Reducing acrylamide precursors in raw materials derived from wheat and potato

A review of agronomic and genetic approaches as strategies for the mitigation of acrylamide risk in wheat and potato is presented. Acrylamide is formed through the Maillard reaction during high-temperature cooking, such as frying, roasting, or baking, and the main precursors are free asparagine and reducing sugars. In wheat flour, acrylamide formation is determined by asparagine levels and asparagine accumulation increases dramatically in response to sulfur deprivation and, to a much lesser extent, with nitrogen feeding. In potatoes, in which sugar concentrations are much lower, the relationships between acrylamide and its precursors are more complex. Much attention has been focused on reducing the levels of sugars in potatoes as a means of reducing acrylamide risk. However, the level of asparagine as a proportion of the total free amino acid pool has been shown to be a key parameter, indicating that when sugar levels are limiting, competition between asparagine and the other amino acids for participation in the Maillard reaction determines acrylamide formation. Genetic approaches to reducing acrylamide risk include the identification of cultivars; and other germplasm in which free asparagine and/or sugar levels are low and the manipulation of genes involved in sugar and amino acid metabolism and signaling. These approaches are made more difficult by genotype/ environment interactions that can result in a genotype being "good" in one environment but "poor" in another. Another important consideration is the effect that any change could have on flavor in the cooked product. Nevertheless, as both wheat and potato are regarded as of relatively high acrylamide risk compared with, for example, maize and rice, it is essential that changes are achieved that mitigate the problem.

Sparse multioutput radial basis function network construction using combined locally regularised orthogonal least square and D-optimality experimental design

A construction algorithm for multioutput radial basis function (RBF) network modelling is introduced by combining a locally regularised orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximised model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious RBF network model with excellent generalisation performance. The D-optimality design criterion enhances the model efficiency and robustness. A further advantage of the combined approach is that the user only needs to specify a weighting for the D-optimality cost in the combined RBF model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design

The note proposes an efficient nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious model with excellent generalization performance. The D-optimality design criterion further enhances the model efficiency and robustness. An added advantage is that the user only needs to specify a weighting for the D-optimality cost in the combined model selecting criterion and the entire model construction procedure becomes automatic. The value of this weighting does not influence the model selection procedure critically and it can be chosen with ease from a wide range of values.

Fully complex-valued radial basis function networks: orthogonal least squares regression and classification

We consider a fully complex-valued radial basis function (RBF) network for regression and classification applications. For regression problems, the locally regularised orthogonal least squares (LROLS) algorithm aided with the D-optimality experimental design, originally derived for constructing parsimonious real-valued RBF models, is extended to the fully complex-valued RBF (CVRBF) network. Like its real-valued counterpart, the proposed algorithm aims to achieve maximised model robustness and sparsity by combining two effective and complementary approaches. The LROLS algorithm alone is capable of producing a very parsimonious model with excellent generalisation performance while the D-optimality design criterion further enhances the model efficiency and robustness. By specifying an appropriate weighting for the D-optimality cost in the combined model selecting criterion, the entire model construction procedure becomes automatic. An example of identifying a complex-valued nonlinear channel is used to illustrate the regression application of the proposed fully CVRBF network. The proposed fully CVRBF network is also applied to four-class classification problems that are typically encountered in communication systems. A complex-valued orthogonal forward selection algorithm based on the multi-class Fisher ratio of class separability measure is derived for constructing sparse CVRBF classifiers that generalise well. The effectiveness of the proposed algorithm is demonstrated using the example of nonlinear beamforming for multiple-antenna aided communication systems that employ complex-valued quadrature phase shift keying modulation scheme. (C) 2007 Elsevier B.V. All rights reserved.

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Potential energy surface and moleculardynamics of MbNO: existence of an unsuspected FeON minimum

Ligands such as CO, O2, or NO are involved in the biological function of myoglobin. Here we investigate the energetics and dynamics of NO interacting with the Fe(II) heme group in native myoglobin using ab initio and molecular dynamics simulations. At the global minimum of the ab initio potential energy surface (PES), the binding energy of 23.4 kcal/mol and the Fe-NO structure compare well with the experimental results. Interestingly, the PES is found to exhibit two minima: There exists a metastable, linear Fe-O-N minimum in addition to the known, bent Fe-N-O global minimum conformation. Moreover, the T-shaped configuration is found to be a saddle point, in contrast to the corresponding minimum for NO interacting with Fe(III). To use the ab initio results for finite temperature molecular dynamics simulations, an analytical function was fitted to represent the Fe-NO interaction. The simulations show that the secondary minimum is dynamically stable up to 250 K and has a lifetime of several hundred picoseconds at 300 K. The difference in the topology of the heme-NO PES from that assumed previously (one deep, single Fe-NO minimum) suggests that it is important to use the full PES for a quantitative understanding of this system. Why the metastable state has not been observed in the many spectroscopic studies of myoglobin interacting with NO is discussed, and possible approaches to finding it are outlined.

Neuromuscular junction morphology, fiber-type proportions, and satellite-cell proliferation rates are altered in MyoD(-/-) mice

Gene compensation by members of the myogenic regulatory factor (MRF) family has been proposed to explain the apparent normal adult phenotype of MyoD(-/-) mice. Nerve and field stimulation were used to investigate contraction properties of muscle from MyoD(-/-) mice, and molecular approaches were used to investigate satellite-cell behavior. We demonstrate that MyoD deletion results in major alterations in the organization of the neuromuscular junction, which have a dramatic influence on the physiological contractile properties of skeletal muscle. Second, we show that the lineage progression of satellite cells (especially initial proliferation) in the absence of MyoD is abnormal and linked to perturbations in the nuclear localization of beta-catenin, a key readout of canonical Wnt signaling. These results show that MyoD has unique functions in both developing and adult skeletal muscle that are not carried out by other members of the MRF family.

Analysis of disputed single-parent/child and sibling relationships using 16 STR loci

This study describes the validation of short tandem repeat (STR) systems for the resolution of cases of disputed parentage where only a single parent is available for testing or where the claimed relationship of both parents is in doubt and also cases where sibship must be tested. Three separate multiplex systems the Second Generation Multiplex, Powerplex 1.2 and FFFL have been employed, giving a total of 16 STR loci. Both empirical and theoretical approaches to the validation have been adopted. Appropriate equations have been derived to calculate likelihood ratios for different relationships, incorporating a correction for subpopulation effects. An F(ST) point estimate of 1% has been applied throughout. Empirically, 101 cases of alleged father, alleged mother and child where analysed using six SLP systems and also using the three multiplex STR systems. Of the 202 relationships tested, 197 were independently resolved by both systems, providing either clear evidence of non-parentage or strong support for the relationship.

Benchmark datasets for detection and tracking

There is a rising demand for the quantitative performance evaluation of automated video surveillance. To advance research in this area, it is essential that comparisons in detection and tracking approaches may be drawn and improvements in existing methods can be measured. There are a number of challenges related to the proper evaluation of motion segmentation, tracking, event recognition, and other components of a video surveillance system that are unique to the video surveillance community. These include the volume of data that must be evaluated, the difficulty in obtaining ground truth data, the definition of appropriate metrics, and achieving meaningful comparison of diverse systems. This chapter provides descriptions of useful benchmark datasets and their availability to the computer vision community. It outlines some ground truth and evaluation techniques, and provides links to useful resources. It concludes by discussing the future direction for benchmark datasets and their associated processes.

Power, nature and neoliberalism: the political ecology of water in Chile

Since the 1990s, international water sector reforms have centred heavily on economic and market approaches. In regard to water resources management, tradable water rights have been promoted, often supported by the neoliberal model adopted in Chile. Chile's 1981 Water Code was reformed to comprise a system of water rights that could be freely traded with few restrictions. International financial institutions have embraced the Chilean model, claiming that it results in more efficient water use, and potentially fosters social and environmental benefits. However, in Chile the Water Code is deeply contested. It has been criticised for being too permissive and has produced a number of problems in practice. Moreover, attempts to modify it have become the focus of a lengthy polemic debate. This paper employs a political ecology perspective to explore the socio-environmental outcomes of water management in Chile, drawing on a case study of agriculture in the semi-arid Norte Chico. The case illustrates how large-scale farmers exert greater control over water, while peasant farmers have increasingly less access. I argue that these outcomes are facilitated by the mode of water management implemented within the framework of the Water Code. Through this preliminary examination of social equity and the environmental aspects of water resources management in Chile, I suggest that the omission of these issues from the international debates on water rights markets is a cause for concern.

Field study on thermal comfort and adaptive strategies in residential buildings in China

This paper fully describes a nation-wide field study on building thermal environment and thermal comfort of occupant, which was carried out in summer 2005 and in winter 2006 respectively in China, illustrating the adaptive strategies adopted by occupants in domestic buildings in China. According to the climate division in China, the buildings in Beijing (BJ), Shanghai (SH), Wuhan (WH) and Chongqing (CQ), Guangzhou (GZ), Kunming (KM), were selected as targets which are corresponding to cold zone, hot summer and cold winter zone (SWC-SH, WH, CQ), hot summer and warm winter zone and temperate zone, respectively. The methodology used in the field study is the combination of subjective questionnaire regarding thermal sensation and adaptive approaches and physical environmental monitoring including indoor air temperature and relative humidity. A total of 1671 subjects participate in this investigation with more than 80% response rate in all surveyed cities. Both physiological and non-physiological factors (behavioural and psychological adaptations) have been analysed.

Asset allocation, cross-class correlation and the structure of property returns

Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.

Evoked prior learning experience and approach to learning as predictors of academic achievement

Background. In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students’ perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. Aim. To investigate how students’ evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Sample. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. Method. A 77-item questionnaire was used to gather students’ self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. Results. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Conclusions. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching–learning contexts are analysed using multi-variable methods.

New governance approaches to environmental regulation: an example of the Code for Sustainable Homes (CSH)

Environmental policy in the United Kingdom (UK) is witnessing a shift from command-and-control approaches towards more innovation-orientated environmental governance arrangements. These governance approaches are required which create institutions which support actors within a domain for learning not only about policy options, but also about their own interests and preferences. The need for construction actors to understand, engage and influence this process is critical to establishing policies which support innovation that satisfies each constituent’s needs. This capacity is particularly salient in an era where the expanding raft of environmental regulation is ushering in system-wide innovation in the construction sector. In this paper, the Code for Sustainable Homes (the Code) in the UK is used to demonstrate the emergence and operation of these new governance arrangements. The Code sets out a significant innovation challenge for the house-building sector with, for example, a requirement that all new houses must be zero-carbon by 2016. Drawing upon boundary organisation theory, the journey from the Code as a government aspiration, to the Code as a catalyst for the formation of the Zero Carbon Hub, a new institution, is traced and discussed. The case study reveals that the ZCH has demonstrated boundary organisation properties in its ability to be flexible to the needs and constraints of its constituent actors, yet robust enough to maintain and promote a common identity across regulation and industry boundaries.