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- Kristensson, K, et al.
(author)
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Distribution of protein tracers in the nervous system of the crayfish (Astacus astacus L) following systemic and local application
- 1972
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In: Journal of Neurocytology. - 0300-4864. ; 1, s. 35-48
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Journal article (peer-reviewed)abstract
- A study was made on the penetration and cellular uptake of two protein tracers, albumin labelled with Evans blue (EBA) and horseradish peroxidase (HP), in the nervous system of the crayfish following systemic and local administration. Followingsystemic injection, EBA did not diffuse freely from the cerebral vessels into the brain parenchyma. When the tracers werelocally applied on the surface of the ventral nerve cord their penetration into the nervous parenchyma was to some extent restricted by the nerve sheath. However, unlike the perineurium of vertebrate peripheral nerves, which acts as an efficient diffusion barrier, the crayfish nerve sheath allowed the diffusion of small amounts of tracers into the ganglia. The tracers could more readily penetrate into peripheral nerves in the vicinity of ganglia. Inside the ganglion the tracers spread in extracellular spaces, between glial cell membranes and reached the neuronal surfaces. The proteins were taken up by pinocytosis in glial cells, and also in axons.
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- Olsson, Gustaf, et al.
(author)
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Modeling and Identification of a Nuclear Reactor
- 1976
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In: System Identification Advances and Case Studies. - 0076-5392. - 9780124879508 ; 126, s. 519-593
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Book chapter (peer-reviewed)abstract
- Some representative results from modeling and identification experiments on the Halden boiling water reactor (HBWR) in Norway are presented in this chapter. Linear input–output models, as well as time invariant and time variable linear state models, have been used as model structures. The chapter describes the different phases of identification and modeling of a complex dynamical system. Different identification methods have been used to demonstrate the applicability of identification techniques as a tool to explore the dynamics of a nuclear reactor. Four different approaches to the model-building techniques are investigated in the chapter: (1) multiple-input–single-output models with no á priori assumption about physical behavior, (2) multivariable (vector difference) models without physical á priori knowledge, (3) the estimation of parameters in linear time invariant state models with known structure and á priori noise structure assumptions, and (4) estimation of time variable parameters in linear stochastic state models.
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