Prevention of indwelling central venous catheter sepsis

In an attempt to decrease the incidence of central venous catheter sepsis in children with cancer, we conducted a study to evaluate the benefit of adding broad-spectrum antibiotics to the catheter "flush solution." In a prospective, placebo-controlled, double-blinded, randomized trial, 69 children with different types of malignancies were studied. The central venous catheters in these children were flushed with either the standard solution (normal saline + 100 U/ml of heparin) or the study solution (25 microgram/ml of both amikacin and vancomycin added to the standard solution). At the conclusion of the study, 64 children with a total of 67 indwelling central venous lines were assessable. The total catheter days on study were 20,700 days, with a median of 323 catheter days per patient. We documented 10 events of catheter-related infections (0.49 events/1,000 catheter days at risk). Five of these events were catheter-related sepsis (0.24 sepses/1,000 catheter days): two were fungal and three were bacterial. Due to the low incidence of catheter-related sepsis in this study, no statement regarding the prophylactic use of antibiotics could be made. The extremely low rate of catheter-related sepsis reported herein may be retrospectively attributed to continuous staff education regarding aseptic techniques in handling these catheters. Staff education is essential, and probably the most effective factor in preventing catheter-related sepsis.     

EcoTRADE – A multi-player network game of a tradable permit market for biodiversity credits

EcoTRADE is a multi-player network game of a virtual biodiversity credit market. Each player controls the land use of a certain amount of parcels on a virtual landscape. The biodiversity credits of a particular parcel depend on neighboring parcels, which may be owned by other players. The game can be used to study the strategies of players in experiments or classroom games and as a communication tool for stakeholders participating in credit markets that include spatially interdependent credits.     

A comprehensive solution for application‐level adaptation

Driven by the emergence of mobile and pervasive computing there is a growing demand for context‐aware software systems that can dynamically adapt to their run‐time environment. We present the results of project MADAM that has delivered a comprehensive solution for the development and operation of context‐aware, self‐adaptive applications. The main contributions of MADAM are (a) a sophisticated middleware that supports the dynamic adaptation of component‐based applications, and (b) an innovative model‐driven development methodology that is based on abstract adaptation models and corresponding model‐to‐code transformations. MADAM has demonstrated the viability of a general, integrated approach to application‐level adaptation. We discuss our experiences with two real‐world case studies that were built using the MADAM approach. Copyright © 2008 John Wiley & Sons, Ltd.     

Certainty equivalence adaptation combined with super-twisting sliding-mode control

ABSTRACT

In this paper, a Lyapunov-based control concept is presented that combines variable structure and adaptive control. The considered system class consists of nonlinear single input systems which are affected by matched structured and unstructured uncertainties. Resorting to the certainty equivalence principle, the controller exploits advantages of both the sliding-mode and the adaptive control methodology. It is demonstrated that the gains of the discontinuous control action may be reduced remarkably when compared with pure sliding-mode-based approaches. The efficiency of the presented concept is demonstrated in detail, using results of numerical simulations.     

A Unified Variational Volume Registration Method Based on Automatically Learned Brain Structures

We introduce a new volumetric registration technique that effectively combines active surfaces with the finite element method. The method simultaneously aligns multi-label automatic structural segmentation results, which can be obtained by the application of existing segmentation software, to produce an anatomically accurate 3D registration. This registration is obtained by the minimization of a single energy functional. Just like registering raw images, obtaining a 3D registration this way still requires solving a fundamentally ill-posed problem. We explain through academic examples as well as an MRI dataset with manual anatomical labels, which are hidden from the registration method, how the quality of a registration method can be measured and the advantages our approach offers.     

Convenient spatial profiling of pulsed laser beams

This paper describes a convenient method for spatial profiling of pulsed laser beams using the scanning knife-edge technique. This method is applied to a Nd:YAG laser and a chopped CO2 laser.     

Reduction of Timed Hybrid Systems

We consider a class of hybrid dynamical systems and obtain conditions under which the behavior of these systems can be reduced to a finite state automaton. Specifically, we consider timed automata with more general enabling regions coupling the continuous and discrete dynamics than those previously considered. We provide a necessary condition for the existence of a finite state reduction, together with examples showing that this condition is not sufficient. We then give two sufficient conditions that provide a large class of systems with general enabling regions which admit finite reductions.     

Extracting Hidden Context

Concept drift due to hidden changes in context complicates learning in many domains including financial prediction, medical diagnosis, and communication network performance. Existing machine learning approaches to this problem use an incremental learning, on-line paradigm. Batch, off-line learners tend to be ineffective in domains with hidden changes in context as they assume that the training set is homogeneous. An off-line, meta-learning approach for the identification of hidden context is presented. The new approach uses an existing batch learner and the process of contextual clustering to identify stable hidden contexts and the associated context specific, locally stable concepts. The approach is broadly applicable to the extraction of context reflected in time and spatial attributes. Several algorithms for the approach are presented and evaluated. A successful application of the approach to a complex flight simulator control task is also presented.     

Iron‐mediated lipid oxidation in 70% fish oil‐in‐water emulsions: effect of emulsifier type and pH

The objective of this study was to investigate the protective effect of five different emulsifiers on iron‐mediated lipid oxidation in 70% fish oil‐in‐water emulsions. The emulsifiers were either based on protein (whey protein isolate and sodium caseinate) or based on phospholipid (soy lecithin and two milk phospholipids with different phospholipid contents, MPL20 and MPL75). Lipid oxidation was studied at pH 4.5 and 7.0, and results were compared to lipid oxidation in neat fish oil. Results showed that all emulsions oxidised more than neat oil. Furthermore, emulsions prepared with proteins oxidised more at low pH than at high pH, and casein emulsions oxidised the least (Peroxide value (PV) at day 7 was 0.5–0.7 meq kg^?1). Among emulsions prepared with phospholipids, emulsions with MPL75 were the most oxidised followed by emulsions prepared with lecithin and MPL20. Thus, PV in MPL75 emulsions was 5.0–5.5 meq kg^?1 at day 7 compared with 0.9–1.9 meq kg^?1 in MPL20 emulsions.