Hall Effect on Falkner–Skan Boundary Layer Flow of FENE-P Fluid over a Stretching Sheet

The Falkner-Skan boundary layer steady flow over a fiat stretching sheet is investigated in this paper. The mathematical model consists of continuity and the momentum equations, while a new model is proposed for MHD Finitely Extensible Nonlinear Elastic Peterlin （FENE-P） fluid. The effects of Hall current with the variation of intensity of non-zero pressure gradient are taken into account. The governing partial differential equations are first transformed to ordinary differential equations using appropriate similarity transformation and then solved by Adomian decomposition method （ADM）. The obtained results are validated by generalized collocation method （GCM） and found to be in good agreement. Effects of pertinent parameters are discussed through graphs and tables. Comparison with the existing studies is made as a limiting case of the considered problem at the end.

Advanced Study of Unsteady Heat and Chemical Reaction with Ramped Wall and Slip Effect on a Viscous Fluid

This paper investigate the effect of slip boundary condition, thermal radiation, heat source, Dufour number,chemical reaction and viscous dissipation on heat and mass transfer of unsteady free convective MHD flow of a viscous fluid past through a vertical plate embedded in a porous media. Numerical results are obtained for solving the nonlinear governing momentum, energy and concentration equations with slip boundary condition, ramped wall temperature and ramped wall concentration on the surface of the vertical plate. The influence of emerging parameters on velocity,temperature and concentration fields are shown graphically.

Discrete biological modeling for the immune response to dengue virus

Dengue infection affects more than half of the world’s population,with 1 billion symp-tomatic cases identified per year and several distinct genetic serotypes:DENV 1–4.Transmitted via the mosquito bite,the dengue virus infects Langerhans cells.Monocytes,B lymphocytes,and mast cells infected with dengue virus produce various cytokines although it is not clear which ones are predominant during DHF disease.A mathemat-ical model of the Dengue virus infection is developed according to complex dynamics determined by many factors.Starting from a state of equilibrium that we could define as“virus-free”asymptotically stable with a viral reproduction number lower than one which means a very effective action of the innate immune system:it stops the infectious process,the mathematical analysis of stability in the presence of the virus demonstrates that the proposed model is dynamically influenced.Dengue fever affects more than half of the world’s population,with 1 billion symptomatic cases and multiple genetic serotypes confirmed each year,which simulates a network of interactions between the various populations involved without considering the speeds of the processes in question which are indicated in a separate computation.In this research,a hybrid approach of petri nets is utilized to connect the discrete models of dengue.

Modeling and simulation of the“IL-36 cytokine”and CAR-T cells interplay in cancer onset

Background:CAR-T cells are chimeric antigen receptor(CAR)-T cells;they are targetspecific engineered cells on tumor cells and produce T cell-mediated antitumor responses.CAR-T cell therapy is the“first-line”therapy in immunotherapy for the treatment of highly clonal neoplasms such as lymphoma and leukemia.This adoptive therapy is currently being studied and tested even in the case of solid tumors such as osteosarcoma since,precisely for this type of tumor,the use of immune checkpoint inhibitors remained disappointing.Although CAR-T is a promising therapeutic technique,there are therapeutic limits linked to the persistence of these cells and to the tumor’s immune escape.CAR-T cell engineering techniques are allowed to express interleukin IL-36,and seem to be much more efficient in antitumoral action.IL-36 is involved in the long-term antitumor action,allowing CAR-T cells to be more efficient in their antitumor action due to a“cross-talk”action between the“IL-36/dendritic cells”axis and the adaptive immunity.Methods:This analysis makes the model useful for evaluating cell dynamics in the case of tumor relapses or specific understanding of the action of CAR-T cells in certain types of tumor.The model proposed here seeks to quantify the action and interaction between the three fundamental elements of this antitumor activity induced by this type of adoptive immunotherapy:IL-36,“armored”CAR-T cells(i.e.,engineered to produce IL-36)and the tumor cell population,focusing exclusively on the action of this interleukin and on the antitumor consequences of the so modified CAR-T cells.Mathematical model was developed and numerical simulations were carried out during this research.The development of the model with stability analysis by conditions of Routh–Hurwitz shows how IL-36 makes CAR-T cells more efficient and persistent over time and more effective in the antitumoral treatment,making therapy more effective against the“solid tumor”.Findings:Primary malignant bone tumors are quite rare(about 3%of all tumors)and the vast majority consist of osteosarcomas and Ewing’s sarcoma and,approximately,the 20%of patients undergo metastasis situations that is the most likely cause of death.Interpretation:In bone tumor like osteosarcoma,there is a variation of the cellular mechanical characteristics that can influence the efficacy of chemotherapy and increase the metastatic capacity;an approach related to adoptive immunotherapy with CAR-T cells may be a possible solution because this type of therapy is not influenced by the biomechanics of cancer cells which show peculiar characteristics.

Artificial intelligence to link environmental endocrine disruptors(EEDs)with bone diseases

Our endocrine system is not only complex,but is also enormously sensitive to the imbalances caused by the environmental stressors,extreme weather situation,and other geographical factors.The endocrine disruptions are associated with the bone diseases.Osteoporosis is a bone disorder that occurs when bone mineral density and bone mass decrease.It affects women and men of all races and ethnic groups,causing bone weakness and the risk of fractures.Environmental stresses are referred to physical,chemical,and biological factors that can impact species productivity.This research aims to examine the impact of environmental stresses on bone diseases like osteoporosis and low bone mass(LBM)in the United States(US).For this purpose,we use an artificial neural network model to evaluate the correlation between the data.A multilayer neural network model is constructed using the Levenberg–Marquardt training algorithm,and its performance is evaluated by mean absolute error and coefficient of correlation.The data of osteoporosis and LBM cases in the US are divided into three groups,including gender group,age group,and race/ethnicity group.Each group shows a positive correlation with environmental stresses and thus the endocrinology.

Numerical analysis of fractional-order tumor model

In this paper, the tumor-immune dynamics are simulated by solving a nonlinear system of differential equations. The fractional-order mathematical model incorporated with three Michaelis-Menten terms to indicate the saturated effect of immune response, the limited immune response to the tumor and to account the self-limiting production of cytokine interleukin-2. Two types of treatments were considered in the mathematical model to demonstrate the importance of immunotherapy. The limiting values of these treatments were considered, satisfying the stability criteria for fractional differential system. A graphical analysis is made to highlight the effects of antigenicity of the tumor and the fractionM-order derivative on the tumor mass.