Results of applying sensor fusion to a control system using optic flow

The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

The relationship between membrane damage, release of protein and loss of viability in Escherichia coli exposed to high hydrostatic pressure

The aim of this work was to examine a possible association between resistance of two Escherichia coli strains to high hydrostatic pressure and the susceptibility of their cell membranes to pressure-induced damage. Cells were exposed to pressures between 100 and 700 MPa at room temperature (~20C) in phosphate-buffered-saline. In the more pressure-sensitive strain E. coli 8164, loss of viability occurred at pressures between 100 MPa and 300 MPa and coincided with irreversible loss of membrane integrity as indicated by uptake of propidium iodide (PI) and leakage of protein of molecular mass between 9 and 78 kDa from the cells. Protein release increased to a maximum at 400 MPa then decreased, possibly due to intracellular aggregation at the higher pressures. In the pressure-resistant strain E. coli J1, PI was taken up during pressure treatment but not after decompression indicating that cells were able to reseal their membranes. Loss of viability in strain J1 coincided with the transient loss of membrane integrity between approximately 200 MPa and 600 MPa. In E. coli J1 leakage of protein occurred before loss of viability and the released protein was of low molecular mass, between 8 and 11 kDa and may have been of periplasmic origin. In these two strains differences in pressure resistance appeared to be related to differences in the ability of their membranes to withstand disruption by pressure. However it appears that transient loss of membrane integrity during pressure can lead to cell death irrespective of whether cells can reseal their membranes afterwards.

Adaptive modelling, estimation and fusion from data: a neurofuzzy approach

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input. This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

Image fusion based on median filters and SOFM neural networks: a three-step scheme

This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map (SOFM) neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image quality. It proves that such a three-step combination offers an impressive effectiveness and performance improvement, which is confirmed by simulations involving three image sensors (each of which has a different noise structure).

Improved process topology for membrane distillation

In membrane distillation in a conventional membrane module, the enthalpies of vaporisation and condensation are supplied and removed by changes in the temperatures of the feed and permeate streams, respectively. Less than 5% of the feed can be distilled in a single pass, because the potential changes in the enthalpies of the liquid streams are much smaller than the enthalpy of vaporisation. Furthermore, the driving force for mass transfer reduces as the feed stream temperature and vapour pressure fall during distillation. These restrictions can be avoided if the enthalpy of vaporisation is uncoupled from the heat capacities of the feed and permeate streams. A specified distillation can then be effected continuously in a single module. Calculations are presented which estimate the performance of a flat plate unit in which the enthalpy of distillation is supplied and removed by the condensing and boiling of thermal fluids in separate circuits, and the imposed temperature difference is independent of position. Because the mass flux through the membrane is dependent on vapour pressure, membrane distillation is suited to applications with a high membrane temperature. The maximum mass flux in the proposed module geometry is predicted to be 30 kg/m2 per h at atmospheric pressure when the membrane temperature is 65°C. Operation at higher membrane temperatures is predicted to raise the mass flux, for example to 85 kg/m2 per h at a membrane temperature of 100°C. This would require pressurisation to 20 bar to prevent boiling at the heating plate of the feed channel. Pre-pressurisation of the membrane pores and control of the dissolved gas concentrations in the feed and the recyled permeate should be investigated as a means to achieve high temperature membrane distillation without pore penetration and wetting.

Direct contact membrane distillation

This review looks at the work carried out over the past 15 years on membrane distillation and reports the conditions utilized for research. The process is still used mainly at the laboratory scale, but a few pilot plants have been built across the world, mostly for desalination and the production of potable water. Studies into membrane distillation have been concerned with the effect of mass transfer, heat transfer, and stirring rate, but the most important effect that has to be considered with this process is temperature polarization. A section on temperature polarization and the effect of boundary layers is included in this review.

Permeate flux modeling of membrane distillation

This paper concerns the modeling of membrane distillation. The model developed has been used to predict permeate fluxes using different initial operating conditions. PVDF and PTFE membranes were successfully used in a flat plate module to experimentally confirm the theoretical results. The correlation between theory and experiment was close for both membranes. The PTFE membranes produced higher fluxes than PVDF. A Versapor membrane was also used for this work. This membrane is a composite, with a thin porous layer on a support layer. It was found not to be suitable for membrane distillation. A comparison of the heat flux was also carried out. Again, there was good correlation between theory and experiment

Advances in module design for membrane distillation

This review looks at the work carried out over the past 15 years on membrane distillation and reports the conditions utilized for research. The process is still used mainly at the laboratory scale, but a few pilot plants have been built across the world, mostly for desalination and the production of potable water. Studies into membrane distillation have been concerned with the effect of mass transfer, heat transfer, and stirring rate, but the most important effect that has to be considered with this process is temperature polarization. A section on temperature polarization and the effect of boundary layers is included in this review.

Tissue engineering a fetal membrane

The aim of this study was to construct an artificial fetal membrane (FM) by combination of human amniotic epithelial stem cells (hAESCs) and a mechanically enhanced collagen scaffold containing encapsulated human amniotic stromal fibroblasts (hASFs). Such a tissue-engineered FM may have the potential to plug structural defects in the amniotic sac after antenatal interventions, or to prevent preterm premature rupture of the FM. The hAESCs and hASFs were isolated from human fetal amniotic membrane (AM). Magnetic cell sorting was used to enrich the hAESCs by positive ATP-binding cassette G2 selection. We investigated the use of a laminin/fibronectin (1:1)-coated compressed collagen gel as a novel scaffold to support the growth of hAESCs. A type I collagen gel was dehydrated to form a material mimicking the mechanical properties and ultra-structure of human AM. hAESCs successfully adhered to and formed a monolayer upon the biomimetic collagen scaffold. The resulting artificial membrane shared a high degree of similarity in cell morphology, protein expression profiles, and structure to normal fetal AM. This study provides the first line of evidence that a compacted collagen gel containing hASFs could adequately support hAESCs adhesion and differentiation to a degree that is comparable to the normal human fetal AM in terms of structure and maintenance of cell phenotype.