Briefing: Factored material properties and limit state loads-unlikely extreme or impossible pretense

In the limit state design (LSD) method each design criterion is formally stated and assessed using a performance function. The performance function defines the relationship between the design parameters and the design criterion. In practice, LSD involves factoring up loads and factoring down calculated strengths and material parameters. This provides a convenient way to carry out routine probabilistic-based design. The factors are statistically calculated to produce a design with an acceptably low probability of failure. Hence the ultimate load and the design material properties are mathematical concepts that have no physical interpretation. They may be physically impossible. Similarly, the appropriate analysis model is also defined by the performance function and may not describe the real behaviour at the perceived physical equivalent limit condition. These points must be understood to avoid confusion in the discussion and application of partial factor LSD methods.

The Antarctic nemertean Parborlasia corrugatus: an example of an extreme oxyconformer

The Antarctic nemertean worm, Parborlasia corrugatus, exhibits gigantism, reaching at least 100 g, yet lacks any specialised respiratory organs. The diffusion of oxygen into this worm occurs cutaneously. We examined the metabolic rate of P. corrugatus at -1degreesC in response to decreasing ambient PO2. As the PO2 of the water decreased. so did the metabolic rate of P. corrugatus, indicating that this nemertean worm is an extreme example of an oxyconformer. When the water PO2 decreased below about 120 mmHg, the normally short, round worms became elongated and extremely flattened. This behavioural mechanism would allow for an increase in surface area of the skin, thereby facilitating the diffusion of oxygen.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

Structure of thermolysin cleaved microcin J25: Extreme stability of a two-chain antimicrobial peptide devoid of covalent links

sThe structure of a two-chain peptide formed by the treatment of the potent antimicrobial peptide microcin J25 (MccJ25) with thermolysin has been characterized by NMR spectroscopy and mass spectrometry. The native peptide is 21 amino acids in size and has the remarkable structural feature of a ring formed by linkage of the side chain of Glu8 to the N-terminus that is threaded by the C-terminal tail of the peptide. Thermolysin cleaves the peptide at the Phe10-Val11 amide bond, but the threading of the C-terminus through the N-terminal ring is so tight that the resultant two chains remain associated both in the solution and in the gas phases. The three-dimensional structure of the thermolysin-cleaved peptide derived using NMR spectroscopy and simulated annealing calculations has a well-defined core that comprises the N-terminal ring and the threading C-terminal tail. In contrast to the well-defined core, the newly formed termini at residues Phe10 and Val11 are disordered in solution. The C-terminal tail is associated to the ring both by hydrogen bonds stabilizing a short beta-sheet and by hydrophobic interactions. Moreover, unthreading of the tail through the ring is prevented by the bulky side chains of Phe19 and Tyr20, which flank the octapeptide ring. This noncovalent two-peptide complex that has a remarkable stability in solution and in highly denaturing conditions and that survives in the gas phase is the first example of such a two-chain peptide lacking disulfide or interchain covalent bonds.

The association between early minor motor difficulties in extreme low birth weight infants and school age attentional difficulties

Introduction: Extremely premature infants of normal intellectual ability have an increased prevalence of motor and attentional difficulties. Knowledge of the relationship between early motor difficulties and measures of attention at school age would enhance understanding of these developmental pathways, their interrelationship and opportunities for intervention. Objective: This study examines whether an association exists between early findings of minor motor difficulties and school age clinical and psychometric measures of attention. Methodology: 45/60 eligible ELBW(1000 g) or preterm (< 27/40 gestation) infants born at the Mater Mother's Hospital were assessed at 12 and 24 months for minor motor deficits (using NSMDA) and at 7-9 years for attention, using clinical (Conners and Du Paul Rating Scales) and psychometric (assessing attention span, selective and divided attention) measures. Results: NSMDA at 12 months was only associated with the psychometric measures of verbal attention span. It was not associated with later clinical measures of attention. NSMDA at 24months was strongly associated with specific clinical measures of attention at school age, independent of biological and social factors. It was not associated with psychometric measures of attention. Conclusion: The major finding of this study is that motor difficulties in ELBW infants at 2 years are associated with later clinical measures of attention. Possible mechanisms underlying this relationship are considered. Crown Copyright (c) 2005 Published by Elsevier Ireland Ltd. All rights reserved.

Using extreme value theory to measure value-at-risk for daily electricity spot prices

The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Genetic and environmental influences on extreme personality dispositions in adolescent female twins

Background: The objective was to determine whether the pattern of environmental and genetic influences on deviant personality scores differs from that observed for the normative range of personality, comparing results in adolescent and adult female twins. Methods: A sample of 2,796 female adolescent twins ascertained from birth records provided Junior Eysenck Personality Questionnaire data. The average age of the sample was 17.0 years ( S. D. 2.3). Genetic analyses of continuous and extreme personality scores were conducted. Results were compared for 3,178 adult female twins. Results: Genetic analysis of continuous traits in adolescent female twins were similar to findings in adult female twins, with genetic influences accounting for between 37% and 44% of the variance in Extraversion (Ex), Neuroticism (N), and Social Non-Conformity (SNC), with significant evidence of shared environmental influences (19%) found only for SNC in the adult female twins. Analyses of extreme personality characteristics, defined categorically, in the adolescent data and replicated in the adult female data, yielded estimates for high N and high SNC that deviated substantially (p < .05) from those obtained in the continuous trait analyses, and provided suggestive evidence that shared family environment may play a more important role in determining personality deviance than has been previously found when personality is viewed continuously. However, multiple-threshold models that assumed the same genetic and environmental determinants of both normative range variation and extreme scores gave acceptable fits for each personality dimension. Conclusions: The hypothesis of differences in genetic or environmental factors responsible for N and SNC among female twins with scores in the extreme versus normative ranges was partially supported, but not for Ex.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Extreme learning machine for predicting HLA-peptide binding

Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.

Some like it wet - biological characteristics underpinning tolerance of extreme water stress events in Antarctic bryophytes

Antarctic bryophyte communities presently tolerate physiological extremes in water availability, surviving both desiccation and submergence events. We investigated the relative ability of three Antarctic moss species to tolerate physiological extremes in water availability and identified physiological, morphological, and biochemical characteristics that assist species performance under such conditions. Tolerance of desiccation and submergence was investigated using chlorophyll fluorescence during a series of field- and laboratory-based water stress events. Turf water retention and degree of natural habitat submergence were determined from gametophyte shoot size and density, and delta C-13 signatures, respectively. Finally, compounds likely to assist membrane structure and function during desiccation events (fatty acids and soluble carbohydrates) were determined. The results of this study show significant differences in the performance of the three study species under contrasting water stress events. The results indicate that the three study species occupy distinctly different ecological niches with respect to water relations, and provide a physiological explanation for present species distributions. The poor tolerance of submergence seen in Ceratodon purpureus helps explain its restriction to drier sites and conversely, the low tolerance of desiccation and high tolerance of submergence displayed by the endemic Grimmia antarctici is consistent with its restriction to wet habitats. Finally the flexible response observed for Bryum pseudotriquetrum is consistent with its co-occurrence with the other two species across the bryophyte habitat spectrum. The likely effects of future climate change induced shifts in water availability are discussed with respect to future community dynamics.

Space efficient quantile summary for constrained sliding windows on a data stream

In many online applications, we need to maintain quantile statistics for a sliding window on a data stream. The sliding windows in natural form are defined as the most recent N data items. In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding windows. Our algorithm makes one pass on the data stream and maintains an E-approximate summary. It uses O((1)/(epsilon2) log(2) epsilonN) space where N is the number of data items in the window. We extend this framework to further process generalized constrained sliding window queries and proved that our technique is applicable for flexible window settings. Our performance study indicates that the space required in practice is much less than the given theoretical bound and the algorithm supports high speed data streams.

Moomba - A collaborative environment for supporting distributed extreme programming in global software development

Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.