Health monitoring of buildings during construction and service stages using vibration characteristics

Columns and walls in buildings are subjected to a number of load increments during the construction and service stages. The combination of these load increments and poor quality construction can cause defects in these structural components. In addition, defects can also occur due to accidental or deliberate actions by users of the building during construction and service stages. Such defects should be detected early so that remedial measures can be taken to improve life time serviceability and performance of the building. This paper uses micro and macro model upgrading methods during construction and service stages of a building based on the mass and stiffness changes to develop a comprehensive procedure for locating and detecting defects in columns and walls of buildings. Capabilities of the procedure are illustrated through examples.

Assessment of “change in flexibility method” in structural health monitoring systems

The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.

Health matters for subscribers to community-supported agriculture

There are a variety of reasons and motivations for people to subscribe to community-supported agriculture (CSA) schemes, many of which include social, ethical, environmental, and economical benefits. The global rise of food allergies and food related health issues in recent years has led to a growing number of initiatives particularly in developing countries to raise more awareness of the current situation amongst individuals, organisations, and government bodies, and to plan for its implications for the existing food and health systems. Based on a mixed method research conducted in Australia, this paper argues that personal health matters are one of the key motivators for consumers to seek out alternative food systems, particularly CSA initiatives. In addition, it presents the willingness for consumers to seek out information about the food they consume and proposes that technology plays a key role in being used as a conduit to share and investigate information relating to alternative food systems. Further research is required to determine the variety of benefits and opportunities alternative food systems can provide consumers with food related health issues.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Health professionals’ perspectives on information provision for patients with brain tumours and their families

A significant number of patients diagnosed with primary brain tumours report unmet information needs. Using concept mapping methodology, this study aimed to identify strategies for improving information provision, and to describe factors that health professionals understood to influence their provision of information to patients with brain tumours and their families. Concept mapping is a mixed methods approach that uses statistical methods to represent participants’ perceived relationships between elements as conceptual maps. These maps, and results of associated data collection and analyses, are used to extract concepts involved in information provision to these patients. Thirty health professionals working across a range of neuro-oncology roles and settings participated in the concept mapping process. Participants rated a care coordinator as the most important strategy for improving brain tumour care, with psychological support as a whole rated as the most important element of care. Five major themes were identified as facilitating information provision: health professionals’ communication skills, style and attitudes; patients’ needs and preferences; perceptions of patients’ need for protection and initiative; rapport and continuity between patients and health professionals; and the nature of the health care system. Overall, health professionals conceptualised information provision as ‘individualised’, dependent on these interconnected personal and environmental factors.

Educational stress among Chinese adolescents : measurement, risk factors and associations with mental health

Academic pressure among adolescents is a major risk factor for poor mental health and suicide and other harmful behaviours. While this is a worldwide phenomenon, it appears to be especially pronounced in China and other East Asian countries. Despite a growing body of research into adolescent mental health in recent years, the multiple constructs within the ‘educational stress’ phenomenon have not been clearly articulated in Chinese contexts. Further, the individual, family, school and peer influencing factors for educational stress and its associations with adolescent mental health are not well understood. An in-depth investigation may provide important information for the ongoing educational reform in Mainland China with a special focus on students’ mental health and wellbeing. The primary goal of this study was to examine the relative contribution of educational stress to poor mental health, in comparison to other well-known individual, family, school and peer factors. Another important task was to identify significant risk factors for educational stress. In addition, due to the lack of a culturally suitable instrument for educational stress in this population, a new tool – the Educational Stress Scale for Adolescents (ESSA) was initially developed in this study and tested for reliability and validity. A self-administered questionnaire was used to collect information from convenient samples of secondary school students in Shandong, China. The pilot survey was conducted with 347 students (grades 8 and 11) to test the psychometric properties of the ESSA and other scales or questions in the questionnaire. Based on factor analysis and reliability and validity testing, the 16-item scale (the ESSA) with five factors showed adequate to good internal consistency, 2-week test-retest reliability, and satisfactory concurrent and predictive validity. Its factor structure was further demonstrated in the main survey with a confirmatory factor analysis illustrating a good fit of the proposed model based on a confirmatory factor analysis. The reliabilities of other scales and questions were also adequate to be used in this study. The main survey was subsequently conducted with a sample of 1627 secondary school (grades 7-12) students to examine the influencing factors of educational stress and its associations with mental health outcomes, including depression, happiness and suicidal behaviours. A wide range of individual, family, school and peer factors were found to have a significant association with the total ESSA and subscale scores. Most of the strong factors for academic stress were school or study-related, including rural school location, low school connectedness, perceived poor academic grades and frequent emotional conflicts with teachers and peers. Unexpectedly, family and parental factors, such as parental bonding, family connectedness and conflicts with parents were found to have little or no association with educational stress. Educational stress was the most predictive variable for depression, but was not strongly associated with happiness. It had a strong association with suicide ideation but not with suicide attempts. Among five subscales of the ESSA, ‘Study despondency’ score had the strongest associations with these mental health measures. Surprising, two subscales, ‘Self-expectation’ and ‘Worry about grades’ showed a protective effect on suicidal behaviours. An additional analysis revealed that although academic pressure was the most commonly reported reason for suicidal thinking, the occurrence of problems in peer relationships such as peer teasing and bullying, and romantic problems had a much stronger relationship with actual attempts. This study provides some insights into the nature and health implications of educational stress among Chinese adolescents. Findings in this study suggest that interventions on educational stress should focus on school environment and academic factors. Intervention programs focused on educational stress may have a high impact on the prevalence of common mental disorders such as depression. Efforts to increase perceived happiness however should cover a wider range of individual, family and school factors. The importance of healthy peer relationships should be adequately emphasised in suicide prevention. In addition, the newly developed scale (the ESSA) demonstrates sound psychometric properties and is expected to be used in future research into academic-related stress among secondary school adolescents.

An exploratory study to examine the phenomenon and practice of ambulance ramping at hospitals within the Queensland Health Southern Districts and the Queensland Ambulance Service

Background: Ambulance Ramping, defined anecdotally as a practice where patients brought to emergency departments by ambulance experience delays to admission, has become more frequent in Australian emergency departments over the last few years. Previous research has shown a link between emergency department overcrowding, ambulance diversion and adverse outcomes for patients. However, there is very little research about Ambulance Ramping. The literature has no consistent definition of Ambulance Ramping, no description of how it is managed, and limited research on the effects it has on patient and service delivery outcomes...

Respiratory health effects of diesel particulate matter

Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.

Nanoparticles in European cities and associated health impacts

Atmospheric nanoparticles are one of those pollutants currently unregulated through ambient air quality standards. The aim of this chapter is to assess the environmental and health impacts of atmospheric nanoparticles in European environments. The chapter begins with the conventional information on the origin of atmospheric nanoparticles, followed by their physical and chemical characteristics. A brief overview of recently published review articles on this topic is then presented to guide those readers interested in exploring any specific aspect of nanoparticles in greater detail. A further section reports a summary of recently published studies on atmospheric nanoparticles in European cities. This covers a total of about 45 sampling locations in 30 different cities within 15 European countries for quantifying levels of roadside and urban background particle number concentrations (PNCs). Average PNCs at roadside and urban background sites were found to be 3.82±3.25 ×104 cm–3 and 1.63±0.82 ×104 cm–3, respectively, giving a roadside to background PNC ratio of ~2.4. Engineered nanoparticles are one of the key emerging categories of airborne nanoparticles, especially for the indoor environments. Their ambient concentrations may increase in future due to widespread use of nanotechnology integrated products. Evaluation of their sources and probable impacts on air quality and human health are briefly discussed in the following section. Respiratory deposition doses received by the public exposed to roadside PNCs in numerous European locations are then estimated. These were found to be in the 1.17–7.56 1010 h–1 range over the studied roadside European locations. The following section discusses the potential framework for airborne nanoparticle regulations in Europe and, in addition, the existing control measures to limit nanoparticle emissions at source. The chapter finally concludes with a synthesis of the topic areas covered and highlights important areas for further work.

The "free-factor" impact on value in health services

Purpose - This paper seeks to understand the impact of financial cost on customer value in health prevention services by comparing free government services with private fee-charging providers. This is important as there is a common belief that a free health service is of lower quality and thus lower value than a paid service. However there is no evidence to verify this notion. Design / Methodology / Approach - A large-scale online survey was administered nationwide to Australian women. The respondents were asked about the functional and emotional value derived from their service experiences. Findings - Structural equation modelling (SEM) revealed non significant relationships between fee/free services and functional and emotional value (FV/EV). The non-significant relationship with FV is contrary to the theory of price quality relationship in services. This could be attributed to consumer perceptions that the technical quality of health professionals is comparable across free and paid services. The non-significant relationship with EV could be explained by the indicators used to reflect EV. These indicators were reflective of breast screening behaviour, not breast screening services. Subsequently, it may be posited that the act of having a breast screen is sufficient for consumers to derive emotional value, regardless of the financial cost. Originality / Value - This research fills an important gap in the literature by investigating the impact of financial cost on a service that consumers use proactively(prevention), rather than reactively (treatment). Insights are provided into the impact of cost on customer value in preventive health services, which are valuable to social marketing academics, health practitioners, and governments

What would it take to optimise young people’s sexual health? A conversational journey with youth workers

Marginalised young people have been consistently identified as a high risk group in relation to sexual health. This research, undertaken through the Youth Affairs Network of Queensland, seeks to explore impacts on youth workers’ ability to provide effective interventions around sexual health? What knowledge,skills, resources, value and ethics, training and support is available to youth workers? What do youth workers identify that they need and what workforce development strategies are recommended to enable the youth sector to respond more effectively? This project report provides a snapshot and introduction to the key themes raised by youth workers and other key stakeholders in Queensland Australia.

Patients undergoing subacute rehabilitation have accurate expectations of their health-related quality of life at discharge

Background Expectations held by patients and health professionals may affect treatment choices and participation (by both patients and health professionals) in therapeutic interventions in contemporary patient-centered healthcare environments. If patients in rehabilitation settings overestimate their discharge health-related quality of life, they may become despondent as their progress falls short of their expectations. On the other hand, underestimating their discharge health-related quality of life may lead to a lack of motivation to participate in therapies if they do not perceive likely benefit. There is a scarcity of empirical evidence evaluating whether patients' expectations of future health states are accurate. The purpose of this study is to evaluate the accuracy with which older patients admitted for subacute in-hospital rehabilitation can anticipate their discharge health-related quality of life. Methods A prospective longitudinal cohort investigation of agreement between patients' anticipated discharge health-related quality of life (as reported on the EQ-5D instrument at admission to a rehabilitation unit) and their actual self-reported health-related quality of life at the time of discharge from this unit was undertaken. The mini-mental state examination was used as an indicator of patients' cognitive ability. Results Overall, 232(85%) patients had all assessment data completed and were included in analysis. Kappa scores ranged from 0.42-0.68 across the five EQ-5D domains and two patient cognition groups. The percentage of exact correct matches within each domain ranged from 69% to 85% across domains and cognition groups. Overall 40% of participants in each cognition group correctly anticipated all of their self-reported discharge EQ-5D domain responses. Conclusions Patients admitted for subacute in-hospital rehabilitation were able to anticipate the discharge health-related quality of life on the EQ-5D instrument with a moderate level of accuracy. This finding adds to the foundational empirical work supporting joint treatment decision making and patient-centered models of care during rehabilitation following acute illness or injury. Accurate patient expectations of the impact of treatment (or disease progression) on future health-related related quality of life is likely to allow patients and health professionals to successfully target interventions to priority areas where meaningful gains can be achieved.

Weight bias on psychological and physical health

It is a round table discussion article. "Weight bias refers to negative weight-related attitudes and beliefs, expressed in a range of forms towards individuals who are overweight or obese. Consequences of weight bias could be very significant to the individuals which may predispose them to additional weight gain. This brief literature review discusses the concept of weight bias and its impact on psychological and physical health on overweight and obese individuals..."

Factors influencing health behaviours of younger women after menopause-inducing cancer treatment

Objective To investigate the health promotion and risk reduction behaviors of younger women previously treated for cancer. Design and Sample Guided by the Precede-Proceed framework, a mixed-method descriptive investigation of the health behaviors of younger women with cancer treatment-induced menopause in one health jurisdiction in Australia was undertaken. Measures This article reports the results of the qualitative interview component of the study. Results Of the 85 women who responded to surveys that quantified their health behaviors, 22 consented to interviews that explored how and why these behaviors might occur. Conclusions Several predisposing, enabling and reinforcing factors that influenced participants will or ability to engage with health-promoting behaviors after cancer treatment were identified in the interviews. These include entrenched precancer diagnosis health behaviors, the disabilities resulting from cancer treatments, perceptions of risk, focused intervention by health professionals and the nature of participants social support. The results indicate a need for flexibility when planning public health initiatives to prepare this cohort for a healthy life after cancer, which accounts for their developmental, knowledge and posttreatment needs.