Psychology students’ beliefs about integrating Complementary and Alternative Therapy (CAT) into their future psychology practice

We investigated whether belief-based differences exist between students who have strong and weak intentions to integrate complementary and alternative therapy (CAT) into future psychology practice by recommending CAT or specific CAT practitioners to clients. A cross-sectional methodology was used. Psychology undergraduate students (N = 106) participated in a paper-based questionnaire design to explore their underlying beliefs related to CAT integration. The study was undertaken at a major university in Queensland, Australia. The theory of planned behaviour belief-based framework guided the study. Multivariate analyses of variance examined the influence of behavioural, normative, and control beliefs on the strong and weak intention groups. A multiple regression analysis investigated the relative importance of these belief sets for predicting intentions. We found that clear differences emerged between strong and weak intenders on behavioural and normative beliefs, but not control beliefs. Strong intenders perceived the positive outcomes of integrating CAT, such as being able to offer clients a more holistic practice and having confidence in the practitioners/practices, as more likely to occur than weak intenders, and perceived the negative outcome of compromising my professional practice as less likely. Strong in-tenders were more likely than weak intenders to perceive that a range of important referents (e.g., clients) would think they should integrate CAT. Results of the regression analysis revealed the same pattern of results in that behavioural and normative beliefs, but not control beliefs, significantly predicted intentions. The findings from this study can be used to inform policy and educational initiatives that aim to encourage CAT use in psychology practice.

Inflammation, hepatic enzymes and resistance training in individuals with metabolic risk factors

AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.

Modeling as a means for making powerful ideas accessible to children at an early age

The SimCalc Vision and Contributions Advances in Mathematics Education 2013, pp 419-436 Modeling as a Means for Making Powerful Ideas Accessible to Children at an Early Age Richard Lesh, Lyn English, Serife Sevis, Chanda Riggs … show all 4 hide » Look Inside » Get Access Abstract In modern societies in the 21st century, significant changes have been occurring in the kinds of “mathematical thinking” that are needed outside of school. Even in the case of primary school children (grades K-2), children not only encounter situations where numbers refer to sets of discrete objects that can be counted. Numbers also are used to describe situations that involve continuous quantities (inches, feet, pounds, etc.), signed quantities, quantities that have both magnitude and direction, locations (coordinates, or ordinal quantities), transformations (actions), accumulating quantities, continually changing quantities, and other kinds of mathematical objects. Furthermore, if we ask, what kind of situations can children use numbers to describe? rather than restricting attention to situations where children should be able to calculate correctly, then this study shows that average ability children in grades K-2 are (and need to be) able to productively mathematize situations that involve far more than simple counts. Similarly, whereas nearly the entire K-16 mathematics curriculum is restricted to situations that can be mathematized using a single input-output rule going in one direction, even the lives of primary school children are filled with situations that involve several interacting actions—and which involve feedback loops, second-order effects, and issues such as maximization, minimization, or stabilizations (which, many years ago, needed to be postponed until students had been introduced to calculus). …This brief paper demonstrates that, if children’s stories are used to introduce simulations of “real life” problem solving situations, then average ability primary school children are quite capable of dealing productively with 60-minute problems that involve (a) many kinds of quantities in addition to “counts,” (b) integrated collections of concepts associated with a variety of textbook topic areas, (c) interactions among several different actors, and (d) issues such as maximization, minimization, and stabilization.

Inferencing design styles using Baysian Networks

Reasoning with uncertain knowledge and belief has long been recognized as an important research issue in Artificial Intelligence (AI). Several methodologies have been proposed in the past, including knowledge-based systems, fuzzy sets, and probability theory. The probabilistic approach became popular mainly due to a knowledge representation framework called Bayesian networks. Bayesian networks have earned reputation of being powerful tools for modeling complex problem involving uncertain knowledge. Uncertain knowledge exists in domains such as medicine, law, geographical information systems and design as it is difficult to retrieve all knowledge and experience from experts. In design domain, experts believe that design style is an intangible concept and that its knowledge is difficult to be presented in a formal way. The aim of the research is to find ways to represent design style knowledge in Bayesian net works. We showed that these networks can be used for diagnosis (inferences) and classification of design style. The furniture design style is selected as an example domain, however the method can be used for any other domain.

Variability in estimation of self-reported dietary intake data from elite athletes resulting from coding by different sports dietitians

A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.

Decentralized detector generation in cooperative intrusion detection system

We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.

Intermediaries and imaginaries in the cultural and creative industries

This paper conducts an historical and conceptual review of the idea of ‘cultural intermediaries’ and sets up a contrast between the cultural and creative industries. It draws on theorizations of ‘economic imaginaries’ and reconstructs the respective imaginaries of cultural and creative industries. It suggests that the former was organized around the culturalization of the economy and the second around the economization of culture. Nevertheless, there are complicities between them, not least in the contention that a new set of economic developments would redeem the traditional promises of culture.

Vibrational spectroscopy of natural cave mineral monetite CaHPO4 and the synthetic analog

Monetite is a phosphate mineral formed by the reaction of the chemicals in bat guano with calcite substrates and is commonly found in caves. The analog of the mineral monetite CaHPO4 has been synthesized and the Raman and infrared spectra of the natural monetite originating from the Murra-el-elevyn Cave, Eucla, Western Australia, compared. Monetite is characterized by a complex set of phosphate bands that arise because of two sets of pairs of phosphate units in the unit cell. Raman and infrared bands are assigned to HPO4(2-), OH stretching and bending vibrations. Infrared bands at 1346 and 1402 cm−1 are assigned to POH deformation modes. Vibrational spectroscopy confirms the presence of monetite in the cave system.

Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Experimental and modelling investigation of monolayer development with clustering

Standard differential equation–based models of collective cell behaviour, such as the logistic growth model, invoke a mean–field assumption which is equivalent to assuming that individuals within the population interact with each other in proportion to the average population density. Implementing such assumptions implies that the dynamics of the system are unaffected by spatial structure, such as the formation of patches or clusters within the population. Recent theoretical developments have introduced a class of models, known as moment dynamics models, which aim to account for the dynamics of individuals, pairs of individuals, triplets of individuals and so on. Such models enable us to describe the dynamics of populations with clustering, however, little progress has been made with regard to applying moment dynamics models to experimental data. Here, we report new experimental results describing the formation of a monolayer of cells using two different cell types: 3T3 fibroblast cells and MDA MB 231 breast cancer cells. Our analysis indicates that the 3T3 fibroblast cells are relatively motile and we observe that the 3T3 fibroblast monolayer forms without clustering. Alternatively, the MDA MB 231 cells are less motile and we observe that the MDA MB 231 monolayer formation is associated with significant clustering. We calibrate a moment dynamics model and a standard mean–field model to both data sets. Our results indicate that the mean–field and moment dynamics models provide similar descriptions of the 3T3 fibroblast monolayer formation whereas these two models give very different predictions for the MDA MD 231 monolayer formation. These outcomes indicate that standard mean–field models of collective cell behaviour are not always appropriate and that care ought to be exercised when implementing such a model.

ICT in vocational education and training: a view of information and communication technology in vocational education in New Zealand

This report looks at opportunities in relation to what is either already available or starting to take off in Information and Communication Technology (ICT). ICT focuses on the entire system of information, communication, processes and knowledge within an organisation. It focuses on how technology can be implemented to serve the information and communication needs of people and organisations. An ICT system involves a combination of work practices, information, people and a range of technologies and applications organised to make the business or organisation fully functional and efficient, and to accomplish goals in an organisation. Our focus is on vocational, workbased education in New Zealand. It is not about eLearning, although we briefly touch on the topic. We provide a background on vocational education in New Zealand, cover what we consider to be key trends impacting workbased, vocational education and training (VET), and offer practical suggestions for leveraging better value from ICT initiatives across the main activities of an Industry Training Organisation (ITO). We use a learning value chain approach to demonstrate the main functions ITOs engage in and also use this approach as the basis for developing and prioritising an ICT strategy. Much of what we consider in this report is applicable to the wider tertiary education sector as it relates to life-long learning. We consider ICT as an enabler that: a) connects education businesses (all types including tertiary education institutions) to learners, their career decisions and their learning, and as well, b) enables those same businesses to run more efficiently. We suggest that these two sets of activities are considered as interconnected parts of the same education or training business ICT strategy.

Safety culture in supply chains : 'Customer is king'

Despite the presence of many regulations governing the operation of heavy vehicles and supply chains in Australia, the truck driving sector continues to have the highest incidence of fatal injuries compared to all other industries. The working environment has been the focus of attention by safety researchers during the past few decades, with particular consideration been given to the concept ‘safety culture’ and how to maintain, modify and advance responses to occupational risk. One important aspect of the heavy industry which sets it apart is the existence of cultural or sub-cultural influences at an industry wide and occupation-specific level rather than organisational level. This paper reports on the findings of stakeholder’s perceptions of the influences of power and control, and culture on industry safety. In-depth structured interviews were conducted during 2011 with Australian industry stakeholders (n=31). The questioning surrounded decision-making processes with regards to identifying risks, self-monitoring and reducing risky activities; as well as how power-affected relationships may influence the operational performance of supply chains and impacts on driver safety. One of the most significant findings from these interviews relates to the notion of power. The perception that the ‘Customer is King’ was widely viewed, with the majority of stakeholders believing that there exists a ‘master slave mentality’ in the industry. There appears to be great frustration in the industry as to the apparent immunity of customers (particularly retail supply chains) to their responsibilities. There was also a strong perception that the customer holds the balance of power by covertly employing remuneration-related incentives and pressures. Smaller trucking companies are perceived as being more vulnerable to the pressure of customer expectations.

Why do tenders vary?

This paper describes the development of hypothetical models of tendering sets. Each tender is theorized as consisting of two variable components, the cost estimate and the mark-up, and in consideration of these variables, the concept of a 'winning zone' is postulated.

A Summative Evaluation of the Stronger Smarter Learning Communities Project : Vol 1 and Vol 2

This is a summative evaluation of the Stronger Smarter Learning Communities (SSLC) project that examines whether and how the SSLC project had an impact on Australian state schools which adopted its models and approaches. Drawing from qualitative and quantitative data sets, it also presents the largest scale and most comprehensive analysis of Indigenous education practices and outcomes to date. It includes empirical findings on: success in changing school ethos and community engagement; challenges in progress at closure of the 'gap' in conventionally measured achievement and performance; schools' and principals' choices in curriculum and instruction; profiles of teachers' and principals' training and views on teacher education; and a strong emphasis on community and school Indigenoous voices and views on Indigenous education.

Destination branding performance measurement for practitioners

While academic interest in destination branding has been gathering momentum since the field commenced in the late 1990s, one important gap in this literature that has received relatively little attention to date is the measurement of destination brand performance. This paper sets out one method for assessing the performance of a destination brand over time. The intent is to present an approach that will appeal to marketing practitioners, and which is also conceptually sound. The method is underpinned by Decision Set Theory and the concept of Consumer-Based Brand Equity (CBBE), while the key variables mirror the branding objectives used by many destination marketing organisations (DMO). The approach is demonstrated in this paper to measure brand performance for Australia in the New Zealand market. It is suggested the findings provide indicators of both i) the success of previous marketing communications, and ii) future performance, which can be easily communicated to a DMO’s stakeholders.