Characterisation of flexural bond strength in thin bed concrete masonry

This paper presents an experimental investigation of the flexural bond strength of thin bed concrete masonry. Flexural bond strength of masonry depends upon the mortar type, the techniques of dispersion of mortar and the surface texture (roughness) of concrete blocks. There exists an abundance of literature on the conventional masonry bond containing 10mm thick mortar; however, the 2mm polymer flue mortar bond is not yet well researched. This paper reports a study on the examination of the effect of mortar compositions, dispersion methods and unit surface textures to the flexural bond strength of thin bed concrete masonry. Three types of polymer modified glue mortars, three surface textures and four techniques of mortar dispersion have been used in preparing 108 four point flexural test specimens. All mortar joints have been carefully prepared to ensure achievement of 2mm layer polymer mortar thickness on average. The results exhibit the flexural bond strength of thin bed concrete masonry much is higher than that of the conventional masonry; moreover the unit surface texture and the mortar dispersion methods are found to have significant influence on the flexural bond strength.

Using process models to support design of airport terminals

The complex design process of airport terminal needs to support a wide range of changes in operational facilities for both usual and unusual/emergency events. Process model describes how activities within a process are connected and also states logical information flow of the various activities. The traditional design process overlooks the necessity of information flow from the process model to the actual building design, which needs to be considered as a integral part of building design. The current research introduced a generic method to obtain design related information from process model to incorporate with the design process. Appropriate integration of the process model prior to the design process uncovers the relationship exist between spaces and their relevant functions, which could be missed in the traditional design approach. The current paper examines the available Business Process Model (BPM) and generates modified Business Process Model(mBPM) of check-in facilities of Brisbane International airport. The information adopted from mBPM then transform into possible physical layout utilizing graph theory.

The development of ground impact models for the analysis of the risks associated with Unmanned Aircraft Operations over inhabited areas

With the emergence of Unmanned Aircraft Systems (UAS) there is a growing need for safety standards and regulatory frameworks to manage the risks associated with their operations. The primary driver for airworthiness regulations (i.e., those governing the design, manufacture, maintenance and operation of UAS) are the risks presented to people in the regions overflown by the aircraft. Models characterising the nature of these risks are needed to inform the development of airworthiness regulations. The output from these models should include measures of the collective, individual and societal risk. A brief review of these measures is provided. Based on the review, it was determined that the model of the operation of an UAS over inhabited areas must be capable of describing the distribution of possible impact locations, given a failure at a particular point in the flight plan. Existing models either do not take the impact distribution into consideration, or propose complex and computationally expensive methods for its calculation. A computationally efficient approach for estimating the boundary (and in turn area) of the impact distribution for fixed wing unmanned aircraft is proposed. A series of geometric templates that approximate the impact distributions are derived using an empirical analysis of the results obtained from a 6-Degree of Freedom (6DoF) simulation. The impact distributions can be aggregated to provide impact footprint distributions for a range of generic phases of flight and missions. The maximum impact footprint areas obtained from the geometric template are shown to have a relative error of typically less than 1% compared to the areas calculated using the computationally more expensive 6DoF simulation. Computation times for the geometric models are on the order of one second or less, using a standard desktop computer. Future work includes characterising the distribution of impact locations within the footprint boundaries.

An authorization framework using building information models

A building information model (BIM) is an electronic repository of structured, three-dimensional data that captures both the physical and dynamic functional characteristics of a facility. In addition to its more traditional function as a tool to aid design and construction, a BIM can be used throughout the life cycle of a facility, functioning as a living database that places resources contained within the building in their spatial and temporal context. Through its comprehension of spatial relationships, a BIM can meaningfully represent and integrate previously isolated control and management systems and processes, and thereby provide a more intuitive interface to users. By placing processes in a spatial context, decision-making can be improved, with positive flow-on effects for security and efficiency. In this article, we systematically analyse the authorization requirements involved in the use of BIMs. We introduce the concept of using a BIM as a graphical tool to support spatial access control configuration and management (including physical access control). We also consider authorization requirements for regulating access to the structured data that exists within a BIM as well as to external systems and data repositories that can be accessed via the BIM interface. With a view to addressing these requirements we present a survey of relevant spatiotemporal access control models, focusing on features applicable to BIMs and highlighting capability gaps. Finally, we present a conceptual authorization framework that utilizes BIMs.

Understanding hydrochemical processes using 3D models and hydrochemical facies in Wairau Plain groundwater, Marlborough

Three dimensional models and groundwater quality are combined to better understand and conceptualise groundwater systems in complex geological settings in the Wairau Plain, Marlborough. Hydrochemical facies, which are characteristic of distinct evolutionary pathways and a common hydrologic history of groundwaters, are identified within geological formations to assess natural water-rock interactions, redox potential and human agricultural impact on groundwater quality in the Wairau Plain.

Development of zonal cartilage constructs : effects of chondrocyte subpopulation, compressive stimulation, and culture models

Articular cartilage is a highly resilient tissue located at the ends of long bones. It has a zonal structure, which has functional significance in load-bearing. Cartilage does not spontaneously heal itself when damaged, and untreated cartilage lesions or age-related wear often lead to osteoarthritis (OA). OA is a degenerative condition that is highly prevalent, age-associated, and significantly affects patient mobility and quality of life. There is no cure for OA, and patients usually resort to replacing the biological joint with an artificial prosthesis. An alternative approach is to dynamically regenerate damaged or diseased cartilage through cartilage tissue engineering, where cells, materials, and stimuli are combined to form new cartilage. However, despite extensive research, major limitations remain that have prevented the wide-spread application of tissue-engineered cartilage. Critically, there is a dearth of information on whether autologous chondrocytes obtained from OA patients can be used to successfully generate cartilage tissues with structural hierarchy typically found in normal articular cartilage. I aim to address these limitations in this thesis by showing that chondrocyte subpopulations isolated from macroscopically normal areas of the cartilage can be used to engineer stratified cartilage tissues and that compressive loading plays an important role in zone-dependent biosynthesis of these chondrocytes. I first demonstrate that chondrocyte subpopulations from the superficial (S) and middle/deep (MD) zones of OA cartilage are responsive to compressive stimulation in vitro, and that the effect of compression on construct quality is zone-dependent. I also show that compressive stimulation can influence pericelluar matrix production, matrix metalloproteinase secretion, and cytokine expression in zonal chondrocytes in an alginate hydrogel model. Subsequently, I focus on recreating the zonal structure by forming layered constructs using the alginate-released chondrocyte (ARC) method either with or without polymeric scaffolds. Resulting zonal ARC constructs had hyaline morphology, and expressed cartilage matrix molecules such as proteoglycans and collagen type II in both scaffold-free and scaffold-based approaches. Overall, my findings demonstrate that chondrocyte subpopulations obtained from OA joints respond sensitively to compressive stimulation, and are able to form cartilaginous constructs with stratified organization similar to native cartilage using the scaffold-free and scaffold-based ARC technique. The ultimate goal in tissue engineering is to help provide improved treatment options for patients suffering from debilitating conditions such as OA. Further investigations in developing functional cartilage replacement tissues using autologous chondrocytes will bring us a step closer to improving the quality of life for millions of OA patients worldwide.

Application of a human bone engineering platform to an in vitro and in vivo breast cancer metastasis model

Breast cancer in its advanced stage has a high predilection to the skeleton. Currently, treatment options of breast cancer-related bone metastasis are restricted to only palliative therapeutic modalities. This is due to the fact that mechanisms regarding the breast cancer celI-bone colonisation as well as the interactions of breast cancer cells with the bone microenvironment are not fully understood, yet. This might be explained through a lack of appropriate in vitro and in vivo models that are currently addressing the above mentioned issue. Hence the hypothesis that the translation of a bone tissue engineering platform could lead to improved and more physiological in vitro and in vivo model systems in order to investigate breast cancer related bone colonisation was embraced in this PhD thesis. Therefore the first objective was to develop an in vitro model system that mimics human mineralised bone matrix to the highest possible extent to examine the specific biological question, how the human bone matrix influences breast cancer cell behaviour. Thus, primary human osteoblasts were isolated from human bone and cultured under osteogenic conditions. Upon ammonium hydroxide treatment, a cell-free intact mineralised human bone matrix was left behind. Analyses revealed a similar protein and mineral composition of the decellularised osteoblast matrix to human bone. Seeding of a panel of breast cancer cells onto the bone mimicking matrix as well as reference substrates like standard tissue culture plastic and collagen coated tissue culture plastic revealed substrate specific differences of cellular behaviour. Analyses of attachment, alignment, migration, proliferation, invasion, as well as downstream signalling pathways showed that these cellular properties were influenced through the osteoblast matrix. The second objective of this PhD project was the development of a human ectopic bone model in NOD/SCID mice using medical grade polycaprolactone tricalcium phosphate (mPCL-TCP) scaffold. Human osteoblasts and mesenchymal stem cells were seeded onto an mPCL-TCP scaffold, fabricated using a fused deposition modelling technique. After subcutaneous implantation in conjunction with the bone morphogenetic protein 7, limited bone formation was observed due to the mechanical properties of the applied scaffold and restricted integration into the soft tissue of flank of NOD/SCID mice. Thus, a different scaffold fabrication technique was chosen using the same polymer. Electrospun tubular scaffolds were seeded with human osteoblasts, as they showed previously the highest amount of bone formation and implanted into the flanks of NOD/SCID mice. Ectopic bone formation with sufficient vascularisation could be observed. After implantation of breast cancer cells using a polyethylene glycol hydrogel in close proximity to the newly formed bone, macroscopic communication between the newly formed bone and the tumour could be observed. Taken together, this PhD project showed that bone tissue engineering platforms could be used to develop an in vitro and in vivo model system to study cancer cell colonisation in the bone microenvironment.

Fixed bed pyrolysis of date seed waste for liquid oil production

The conversion of biomass waste in the form of date seed into pyrolysis oil by fixed bed pyrolysis reactor has been taken into consideration in this study. A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from these date seeds. The major component of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collector. The date seed in particle form is pyrolysed in an externally heated 7.6 cm diameter and 46 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 4000C to 6000C. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. The parameters are found to influence the product yield significantly. A maximum liquid yield of 50 wt.% is obtained at a reactor bed temperature of 5000 C for a feed size volume of 0.11- 0.20 cm3 with a running time of 120 minutes. The pyrolysis oil obtained at this optimum process conditions are analyzed for some fuel properties and compared with some other biomass derived pyrolysis oils and also with conventional fuels. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 28.636 MJ/kg which is significantly higher than other biomass derived pyrolysis oils.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Design and construction of fixed bed pyrolysis system and plum seed pyrolysis for bio-oil production

This work investigated the production of bio oil from plum seed (Zyziphus jujuba) by fixed bed pyrolysis technology. A fixed bed pyrolysis system has been designed and fabricated for production of bio oil. The major components of the system are: fixed bed reactor, liquid condenser and liquid collector. Nitrogen gas was used to maintain the inert atmosphere in the reactor where the pyrolysis reaction takes place. The feedstock considered in this study is plum seed as it is available waste material in Bangladesh. The reactor is heated by means of a cylindrical biomass external heater. Rice husk was used as the energy source. The products are oil, char and gas. The parameters varied are reactor bed temperature, running time and feed particle size. The parameters are found to influence the product yields significantly. The maximum liquid yield of 39 wt% at 5200C for a feed particle size of 2.36-4.75 mm and a gas flow rate of 8 liter/min with a running time of 120 minute. The pyrolysis oil obtained at these optimum process conditions are analyzed for some of their properties as an alternative fuel. The density of the liquid was closer with diesel. The viscosity of the plum seed liquid was lower than that of the conventional fuels. The calorific value of the pyrolysis oil is one half of the diesel fuel.

Fixed bed pyrolysis of pulm seed waste for liquid oil production

Among various thermo-chemical conversion processes, pyrolysis is considered as an emerging technology for liquid oil production. The conversion of biomass waste in the form of plum seed into pyrolysis oil by fixed bed pyrolysis reactor has been taken into consideration in this study. A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from this plum seeds. The major component of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collectors. The plum seed in particle form is pyrolysed in an externally heated 7.6 cm diameter and 46 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 4000C to 6000C. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. The parameters are found to influence the product yield significantly. A maximum liquid yield of 39 wt% of biomass feed is obtained with particle size of 2.36-4.75 mm at a reactor bed temperature of 520oC with a running time of 120 minutes. The pyrolysis oil obtained at this optimum process conditions are analyzed for some fuel properties and compared with some other biomass derived pyrolysis oils and conventional fuels. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 22.39 MJ/kg which is higher than other biomass derived pyrolysis oils.

Quantum models of cognition and decision

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, "contextuality", is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, "entanglement", allows cognitive phenomena to be modelled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light...

Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.