A mathematical model for intermittent microwave convective (IMCD) drying of food materials

Intermittent microwave convective drying (IMCD) is an advanced technology that improves both energy efficiency and food quality in drying. Modelling of IMCD is essential to understand the physics of this advanced drying process and to optimize the microwave power level and intermittency during drying. However, there is still a lack of modelling studies dedicated to IMCD. In this study, a mathematical model for IMCD was developed and validated with experimental data. The model showed that the interior temperature of the material was higher than the surface in IMCD, and that the temperatures fluctuated and redistributed due to the intermittency of the microwave power. This redistribution of temperature could significantly contribute to the improvement of product quality during IMCD. Limitations when using Lambert's Law for microwave heat generation were identified and discussed.

The impact of personality and workplace belongingness on mental health workers’ professional quality of life

Objectives Mental health workers are constantly exposed to their clients’ stories of distress and trauma. While listening to these stories can be emotionally draining, professionals in this field still derive pleasure from their work. This study examined the role of personality and workplace belongingness in predicting compassion satisfaction, secondary traumatic stress, and burnout in mental health professionals. Methods Mental health staff (N = 156) working in a counselling service completed a questionnaire that included measures relating to professional quality of life, the Five-Factor Model of personality, workplace belongingness, as well as questions relating to the participants’ demographic profile, work roles and trauma history. Results The results indicated that, high levels of emotional stability (low neuroticism), extraversion, agreeableness, conscientiousness, and being connected at work, are essential factors that promote the professional quality of life of mental health workers. Specifically, workplace belongingness was the strongest predictor of compassion satisfaction and low levels of burnout, while neuroticism was the strongest predictor of secondary traumatic stress. Conclusions Important implications from this study include: (1) encouraging mental health staff to increase self-awareness of their dispositional characteristics and how their personalities affect their wellbeing at work, and; (2) encouraging management to facilitate practices where mental health workers feel connected, respected, and supported in their organisation.

Evaluation of a skin self examination attitude scale using an item response theory model approach

Introduction The Skin Self-Examination Attitude Scale (SSEAS) is a brief measure that allows for the assessment of attitudes in relation to skin self-examination. This study evaluated the psychometric properties of the SSEAS using Item Response Theory (IRT) methods in a large sample of men ≥ 50 years in Queensland, Australia. Methods A sample of 831 men (420 intervention and 411 control) completed a telephone assessment at the 13-month follow-up of a randomized-controlled trial of a video-based intervention to improve skin self-examination (SSE) behaviour. Descriptive statistics (mean, standard deviation, item–total correlations, and Cronbach’s alpha) were compiled and difficulty parameters were computed with Winsteps using the polytomous Rasch Rating Scale Model (RRSM). An item person (Wright) map of the SSEAS was examined for content coverage and item targeting. Results The SSEAS have good psychometric properties including good internal consistency (Cronbach’s alpha = 0.80), fit with the model and no evidence for differential item functioning (DIF) due to experimental trial grouping was detected. Conclusions The present study confirms the SSEA scale as a brief, useful and reliable tool for assessing attitudes towards skin self-examination in a population of men 50 years or older in Queensland, Australia. The 8-item scale shows unidimensionality, allowing levels of SSE attitude, and the item difficulties, to be ranked on a single continuous scale. In terms of clinical practice, it is very important to assess skin cancer self-examination attitude to identify people who may need a more extensive intervention to allow early detection of skin cancer.

Significant deterioration in nanomechanical quality occurs through incomplete extrafibrillar mineralization in rachitic bone: Evidence from in-situ synchrotron X-ray scattering and backscattered electron imaging

Bone diseases such as rickets and osteoporosis cause significant reduction in bone quantity and quality, which leads to mechanical abnormalities. However, the precise ultrastructural mechanism by which altered bone quality affects mechanical properties is not clearly understood. Here we demonstrate the functional link between altered bone quality (reduced mineralization) and abnormal fibrillar-level mechanics using a novel, real-time synchrotron X-ray nanomechanical imaging method to study a mouse model with rickets due to reduced extrafibrillar mineralization. A previously unreported N-ethyl-N-nitrosourea (ENU) mouse model for hypophosphatemic rickets (Hpr), as a result of missense Trp314Arg mutation of the phosphate regulating gene with homologies to endopeptidase on the X chromosome (Phex) and with features consistent with X-linked hypophosphatemic rickets (XLHR) in man, was investigated using in situ synchrotron small angle X-ray scattering to measure real-time changes in axial periodicity of the nanoscale mineralized fibrils in bone during tensile loading. These determine nanomechanical parameters including fibril elastic modulus and maximum fibril strain. Mineral content was estimated using backscattered electron imaging. A significant reduction of effective fibril modulus and enhancement of maximum fibril strain was found in Hpr mice. Effective fibril modulus and maximum fibril strain in the elastic region increased consistently with age in Hpr and wild-type mice. However, the mean mineral content was ∼21% lower in Hpr mice and was more heterogeneous in its distribution. Our results are consistent with a nanostructural mechanism in which incompletely mineralized fibrils show greater extensibility and lower stiffness, leading to macroscopic outcomes such as greater bone flexibility. Our study demonstrates the value of in situ X-ray nanomechanical imaging in linking the alterations in bone nanostructure to nanoscale mechanical deterioration in a metabolic bone disease. Copyright

Rank regression analysis of correlated water quality data from South East Queensland

With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.

Assessment of quality defects in macadamia kernels using NIR spectroscopy

Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.

Robustness of NIR calibrations for assessing fruit quality

Predictive models based on near infra-red spectroscopy for the assessment of fruit internal quality attributes must exhibit a degree of robustness across the parameters of variety, district and time to be of practical use in fruit grading. At the time this thesis was initiated, while there were a number of published reports on the development of near infra-red based calibration models for the assessment of internal quality attributes of intact fruit, there were no reports of the reliability ("robustness") of such models across time, cultivars or growing regions. As existing published reports varied in instrumentation employed, a re-analysis of existing data was not possible. An instrument platform, based on partial transmittance optics, a halogen light source and (Zeiss MMS 1) detector operating in the short wavelength near infra-red region was developed for use in the assessment of intact fruit. This platform was used to assess populations of macadamia kernels, melons and mandarin fruit for total soluble solids, dry matter and oil concentration. Calibration procedures were optimised and robustness assessed across growing areas, time of harvest, season and variety. In general, global modified partial least squares regression (MPLS) calibration models based on derivatised absorbance data were better than either multiple linear regression or `local' MPLS models in the prediction of independent validation populations . Robustness was most affected by growing season, relative to the growing district or variety . Various calibration updating procedures were evaluated in terms of calibration robustness. Random selection of samples from the validation population for addition to the calibration population was equivalent to or better than other methods of sample addition (methods based on the Mahalanobis distance of samples from either the centroid of the population or neighbourhood samples). In these exercises the global Mahalanobis distance (GH) was calculated using the scores and loadings from the calibration population on the independent validation population. In practice, it is recommended that model predictive performance be monitored in terms of predicted sample GH, with model updating using as few as 10 samples from the new population undertaken when the average GH value exceeds 1 .0 .

Runoff, sediment loss and water quality from forest roads in a southeast Queensland coastal plain Pinus plantation

Runoff and sediment loss from forest roads were monitored for a two-year period in a Pinus plantation in southeast Queensland. Two classes of road were investigated: a gravelled road, which is used as a primary daily haulage route for the logging area, and an ungravelled road, which provides the main access route for individual logging compartments and is intensively used as a haulage route only during the harvest of these areas (approximately every 30 years). Both roads were subjected to routine traffic loads and maintenance during the study. Surface runoff in response to natural rainfall was measured and samples taken for the determination of sediment and nutrient (total nitrogen, total phosphorus, dissolved organic carbon and total iron) loads from each road. Results revealed that the mean runoff coefficient (runoff depth/rainfall depth) was consistently higher from the gravelled road plot with 0.57, as compared to the ungravelled road with 0.38. Total sediment loss over the two-year period was greatest from the gravelled road plot at 5.7 t km−1 compared to the ungravelled road plot with 3.9 t km−1. Suspended solids contributed 86% of the total sediment loss from the gravelled road, and 72% from the ungravelled road over the two years. Nitrogen loads from the two roads were both relatively constant throughout the study, and averaged 5.2 and 2.9 kg km−1 from the gravelled and ungravelled road, respectively. Mean annual phosphorus loads were 0.6 kg km−1 from the gravelled road and 0.2 kg km−1 from the ungravelled road. Organic carbon and total iron loads increased in the second year of the study, which was a much wetter year, and are thought to reflect the breakdown of organic matter in roadside drains and increased sediment generation, respectively. When road and drain maintenance (grading) was performed runoff and sediment loss were increased from both road types. Additionally, the breakdown of the gravel road base due to high traffic intensity during wet conditions resulted in the formation of deep (10 cm) ruts which increased erosion. The Water Erosion Prediction Project (WEPP):Road model was used to compare predicted to observed runoff and sediment loss from the two road classes investigated. For individual rainfall events, WEPP:Road predicted output showed strong agreement with observed values of runoff and sediment loss. WEPP:Road predictions for annual sediment loss from the entire forestry road network in the study area also showed reasonable agreement with the extrapolated observed values.

Assessing performance in critical care nursing practice using the Benner Novice to expert model: A pilot study

Background It is often believed that by ensuring the ongoing completion of competency documents and life-long learning in nursing practice guarantees quality patient care. This is probably true in most cases where it provides reassurances that the nursing team is maintaining a safe “generalised” level of practice. However, competency does not always promise quality performance. There are a number of studies that have reported differences in what practitioners know and what they actually do despite being deemed competent. Aim The aim of this study was to assess whether our current competency documentation is fit for purpose and to ascertain whether performance assessment needs to be a key component in determining competence. Method 15 nurses within a General ICU who had been on the unit <4 years agreed to participate in this project. Using participant observation and assessing performance against key indicators of the Benner Novice to Expert5 model the participants were supported and assessed over the course of a ‘normal’ nursing shift. Results The results were surprising both positively and negatively. First, the nurses felt more empowered in their clinical decision making skills; second, it identified individual learning needs and milestones in educational development. There were some key challenges identified which included 5 nurses over estimating their level of competence, practice was still very much focused on task acquisition and skill and surprisingly some nurses still felt dominated by the other health professionals within the unit. Conclusion We found that the capacity and capabilities of our nursing workforce needs continual ongoing support especially if we want to move our staff from capable task-doer to competent performers. Using the key novice to expert indicators identified the way forward for us in how we assess performance and competence in practice particularly where promotion to higher grades is based on existing documentation.

NIR model development and robustness in prediction of melon fruit total soluble solids

Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

Achieving Quality: Consumer Involvement in Quality Evaluation of Services

[Excerpt] The aim of this paper is to raise awareness of the fact that changes in the approach towards the “clients” or “consumers” of services for people with intellectual disability do have an important impact on the way the quality evaluation systems of these services should be designed and organised.

Choosing a model of maternity care: decision support needs of Australian women

- BACKGROUND Access to information on the features and outcomes associated with the various models of maternity care available in Australia is vital for women's informed decision-making. This study sought to identify women's preferences for information access and decision-making involvement, as well as their priority information needs, for model of care decision-making. - METHODS A convenience sample of adult women of childbearing age in Queensland, Australia were recruited to complete an online survey assessing their model of care decision support needs. Knowledge on models of care and socio-demographic characteristics were also assessed. - RESULTS Altogether, 641 women provided usable survey data. Of these women, 26.7 percent had heard of all available models of care before starting the survey. Most women wanted access to information on models of care (90.4%) and an active role in decision-making (99.0%). Nine priority information needs were identified: cost, access to choice of mode of birth and care provider, after hours provider contact, continuity of carer in labor/birth, mobility during labor, discussion of the pros/cons of medical procedures, rates of skin-to-skin contact after birth, and availability at a preferred birth location. This information encompassed the priority needs of women across age, birth history, and insurance status subgroups. - CONCLUSIONS This study demonstrates Australian women's unmet needs for information that supports them to effectively compare available options for model of maternity care. Findings provide clear direction on what information should be prioritized and ideal channels for information access to support quality decision-making in practice.

Seasonal changes in pasture quality and diet selection and their relationship with liveweight gain of steers grazing tropical grass and grass-legume pastures in northern Australia.

The variation in liveweight gain in grazing beef cattle as influenced by pasture type, season and year effects has important economic implications for mixed crop-livestock systems and the ability to better predict such variation would benefit beef producers by providing a guide for decision making. To identify key determinants of liveweight change of Brahman-cross steers grazing subtropical pastures, measurements of pasture quality and quantity, and diet quality in parallel with liveweight were made over two consecutive grazing seasons (48 and 46 weeks, respectively), on mixed Clitoria ternatea/grass, Stylosanthes seabrana/grass and grass swards (grass being a mixture of Bothriochloa insculpta cv. Bisset, Dichanthium sericeum and Panicum maximum var. trichoglume cv. Petrie). Steers grazing the legume-based pastures had the highest growth rate and gained between 64 and 142 kg more than those grazing the grass pastures in under 12 months. Using an exponential model, green leaf mass, green leaf %, adjusted green leaf % (adjusted for inedible woody legume stems), faecal near infrared reflectance spectroscopy predictions of diet crude protein and diet dry matter digestibility, accounted for 77, 74, 80, 63 and 60%, respectively, of the variation in daily weight gain when data were pooled across pasture types and grazing seasons. The standard error of the regressions indicated that 95% prediction intervals were large (+/- 0.42-0.64 kg/head.day) suggesting that derived regression relationships have limited practical application for accurately estimating growth rate. In this study, animal factors, especially compensatory growth effects, appeared to have a major influence on growth rate in relation to pasture and diet attributes. It was concluded that predictions of growth rate based only on pasture or diet attributes are unlikely to be accurate or reliable. Nevertheless, key pasture attributes such as green leaf mass and green leaf% provide a robust indication of what proportion of the potential growth rate of the grazing animals can be achieved.

The effect of data sources and quality on the predictive capacity of CLIMEX models: an assessment of Teleonemia scrupulosa and Octotoma scabripennis for the biocontrol of Lantana camara in Australia

Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.