This study investigates the effects of red mud on the performance of geopolymer concrete in regard to fresh and mechanical properties. Red mud was used as a binder, and GGBS replaced the binder. Different proportions of red mud ranging from 0 to 30% with an interval of 2% and activator agents such as KOH and K₂SiO₃ for various alkaline-to-binder ratios such as 0.30, 0.40, and 0.50 were used; their effect on the fresh and mechanical properties of geopolymer concrete were the focusing parameter on the current study. Fresh properties such as setting time, slump, compaction factor, and vee-bee consistometer test, and mechanical properties such as compressive strength, split tensile strength, flexural strength, modulus of elasticity, and impact energy were studied. ANOVA and radar plot analysis were studied for various alkaline to binder (A/B) compressive strength results tested for 7 to 90 days. The increase of red mud quantity caused the decline of workability, but there was continuous enhancement of mechanical properties of GPC up to a specific limit. An alkaline-to-binder ratio of 0.4 shows excellent results compared with other ratios at ambient conditions for strength properties. ANOVA and radar plot reveal that A/B of 0.40 for 90 days shows excellent results compared with other ratios, and CS values vary in a linear manner.

Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Streptococcus mutans favours in the selection of appropriate caries excavation method which eventually results in meliorate caries-free cavity preparation for restoration. The objective of this study is to predict the post-Streptococcus mutans prior to dental caries excavation based on pre- Streptococcus mutans using iOS App developed on Artificial Neural Network (ANN) model. For the current research work, children with occlusal dentinal caries lesion were chosen, 45 primary molar teeth cases were studied. Caries excavation was done with carbide bur, polymer bur and spoon excavator. The colony forming units for pre and post-Streptococcus mutans were recorded, data emanating from clinical trials was employed to develop the ANN models. ANN models were trained, validated and tested with the registered clinical data using different ANN architectures. Feedforward backpropagation ANN model with an architecture of 4-5-1, predicts post-Streptococcus mutans with an efficiency of 0.99033, mean squared error and mean absolute percentage error for testing cases were 0.2341 and 4.967 respectively. Caries excavation methods and pre-Streptococcus mutans are feed as inputs, while post-Streptococcus mutans as targets to develop ANN model. Based on the developed ANN model, an ingenious iOS App was developed, the global clinician may utilize the App to meticulously predict post-Streptococcus mutans on iPhone based on pre-Streptococcus mutans, which in turn aids in decision making for the selection of caries excavation method. This study manifests the potential application of iOS App with built-in ANN model in efficiently predicting the post-Streptococcus mutans. Also, the study extends scope for applications of iOS App with built-in ANN models in clinical medicine.

Geopolymer is the alternative to current construction material trends. In this paper, an attempt is made to produce a sustainable construction composite material using geopolymer. Ground granulated blast furnace slag (GGBS)-based geopolymer concrete was prepared and tested for different alkaline to binder ratios (A/B). The effect of various temperatures on compressive strength properties was assessed. The cubes were exposed to temperature ranging from 50 to 70 °C for a duration ranging from 2 to 10 h, and the compressive strength of the specimens was analyzed for destructive and non-destructive analysis and tested for 7, 28, and 90 days. The obtained compressive strength (CS) results were analyzed employing the probability plot (PP) curve, distribution overview curve (DOC), probability density function (PDF), Weibull, survival, and hazard function curve. Maximum compressive strength was achieved for the temperature of 70 °C and an A/B of 0.45 for destructive tests and non-destructive tests with 44.6 MPa and 43.56 MPa, respectively, on 90 days of testing. The survival and hazard function curves showed incremental distribution characteristics for 28 and 90 days of testing results with a probability factor ranging from 0.8 to 1.0.