Pre-service Physical Education teachers and concerns regarding their ability to successfully facilitate school-based physical activity promotion strategies

Regular physical activity (PA) in youth has numerous immediate and long-term health benefits. With several studies indicating low levels of youth PA globally, schools settings have become increasingly critical settings for youth health promotion strategies. The role of physical education (PE) teachers has long been considered central to the facilitation of such strategies. However, PE teachers have a selfreported lack of knowledge, skills, understanding, and competence to successfully implement these strategies. Tertiary education programs are fundamental to adequately preparing, and shaping the attitudes and philosophies of future PE teachers towards their involvement within these programs. The aim of this investigation was to explore the beliefs and perceptions of future secondary school PE teachers, regarding their potential roles in future school-based programs designed to promote student PA. Fifty-seven (21 males and 36 females) pre-service PE teachers completed a series of open-ended survey questions concerning their perceptions towards participating in school-based PA promotion programs both as preservice during practicum, and prospectively as practising teachers. Responses were analysed thematically. Participants responded both positively and enthusiastically to both questions. Concerns regarding time, and the intention or expectation to participate in such programs were also key themes for pre-service and practicing teacher participation respectively. Critically in this study, participants did not identify any limitations which may impact upon their ability to successfully promote youth PA in school settings. This may indicate that participants have misconceptions regarding their ability to fulfil this role, or conversely, the deficiency of current PE teachers regarding school-based PA promotion has been recognised by the tertiary institution, and addressed to adequately prepare its students. School-based PA promotion is an integral element of pre-service PE teacher education, and ongoing professional development of practicing PE teachers. This trend is expected to continue in the future, in order to address ongoing public health concerns.

Something’s coming, something good: Identifying TPACK competence in pre-service teachers’ analyses of learning objects

There is a song at the beginning of the musical, West Side Story, where the character Tony sings that “something’s coming, something good.” The song is an anthem of optimism, brimming with promise. This paper is about the long-held promise of information and communication technology (ICT) to transform teaching and learning, to modernise the learning environment of the classroom, and to create a new digital pedagogy. But much of our experience to date in the schooling sector tells more of resistance and reaction than revolution, of more of the same but with a computer in the corner and of ICT activities as unwelcome time-fillers/time-wasters. Recently, a group of pre-service teachers in a postgraduate primary education degree in an Australian university were introduced to learning objects in an ICT immersion program. Their analyses and related responses, as recorded in online journals, have here been interpreted in terms of TPACK (Technological Pedagogical and Content Knowledge). Against contemporary observation, these students generally displayed high levels of competence and highly positive dispositions of students to the integration of ICT in their future classrooms. In short, they displayed the same optimism and confidence as the fictional “Tony” in believing that something good was coming.

Rethinking the literacy capabilities of pre-service primary teachers in testing times

As a group of committed literacy teacher educators from five universities across three Australian states, the authors bring professional critique to the problematic issue of what counts in current and possible future measures of pre-service teachers’ literacy capacity. In times when normalising models of literacy assessment ignore innovative developments in technologies, we provide an example of what is happening at the ‘chalk-face’ of literacy teacher education. This paper describes a study that demonstrates how responsible alignment of teacher accreditation requirements with a scholarly impetus to incorporate digital literacies to prepare pre-service teachers will help address changing educational needs and practices (AITSL 2012; Gillen & Barton 2010; Hattie 2003; Johnson, Smith, Willis, Levine & Haywood 2011; Klein 2006; Masny & Cole 2012; OECD 2011).

Integrating collaborative filtering and matching-based search for product recommendations

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user’s query are retrieved and recommended. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of the products in which the target user’s neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAgQuery technique uses the attributes of the products that the user’s neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.

Bending properties of Ag nanowires with pre-existing surface defects

Materials used in the engineering always contain imperfections or defects which significantly affect their performances. Based on the large-scale molecular dynamics simulation and the Euler–Bernoulli beam theory, the influence from different pre-existing surface defects on the bending properties of Ag nanowires (NWs) is studied in this paper. It is found that the nonlinear-elastic deformation, as well as the flexural rigidity of the NW is insensitive to different surface defects for the studied defects in this paper. On the contrary, an evident decrease of the yield strength is observed due to the existence of defects. In-depth inspection of the deformation process reveals that, at the onset of plastic deformation, dislocation embryos initiate from the locations of surface defects, and the plastic deformation is dominated by the nucleation and propagation of partial dislocations under the considered temperature. Particularly, the generation of stair-rod partial dislocations and Lomer–Cottrell lock are normally observed for both perfect and defected NWs. The generation of these structures has thwarted attempts of the NW to an early yielding, which leads to the phenomenon that more defects does not necessarily mean a lower critical force.

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Lane filtering and situation awareness in motorcyclists : an on-road proof of concept study

In Victoria, as in other jurisdictions, there is very little research on the potential risks and benefits of lane filtering by motorcyclists, particularly from a road safety perspective. This on-road proof of concept study aimed to investigate whether and how lane filtering influences motorcycle rider situation awareness at intersections and to address factors that need to be considered for the design of a larger study in this area. Situation awareness refers to road users’ understanding of ‘what is going on’ around them and is a critical commodity for safe performance. Twenty-five experienced motorcyclists rode their own instrumented motorcycle around an urban test route in Melbourne whilst providing verbal protocols. Lane filtering occurred in 27% of 43 possible instances in which there were one or more vehicles in the traffic queue and the traffic lights were red on approach to the intersection. A network analysis procedure, based on the verbal protocols provided by motorcyclists, was used to identify differences in motorcyclist situation awareness between filtering and non-filtering events. Although similarities in situation awareness across filtering and nonfiltering motorcyclists were found, the analysis revealed some differences. For example, filtering motorcyclists placed more emphasis on the timing of the traffic light sequence and on their own actions when moving to the front of the traffic queue, whilst non-filtering motorcyclists paid greater attention to traffic moving through the intersection and approaching from behind. Based on the results of this study, the paper discusses some methodological and theoretical issues to be addressed in a larger study comparing situation awareness between filtering and non-filtering motorcyclists.

A pre-post evaluation of an ambulatory nutrition support service for malnourished patients post hospital discharge: a pilot study

Introduction Malnutrition is common among hospitalised patients, with poor follow-up of nutrition support post-discharge. Published studies on the efficacy of ambulatory nutrition support (ANS) for malnourished patients post-discharge are scarce. The aims of this study were to evaluate the rate of dietetics follow-up of malnourished patients post-discharge, before (2008) and after (2010) implementation of a new ANS service, and to evaluate nutritional outcomes post-implementation. Materials and Methods Consecutive samples of 261 (2008) and 163 (2010) adult inpatients referred to dietetics and assessed as malnourished using Subjective Global Assessment (SGA) were enrolled. All subjects received inpatient nutrition intervention and dietetic outpatient clinic follow-up appointments. For the 2010 cohort, ANS was initiated to provide telephone follow-up and home visits for patients who failed to attend the outpatient clinic. Subjective Global Assessment, body weight, quality of life (EQ-5D VAS) and handgrip strength were measured at baseline and five months post-discharge. Paired t-test was used to compare pre- and post-intervention results. Results In 2008, only 15% of patients returned for follow-up with a dietitian within four months post-discharge. After implementation of ANS in 2010, the follow-up rate was 100%. Mean weight improved from 44.0 ± 8.5kg to 46.3 ± 9.6kg, EQ-5D VAS from 61.2 ± 19.8 to 71.6 ± 17.4 and handgrip strength from 15.1 ± 7.1 kg force to 17.5 ± 8.5 kg force; p<0.001 for all. Seventy-four percent of patients improved in SGA score. Conclusion Ambulatory nutrition support resulted in significant improvements in follow-up rate, nutritional status and quality of life of malnourished patients post-discharge.

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals

Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions

Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

A pre-clinical functional assessment of an acellular scaffold intended for the treatment of hard-to-heal wounds

Dermal wound healing is a biochemical and cellular process critical to life. While the majority of the population will only ever experience successful wound healing outcomes, some 1-3 % of those aged over 65 years will experience wound healing delay or perpetuation. These hard-to-heal wounds are comprised of degraded and dysfunctional extracellular matrix, yet the integrity of this structure is critical in the processes of normal wound healing. As such, extracellular matrix replacements have been devised that can replace dysfunctional extracellular matrix in hard-to-heal wounds with the aim of restoring normal wound healing processes. Here we evaluated a novel synthetic matrix protein for its ability to act as an acellular scaffold that can replace dysfunctional extracellular matrix. In this regard the synthetic protein demonstrated an ability to rapidly adsorb to the dermal surface, permit cell attachment and facilitate the cellular functions essential to wound healing. When applied to deep partial thickness wounds in a porcine animal model the matrix protein also demonstrated the ability to reduce wound duration. These data provide evidence that the synthetic matrix protein has the ability to function as an acellular scaffold for wound healing purposes.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.