Using an extended theory of planned behavior to predict a change in the type of blood product donated

Background Demand for essential plasma-derived products is increasing. Purpose This prospective study aims to identify predictors of voluntary non-remunerated whole blood (WB) donors becoming plasmapheresis donors. Methods Surveys were sent to WB donors who had recently (recent n = 1,957) and not recently donated (distant n = 1,012). Theory of Planned Behavior (TPB) constructs (attitude, subjective norm, self-efficacy) were extended with moral norm, anticipatory regret, and donor identity. Intentions and objective plasmapheresis donation for 527 recent and 166 distant participants were assessed. Results Multi-group analysis revealed that the model was a good fit. Moral norm and self-efficacy were positively associated while role identity (suppressed by moral norm) was negatively associated with plasmapheresis intentions. Conclusions The extended TPB was useful in identifying factors that facilitate conversion from WB to plasmapheresis donation. A superordinate donor identity may be synonymous with WB donation and, for donors with a strong moral norm for plasmapheresis, may inhibit conversion.

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.

Hole mobility of 3.56 cm2V−1s−1accomplished using more extended dithienothiophene with furan flanked diketopyrrolopyrrole polymer

A highly extended dithienothiophene comonomer building block was used in combination with highly fused aromatic furan substituted diketopyrrolopyrrole for the synthesis of novel donor–acceptor alternating copolymer PDPPF-DTT. Upon testing PDPPF-DTT as a channel semiconductor in top contact bottom gate organic field effect transistors (OFETs), it was found to exhibit p-channel behaviour. The highest hole mobility of 3.56 cm2 V−1 s−1 was reported for PDPPF-DTT. To our knowledge, this is the highest mobility reported so far for the furan flanked diketopyrrolopyrrole class of copolymers using conventional device geometry with straightforward processing.

Hybrid metaheuristic techniques for optimising sugarcane rail operations

Mixed integer programming and parallel-machine job shop scheduling are used to solve the sugarcane rail transport scheduling problem. Constructive heuristics and metaheuristics were developed to produce a more efficient scheduling system and so reduce operating costs. The solutions were tested on small and large size problems. High-quality solutions and improved CPU time are the result of developing new hybrid techniques which consist of different ways of integrating simulated annealing and Tabu search techniques.

Exploring the role of energy, trade and financial development in explaining economic growth in South Africa: A revisit

South Africa is an emerging and industrializing economy which is experiencing remarkable progress. We contend that amidst the developments in the economy, the role of energy, trade openness and financial development are critical. In this article, we revisit the pivotal role of these factors. We use the ARDL bounds [72], the Bayer and Hanck [11] cointegration techniques, and an extended Cobb–Douglas framework, to examine the long-run association with output per worker over the sample period 1971–2011. The results support long-run association between output per worker, capital per worker and the shift parameters. The short-run elasticity coefficients are as follows: energy (0.24), trade (0.07), financial development (−0.03). In the long-run, the elasticity coefficients are: trade openness (0.05), energy (0.29), and financial development (−0.04). In both the short-run and the long-run, we note the post-2000 period has a marginal positive effect on the economy. The Toda and Yamamoto [91] Granger causality results show that a unidirectional causality from capital stock and energy consumption to output; and from capital stock to trade openness; a bidirectional causality between trade openness and output; and absence (neutrality) of any causality between financial development and output thus indicating that these two variables evolve independent of each other.

Measuring load of phosphate in the environment by passive sampling techniques: An introduction

Phosphorus has a number of indispensable biochemical roles, but its natural deposition and the low solubility of phosphates as well as their rapid transformation to insoluble forms make the element commonly the growth-limiting nutrient, particularly in aquatic ecosystems. Famously, phosphorus that reaches water bodies is commonly the main cause of eutrophication. This undesirable process can severely affect many aquatic biotas in the world. More management practices are proposed but long-term monitoring of phosphorus level is necessary to ensure that the eutrophication won't occur. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing flow proportional load as well as representative average of concentrations of phosphorus in the environment. Although some types of passive samplers are commercially available, their uses are still scarcely reported in the literature. In Japan, there is limited application of passive sampling technique to monitor phosphorus even in the field of agricultural environment. This paper aims to introduce the relatively new P-sampling techniques and their potential to use in environmental monitoring studies.

Applications of passive sampling techniques in monitoring organic pollutants in the environment

As there are a myriad of micro organic pollutants that can affect the well-being of human and other organisms in the environment the need for an effective monitoring tool is eminent. Passive sampling techniques, which have been developed over the last decades, could provide several advantages to the conventional sampling methods including simpler sampling devices, more cost-effective sampling campaign, providing time-integrated load as well as representative average of concentrations of pollutants in the environment. Those techniques have been applied to monitor many pollutants caused by agricultural activities, i.e. residues of pesticides, veterinary drugs and so on. Several types of passive samplers are commercially available and their uses are widely accepted. However, not many applications of those techniques have been found in Japan, especially in the field of agricultural environment. This paper aims to introduce the field of passive sampling and then to describe some applications of passive sampling techniques in environmental monitoring studies related to the agriculture industry.

Raman spectroscopy techniques for detection of energetic materials at high and low concentration

This thesis presents the development of a rapid, sensitive and reproducible spectroscopic method for the detection of TNT in forensic and environmental applications. Simple nano sensors prepared by cost effective methods were utilized as sensitive platforms for the detection of TNT by surface enhanced Raman spectroscopy. The optimization of the substrate and the careful selection of a suitable recognition molecule contributed to the significant improvements of sensitive and selective targeting over current detection methods. The work presented in this thesis paves the way for effective detection and monitoring of explosives residues in law enforcement and environmental health applications.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

State-formation, teaching techniques, and globalization as aporia

Eleanor Smith [pseudonym], teacher : I was talking to the kids about MacDonalds*/I forget exactly what the context was*/I said ‘‘ah, the Americans call them French fries, and, you know, MacDonalds is an American chain and they call them French fries because the Americans call them French fries’’, and this little Australian kid in the front row, very Australian child, said to me, ‘‘I call them French fries!’’ . . . Um, a fourth grade boy whom I taught in 1993 at this school, the world basketball championships were on . . . Americans were playing their dream machine and the Boomers were up against them . . . and, ah, this boy was very interested in basketball . . . but it’s not in my blood, not in the way cricket is for example . . . Um, Um, and I said to this fellow, ‘‘um, well’’, I said, ‘‘Australia’s up against Dream Machine tomorrow’’. He [Jason, pseudonym] said, ‘‘Ah, you know, Boomers probably won’t win’’. . . . I said, ‘‘Well that’s sport, mate’’. I said, ‘‘You never know in sport. Australia might win’’. And he looked at me and he said, ‘‘I’m not going for Australia, I’m going for America’’. This is from an Australian boy! And I thought so strong is the hype, so strong is the, is the, power of the media, etc., that this boy is not [pause], I can’t tell you how outraged I was. Here’s me as an Australian and I don’t even support basketball, it’s not even my sport, um, but that he would respond like that because of the power of the American machine that’s converting kids’ minds, the way they think, where they’re putting their loyalties, etc. I was just appalled, but that’s where he was. And when I asked kids for their favourite place, he said Los Angeles.

Simulated systems optimization through response surface techniques [Optimización de sistemas simulados a través de técnicas de superficie de respuesta]

The purpose of this article is to show the applicability and benefits of the techniques of design of experiments as an optimization tool for discrete simulation models. The simulated systems are computational representations of real-life systems; its characteristics include a constant evolution that follows the occurrence of discrete events along the time. In this study, a production system, designed with the business philosophy JIT (Just in Time) is used, which seeks to achieve excellence in organizations through waste reduction in all the operational aspects. The most typical tool of JIT systems is the KANBAN production control that seeks to synchronize demand with flow of materials, minimize work in process, and define production metrics. Using experimental design techniques for stochastic optimization, the impact of the operational factors on the efficiency of the KANBAN / CONWIP simulation model is analyzed. The results show the effectiveness of the integration of experimental design techniques and discrete simulation models in the calculation of the operational parameters. Furthermore, the reliability of the methodologies found was improved with a new statistical consideration.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Adolescent writing development: Improving succinctness using the extended noun phrase

This study examined an aspect of adolescent writing development, specifically whether teaching secondary school students to use strategies to enhance succinctness in their essays changed the grammatical sophistication of their sentences. A quasi-experimental intervention was used to compare changes in syntactic complexity and lexical density between one-draft and polished essays. No link was demonstrated between the intervention and the changes. A thematic analysis of teacher interviews explored links between changes to student texts and teaching approaches. The study has implications for making syntactic complexity an explicit goal of student drafting.

Where do consumers draw the line? Factors informing perceptions and justifications of deviant consumer behaviour

Deviant consumer behaviour in the marketplace is an ongoing problem causing harm to the organisation, employees, and other consumers. To address this problem, this study explores consumer perceptions of right and wrong using the novel concept of a deviance threshold – the mental line in the sand dictating right and wrong. Using consumer-based interviews with a card-sort activity, findings supported and extended dimensions proposed to explain why some behaviours are perceived as more serious or unethical than others. Moreover, why specific neutralisation techniques are used and how they affect categorisations of behaviours within an individual’s deviance threshold is explained. This study offers alternative strategies tailored to challenging consumer justifications to curb deviance. Implications support abandoning the universal approach to deterrence.

Special Issue on Spatial Moment Techniques for Modelling Biological Processes

Over the last two decades, there has been an increasing awareness of, and interest in, the use of spatial moment techniques to provide insight into a range of biological and ecological processes. Models that incorporate spatial moments can be viewed as extensions of mean-field models. These mean-field models often consist of systems of classical ordinary differential equations and partial differential equations, whose derivation, at some point, hinges on the simplifying assumption that individuals in the underlying stochastic process encounter each other at a rate that is proportional to the average abundance of individuals. This assumption has several implications, the most striking of which is that mean-field models essentially neglect any impact of the spatial structure of individuals in the system. Moment dynamics models extend traditional mean-field descriptions by accounting for the dynamics of pairs, triples and higher n-tuples of individuals. This means that moment dynamics models can, to some extent, account for how the spatial structure affects the dynamics of the system in question.