Exploring the process of implementing a smoking cessation intervention in pregnancy training program for midwives

The question of how to implement evidence effectively reveals a deficiency in our knowledge and understanding of the compound factors involved in such a process (Kitson, Rycroft-Malone et al. 2008). Although there is some awareness of the complexities of the process, there has been little exploration of the effectiveness of implementing evidence-based programs in health care. Despite public awareness of the dangers of smoking in pregnancy, and widespread public health measures to prevent smoking-related disease, women still continue to smoke in pregnancy (Ananth, Savitz et al. 1997; Laws and Hilder 2008). Evaluation of public health measures concludes that smoking cessation interventions during pregnancy increase quit rates among pregnant women (Melvin, Dolan-Mullen et al. 2000; Albrecht, Maloni et al. 2004; Lumley, Oliver et al. 2007). Notwithstanding the potential for improvement in health outcomes for pregnant women and their unborn babies, smoking interventions are often conducted poorly or not at all. Although midwives understand why women smoke in pregnancy and parenthood and are aware of the risks of smoking to both the pregnancy and the unborn child, they require specific knowledge and skills in the provision of support and advice on smoking for pregnant women (Bull and Whitehead 2006) . Organisational-change research demonstrates the complexity of the process of planned change in professionalised institutions such as health care (Greenhalgh, Robert et al. 2005). Some innovations and interventions are never accepted, and others are poorly supported (Greenhalgh, Robert et al. 2004). Comprehension of the change process around health promotion is crucial to the implementation of new health promotion interventions within health care (Riley, Taylor et al. 2003). This study utilised a case study approach to explore the process of implementing a smoking cessation training program for midwives in Queensland metropolitan and regional clinical areas, who attended a ‘Train-the-Trainer program’. The study draws on the organisational change work of Greenhalgh et al (2004) as the theoretical framework through which situational and structural factors are explored and examined as they inform the implementation of smoking cessation programs. The research data constituted staged interviews with midwives who instituted training programs for midwives, as well as organisational and policy documentation. Analysis of the data identified some areas that were not fully addressed in the theoretical model; these formed the basis of the Discussion and Implications for Future Research.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Structural Systematics of the Anhydrous 1:1 Proton-Transfer Compounds of 3,5-Dinitrosalicylic Acid with Aniline and Monosubstituted Anilines

The crystal structures of the proton-transfer compounds of 3,5-dinitrosalicylic acid (DNSA) with a series of aniline-type Lewis bases [aniline, 2-hydroxyaniline, 2-methoxyaniline, 3-methoxyaniline, 4-fluoroaniline, 4-chloroaniline and 2-aminoaniline] have been determined and their hydrogen-bonding systems analysed. All are anhydrous 1:1 salts: [(C6H8N)+(C7H3N2O7)-], (1), [(C6H8NO)+(C7H3N2O7)-], (2), [(C7H10NO)+(C7H3N2O7)-], (3), [(C7H10NO)+(C7H3N2O7)-], (4), [(C6H7FN)+(C7H3N2O7)-], (5), [(C6H7ClN)+(C7H3N2O7)-], (6), and [(C6H9N2)+(C7H3N2O7)-], (7) respectively. Crystals of 1 and 6 are triclinic, space group P-1 while the remainder are monoclinic with space group either P21/n (2, 4, 5 and 7) or P21 (3). Unit cell dimensions and contents are: for 1, a = 7.2027(17), b = 7.5699(17), c = 12.9615(16) Å, α = 84.464(14), β = 86.387(15), γ = 75.580(14)o, Z = 2; for 2, a = 7.407(3), b = 6.987(3), c = 27.653(11) Å, β = 94.906(7)o, Z = 4; for 3, a = 8.2816(18), b = 23.151(6), c = 3.9338(10), β = 95.255(19)o, Z = 2; for 4, a = 11.209(2), b = 8.7858(19), c = 15.171(3) Å, β = 93.717(4)o, Z = 4; for 5, a = 26.377(3), b = 10.1602(12), c = 5.1384(10) Å, β = 91.996(13)o, Z = 4; for 6, a = 11.217(3), b = 14.156(5), c = 4.860(3) Å, α = 99.10(4), β = 96.99(4), γ = 76.35(2)o, Z = 2; for 7, a = 12.830(4), b = 8.145(3), c = 14.302(4) Å, β = 102.631(6)o, Z = 4. In all compounds at least one primary linear intermolecular N+-H…O(carboxyl) hydrogen-bonding interaction is present which, together with secondary hydrogen bonding results in the formation of mostly two-dimensional network structures, exceptions being with compounds 4 and 5 (one-dimensional) and compound 6 (three-dimensional). In only two cases [compounds 1 and 4], are weak cation-anion or cation-cation π-π interactions found while weak aromatic C-H…O interactions are insignificant. The study shows that all compounds fit the previously formulated classification scheme for primary and secondary interactive modes for proton-transfer compounds of 3,5-dinitrosalicylic acid but there are some unusual variants.

Structural and thermal performance of cold-formed steel stud wall systems under fire conditions

Cold-formed steel stud walls are a major component of Light Steel Framing (LSF) building systems used in commercial, industrial and residential buildings. In the conventional LSF stud wall systems, thin steel studs are protected from fire by placing one or two layers of plasterboard on both sides with or without cavity insulation. However, there is very limited data about the structural and thermal performance of stud wall systems while past research showed contradicting results, for example, about the benefits of cavity insulation. This research was therefore conducted to improve the knowledge and understanding of the structural and thermal performance of cold-formed steel stud wall systems (both load bearing and non-load bearing) under fire conditions and to develop new improved stud wall systems including reliable and simple methods to predict their fire resistance rating. Full scale fire tests of cold-formed steel stud wall systems formed the basis of this research. This research proposed an innovative LSF stud wall system in which a composite panel made of two plasterboards with insulation between them was used to improve the fire rating. Hence fire tests included both conventional steel stud walls with and without the use of cavity insulation and the new composite panel system. A propane fired gas furnace was specially designed and constructed first. The furnace was designed to deliver heat in accordance with the standard time temperature curve as proposed by AS 1530.4 (SA, 2005). A compression loading frame capable of loading the individual studs of a full scale steel stud wall system was also designed and built for the load-bearing tests. Fire tests included comprehensive time-temperature measurements across the thickness and along the length of all the specimens using K type thermocouples. They also included the measurements of load-deformation characteristics of stud walls until failure. The first phase of fire tests included 15 small scale fire tests of gypsum plasterboards, and composite panels using different types of insulating material of varying thickness and density. Fire performance of single and multiple layers of gypsum plasterboards was assessed including the effect of interfaces between adjacent plasterboards on the thermal performance. Effects of insulations such as glass fibre, rock fibre and cellulose fibre were also determined while the tests provided important data relating to the temperature at which the fall off of external plasterboards occurred. In the second phase, nine small scale non-load bearing wall specimens were tested to investigate the thermal performance of conventional and innovative steel stud wall systems. Effects of single and multiple layers of plasterboards with and without vertical joints were investigated. The new composite panels were seen to offer greater thermal protection to the studs in comparison to the conventional panels. In the third phase of fire tests, nine full scale load bearing wall specimens were tested to study the thermal and structural performance of the load bearing wall assemblies. A full scale test was also conducted at ambient temperature. These tests showed that the use of cavity insulation led to inferior fire performance of walls, and provided good explanations and supporting research data to overcome the incorrect industry assumptions about cavity insulation. They demonstrated that the use of insulation externally in a composite panel enhanced the thermal and structural performance of stud walls and increased their fire resistance rating significantly. Hence this research recommends the use of the new composite panel system for cold-formed LSF walls. This research also included steady state tensile tests at ambient and elevated temperatures to address the lack of reliable mechanical properties for high grade cold-formed steels at elevated temperatures. Suitable predictive equations were developed for calculating the yield strength and elastic modulus at elevated temperatures. In summary, this research has developed comprehensive experimental thermal and structural performance data for both the conventional and the proposed non-load bearing and load bearing stud wall systems under fire conditions. Idealized hot flange temperature profiles have been developed for non-insulated, cavity insulated and externally insulated load bearing wall models along with suitable equations for predicting their failure times. A graphical method has also been proposed to predict the failure times (fire rating) of non-load bearing and load bearing walls under different load ratios. The results from this research are useful to both fire researchers and engineers working in this field. Most importantly, this research has significantly improved the knowledge and understanding of cold-formed LSF walls under fire conditions, and developed an innovative LSF wall system with increased fire rating. It has clearly demonstrated the detrimental effects of using cavity insulation, and has paved the way for Australian building industries to develop new wall panels with increased fire rating for commercial applications worldwide.

Performance load testing and structural adequacy evaluation of road bridge decks

Many ageing road bridges, particularly timber bridges, require urgent improvement due to the demand imposed by the recent version of the Australian bridge loading code, AS 5100. As traffic volume plays a key role in the decision of budget allocations for bridge refurbishment/ replacement, many bridges in low volume traffic network remain in poor condition with axle load and/ or speed restrictions, thus disadvantaging many rural communities. This thesis examines an economical and environmentally sensible option of incorporating disused flat rail wagons (FRW) in the construction of bridges in low volume, high axle load road network. The constructability, economy and structural adequacy of the FRW road bridge is reported in the thesis with particular focus of a demonstration bridge commissioned in regional Queensland. The demonstration bridge comprises of a reinforced concrete slab (RCS) pavement resting on two FRWs with custom designed connection brackets at regular intervals along the span of the bridge. The FRW-RC bridge deck assembly is supported on elastomeric rubber pads resting on the abutment. As this type of bridge replacement technology is new and its structural design is not covered in the design standards, the in-service structural performance of the FRW bridge subjected to the high axle loadings prescribed in AS 5100 is examined through performance load testing. Both the static and the moving load tests are carried out using a fully laden commonly available three-axle tandem truck. The bridge deck is extensively strain gauged and displacement at several key locations is measured using linear variable displacement transducers (LVDTs). A high speed camera is used in the performance test and the digital image data are analysed using proprietary software to capture the locations of the wheel positions on the bridge span accurately. The wheel location is thus synchronised with the displacement and strain time series to infer the structural response of the FRW bridge. Field test data are used to calibrate a grillage model, developed for further analysis of the FRW bridge to various sets of high axle loads stipulated in the bridge design standard. Bridge behaviour predicted by the grillage model has exemplified that the live load stresses of the FRW bridge is significantly lower than the yield strength of steel and the deflections are well below the serviceability limit state set out in AS 5100. Based on the results reported in this thesis, it is concluded that the disused FRWs are competent to resist high axle loading prescribed in AS 5100 and are a viable alternative structural solution of bridge deck in the context of the low volume road networks.

Prediction of structural integrity, robustness and service life using advanced finite element methods

Corrosion is a common phenomenon and critical aspects of steel structural application. It affects the daily design, inspection and maintenance in structural engineering, especially for the heavy and complex industrial applications, where the steel structures are subjected to hash corrosive environments in combination of high working stress condition and often in open field and/or under high temperature production environments. In the paper, it presents the actual engineering application of advanced finite element methods in the predication of the structural integrity and robustness at a designed service life for the furnaces of alumina production, which was operated in the high temperature, corrosive environments and rotating with high working stress condition.

Molecular structural studies of the amorphous mineral pitticite Fe, AsO4, SO4, H2O

Some minerals are colloidal and show no X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of these types of mineral. Among this group of minerals is pitticite simply described as Fe, AsO4, SO4, H2O. The objective of this research is to determine the molecular structure of the mineral pitticite using vibrational spectroscopy. Raman microscopy offers a useful method for the analysis of such colloidal minerals. Raman and infrared bands are attributed to the , and water stretching vibrations. The Raman spectrum is dominated by a very intense sharp band at 983 cm−1 assigned to the symmetric stretching mode. A strong Raman band at 1041 cm−1 is observed and is assigned to the antisymmetric stretching mode. Low intensity Raman bands at 757 and 808 cm−1 may be assigned to the antisymmetric and symmetric stretching modes. Raman bands observed at 432 and 465 cm−1 are attributable to the doubly degenerate ν2(SO4)2- bending mode.

The analysis of social capital in online social communities

Social networks have proven to be an attractive avenue of investigation for researchers since humans are social creatures. Numerous literature have explored the term “social networks” from different perspectives and in diverse research fields. With the popularity of the Internet, social networking has taken on a new dimension. Online social communities therefore have become an emerging social avenue for people to communicate in today’s information age. People use online social communities to share their interests, maintain friendships, and extend their so-called circle of “friends”. Likewise, social capital, also known as human capital, is an important theory in sociology. Researchers usually utilise social capital theory when they investigate the topic relating to social networks. However, there is little literature that can provide an explicit and strong assertion in that research area due to the complexity of social capital. This thesis therefore focuses on the issue related to providing a better understanding about the relationship between social capital and online social communities. To enhance the value within the scope of this analysis, an online survey was conducted to examine the effects of the dimensions of social capital: relational capital, structural capital, and cognitive capital, determining the intensity of using online social communities. The data were derived from a total of 350 self-selected respondents completing an online survey during the research period. The main results indicate that social capital exists in online social communities under normal circumstances. Finally, this thesis also presents three contributions for both theory and practice in Chapter 5. The main results contribute to the understanding of connectivity in the interrelationships between individual social capital exchange within online social networks. Secondly, social trust was found to have a weak effect in influencing the intensity of individuals using online social communities. Third, the perpetual role of information sharing has an indirect influence on individual users participating in online social communities. This study also benefits online marketing consultants as marketers can not only gain consumer information easier from online social communities but also this understanding assists in designing effective communication within online social communities. The cross-sectional study, the reliability of Internet survey data, and sampling issues are the major three limitations in this research. The thesis provides a new research model and recommends that the mediating effects, privacy paradox, and social trust on online social communities should be further explored in future research.

Complexity, evolution, and the structure of demand

This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.

Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.

Interactive axial shortening of columns and walls in high rise buildings

Concrete is commonly used as a primary construction material for tall building construction. Load bearing components such as columns and walls in concrete buildings are subjected to instantaneous and long term axial shortening caused by the time dependent effects of "shrinkage", "creep" and "elastic" deformations. Reinforcing steel content, variable concrete modulus, volume to surface area ratio of the elements and environmental conditions govern axial shortening. The impact of differential axial shortening among columns and core shear walls escalate with increasing building height. Differential axial shortening of gravity loaded elements in geometrically complex and irregular buildings result in permanent distortion and deflection of the structural frame which have a significant impact on building envelopes, building services, secondary systems and the life time serviceability and performance of a building. Existing numerical methods commonly used in design to quantify axial shortening are mainly based on elastic analytical techniques and therefore unable to capture the complexity of non-linear time dependent effect. Ambient measurements of axial shortening using vibrating wire, external mechanical strain, and electronic strain gauges are methods that are available to verify pre-estimated values from the design stage. Installing these gauges permanently embedded in or on the surface of concrete components for continuous measurements during and after construction with adequate protection is uneconomical, inconvenient and unreliable. Therefore such methods are rarely if ever used in actual practice of building construction. This research project has developed a rigorous numerical procedure that encompasses linear and non-linear time dependent phenomena for prediction of axial shortening of reinforced concrete structural components at design stage. This procedure takes into consideration (i) construction sequence, (ii) time varying values of Young's Modulus of reinforced concrete and (iii) creep and shrinkage models that account for variability resulting from environmental effects. The capabilities of the procedure are illustrated through examples. In order to update previous predictions of axial shortening during the construction and service stages of the building, this research has also developed a vibration based procedure using ambient measurements. This procedure takes into consideration the changes in vibration characteristic of structure during and after construction. The application of this procedure is illustrated through numerical examples which also highlight the features. The vibration based procedure can also be used as a tool to assess structural health/performance of key structural components in the building during construction and service life.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Measuring complexity for building projects : a Delphi study

Purpose---The aim of this study is to identify complexity measures for building projects in the People’s Republic of China (PRC). Design/Methodology/Approach---A three-round of Delphi questionnaire survey was conducted to identify the key parameters that measure the degree of project complexity. A complexity index (CI) was developed based on the identified measures and their relative importance. Findings---Six key measures of project complexity have been identified, which include, namely (1) building structure & function; (2) construction method; (3) the urgency of the project schedule; (4) project size/scale; (5) geological condition; and (6) neighboring environment. Practical implications---These complexity measures help stakeholders assess degrees of project complexity and better manage the potential risks that might be induced to different levels of project complexity. Originality/Value---The findings provide insightful perspectives to define and understand project complexity. For stakeholders, understanding and addressing the complexity help to improve project planning and implementation.