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Expanding the Tanh-Function Method for Solving Nonlinear Equations

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Applied Mathematics 2011年第9期2卷 1096-1104页

作者： nassar hassan abdel-all Mohamed Abd-allah abdel-Razek Abd-allah Kamel Seddeek 不详

In this paper, using the tanh-function method, we introduce a new approach to solitary wave solutions for solving nonlinear PDEs. The proposed method is based on adding integration constants to the resulting nonlinear ODEs from the nonlinear PDEs using the wave transformation. Also, we use a transformation related to those integration constants. Some examples are considered to find their exact solutions such as KdV- Burgers class and Fisher, Boussinesq and Klein-Gordon equations. Moreover, we discuss the geometric interpretations of the resulting exact solutions.

关键词： Tanh-Function Method Nonlinear Equations Solitary Waves

Computation of Some Geometric Properties for New Nonlinear PDE Models

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Applied Mathematics 2011年第6期2卷 666-675页

作者： nassar hassan abdel-all Mohammed Abdullah Abdullah Hamad Mohammed Abdullah abdel-Razek Amal Aboelwafa Khalil 不详

The purpose of the present work is to construct new geometrical models for motion of plane curve by Darboux transformations. We get nonlinear partial differential equations (PDE). We have obtained the exact solutions of the resulting equations using symmetry groups method. Also, the Gaussian and mean curvatures of Monge form of the soliton surfaces have been calculated and discussed.

关键词： Motion of Curve Darboux Transformations Gaussian and Mean Curvatures Symmetry Groups

Computational Analysis of Novel Extended Lindley Progressively Censored Data

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2571-2596页

作者： Refah Alotaibi Mazen nassar Ahmed Elshahhat Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Statistics Faculty of CommerceZagazig UniversityZagazigEgypt Faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is *** this research, using a progressive Type-II censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.

关键词： Marshall-Olkin-Lindleymodel reliability inference Bayesian and classical inference progressive Type-II censoring

Glucagon-like peptide-1 receptor agonists as a possible intervention to delay the onset of type 1 diabetes:A new horizon

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World Journal of Diabetes 2024年第2期15卷 133-136页

作者： Mahmoud nassar Ajay Chaudhuri Husam Ghanim Paresh Dandona Department of Internal Medicine Division of EndocrinologyDiabetes and MetabolismJacobs School of Medicine and Biomedical SciencesUniversity of BuffaloBuffaloNY 14221United States

Type 1 diabetes(T1D)is a chronic autoimmune condition that destroys insulinproducing beta cells in the pancreas,leading to insulin deficiency and *** management of T1D primarily focuses on exogenous insulin replacement to control blood glucose ***,this approach does not address the underlying autoimmune process or prevent the progressive loss of beta *** research has explored the potential of glucagon-like peptide-1 receptor agonists(GLP-1RAs)as a novel intervention to modify the disease course and delay the onset of ***-1RAs are medications initially developed for treating type 2 *** exert their effects by enhancing glucose-dependent insulin secretion,suppressing glucagon secretion,and slowing gastric *** evidence suggests that GLP-1RAs may also benefit the treatment of newly diagnosed patients with *** article aims to highlight the potential of GLP-1RAs as an intervention to delay the onset of T1D,possibly through their potential immunomodulatory and anti-inflammatory effects and preservation of *** article aims to explore the potential of shifting the paradigm of T1D management from reactive insulin replacement to proactive disease modification,which should open new avenues for preventing and treating T1D,improving the quality of life and long-term outcomes for individuals at risk of T1D.

关键词： Type 1 diabetes Semaglutide Glucagon-like peptide-1 receptor agonists Insulin therapy Autoimmune response Blood glucose monitoring Β-cell preservation Early screening Teplizumab Randomized controlled trials

A modular microfluidic platform to study how fluid shear stress alters estrogen receptor phenotype in ER+breast cancer cells

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Microsystems & Nanoengineering 2024年第1期10卷 287-299页

作者： Braulio Andrés Ortega Quesada Jonathan Cuccia Rachael Coates Blake nassar Ethan Littlefield Elizabeth C.Martin Adam T.Melvin Cain Department of Chemical Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Chemical and Biological Engineering Clemson UniversityClemsonSC 29634USA Biological and Agricultural Engineering Louisiana State UniversityBaton RougeLA 70803USA Department Medicine Section Hematology and Medical OncologyTulane UniversityNew OrleansLA 70118USA

Metastatic breast cancer leads to poor prognoses and worse outcomes in patients due to its invasive behavior and poor response to *** is still unclear what biophysical and biochemical factors drive this more aggressive phenotype in metastatic cancer;however recent studies have suggested that exposure to fluid shear stress in the vasculature could cause *** this study a modular microfluidic platform capable of mimicking the magnitude of fluid shear stress(FSS)found in human vasculature was designed and *** device provides a platform to evaluate the effects of FSS on MCF-7 cell line,an estrogen receptor positive(ER+)breast cancer cell line,during circulation in the *** of the effects of FSS on MCF-7 cells was carried out utilizing two approaches:single cell analysis and bulk *** single cell analysis,cells were trapped in a microarray after exiting the serpentine channel and followed by immunostaining on the device(on-chip).Bulk analysis was performed after cells were collected in a microtube at the outlet of the microfluidic serpentine channel for western blotting(off-chip).It was found that cells exposed to an FSS magnitude of 10 dyn/cm^(2) with a residence time of 60 s enhanced expression of the proliferation marker Ki67 in the MCF-7 cell line at a single cell *** understand possible mechanisms for enhanced Ki67 expression,on-chip and off-chip analyses were performed for pro-growth and survival pathways ERK,AKT,and JAK/*** demonstrated that after shearing the cells phosphorylation of p-AKT,p-mTOR,and p-STAT3 were ***,there was no change in p-ERK1/*** is a mediator of ER rapid signaling,analysis of phosphorylated ERαwas carried out and no significant differences between sheared and non-sheared populations were *** together these results demonstrate that FSS can increase phosphorylation of proteins associated with a more aggressive phenotype in circulating cancer *** findin

关键词： fluid breast estrogen

Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

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Computers, Materials & Continua 2024年第4期79卷 1157-1185页

作者： Sapiah Sakri Shakila Basheer Zuhaira Muhammad Zain Nurul Halimatul Asmak Ismail Dua’abdellatef nassar Manal Abdullah Alohali Mais Ayman Alharaki Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia

Background:Sepsis,a potentially fatal inflammatory disease triggered by infection,carries significant healthimplications *** detection is crucial as sepsis can rapidly escalate if left *** in deep learning(DL)offer powerful tools to address this ***:Thus,this study proposeda hybrid CNNBDLSTM,a combination of a convolutional neural network(CNN)with a bi-directional long shorttermmemory(BDLSTM)model to predict sepsis *** the proposed model provides a robustframework that capitalizes on the complementary strengths of both architectures,resulting in more accurate andtimelier ***:The sepsis prediction method proposed here utilizes temporal feature extraction todelineate six distinct time frames before the onset of *** time frames adhere to the sepsis-3 standardrequirement,which incorporates 12-h observation windows preceding sepsis *** models were trained usingthe Medical Information Mart for Intensive Care III(MIMIC-III)dataset,which sourced 61,522 patients with 40clinical variables obtained from the IoT medical *** confusion matrix,the area under the receiveroperating characteristic curve(AUCROC)curve,the accuracy,the precision,the F1-score,and the recall weredeployed to evaluate ***:The CNNBDLSTMmodel demonstrated superior performance comparedto the benchmark and other models,achieving an AUCROC of 99.74%and an accuracy of 99.15%one hour beforesepsis *** results indicate that the CNNBDLSTM model is highly effective in predicting sepsis onset,particularly within a close proximity of one ***:The results could assist practitioners in increasingthe potential survival of the patient one hour before sepsis onset.

关键词： Temporal derivatives hybrid deep learning predicting sepsis onset MIMIC III machine learning(ML) deep learning

On a New Version of Weibull Model:Statistical Properties,Parameter Estimation and Applications

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2219-2241页

作者： hassan Okasha Mazen nassar Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNasr CityCairo11884Egypt Department of Statistics Faculty of CommerceZagazig UniversityZagazig44519Egypt

In this paper,we introduce a new four-parameter version of the traditional Weibull *** is able to provide seven shapes of hazard rate,including constant,decreasing,increasing,unimodal,bathtub,unimodal then bathtub,and bathtub then unimodal *** basic characteristics of the proposedmodel are studied,including moments,entropies,mean deviations and order statistics,and its parameters are estimated using the maximum likelihood *** on the asymptotic properties of the estimators,the approximate confidence intervals are also taken into consideration in addition to the point *** examine the effectiveness of the maximum likelihood estimators of the model’s parameters through simulation *** on the simulation findings,it can be concluded that the provided estimators are consistent and that asymptotic normality is a good method to get the interval *** actual data sets for COVID-19,engineering and blood cancer are used to empirically demonstrate the new distribution’s usefulness inmodeling real-world *** analysis demonstrates the proposed distribution’s ability in modeling many forms of data as opposed to some of its well-known sub-models,such as alpha powerWeibull distribution.

关键词： Weibull distribution alpha power transformation method maximum likelihood entropy order statistics

A New Three-Parameter Inverse Weibull Distribution with Medical and Engineering Applications

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Computer Modeling in Engineering & Sciences 2023年第5期135卷 1255-1274页

作者： Refah Alotaibi hassan Okasha Hoda Rezk Mazen nassar Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNasr City11884CairoEgypt Department of Statistics Faculty of CommerceAl-Azhar UniversityNasr City11884CairoEgypt Department of Statistics Faculty of CommerceZagazig UniversityZagazig44519Egypt

The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its *** addition is beneficial in a variety of fields,including reliability,economics,engineering,biomedical science,biological research,environmental studies,and *** modeling real data,several expanded classes of distributions have been *** modified alpha power transformed approach is used to implement the new *** datamatches the new inverseWeibull distribution better than the inverse Weibull distribution and several other competing *** appears to be a distribution designed to support decreasing or unimodal shaped distributions based on its *** expressions for quantiles,moments,incomplete moments,moment generating function,characteristic generating function,and entropy expression are among the determined attributes of the new *** point and interval estimates are studied using the maximum likelihood *** research is conducted to illustrate the correctness of the theoretical *** applications to medical and engineering data are utilized to illustrate the model’s flexibility.

关键词： Inverse weibull distribution modified alpha power transformation method moments order statistics

A Novel Modified Alpha Power Transformed Weibull Distribution and Its Engineering Applications

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2065-2089页

作者： Refah Alotaibi hassan Okasha Mazen nassar Ahmed Elshahhat Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah80200Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNasr CityCairo11884Egypt Department of Statistics Faculty of CommerceZagazig UniversityZagazig44519Egypt Faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed *** refer to the new model as modified alpha power transformed Weibull *** attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions,which are quite familiar in environmental *** hazard rate function can be decreasing,increasing,bathtub and upside-down then bathtub *** structural properties of the proposed model are acquired including quantile function,moments,entropies,order statistics,residual life and reversed failure rate *** parameters of the distribution were estimated using the maximum likelihood *** maximum likelihood method is employed to estimate the model parameters and the approximate confidence intervals are also *** a simulation study,the performance of the point and interval estimates are compared using different *** real lifetime data sets,we verify that the offered model furnishes a better fit than some other lifetime models including Weibull,gamma and alpha powerWeibull models.

关键词： Weibull distribution modified alpha power transformationmethod maximum likelihood entropy order statistics