Constituents of the venom of a south african fire ant (solenopsis punctaticeps): 2,5-dialkylpyrrolidines and -pyrrolines,identification and synthesis

Structures of a series of 2,5-dialkylpyrrolidines and -pyrrolines isolated from the South African fire ant, Solenopsis punctaticeps, are determined by gas chromatography-mass spectrometry and confirmed by synthesis using the Hofmann-Löffler reaction on the corresponding primary amine.     

The Application of Advanced Signal Processing Techniques to Induction Motor Bearing Condition Diagnosis

Four approaches based on bispectral and wavelet analysis of vibration signals are investigated as signal processing techniques for application in the diagnosis of a number of induction motor rolling element bearing faults. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the bispectrum, the bispectrum diagonal slice, the summed bispectrum and wavelets. Singular value decomposition (SVD) is used to extract the most significant features from the vibration signatures and the features are used as inputs to an artificial neural network trained to identify the bearing faults. The results obtained show that the diagnostic system using a supervised multi-layer perceptron type neural network is capable of classifying bearing condition with high success rate, particularly when applied to summed bispectrum signatures.     

Crack detection in a rotating shaft using artificial neural networks and PSD characterisation

The diagnosis of cracks in rotating shafts using non-destructive techniques provides a route for avoiding catastrophic failure of these common components. This study measured the dynamic response of a full-scale rotating shaft with three different crack depths. A novel non-destructive system is developed and described. The system uses vertical vibration of the system measured over time and characterises its behaviour using elements of the power spectral density (PSD) gained from a fast Fourier transform of the time-history. The PSDs were used as an input into an artificial neural network (ANN) to detect the presence of cracks using changes in the spectral content of the vibration of the system. A novel method for reducing the amount of data input into the ANN is described. The Peak Position Component Method (PPCM) reduces data transfer by using statistical characterisation of the position of the peaks in the PSD. The peak positions represent a small fraction of the information contained in the total frequency range. The number of the PSD peaks used as input to the neural net is a small fraction of the total frequency range. The ANN was a supervised feed-forward network with Levenberg-Marquardt back-propagation algorithm acting on the PPCM results. The frequency spectrum for the three different crack lengths examined show clear shifts in the peak positions of the PSD and the results clearly demonstrate the feasibility of using the new system to detect cracks in-service.     

Recent results in insect pheromone chemistry

Pheromones are substances which are secreted to the outside by an animal, especially an insect, and received by a second individual of the same species, in which they release a specific reaction, for example, a definite behavior or developmental process. The name is derived from the Greek pherein (to bear, transmit) and hormon (impel, excite). Pheromones include, inter alia, sex attractants, warning substances, and “aggregation pheromones”. Many of these substances are effective at very low concentration. The insect pheromones are predominantly derivatives of long-chain, slightly branched hydrocarbons.