Sensory acceptability of foods containing Australian sweet lupin (Lupinus angustifolius) flour

Foods containing Australian sweet lupin (Lupinus angustifolius) flour (ASLF) were assessed by consumer panelists (n= 54) in comparison to wheat flour (control) and defatted soy flour (DFSF) products. All ASLF products were rated in the acceptable half of the evaluation scale. General acceptability of ASLF chocolate chip cookies and breakfast bars was rated similarly to the control and DFSF variants (P > 0.05). ASLF pasta was rated lower than control but higher than DFSF pasta (P < 0.05), whereas ASLF addition reduced the general acceptability of muffins and bread (P < 0.05) compared with the other variants. Some ASLF products appeared palatable whereas ASLF incorporation rate in others requires reduction.

Modeling the tensile behavior of fiber bundles with irregular constituent fibers

In this paper, the effect of fiber dimensional irregularities on the tensile behavior of fiber bundles is modeled, using the finite element method (FEM). Fiber dimensional irregularities are simulated with sine waves of different magnitude. The specific stress-strain curves of fiber bundles and the constituent single fibers are obtained and compared. The results indicate that fiber diameter irregularity along fiber length has a significant effect on the tensile behavior of the fiber bundle. For a bundle of uniform fibers of different diameters, all constituent fibers will break simultaneously regardless of the fiber diameter. Similarly, if fibers within a bundle have the same pattern and level of diameter irregularity along fiber length, the fibers will break at the same time also regardless of the difference in average diameter of each fiber. In these cases, the specific stress and strain curve for the bundle overlaps with that of the constituent fibers. When the fiber bundle consists of single fibers with different levels of diameter irregularity, the specific stress-strain and load-elongation curves of the fiber bundle exhibit a stepped or “ladder” shape. The fiber with the highest irregularity breaks first, even when the thinnest section of the fiber is still coarser than the diameter of a very thin but uniform fiber in the bundle. This study suggests that fiber diameter irregularity along fiber length is a more important factor than the fiber diameter itself in determining the tensile behavior of a fiber bundle consisting of irregular fibers.

Australian sweet lupin flour addition reduces the glycaemic index of a white bread breakfast without affecting palatability in healthy human volunteers

The addition of some legume ingredients to bread has been associated with effects on glycaemic, insulinaemic and satiety responses that may be beneficial in controlling type 2 diabetes, cardiovascular disease and obesity. However, the effect of Australian sweet lupin (Lupinus angustifolius) flour (ASLF) is unknown. This investigation examined the effect of adding ASLF to standard white bread on post-meal glycaemic, insulinaemic and satiety responses and palatability in healthy subjects. Using a randomised, single-blind, cross-over design, 11 subjects consumed one breakfast of ASLF bread and two of standard white bread ≥ 7 days apart after fasting overnight. Each breakfast also included margarine, jam, and tea with milk and contained 50g available carbohydrate. On each test day, blood samples were taken after fasting, then several times over 2 hours post-prandially, and analysed for plasma glucose and serum insulin. Subjects rated breakfast palatability and perception of satiety, in the fasting state and over 3 hours post-prandially, after which food intake from an ad libitum buffet and for the rest of the day was recorded. Incremental areas under the curves for glucose, insulin and satiety, glycaemic index, insulinaemic index and satiety index were calculated. ASLF addition to the breakfast reduced its glycaemic index (mean ± SEM; ASLF bread breakfast = 74.0 ± 9.6. Standard white bread breakfast = 100, P=0.022), raised its insulinaemic index (ASLF bread breakfast = 127.7 ± 12.0. Standard white bread breakfast = 100, P=0.046), but did not affect palatability, satiety or food intake. ASLF addition resulted in a palatable breakfast; however, the potential benefits of the lowered glycaemic index may be eclipsed by the increased insulinaemic index.

The hairiness of worsted wool and cashmere yarns and the impact of fiber curvature on hairiness

In this study, a range of carefully selected wool and cashmere yarns as well as their blends were used to examine the effects of fiber curvature and blend ratio on yarn hairiness. The results indicate that yarns spun from wool fibers with a higher curvature have lower yarn hairiness than yarns spun from similar wool of a lower curvature. For blend yarns made from wool and cashmere of similar diameter, yarn hairiness increases with the increase in the cashmere content in the yarn. This is probably due to the presence of increased proportion of the shorter cashmere fibers in the surface regions of the yarn, leading to increased yarn hairiness. A modified hairiness composition model is used to explain these results and the likely origin of leading and trailing hairs. This model highlights the importance of yarn surface composition on yarn hairiness.

Flexural characteristics of coir fiber reinforced cementitious composites

This study has examined the flexural properties of natural and chemically modified coir fiber reinforced cementitious composites (CFRCC). Coir fibers of two different average lengths were used, and the longer coir fibers were also treated with a 1 % NaOH solution for comparison. The fibers were combined with cementitious materials and chemical agents (dispersant, defoamer or wetting agent) to form CFRCC. The flexural properties of the composites, including elastic stress, flexural strength, toughness and toughness index, were measured. The effects of fiber treatments, addition of chemical agents and accelerated ageing of composites on the composites’ flexural properties were examined. The results showed that the CFRCC samples were 5–12 % lighter than the conventional mortar, and that the addition of coir fibers improved the flexural strength of the CFRCC materials. Toughness and toughness index, which were associated with the work of fracture, were increased more than ten times. For the alkalized long coir fiber composites, a higher immediate and long-term toughness index was achieved. SEM microstructure images revealed improved physicochemical bonding in the treated CFRCC.

Parameter optimization of kernel-based one-class classifier on imbalance learning

Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to learn from unbalanced data set is regarded as the recognition based learning and has shown to have the potential of achieving better performance. Similar to twoclass learning, parameter selection is a significant issue, especially when the classifier is sensitive to the parameters. For one-class learning scheme with the kernel function, such as one-class Support Vector Machine and Support Vector Data Description, besides the parameters involved in the kernel, there is another one-class specific parameter: the rejection rate v. In this paper, we proposed a general framework to involve the majority class in solving the parameter selection problem. In this framework, we first use the minority target class for training in the one-class classification stage; then we use both minority and majority class for estimating the generalization performance of the constructed classifier. This generalization performance is set as the optimization criteria. We employed the Grid search and Experiment Design search to attain various parameter settings. Experiments on UCI and Reuters text data show that the parameter optimized one-class classifiers outperform all the standard one-class learning schemes we examined.

Endurance training in humans leads to fiber type-specific increases in levels of peroxisome proliferator-activated receptor-[gamma] coactivator-1 and peroxisome proliferator-activated receptor-[alpha] in skeletal muscle

The peroxisome proliferator-activated receptor (PPAR)-γ coactivator-1 (PGC-1) can induce mitochondria biogenesis and has been implicated in the development of oxidative type I muscle fibers. The PPAR isoforms α, β/δ, and γ control the transcription of genes involved in fatty acid and glucose metabolism. As endurance training increases skeletal muscle mitochondria and type I fiber content and fatty acid oxidative capacity, our aim was to determine whether these increases could be mediated by possible effects on PGC-1 or PPAR-α, -β/δ, and -γ. Seven healthy men performed 6 weeks of endurance training and the expression levels of PGC-1 and PPAR-α, -β/δ, and -γ mRNA as well as the fiber type distribution of the PGC-1 and PPAR-α proteins were measured in biopsies from their vastus lateralis muscle. PGC-1 and PPAR-α mRNA expression increased by 2.7- and 2.2-fold (P < 0.01), respectively, after endurance training. PGC-1 expression was 2.2- and 6-fold greater in the type IIa than in the type I and IIx fibers, respectively. It increased by 2.8-fold in the type IIa fibers and by 1.5-fold in both the type I and IIx fibers after endurance training (P < 0.015). PPAR-α was 1.9-fold greater in type I than in the II fibers and increased by 3.0-fold and 1.5-fold in these respective fibers after endurance training (P < 0.001). The increases in PGC-1 and PPAR-α levels reported in this study may play an important role in the changes in muscle mitochondria content, oxidative phenotype, and sensitivity to insulin known to be induced by endurance training.

Flowchart and kernel software for modular robot

Flowcharting is a common method of setting out the requirements for a piece of code. It is simple with few rules to follow. Rarely however, s it used as the code itself. This paper describes the outline of a software package that uses the flowchart as the code for a small, autonomous, modular robot, designed for use in High Schools. It also describe the code used by the robot to complement the flowchart software creating a system that can be used by students and their teachers to design, build and program a robot without previous programming experience.

An autonomous trimming system of large glass fiber reinforced plastics parts using an omni-directional mobile robot and its control

This paper describes an automated trimming system of large glass fiber reinforced plastic (GFRP) using an omni-directional wheeled mobile robot (WMR) and its path control method. In trimming GFRP parts, much glass fiber and plastic powder dust occur and it becomes bad visible in environment. It is necessary to correct dead-reckoning errors of the WMR in order to control its moving path. We have discussed an external correction method of the dead-reckoning errors for the WMR using ultrasonic sensor.

Manufacturing influence on the delamination fracture behavior of the T800H/3900-2 carbon fiber reinforced polymer composites

'Torayca' T800H/3900-2 is the first material qualified on Boeing Material Specification (BMS 8-276) which utilizes the thermoplastic-particulate interlayer toughening technology. Two manufacturing processes, the autoclave process and the fast heating rated Quickstep™ process, were employed to cure this material. The Quickstep process is a unique composite production technology which utilizes the fast heat transfer rate of fluid to heat and cure polymer composite components. The manufacturing influence on the mode I delamination fracture toughness of laminates was investigated by performing double cantilever beam tests. The composite specimens fabricated by two processes exhibited dissimilar delamination resistance curves (R-curves) under mode I loading. The initial value of fracture toughness GIC-INIT was 564 J/m2 for the autoclave specimens and 527 J/m2 for the Quickstep specimens. However, the average propagation fracture toughness GIC-PROP was 783 J/m2 for the Quickstep specimens, which was 2.6 times of that for the autoclave specimens. The mechanism of fracture occurred during delamination was studied under scanning electron microscope (SEM). Three types of fracture were observed: the interlayer fracture, the interface fracture, and the intralaminar fracture. These three types of fracture played different roles in affecting the delamination resistance curves during the crack growth. More fiber bridging was found in the process of delamination for the Quickstep specimens. Better fiber/matrix adhesion was found in the Quickstep specimens by conducting indentation-debond tests.

Kernel-based naive bayes classifier for breast cancer prediction

The classification of breast cancer patients is of great importance in cancer diagnosis. Most classical cancer classification methods are clinical-based and have limited diagnostic ability. The recent advances in machine learning technique has made a great impact in cancer diagnosis. In this research, we develop a new algorithm: Kernel-Based Naive Bayes (KBNB) to classify breast cancer tumor based on memography data. The performance of the proposed algorithm is compared with that of classical navie bayes algorithm and kernel-based decision tree algorithm C4.5. The proposed algorithm is found to outperform in the both cases. We recommend the proposed algorithm could be used as a tool to classify the breast patient for early cancer diagnosis.

Microarray data classification using automatic SVM kernel selection

Microarray data classification is one of the most important emerging clinical applications in the medical community. Machine learning algorithms are most frequently used to complete this task. We selected one of the state-of-the-art kernel-based algorithms, the support vector machine (SVM), to classify microarray data. As a large number of kernels are available, a significant research question is what is the best kernel for patient diagnosis based on microarray data classification using SVM? We first suggest three solutions based on data visualization and quantitative measures. Different types of microarray problems then test the proposed solutions. Finally, we found that the rule-based approach is most useful for automatic kernel selection for SVM to classify microarray data.

UCP3 protein expression is lower in type I, IIa and IIx muscle fiber types of endurance-trained compared to untrained subjects

Uncoupling protein 3 (UCP3) is a muscle mitochondrial protein believed to uncouple the respiratory chain, producing heat and reducing aerobic ATP production. Our aim was to quantify and compare the UCP3 protein levels in type I, IIa and IIx skeletal muscle fibers of endurance-trained (Tr) and healthy untrained (UTr) individuals. UCP3 protein content was quantified using Western blot and immunofluorescence. Skeletal muscle fiber type was determined by both an enzymatic ATPase stain and immunofluorescence. UCP3 protein expression measured in skeletal muscle biopsies was 46% lower ( P=0.01) in the Tr compared to the UTr group. UCP3 protein expression in the different muscle fibers was expressed as follows; IIx>IIa>I in the fibers for both groups ( P<0.0167) but was lower in all fiber types of the Tr when compared to the UTr subjects ( P<0.001). Our results show that training status did not change the skeletal muscle fiber hierarchical UCP3 protein expression in the different fiber types. However, it affected UCP3 content more in type I and type IIa than in the type IIx muscle fibers. We suggest that this decrease may be in relation to the relative improvement in the antioxidant defense systems of the skeletal muscle fibers and that it might, as a consequence, participate in the training induced improvement in mechanical efficiency.