Tribulus terrestris L. is a herb renowned for its abundance of saponins, flavonoids, and alkaloids, which are utilized in treating various health conditions. Protodioscin functions by enhancing the conversion of testosterone into potent dihydrotestosterone, stimulating an increase in libido, red blood cell production from the bone marrow, and muscle development. Contemporary ultrasound-assisted-extraction (UAE) process employing green extraction solvents was selected to design the required separation system. The experimental plan was developed based on the independent operating variables - extraction time, operating temperature and solvent system composition in order to determine the influence of defined parameters and their interactions on the extraction yield and the presence of protodioscin. The 3D-RSM approach was introduced to determine the optimal values of studied independent variables in the area of maximal extraction yield. UAE process performed at optimal operating conditions generated maximal extraction yield (31 %, w/w) and protodioscin content of 5.9 mg/g dry plant matrix. Experimental data was used to develop an ANN for the defined extraction system using the operating variables values as the input matrix and observed yield as target matrix. Successfully designed and trained ANN generated high correlation (r = 0.9992) between observed data and predictive model' outputs, and MSE value of 0.29107.

In recent decades, due to the rapid development and application of wireless communication, flexible electronics, and smart devices, electromagnetic interference (EMI) and radiation pollution have been intensified, creating an urgent demand for efficient EMI shielding materials. Carbon nanostructures such as graphene and carbon nanotubes are considered promising candidates due to their excellent properties, such as high electrical conductivity, low density, large specific surface area, and flexibility. This work reports our recent results in the design and testing of polymer nanocomposites with irradiated hybrid carbon nanostructure (graphene/multi-walled carbon nanotubes) used as EMI shielding materials. Five representative composites with varying filler loadings (AH of 15% and AM1 of 20 wt%), thicknesses (0.208–0.48 mm), and e-beam irradiation doses (from 50 to 400 kGy) were systematically characterized using SEM, FTIR, TGA/DSC, and vector network analyzer (VNA) measurements in the S-band (2.65–3.90 GHz). The effects of different e-beam irradiation doses and hybrid carbon contents on conductive network construction, interface engineering, and porous or layered structures on EMI shielding performance are discussed. Experimental results show that all studied composites exhibited strong absorption-dominant behavior (SE_A), while the multiple reflection component (SE_M) was found to be negligible. Both filler loading and sample thickness significantly enhanced shielding performance, with a pronounced synergistic interaction observed between these parameters. A quadratic Response Surface Methodology (RSM) model was developed to correlate the total shielding effectiveness (SE_T) with thickness and filler content, yielding high predictive accuracy (R² > 0.96). The model enables efficient optimization of composite design for targeted shielding levels.

Dry tomato peels were investigated as a natural source of lycopene in this study. Microwave-assisted extraction (MAE) was used for the isolation of bioactive compound of interest. The MAE was performed at a microwave power of 120, 230, and 385 W for a duration of 2, 5, 8, and 10 min. The concentration of lycopene in the separated extract with n-hexane was quantified by UV/Vis spectrophotometer. The absorbance at 501 nm was selected for the determination of lycopene content and the calculation of lycopene yield (mg/100 g). An adequate feedforward artificial neural network (ANN) model with architecture 2-10-1, trained by the Levenberg-Marquardt (LM) backpropagation algorithm was developed for modeling the MAE process and for the prediction of the lycopene yield. The model predicted lycopene yield with a high coefficient of determination R2=0.9957 and low mean squared error MSE=0.475. The response surface methodology (RSM) was successfully applied and combined with the ANN model to optimize the MAE process with R2=0.9477 and a low mean absolute error MAE=1.84507. The analysis of variance showed that extraction time and time-squared have statistically significant effects on the lycopene yield. The created 3D response surface showed that the optimum lycopene yield was 27.25 mg/100g of tomato peels at the microwave power of 324 W and extraction time of 8.6 min.