Fluxgate magnetic sensor with overload detection

A measurement system for magnetic fields and electric currents uses a single-core fluxgate device driven with a radio frequency excitation source and is provided with a means to indicate saturation of the core of the sensor. A means is provided for detecting overload of the sensor as the core approaches continuous saturation using a pair of demodulators and a comparator.

The use of object oriented modelling and simulation tools in constraint satisfaction for embodiment design

The software package Dymola, which implements the new, vendor-independent standard modelling language Modelica, exemplifies the emerging generation of object-oriented modelling and simulation tools. This paper shows how, in addition to its simulation capabilities, it may be used as an embodiment design tool, to size automatically a design assembled from a library of generic parametric components. The example used is a miniature model aircraft diesel engine. To this end, the component classes contain extra algebraic equations calculating the overload factor (or its reciprocal, the safety factor) for all the different modes of failure, such as buckling or tensile yield. Thus the simulation results contain the maximum overload or minimum safety factor for each failure mode along with the critical instant and the device state at which it occurs. The Dymola "Initial Conditions Calculation" function, controlled by a simple software script, may then be used to perform automatic component sizing. Each component is minimised in mass, subject to a chosen safety factor against failure, over a given operating cycle. Whilst the example is in the realm of mechanical design, it must be emphasised that the approach is equally applicable to the electrical or mechatronic domains, indeed to any design problem requiring numerical constraint satisfaction.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

A ferrofluid seal technology for fluidic microactuators

Recent research revealed that microacruators driven by pressurized fluids are able to generate high power and force densities at microscale. Despite these promising properties, fluidic actuators are rare in microsystem technology. The main technological barrier in the development of these actuators is the fabrication of powerful seals with low leakage. This paper presents a seal technology for linear fluidic microacruators based on ferrofluids. An accurate design method for these seals has been developed and validated by measurements on miniaturized actuator prototypes. Our current actuator prototypes are able to seal pressures up to 16 bar without leakage. The actuator has an outside diameter of 2 mm, a length of 13 mm and the actuator is able to generate forces of 0.65 N and a stroke of 10 mm. Moreover, promising properties such as the restoration of the seal after a pressure overload have been observed.

Assessment of dry weight by monitoring changes in blood volume during hemodialysis using Crit-Line.

BACKGROUND: Routine assessment of dry weight in chronic hemodialysis patients relies primarily on clinical evaluation of patient fluid status. We evaluated whether measurement of postdialytic vascular refill could assist in the assessment of dry weight. METHODS: Twenty-eight chronic, stable hemodialysis patients were studied during routine treatment sessions using constant dialysate temperature and dialysate sodium concentration, and relative changes in blood volume were monitored using Crit-Line III monitors throughout this study. The study was divided into three phases. Phase 1 studies evaluated the time-dependence of vascular compartment refill after completion of hemodialysis. Phase 2 studies evaluated the relationships in patient subgroups between intradialytic changes in blood volume and the presence of postdialytic vascular compartment refill during that last 10 minutes of hemodialysis after stopping ultrafiltration. Phase 3 studies evaluated the extent of dry weight changes following the application of a protocol for blood volume reduction, postdialytic vascular compartment refill, and correlation with clinical evidence of intradialytic hypovolemia and/or postdialytic fatigue. Phase 3 included anywhere from three to five treatments. RESULTS: Phase 1 studies demonstrated that despite interpatient variability in the magnitude of postdialytic vascular compartment refill, when significant refill was evident, it always continued for at least 30 minutes. However, the majority of refill took place within 10 minutes postdialysis. Phase 2 studies identified 3 groups of patients: those who exhibited intradialytic reductions in blood volume but not postdialytic vascular compartment refill (group 1), those who exhibited intradialytic reductions in blood volume and postdialytic vascular compartment refill (group 2), and those whose blood volume did not change substantially during hemodialysis treatment (group 3). In phase 3 studies, use of an ultrafiltration protocol for blood volume reduction and monitoring of postdialytic vascular compartment refill combined with clinical assessment of hypovolemia and postdialytic fatigue demonstrated that patients often had a clinical dry weight assessment which was too low or too high. In all 28 patients studied, dry weight was either increased or decreased following use of this protocol. CONCLUSION: Determination of the extent of both intradialytic decreases in blood volume and postdialytic vascular compartment refill, combined with clinical assessment of intradialytic hypovolemia and postdialytic fatigue, can help assess patient dry weight and optimize volume status while reducing dialysis associated morbidity. The number of hospital admissions due to fluid overload may be reduced.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.