Fruit quality sensing:Post-harvest ripeness

Firmness sensing of selected varieties of apples, pears and avocado fruits has been developed using a nondestructive impact technique. In addition to firmness measurements, postharvest ripeness of apples and pears was monitored by spectrophotometric reflectance measurements, and that of avocadoes by Hunter colour measurements. The data obtained from firmness sensing were analyzed by three analytical procedures: principal component, correlation and regression, and stepwise discriminant analysis. A new software was developed to control the impact test, analyse the data, and sort the fruit into specified classes, based on the criteria obtained from a training procedure. Similar procedures were used to analyse the reflectance and colour data. Both sensing systems were able to classify fruits w i th good accuracy.

Quorum sensing in Escherichia coli and Salmonella typhimurium

Escherichia coli and Salmonella typhimurium strains grown in Luria–Bertani medium containing glucose secrete a small soluble heat labile organic molecule that is involved in intercellular communication. The factor is not produced when the strains are grown in Luria–Bertani medium in the absence of glucose. Maximal secretion of the substance occurs in midexponential phase, and the extracellular activity is degraded as the glucose is depleted from the medium or by the onset of stationary phase. Destruction of the signaling molecule in stationary phase indicates that, in contrast to other quorum-sensing systems, quorum sensing in E. coli and S. typhimurium is critical for regulating behavior in the prestationary phase of growth. Our results further suggest that the signaling factor produced by E. coli and S. typhimurium is used to communicate both the cell density and the metabolic potential of the environment. Several laboratory and clinical strains of E. coli and S. typhimurium were screened for production of the signaling molecule, and most strains make it under conditions similar to those shown here for E. coli AB1157 and S. typhimurium LT2. However, we also show that E. coli strain DH5α does not make the soluble factor, indicating that this highly domesticated strain has lost the gene(s) or biosynthetic machinery necessary to produce the signaling substance. Implications for the involvement of quorum sensing in pathogenesis are discussed.

Quorum sensing controls expression of the type III secretion gene transcription and protein secretion in enterohemorrhagic and enteropathogenic Escherichia coli

Enterohemorrhagic Escherichia coli O157:H7 and enteropathogenic E. coli cause a characteristic histopathology in intestinal cells known as attaching and effacing. The attaching and effacing lesion is encoded by the Locus of Enterocyte Effacement (LEE) pathogenicity island, which encodes a type III secretion system, the intimin intestinal colonization factor, and the translocated intimin receptor protein that is translocated from the bacterium to the host epithelial cells. Using lacZ reporter gene fusions, we show that expression of the LEE operons encoding the type III secretion system, translocated intimin receptor, and intimin is regulated by quorum sensing in both enterohemorrhagic E. coli and enteropathogenic E. coli. The luxS gene recently shown to be responsible for production of autoinducer in the Vibrio harveyi and E. coli quorum-sensing systems is responsible for regulation of the LEE operons, as shown by the mutation and complementation of the luxS gene. Regulation of intestinal colonization factors by quorum sensing could play an important role in the pathogenesis of disease caused by these organisms. These results suggest that intestinal colonization by E. coli O157:H7, which has an unusually low infectious dose, could be induced by quorum sensing of signals produced by nonpathogenic E. coli of the normal intestinal flora.

Quorum-sensing acts at initiation of chromosomal replication in Escherichia coli

Chromosomal replication in Escherichia coli was studied by flow cytometry and was found to be inhibited by an extracellular factor present in conditioned media collected during late exponential and early stationary phase, i.e., via a quorum-sensing mechanism. Our results suggest that the inhibitory activity of the extracellular factor is exerted during initiation of DNA replication rather than during elongation. Furthermore, we present evidence that this interaction may occur directly at each of the replication forks. Unlike other quorum-sensing systems described so far for Gram-negative bacteria, this inhibitory activity does not require transcription or translation to be effective. Implications of quorum-sensing regulation of DNA replication are discussed.

Evaluation of remote sensing for the detection of landfill gas and leachate in an urban environment

The technique of remote sensing provides a unique view of the earth's surface and considerable areas can be surveyed in a short amount of time. The aim of this project was to evaluate whether remote sensing, particularly using the Airborne Thematic Mapper (ATM) with its wide spectral range, was capable of monitoring landfill sites within an urban environment with the aid of image processing and Geographical Information Systems (GIS) methods. The regions under study were in the West Midlands conurbation and consisted of a large area in what is locally known as the Black Country containing heavy industry intermingled with residential areas, and a large single active landfill in north Birmingham. When waste is collected in large volumes it decays and gives off pollutants. These pollutants, landfill gas and leachate (a liquid effluent), are known to be injurious to vegetation and can cause stress and death. Vegetation under stress can exhibit a physiological change, detectable by the remote sensing systems used. The chemical and biological reactions that create the pollutants are exothermic and the gas and leachate, if they leave the waste, can be warmer than their surroundings. Thermal imagery from the ATM (daylight and dawn) and thermal video were obtained and used to find thermal anomalies on the area under study. The results showed that vegetation stress is not a reliable indicator of landfill gas migration, as sites within an urban environment have a cover too complex for the effects to be identified. Gas emissions from two sites were successfully detected by all the thermal imagery with the thermal ATM being the best. Although the results were somewhat disappointing, recent technical advancements in the remote sensing systems used in this project would allow geo-registration of ATM imagery taken on different occasions and the elimination of the effects of solar insolation.

Tactile sensing with fibre Bragg gratings and neural networks

Fibre Bragg grating sensors are usually expensive to interrogate, and part of this thesis describes a low cost interrogation system for a group of such devices which can be indefinitely scaled up for larger numbers of sensors without requiring an increasingly broadband light source. It incorporates inherent temperature correction and also uses fewer photodiodes than the number or sensors it interrogates, using neural networks to interpret the photodiode data. A novel sensing arrangement using an FBG grating encapsulated in a silicone polymer is presented. This sensor is capable of distinguishing between different surface profiles with ridges 0.5 to 1mm deep and 2mm pitch and either triangular, semicircular or square in profile. Early experiments using neural networks to distinguish between these profiles are also presented. The potential applications for tactile sensing systems incorporating fibre Bragg gratings and neural networks are explored.

Distributive tactile sensing using fibre Bragg grating sensors

Two distributive tactile sensing systems are presented, based on fibre Bragg grating sensors. The first is a onedimensional metal strip with an array of 4 sensors, which is capable of detecting the magnitude and position of a contacting load. This system is compared experimentally with a similar system using resistive strain gauges. The second is a two-dimensional steel plate with 9 sensors which is able to distinguish the position and shape of a contacting load. This system is compared with a similar system using 16 infrared displacement sensors. Each system uses neural networks to process the sensor data to give information concerning the type of contact.

Distributive tactile sensing using fibre Bragg grating sensors for biomedical applications

Artificial tactile sensing systems using the distributive tactile sensing technique and fibre Bragg grating sensors are presented. A one-dimensional arrangement, with possible applications in an endoscope, is compared with a similar arrangement using conventional electronic sensors. A two-dimensional sensing surface is described, with potential applications in human balance and gait analysis, capable of detecting simultaneously the position and shape of an object placed upon it. It is believed that this work represents the first use of fibre Bragg grating sensors in a distributive sensing regime.

Distributive tactile sensing using fibre bragg grating sensors

Two distributive tactile sensing systems are presented, based on fibre Bragg grating sensors. The first is a one-dimensional metal strip with an array of 4 sensors, which is capable of detecting the magnitude and position of a contacting load. This system is compared experimentally with a similar system using resistive strain gauges. The second is a two-dimensional steel plate with 9 sensors which is able to distinguish the position and shape of a contacting load. This system is compared with a similar system using 16 infrared displacement sensors. Each system uses neural networks to process the sensor data to give information concerning the type of contact.

Optical immersion of mid-infrared LEDs and photodiodes for gas-sensing applications

The high gains in performance predicted for optical immersion are difficult to achieve in practice due to total internal reflection at the lens/detector interface. By reducing the air gap at this interface optical tunneling becomes possible and the predicted gains can be realized in practical devices. Using this technique we have demonstrated large performance gains by optically immersing mid-infrared heterostructure InA1Sb LEDs and photodiodes using hypershperical germanium lenses. The development of an effective method of optical immersion that gives excellent optical coupling has produced a photodiode with a peak room temperature detectivity (D*) of 5.3 x 109 cmHz½W-1 at λpeak=5.4μm and a 40° field of view. A hyperspherically immersed LED showed a f-fold improvement in the external efficiency, and a 3-fold improvement in the directionality compared with a conventional planar LED for f/2 optical systems. The incorporation of these uncooled devices in a White cell produced a NO2 gas sensing system with 2 part-per-million sensitivity, with an LED drive current of <5mA. These results represent a significant advance in the use of solid state devices for portable gas sensing systems.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Field Testing and Development of Novel SHM systems at Queen’s University Belfast

Ageing and deterioration of infrastructure is a challenge facing transport authorities. In
particular, there is a need for increased bridge monitoring in order to provide adequate
maintenance and to guarantee acceptable levels of transport safety. The Intelligent
Infrastructure group at Queens University Belfast (QUB) are working on a number of aspects
of infrastructure monitoring and this paper presents summarised results from three distinct
monitoring projects carried out by this group. Firstly the findings from a project on next
generation Bridge Weight in Motion (B-WIM) are reported, this includes full scale field testing
using fibre optic strain sensors. Secondly, results from early phase testing of a computer
vision system for bridge deflection monitoring are reported on. This research seeks to exploit
recent advances in image processing technology with a view to developing contactless
bridge monitoring approaches. Considering the logistical difficulty of installing sensors on a
‘live’ bridge, contactless monitoring has some inherent advantages over conventional
contact based sensing systems. Finally the last section of the paper presents some recent
findings on drive by bridge monitoring. In practice a drive-by monitoring system will likely
require GPS to allow the response of a given bridge to be identified; this study looks at the
feasibility of using low-cost GPS sensors for this purpose, via field trials. The three topics
outlined above cover a spectrum of SHM approaches namely, wired monitoring, contactless
monitoring and drive by monitoring

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Designing for User-facing Uncertainty in Everyday Sensing and Prediction

Thesis (Ph.D.)--University of Washington, 2016-07

Optics-Based Quantum Information and Sensing Platforms Utilizing the Nitrogen-Vacancy Center in Diamond

Thesis (Ph.D.)--University of Washington, 2016-08