Catálogo de publicaciones - libros

We present a further step in developing an in silico model that simulates the immune system responses to tumor cells in vaccinated mice. Our study is based on our previous model that simulates the cancer – immune System competition activated by a tumor vaccine. In what follows, we show first results on effects of deconstructing the components of Triplex vaccine that are in very good agreement with in vivo results.

Detecting individual microbubbles is important for the quantification of the amount of bubbles in the tissues, determination of microvascular volume and targeted microbubble imaging. We took the advantage of a theoretical bubble oscillation model to construct a matched wavelet, bubble wavelet as mother wavelet to detect individual microbubble using wavelet transform. The experimental echoes with different levels of added noises were processed. The results showed significant improvement even for an Echo-Noise-Ratio () of -20 dB and the spatial location demonstrated very close agreement with the original experimental echo. This technique was much better than those based on harmonic analysis especially under the circumstance of short pulse insonation.

This paper presents a new approach to detect depth of anaesthesia by using recurrence quantification analysis of electroencephalogram (EEG) and artificial neural network(ANN) . From 98 consenting patient experiments, 98 distinct EEG recordings were collected prior to incision during isoflurane anaesthesia of different levels. The seven measures of recurrence plot were extracted from each of four-channel EEG time series. Prediction was made by means of ANN. Training and testing the ANN used the ‘leave-one-out’ method. The prediction was tested by monitoring the responses to incision. The system was able to correctly classify purposeful responses in average accuracy of 92.86% of the cases. This method is also computationally fast and acceptable real-time clinical performance was obtained.

Contribution of chemical shift to intermolecular multiple-quantum coherence (iMQC) imaging signals in two-component systems was simulated and discussed using an efficient numerical algorithm based on the Bloch equations with an additional nonlinear term describing distant dipolar field. Numerical simulation switches back and forth between real and Fourier spaces to handle dipolar field effects in three-dimensional sample. The iMQC signals of each component of two-component systems can be obtained respectively when the second pulse of the CRAZED pulse sequence is selective. Simulation results show that chemical shift provides an edge detection method to regions containing spins with chemical shift offset and selected by the second RF pulse, and different gray value is related to different chemical shift in detected regions. These results indicate that chemical shift may provide new imaging information helpful for iMQC magnetic resonance imaging.

We discuss secrecy of signals in signal transduction. As we have developed a basic concurrent language with interferencial coefficients, Iπ - calculus , to describe aberrance in biological models, a typing system for Iπ - calculus is proposed for achieving secrecy of signals in signal transduction. We show that this typing system guarantees that, if signal transduction typechecks, then it does not leak aberrance of signals.

A novel detection algorithm for V-BLAST system is proposed, based on the clonal selection theory and the idea of immune evolution. The complexity of the clonal selection detection algorithm for V-BLAST system (CA-VBLAST) is analyzed and the bit error ratio (BER) performance is verified via computer simulations. Simulation results show that the BER performance of CA-VBLAST detector with proper algorithm parameters is comparable with the maximum likelihood (ML) detector which presents the best BER performance but the highest computational complexity, and our CA-VBLAST detector obtains a much more decreased complexity.

In order to improve error resilient capability and transmission efficiency for image transmission over wireless channels, a joint source channel coding (JSCC) scheme was proposed. Adaptive segmentation can segment an image into different size of block with different level of significance; high degree bit nodes within an irregular low-density parity check (LDPC) code can provide unequal error protection (UEP) scheme. So the adaptive segmentation and irregular LDPC coding were combined together to provide JSCC. Simulation results show that the proposed scheme can support robust image transmission in a very effective way with high visual quality.

Wireless sensor and actor networks (WSANs) are composed of a large number of sensors and a small number of (mobile) resource-rich actors. Sensors gather information about the physical phenomenon, while actors take decisions and then perform appropriate actions upon the environment. Real time and network lifetime are important factors of WSANs. So in this paper, a single-actor selection problem for WSANs is addressed from real time and nodes’ Relay Bound constraints first, and then a multi-objective programming is provided. After that, two approximate algorithms, Global Relay-Bounded and MIN-MAX Hops (GRBMMH) and Distributed Relay-Bounded and MIN-MAX Hops (DRBMMH), are put forward. In the performance evaluation, those algorithms are compared with MECT (Minimum Energy Cost Tree) and MPLCT (Minimum Path Length Cost Tree) algorithms.

Future high-speed networks will simultaneously support multiple types of services over a single physical infrastructure. Packet scheduling discipline is a crucial technique to enable this. This paper proposes a new weighted fair queuing discipline – Probability based Weighted Fair Queueing, P-WFQ – for high-speed, integrated-service, packet-switched networks. P-WFQ reduces the complexity of implementation by avoiding the main problem of traditional weighted fair queueing algorithm – the calculation of the weight parameter for each packet. It uses a random number to find the next packet to be serviced. In addition, it uses a novel grouping technology, which congregates large number of different flows into a smaller number of groups and reduces the complexity of P-WFQ greatly. This makes it suit for high-speed networks. The simulations prove the validity and practicability of P-WFQ.

A new method for synthesis of fiber Bragg gratings based filter is proposed. By combining the transmission matrix method and the particles swarm optimization algorithm, we obtain a novel method for the inverse problem of the synthesizing fiber gratings. With adjusting the parameters of the PSO algorithm we can get the demand index modulation for the target reflection spectrums including the phase response. Compared with other synthesis methods, the PSO algorithm characteristics are simple and faster convergence, especially by using the improved local PSO (LPSO) algorithm, we obtained the better results for the same problem.