A hybrid planning method for transmission networks in a deregulated environment

The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Objectives for multiple-species conservation planning

The first step in conservation planning is to identify objectives. Most stated objectives for conservation, such as to maximize biodiversity outcomes, are too vague to be useful within a decision-making framework. One way to clarify the issue is to define objectives in terms of the risk of extinction for multiple species. Although the assessment of extinction risk for single species is common, few researchers have formulated an objective function that combines the extinction risks of multiple species. We sought to translate the broad goal of maximizing the viability of species into explicit objectives for use in a decision-theoretic approach to conservation planning. We formulated several objective functions based on extinction risk across many species and illustrated the differences between these objectives with simple examples. Each objective function was the mathematical representation of an approach to conservation and emphasized different levels of threat Our objectives included minimizing the joint probability of one or more extinctions, minimizing the expected number of extinctions, and minimizing the increase in risk of extinction from the best-case scenario. With objective functions based on joint probabilities of extinction across species, any correlations in extinction probabilities bad to be known or the resultant decisions were potentially misleading. Additive objectives, such as the expected number of extinctions, did not produce the same anomalies. We demonstrated that the choice of objective function is central to the decision-making process because alternative objective functions can lead to a different ranking of management options. Therefore, decision makers need to think carefully in selecting and defining their conservation goals.

Direct evidence for the expression of multiple endogenous retroviruses in the synovial compartment in rheumatoid arthritis

Objective. Circumstantial evidence links retroviruses (RVs) with human autoimmune diseases, The aim of the present study was to obtain direct evidence of RV gene expression in rheumatoid arthritis (RA). Methods. Synovial samples were obtained from patients with RA, patients with osteoarthritis (OA), and normal control subjects, Reverse transcription-polymerase chain reaction (RT-PCR) was performed using synovial RNA and primers to conserved sequences in the polymerase (pol) genes of known RVs. Results. PCR products (n = 857) were cloned and sequenced, Multiple pol transcripts, many with open reading frames, were expressed in every sample, Sequences were aligned and classified into 6 families (F1-F6) that contained 33 groups of known and unknown endogenous RVs (ERVs), each distinguished by a specific, deduced peptide motif, The frequency of sequences in each family was similar between RA, OA, and normal synovial tissue, but differed significantly in RA synovial fluid cells, F1 sequences (undefined, but related to murine and primate type C RVs) were lower in frequency, F2 (ERV-9-related), F4 (HERV-K-related), and F6 (HERV-L-related) sequences were higher in frequency, and F3 (RTVL-H-related) sequences were not detected, in the RA synovial fluid cells compared with the RA synovial tissues. Conclusion. Multiple ERVs are expressed in normal and diseased synovial compartments, but specific transcripts can be differentially expressed in RA.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem. (C) 2001 Elsevier Science B.V. All rights reserved.

Extensive multiple test centre evaluation of the VecTest malaria antigen panel assay

To determine which species and populations of Anopheles transmit malaria in any given situation, immunological assays for malaria sporozoite antigen can replace traditional microscopical examination of freshly dissected Anopheles. We developed a wicking assay for use with mosquitoes that identifies the presence or absence of specific peptide epitopes of circumsporozoite (CS) protein of Plasmodium falciparum and two strains of Plasmodium vivax (variants 210 and 247). The resulting assay (VecTest(TM) Malaria) is a rapid, one-step procedure using a 'dipstick' test strip capable of detecting and distinguishing between P. falciparum and P. vivax infections in mosquitoes. The objective of the present study was to test the efficacy, sensitivity, stability and field-user acceptability of this wicking dipstick assay. In collaboration with 16 test centres world-wide, we evaluated more than 40 000 units of this assay, comparing it to the standard CS ELISA. The 'VecTest(TM) Malaria' was found to show 92% sensitivity and 98.1% specificity, with 97.8% accuracy overall. In accelerated storage tests, the dipsticks remained stable for >15 weeks in dry conditions up to 45degreesC and in humid conditions up to 37degreesC. Evidently, this quick and easy dipstick test performs at an acceptable level of reliability and offers practical advantages for field workers needing to make rapid surveys of malaria vectors.

Efficacy of twice-weekly multiple micronutrient supplementation for improving the hemoglobin and micronutrient status of anemic adolescent schoolgirls in Bangladesh

Background: Although iron deficiency is a major cause of anemia, other micronutrient deficiencies may also play a role. Objective: We examined whether multiple micronutrient supplementation is more efficacious than is supplementation with iron and folic acid alone for improving the hemoglobin and iron status of anemic adolescent girls in Bangladesh. Design: Anemic (hemoglobin < 12.0 g/dL) girls (n = 197) aged 14-18 y from rural schools in Dhaka District were entered into a randomized double-blind trial and received twice-weekly supplements of iron and folic acid (IFA group) or multiple micronutrients (15 micronutrients, including iron and folic acid; MMN group) for 12 wk. Results: At recruitment, the characteristics of the girls in the 2 groups were not significantly different, except for family size and body mass index. At the end of the study, although both groups benefited significantly from supplementation, mean changes in hemoglobin and serum ferritin concentrations were not significantly different between groups. Compared with the IFA group, girls in the MMN group had significantly greater increases in mean serum vitamin A, plasma vitamin C, red blood cell folic acid, and riboflavin concentrations (assessed as erythrocyte glutathione reductase activation coefficient). After 12 wk of supplementation, only the prevalence of vitamins A and C and riboflavin deficiencies decreased more significantly in the MMN group than in the IFA group. Conclusions: Twice-weekly MMN supplementation for 12 wk significantly improved the status of the micronutrients assessed but was not more efficacious than was supplementation with iron and folic acid alone in improving the hematologic status of anemic adolescent girls. More frequent doses may be needed to achieve full benefit.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Variance components analyses of multiple asthma traits in a large sample of Australian families ascertained through a twin proband

Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.

A new method for conservation planning for the persistence of multiple species

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Relations between social support, appraisal and coping and both positive and negative outcomes for children of a parent with multiple sclerosis and comparisons with children of healthy parents

Objective: To examine adjustment in children of a parent with multiple sclerosis within a stress and coping framework and compare them with those who have 'healthy' parents. Subjects: A total of 193 participants between 10 and 25 years completed questionnaires; 48 youngsters who had a parent with multiple sclerosis and 145 youngsters who reported that they did not have a parent with an illness or disability. Method: A questionnaire survey methodology was used. Variable sets included caregiving context (e.g. additional parental illness, family responsibilities, parental functional impairment, choice in helping), social support (network size, satisfaction), stress appraisal, coping (problem solving, seeking support, acceptance, wishful thinking, denial), and positive (life satisfaction, positive affect, benefits) and negative (distress, health) adjustment outcomes. Results: Caregiving context variables significantly correlated with poorer adjustment in children of a parent with multiple sclerosis included additional parental illness, higher family responsibilities, parental functional impairment and unpredictability of the parent's multiple sclerosis, and less choice in helping. As predicted, better adjustment in children of a parent with multiple sclerosis was related to higher levels of social support, lower stress appraisals, greater reliance on approach coping strategies (problem solving, seeking support and acceptance) and less reliance on avoidant coping (wishful thinking and denial). Compared with children of 'healthy' parents, children of a parent with multiple sclerosis reported greater family responsibilities, less reliance on problem solving and seeking social support coping, higher somatization and lower life satisfaction and positive affect. Conclusions: Findings delineate the key impacts of young caregiving and support a stress and coping model of adjustment in children of a parent with multiple sclerosis.

The cross-entropy method for continuous multi-extremal optimization

In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.