The psychological and economic factors that influence energy consumption habits of low-income earners

Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?

Performance profiling for predictive train schedules

In this article an alternate sensitivity analysis is proposed for train schedules. It characterises the schedules robustness or lack thereof and provides unique profiles of performance for different sources of delay and for different values of delay. An approach like this is necessary because train schedules are only a prediction of what will actually happen. They can perform poorly with respect to a variety of performance metrics, when deviations and other delays occur, if for instance they can even be implemented, and as originally intended. The information provided by this analytical approach is beneficial because it can be used as part of a proactive scheduling approach to alter a schedule in advance or to identify suitable courses of action for specific “bad behaviour”. Furthermore this information may be used to quantify the cost of delay. The effect of sectional running time (SRT) deviations and additional dwell time in particular were quantified for three railway schedule performance measures. The key features of this approach were demonstrated in a case study.

Machine learning for activity recognition : hip versus wrist data

Problem addressed Wrist-worn accelerometers are associated with greater compliance. However, validated algorithms for predicting activity type from wrist-worn accelerometer data are lacking. This study compared the activity recognition rates of an activity classifier trained on acceleration signal collected on the wrist and hip. Methodology 52 children and adolescents (mean age 13.7 +/- 3.1 year) completed 12 activity trials that were categorized into 7 activity classes: lying down, sitting, standing, walking, running, basketball, and dancing. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the right hip and the non-dominant wrist. Features were extracted from 10-s windows and inputted into a regularized logistic regression model using R (Glmnet + L1). Results Classification accuracy for the hip and wrist was 91.0% +/- 3.1% and 88.4% +/- 3.0%, respectively. The hip model exhibited excellent classification accuracy for sitting (91.3%), standing (95.8%), walking (95.8%), and running (96.8%); acceptable classification accuracy for lying down (88.3%) and basketball (81.9%); and modest accuracy for dance (64.1%). The wrist model exhibited excellent classification accuracy for sitting (93.0%), standing (91.7%), and walking (95.8%); acceptable classification accuracy for basketball (86.0%); and modest accuracy for running (78.8%), lying down (74.6%) and dance (69.4%). Potential Impact Both the hip and wrist algorithms achieved acceptable classification accuracy, allowing researchers to use either placement for activity recognition.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Youth off the Streets "Our Place, Walgett Youth and Young Families Project" Project Evaluation.

The Project: • YOTS is a major youth specific agency established in 1991. It is a non-denominational, non-discriminatory and not-for-profit organisation, providing a wide range of services and offering a full continuum of care. It seeks to build on the strengths and positive aspects of marginalised young people and communities. • The 'Our Place, Walgett Youth and Young Families Project' further develops an existing YOTS capacity to provide services to Aboriginal young people. • The project adopted an action-research and community development model in which YOTS worked in partnership with the Youth Sub-committee of the Walgett Interagency. • Specific goals/objectives of the program were to: Coordinate youth and young family activities in partnership with local services and the community to build self-esteem, pride, resilience, motivation and skills; Contribute to the prevention and reduction of homelessness, unstable and unsafe housing and disruptive mobility (Walgett/Redfern) in youth and young families; Increase and improve collaborative engagement between youth and family focused services; and, research, adapt and implement Australian and international best-practice homelessness prevention/reduction initiatives to contribute to new models of practice relevant to rural and regional areas. • The project centred around an out-reach model that focused on providing a safe space with relevant structured activities coordinated by YOTS youth and family workers. Through community and service provider consultation, it was proposed that local services could coordinate strategies and activities and run them, where possible, from the centre, providing ease of access in a safe and supportive context. • Specific activities included: Implementing regular meetings with the stakeholders and community representatives; Developing a Terms of Reference for YOTS presence in the Walgett community; Undertaking a community consultation prior to finalising program activities; Implementing a range of recreational activities (sports, music, arts and crafts) early on in the activity; Implementing young family support initiatives; implementing a volunteering program, including volunteer support to young families through intergenerational volunteering; running a series of Culture and Healing Camps in partnership with local Elders and other services; Running a series of Music Camps; Providing alternative education support and referrals in partnership with local schools; Researching, identifying and adapting other best-practice models.

Not drowning, (hand)waving? Molecular phylogenetics, biogeography and evolutionary tempo of the ‘Gondwanan’ midge Stictocladius Edwards (Diptera: Chironomidae)

Many insect clades, especially within the Diptera (true flies), have been considered classically ‘Gondwanan’, with an inference that distributions derive from vicariance of the southern continents. Assessing the role that vicariance has played in the evolution of austral taxa requires testing the location and tempo of diversification and speciation against the well-established predictions of fragmentation of the ancient super-continent. Several early (anecdotal) hypotheses that current austral distributions originate from the breakup of Gondwana derive from studies of taxa within the family Chironomidae (non-biting midges). With the advent of molecular phylogenetics and biogeographic analytical software, these studies have been revisited and expanded to test such conclusions better. Here we studied the midge genus Stictocladius Edwards, from the subfamily Orthocladiinae, which contains austral-distributed clades that match vicariance-based expectations. We resolve several issues of systematic relationships among morphological species and reveal cryptic diversity within many taxa. Time-calibrated phylogenetic relationships among taxa accorded partially with the predicted tempo from geology. For these apparently vagile insects, vicariance-dated patterns persist for South America and Australia. However, as often found, divergence time estimates for New Zealand at c. 50 mya post-date separation of Zealandia from Antarctica and the remainder of Gondwana, but predate the proposed Oligocene ‘drowning’ of these islands. We detail other such ‘anomalous’ dates and suggest a single common explanation rather than stochastic processes. This could involve synchronous establishment following recovery from ‘drowning’ and/or deleteriously warming associated with the mid-Eocene climatic optimum (hence ‘waving’, which refers to cycles of drowning events) plus new availability of topography providing of cool running waters, or all these factors in combination. Alternatively a vicariance explanation remains available, given the uncertain duration of connectivity of Zealandia to Australia–Antarctic–South America via the Lord Howe and Norfolk ridges into the Eocene.

A framework for people capability enhancement to support sustainable facility management practices

Spanning over a considerable length of time, facility management is a key phase in the development cycle of built assets. Therefore facility managers are in a commanding position to maximise the potential of sustainability through the operation, maintenance and upgrade of built facilities leading to decommission and deconstruction. Sustainability endeavours in facility management practices will not only contribute to reducing energy consumption, waste and running costs, but also help improve organisational productivity, financial returns and community standing of the organisation. At the forefront facing sustainability challenge, facility manager should be empowered with the necessary knowledge and capabilities. However, literature studies show a gap between the current level of awareness and the specific knowledge and necessary skills required to pursue sustainability in the profession. People capability is considered as the key enabler in managing the sustainability agenda as well as being central to the improvement of competency and innovation in an organization. This paper aims to identify the critical factors for enhancing people capabilities in promoting the sustainability agenda in facility management practices. Starting with a total of 60 factors identified through literature review, the authors conducted a questionnaire survey to assess the perceived importance of these factors. The findings reveal 23 critical factors as significantly important. They form the basis of a mechanism framework developed to equip facility managers with the right knowledge, to continue education and training and to develop new mind-sets to enhance the implementation of sustainability measures in FM practices.

Long-tailed bats' use of a Pinus radiata stand in Kinleith Forest : Recommendations for monitoring

Targeted monitoring of threatened species within plantations is becoming more important due to forest certification programmes’ requirement to consider protection of threatened species, and to increase knowledge of the distribution of species. To determine patterns of long-tailed bat (Chalinolobus tuberculatus) activity in different habitat structures, with the aim of improving the likelihood of detection by targeting monitoring, we monitored one stand of 26 year-old Pinus radiata over seven months between December 2007 and June 2008 in Kinleith Forest, an exotic plantation forest centred around Tokoroa, South Waikato, New Zealand. Activity was determined by acoustic recording equipment, which is able to detect and record bats’ echolocation calls. We monitored activity from sunset to sunrise along a road through the stand, along stand edges, and in the interior of the stand. Bats were recorded on 80% of the 35 nights monitored. All activity throughout the monitoring period was detected on the edge of the stand or along the road. No bats were detected within the interior of the stand. Bat activity was highest along the road through the stand (40.4% of all passes), followed by an edge with stream running alongside (35.2%), along the road within a skidsite (19.8%), and along an edge without a stream (4.6%). There was a significant positive relationship between bat pass rate (bat passes h-1) and the feeding buzz rate (feeding buzzes h-1) indicating that bat activity was associated with feeding and not just commuting. Bat feeding activity was also highest along the road through the stand (59.2% of feeding buzzes), followed by the road within the skidsite (30.6%), and along the stream-side edge (10.2%). No feeding buzzes were recorded in either the interior or along the edge without the stream. Differences in overall feeding activity were significant only between the road and edge and between edges with and without a stream. Bat activity was detected each month and always by the second night of monitoring, and in this stand was highest during April. We recommend targeted monitoring for long-tailed bats be focused on road-side and stand edge habitat, and along streams, and that monitoring take place for at least three nights to maximise probability of detection.

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Do we need a law to help people try experimental drugs?

People with life-threatening or incurable diseases may be willing to try experimental drugs and unproven treatments, but they face the risk of exploitation. Is the law the best avenue to ensure that they are protected while medical innovation is encouraged? Protection of vulnerable people is a thread running through many laws, in Australia and elsewhere. In medical law, for instance, children and people with impaired decision-making capacity warrant special attention. But what of the ordinary person diagnosed with a life-threatening disease? Such people are vulnerable to harm and potential exploitation when they seek access to innovative, experimental or unproven treatments that depart from the existing range of accepted medicine.

Voluntary exercise decreases atherosclerosis in nephrectomised ApoE knockout mice

Cardiovascular disease is the main cause of morbidity and mortality in patients with kidney disease. The effectiveness of exercise for cardiovascular disease that is accelerated by the presence of chronic kidney disease remains unknown. The present study utilized apolipoprotein E knockout mice with 5/6 nephrectomy as a model of combined kidney disease and cardiovascular disease to investigate the effect of exercise on aortic plaque formation, vascular function and systemic inflammation. Animals were randomly assigned to nephrectomy or control and then to either voluntary wheel running exercise or sedentary. Following 12-weeks, aortic plaque area was significantly (p<0.05, d=1.2) lower in exercising nephrectomised mice compared to sedentary nephrectomised mice. There was a strong, negative correlation between average distance run each week and plaque area in nephrectomised and control mice (r=–0.76, p=0.048 and r=–0.73, p=0.062; respectively). In vitro aortic contraction and endothelial-independent and endothelial-dependent relaxation were not influenced by exercise (p>0.05). Nephrectomy increased IL-6 and TNF-α concentrations compared with control mice (p<0.001 and p<0.05, respectively), while levels of IL-10, MCP-1 and MIP-1α were not significantly influenced by nephrectomy or voluntary exercise (p>0.05). Exercise was an effective non-pharmacologic approach to slow cardiovascular disease in the presence of kidney disease in the apolipoprotein E knockout mouse.

Watermarking capacity control for dynamic payload embedding

Despite significant improvements in capacity-distortion performance, a computationally efficient capacity control is still lacking in the recent watermarking schemes. In this paper, we propose an efficient capacity control framework to substantiate the notion of watermarking capacity control to be the process of maintaining “acceptable” distortion and running time, while attaining the required capacity. The necessary analysis and experimental results on the capacity control are reported to address practical aspects of the watermarking capacity problem, in dynamic (size) payload embedding.

Vote as you go : Blending interfaces for community engagement into the urban space

This paper presents a series of studies on situated interfaces for community engagement. Firstly, we identify five recurring design challenges as well as four common strategies used to overcome them. We then assess the effectiveness of these strategies through field studies with public polling interfaces. We developed two very different polling interfaces in the form of (1) a web application running on an iPad mounted on a stand, allowing one vote at a time, and (2) a playful full-body interaction application for a large urban screen allowing concurrent participation. We deployed both interfaces in an urban precinct with high pedestrian traffic and equipped with a large urban screen. Analysing discoverability and learnability of each scenario, we derive insights regarding effective ways of blending community engagement interfaces into the built environment, while attracting the attention of passers-by and communicating the results of civic participation.

A new approach to the cloud-based heterogeneous MapReduce placement problem

Guaranteeing Quality of Service (QoS) with minimum computation cost is the most important objective of cloud-based MapReduce computations. Minimizing the total computation cost of cloud-based MapReduce computations is done through MapReduce placement optimization. MapReduce placement optimization approaches can be classified into two categories: homogeneous MapReduce placement optimization and heterogeneous MapReduce placement optimization. It is generally believed that heterogeneous MapReduce placement optimization is more effective than homogeneous MapReduce placement optimization in reducing the total running cost of cloud-based MapReduce computations. This paper proposes a new approach to the heterogeneous MapReduce placement optimization problem. In this new approach, the heterogeneous MapReduce placement optimization problem is transformed into a constrained combinatorial optimization problem and is solved by an innovative constructive algorithm. Experimental results show that the running cost of the cloud-based MapReduce computation platform using this new approach is 24:3%-44:0% lower than that using the most popular homogeneous MapReduce placement approach, and 2:0%-36:2% lower than that using the heterogeneous MapReduce placement approach not considering the spare resources from the existing MapReduce computations. The experimental results have also demonstrated the good scalability of this new approach.

Antioxidants in Athlete's Basic Nutrition: Considerations towards a Guideline for the Intake of Vitamin C and Vitamin E

Antioxidants in acute physical exercise and exercise training remain a hot topic in sport nutrition, exercise physiology and biology, in general (Jackson, 2008; Margaritis and Rousseau, 2008; Gomez-Cabrera et al., 2012; Nikolaidis et al., 2012). During the past few decades, antioxidants have received attention predominantly as a nutritional strategy for preventing or minimising detrimental effects of reactive oxygen and nitrogen species (RONS), which are generated during and after strenuous exercise (Jackson, 2008, 2009; Powers and Jackson, 2008). Antioxidant supplementation has become a common practice among athletes as a means to (theoretically) reduce oxidative stress, promote recovery and enhance performance (Peternelj and Coombes, 2011). However, until now, requirements of antioxidant micronutrients and antioxidant compounds for athletes training for and competing in different sport events, including marathon running, triathlon races or team sport events involving repeated sprinting, have not been determined sufficiently (Williams et al., 2006; Margaritis and Rousseau, 2008). Crucially, evidence has been emerging that higher dosages of antioxidants may not necessarily be beneficial in this context, but can also elicit detrimental effects by interfering with performance-enhancing (Gomez-Cabrera et al., 2008) and health-promoting training adaptations (Ristow et al., 2009). As originally postulated in a pioneering study on exercise-induced production of RONS by Davies et al. (1982) in the early 1980s, evidence has been increasing in recent years that RONS are not only damaging agents, but also act as signalling molecules for regulating muscle function (Reid, 2001; Jackson, 2008) and for initiating adaptive responses to exercise (Jackson, 2009; Powers et al., 2010). The recognition that antioxidants could, vice versa, interact with the signalling pathways underlying the responses to acute (and repeated) bouts of exercise has contributed important novel aspects to the continued discussion on antioxidant requirements for athletes. In view of the recent advances in this field, it is the aim of this report to examine the current knowledge of antioxidants, in particular of vitamins C and E, in the basic nutrition of athletes. While overviews on related topics including basic mechanisms of exercise-induced oxidative stress, redox biology, antioxidant defence systems and a summary of studies on antioxidant supplementation during exercise training are provided, this does not mean that this report is comprehensive. Several issues of the expanding and multidisciplinary field of antioxidants and exercise are covered elsewhere in this book and/or in the literature. Exemplarily, the reader is referred to reviews on oxidative stress (Konig et al., 2001; Vollaard et al., 2005; Knez et al., 2006; Powers and Jackson, 2008; Nikolaidis et al., 2012), redox-sensitive signalling and muscle function (Reid, 2001; Vollaard et al., 2005; Jackson, 2008; Ji, 2008; Powers and Jackson, 2008; Powers et al., 2010; Radak et al., 2013) and antioxidant supplementation (Williams et al., 2006; Peake et al., 2007; Peternelj and Coombes, 2011) in the context with exercise. Within the scope of the report, we rather aim to address the question regarding requirements of antioxidants, specifically vitamins C and E, during exercise training, draw conclusions and provide practical implications from the recent research.