Food neophobia and its association with diet quality and weight in children aged 24 months : a cross sectional study

Background Food neophobia, the rejection of unknown or novel foods, may result in poor dietary patterns. This study investigates the cross-sectional relationship between neophobia in children aged 24 months and variety of fruit and vegetable consumption, intake of discretionary foods and weight. Methods Secondary analysis of data from 330 parents of children enrolled in the NOURISH RCT (control group only) and SAIDI studies was performed using data collected at child age 24 months. Neophobia was measured at 24 months using the Child Food Neophobia Scale (CFNS). The cross-sectional associations between total CFNS score and fruit and vegetable variety, discretionary food intake and BMI (Body Mass Index) Z-score were examined via multiple regression models; adjusting for significant covariates. Results At 24 months, more neophobic children were found to have lower variety of fruits (β=-0.16, p=0.003) and vegetables (β=-0.29, p<0.001) but have a greater proportion of daily energy from discretionary foods (β=0.11, p=0.04). There was no significant association between BMI Z-score and CFNS score. Conclusions Neophobia is associated with poorer dietary quality. Results highlight the need for interventions to (1) begin early to expose children to a wide variety of nutritious foods before neophobia peaks and (2) enable health professionals to educate parents on strategies to overcome neophobia.

Source characterisation of urban road surface pollutants for enhanced water quality predictions

This study developed a comprehensive research methodology for identification and quantification of sources responsible for pollutant build-up and wash-off from urban road surfaces. The study identified soil and asphalt wear, and non-combusted diesel fuel as the most influential sources for metal and hydrocarbon pollution respectively. The study also developed mathematical models to relate contributions from identified sources to underlying site specific factors such as land use and traffic. Developed mathematical model will play a key role in urban planning practices, enabling the implementation of effective water pollution control strategies.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

Managing and learning with multiple models: Objectives and optimization algorithms

The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. © 2010 Elsevier Ltd.

Optimal allocation of conservation effort among subpopulations of a threatened species: How important is patch quality?

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations of a threatened species, the combined effects of differences in habitat quality, cost of action, and current subpopulation probability of extinction need to be integrated. We provide a useful guideline for allocating resources among isolated subpopulations of any threatened species. © 2010 by the Ecological Society of America.

Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation

Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

Multi-parametric hydrogels support 3D in vitro bioengineered microenvironment models of tumour angiogenesis

Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.

A theoretical approach to conceptualize information quality in social media

While organizations strive to leverage the vast information generated daily from social media platforms, and decision makers are keen to identify and exploit its value, the quality of this information remains uncertain. Past research on information quality criteria and evaluation issues in social media is largely disparate, incomparable and lacking any common theoretical basis. In attention to this gap, this study adapts existing guidelines and exemplars of construct conceptualization in information systems research, to deductively define information quality and related criteria in the social media context. Building on a notion of information derived from semiotic theory, this paper suggests a general conceptualization of information quality in the social media context that can be used in future research to develop more context specific conceptual models.

Role of rainfall and catchment characteristics on urban stormwater quality

Urbanisation significantly changes the characteristics of a catchment as natural areas are transformed to impervious surfaces such as roads, roofs and parking lots. The increased fraction of impervious surfaces leads to changes to the stormwater runoff characteristics, whilst a variety of anthropogenic activities common to urban areas generate a range of pollutants such as nutrients, solids and organic matter. These pollutants accumulate on catchment surfaces and are removed and trans- ported by stormwater runoff and thereby contribute pollutant loads to receiving waters. In summary, urbanisation influences the stormwater characteristics of a catchment, including hydrology and water quality. Due to the growing recognition that stormwater pollution is a significant environmental problem, the implementation of mitigation strategies to improve the quality of stormwater runoff is becoming increasingly common in urban areas. A scientifically robust stormwater quality treatment strategy is an essential requirement for effective urban stormwater management. The efficient design of treatment systems is closely dependent on the state of knowledge in relation to the primary factors influencing stormwater quality. In this regard, stormwater modelling outcomes provide designers with important guidance and datasets which significantly underpin the design of effective stormwater treatment systems. Therefore, the accuracy of modelling approaches and the reliability modelling outcomes are of particular concern. This book discusses the inherent complexity and key characteristics in the areas of urban hydrology and stormwater quality, based on the influence exerted by a range of rainfall and catchment characteristics. A comprehensive field sampling and testing programme in relation to pollutant build-up, an urban catchment monitoring programme in relation to stormwater quality and the outcomes from advanced statistical analyses provided the platform for the knowledge creation. Two case studies and two real-world applications are discussed to illustrate the translation of the knowledge created to practical use in relation to the role of rainfall and catchment characteristics on urban stormwater quality. An innovative rainfall classification based on stormwater quality was developed to support the effective and scientifically robust design of stormwater treatment systems. Underpinned by the rainfall classification methodology, a reliable approach for design rainfall selection is proposed in order to optimise stormwater treatment based on both, stormwater quality and quantity. This is a paradigm shift from the common approach where stormwater treatment systems are designed based solely on stormwater quantity data. Additionally, how pollutant build-up and stormwater runoff quality vary with a range of catchment characteristics was also investigated. Based on the study out- comes, it can be concluded that the use of only a limited number of catchment parameters such as land use and impervious surface percentage, as it is the case in current modelling approaches, could result in appreciable error in water quality estimation. Influential factors which should be incorporated into modelling in relation to catchment characteristics, should also include urban form and impervious surface area distribution. The knowledge created through the research investigations discussed in this monograph is expected to make a significant contribution to engineering practice such as hydrologic and stormwater quality modelling, stormwater treatment design and urban planning, as the study outcomes provide practical approaches and recommendations for urban stormwater quality enhancement. Furthermore, this monograph also demonstrates how fundamental knowledge of stormwater quality processes can be translated to provide guidance on engineering practice, the comprehensive application of multivariate data analyses techniques and a paradigm on integrative use of computer models and mathematical models to derive practical outcomes.

What are the barriers of quality survivorship care for haematology cancer patients? Qualitative insights from cancer nurses

Purpose: Many haematological cancer survivors report long-term physiological and psychosocial effects beyond treatment completion. These survivors continue to experience impaired quality of life (QoL) as a result of their disease and aggressive treatment. As key members of the multidisciplinary team, the purpose of this study is to examine the insights of cancer nurses to inform future developments in survivorship care provision. Methods: Open text qualitative responses from two prospective Australian cross-sectional surveys of nurses (n=136) caring for patients with haematological cancer. Data were analysed thematically, using an inductive approach to identify themes. Results: This study has identified a number of issues that nurses perceive as barriers to quality survivorship care provision. Two main themes were identified; the first relating to the challenges nurses face in providing care (‘care challenges’), and the second relating to the challenges of providing survivorship care within contemporary health care systems (‘system challenges’). Conclusions: Cancer nurses perceive the nature of haematological cancer and its treatment, and of the health care system itself, as barriers to the provision of quality survivorship care. Care challenges such as the lack of a standard treatment path and the relapsing or remitting nature of haematological cancers may be somewhat intractable, but system challenges relating to clearly defining and delineating professional responsibilities and exchanging information with other clinicians are not. Implications for Cancer Survivors: Addressing the issues identified will facilitate cancer nurses’ provision of survivorship care, and help address haematological survivors’ needs with regard to the physical and psychosocial consequences of their cancer and treatment.

Survivorship care provision for patients with hematologic malignancies: The quest for quality evidence

This is an editorial that depicts the importance for developing more quality evidence to guide the survivorship care provision for patients with hematologic malignancies. Treatments for hematologic malignancies are often complex and debilitating, with increased risk of immune suppression and infections1. Some patients receive allogeneic stem cell transplantation that often requires in-patient stay of several weeks and life-long medical follow up. In recent years, advances in treatment regimens, and an aging population saw an increasing number of patients living with a hematologic malignancies or surviving curative therapy.2 The increased use of targeted therapies in hematologic malignancies (e.g. rituximab for non-Hodgkin lymphoma, bortezomib in multiple myeloma and imatinib in Chronic Myelogenous Leukemia has also resulted in improved overall survival...

Perceived safety, quality and cultural competency of maternity care for culturally and linguistically diverse women in Queensland

Various policies, plans, and initiatives have been implemented to provide safe, quality, and culturally competent care to patients within Queensland’s healthcare system. A series of models of maternity care are available in Queensland that range from standard public care to private midwifery care. The current study aimed to determine whether identifying as Culturally or Linguistically Diverse (CALD) was associated with the perceived safety, quality, and cultural competency of maternity care from a consumer perspective, and to identify specific needs and preferences of CALD maternity care consumers. Secondary analysis of data collected in the Having a Baby in Queensland Survey 2012 was used to compare the experiences of 655 CALD women to those of 4049 non-CALD women in Queensland, Australia, across three stages of maternity care: pregnancy, labour and birth, and after birth. After adjustment for model of maternity care received and socio-demographic characteristics, CALD women were significantly more likely than non-CALD women to experience suboptimal staff technical competence in pregnancy, overall perceived safety in pregnancy and labour/birth, and interpersonal sensitivity in pregnancy and labour/birth. Approximately 50% of CALD women did not have the choice to use a translator or interpreter, or the gender of their care provider, during labour and birth. Thirteen themes of preferences and needs of CALD maternity care consumers based on ethnicity, cultural beliefs, or traditions were identified, however, these were rarely met. Findings imply that CALD women in Queensland experience disadvantageous maternity care with regards to perceived staff technical competence, safety, and interpersonal sensitivity, and receive care that lacks cultural competence. Improved access to support persons, continuity and choice of carer, and staff availability and training is recommended.

A network DEA quantity and quality-orientated production model: An application to Australian university research services

The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.

Assessing testamentary and decision-making capacity: Approaches and models

The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.

Development of a method to assess the quality of ankle joint reduction in 3D

This project developed a quantitative method for determining the quality of the surgical alignment of the bone fragments after an ankle fracture. The research examined the feasibility of utilising MRI-based bone models versus the gold standard CT-based bone models in order to reduce the amount of ionising radiation the patient is exposed to. In doing so, the thesis reports that there is potential for MRI to be used instead of CT depending on the scanning parameters used to obtain the medical images, the distance of the implant relative to the joint surface, and the implant material.