algeria based on the Health Belief Model (HBM). Using the snowball and convenience sampling methods, a cross-sectional study was conducted from November 1 to December 15, 2022, among parents with at least 1 child eligible for compulsory vaccination.

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This study investigates the significance of single-walled (SWCNTs) and multi-walled (MWCNTs) carbon nanotubes with a convectional fluid (water) over a vertical cone under the influences of chemical reaction, magnetic field, thermal radiation and saturated porous media. The impact of heat sources is also examined. Based on the flow assumptions, the fundamental flow equations are modeled as partial differential equations (PDEs).

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Zinc oxide nanoparticles (ZnO NPs) can possibly serve as a pervasive source of essential nutrient zinc in agricultural crops in the future. The major environmental concerns with ZnO NPs might be their toxicity and incorrect dosage, which might lead to crop damage and environmental pollution. Interplay between ZnO NPs and () will be of interest, yet little is known about apropos interaction of these two, which will assist in optimizing the dose of ZnO NPs for their commercial use in agriculture.

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In the distributed computing era, cloud computing has completely changed organizational operations by facilitating simple access to resources. However, the rapid development of the IoT has led to collaborative computing, which raises scalability and security challenges. To fully realize the potential of the Internet of Things (IoT) in smart home technologies, there is still a need for strong data security solutions, which are essential in dynamic offloading in conjunction with edge, fog, and cloud computing.

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Article Synopsis
  • This paper introduces a new two-parameter unit probability model that generalizes the Kumaraswami distribution, offering more flexibility in its hazard and density functions compared to existing distributions.
  • It conducts a thorough analysis of the model's statistical features, including moments and order statistics, and provides explicit formulas for these.
  • The model's parameters are estimated using maximum likelihood estimation, with simulations showing its reliability, and its effectiveness is validated through application to four real data sets, highlighting its potential for diverse analytical use across various fields.
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This study introduces innovative operational laws, Einstein operations, and novel aggregation algorithms tailored for handling q-spherical fuzzy rough data. The research article presents three newly designed arithmetic averaging operators: q-spherical fuzzy rough Einstein weighted averaging, q-spherical fuzzy rough Einstein ordered weighted averaging, and q-spherical fuzzy rough Einstein hybrid weighted averaging. These operators are meticulously crafted to enhance precision and accuracy in arithmetic averaging.

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Pakistan Railway (PR) is vital to the country's transportation infrastructure, facilitating passenger and freight transportation. However, the growing number of accidents associated with PR has raised concerns about its overall safety. In addition, there have been limited research efforts to investigate PR accidents and their underlying causes The present study conducts a comprehensive risk assessment and safety management of PR using a semi-quantitative risk matrix approach.

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q-spherical fuzzy rough set (q-SFRS) is also one of the fundamental concepts for addressing more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi-parameters. Taking this feature and the significance of the q-SFRSs into consideration, the main objective of the article is to describe some reliable sine trigonometric laws for SFSs.

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This study investigates advanced data collection methodologies and their implications for understanding employee and customer behavior within specific locations. Employing a comprehensive multi-criteria decision-making framework, we evaluate various technologies based on four distinct criteria and four technological alternatives. To identify the most effective technological solution, we employ the q-spherical fuzzy rough TOPSIS method, integrating three key parameters: lower set approximation, upper set approximation, and parameter q (where q ≥ 1).

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This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion.

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An effort was being made to incorporate waste bagasse ash (WBA) both in carbonized and uncarbonized form into the formulation of Al6063 matrix-based metal matrix composites (MMC's) by partially substituting ceramic particles for them. In the process of developing composites, comparative research on carbonized WBA and uncarbonized bagasse powder was carried out in the role of reinforcement. Microstructure investigations revealed that carbonized WBA particles were properly distributed throughout the aluminum-base metal matrix alloy.

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In this manuscript, a mathematical model known as the Heimburg model is investigated analytically to get the soliton solutions. Both biomembranes and nerves can be studied using this model. The cell membrane's lipid bilayer is regarded by the model as a substance that experiences phase transitions.

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Sustainable agricultural practices help to manage and use natural resources efficiently. Due to global climate and geospatial land design, soil texture, soil-water content (SWC), and other parameters vary greatly; thus, real time, robust, and accurate soil analytical measurements are difficult to be developed. Conventional statistical analysis tools take longer to analyze and interpret data, which may have delayed a crucial decision.

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Dietary fiber has an immense role in the gut microbiome by modulating juvenile growth, immune system maturation, glucose, and lipid metabolism. Lifestyle changes might disrupt gut microbiota symbiosis, leading to various chronic diseases with underlying inflammatory conditions, obesity, and its associated pathologies. An interventional study of 16 weeks examined the impact of psyllium husk fiber with and without lifestyle modification on gut health and sleep quality in people with central obesity (men = 60 and women = 60), those aged from 40 to 60 years, those having WC ≥ 90 cm (men) and WC ≥ 80 cm (women), and no history of any chronic disease or regular medication.

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Montmorillonite clay and agar are naturally occurring materials of significant importance in designing biocompatible materials tailored for applications in biotechnology and medicine. The introduction of magnetic properties has the potential to significantly boost their characteristics and expand their applications. In this study, we have successfully synthesized highly intercalated magnetic composites, incorporating magnetic iron oxide nanoparticles (MNPs), montmorillonite clay (MMT), and agar (AG), through a thermo-physicomechanical method.

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The modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products.

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This paper aims to demonstrate a numerical strategy via finite difference formulations for time fractional reaction-diffusion models which are ubiquitous in chemical and biological phenomena. The time-fractional derivative is considered in the Caputo sense for both linear and nonlinear problems. First, the Caputo derivative is replaced with a quadrature formula, then an implicit method is used for the remaining part.

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This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature.

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Deposition of high entropy alloy FeCoNiMnCu on SS-304 was carried out by microwave energy for application in "solid oxide fuel-cell (SOFC) interconnects". The ball-milling has been performed by taking "Fe, Co, Ni, Mn, and Cu" in equal 20 wt. % of before deposited on SS-304 substrate.

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This work aims to analyze the transfer of heat through new fractional-order convective straight fins by using the Riemann-Liouville type fractional derivatives. The convection through the fins is considered in such a way that the thermal conductivity depends on the temperature. The transformed fractional-order problems are constituted through an optimization problem in such a way that the norm remains minimal.

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