Germin and germin-like proteins: evolution, structure, and function

Germin and germin-like proteins (GLPs) are encoded by a family of genes found in all plants. They are part of the cupin superfamily of biochemically diverse proteins, a superfamily that has a conserved tertiary structure, though with limited similarity in primary sequence. The subgroups of GLPs have different enzyme functions that include the two hydrogen peroxide-generating enzymes, oxalate oxidase (OxO) and superoxide dismutase. This review summarizes the sequence and structural details of GLPs and also discusses their evolutionary progression, particularly their amplification in gene number during the evolution of the land plants. In terms of function, the GLPs are known to be differentially expressed during specific periods of plant growth and development, a pattern of evolutionary subfunctionalization. They are also implicated in the response of plants to biotic (viruses, bacteria, mycorrhizae, fungi, insects, nematodes, and parasitic plants) and abiotic (salt, heat/cold, drought, nutrient, and metal) stress. Most detailed data come from studies of fungal pathogenesis in cereals. This involvement with the protection of plants from environmental stress of various types has led to numerous plant breeding studies that have found links between GLPs and QTLs for disease and stress resistance. In addition the OxO enzyme has considerable commercial significance, based principally on its use in the medical diagnosis of oxalate concentration in plasma and urine. Finally, this review provides information on the nutritional importance of these proteins in the human diet, as several members are known to be allergenic, a feature related to their thermal stability and evolutionary connection to the seed storage proteins, also members of the cupin superfamily.

Parallel Monte Carlo algorithms for information retrieval

In any data mining applications, automated text and text and image retrieval of information is needed. This becomes essential with the growth of the Internet and digital libraries. Our approach is based on the latent semantic indexing (LSI) and the corresponding term-by-document matrix suggested by Berry and his co-authors. Instead of using deterministic methods to find the required number of first "k" singular triplets, we propose a stochastic approach. First, we use Monte Carlo method to sample and to build much smaller size term-by-document matrix (e.g. we build k x k matrix) from where we then find the first "k" triplets using standard deterministic methods. Second, we investigate how we can reduce the problem to finding the "k"-largest eigenvalues using parallel Monte Carlo methods. We apply these methods to the initial matrix and also to the reduced one. The algorithms are running on a cluster of workstations under MPI and results of the experiments arising in textual retrieval of Web documents as well as comparison of the stochastic methods proposed are presented. (C) 2003 IMACS. Published by Elsevier Science B.V. All rights reserved.

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Livelihood diversification and the expansion of artisanal mining in rural Tanzania: drivers and policy implications

This paper provides an extended analysis of livelihood diversification in rural Tanzania, with special emphasis on artisanal and small-scale mining (ASM). Over the past decade, this sector of industry, which is labour-intensive and comprises an array of rudimentary and semi-mechanized operations, has become an indispensable economic activity throughout Sub-Saharan Africa, providing employment to a host of redundant public sector workers, retrenched large-scale mine labourers and poor farmers. In many of the region’s rural areas, it is overtaking subsistence agriculture as the primary industry. Such a pattern appears to be unfolding within the Morogoro and Mbeya regions of southern Tanzania, where findings from recent research suggest that a growing number of smallholder farmers are turning to ASM for employment and financial support. It is imperative that national rural development programmes take this trend into account and provide support to these people.

Howard Barker’s ‘monstrous assaults’: eroticism, death and the antique text

Howard Barker is a writer who has made several notable excursions into what he calls ‘the charnel house…of European drama.’ David Ian Rabey has observed that a compelling property of these classical works lies in what he calls ‘the incompleteness of [their] prescriptions’, and Barker’s Women Beware Women (1986), Seven Lears (1990) and Gertrude: The Cry (2002), are in turn based around the gaps and interstices found in Thomas Middleton’s Women Beware Women (c1627), Shakespeare’s King Lear (c1604) and Hamlet (c1601) respectively. This extends from representing the missing queen from King Lear, who Barker observes, ‘is barely quoted even in the depths of rage or pity’, to his new ending for Middleton’s Jacobean tragedy and the erotic revivification of Hamlet’s mother. This paper will argue that each modern reappropriation accentuates a hidden but powerful feature in these Elizabethan and Jacobean plays – namely their clash between obsessive desire, sexual transgression and death against the imposed restitution of a prescribed morality. This contradiction acts as the basis for Barker’s own explorations of eroticism, death and tragedy. The paper will also discuss Barker’s project for these ‘antique texts’, one that goes beyond what he derisively calls ‘relevance’, but attempts instead to recover ‘smothered genius’, whereby the transgressive is ‘concealed within structures that lend an artificial elegance.’ Together with Barker’s own rediscovery of tragedy, the paper will assert that these rewritings of Elizabethan and Jacobean drama expose their hidden, yet unsettling and provocative ideologies concerning the relationship between political corruption / justice through the power of sexuality (notably through the allure and danger of the mature woman), and an erotics of death that produces tragedy for the contemporary age.

Adaptive modelling, estimation and fusion from data: a neurofuzzy approach

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input. This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

Selecting from amongst non–nested conditional variance models: information criteria and portfolio determination

We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.

The data-mining of studies database 'HHdbIV'

This article clarifies what was done with the sub-7-man positions in data-mining Harold van der Heijden's 'HHdbIV' database of chess studies prior to its publication. It emphasises that only positions in the main lines of studies were examined and that the information about uniqueness of move was not incorporated in HHdbIV. There is some reflection on the separate technical and artistic dimensions of study evaluation.

Maternally expressed gene1 is a novel maize endosperm transfer cell-specific gene with a maternal parent-of-origin pattern of expression

Growth of the maize (Zea mays) endosperm is tightly regulated by maternal zygotic and sporophytic genes, some of which are subject to a parent-of-origin effect. We report here a novel gene, maternally expressed gene1 (meg1), which shows a maternal parent-of-origin expression pattern during early stages of endosperm development but biallelic expression at later stages. Interestingly, a stable reporter fusion containing the meg1 promoter exhibits a similar pattern of expression. meg1 is exclusively expressed in the basal transfer region of the endosperm. Further, we show that the putatively processed MEG1 protein is glycosylated and subsequently localized to the labyrinthine ingrowths of the transfer cell walls. Hence, the discovery of a parent-of-origin gene expressed solely in the basal transfer region opens the door to epigenetic mechanisms operating in the endosperm to regulate certain aspects of nutrient trafficking from the maternal tissue into the developing seed.

How Twitter is studied in the medical professions: a classification of Twitter papers indexed in PubMed

Background: Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. // Objective: This paper aims to identify published work relating to Twitter indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Limiting the study to papers indexed by PubMed ensures the work provides a reproducible benchmark. // Methods: Papers, indexed by PubMed, on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain and aspect. // Results: As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focussed on Twitter (the others referring to it tangentially). The early Twitter focussed papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. // Conclusions: This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used five dimensions to categorise published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research relating to Twitter in the area of medicine and beyond, can position and ground their work.

Direct evidence for attention-dependent influences of the frontal eye-fields on feature-responsive visual cortex

Voluntary selective attention can prioritize different features in a visual scene. The frontal eye-fields (FEF) are one potential source of such feature-specific top-down signals, but causal evidence for influences on visual cortex (as was shown for "spatial" attention) has remained elusive. Here, we show that transcranial magnetic stimulation (TMS) applied to right FEF increased the blood oxygen level-dependent (BOLD) signals in visual areas processing "target feature" but not in "distracter feature"-processing regions. TMS-induced BOLD signals increase in motion-responsive visual cortex (MT+) when motion was attended in a display with moving dots superimposed on face stimuli, but in face-responsive fusiform area (FFA) when faces were attended to. These TMS effects on BOLD signal in both regions were negatively related to performance (on the motion task), supporting the behavioral relevance of this pathway. Our findings provide new causal evidence for the human FEF in the control of nonspatial "feature"-based attention, mediated by dynamic influences on feature-specific visual cortex that vary with the currently attended property.

‘Cursed’ communities? Corporate Social Responsibility (CSR), company towns and the mining industry in Namibia

This article examines Corporate Social Responsibility (CSR) and mining community development, sustainability and viability. These issues are considered focussing on current and former company-owned mining towns in Namibia. Historically company towns have been a feature of mining activity in Namibia. However, the fate of such towns upon mine closure has been and remains controversial. Declining former mining communities and even ghost mining towns can be found across the country. This article draws upon research undertaken in Namibia and considers these issues with reference to three case study communities. This article examines the complexities which surround decision-making about these communities, and the challenges faced in efforts to encourage their sustainability after mining. In this article, mine company engagements through CSR with the development, sustainability and viability of such communities are also critically discussed. The role, responsibilities, and actions of the state in relation to these communities are furthermore reflected upon. Finally, ways forward for these communities are considered.