Measuring, modelling and understanding the mechanical behavior of bagasse

In the Australian sugar industry, sugar cane is smashed into a straw like material by hammers before being squeezed between large rollers to extract the sugar juice. The straw like material is initially called prepared cane and then bagasse as it passes through successive roller milling units. The sugar cane materials are highly compressible, have high moisture content, are fibrous, and they resemble some peat soils in both appearance and mechanical behaviour. A promising avenue to improve the performance of milling units for increased throughput and juice extraction, and to reduce costs is by modelling of the crushing process. To achieve this, it is believed necessary that milling models should be able to reproduce measured bagasse behaviour. This investigation sought to measure the mechanical (compression, shear, and volume) behaviour of prepared cane and bagasse, to identify limitations in currently used material models, and to progress towards a material model that can predict bagasse behaviour adequately. Tests were carried out using a modified direct shear test equipment and procedure at most of the large range of pressures occurring in the crushing process. The investigation included an assessment of the performance of the direct shear test for measuring bagasse behaviour. The assessment was carried out using finite element modelling. It was shown that prepared cane and bagasse exhibited critical state behavior similar to that of soils and the magnitudes of material parameters were determined. The measurements were used to identify desirable features for a bagasse material model. It was shown that currently used material models had major limitations for reproducing bagasse behaviour. A model from the soil mechanics literature was modified and shown to achieve improved reproduction while using magnitudes of material parameters that better reflected the measured values. Finally, a typical three roller mill pressure feeder configuration was modelled. The predictions and limitations were assessed by comparison to measured data from a sugar factory.

The impact of diabetic ketoacidosis and age on behavior six months post-diagnosis in children with type 1 diabetes

Objectives: Children with type 1 diabetes mellitus (DM1) may be at increased risk of psychosocial and adjustment difficulties. We examined behavioral outcomes six months post-diagnosis in a group of children with newly diagnosed DM1. Methods: This study formed part of a larger longitudinal project examining pathophysiology and neuropsychological outcomes in diabetic patients with or without diabetic ketoacidosis (DKA). Participants were 61 children (mean age 11.8 years, SD 2.7 years) who presented with a new diagnosis of DM1 at the Royal Children’s Hospital, Melbourne. Twenty-three (11 female) presented in DKA and 38 (14 female) without DKA. Parents completed the behavior assessment system for children, second edition six months post-diagnosis. Results: There was a non-linear relationship between age and behavior. Internalising problems (i.e. anxiety depression, withdrawal) peaked in the transition from childhood to adolescence; children aged 10–13 years had elevated rates relative to the normal population (t = 2.55, P = 0.018). There was a non-significant trend for children under 10 to display internalising problems (P = 0.052), but rates were not elevated in children over 13 (P = 0.538). Externalising problems were not significantly elevated in any age group. Interestingly, children who presented in DKA were at lower risk of internalising problems than children without DKA (t = 3.83, P < 0.001). There was no effect of DKA on externalising behaviors. Conclusions: Children transitioning from childhood to adolescence are at significant risk for developing internalising problems such as anxiety and lowered mood after diagnosis of DM1. Somewhat counter-intuitively, parents of children presenting in DKA reported fewer internalising symptoms than parents of children without DKA. These results highlight the importance of monitoring and supporting psychosocial adjustment in newly diagnosed children even when they seem physically well.

Comparative behavior of CdS and CdSe quantum dots in poly(3-hexylthiophene) based nanocomposites

CdS and CdSe nanoparticles have been prepared using conducting poly(3-hexylthiophene) (P3HT) matrix with an objective to understand the effect of nanoparticles on the polymer matrix using electrochemical and spectroscopic techniques. The spectroscopic results reveal that the electronic structure of polymer is strongly influenced by the characteristics of embedded semiconducting nanoparticles. SEM and TEM images show the ordered morphology of the CdS and CdSe nanoparticles in presence of the polymer matrix. Cyclic voltammetry performed both in the presence and absence of light enables us to understand the redox changes in P3HT due to CdS and CdSe quantum dots such as the generation of free radical in the excited state and their electrochemical band gaps.

Public preferences for biodiversity conservation and climate-change mitigation: A choice experiment using ecosystem services indicators

Potential conflicts exist between biodiversity conservation and climate-change mitigation as trade-offs in multiple-use land management. This study aims to evaluate public preferences for biodiversity conservation and climate-change mitigation policy considering respondents’ uncertainty on their choice. We conducted a choice experiment using land-use scenarios in the rural Kushiro watershed in northern Japan. The results showed that the public strongly wish to avoid the extinction of endangered species in preference to climate-change mitigation in the form of carbon sequestration by increasing the area of managed forest. Knowledge of the site and the respondents’ awareness of the personal benefits associated with supporting and regulating services had a positive effect on their preference for conservation plans. Thus, decision-makers should be careful about how they provide ecological information for informed choices concerning ecosystem services tradeoffs. Suggesting targets with explicit indicators will affect public preferences, as well as the willingness of the public to pay for such measures. Furthermore, the elicited-choice probabilities approach is useful for revealing the distribution of relative preferences for incomplete scenarios, thus verifying the effectiveness of indicators introduced in the experiment.

Modal choice between air and rail : a social efficiency benchmarking analysis that considers CO2 emissions

The problem of modal choice between rail and air arises as public awareness of carbon dioxide (CO2) emissions by the transportation sector rises. In this paper, we answer this question quantitatively by performing an efficiency benchmarking analysis that takes into account life-cycle CO2 emission due to transport service provision. The paper employs nonparametric efficiency estimation methods, namely a slacks-based inefficiency measure, as well as a more conventional directional distance function approach. We apply them to a panel data set for three major railway companies and the aviation sector in Japan for the period from 1999 to 2007. Results shows that, contrary to the common argument, air transport can still be more socially efficient than rail transport, even when the environmental load due to CO2 emission is incorporated. This is due to the aviation sector's extremely low user cost, measured in terms of in-vehicle time. In other words, aviation is a necessary transportation mode for those with a very high willingness to pay for their time.

Young driver distraction : state of the evidence and directions for behavior change programs

Adolescent drivers are over-represented in distraction-related motor vehicle crashes. There are a number of potential reasons for such elevated risk with driving inexperience, high adoption of communication technology, increased peer involvement and tendency to take risks, rendering young drivers particularly vulnerable. Major legislative efforts in Graduated Licensing Systems that include passenger restrictions have shown positive effects. Restrictions on cell phone use are also being introduced however enforcement of such regulations is challenging. This paper argues that such contextual, legislative interventions are an essential prevention strategy however there is an unfilled need to introduce behavior change programs that may target adolescents, parents and friends. A theoretical framework is applied in which risk and protective factors are identified from research within community and jurisdiction contexts. In the literature on distraction social context and normative influences are the key elements used to inform program design for adolescent drivers with parental monitoring informing interventions targeting parents. Following from this assessment of the message content assessment, the design of strategies to deliver the messages are reviewed. In the current literature, school-based programs, simulations and web-delivered programs have been evaluated with supplementary strategies delivered by physicians and parents. Such developments are still at an early stage of development and ultimately will need controlled implementation and evaluation studies. There is of course, no likely single approach to prevent adolescent driver distraction and complementary approaches such as the further development of technological interventions to manage phone use are needed. Implications and Contributions The paper describes the intervention design process alongside key research in young driver distraction including selecting target behavior, audience, theoretically-derived strategies and delivery strategies. Currently graduated driver licensing and technology use and acceptance and parent-adolescent and adolescent-peer interactions are opportunities for further research and exploration.

The choice of spatial scales and spatial smoothness priors for various spatial patterns

Given the drawbacks for using geo-political areas in mapping outcomes unrelated to geo-politics, a compromise is to aggregate and analyse data at the grid level. This has the advantage of allowing spatial smoothing and modelling at a biologically or physically relevant scale. This article addresses two consequent issues: the choice of the spatial smoothness prior and the scale of the grid. Firstly, we describe several spatial smoothness priors applicable for grid data and discuss the contexts in which these priors can be employed based on different aims. Two such aims are considered, i.e., to identify regions with clustering and to model spatial dependence in the data. Secondly, the choice of the grid size is shown to depend largely on the spatial patterns. We present a guide on the selection of spatial scales and smoothness priors for various point patterns based on the two aims for spatial smoothing.

Understanding Heliothine (Lepidoptera: Heliothinae) pests: What is a host plant?

Heliothine moths (Lepidoptera: Heliothinae) include some of the world's most devastating pest species. Whereas the majority of nonpest heliothinae specialize on a single plant family, genus, or species, pest species are highly polyphagous, with populations often escalating in size as they move from one crop species to another. Here, we examine the current literature on heliothine host-selection behavior with the aim of providing a knowledge base for research scientists and pest managers. We review the host relations of pest heliothines, with a particular focus on Helicoverpa armigera (Hubner), the most economically damaging of all heliothine species. We then consider the important question of what constitutes a host plant in these moths, and some of the problems that arise when trying to determine host plant status from empirical studies on host use. The top six host plant families in the two main Australian pest species (H. armigera and Helicoverpa punctigera Wallengren) are the same and the top three (Asteraceae, Fabaceae, and Malvaceae) are ranked the same (in terms of the number of host species on which eggs or larvae have been identified), suggesting that these species may use similar cues to identify their hosts. In contrast, for the two key pest heliothines in the Americas, the Fabaceae contains approximate to 1/3 of hosts for both. For Helicoverpa zea (Boddie), the remaining hosts are more evenly distributed, with Solanaceae next, followed by Poaceae, Asteraceae, Malvaceae, and Rosaceae. For Heliothis virescens (F.), the next highest five families are Malvaceae, Asteraceae, Solanaceae, Convolvulaceae, and Scrophulariaceae. Again there is considerable overlap in host use at generic and even species level. H. armigera is the most widely distributed and recorded from 68 plant families worldwide, but only 14 families are recorded as a containing a host in all geographic areas. A few crop hosts are used throughout the range as expected, but in some cases there are anomalies, perhaps because host plant relation studies are not comparable. Studies on the attraction of heliothines to plant odors are examined in the context of our current understanding of insect olfaction, with the aim of better understanding the connection between odor perception and host choice. Finally, we discuss research into sustainable management of pest heliothines using knowledge of heliothine behavior and ecology. A coordinated international research effort is needed to advance our knowledge on host relations in widely distributed polyphagous species instead of the localized, piecemeal approaches to understanding these insects that has been the norm to date.

Influence of visible work activity on drivers’ speed choice at roadworks

Vehicle traffic through roadwork sites creates a hazardous work environment, with speed limit noncompliance a major contributor to the high risk and high severity of roadwork crashes. This paper examines responses to an online survey to better understand the factors underlying drivers’ work zone speed choices. Drivers’ stated speed choice was compared between two photographs of the same work zone section – one with workers and machinery present and another with no visible activity. Drivers also provided comments on any aspect of roadwork safety they thought was important. A paired t-test of stated speed choice revealed that significantly lower mean speeds were nominated when workers and machinery were clearly present and active (41.7 vs 53.5 km/h, p<0.01). Participants expressed concern about roadwork signage and reduced speed limits being left in place when there was no apparent work activity. Driver perceptions, and thus compliance, may be improved through technological and operational changes.

Fischer rats consume 20% ethanol in a long-term intermittent-access two-bottle-choice paradigm

The 20% ethanol intermittent-access (IAE) two-bottle-choice drinking procedure has been shown to produce high voluntary ethanol consumption in a number of rat strains. For this study, we applied this procedure to male Fischer (F344) rats, a strain previously reported to exhibit low levels of ethanol consumption. We also subjected these animals to a two-week ethanoldeprivation- period to see if they would exhibit an alcohol deprivation effect (ADE) signified by a transient increase in alcohol consumption following deprivation. Our data show a separation between high and low consuming animals within this strain, with high-consumers exhibiting an escalation in consumption. In contrast, Fischer rats did not show a significant separation between high and low consumers or any significant escalation in consumption, using the 20% ethanol continuous-access two-bottle-choice drinking protocol. Following the two-week deprivation period, animals in the high (but not the low) IAE group exhibited the transient increase in ethanol consumption and preference typically associated with an ADE. Together, the data suggest that the intermittent access protocol is a useful protocol for increasing ethanol consumption.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.