Computational intelligence modelling of pharmaceutical tabletting processes using bio-inspired optimization algorithms

In pharmaceutical development, it is very useful to exploit the knowledge of the causal relationship between product quality and critical material attributes (CMA) in developing new formulations and products, and optimizing manufacturing processes. With the big data captured in the pharmaceutical industry, computational intelligence (CI) models could potentially be used to identify critical quality attributes (CQA), CMA and critical process parameters (CPP). The objective of this study was to develop computational intelligence models for pharmaceutical tabletting processes, for which bio-inspired feature selection algorithms were developed and implemented for optimisation while artificial neural network (ANN) was employed to predict the tablet characteristics such as porosity and tensile strength. Various pharmaceutical excipients (MCC PH 101, MCC PH 102, MCC DG, Mannitol Pearlitol 200SD, Lactose, and binary mixtures) were considered. Granules were also produced with dry granulation using roll compaction. The feed powders and granules were then compressed at various compression pressures to produce tablets with different porosities, and the corresponding tensile strengths were measured. For the CI modelling, the efficiency of seven bio-inspired optimization algorithms were explored: grey wolf optimization (GWO), bat optimization (BAT), cuckoo search (CS), flower pollination algorithm (FPA), genetic algorithm (GA), particle swarm optimization (PSO), and social spider optimization (SSO). Two-thirds of the experimental dataset was randomly chosen as the training set, and the remaining was used to validate the model prediction. The model efficiency was evaluated in terms of the average reduction (representing the fraction of selected input variables) and the mean square error (MSE). It was found that the CI models can well predict the tablet characteristics (i.e. porosity and tensile strength). It was also shown that the GWO algorithm was the most accurate in predicting porosity. While the most accurate prediction for the tensile strength was achieved using the SSO algorithm. In terms of the average reduction, the GA algorithm resulted in the highest reduction of inputs (i.e. 60%) for predicting both the porosity and the tensile strength.     

On thermoelectric materials with memory-dependent derivative and subjected to a moving heat source

We develop a model of generalized thermoelasticity with memory-dependent derivative (MDD) heat conduction law for a thermoelectric half-space. Some urgent theories take after as most remote point cases. The Laplace transform and state-space procedures are utilized to urge the overall account for any arrangement of limit conditions. The general solution acquired is connected to the particular issue of a half-space exposed to a uniform magnetic field, a moving heat source with consistent speed and ramp-type heating. The inverse Laplace transforms are registered numerically. The impacts of various estimations of the figure-of-merit quantity, heat source speed, MDD parameters, the magnetic number and the ramping time parameter are thought about.

     

A multi-variate heart disease optimization and recognition framework

Neural Computing and Applications - Cardiovascular diseases (CVD) are the most widely spread diseases all over the world among the common chronic diseases. CVD represents one of the main causes of...     

Separation of a compound effective against Biomphalaria alexandrina snails from the filtrate of Penicillium janthinellum

Biomphalaria alexandrina snails, as intermediate hosts of schistosomiasis, play a central role in dissemination of the disease. Control of these snails by chemical molluscicides adversely affects the aquatic environment, causing toxic and carcinogenic effects on non-target organisms. Searching for promising substances from biological origin becomes an urgent need to overcome these drawbacks. Screening tests were carried out on 236 fungal genera isolated from the habitat of freshwater snails in four Egyptian governorates. Twenty species were effective against B. alexandrina snails, but the most potent was Penicillium janthinellum as the value of LC₅₀ was 1.03%. Chemical analyses of this filtrate resulted in the separation of a compound effective against snails; it was identified as methyl gallate. Protein electrophoresis showed that both fungal filtrate and methyl gallate affect the protein pattern of snails’ haemolymph. Little or no mortality of Daphnia pulex individuals was observed after their exposure to sub lethal concentrations of each treatment.     

Fatigue Crack Tip Plasticity for Inclined Cracks

The evaluation of the crack tip deformation is essential to the estimation of crack growth under either static or cyclic loading. A 3-D elastic–plastic finite element analysis was developed to simulate the crack tip deformation along mixed mode inclined edge cracks in a steel plate subjected to either monotonic or cyclic loading at selected R-ratios. In this paper, two types of crack configurations were investigated: inclined cracks with equal inclined lengths (EICL) and inclined cracks with equal horizontal projection length (ECHP). The development of the monotonic (Δm) and cyclic (Δc) crack tip plastically zones and the monotonic (CTOD) and cyclic (ΔCTOD) crack tip opening displacements were traced to find the effect of the crack inclination angle, which significantly affected the size and shape of the crack tip plastic zone. The finite element results compared well with the analytical results based on modified Dugdale’s model. It was observed that Mode II has a significant effect on the plastic zone in the case of equal inclined crack length (EICL), i.e., Mode II increases as the crack angle decreases. Also, it is interesting to note that for the EICL case, the magnitude of Δc is delayed to appear with decreasing the inclination angle, for example, for θ?=?90° the cyclic plastic zone appeared at Δσ?=?103.32 MPa, while for θ?=?45° the cyclic plastic zone appeared at Δσ?=?132.84 MPa. Whereas, the variation of monotonic and cyclic plastic zone size in the equal crack horizontal projection (ECHP) case is not affected by the crack inclination angle. Furthermore, it was observed that the static crack tip opening displacement (CTOD) and the cyclic (ΔCTOD) are independent of the crack inclination angle in case of ECHP, due to such cracks take into consideration the effect of inclination angle through its length.     

Preparation of Electrolytic Quasi-Solid-State Nanofibers for Dye-Sensitized Solar Cells

JOM - Nanofibers were prepared from a poly(acrylonitrile-co-vinyl acetate) [P(AN-co-VAC)]/polyvinylidene fluoride (PVDF) blend and used as a quasi-solid (QS) electrolyte for dye-sensitized solar...     

A multi-verse optimizer approach for feature selection and optimizing SVM parameters based on a robust system architecture

Neural Computing and Applications - Support vector machine (SVM) is a well-regarded machine learning algorithm widely applied to classification tasks and regression problems. SVM was founded based...     

Performance optimization of integrated gas and power within microgrids using hybrid PSO–PS algorithm

In this paper, a hybrid algorithm consisting of particle swarm optimization and pattern search algorithm is proposed to evaluate and optimize the design and operation of microgrids (MGs) in combined gas and power networks. Key performance indicators (KPIs) are modeled and proposed to evaluate and assess MGs. The paper begins by proposing a comprehensive study to define KPIs, which are used to evaluate the following MG parameters: economical efficiency, reliability, environmental conservation, and power quality. Multi‐objective evaluation functions are then developed by building a relationship matrix of MG and KPI components. The results are then displayed as optimized power generation percentages for each technology with values for four KPI categories: cost, quality, reliability and environmental friendliness. Two case studies are examined in this paper; both the province of Ontario and Toronto regional zone under all system parameters with varying percentage of generation via gas technology. Results indicated that the optimal scenario for both Ontario and Toronto was achieved at hybrid PSO–patern search percentage generation via gas technology with improved cost KPI and other KPIs remaining approximately constant. Copyright © 2016 John Wiley & Sons, Ltd.