Biomedical subjects

Katarzyna Sznajd-Weron

Publications and source records attributed to Katarzyna Sznajd-Weron.

5 recordsLinked to original sources

PubMed2007

Noninvasive measurement of intracranial pressure: is it possible?

BACKGROUND: Some publications suggest a strong correlation between the intracranial pressure and the intraocular pressure. Other studies claim no correlation between these two physiologic variables. Our aim was to study whether the tonometry could be a useful method to evaluate intracranial pressure in patients with suspected intracranial abnormality. METHODS: We evaluated the correlation between the intracranial pressure and the intraocular pressure, the intracranial pressure and the mean arterial pressure, and the intraocular pressure and the mean arterial pressure in 22 patients, initially comatose, who were admitted to our hospital. All patients required the intracranial pressure monitoring on clinical grounds. Simultaneous measurements were performed and recorded. RESULTS: We calculated both the linear correlation coefficient and the Spearman rank-order correlation coefficient. We found significant correlation between the intraocular pressure and the mean arterial pressure in 12 patients; however, significant correlation between the intraocular pressure and the intracranial pressure was found in only 2 patients. CONCLUSION: Tonometry is not an appropriate method for the assessment of intracranial pressure increases.

Adult↗

PubMed2006

Inflow versus outflow zero-temperature dynamics in one dimension.

It has been suggested that Glauber (inflow) and Sznajd (outflow) zero-temperature dynamics for the one-dimensional Ising ferromagnet with nearest-neighbor interactions are equivalent. Here we compare the two dynamics from the analytical and computational points of view. We use the method of mapping an Ising spin system onto the dimer RSA model and show that already this simple mapping allows us to see the differences between inflow and outflow zero-temperature dynamics. Then we investigate both dynamics with synchronous, partially synchronous, and random sequential updating using the Monte Carlo technique and compare both dynamics in the number of persistent spins, clusters, mean relaxation time, and relaxation time distribution.

Journal Article↗

PubMed2005

Metastabilities in the degenerated phase of the two-component model.

In previous papers, we have introduced a new dynamical model of Ising spins, namely the two-component (TC) model. Using the Boltzmann factor, in this paper we introduce parameter T to the model. This is the standard method for introducing temperature. However, since we have not defined the energy for the TC model, but only the disagreement function, we will not call this parameter temperature. We will investigate the system in its degenerated phase, which consists of four qualitatively different steady states at T = 0. We will show that for T>0, three of these steady states become metastable, and that above T = T* they become unstable. In the range 0<T< T*, the evolution of the system consists of relatively long stagnation periods, where the system remains in one of the metastable states, and rapid transition periods, where the system goes from one metastable state to another. In this range, the distribution function of waiting times needed to reach one of the states (steady for T = 0) has an exponential tail with a T-dependent exponent.

Journal Article↗

PubMed2005

Mean-field results for the two-component model.

In previous papers we have introduced a new dynamical model of Ising spins: the two-component (TC) model. In this paper we formulate a mean-field version of the TC model by putting it on a complete graph. With such an approach we are able to describe the kinetics in terms of a one-dimensional stochastic process with hopping probabilities depending on the magnetization. This allows us to understand the differences in relaxation between phases observed previously in computer simulations for the TC model on the square lattice.

Journal Article↗

PubMed2004

Dynamical model of Ising spins.

A two-dimensional dynamical model of Ising spins is introduced. Since we were not able to define energy in our system, we introduced an object called the disagreement function. This function controls the dynamics-minimizing it locally we decide upon spin flipping. Amazingly, local minimization of the disagreement function can lead to an increase of its global value. We present the phase diagram of the system and show that exactly the same initial conditions can lead the system to one of several, completely different final steady states.

Journal Article↗