On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples

We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

Developing an engineering approach for migrating from prescriptive to performance-based specification for concrete

The integral variability of raw materials, lack of awareness and appreciation of the technologies for achieving quality control and lack of appreciation of the micro and macro environmental conditions that the structures will be subjected, makes modern day concreting a challenge. This also makes Designers and Engineers adhere more closely to prescriptive standards developed for relatively less aggressive environments. The data from exposure sites and real structures prove, categorically, that the prescriptive specifications are inadequate for chloride environments. In light of this shortcoming, a more pragmatic approach would be to adopt performance-based specifications which are familiar to industry in the form of specification for mechanical strength. A recently completed RILEM technical committee made significant advances in making such an approach feasible.
Furthering a performance-based specification requires establishment of reliable laboratory and on-site test methods, as well as easy to perform service-life models. This article highlights both laboratory and on-site test methods for chloride diffusivity/electrical resistivity and the relationship between these tests for a range of concretes. Further, a performance-based approach using an on-site diffusivity test is outlined that can provide an easier to apply/adopt practice for Engineers and asset managers for specifying/testing concrete structures.

Developing the digital literacies of academic staff: an institutional approach

Institutional engagement with digital literacies at the University of Brighton has been promoted through the creation of a Digital Literacies Framework (DLF) aimed at academic staff. The DLF consists of 38 literacies divided into four categories that align to the following key areas of academic work: • Learning and teaching • Research • Communication and collaboration • Administration For each literacy, there is an explanation of what the literacy is, why it is important and how to gain it, with links to resources and training opportunities. After an initial pilot, the DLF website was launched in the summer of 2014. This paper discusses the strategic context and policy development of the DLF, its initial conception and subsequent development based on a pilot phase, feedback and evaluation. It critically analyses two of the ways that engagement with the DLF have been promoted: (1) formal professional development schemes and (2) the use of a ‘School-based’ approach. It examines the successes and challenges of the University of Brighton's scheme and makes some suggestions for subsequent steps including taking a course-level approach.

Decentralized control design for nonlinear plants: a v-metric approach

In this paper, a new v-metric based approach is proposed to design decentralized controllers for multi-unit nonlinear plants that admit a set of plant decompositions in an operating space. Similar to the gap metric approach in literature, it is shown that the operating space can also be divided into several subregions based on a v-metric indicator, and each of the subregions admits the same controller structure. A comparative case study is presented to display the advantages of proposed approach over the gap metric approach. (C) 2000 Elsevier Science Ltd. All rights reserved.

Adult starvation and disease-related malnutrition: A proposal for etiology-based diagnosis in the clinical practice setting from the International Consensus Guideline Committee

Background & aims: Multiple definitions for malnutrition syndromes are found in the literature resulting in confusion. Recent evidence suggests that varying degrees of acute or chronic inflammation are key contributing factors in the pathophysiology of malnutrition that is associated with disease or injury. Methods: An International Guideline Committee was constituted to develop a consensus approach to defining malnutrition syndromes for adults in the clinical setting. Consensus was achieved through a series of meetings held at the ASPEN and ESPEN Congresses. Results: It was agreed that an etiology-based approach that incorporates a current understanding of inflammatory response would be most appropriate. The Committee proposes the following nomenclature for nutrition diagnosis in adults in the clinical practice setting. ""Starvation-related malnutrition"", when there is chronic starvation without inflammation, ""chronic disease-related malnutrition"", when inflammation is chronic and of mild to moderate degree, and ""acute disease or injury-related malnutrition"", when inflammation is acute and of severe degree. Conclusions: This commentary is intended to present a simple etiology-based construct for the diagnosis of adult malnutrition in the clinical setting. Development of associated laboratory, functional, food intake, and body weight criteria and their application to routine clinical practice will require validation. (C) 2009 European Society for Clinical Nutrition and Metabolism and ASPEN American Society for Parenteral and Enteral Nutrition. Published by Elsevier Ltd. All rights reserved.

Adult Starvation and Disease-Related Malnutrition: A Proposal for Etiology-Based Diagnosis in the Clinical Practice Setting From the International Consensus Guideline Committee

Background & Aims: Multiple definitions for malnutrition syndromes are found in the literature resulting in confusion. Recent evidence suggests that varying degrees of acute or chronic inflammation are key contributing factors in the pathophysiology of malnutrition that is associated with disease or injury. Methods: An International Guideline Committee was constituted to develop a consensus approach to defining malnutrition syndromes for adults in the clinical setting. Consensus was achieved through a series of meetings held at the ASPEN. and ESPEN Congresses. Results: It was agreed that an etiology-based approach that incorporates a current understanding of inflammatory response would be most appropriate. The Committee proposes the following nomenclature for nutrition diagnosis in adults in the clinical practice setting. ""Starvation-related malnutrition,"" when there is chronic starvation without inflammation, ""chronic disease-related malnutrition"", when inflammation is chronic and of mild to moderate degree, and ""acute disease or injury-related malnutrition"", when inflammation is acute and of severe degree. Conclusions: This commentary is intended to present a simple etiology-based construct for the diagnosis of adult malnutrition in the clinical setting. Development of associated laboratory, functional, food intake, and body weight criteria and their application to routine clinical practice will require validation. (JPEN J Parenter Enteral Mar. 2010;34:156-159)

Association Between Polymorphisms in GRIK2 Gene and Obsessive-Compulsive Disorder: A Family-Based Study

Several studies support a genetic influence on obsessive-compulsive disorder (OCD) etiology. The role of glutamate as an important neurotransmitter affecting OCD pathophysiology has been supported by neuroimaging, animal model, medication, and initial candidate gene studies. Genes involved in glutamatergic pathways, such as the glutamate receptor, ionotropic, kainate 2 (GRIK2), have been associated with OCD in previous studies. This study examines GRIK2 as a candidate gene for OCD susceptibility in a family-based approach. Probands had full DSM-IV diagnostic criteria for OCD. Forty-seven OCD probands and their parents were recruited from tertiary care OCD specialty clinics from France and USA. Genotypes of single nucleotide polymorphism (SNP) markers and related haplotypes were analyzed using Haploview and FBAT software. The polymorphism at rs1556995 (P = 0.0027; permuted P-value = 0.03) was significantly associated with the presence of OCD. Also, the two marker haplotype rs1556995/rs1417182, was significantly associated with OCD (P = 0.0019, permuted P-value = 0.01). This study supports previously reported findings of association between proximal GRIK2 SNPs and OCD in a comprehensive evaluation of the gene. Further study with independent samples and larger sample sizes is required.

Inferring genome trees by using a filter to eliminate phylogenetically discordant sequences and a distance matrix based on mean normalized BLASTP scores

Darwin's paradigm holds that the diversity of present-day organisms has arisen via a process of genetic descent with modification, as on a bifurcating tree. Evidence is accumulating that genes are sometimes transferred not along lineages but rather across lineages. To the extent that this is so, Darwin's paradigm can apply only imperfectly to genomes, potentially complicating or perhaps undermining attempts to reconstruct historical relationships among genomes (i.e., a genome tree). Whether most genes in a genome have arisen via treelike (vertical) descent or by lateral transfer across lineages can be tested if enough complete genome sequences are used. We define a phylogenetically discordant sequence (PDS) as an open reading frame (ORF) that exhibits patterns of similarity relationships statistically distinguishable from those of most other ORFs in the same genome. PDSs represent between 6.0 and 16.8% (mean, 10.8%) of the analyzable ORFs in the genomes of 28 bacteria, eight archaea, and one eukaryote (Saccharomyces cerevisiae). In this study we developed and assessed a distance-based approach, based on mean pairwise sequence similarity, for generating genome trees. Exclusion of PDSs improved bootstrap support for basal nodes but altered few topological features, indicating that there is little systematic bias among PDSs. Many but not all features of the genome tree from which PDSs were excluded are consistent with the 16S rRNA tree.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.

The rights approach to local public management: experiences from Brazil

The Fundação Getulio Vargas, São Paulo, Public Management and Citizenship Program was set up in 1996 with Ford Foundation support to identify and disseminate Brazilian subnational government initiatives in service provision that have a direct effect on citizenship. Already, the program has 2,500 different experiences in its data bank, the results of four annual cycles. The article draws some initial conclusions about the possibilities of a rights-based approach to public management and about the engagement of other agencies and civil society organizations.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.