## 6 Conclusions  
A mathematical model has been developed to simulate the influence of viscous dissipation, second-order slip and variable transport properties (viscosity, thermal conductivity, nanoparticle mass and micro-organism species diffusivity) in melting magneto-nanofluid bioconvection heat transfer from a stretching sheet. Via a group of similarity transformations, the governing partial differential equations, wall and free stream boundary conditions have been rendered into ordinary differential form. The emerging nonlinear two-point ordinary differential boundary value problem has been solved with the BVP4C MATLAB numerical code. The velocity, temperature, concentration and microorganism profiles have been plotted for various values of parameters. The computations have shown that:  
* Increasing magnetic body force parameter reduces velocity, nanoparticle concentration and motile microorganism species number density, whereas hydrodynamic boundary layer thickness is increased as are temperatures. * Increasing Brownian motion and thermophoresis effect lead to an enhancement in temperatures. Increasing melting effect accelerates the flow (via momentum diffusion assistance) whereas it decreases temperatures. Increasing first-order slip and temperature-dependent thermal conductivity parameters significantly cool the boundary layer regime. Figure 10: Local Sherwood number, \(-\phi^{\prime}(0)\) versus \(Sc\) and \(Nb\) for different values of \(Nt\). Figure 9: Local Nusselt number, \(-\theta^{\prime}(0)\) versus \(h_{2}\) and \(Me\) for different values of \(Ec\). * Nanoparticle volume fraction and motile microorganism density number are both elevated with increasing mass diffusivity parameter whereas they are depressed with greater Schmidt number. * Motile microorganism density number is boosted with increasing microorganism diffusivity parameter, whereas the converse response is induced with increasing bioconvection Schmidt number. * Increasing temperature-dependent viscous parameter and Eckert number increases temperatures but reduce nanoparticle volume fraction. * Local Sherwood number is depressed with Brownian motion parameter and Schmidt number, whereas it is enhanced with thermophoresis parameter. * Increasing nanomaterial viscosity, viscous dissipation and melting heat transfer reduce local Nusselt number at the sheet surface. The present study has ignored electrical field effects which are also relevant to nanofluid materials processing [61; 62]. Furthermore, field simulation with computational fluid dynamics software is required for fully three-dimensional flow modelling; these aspects are also being explored [63]. All authors were jointly involved in the formulation of the problem, numerical solution and writing up the paper. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] contributed reagents/materials/analysis tools; [PERSON] wrote the paper. This research was funded by Universiti Sains Malaysia, grant number 1001/PMATHS/8011013 and the APC was funded by Universiti Sains Malaysia, grant number 1001/PMATHS/8011013. The authors