The cardiovascular system with its nervous control has been the focus of several mathematical modeling studies and numerous experimental investigations in the past. The purpose of the paper is to establish, by improving the existing models, an appropriate model of the cardiovascular system with its nervous control adapted to human characteristics. The research starts from a well-known model from the literature. Improvements are done in the ventricle compartments, considering the dynamics of the four heart valves and using a model for the elastance function based on human experimental data. Following correlation and calibration procedures the resulted model reveals for a normal scenario a behavior closer to reality.

 We present control problems related to a three compartmental model of combinations of antiangiogenic treatment with chemotherapy. The line of reasoning is based on the idea of Hahnfeldt et al.(1999) with modifications resulting from the use of multiple modalities and effects of drug resistance. We present analysis of dynamic properties of the models and some simulation results for different treatment protocols.

 Machine vision algorithms provide significant benefits for Lab-on-Chip (LoC) systems by automating the experimental process. This paper presents an FPGA-based machine vision flow detection implementation for microfluidic Lab-on-Chip (LoC) experiments. We propose and implement a novel architecture that exploits modern FPGA parallelism capabilities and makes efficient use of device resources to achieve real-time data collection in megapixel resolutions, at rates exceeding 30000 frames per second

 AbstractThis study presents multivariable control strategies for humidity and temperature for neonate incubator.This process is TITO system (Tow Input Tow output). Identification process of incubator is the first step for design and implementation controller. An experiment method is proposed to determine the transfer function matrix, which decouples the TITO system into four independent loops. Discrete-time system transfer matrix parameters were estimated in real time by the least-squares method. Secondly we take into account couplings between outputs and we consider a decoupling controller to eliminate the strong interaction. After that we develop a generalized predictive decoupled control. At last the simulation results demonstrate the effectiveness of this proposed strategy.

 Several methods allow to measure arterial distensibilty. One of them consists in estimating the direct distensibility (D) from diameter and distending blood pressure. Herein, we propose a new method to assess the distensibility in small arteries which is based on spectral analysis of time motion mode ultrasound images of radial arteries. A Fourier transform was performed on intensity of upper and lower walls. Spectral amplitude at heart frequency from both wall spectra was estimated and summed (SumAmp). SumAmp was then compared with direct distensibility. A significant correlation was found between SumAmp and D (r = 0.7, p = 0.02).