Ultrasonic wave reflection measurements on self-compacting pastes and concretes

The objective of this study was to extend the use of combined longitudinal (P-wave) and shear (S-wave) ultrasonic wave reflection (UWR) to monitor the setting and stiffening of self-compacting pastes and concretes. An additional objective was to interpret the UWR responses of various modified cement pastes. A polymeric buffer with acoustic impedance close to that of cement paste, high impact polystyrene, was chosen to obtain sensitive results from the early hydration period. Criteria for initial and final set developed by our group in a prior study were used to compute setting times by UWR. UWR results were compared with standard penetration measurements. Stiffening behavior and setting times for normal cement pastes, pastes modified with mineral and chemical admixtures, self-compacting pastes, and concretes were explored using penetration resistance, S-wave and P-wave reflection. All three methods showed that set times of pastes varied linearly with w/c, that superplasticizer and fly ash delayed the set times of pastes, and that differences in w/cm, sp/cm, and fa/cm could be detected. Final set times determined from UWR correlated well with those from penetration resistance. Initial set times from S-wave reflection did not correlate very well with those from penetration resistance. Final set times from P-wave and S-wave reflection were roughly the same. Pastes with different chemical admixtures were tested, and the effects of these admixtures on stiffening were determined using UWR. Self-compacting concretes were studied using UWR, and their response and setting times were largely similar to that of corresponding self-compacting pastes. The P-wave reflection response was explored in detail, and the phenomenon of partial debonding and the factors affecting it were explained. Partial debonding is probably caused by autogenous shrinkage at final set, and was controlled and limited by water. The extent of partial debonding was higher with the transducers placed on the side as opposed to the bottom, and the S-wave transducer seemed to promote debonding in the P-wave reflection, whereas the P-wave transducer seemed to reduce debonding in the S-wave reflection. Simultaneous formwork pressure testing and UWR were performed; however, no clear correlation was seen between the two properties.

Air-coupled ultrasonic tomographic imaging of concrete elements

Ultrasonic tomography is a powerful tool for identifying defects within an object or structure. This method can be applied on structures where x-ray tomography is impractical due to size, low contrast, or safety concerns. By taking many ultrasonic pulse velocity (UPV) readings through the object, an image of the internal velocity variations can be constructed. Air-coupled UPV can allow for more automated and rapid collection of data for tomography of concrete. This research aims to integrate recent developments in air-coupled ultrasonic measurements with advanced tomography technology and apply them to concrete structures. First, non-contact and semi-contact sensor systems are developed for making rapid and accurate UPV measurements through PVC and concrete test samples. A customized tomographic reconstruction program is developed to provide full control over the imaging process including full and reduced spectrum tomographs with percent error and ray density calculations. Finite element models are also used to determine optimal measurement configurations and analysis procedures for efficient data collection and processing. Non-contact UPV is then implemented to image various inclusions within 6 inch (152 mm) PVC and concrete cylinders. Although there is some difficulty in identifying high velocity inclusions, reconstruction error values were in the range of 1.1-1.7% for PVC and 3.6% for concrete. Based upon the success of those tests, further data are collected using non-contact, semi-contact, and full contact measurements to image 12 inch (305 mm) square concrete cross-sections with 1 inch (25 mm) reinforcing bars and 2 inch (51 mm) square embedded damage regions. Due to higher noise levels in collected signals, tomographs of these larger specimens show reconstruction error values in the range of 10-18%. Finally, issues related to the application of these techniques to full-scale concrete structures are discussed.

Enzymatic hydrolysis and fermentation of ultradispersed wood particles after ultrasonic pretreatment

Background: A study of the correlation between the particle size of lignocellulosic substrates and ultrasound pretreatment on the efficiency of further enzymatic hydrolysis and fermentation to ethanol. Results: Themaximumconcentrations of glucose and, to a lesser extent, di- and trisaccharideswere obtained in a series of experiments with 48-h enzymatic hydrolysis of pine rawmaterials ground at 380–400 rpm for 30min. The highest glucose yield was observed at the end of the hydrolysis with a cellulase dosage of 10 mg of protein (204 ± 21 units CMCase per g of sawdust). The greatest enzymatic hydrolysis efficiency was observed in a sample that combined two-stage grinding at 400 rpm with ultrasonic treatment for 5–10 min at a power of 10 W per kg of sawdust. The glucose yield in this case (35.5 g glucose l−1) increased twofold compared to ground substrate without further preparation. Conclusions: Using a mechanical two-stage grinding of lignocellulosic raw materials with ultrasonication increases the efficiency of subsequent enzymatic hydrolysis and fermentation.

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.

Design of functional hybrid coatings with anti-biofouling, self-cleaning and anti-reflecting applications

263 p.

Removable orthodontic appliances: frequency and cleaning agents used by students and recommended by dentists

Aim: To evaluate the prevalence and hygiene habits of 13-19 years-old adolescent users of removable orthodontic appliances (ROA) and to determine hygiene methods for the appliances prescribed by dentists, in the city of Pelotas. Methods: The study had two stages. The first stage was a telephone interview with dentists. Dentists were interview by telephone calls in order to obtain information regarding the hygiene methods for cleaning acrylic appliances. Second stage was a cross-sectional study performed with schoolchildren. Children from public and private schools with secondary level were included in the sample. A questionnaire was applied to the students using any type of ROA. Questionnaires included demographic information and behavioral characteristics. Data collected were subjected to Chi-square test and logistic regression. Results: The prevalence of children using ROA was 5.4%. Students (89.7%) and dentists (47.2%) reported to prefer mechanical methods to clean their ROA. Cleaning with soup, hydrogen peroxide or effervescent tabs were less used. High frequency of use was associated with higher frequency of hygiene on the ROA. Conclusions: The prevalence of schoolchildren using removable appliances was low. The common cleaning method used by children and prescribed by dentists was mechanical. Hygiene frequency was significantly associated with the routine of use of the appliance and with the type of hygiene method.

Ensemble Stream Model for Data-Cleaning in Sensor Networks

Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

Effect of sonic and ultrasonic activation on organic tissue dissolution from simulated grooves in root canals using sodium hypochlorite and EDTA

Aim: To compare soft-tissue dissolution by sodium hypochlorite, with an EDTA intermediate rinse, with or without activation with passive ultrasonic activation (PUI) or sonic activation using the Endoactivator (EA) or Eddy tips (ED). Methodology: The root canals of eighty-three human maxillary central incisors were chemo-mechanically prepared and the teeth split. A standardized longitudinal intracanal groove was created in one of the root halves. Eighty-three porcine palatal mucosa samples were collected, adapted to fit into the grooves and weighed. The re-assembled specimens were randomly divided into four experimental groups (n = 20), based on the final rinse: no activation; EA; PUI; ED, using 2.5% sodium hypochlorite, with an EDTA intermediate rinse. A control group (n = 3) was irrigated with distilled water without activation. The solutions were delivered using a syringe and needle 2 mm from working length. Total irrigation time was 150 s, including 60 s of activation in the specific groups. The study was carried out at 36 ± 2 °C. The porcine palatal mucosa samples were weighed after completion of the assays. Student paired t-test and anova were used to assess the intra- and intergroup weight changes. The multiple comparisons were evaluated using Bonferroni correction (α = 0.05). Results: Weight loss occurred in all experimental groups. Irrigant activation resulted in greater weight loss when compared to the nonactivated group [vs. EA (P = 0.001); vs. PUI (P < 0.001); vs. ED (P < 0.001)]. No significant differences were found amongst the different activation systems. Conclusions: Activation increased the tissue-dissolving activity of irrigants from artificial grooves in root canals of maxillary central incisors. © 2016 International Endodontic Journal. Published by John Wiley & Sons Ltd.

First report of cleaning behaviour in white sea bream (Diplodus sargus)

Several studies have reported the existence of ectoparasites in the stomach contents of Diplodus sargus. The cleaning behaviour has, however, never been previously observed for this species. In this short study, we report the first observations of the cleaning behaviour of D. sargus. These observations were in two yachting marinas, located in the Portuguese western coast between the months of April and August. The cleaning behaviour was only observed towards two Mugilidae species, Chelon labrosus and Mugil cephalus.

Testing the cleaning effectiveness of new ecological aqueousdispersions applied on old icons

Adherent deposits are very aggressive towards ancient heritage paintings since they affect the varnish and the painting’s layers, sometimes reaching the preparative layers. The biggest problem to the restorer is their removal without affecting the patina, the transparent varnish (well preserved) and fine colour glazes made during painting. Therefore, their removal requires preliminary cleaning tests that allow the optimization of the cleaning system composition that is going to be used. The study was focused on organic natural systems, as colourless supernatants, some of them used during ages, but insufficiently studied. The paper presents an evaluation of the effectiveness of cleaning varnished icons of the nineteenth century, with complex conservation cases using supernatants derived from aqueous dispersions extracted from vegetables and dry indigenous herbal infusions. Best results, after six consecutive cleaning steps, on tempera old icon was obtained for a mixture made of mature white onion juice + extract of Soapwort flowers + corn silk tea + acacia tea. As a best result after just one cleaning step was obtained for a quaternary mixture composed from mature white onion juice + mature carrot juice + corn silk tea + aqueous extract of Soapwort flowers.

Development and optimisation of protocols for surface cleaning of cultural heritage metals

The conservation and valorisation of cultural heritage is of fundamental importance for our society, since it is witness to the legacies of human societies. In the case of metallic artefacts, because corrosion is a never-ending problem, the correct strategies for their cleaning and preservation must be chosen. Thus, the aim of this project was the development of protocols for cleaning archaeological copper artefacts by laser and plasma cleaning, since they allow the treatment of artefacts in a controlled and selective manner. Additionally, electrochemical characterisation of the artificial patinas was performed in order to obtain information on the protective properties of the corrosion layers. Reference copper samples with different artificial corrosion layers were used to evaluate the tested parameters. Laser cleaning tests resulted in partial removal of the corrosion products, but the lasermaterial interactions resulted in melting of the desired corrosion layers. The main obstacle for this process is that the materials that must be preserved show lower ablation thresholds than the undesired layers, which makes the proper elimination of dangerous corrosion products very difficult without damaging the artefacts. Different protocols should be developed for different patinas, and real artefacts should be characterised previous to any treatment to determine the best course of action. Low pressure hydrogen plasma cleaning treatments were performed on two kinds of patinas. In both cases the corrosion layers were partially removed. The total removal of the undesired corrosion products can probably be achieved by increasing the treatment time or applied power, or increasing the hydrogen pressure. Since the process is non-invasive and does not modify the bulk material, modifying the cleaning parameters is easy. EIS measurements show that, for the artificial patinas, the impedance increases while the patina is growing on the surface and then drops, probably due to diffusion reactions and a slow dissolution of copper. It appears from these results that the dissolution of copper is heavily influenced by diffusion phenomena and the corrosion product film porosity. Both techniques show good results for cleaning, as long as the proper parameters are used. These depend on the nature of the artefact and the corrosion layers that are found on its surface.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Nurse-determined assessment of cardiac output. Comparing a non-invasive cardiac output device and pulmonary artery catheter: a prospective observational study.

Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.

Procurement Case Study and Decision-making Strategies

Objectives The procurement research of Sydney Opera House FM Exemplar Project aims to develop innovative methods and guidelines for the procurement of FM services, applicable to iconic and / or performing arts centre facilities, or facilities with similar FM functions. The initial procurement report in June 2005 analysed the strategic objectives and operational requirements that provide ‘demand statements’ as evaluation criteria in the service procurement process. The subsequent interim procurement report in September 2005 discussed the elements contributing to the criteria for decision-making in the service procurement process. This procurement report concentrates on the research on procurement strategies and innovative methods using a case study approach. The objectives of this report are: • to investigate service procurement methods and process in iconic and/or performing arts centre facilities; • to showcase FM innovation in Sydney Opera House through a case study; • to establish a preliminary decision-making framework and guidelines for selection of appropriate FM procurement routes to provide a useful model for FM community. Findings Findings from this procurement research are presented as follows. • FM innovation and experience of Sydney Opera House • Innovative procurement methods and processes, drawn from a case study of Sydney Opera House as exemplar • An integrated performance framework to link maintenance service functions to high level organisational objective and strategies • Procurement methods and contract outcomes, focusing on building maintenance and cleaning services of Sydney Opera House • Multi-dimensional assessment of Service Providers • General decision-making strategies and guidelines for selection of appropriate FM procurement routes Further Research Whilst the Sydney Opera House case study emphasises the experience of Sydney Opera House, a study of procurement strategies and methods from published research and FM good practice will supply facilities managers with alternative procurement routes. Further research on the procurement theme will develop a final decision-making model for the procurement of FM services, drawn from the evaluation of the case study outcomes, as well as FM good practice and findings from current published research.