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In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.
Not only is the number of new devices constantly increasing, but so is their application complexity and power. Most of their applications are in optics, photonics, acoustic and mobile devices. Working speed and functionality is achieved in most of media devices by strategic use of digital signal processors and microcontrollers of the new generation. Considering all these premises of media development dynamics, the authors present how to integrate microcontrollers and digital signal processors in the curricula of media technology lectures by using adequate content. This also includes interdisciplinary content that consists of using the acquired knowledge in media software. These entries offer a deeper understanding of photonics, acoustics and media engineering.
We report the use of the Raman spectral information of the chemical compound toluene C7H8 as a reference on the analysis of laboratory-prepared and commercially acquired gasoline-ethanol blends. The rate behavior of the characteristic Raman lines of toluene and gasoline has enabled the approximated quantification of this additive in commercial gasoline-ethanol mixtures. This rate behavior has been obtained from the Raman spectra of gasoline-ethanol blends with different proportions of toluene.
All these Raman spectra have been collected by using a self-designed, frequency precise and low-cost Fourier-transform Raman spectrometer (FT-Raman spectrometer) prototype. This FT-Raman prototype has helped to accurately confirm the frequency position of the main characteristic Raman lines of toluene present on the different gasoline-ethanol samples analyzed at smaller proportions than those commonly found in commercial gasoline-ethanol blends. The frequency accuracy validation has been performed by analyzing the same set of toluene samples with two additional state-of-the-art commercial FT-Raman devices. Additionally, the spectral information has been contrasted, with highly-correlated coefficients as a result, with the values of the standard Raman spectrum of toluene.
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