Swimming between the flags: A preliminary exploration of the influences on Australians’ intentions to swim between the flags at patrolled beaches

Swimming at patrolled beaches reduces the likelihood of drownings and near-drownings. The present study tested the theory of planned behaviour (TPB), with the addition of risk perceptions, in predicting people’s intentions to swim between the flags at patrolled beaches. We examined also the predictors of people’s willingness to swim [1] up to 10 metres and [2] more than 10 metres outside of the patrol flags. Participants (N = 526) completed measures of attitudes, subjective norm, perceived behavioural control (PBC), intentions/willingness, and both objective and subjective risk perceptions. Two weeks later, a sub-sample of participants reported on their beach swimming behaviour for the previous fortnight. Attitude and subjective norm predicted intentions to swim between and willingness to swim outside of the flags. Age and PBC influenced willingness to swim beyond the flags. Objective risk predicted willingness to swim beyond the flags (both distances) while subjective risk predicted willingness to swim up to 10 metres outside the flags. People’s intentions to swim between the flags were correlated with their behaviour at follow-up. This study provides a preliminary investigation into an important safety behaviour and identifies factors to target when promoting safe swimming behaviours to prevent drowning deaths on Australian beaches.

Phosphorylation of Exo1 modulates homologous recombination repair of DNA double-strand breaks

DNA double-strand break (DSB) repair via the homologous recombination pathway is a multi-stage process, which results in repair of the DSB without loss of genetic information or fidelity. One essential step in this process is the generation of extended single-stranded DNA (ssDNA) regions at the break site. This ssDNA serves to induce cell cycle checkpoints and is required for Rad51 mediated strand invasion of the sister chromatid. Here, we show that human Exonuclease 1 (Exo1) is required for the normal repair of DSBs by HR. Cells depleted of Exo1 show chromosomal instability and hypersensitivity to ionising radiation (IR) exposure. We find that Exo1 accumulates rapidly at DSBs and is required for the recruitment of RPA and Rad51 to sites of DSBs, suggesting a role for Exo1 in ssDNA generation. Interestingly, the phosphorylation of Exo1 by ATM appears to regulate the activity of Exo1 following resection, allowing optimal Rad51 loading and the completion of HR repair. These data establish a role for Exo1 in resection of DSBs in human cells, highlighting the critical requirement of Exo1 for DSB repair via HR and thus the maintenance of genomic stability.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.

ICU nurses' experiences and perspectives of caring for obstetric patients in intensive care: A qualitative study

Aims and objectives.  The aim of this study was to gain an understanding of the experiences and perspectives of intensive care nurses caring for critically ill obstetric patients. Background.  Current literature suggests critically ill obstetric patients need specialised, technically appropriate care to meet their specific needs with which many intensive care nurses are unfamiliar. Furthermore, there is little research and evidence to guide the care of this distinct patient group. Design.  This study used a descriptive qualitative design. Methods.  Two focus groups were used to collect data from 10 Australian intensive care units nurses in May 2007. Open-ended questions were used to guide the discussion. Latent content analysis was used to analyse the data set. Each interview lasted no longer than 60 minutes and was recorded using audio tape. The full interviews were transcribed prior to in-depth analysis to identify major themes. Results.  The themes identified from the focus group interviews were competence with knowledge and skills for managing obstetric patients in the intensive care unit, confidence in caring for obstetric patients admitted to the intensive care unit and acceptance of an expanded scope of practice perceived to include fundamental midwifery knowledge and skills. Conclusion.  The expressed lack of confidence and competence in meeting the obstetric and support needs of critically ill obstetric women indicates a clear need for greater assistance and education of intensive care nurses. This in turn may encourage critical care nurses to accept an expanded role of clinical practice in caring for critically ill obstetric patients. Relevance to clinical practice.  Recognition of the issues for nurses in successfully caring for obstetric patients admitted to an adult intensive care setting provides direction for designing education packages, ensuring specific carepaths and guidelines are in place and that support from a multidisciplinary team is available including midwifery staff.

Negative space and positive environment : mapping opportunities for urban resilience

Cities have long held a fascination for people – as they grow and develop, there is a desire to know and understand the intricate interplay of elements that makes cities ‘live’. In part, this is a need for even greater efficiency in urban centres, yet the underlying quest is for a sustainable urban form. In order to make sense of the complex entities that we recognise cities to be, they have been compared to buildings, organisms and more recently machines. However the search for better and more elegant urban centres is hardly new, healthier and more efficient settlements were the aim of Modernism’s rational sub-division of functions, which has been translated into horizontal distribution through zoning, or vertical organisation thought highrise developments. However both of these approaches have been found to be unsustainable, as too many resources are required to maintain this kind or urbanisation and social consequences of either horizontal or vertical isolation must also be considered. From being absolute consumers of resources, of energy and of technology, cities need to change, to become sustainable in order to be more resilient and more efficient in supporting culture, society as well as economy. Our urban centres need to be re-imagined, re-conceptualised and re-defined, to match our changing society. One approach is to re-examine the compartmentalised, mono-functional approach of urban Modernism and to begin to investigate cities like ecologies, where every element supports and incorporates another, fulfilling more than just one function. This manner of seeing the city suggests a framework to guide the re-mixing of urban settlements. Beginning to understand the relationships between supporting elements and the nature of the connecting ‘web’ offers an invitation to investigate the often ignored, remnant spaces of cities. This ‘negative space’ is the residual from which space and place are carved out in the Contemporary city, providing the link between elements of urban settlement. Like all successful ecosystems, cities need to evolve and change over time in order to effectively respond to different lifestyles, development in culture and society as well as to meet environmental challenges. This paper seeks to investigate the role that negative space could have in the reorganisation of the re-mixed city. The space ‘in-between’ is analysed as an opportunity for infill development or re-development which provides to the urban settlement the variety that is a pre-requisite for ecosystem resilience. An analysis of the urban form is suggested as an empirical tool to map the opportunities already present in the urban environment and negative space is evaluated as a key element in achieving a positive development able to distribute diverse environmental and social facilities in the city.

Identification of long intergenic region sequences involved in maize streak virus replication

The main cis-acting control regions for replication of the single-stranded DNA genome of maize streak virus (MSV) are believed to reside within an approximately 310 nt long intergenic region (LIR). However, neither the minimum LIR sequence required nor the sequence determinants of replication specificity have been determined experimentally. There are iterated sequences, or iterons, both within the conserved inverted-repeat sequences with the potential to form a stem-loop structure at the origin of virion-strand replication, and upstream of the rep gene TATA box (the rep-proximal iteron or RPI). Based on experimental analyses of similar iterons in viruses from other geminivirus genera and their proximity to known Rep-binding sites in the distantly related mastrevirus wheat dwarf virus, it has been hypothesized that the iterons may be Rep-binding and/or -recognition sequences. Here, a series of LIR deletion mutants was used to define the upper bounds of the LIR sequence required for replication. After identifying MSV strains and distinct mastreviruses with incompatible replication-specificity determinants (RSDs), LIR chimaeras were used to map the primary MSV RSD to a 67 nt sequence containing the RPI. Although the results generally support the prevailing hypothesis that MSV iterons are functional analogues of those found in other geminivirus genera, it is demonstrated that neither the inverted-repeat nor RPI sequences are absolute determinants of replication specificity. Moreover, widely divergent mastreviruses can trans-replicate one another. These results also suggest that sequences in the 67 nt region surrounding the RPI interact in a sequence-specific manner with those of the inverted repeat.

The effect of alcohol and drug consumption on academic performance : a treatment effect evaluation

It is often argued that consumption of alcohol, tobacco and drugs is detrimental to the cognitive abilities of teenagers. In order to disentangle a possible causal effect of these substances use from a self-selection bias, we control for pupils previous performance and for their previous rate of progression applying a DiDiD strategy. Using the NELS 1988 panel dataset, we find that the effects of alcohol and tobacco on test scores disappear once the selection bias is controlled for (this does not preclude long term detrimental effects). However, we find reliable evidence that heavy use of drugs (marijuana and cocaine) has direct detrimental effects on educational achievements. Hence, our results may have significant policy implications.

Graphene-like nano-sheets/36° LiTaO3 surface acoustic wave hydrogen gas sensor

Presented is the material and gas sensing properties of graphene-like nano-sheets deposited on 36° YX lithium tantalate (LiTaO3) surface acoustic wave (SAW) transducers. The graphene-like nano-sheets were characterized via scanning electron microscopy (SEM), atomic force microscopy(AFM)and X-ray photoelectron spectroscopy (XPS). The graphenelike nano-sheet/SAW sensors were exposed to different concentrations of hydrogen (H2) gas in a synthetic air at room temperature. The developed sensors exhibit good sensitivity towards low concentrations of H2 in ambient conditions, as well as excellent dynamic performance towards H2 at room temperature.

Synergies and goal conflicts for climate change policy and spatial planning

The purpose of this paper is to identify goal conflicts – both actual and potential – between climate and social policies in government strategies in response to the growing significance of climate change as a socioecological issue (IPCC 2007). Both social and climate policies are political responses to long-term societal trends related to capitalist development, industrialisation, and urbanisation (Koch, 2012). Both modify these processes through regulation, fiscal transfers and other measures, thereby affecting conditions for the other. This means that there are fields of tensions and synergies between social policy and climate change policy. Exploring these tensions and synergies is an increasingly important task for navigating genuinely sustainable development. Gough et al (2008) highlight three potential synergies between social and climate change policies: First, income redistribution – a traditional concern of social policy – can facilitate use of and enhance efficiency of carbon pricing. A second area of synergy is housing, transport, urban policies and community development, which all have potential to crucially contribute towards reducing carbon emissions. Finally, climate change mitigation will require substantial and rapid shifts in producer and consumer behaviour. Land use planning policy is a critical bridge between climate change and social policy that provides a means to explore the tensions and synergies that are evolving within this context. This paper will focus on spatial planning as an opportunity to develop strategies to adapt to climate change, and reviews the challenges of such change. Land use and spatial planning involve the allocation of land and the design and control of spatial patterns. Spatial planning is identified as being one of the most effective means of adapting settlements in response to climate change (Hurlimann and March, 2012). It provides the instrumental framework for adaptation (Meyer, et al., 2010) and operates as both a mechanism to achieve adaptation and a forum to negotiate priorities surrounding adaptation (Davoudi, et al., 2009). The acknowledged role of spatial planning in adaptation however has not translated into comparably significant consideration in planning literature (Davoudi, et al., 2009; Hurlimann and March, 2012). The discourse on adaptation specifically through spatial planning is described as ‘missing’ and ‘subordinate’ in national adaptation plans (Greiving and Fleischhauer, 2012),‘underrepresented’ (Roggema, et al., 2012)and ‘limited and disparate’ in planning literature (Davoudi, et al., 2009). Hurlimann and March (2012) suggest this may be due to limited experiences of adaptation in developed nations while Roggema et al. (2012) and Crane and Landis (2010) suggest it is because climate change is a wicked problem involving an unfamiliar problem, various frames of understanding and uncertain solutions. The potential for goal conflicts within this policy forum seem to outweigh the synergies. Yet, spatial planning will be a critical policy tool in the future to both protect and adapt communities to climate change.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions

In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.