Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

Numerical characterization of the mechanical properties of metal nanowires

Nanowires (NWs) have attracted appealing and broad application owing to their remarkable mechanical, optical, electrical, thermal and other properties. To unlock the revolutionary characteristics of NWs, a considerable body of experimental and theoretical work has been conducted. However, due to the extremely small dimensions of NWs, the application and manipulation of the in situ experiments involve inherent complexities and huge challenges. For the same reason, the presence of defects appears as one of the most dominant factors in determining their properties. Hence, based on the experiments' deficiency and the necessity of investigating different defects' influence, the numerical simulation or modelling becomes increasingly important in the area of characterizing the properties of NWs. It has been noted that, despite the number of numerical studies of NWs, significant work still lies ahead in terms of problem formulation, interpretation of results, identification and delineation of deformation mechanisms, and constitutive characterization of behaviour. Therefore, the primary aim of this study was to characterize both perfect and defected metal NWs. Large-scale molecular dynamics (MD) simulations were utilized to assess the mechanical properties and deformation mechanisms of different NWs under diverse loading conditions including tension, compression, bending, vibration and torsion. The target samples include different FCC metal NWs (e.g., Cu, Ag, Au NWs), which were either in a perfect crystal structure or constructed with different defects (e.g. pre-existing surface/internal defects, grain/twin boundaries). It has been found from the tensile deformation that Young's modulus was insensitive to different styles of pre-existing defects, whereas the yield strength showed considerable reduction. The deformation mechanisms were found to be greatly influenced by the presence of defects, i.e., different defects acted in the role of dislocation sources, and many affluent deformation mechanisms had been triggered. Similar conclusions were also obtained from the compressive deformation, i.e., Young's modulus was insensitive to different defects, but the critical stress showed evident reduction. Results from the bending deformation revealed that the current modified beam models with the considerations of surface effect, or both surface effect and axial extension effect were still experiencing certain inaccuracy, especially for the NW with ultra small cross-sectional size. Additionally, the flexural rigidity of the NW was found to be insensitive to different pre-existing defects, while the yield strength showed an evident decrease. For the resonance study, the first-order natural frequency of the NW with pre-existing surface defects was almost the same as that from the perfect NW, whereas a lower first-order natural frequency and a significantly degraded quality factor was observed for NWs with grain boundaries. Most importantly, the <110> FCC NWs were found to exhibit a novel beat phenomenon driven by a single actuation, which was resulted from the asymmetry in the lattice spacing in the (110) plane of the NW cross-section, and expected to exert crucial impacts on the in situ nanomechanical measurements. In particular, <110> Ag NWs with rhombic, truncated rhombic, and triangular cross-sections were found to naturally possess two first-mode natural frequencies, which were envisioned with applications in NEMS that could operate in a non-planar regime. The torsion results revealed that the torsional rigidity of the NW was insensitive to the presence of pre-existing defects and twin boundaries, but received evident reduction due to grain boundaries. Meanwhile, the critical angle decreased considerably for defected NWs. This study has provided a comprehensive and deep investigation on the mechanical properties and deformation mechanisms of perfect and defected NWs, which will greatly extend and enhance the existing knowledge and understanding of the properties/performance of NWs, and eventually benefit the realization of their full potential applications. All delineated MD models and theoretical analysis techniques that were established for the target NWs in this research are also applicable to future studies on other kinds of NWs. It has been suggested that MD simulation is an effective and excellent tool, not only for the characterization of the properties of NWs, but also for the prediction of novel or unexpected properties.

Reliability and validity of query intent assessments

In most intent recognition studies, annotations of query intent are created post hoc by external assessors who are not the searchers themselves. It is important for the field to get a better understanding of the quality of this process as an approximation for determining the searcher's actual intent. Some studies have investigated the reliability of the query intent annotation process by measuring the interassessor agreement. However, these studies did not measure the validity of the judgments, that is, to what extent the annotations match the searcher's actual intent. In this study, we asked both the searchers themselves and external assessors to classify queries using the same intent classification scheme. We show that of the seven dimensions in our intent classification scheme, four can reliably be used for query annotation. Of these four, only the annotations on the topic and spatial sensitivity dimension are valid when compared with the searcher's annotations. The difference between the interassessor agreement and the assessor-searcher agreement was significant on all dimensions, showing that the agreement between external assessors is not a good estimator of the validity of the intent classifications. Therefore, we encourage the research community to consider using query intent classifications by the searchers themselves as test data.

Enabling open access to and re-use of publicly funded research data in Malaysian public universities : a legal and policy analysis

Numerous statements and declarations have been made over recent decades in support of open access to research data. The growing recognition of the importance of open access to research data has been accompanied by calls on public research funding agencies and universities to facilitate better access to publicly funded research data so that it can be re-used and redistributed as public goods. International and inter-governmental bodies such as the ICSU/CODATA, the OECD and the European Union are strong supporters of open access to and re-use of publicly funded research data. This thesis focuses on the research data created by university researchers in Malaysian public universities whose research activities are funded by the Federal Government of Malaysia. Malaysia, like many countries, has not yet formulated a policy on open access to and re-use of publicly funded research data. Therefore, the aim of this thesis is to develop a policy to support the objective of enabling open access to and re-use of publicly funded research data in Malaysian public universities. Policy development is very important if the objective of enabling open access to and re-use of publicly funded research data is to be successfully achieved. In developing the policy, this thesis identifies a myriad of legal impediments arising from intellectual property rights, confidentiality, privacy and national security laws, novelty requirements in patent law and lack of a legal duty to ensure data quality. Legal impediments such as these have the effect of restricting, obstructing, hindering or slowing down the objective of enabling open access to and re-use of publicly funded research data. A key focus in the formulation of the policy was the need to resolve the various legal impediments that have been identified. This thesis analyses the existing policies and guidelines of Malaysian public universities to ascertain to what extent the legal impediments have been resolved. An international perspective is adopted by making a comparative analysis of the policies of public research funding agencies and universities in the United Kingdom, the United States and Australia to understand how they have dealt with the identified legal impediments. These countries have led the way in introducing policies which support open access to and re-use of publicly funded research data. As well as proposing a policy supporting open access to and re-use of publicly funded research data in Malaysian public universities, this thesis provides procedures for the implementation of the policy and guidelines for addressing the legal impediments to open access and re-use.

Characterisation and source apportionment of polycyclic aromatic hydrocarbons in the sediments of Brisbane River

The thesis was a step forward in predicting the levels and sources of polycyclic aromatic hydrocarbons (PAHs) in sediments of Brisbane river, especially after the Brisbane floods in 2011. It employed different statistical techniques to provide valuable information that may assist source control and formulation of pollution mitigation measures for the river.

Development and formative evaluation of a motorcycle rider training intervention to address risk taking

The need to address on-road motorcycle safety in Australia is important due to the disproportionately high percentage of riders and pillions killed and injured each year. One approach to preventing motorcycle-related injury is through training and education. However, motorcycle rider training lacks empirical support as an effective road safety countermeasure to reduce crash involvement. Previous reviews have highlighted that risk-taking is a contributing factor in many motorcycle crashes, rather than merely a lack of vehicle-control skills (Haworth & Mulvihill, 2005; Jonah, Dawson & Bragg, 1982; Watson et al, 1996). Hence, though the basic vehicle-handling skills and knowledge of road rules that are taught in most traditional motorcycle licence training programs may be seen as an essential condition of safe riding, they do not appear to be sufficient in terms of crash reduction. With this in mind there is considerable scope for the improvement of program focus and content for rider training and education. This program of research examined an existing traditional pre-licence motorcycle rider training program and formatively evaluated the addition of a new classroom-based module to address risky riding; the Three Steps to Safer Riding program. The pilot program was delivered in the real world context of the Q-Ride motorcycle licensing system in the state of Queensland, Australia. Three studies were conducted as part of the program of research: Study 1, a qualitative investigation of delivery practices and student learning needs in an existing rider training course; Study 2, an investigation of the extent to which an existing motorcycle rider training course addressed risky riding attitudes and motives; and Study 3, a formative evaluation of the new program. A literature review as well as the investigation of learning needs for motorcyclists in Study 1 aimed to inform the initial planning and development of the Three Steps to Safer Riding program. Findings from Study 1 suggested that the training delivery protocols used by the industry partner training organisation were consistent with a learner-centred approach and largely met the learning needs of trainee riders. However, it also found that information from the course needs to be reinforced by on-road experiences for some riders once licensed and that personal meaning for training information was not fully gained until some riding experience had been obtained. While this research informed the planning and development of the new program, a project team of academics and industry experts were responsible for the formulation of the final program. Study 2 and Study 3 were conducted for the purpose of formative evaluation and program refinement. Study 2 served primarily as a trial to test research protocols and data collection methods with the industry partner organisation and, importantly, also served to gather comparison data for the pilot program which was implemented with the same rider training organisation. Findings from Study 2 suggested that the existing training program of the partner organisation generally had a positive (albeit small) effect on safety in terms of influencing attitudes to risk taking, the propensity for thrill seeking, and intentions to engage in future risky riding. However, maintenance of these effects over time and the effects on riding behaviour remain unclear due to a low response rate upon follow-up 24 months after licensing. Study 3 was a formative evaluation of the new pilot program to establish program effects and possible areas for improvement. Study 3a examined the short term effects of the intervention pilot on psychosocial factors underpinning risky riding compared to the effects of the standard traditional training program (examined in Study 2). It showed that the course which included the Three Steps to Safer Riding program elicited significantly greater positive attitude change towards road safety than the existing standard licensing course. This effect was found immediately following training, and mean scores for attitudes towards safety were also maintained at the 12 month follow-up. The pilot program also had an immediate effect on other key variables such as risky riding intentions and the propensity for thrill seeking, although not significantly greater than the traditional standard training. A low response rate at the 12 month follow-up unfortunately prevented any firm conclusions being drawn regarding the impact of the pilot program on self-reported risky riding once licensed. Study 3a further showed that the use of intermediate outcomes such as self-reported attitudes and intentions for evaluation purposes provides insights into the mechanisms underpinning risky riding that can be changed by education and training. A multifaceted process evaluation conducted in Study 3b confirmed that the intervention pilot was largely delivered as designed, with course participants also rating most aspects of training delivery highly. The complete program of research contributed to the overall body of knowledge relating to motorcycle rider training, with some potential implications for policy in the area of motorcycle rider licensing. A key finding of the research was that psychosocial influences on risky riding can be shaped by structured education that focuses on awareness raising at a personal level and provides strategies to manage future riding situations. However, the formative evaluation was mainly designed to identify areas of improvement for the Three Steps to Safer Riding program and found several areas of potential refinement to improve future efficacy of the program. This included aspects of program content, program delivery, resource development, and measurement tools. The planned future follow-up of program participants' official crash and traffic offence records over time may lend further support for the application of the program within licensing systems. The findings reported in this thesis offer an initial indication that the Three Steps to Safer Riding is a useful resource to accompany skills-based training programs.

Bioequivalence of two tablet formulations of capecitabine and exploration of age, gender, body surface area, and creatinine clearance as factors influencing systemic exposure in cancer patients

Purpose: The objective of the study was to assess the bioequivalence of two tablet formulations of capecitabine and to explore the effect of age, gender, body surface area and creatinine clearance on the systemic exposure to capecitabine and its metabolites. Methods: The study was designed as an open, randomized two-way crossover trial. A single oral dose of 2000 mg capecitabine was administered on two separate days to 25 patients with solid tumors. On one day, the patients received four 500-mg tablets of formulation B (test formulation) and on the other day, four 500-mg tablets of formulation A (reference formulation). The washout period between the two administrations was between 2 and 8 days. After each administration, serial blood and urine samples were collected for up to 12 and 24 h, respectively. Unchanged capecitabine and its metabolites were determined in plasma using LC/MS-MS and in urine by NMRS. Results: Based on the primary pharmacokinetic parameter, AUC(0-∞) of 5'-DFUR, equivalence was concluded for the two formulations, since the 90% confidence interval of the estimate of formulation B relative to formulation A of 97% to 107% was within the acceptance region 80% to 125%. There was no clinically significant difference between the t(max) for the two formulations (median 2.1 versus 2.0 h). The estimate for C(max) was 111% for formulation B compared to formulation A and the 90% confidence interval of 95% to 136% was within the reference region 70% to 143%. Overall, these results suggest no relevant difference between the two formulations regarding the extent to which 5'-DFUR reached the systemic circulation and the rate at which 5'-DFUR appeared in the systemic circulation. The overall urinary excretions were 86.0% and 86.5% of the dose, respectively, and the proportion recovered as each metabolite was similar for the two formulations. The majority of the dose was excreted as FBAL (61.5% and 60.3%), all other chemical species making a minor contribution. Univariate and multivariate regression analysis to explore the influence of age, gender, body surface area and creatinine clearance on the log-transformed pharmacokinetic parameters AUC(0-∞) and C(max) of capecitabine and its metabolites revealed no clinically significant effects. The only statistically significant results were obtained for AUC(0-∞) and C(max) of intact drug and for C(max) of FBAL, which were higher in females than in males. Conclusion: The bioavailability of 5'-DFUR in the systemic circulation was practically identical after administration of the two tablet formulations. Therefore, the two formulations can be regarded as bioequivalent. The variables investigated (age, gender, body surface area, and creatinine clearance) had no clinically significant effect on the pharmacokinetics of capecitabine or its metabolites.

Assessing land-use and transport integration via a spatial composite indexing model

Achieving sustainable urban development is identified as one ultimate goal of many contemporary planning endeavours and has become central to formulation of urban planning policies. Within this concept, land-use and transport integration is highlighted as one of the most important and attainable policy objectives. In many cities, integration is embraced as an integral part of local development plans, and a number of key integration principles are identified. However, the lack of available evaluation methods to measure extent of urban sustainability levels prevents successful implementation of these principles. This paper introduces a new indicator-based spatial composite indexing model developed to measure sustainability performance of urban settings by taking into account land-use and transport integration principles. Model indicators are chosen via a thorough selection process in line with key principles of land-use and transport integration. These indicators are grouped into categories and themes according to their topical relevance. These indicators are then aggregated to form a spatial composite index to portray an overview of the sustainability performance of the pilot study area used for model demonstration. The study results revealed that the model is a practical instrument for evaluating success of local integration policies and visualizing sustainability performance of built environments and useful in both identifying problematic areas as well as formulating policy interventions.

Dry powder inhaler formulations-effect of polymer carrier size on the drug dispersion

Background The size of the carrier influences the aerosolization of drug from a dry powder inhaler (DPI) formulation. Currently, lactose monohydrate particles in a variety of sizes are preferably used in carrier based DPI formulations of various drugs; however, contradictory reports exist regarding the effect of the size of the carrier on the dispersion of drug. In this study we examined the influence of the intrinsic particle size of the polymeric carrier on the aerosolization of a model drug salbutamol sulphate (SS). Methods Four different sizes (20–150 lm) of polymer carriers were fabricated using solvent evaporation technique and the dispersion of SS particles from these carriers was measured by a Twin Stage Impinger (TSI). The size and morphological properties of polymer carriers were by laser diffraction and SEM, respectively. Results The FPF from these carriers was found to be increasing from 5.6% to 21.3% with increasing the carrier size. The FPF was found to be greater (21%) with the highest particle size of the carrier (150 lm). Conclusions The aerosolization of drug was dependent on the size of polymer carriers. The smaller size of the carrier resulted in lower FPF which was increased with increasing the carrier size. For a fixed mass of drug particles in a formulation, the mass of drug particles per unit area of carriers is higher in formulations containing the larger carriers, which leads to an increase in the dispersion of drug due to the increased mechanical forces occurred between the carriers and the device walls.

Understanding the fabric of social interactions for ridesharing through mining social networking sites

The design of applications for dynamic ridesharing or carpooling is often formulated as a matching problem of connecting people with an aligned set of transport needs within a reasonable interval of time and space. This problem formulation relegates social connections to being secondary factors. Technology assisted ridesharing applications that put the matching problem first have revealed that they suffer from being unable to address the factor of social comfort, even after adding friend features or piggybacking on social networking sites. This research aims to understand the fabric of social interactions through which ridesharing happens. We take an online observation approach in order to understand the fabric of social interactions for ridesharing that is happening in highly subscribed online groups of local residents. This understanding will help researchers to identify design challenges and opportunities to support ridesharing in local communities. This paper contributes a fundamental understanding of how social interactions and social comfort precede rideshare requests in local communities.

Colloidal drug probe : method development and validation for adhesion force measurement using atomic force microscopy

This study demonstrates a novel technique of preparing drug colloid probes to determine the adhesion force between the drug salbutamol sulphate (SS) and the surfaces of polymer microparticles to be used as carriers for the dispersion of drug particles from a dry powder inhaler (DPI) formulation. Initially model silica probes of approximately 4 μm size, similar to a drug particle used in DPI formulations, were coated with a saturated SS solution with the aid of capillary forces acting between the silica probe and the drug solution. The developed method of ensuring a smooth and uniform layer of SS on the silica probe was validated using X-Ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM). Using the same technique, silica microspheres preattached on the AFM cantilever were coated with SS. The adhesion forces between the silica probe and drug coated silica (drug probe) and polymer surfaces (hydrophilic and hydrophobic) were determined. Our experimental results showed that the technique for preparing the drug probe was robust and can be used to determine the adhesion force between hydrophilic/hydrophobic drug probe and carrier surfaces to gain a better understanding on drug carrier adhesion forces in DPI formulations.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

Transcutaneous immunization with a novel lipid-based adjuvant protects against Chlamydia genital and respiratory infections

Mucosal adjuvants are important to overcome the state of immune tolerance normally associated with mucosal delivery and to enhance adaptive immunity to often-weakly immunogenic subunit vaccine antigens. Unfortunately, adverse side effects of many experimental adjuvants limit the number of adjuvants approved for vaccination. Lipid C is a novel, non-toxic, lipid oral vaccine-delivery formulation, developed originally for oral delivery of the live Mycobacterium bovis Bacille Calmette-Guerin (BCG) vaccine. In the present study, murine models of chlamydial respiratory and genital tract infections were used to determine whether transcutaneous immunization (TCI) with Lipid C-incorporated protein antigens could elicit protective immunity at the genital and respiratory mucosae. BALB/c mice were immunized transcutaneously with Lipid C containing the chlamydial major outer membrane protein (MOMP), with and without addition of cholera toxin and CpG-ODN 1826 (CT/CpG). Both vaccine combinations induced mixed cell-mediated and mucosal antibody immune responses. Immunization with Lipid C-incorporated MOMP (Lipid C/MOMP), either alone or with CT/CpG resulted in partial protection following live challenge with Chlamydia muridarum as evidenced by a significant reduction in recoverable Chlamydia from both the genital secretions and lung tissue. Protection induced by immunization with Lipid C/MOMP alone was not further enhanced by the addition of CT/CpG. These results highlight the potential of Lipid C as a novel mucosal adjuvant capable of targeting multiple mucosal surfaces following TCI. Protection at both the respiratory and genital mucosae was achieved without the requirement for potentially toxic adjuvants, suggesting that Lipid C may provide a safe effective mucosal adjuvant for human vaccination.

Technological tools for science classrooms : choosing and using for productive and sustainable teaching and learning experiences

In this age of rapidly evolving technology, teachers are encouraged to adopt ICTs by government, syllabus, school management, and parents. Indeed, it is an expectation that teachers will incorporate technologies into their classroom teaching practices to enhance the learning experiences and outcomes of their students. In particular, regarding the science classroom, a subject that traditionally incorporates hands-on experiments and practicals, the integration of modern technologies should be a major feature. Although myriad studies report on technologies that enhance students’ learning outcomes in science, there is a dearth of literature on how teachers go about selecting technologies for use in the science classroom. Teachers can feel ill prepared to assess the range of available choices and might feel pressured and somewhat overwhelmed by the avalanche of new developments thrust before them in marketing literature and teaching journals. The consequences of making bad decisions are costly in terms of money, time and teacher confidence. Additionally, no research to date has identified what technologies science teachers use on a regular basis, and whether some purchased technologies have proven to be too problematic, preventing their sustained use and possible wider adoption. The primary aim of this study was to provide research-based guidance to teachers to aid their decision-making in choosing technologies for the science classroom. The study unfolded in several phases. The first phase of the project involved survey and interview data from teachers in relation to the technologies they currently use in their science classrooms and the frequency of their use. These data were coded and analysed using Grounded Theory of Corbin and Strauss, and resulted in the development of a PETTaL model that captured the salient factors of the data. This model incorporated usability theory from the Human Computer Interaction literature, and education theory and models such as Mishra and Koehler’s (2006) TPACK model, where the grounded data indicated these issues. The PETTaL model identifies Power (school management, syllabus etc.), Environment (classroom / learning setting), Teacher (personal characteristics, experience, epistemology), Technology (usability, versatility etc.,) and Learners (academic ability, diversity, behaviour etc.,) as fields that can impact the use of technology in science classrooms. The PETTaL model was used to create a Predictive Evaluation Tool (PET): a tool designed to assist teachers in choosing technologies, particularly for science teaching and learning. The evolution of the PET was cyclical (employing agile development methodology), involving repeated testing with in-service and pre-service teachers at each iteration, and incorporating their comments i ii in subsequent versions. Once no new suggestions were forthcoming, the PET was tested with eight in-service teachers, and the results showed that the PET outcomes obtained by (experienced) teachers concurred with their instinctive evaluations. They felt the PET would be a valuable tool when considering new technology, and it would be particularly useful as a means of communicating perceived value between colleagues and between budget holders and requestors during the acquisition process. It is hoped that the PET could make the tacit knowledge acquired by experienced teachers about technology use in classrooms explicit to novice teachers. Additionally, the PET could be used as a research tool to discover a teachers’ professional development needs. Therefore, the outcomes of this study can aid a teacher in the process of selecting educationally productive and sustainable new technology for their science classrooms. This study has produced an instrument for assisting teachers in the decision-making process associated with the use of new technologies for the science classroom. The instrument is generic in that it can be applied to all subject areas. Further, this study has produced a powerful model that extends the TPACK model, which is currently extensively employed to assess teachers’ use of technology in the classroom. The PETTaL model grounded in data from this study, responds to the calls in the literature for TPACK’s further development. As a theoretical model, PETTaL has the potential to serve as a framework for the development of a teacher’s reflective practice (either self evaluation or critical evaluation of observed teaching practices). Additionally, PETTaL has the potential for aiding the formulation of a teacher’s personal professional development plan. It will be the basis for further studies in this field.