Measuring the reactivity of commercially available zero-valent iron nanoparticles used for environmental remediation with iopromide.

The high specific surface area and high reactivity of nanoscale zero-valent iron (nZVI) particles have led to much research on their application to environmental remediation. The reactivity of nZVI is affected by both the water chemistry and the properties of the particular type of nZVI particle used. We have investigated the reactivity of three types of commercially available Nanofer particles (from Nanoiron, s.

Mobility enhancement of nanoscale zero-valent iron in carbonate porous media through co-injection of polyelectrolytes.

The mobility of nanoscale zero-valent iron (nZVI), which is used for in situ groundwater remediation, is affected by chemical and physical heterogeneities within aquifers. Carbonate minerals in porous aquifers and the presence of divalent cations reduce nZVI mobility. This study assesses the potential for enhancing the mobility of polyacrylic acid coated nZVI (PAA-nZVI) in such aquifers through the co-injection of polyelectrolytes (natural organic matter, humic acid, carboxymethyl cellulose, and lignin sulfonate).

Carbonate minerals in porous media decrease mobility of polyacrylic acid modified zero-valent iron nanoparticles used for groundwater remediation.

The limited transport of nanoscale zero-valent iron (nZVI) in porous media is a major obstacle to its widespread application for in situ groundwater remediation. Previous studies on nZVI transport have mainly been carried out in quartz porous media. The effect of carbonate minerals, which often predominate in aquifers, has not been evaluated to date.

Process mining for clinical workflows: challenges and current limitations.

Process mining is an emerging technology in the context of Business Process Management with the goal to derive process models from observed system behavior. The global goals are: to detect previously unknown process structures, to implement consistent process controlling which may involve computation of realistic cycle times and frequency of occurrence of process pathways, or to quantify the conformance to guidelines. We did a detailed hands-on evaluation and analysis of established process-mining approaches and assessed their abilities to cope with the challenges of clinical environments.

Results from data mining in a radiology department: the relevance of data quality.

This work is part of an ongoing effort to examine and improve clinical workflows in radiology. Classical workflow analysis is time consuming and expensive. Here we present a purely data-driven approach using data mining techniques to detect causes for poor data quality and areas with poor workflow performance.