The Hybrid System for the Magnetic Characterization of Superparamagnetic Nanoparticles.

The characterization of nanoparticles is crucial in several medical applications, such as hyperthermic therapy, which heats superparamagnetic nanoparticles with an external electromagnetic field. The knowledge of heating ability (magnetic losses) in AC magnetic field frequency function allows for selecting the optimal excitation. A hybrid system for the characterization of superparamagnetic nanoparticles was designed and tested. The proposed setup consists of an excitation coil and two sensing probes: calorimetric and magnetic. The measurements of the imaginary part of the complex magnetic susceptibility of superparamagnetic nanoparticles are possible in the kilohertz range. The system was verified using a set of nanoparticles with different diameters. The measurement procedure was described and verified. The results confirmed that an elaborated sensor system and measuring procedures could properly characterize the magnetic characteristics of nanoparticles. The main advantage of this system is the ability to compare both characteristics and confirm the selection of optimal excitation parameters.

Performance of an openEHR based hospital information system.

BACKGROUND: A desirable feature of hospital information systems is interoperability, which is generally quite limited due to the lack of standardization of the data model. This results in high development and maintenance costs for such systems. The openEHR standard addresses this problem. Due to its two-level modelling, it allows the separation of demographic and medical data and the storage of this data so that it can be easily processed and exchanged. However, it introduces an additional software layer that may affect system performance. This article examines the performance of a system based on the openEHR standard and compares it with the performance of a proprietary system developed in a classic way. METHODS: Two hospital information systems with the same functionality were designed and developed. One was based on an openEHR server, and another was using proprietary data model having both demographic and medical data. Systems were deployed on Azure platform and load tests using JMeter were conducted to calculate statistics of elapsed time of requests as well as throughput of both systems. RESULTS: Endpoints which fetch only demographic data had the same performance, but when medical data had to be queried, a decrease in performance of the openEHR based system was noticed. The system based on a proprietary data had about 6 times bigger throughput in terms of medical data fetching. CONCLUSIONS: OpenEHR adds another layer to the architecture of a hospital information system which might result in performance issues. Such a system must be designed to operate on a sufficiently strong architecture if it is intended to serve many users.