A scale conjugate neural network learning process for the nonlinear malaria disease model

The purpose of this work is to provide a stochastic framework based on the scale conjugate gradient neural networks (SCJGNNs) for solving the malaria disease model of pesticides and medication (MDMPM). The host and vector populations are divided in the mathematical form of the malaria through the pesticides and medication. The stochastic SCJGNNs procedure has been presented through the supervised neural networks based on the statics of validation (12%), testing (10%), and training (78%) for solving the MDMPM. The optimization is performed through the SCJGNN along with the log-sigmoid transfer function in the hidden layers along with fifteen numbers of neurons to solve the MDMPM. The accurateness and precision of the proposed SCJGNNs is observed through the comparison of obtained and source (Runge-Kutta) results, while the small calculated absolute error indicate the exactitude of designed framework based on the SCJGNNs. The reliability and consistency of the SCJGNNs is observed by using the process of correlation, histogram curves, regression, and function fitness

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

In this study, the solution of the non-linear influenza disease system (NIDS) is presented using the Morlet wavelet neural networks (MWNNs) together with the optimisation procedures of the hybrid process of global/local search approaches. The genetic algorithm (GA) and sequential quadratic programming (SQP), that is, GA-SQP, are executed as the global and local search techniques. The mathematical form of the NIDS depends upon four groups: susceptible S(y), infected I(y), recovered R(y) and cross-immune individuals C(y). To solve the NIDS, an error function is designed using NIDS and its leading initial conditions (ICs). This error function is optimised with a combination of MWNNs and GA-SQP to solve for all the groups of NIDS. The comparison of the obtained solutions and Runge–Kutta results is presented to authenticate the correctness of the designed MWNNs along with the GA-SQP for solving NIDS. Moreover, the statistical operators using different measures are presented to check the reliability and constancy of the MWNNs along with the GA-SQP to solve the NIDS

Graphene nanoplatelets/CeO2 nanotiles nanocomposites as effective antibacterial material for multiple drug-resistant bacteria.

Antibacterial agents with low toxicity to normal cells, redox activity and free radical scavenging property are urgently needed to address the global health crisis. The phenomenal conducting nature of graphene is a best fit to enhance the antibacterial properties of metal oxides. In this work, CeO2 nanotiles and graphene nanoplatelets/CeO2 nanotiles nanocomposites (G/CeO2) have been synthesized by a solvothermal method. The prepared materials have been characterized using XRD, FE-SEM, EDX, and UV-visible spectroscopy techniques to investigate their crystallinity, morphology, composition, and optical bandgap energies. The CeO2 and G/CeO2 nanocomposites have also been tested for antibacterial applications. The neat CeO 2 nanotiles sample inhibits the bacterial growth of Pseudomonas aeruginosa and Staphylococcus aureus up to 14.21% and 39.53% respectively. The antibacterial activity was tremendously enhanced using 25% graphene-loaded sample (G/CeO2-II) i.e., approximately 83% loss of P. aeruginosa and 89% in case of S. aureus has been observed. This can be attributed to the unique nano-architecture, oxidative stress due to the excellent ability of reversible conversion between the two electronic states of CeO2 and the stress exerted by the planar graphene and CeO2 nanotiles. Therefore, the G/CeO2 nanocomposites can find potential application as nano-antibiotics for controlling pathogens

In vivo integrity of polymer-coated gold nanoparticles.

Inorganic nanoparticles (NPs) are frequently engineered with an organic surface coating to improve their physicochemical properties, and it is well-known that their colloidal properties1 may change upon internalization by cells2, 3. While the stability of such NPs is typically assayed in simple in vitro tests, their stability in a mammalian organism remains unknown. Here, we show that firmly grafted polymer shells around gold NPs may degrade when injected into rats. We synthesized monodisperse radioactively labelled gold nanoparticles (198Au)4 and engineered an 111In-labelled polymer shell around them5. Upon intravenous injection into rats, quantitative biodistribution analyses performed independently for 198Au and 111In showed partial removal of the polymer shell in vivo. While 198Au accumulates mostly in the liver, part of the 111In shows a non-particulate biodistribution similar to intravenous injection of chelated 111In. Further in vitro studies suggest that degradation of the polymer shell is caused by proteolytic enzymes in the liver. Our results show that even NPs with high colloidal stability can change their physicochemical properties in vivo