Ficus plants are commonly planted as ornamentals along roadsides in Malaysia. In 2010, Ficus plants in Kuala Terengganu were found to be attacked by a moth, identified as Trilocha varians. The larvae of this moth fed on Ficus leaves causing up to 100% defoliation. This study was conducted to determine the life cycle of T. varians under two different environmental temperatures and to control this pest using two different insecticides. Our findings showed that there were significant differences in the time taken for eggs to hatch and larval and pupation period between low and high environmental temperatures. Results also showed that fipronil had lower LT50 and LT95 than malathion. This study provides new information on the life history of T. varians under two different conditions and the efficiency in controlling T. varians larvae using insecticides. The results of this study are important for future management in controlling T. varians population especially in Kuala Terengganu, Malaysia.
Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states. The estimated bispectrum mapped in the contour plots show the different appearance of nonlinearity in the EEG signals for different emotional states. Bispectrum features were extracted from the alpha (8-13) Hz, beta (13-30) Hz and gamma (30-49) Hz bands, respectively. The k-nearest neighbor (KNN) and probabilistic neural network (PNN) classifiers were used to classify the six emotions in LBD, RBD and NC. The bispectrum features showed statistical significance for all three groups. The beta frequency band was the best performing EEG frequency-sub band for emotion classification. The combination of alpha to gamma bands provides the highest classification accuracy in both KNN and PNN classifiers. Sadness emotion records the highest classification, which was 65.37% in LBD, 71.48% in RBD and 75.56% in NC groups.