Fracture analysis of spherical shells : application to cracking of macadamia nuts

The main consideration in recovering the macadamia kernal is to crack the spherical nutshell without damaging the kernal. Five mechanical cracking tools were tested, and the fracture mechanisms of nutshells, under various cracking loads, were studied. A classical theoretical approach and a numerical method were both used to investigate the influence of crack face closure on the stress intensity factor for a cracked spherical shell subjected to membrane forces and bending moments.

Habitat manipulation and rodent damage control: reducing rodent damage in Australian macadamia orchards

This paper examines the relationship between adjacent non-crop vegetation and rodent (Rattus rattus) damage in Australian macadamia (Macadamia integrifolia) orchard systems. Orchards adjacent to structurally diverse, non-crop vegetation dominated by woody weeds exhibited significantly higher damage when compared to orchards adjacent to managed grasslands. This relationship formed the basis for a rodent damage reduction strategy utilising habitat manipulation. Structurally diverse, non-crop habitats were modified to grasslands leading to a reduction in rodent damage of 65%. This strategy was cost-effective and has the potential to be long-term with minimal effort needed to maintain sites in a modified state. Habitat manipulation is a process whereby the resource load in a system is reduced and hence rodent densities cannot reach levels where they cause significant crop damage. This paper provides empirical evidence to support habitat manipulation as a practical, cost-effective control strategy for rodent pests.

IgE cross-reactivity between the major peanut allergen Ara h 2 and tree nut allergens

Allergy to peanut and tree nuts is characterised by a high frequency of life-threatening anaphylactic reactions and typically lifelong persistence. Although peanut is the most common cause of nut allergy, peanut allergic patients are frequently also sensitive to tree nuts. It is not known if this is due to cross-reactivity between peanut and tree nut allergens. In this study, the major peanut allergen Ara h 2 was cloned from peanut cDNA, expressed in E. coli cells as a His-tag fusion protein and purified using a Ni-NTA column. Immunoblotting, ELISA and basophil activation indicated by CD63 expression all confirmed the IgE reactivity and biological activity of rAra h 2. To determine whether or not this allergen plays a role in IgE cross-reactivity between peanut and tree nuts, inhibition ELISA was performed. Pre-incubation of serum from peanut allergic patients with increasing concentrations of almond or Brazil nut extract inhibited IgE binding to rAra h 2. Purified rAra h 2-specific serum IgE antibodies also bound to proteins present in almond and Brazil nut extracts by immunoblotting. This indicates that the major peanut allergen, Ara h 2, shares common IgE-binding epitopes with almond and Brazil nut allergens, which may contribute to the high incidence of tree nut sensitisation in peanut allergic individuals.

The control of rodent damage in Australian macadamia orchards by manipulation of adjacent non-crop habitats

 Habitat manipulation was used as a management strategy for the control of rodent (Rattus rattus) damage in Australian macadamia orchard systems. Large, temporally stable non-crop habitats were converted to highly modified grasslands. These sites were manipulated by removing all non-crop vegetation over 10 cm in height to a distance of approximately 20 m from the orchard. Regrowth was controlled by the application of herbicide. The total cost of the habitat manipulation was $AUD 292 per site. Manipulation resulted in a reduction in damage of 65% within the associated orchards. This reduction in rodent damage resulted in a saving of $AUD 980 per site. Therefore habitat manipulation was cost-effective and is a viable startegy for the control of rodent damage in Australian macadamia orchard systems.

Distilled technical cashew nut shell liquid (DT-CNSL) as an effective biofuel and additive to stabilize triglyceride biofuels in diesel

We report distilled technical cashew nut shell liquid (DT-CNSL) as a non-transesterified biofuel and also as an additive to convert triglycerides to biofuel, without the need for the formation of methyl esters. DT-CNSL blends of diesel obey physico-chemical parameters of diesel. DT-CNSL offers stability to blends of straight vegetable oil (SVO) and tallow oil in diesel. Fluorescence studies using charge transfer probes show that the blend of DT-CNSL, triglycerides and diesel is a uniform solution, and fluorescence behavior is similar to that of diesel. The economics for the cultivation of cashew (Anacardium occidentale), its industrial use and rich carbon sink properties indicate that DT-CNSL could complement or replace traditional biodiesel crops like Jatropha and improve income for farmers. © 2014 Elsevier Ltd.

Effect of a weight-loss program on mental stress-induced cardiovascular responses and recovery

Objective: We assessed the effect of weight loss on blood pressure (BP) and pulse rate during rest, psychological stress, and recovery after stress.

Methods: Two groups of men completed two mental stress tests 12 wk apart. The control group continued their usual diet, whereas the weight-loss group underwent a dietary weight-loss program in which they were randomized to a high-fruit/vegetable and low-fat dairy diet or a low-fat diet.

Results: Fifty-five men with a baseline BP of 125.9 ± 6.9/83.6 ± 7.1 mmHg (mean ± SD) completed the study (weight-loss group, n = 28; control group, n = 27). The weight-loss group lost weight (mean ± SEM, −4.3 ± 0.3 versus +0.4 ± 0.4 kg, P = 0.001) compared with controls and had a significant decrease in resting systolic BP (SBP; −2.0 ± 1.1% versus +2.0 ± 1.1%, P < 0.05). There was a greater decrease in SBP (P < 0.05) and pulse rate (P < 0.05) at all time points during the stress test in the weight loss compared with the control group. At week 12, SBP in 23 (82%) subjects in the weight-loss group and 24 (89%) in the control group returned to resting levels, with recovering levels in the weight-loss group returning to resting levels 6.1 ± 2.6 min earlier than in the control group (P < 0.05). There was an overall greater decrease in diastolic BP (DBP; P < 0.05) and DBP during recovery up to 27 min after stress (P < 0.05) in the high-fruit/vegetable and low-fat dairy diet group (n = 14) compared with the low-fat diet group (n = 14).

Conclusion: A 5% loss of weight decreased BP during rest and returned SBP to resting levels faster, thus decreasing the period of increased BP as a result of mental stress, which is likely to lower the risk of cardiovascular disease in the long term.

Relationship between stress, eating behavior and obesity

Stress is thought to influence human eating behavior and has been examined in animal and human studies. Our understanding of the stress-eating relation is confounded by limitations inherent in the study designs; however, we can make some tentative conclusions that support the notion that stress can influence eating patterns in humans. Stress appears to alter overall food intake in two ways, resulting in under- or overeating, which may be influenced by stressor severity. Chronic life stress seems to be associated with a greater preference for energy- and nutrient-dense foods, namely those that are high in sugar and fat. Evidence from longitudinal studies suggests that chronic life stress may be causally linked to weight gain, with a greater effect seen in men. Stress-induced eating may be one factor contributing to the development of obesity. Future studies that measure biological markers of stress will assist our understanding of the physiologic mechanism underlying the stress-eating relation and how stress might be linked to neurotransmitters and hormones that control appetite.

Increased probiotic yogurt or resistant starch intake does not affect isoflavone bioavailability in subjects consuming a high soy diet

Objective - Probiotics and prebiotics that affect gut microflora balance and its associated enzyme activity may contribute to interindividual variation in isoflavone absorption after soy intake, possibly enhancing isoflavone bioavailability. This study examined the effects of the consumption of bioactive yogurt (a probiotic) or resistant starch (a known prebiotic) in combination with high soy intake on soy isoflavone bioavailability.

Methods - Using a crossover design, chronic soy consumption was compared with soy plus probiotic yogurt or resistant starch in older male and postmenopausal females (n = 31). Isoflavone bioavailability was assessed at the beginning and end of each 5-wk dietary period by sampling plasma and urine after a standardized soy meal.

Results - Chronic soy intake did not significantly affect plasma or urinary isoflavones after the soy meal and there were no significant effects of probiotic or resistant starch treatment. However, there were trends for increased circulating plasma daidzein and genistein after the probiotic treatment and for increased plasma daidzein and genistein 24 h after soy intake with resistant starch treatment. Neither treatment induced or increased equol production, although there was a trend for increased plasma equol in “equol-positive” subjects (n = 12) after probiotic treatment.

Conclusion - The weak or absence of effects of probiotic yogurt or resistant starch supplement to a chronic soy diet suggests that gut microflora were not modified in a manner that significantly affected isoflavone bioavailability or metabolism.

Food security measurement in cultural pluralism : missing the point or conceptual misunderstanding?

Objective : Food Security has become a global concern, yet its measurement has varied considerably across disciplines and countries. We examined the current discrepancies in the definitions of food security and propose a framework for understanding and measuring food security.

Methods : This conceptual review draws from a range of works published in Medline and the gray literature to advance the understanding of food security concepts. We begin by examining the historical background of food security and then move on to examine its various definitions and interpret food through cultural lenses in terms of food access and utilization. We finish by examining various measurements and indicators of food security and reviewing implications for public health.

Results : We argue that the reliance on coping strategies as surrogate measurements of food insecurity without taking into account the social, cultural, and political contexts in which they occur is misleading, and viewing food insecurity solely from a food access or availability perspective, without taking into account food utilization and asset creation as pillars of food security, paints an incomplete picture. Although this review does not claim to provide solutions to the discrepancies in the conceptual definition of food security, it attempts to highlights areas of concern and provide a way forward.

Conclusion : When coping strategies are used as an indicator of food insecurity, they need to be culturally relevant and focus tested, and together with objective measurements of nutritional outcomes, would allow policy makers to make evidence-based decisions to inform social and nutrition policies.

Learning from large data : bias, variance, sampling, and learning curves

One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.

Experimental stress analysis of a steel light truck wheel

The development of a new automotive wheel requires extensive testing and possible design changes. The wheel investigated had three major changes during development. These three designs were subjected to a stress analysis, by experimental methods, to allow a comparison to be made between each design. The experimental program tested the wheels under conditions designed to simulate the loading of the front wheels whilst cornering. A loading frame was built for this purpose and all testing was performed statically by multiple loading for different directions of bending moment. Brittle lacquer coatings were used on each wheel to highlight high strain areas and indicate optimum locations for the placement of strain gauges. The strain gauges were then used to evaluate the strains. Wheel stud loads were also monitored via strain gauges applied to two of the wheel studs. All data was stored on magnetic tapes and the stress analysis performed by means of a minicomputer. The results of the stress analysis showed quantitatively the improvement in design from the first to the third wheel design. The analysis of the stud loads and their variation during loading indicated the optimum wheel mounting face geometry to ensure nut loosening would not occur in service.

Solar thermal drying of canarium indicum nuts

Many situations exist in rural areas of developing countries where the help of simple technology can make substantial positive impacts on living conditions, finance, and in this case; sustainability. In the Melanesia region, there are numerous areas identified as needing improvement, including indigenous food preservation which will be addressed with a proposed solar thermal solution utilizing locally available materials as much as possible for low cost local construction. The current knowledge of the drying requirements for the product chosen in this study is quite limited. However, it is believed that solar thermal drying might be feasible for the remote sunny regions as in Melanesia. This paper describes the processes involved in determining the drying parameters of the Canarium indicum nut, and the proposed solar dryer designs that have been considered for the particular environmental conditions and product specifications. Through the selection process, a mixed mode, low-tunnel solar dryer was chosen as the best match to satisfy the different parameters.