Development of a multivariable online monitoring system for the thermoforming process

The thermoforming industry has been relatively slow to embrace modern measurement technologies. As a result researchers have struggled to develop accurate thermoforming simulations as some of the key aspects of the process remain poorly understood. For the first time, this work reports the development of a prototype multivariable instrumentation system for use in thermoforming. The system contains sensors for plug force, plug displacement, air pressure and temperature, plug temperature, and sheet temperature. Initially, it was developed to fit the tooling on a laboratory thermoforming machine, but later its performance was validated by installing it on a similar industrial tool. Throughout its development, providing access for the various sensors and their cabling was the most challenging task. In testing, all of the sensors performed well and the data collected has given a powerful insight into the operation of the process. In particular, it has shown that both the air and plug temperatures stabilize at more than 80C during the continuous thermoforming of amorphous polyethylene terephthalate (aPET) sheet at 110C. The work also highlighted significant differences in the timing and magnitude of the cavity pressures reached in the two thermoforming machines. The prototype system has considerable potential for further development. 

Implementation of a drive-by monitoring system for transport infrastructure utilising GNSS

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, prioritise allocation of funds and guarantee acceptable levels of transport safety. Existing bridge structural health monitoring (SHM) techniques typically involve direct instrumentation of the bridge with sensors and equipment for the measurement of properties such as frequencies of vibration. These techniques are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive due to the requirement for on-site installations. In recent years, alternative low-cost indirect vibrationbased SHM approaches have been proposed which utilise the dynamic response of a vehicle to carry out “drive-by” pavement and/or bridge monitoring. The vehicle is fitted with sensors on its axles thus reducing the need for on-site installations. This paper investigates the use of low-cost sensors incorporating global navigation satellite systems (GNSS) for implementation of the drive-by system in practice, via field trials with an instrumented vehicle. The potential of smartphone technology to be harnessed for drive by monitoring is established, while smartphone GNSS tracking applications are found to compare favourably in terms of accuracy, cost and ease of use to professional GNSS devices.

NI health and social care inequalities monitoring system (HSCIMS) - health inequalities in Northern Ireland: key facts 2015

This key facts publication provides an interim update to the NI health & social care inequalities monitoring system (HSCIMS) regional reports which are published every other year. It presents a summary of the latest position and inequality gaps between the most deprived areas and both the least deprived areas and the NI average in addition to a regional comparison with rural areas for a range of health outcomes included within the HSCIMS series, in addition to the health survey Northern Ireland (HSNI).

State of Iowa Outcomes Monitoring System Year 16 Annual Evaluation Report, September 2014

The Outcomes Monitoring System (OMS) was established to systematically gather data on substance abuse treatment outcomes in Iowa. Randomly selected clients from 22 Iowa Department of Public Health-funded treatment agencies were contacted for follow-up interviews that occurred approximately six months after discharge from treatment. This report examines outcomes for clients admitted in calendar year 2013. Outcomes are presented for 334 of the clients who completed the follow-up interview.

Flexible Sensor for Wearable Vital Sign Monitoring System

In modern society, the body health is a very important issue to everyone. With the development of the science and technology, the new and developed body health monitoring device and technology will play the key role in the daily medical activities. This paper focus on making progress in the design of the wearable vital sign system. A vital sign monitoring system has been proposed and designed. The whole detection system is composed of signal collecting subsystem, signal processing subsystem, short-range wireless communication subsystem and user interface subsystem. The signal collecting subsystem is composed of light source and photo diode, after emiting light of two different wavelength, the photo diode collects the light signal reflected by human body tissue. The signal processing subsystem is based on the analog front end AFE4490 and peripheral circuits, the collected analog signal would be filtered and converted into digital signal in this stage. After a series of processing, the signal would be transmitted to the short-range wireless communication subsystem through SPI, this subsystem is mainly based on Bluetooth 4.0 protocol and ultra-low power System on Chip(SoC) nRF51822. Finally, the signal would be transmitted to the user end. After proposing and building the system, this paper focus on the research of the key component in the system, that is, the photo detector. Based on the study of the perovskite materials, a low temperature processed photo detector has been proposed, designed and researched. The device is made up of light absorbing layer, electron transporting and hole blocking layer, hole transporting and electron blocking layer, conductive substrate layer and metal electrode layer. The light absorbing layer is the important part of whole device, and it is fabricated by perovskite materials. After accepting the light, the electron-hole pair would be produced in this layer, and due to the energy level difference, the electron and hole produced would be transmitted to metal electrode and conductive substrate electrode through electron transporting layer and hole transporting layer respectively. In this way the response current would be produced. Based on this structure, the specific fabrication procedure including substrate cleaning; PEDOT:PSS layer preparation; pervoskite layer preparation; PCBM layer preparation; C60, BCP, and Ag electrode layer preparation. After the device fabrication, a series of morphological characterization and performance testing has been done. The testing procedure including film-forming quality inspection, response current and light wavelength analysis, linearity and response time and other optical and electrical properties testing. The testing result shows that the membrane has been fabricated uniformly; the device can produce obvious response current to the incident light with the wavelength from 350nm to 800nm, and the response current could be changed along with the light wavelength. When the light wavelength keeps constant, there exists a good linear relationship between the intensity of the response current and the power of the incident light, based on which the device could be used as the photo detector to collect the light information. During the changing period of the light signal, the response time of the device is several microseconds, which is acceptable working as a photo detector in our system. The testing results show that the device has good electronic and optical properties, and the fabrication procedure is also repeatable, the properties of the devices has good uniformity, which illustrates the fabrication method and procedure could be used to build the photo detector in our wearable system. Based on a series of testing results, the paper has drawn the conclusion that the photo detector fabricated could be integrated on the flexible substrate and is also suitable for the monitoring system proposed, thus made some progress on the research of the wearable monitoring system and device. Finally, some future prospect in system design aspect and device design and fabrication aspect are proposed.

Monitoring system for small sized photovoltaic power plants

This paper presents a monitoring system devoted to small sized photovoltaic (PV) power plants. The system is characterized by: a high level of integration; a low cost, when compared to the cost of the PV system to be monitored; and an easy installation in the majority of the PV plants with installed power of some kW. The system is able to collect, store, process and display electrical and meteorological parameters that are crucial when monitoring PV facilities. The identification of failures in the PV system and the elaboration of performance analysis of such facilities are other important characteristics of the developed system. The access to the information about the monitored facilities is achieved by using a web application, which was developed with a focus on the mobile devices. In addition, there is the possibility of an integration between the developed monitoring system and the central supervision system of Martifer Solar (a company focused on the development, operation and maintenance of PV systems).

Machine Learning Unsupervised Methods in the Design of an On-board Health Monitoring System for Satellite Applications

The dissertation starts by providing a description of the phenomena related to the increasing importance recently acquired by satellite applications. The spread of such technology comes with implications, such as an increase in maintenance cost, from which derives the interest in developing advanced techniques that favor an augmented autonomy of spacecrafts in health monitoring. Machine learning techniques are widely employed to lay a foundation for effective systems specialized in fault detection by examining telemetry data. Telemetry consists of a considerable amount of information; therefore, the adopted algorithms must be able to handle multivariate data while facing the limitations imposed by on-board hardware features. In the framework of outlier detection, the dissertation addresses the topic of unsupervised machine learning methods. In the unsupervised scenario, lack of prior knowledge of the data behavior is assumed. In the specific, two models are brought to attention, namely Local Outlier Factor and One-Class Support Vector Machines. Their performances are compared in terms of both the achieved prediction accuracy and the equivalent computational cost. Both models are trained and tested upon the same sets of time series data in a variety of settings, finalized at gaining insights on the effect of the increase in dimensionality. The obtained results allow to claim that both models, combined with a proper tuning of their characteristic parameters, successfully comply with the role of outlier detectors in multivariate time series data. Nevertheless, under this specific context, Local Outlier Factor results to be outperforming One-Class SVM, in that it proves to be more stable over a wider range of input parameter values. This property is especially valuable in unsupervised learning since it suggests that the model is keen to adapting to unforeseen patterns.

Design and implementation of a vibrational condition monitoring system

Industrial companies, particularly those with induction motors and gearboxes as integral components of their systems, are utilizing Condition Monitoring (CM) systems more frequently in order to discover the need for maintenance in advance, as traditional maintenance only performs tasks when a failure has been identified. Utilizing a CM system is essential to boost productivity and minimize long-term failures that result in financial loss. The more exact and practical the CM system, the better the data analysis, which adds to a more precise maintenance forecast. This thesis project is a cooperation with PEI Vibration Monitoring s.r.l. to design and construct a low-cost vibrational condition monitoring system to check the health of induction motors and gearboxes automatically. Moreover, according to the company's request, such a system should have specs comparable to NI 9234, one of the company's standard Data Acquisition (DAQ) boards, but at a significantly cheaper price. Additionally, PEI VM Company has supplied all hardware and electronic components. The suggested CM system is capable of highprecision autonomous monitoring of induction motors and gearboxes, and it consists of a Raspberry Pi 3B and MCC 172 DAQ board.

Habitudes de vie et contrôle glycémique chez des adultes atteints de diabète de type 1 : des barrières envers l’activité physique au calcul des glucides.

Le diabète de type 1 (DT1) est une maladie complexe qui requiert une implication importante des patients pour contrôler leur glycémie et ainsi prévenir les complications et comorbidités. L’activité physique (AP) régulière et une attention constante pour les glucides ingérés sont des adjuvants essentiels au traitement insulinique. Nous avons démontré que le questionnaire BAPAD-1, spécifiquement développé pour des adultes atteints de DT1, est un outil valide (validité prédictive, fiabilité interne et reproductibilité) pour définir des barrières associées à l’AP. Bien que le niveau de barrières envers l’AP soit faible, la crainte de l’hypoglycémie est la barrière la plus importante chez cette population. L’adoption d’un mode de vie actif est associée à un profil corporel favorable. Les adultes, avec un DT1 et non diabétique, qui maintiennent un bon niveau d’AP, soit un ratio entre la dépense énergétique totale et celle au repos ≥ 1.7, ont une masse grasse, un indice de masse corporelle et un tour de taille significativement inférieurs à ceux d’adultes moins actifs. Le niveau d’AP peut être estimé au moyen d’un moniteur d’AP comme le SenseWear Armband™. Afin de compléter les études de validation de cet outil, nous avons évalué et démontré la reproductibilité des mesures. Toutefois, la dépense énergétique est sous-estimée durant les 10 premières minutes d’une AP d’intensité modérée sur ergocycle. L’utilisation de cet appareil est donc justifiée pour une évaluation de la dépense énergétique sur de longues périodes. Le calcul des glucides est une méthode largement utilisée pour évaluer la quantité d’insuline à injecter lors des repas. Nous avons évalué dans un contexte de vie courante, sans révision de la technique, la précision des patients pour ce calcul. L’erreur moyenne est de 15,4 ± 7,8 g par repas, soit 20,9 ± 9,7 % du contenu glucidique. L’erreur moyenne est positivement associée à de plus grandes fluctuations glycémiques mesurées via un lecteur de glucose en continu. Une révision régulière du calcul des glucides est probablement nécessaire pour permettre un meilleur contrôle glycémique. Nous avons développé et testé lors d’un essai clinique randomisé contrôlé un programme de promotion de l’AP (PEP-1). Ce programme de 12 semaines inclut une séance hebdomadaire en groupe ayant pour but d’initier l’AP, d’établir des objectifs et d’outiller les adultes atteints de DT1 quant à la gestion de la glycémie à l’AP. Bien que n’ayant pas permis d’augmenter la dépense énergétique, le programme a permis un maintien du niveau d’AP et une amélioration de la condition cardio-respiratoire et de la pression artérielle. À la fin du programme, une plus grande proportion de patients connaissait la pharmacocinétique de l’insuline et une plus grande variété de méthodes pour contrer l’hypoglycémie associée à l’AP était utilisée. En conclusion, le diabète de type 1 engendre des défis quotidiens particuliers. D’une part, le calcul des glucides est une tâche complexe et son imprécision est associée aux fluctuations glycémiques quotidiennes. D’autre part, l’adoption d’un mode de vie actif, qui est associée à un meilleur profil de composition corporelle, est limitée par la crainte des hypoglycémies. Le programme PEP-1 offre un support pour intégrer l’AP dans les habitudes de vie des adultes avec un DT1 et ainsi améliorer certains facteurs de risque cardio-vasculaire.

Hypoglycémie nocturne et habitudes alimentaires en soirée chez l'adulte atteint de diabète de type 1

L’hypoglycémie est une barrière au traitement du diabète de type 1 (DbT1). La collation au coucher est recommandée pour prévenir l’hypoglycémie nocturne (HN), mais son efficacité n’est pas démontrée. Objectif : Déterminer si une prise alimentaire en soirée est associée à la survenue d’HN. Étude observationnelle : 100 DbT1 ont porté un lecteur de glucose en continu et complété un journal alimentaire pendant 72 heures. L’HN est survenue durant 28 % des nuits. Une prise alimentaire en soirée n’était pas associée à l’HN. Toutefois, dans un modèle ajusté, l’apport en glucides en soirée était positivement associé aux HN (avec injection d’insuline rapide) et l’apport en protéines inversement associé aux HN (sans injection d’insuline rapide). Manger en soirée ne semble pas associé à moins d’HN. Des études contrôlées sont nécessaires pour comprendre l’effet de la collation au coucher sur le contrôle glycémique et le rôle de l’insuline rapide injectée en soirée.

Propuesta de algoritmos de predicción de glucosa en pacientes diabéticos

La diabetes mellitus es el conjunto de alteraciones provocadas por un defecto en la cantidad de insulina secretada o por un aprovechamiento deficiente de la misma. Es causa directa de complicaciones a corto, medio y largo plazo que disminuyen la calidad y las expectativas de vida de las personas con diabetes. La diabetes mellitus es en la actualidad uno de los problemas más importantes de salud. Ha triplicado su prevalencia en los últimos 20 anos y para el año 2025 se espera que existan casi 300 millones de personas con diabetes. Este aumento de la prevalencia junto con la morbi-mortalidad asociada a sus complicaciones micro y macro-vasculares convierten la diabetes en una carga para los sistemas sanitarios, sus recursos económicos y sus profesionales, haciendo de la enfermedad un problema individual y de salud pública de enormes proporciones. De momento no existe cura a esta enfermedad, de modo que el objetivo terapéutico del tratamiento de la diabetes se centra en la normalización de la glucemia intentando minimizar los eventos de hiper e hipoglucemia y evitando la aparición o al menos retrasando la evolución de las complicaciones vasculares, que constituyen la principal causa de morbi-mortalidad de las personas con diabetes. Un adecuado control diabetológico implica un tratamiento individualizado que considere multitud de factores para cada paciente (edad, actividad física, hábitos alimentarios, presencia de complicaciones asociadas o no a la diabetes, factores culturales, etc.). Sin embargo, a corto plazo, las dos variables más influyentes que el paciente ha de manejar para intervenir sobre su nivel glucémico son la insulina administrada y la dieta. Ambas presentan un retardo entre el momento de su aplicación y el comienzo de su acción, asociado a la absorción de los mismos. Por este motivo la capacidad de predecir la evolución del perfil glucémico en un futuro cercano, ayudara al paciente a tomar las decisiones adecuadas para mantener un buen control de su enfermedad y evitar situaciones de riesgo. Este es el objetivo de la predicción en diabetes: adelantar la evolución del perfil glucémico en un futuro cercano para ayudar al paciente a adaptar su estilo de vida y sus acciones correctoras, con el propósito de que sus niveles de glucemia se aproximen a los de una persona sana, evitando así los síntomas y complicaciones de un mal control. La aparición reciente de los sistemas de monitorización continua de glucosa ha proporcionado nuevas alternativas. La disponibilidad de un registro exhaustivo de las variaciones del perfil glucémico, con un periodo de muestreo de entre uno y cinco minutos, ha favorecido el planteamiento de nuevos modelos que tratan de predecir la glucemia utilizando tan solo las medidas anteriores de glucemia o al menos reduciendo significativamente la información de entrada a los algoritmos. El hecho de requerir menor intervención por parte del paciente, abre nuevas posibilidades de aplicación de los predictores de glucemia, haciéndose viable su uso en tiempo real, como sistemas de ayuda a la decisión, como detectores de situaciones de riesgo o integrados en algoritmos automáticos de control. En esta tesis doctoral se proponen diferentes algoritmos de predicción de glucemia para pacientes con diabetes, basados en la información registrada por un sistema de monitorización continua de glucosa así como incorporando la información de la insulina administrada y la ingesta de carbohidratos. Los algoritmos propuestos han sido evaluados en simulación y utilizando datos de pacientes registrados en diferentes estudios clínicos. Para ello se ha desarrollado una amplia metodología, que trata de caracterizar las prestaciones de los modelos de predicción desde todos los puntos de vista: precisión, retardo, ruido y capacidad de detección de situaciones de riesgo. Se han desarrollado las herramientas de simulación necesarias y se han analizado y preparado las bases de datos de pacientes. También se ha probado uno de los algoritmos propuestos para comprobar la validez de la predicción en tiempo real en un escenario clínico. Se han desarrollado las herramientas que han permitido llevar a cabo el protocolo experimental definido, en el que el paciente consulta la predicción bajo demanda y tiene el control sobre las variables metabólicas. Este experimento ha permitido valorar el impacto sobre el control glucémico del uso de la predicción de glucosa. ABSTRACT Diabetes mellitus is the set of alterations caused by a defect in the amount of secreted insulin or a suboptimal use of insulin. It causes complications in the short, medium and long term that affect the quality of life and reduce the life expectancy of people with diabetes. Diabetes mellitus is currently one of the most important health problems. Prevalence has tripled in the past 20 years and estimations point out that it will affect almost 300 million people by 2025. Due to this increased prevalence, as well as to morbidity and mortality associated with micro- and macrovascular complications, diabetes has become a burden on health systems, their financial resources and their professionals, thus making the disease a major individual and a public health problem. There is currently no cure for this disease, so that the therapeutic goal of diabetes treatment focuses on normalizing blood glucose events. The aim is to minimize hyper- and hypoglycemia and to avoid, or at least to delay, the appearance and development of vascular complications, which are the main cause of morbidity and mortality among people with diabetes. A suitable, individualized and controlled treatment for diabetes involves many factors that need to be considered for each patient: age, physical activity, eating habits, presence of complications related or unrelated to diabetes, cultural factors, etc. However, in the short term, the two most influential variables that the patient has available in order to manage his/her glycemic levels are administered insulin doses and diet. Both suffer from a delay between their time of application and the onset of the action associated with their absorption. Therefore, the ability to predict the evolution of the glycemic profile in the near future could help the patient to make appropriate decisions on how to maintain good control of his/her disease and to avoid risky situations. Hence, the main goal of glucose prediction in diabetes consists of advancing the evolution of glycemic profiles in the near future. This would assist the patient in adapting his/her lifestyle and in taking corrective actions in a way that blood glucose levels approach those of a healthy person, consequently avoiding the symptoms and complications of a poor glucose control. The recent emergence of continuous glucose monitoring systems has provided new alternatives in this field. The availability of continuous records of changes in glycemic profiles (with a sampling period of one or five minutes) has enabled the design of new models which seek to predict blood glucose by using automatically read glucose measurements only (or at least, reducing significantly the data input manually to the algorithms). By requiring less intervention by the patient, new possibilities are open for the application of glucose predictors, making its use feasible in real-time applications, such as: decision support systems, hypo- and hyperglycemia detectors, integration into automated control algorithms, etc. In this thesis, different glucose prediction algorithms are proposed for patients with diabetes. These are based on information recorded by a continuous glucose monitoring system and incorporate information of the administered insulin and carbohydrate intakes. The proposed algorithms have been evaluated in-silico and using patients’ data recorded in different clinical trials. A complete methodology has been developed to characterize the performance of predictive models from all points of view: accuracy, delay, noise and ability to detect hypo- and hyperglycemia. In addition, simulation tools and patient databases have been deployed. One of the proposed algorithms has additionally been evaluated in terms of real-time prediction performance in a clinical scenario in which the patient checked his/her glucose predictions on demand and he/she had control on his/her metabolic variables. This has allowed assessing the impact of using glucose prediction on glycemic control. The tools to carry out the defined experimental protocols were also developed in this thesis.

Tiempo promedio del efecto máximo de la insulina análoga en la glucemia postprandial y factores relacionados

Introducción: El tiempo promedio del efecto máximo de la insulina regular rápida en la glucemia postprandial ha sido considerado durante años de 120 minutos. En pacientes con Diabetes Mellitus (DM) que usan insulinas análogas este tiempo y los factores asociados no se encuentran reportados para ser aplicados en el automonitoreo. El objetivo de este estudio fue calcular el tiempo y factores relacionados al efecto máximo de la insulina en la glucemia postprandial. Metodología: Se desarrolló un estudio longitudinal retrospectivo a partir de una fuente secundaria donde se realizó un análisis descriptivo y bivariado con las variables demográficas y clínicas presentes en la población. Resultados: El tiempo promedio del pico máximo de insulina en pacientes con DM1 fue de 78.4 (DE± 16.512) y DM2 75.01(DE± 12.02) minutos. El 75% de la población con DM1 y el 54.2% en DM2 era de sexo femenino, la edad promedio en DM1 era 42.38 años y en DM2 68 años, en cuanto a la categorización del IMC el 50% de la población en DM1 y el 37.5% en DM2 estaban dentro del rango de obesidad y se encontró una relación con respecto al tipo de comida “desayuno-cena” vs el tiempo promedio del efecto máximo de la insulina calculado para ambos grupos (p:0.010). Conclusiones: El tiempo promedio del efecto máximo de la insulina calculado fue menor al tiempo reportado en la literatura clínica de 120 minutos. El tipo de comida principal mostró una relación con el tiempo promedio del efecto máximo en ambos grupos.

Diabete mellito nel cane: terapia, monitoraggio e aspetti prognostici

Il diabete mellito (DM) è una delle malattie endocrine più comuni nel cane. Una volta raggiunta la diagnosi di DM, è necessario iniziare un trattamento insulinico nonché una dieta specifica, al fine di controllare i livelli di glucosio nel sangue e di conseguenza i segni clinici. Inoltre, al fine di ottenere un buon controllo glicemico, è essenziale garantire uno stretto monitoraggio terapeutico. Nella presente tesi sono riportati numerosi studi relativi a trattamento, monitoraggio e prognosi dei cani con DM. Il capitolo 2 è una review che illustra i principali aspetti terapeutici e di monitoraggio del DM. Il capitolo 3 riporta uno studio che confronta l'efficacia e la sicurezza dell'insulina Lenta e dell'insulina Neutra Protamine Hagedorn (NPH). I metodi di monitoraggio per cani con DM possono essere classificati in diretti od indiretti. I metodi di monitoraggio diretto includono misurazioni serali della glicemia o monitoraggio continuo del glucosio interstiziale tramite appositi dispositivi (Continuous Glucose Monitoring System, CGMS). Le modalità indirette comprendono la valutazione dell'assunzione di acqua e del peso corporeo, la quantificazione del glucosio/chetoni nelle urine e la misurazione delle concentrazioni di proteine glicate. Il capitolo 4 mostra uno studio volto a valutare l'accuratezza e la precisione di un glucometro e un glucometro/chetometro nel cane. Il Flash Glucose Monitoring system è un CGMS recentemente validato per l'uso nel cane; la sua utilità clinica nel monitoraggio del DM canino è esaminata nel capitolo 5. Il capitolo 6 descrive uno studio in cui si validano 2 metodi analitici per la misurazione delle fruttosamine sieriche e dell'emoglobina glicata nel cane e confronta l’utilità delle due proteine glicate nel definire il controllo glicemico. Infine, il capitolo 7 riporta uno studio finalizzato a determinare il tempo di sopravvivenza e ad identificare il valore prognostico di diverse variabili cliniche e clinico-patologiche nei cani con DM.

Surface acoustic wave streaming in a PDMS microfluidic system: effect of frequency and fluid geometry & A remote ultrasonic glucose sensor

This thesis describes two separate projects. The first is a theoretical and experimental investigation of surface acoustic wave streaming in microfluidics. The second is the development of a novel acoustic glucose sensor. A separate abstract is given for each here. Optimization of acoustic streaming in microfluidic channels by SAWs Surface Acoustic Waves, (SAWs) actuated on flat piezoelectric substrates constitute a convenient and versatile tool for microfluidic manipulation due to the easy and versatile interfacing with microfluidic droplets and channels. The acoustic streaming effect can be exploited to drive fast streaming and pumping of fluids in microchannels and droplets (Shilton et al. 2014; Schmid et al. 2011), as well as size dependant sorting of particles in centrifugal flows and vortices (Franke et al. 2009; Rogers et al. 2010). Although the theory describing acoustic streaming by SAWs is well understood, very little attention has been paid to the optimisation of SAW streaming by the correct selection of frequency. In this thesis a finite element simulation of the fluid streaming in a microfluidic chamber due to a SAW beam was constructed and verified against micro-PIV measurements of the fluid flow in a fabricated device. It was found that there is an optimum frequency that generates the fastest streaming dependent on the height and width of the chamber. It is hoped this will serve as a design tool for those who want to optimally match SAW frequency with a particular microfluidic design. An acoustic glucose sensor Diabetes mellitus is a disease characterised by an inability to properly regulate blood glucose levels. In order to keep glucose levels under control some diabetics require regular injections of insulin. Continuous monitoring of glucose has been demonstrated to improve the management of diabetes (Zick et al. 2007; Heinemann & DeVries 2014), however there is a low patient uptake of continuous glucose monitoring systems due to the invasive nature of the current technology (Ramchandani et al. 2011). In this thesis a novel way of monitoring glucose levels is proposed which would use ultrasonic waves to ‘read’ a subcutaneous glucose sensitive-implant, which is only minimally invasive. The implant is an acoustic analogy of a Bragg stack with a ‘defect’ layer that acts as the sensing layer. A numerical study was performed on how the physical changes in the sensing layer can be deduced by monitoring the reflection amplitude spectrum of ultrasonic waves reflected from the implant. Coupled modes between the skin and the sensing layer were found to be a potential source of error and drift in the measurement. It was found that by increasing the number of layers in the stack that this could be minimized. A laboratory proof of concept system was developed using a glucose sensitive hydrogel as the sensing layer. It was possible to monitor the changing thickness and speed of sound of the hydrogel due to physiological relevant changes in glucose concentration.

Development of a DNA-dosimeter system for monitoring the effects of solar-ultraviolet radiation

Solar radiation sustains and affects all life forms on Earth. In recent years, the increase in environmental levels of solar-UV radiation due to depletion of the stratospheric ozone layer, as a result of anthropogenic emission of destructive chemicals, has highlighted serious issues of social concern. This becomes still more dramatic in tropical and subtropical regions, where the intensity of solar radiation is higher. To better understand the impact of the harmful effects of solar-UV radiation on the DNA molecule, we developed a reliable biological monitoring system based on the exposure of plasmid DNA to artificial UV lamps and sunlight. The determination and quanti. cation of different types of UV photoproducts were performed through the use of specific DNA repair enzymes and antibodies. As expected, a significant number of CPDs and 6-4PPs was observed when the DNA-dosimeter system was exposed to increasing doses of UVB radiation. Moreover, CPDs could also be clearly detected in plasmid DNA when this system was exposed to either UVA or directly to sunlight. Interestingly, although less abundant, 6-4PPs and oxidative DNA damage were also generated after exposure to both UVA and sunlight. These results confirm the genotoxic potential of sunlight, reveal that UVA may also produce CPDs and 6-4PPs directly in naked DNA and demonstrate the applicability of a DNA-dosimeter system for monitoring the biological effects of solar-UV radiation.