Lysosomal secretion of Flightless I upon injury has the potential to alter inflammation

Intracellular Flightless I (Flii), a gelsolin family member, has been found to have roles modulating actin regulation, transcriptional regulation and inflammation. In vivo Flii can regulate wound healing responses. We have recently shown that a pool of Flii is secreted by fibroblasts and macrophages, cells typically found in wounds, and its secretion can be upregulated upon wounding. We show that secreted Flii can bind to the bacterial cell wall component lipopolysaccharide and has the potential to regulate inflammation. We now show that secreted Flii is present in both acute and chronic wound fluid.

The ethnographer as community manager : language translation and user negotiation

This article investigates the ethnographic methodological question of how the researcher observes objectively while being part of the problem they are observing. It uses a case study of ABC Pool to argue a cooperative approach that combines the roles of the ethnographer with that of a community manager who assists in constructing a true representation of the researched environment. By using reflexivity as a research tool, the ethnographer engages in a process to self-check their personal presumptions and prejudices, and to strengthen the constructed representation of the researched environment. This article also suggests combining management and expertise research from the social sciences with ethnography, to understand and engage with the research field participants more intimately - which, ultimately, assists in gathering and analysing richer qualitative data.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pairwise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighboring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools.

Of things in the dark, remembered

Excerpt: "To enter the shadow world cast by each installation of Moule is to enter the waking dream of the half remembered. Each object, in its own pool of light, connected to other objects by fields of the twilit, is evocative of some object from our waking world, but recast into that which cannot be and yet is here, palpably so - insistent. All that confronts us is so determinedly derived from some internal gesture and rendered into some partial-reality, without surety of line or contour to combat our internal world of meaning and sense."

Animating and sustaining niche social networks

Within the communicative space online Social Network Sites (SNS) afford, Niche Social Networks Sites (NSNS) have emerged around particular geographic, demographic or topic-based communities to provide what broader SNS do not: specified and targeted content for an engaged and interested community. Drawing on a research project developed at the Queensland University of Technology in conjunction with the Australian Smart Services Cooperative Research Centre that produced an NSNS based around Adventure Travel, this paper outlines the main drivers for community creation and sustainability within NSNS. The paper asks what factors motivate users to join and stay with these sites and what, if any, common patterns can be noted in their formation. It also outlines the main barriers to online participation and content creation in NSNS, and the similarities and differences in SNS and NSNS business models. Having built a community of 100 registered members, the staywild.com.au project was a living laboratory, enabling us to document the steps taken in producing a NSNS and cultivating and retaining active contributors. The paper incorporates observational analysis of user-generated content (UGC) and user profile submissions, statistical analysis of site usage, and findings from a survey of our membership pool in noting areas of success and of failure. In drawing on our project in this way we provide a template for future iterations of NSNS initiation and development across various other social settings: not only niche communities, but also the media and advertising with which they engage and interact. Positioned within the context of online user participation and UGC research, our paper concludes with a discussion of the ways in which the tools afforded by NSNS extend earlier understandings of online ‘communities of interest’. It also outlines the relevance of our research to larger questions about the diversity of the social media ecology.

Mycobacterium abscessus infection and potable water

Mycobacterium abscessus is a rapidly growing mycobacteria responsible for progressive pulmonary disease, soft tissue and wound infections, and can contaminate clinical specimens. Nontuberculous mycobacteria (NTM) are generally considered environmental organisms though M. abscessus has not featured frequently in environmental studies, particularly those examining potable water. In a study of Brisbane potable water, M. abscessus was isolate from ten different locations. The incidence of disease due to M. abscessus has been increasing in Queensland. Aim: To compare genotypically the M. abscessus isolates obtained from water to those obtained from human clinical specimens. Methods: From a study of Brisbane potable water between 2007 and 2009, ten isolates confirmed as M. abscessus were recovered. In addition, one strain was isolated from a rainwater tank of a patient with disease due to M. avium, and another from the swimming pool of a patient with M. intracellulare disease. A random sample of 74 clinical isolates referred to the QLD Mycobacterial reference laboratory during the same time period was available for comparison using repPCR strain typing (Diversilab). Results: The drinking water isolates formed two distinct strain patterns (A and B) that shared >90% similarity. The tankwater isolate (pattern C) shared >85% similarity with the potable water isolates, but the pool isolate (D) was distinctly different. Fifty-three clinical isolates clustered tightly (>95% similarity) with the Group A potable water isolates, 4 patients with Group B. Thirteen patient isolates clustered with the Rainwater tank isolate. One patient matched the pool isolate. There were a further 3 patient isolates that were unrelated to the water isolates. No differences were found between strain types in terms of geographic origin, gender, age, or site/type of infection. Conclusion: The high degree of similarity between strains of M. abscessus from potable water and strains causing infection in humans from the same area, strengthens the possibility that drinking water may be a source of infection in these patients.

Empirical study of interactions between knowledge management activities

Purpose – Recent knowledge management (KM) literature suggests that KM activities are not independent of each other, rather they interact with each other to form a process which receives input from both external and internal business environments, and then produces new knowledge for future utilisation. The purpose of this paper is to empirically investigate the relationships between KM activities within the construction business context in order to identify and map the pattern of their interactions. Design/methodology/approach – A questionnaire survey was administered to a sample of contracting organisations operating in Hong Kong to elicit opinions of construction professionals on the intensity of KM activities currently being executed by their organisations in order to facilitate knowledge capture, sharing and utilisation. More than 150 respondents from 99 organisations responded to the survey. Additionally, a total of 15 semi-structured interviews were undertaken to provide a unique perspective on many of the challenges facing local construction organisations when dealing with KM activities. Findings – Knowledge acquisition and utilisation play paramount roles in the development of the organisational knowledge asset. The higher the intensity of these two activities, the larger the organisational knowledge pool which, in turn, demands greater knowledge dissemination capacity. This dissemination capacity enables more active and intense responses to market changes and clients' needs, thus facilitating and stimulating acquisition and utilisation of new tacit knowledge, thus improving organisational business performance. Originality/value – Interactions between KM activities were empirically investigated, from a strategic perspective, in the construction business context.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pair wise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighbouring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighbouring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools. Comparison to probabilistic schemes shows that our combinatorial approach produces better connectivity with smaller key-chain sizes.

Cohort normalization based sparse representation for undersampled face recognition

Abstract. In recent years, sparse representation based classification(SRC) has received much attention in face recognition with multipletraining samples of each subject. However, it cannot be easily applied toa recognition task with insufficient training samples under uncontrolledenvironments. On the other hand, cohort normalization, as a way of mea-suring the degradation effect under challenging environments in relationto a pool of cohort samples, has been widely used in the area of biometricauthentication. In this paper, for the first time, we introduce cohort nor-malization to SRC-based face recognition with insufficient training sam-ples. Specifically, a user-specific cohort set is selected to normalize theraw residual, which is obtained from comparing the test sample with itssparse representations corresponding to the gallery subject, using poly-nomial regression. Experimental results on AR and FERET databases show that cohort normalization can bring SRC much robustness against various forms of degradation factors for undersampled face recognition.

Exit humidity of wet scrubbers for underground coal mines

A wet scrubber is a device used in underground coal mines for the exhaust treatment system of various internal combustion engines (generally diesel) primarily as a spark arrestor with a secondary function to remove pollutants from the exhaust gas. A pool of scrubbing liquid (generally water based) is used in conjunction with a Diesel Particulate Filter (DPF). Scrubbers are widely used in underground applications of diesel engines as their exhaust contains high concentration of harmful diesel particulate matter (DPM) and other pollutant gases. Currently the DPFs have to be replaced frequently because moisture output from the wet scrubber blocks the filter media and causes reduced capacity. This paper presents experimental and theoretical studies on the heat and mass transfer mechanisms of the exhaust flow both under and above the water surface, aiming at finding the cause and effects of the moisture reaching the filters and employing a solution to reduce the humidity and DPM output, and to prolong the change-out period of the DPF. By assuming a steady flow condition, heat transfer from the inlet exhaust gas balances energy required for the water evaporation. Hence the exit humidity will decrease with the increase of exit temperature. Experiments on a real scrubber are underway.

Prediction of age at menopause from assessment of ovarian reserve may be improved by using body mass index and smoking status

Objective: Menopause is the consequence of exhaustion of the ovarian follicular pool. AMH, an indirect hormonal marker of ovarian reserve, has been recently proposed as a predictor for age at menopause. Since BMI and smoking status are relevant independent factors associated with age at menopause we evaluated whether a model including all three of these variables could improve AMH-based prediction of age at menopause. Methods: In the present cohort study, participants were 375 eumenorrheic women aged 19–44 years and a sample of 2,635 Italian menopausal women. AMH values were obtained from the eumenorrheic women. Results: Regression analysis of the AMH data showed that a quadratic function of age provided a good description of these data plotted on a logarithmic scale, with a distribution of residual deviates that was not normal but showed significant leftskewness. Under the hypothesis that menopause can be predicted by AMH dropping below a critical threshold, a model predicting menopausal age was constructed from the AMH regression model and applied to the data on menopause. With the AMH threshold dependent on the covariates BMI and smoking status, the effects of these covariates were shown to be highly significant. Conclusions: In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMH-based prediction of age at menopause.

The determinants of demand for private health insurance under Medicare

Since the introduction of Medicare in 1984, the proportion of the Australian population with private health insurance has declined considerably. Insurance for health care consumption is compulsory for the public health sector but optional for the private health sector. In this paper, we explore a number of important issues in the demand for private health insurance in Australia. The socio-economic variables which influence demand are examined using a binary logic model. A number of simulations are performed to highlight the influence and relative importance of various characteristics such as age, income, health status and geographical location on demand. A number of important policy issues in the private health insurance market are highlighted. First, evidence is provided of adverse selection in the private health insurance pool, second, the notion of the wealthy uninsured is refuted, and finally it is confirmed that there are significant interstate differences in the demand for private health insurance.

Contrast water therapy and exercise induced muscle damage : a systematic review and meta-analysis

The aim of this systematic review was to examine the effect of Contrast Water Therapy (CWT) on recovery following exercise induced muscle damage. Controlled trials were identified from computerized literature searching and citation tracking performed up to February 2013. Eighteen trials met the inclusion criteria; all had a high risk of bias. Pooled data from 13 studies showed that CWT resulted in significantly greater improvements in muscle soreness at the five follow-up time points(<6, 24, 48, 72 and 96 hours) in comparison to passive recovery. Pooled data also showed that CWT significantly reduced muscle strength loss at each follow-up time (<6, 24, 48, 72 and 96 hours) in comparison to passive recovery. Despite comparing CWT to a large number of other recovery interventions, including cold water immersion, warm water immersion, compression, active recovery and stretching, there was little evidence for a superior treatment intervention. The current evidence base shows that CWT is superior to using passive recovery or rest after exercise; the magnitudes of these effects may be most relevant to an elite sporting population. There seems to be little difference in recovery outcome between CWT and other popular recovery interventions.

Speaker diarization : "who spoke when"

Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.