Time-Frequency (t-f) distributions are frequently employed for analysis of new-born EEG signals because of their non-stationary characteristics. Most of the existing time-frequency distributions fail to concentrate energy for a multicomponent signal having multiple directions of energy distribution in the t-f domain. In order to analyse such signals, we propose an Adaptive Directional Time-Frequency Distribution (ADTFD). The ADTFD outperforms other adaptive kernel and fixed kernel TFDs in terms of its ability to achieve high resolution for EEG seizure signals. It is also shown that the ADTFD can be used to define new time-frequency features that can lead to better classification of EEG signals, e.g. the use of the ADTFD leads to 97.5% total accuracy, which is by 2% more than the results achieved by the other methods.
The pollen morphology of many collections of taxa of the tribe Nigelleae from the family Ranunculaceae which occur worldwide is presented in this study. A total of 88 specimens from 21 taxa, some of which were recently proposed, belonging to the genera Komaroffia, Garidella, and Nigella of Nigelleae were examined using light microscopy (LM) and scanning electron microscopy (SEM). In the tribe, the pollen type is mostly trizonocolpate, but in many taxa and specimens, both trizonocolpate and non-trizonocolpate types occur together. The pollen grains are small to medium (25–53.75 μm × 20–55 μm) in size and oblate to prolate in shape. The exine pattern at the mesocolpium in all the taxa investigated is similar: micro-echinate in LM and micro-echinate-punctate in SEM. The colpus membrane in Komaroffia and Nigella is micro-echinate in both LM and SEM. In Garidella, it is micro-echinate in LM but echinate (spinulose) in SEM. In this study, multivariate analyses, principal component analysis (PCA), and unweighted pair group method with arithmetic mean (UPGMA), were used to evaluate relationships between the genera and species within the tribe with respect to pollen morphology. PCA results show three main groups in the tribe: Garidella, Komaroffia, and Nigella. Moreover, the UPGMA tree also chiefly supports generic segregation into the smaller genera. An overall synthesis of the pollen characteristics of the three genera is provided and discussed.
This work presents a simulation of the response of packets of microbubbles in an ultrasonic pulse-echo scan line. Rayleigh-Plesset equation has been used to predict the echo from numerically obtained radial dynamics of microbubbles. Varying the number of scattering microbubbles on the pulse wave form has been discussed. To improve microbubble-specific imaging at high frequencies, the subharmonic and second harmonic signals from individual microbubbles as well as microbubbles packets were simulated as a function of size and pressure. Two different modes of harmonic generation have been distinguished. The strength and bandwidth of the subharmonic component in the scattering spectrum of microbubbles is greater than that of the second harmonic. The pressure spectra provide quantitative and detailed information on the dynamic behaviour of ultrasound contrast agent microbubbles packet.
In this work, an approach to the design of broadband thickness-mode piezoelectric transducer is pre- sented. In this approach, simulation of discrete time model of the impulse response of matched and backed piezoelectric transducer is used to design high sensitivity, broad bandwidth, and short-duration impulse response transducers. The effect of matching the performance of transmitting and receiving air backed PZT-5A transducer working into water load is studied. The optimum acoustical characteristics of the quarter wavelength matching layers are determined by a compromise between sensitivity and pulse duration. The thickness of bonding layers is smaller than that of the quarter wavelength matching layers so that they do not change the resonance peak significantly. Our calculations show that the −3 dB air backed transducer bandwidth can be improved considerably by using quarter wavelength matching layers. The computer model developed in this work to predict the behavior of multilayer structures driven by a transient waveform agrees well with measured results. Furthermore, the advantage of this this model over other approaches is that the time signal for optimum set of matching layers can be predicted rapidly