Performance Of GP Research Articles

Performance of the JF5-Based Galactomannoprotein EIA Compared to the Lateral Flow Device and the Galactomannan EIA in Serum and Bronchoalveolar Lavage Fluid.

Early diagnosis of invasive aspergillosis is an important factor to improve survival but remains challenging. The detection of Aspergillus antigens is included in the consensus case definitions of the European Organization for Research and Treatment of Cancer and the National Institute of Allergy and Infectious Diseases Mycoses Study Group as a criterion of "probable" invasive aspergillosis. JF5, a mouse IgG3 monoclonal antibody detecting an Aspergillus mannoprotein, has already been implemented as a lateral flow device (LFD). Now, also a JF5-based enzyme-linked immunosorbent assay (EIA) is commercialized (Aspergillus specific galactomannoprotein [GP] EIA, Euroimmun Medizinische Labordiagnostika AG). In this study, we analyzed the diagnostic performance of GP in 63 bronchoalveolar lavage fluid (BALf) samples and 224 serum samples and compared it to performance of the galactomannan (GM) (Platelia Aspergillus enzyme immunoassay (EIA) (Bio-Rad, Marnes-la-Coquette, France)) and the JF5-based LFD (AspLFD; OLM Diagnostics, Newcastle Upon Tyne, United Kingdom). The diagnostic performance of GP and GM correlated well with both having high specificity. With an optimized cutoff threshold for positivity of 0.4-deviating from the 0.5 threshold recommended by the manufacturer-sensitivity of GP in serum is not significantly different than that of GM. However, in BALf sensitivity of GP is significantly less than for GM.

Effect of Morphology and Concentration of Two Carbon Allotropes on the Enhancement of Specific Heat Capacity of Eutectic Molten Salt

Abstract This study aims at investigating the effect of nanoparticle morphology and concentration on the specific heat capacity of a molten salt used as thermal energy storage material in concentrated solar power plants. Binary carbonate salt eutectic (lithium carbonate and potassium carbonate at a molar ratio of 62:38, respectively) is used as the base material. Two different carbon allotropes, graphite nanoparticles (Gp) and carbon nanotube (CNT) are used as dopants to look into the morphological effect on specific heat (Cp). A series of experiments are carried out to systematically investigate the effect of nanoparticle concentration by varying the mass percentages of carbon allotropes (2 wt.%, 4 wt.%, and 6 wt.%) in the base material. The specific heat capacity of the samples is measured both in solid (250 °C and 400 °C) and liquid phases (520°–560 °C) using a differential scanning calorimeter (DSC). The results show a maximum enhancement of 35% in Cp for 6 wt.% Gp -based salt in the liquid phase. CNT-based nanomaterials exhibit a maximum enhancement of 20% for 4 wt.% CNT inclusion in the liquid phase. The superior performance of Gp compared to CNT and mass concentration-controlled specific heat is explained using field emission scanning electron microscope (FESEM) and energy-dispersive X-ray spectroscopy (EDS) analysis. FESEM and EDS analysis confirm the presence and the composition of the compressed layer, respectively. These layers are considered to be responsible for the anomalous increase in specific heat capacity at different mass concentrations for the carbon allotropes.

Robust estimation of heritability and predictive accuracy in plant breeding: evaluation using simulation and empirical data

BackgroundGenomic prediction (GP) is used in animal and plant breeding to help identify the best genotypes for selection. One of the most important measures of the effectiveness and reliability of GP in plant breeding is predictive accuracy. An accurate estimate of this measure is thus central to GP. Moreover, regression models are the models of choice for analyzing field trial data in plant breeding. However, models that use the classical likelihood typically perform poorly, often resulting in biased parameter estimates, when their underlying assumptions are violated. This typically happens when data are contaminated with outliers. These biases often translate into inaccurate estimates of heritability and predictive accuracy, compromising the performance of GP. Since phenotypic data are susceptible to contamination, improving the methods for estimating heritability and predictive accuracy can enhance the performance of GP. Robust statistical methods provide an intuitively appealing and a theoretically well justified framework for overcoming some of the drawbacks of classical regression, most notably the departure from the normality assumption. We compare the performance of robust and classical approaches to two recently published methods for estimating heritability and predictive accuracy of GP using simulation of several plausible scenarios of random and block data contamination with outliers and commercial maize and rye breeding datasets.ResultsThe robust approach generally performed as good as or better than the classical approach in phenotypic data analysis and in estimating the predictive accuracy of heritability and genomic prediction under both the random and block contamination scenarios. Notably, it consistently outperformed the classical approach under the random contamination scenario. Analyses of the empirical maize and rye datasets further reinforce the stability and reliability of the robust approach in the presence of outliers or missing data.ConclusionsThe proposed robust approach enhances the predictive accuracy of heritability and genomic prediction by minimizing the deleterious effects of outliers for a broad range of simulation scenarios and empirical breeding datasets. Accordingly, plant breeders should seriously consider regularly using the robust alongside the classical approach and increasing the number of replicates to three or more, to further enhance the accuracy of the robust approach.

Groundwater level forecasting using soft computing techniques

Knowledge of groundwater level is very important in studies dealing with utilization and management of groundwater supply. Earlier studies have reported that ELM performs better than SVM for groundwater level prediction. This has been verified by comparing the prediction of groundwater levels at six locations in the district of Vizianagaram, Andhra Pradesh, using ANN, GP, SVM and ELM. Based on the comparison, it is observed that the performance of ELM is the best compared to other models. ELM is capable of predicting the nonlinear behavior of the groundwater levels. SVM performs better than GP and ANN. The performance of GP and ANN is analogous. Furthermore, an attempt has been made to enhance the performance of SVM by using SVM hybrid models such as SVM-QPSO and SVM-RBF, and the same has been compared with SVM and ELM. Results indicate that the performance of SVM-QPSO is far better compared to the performance of SVM and SVM-RBF. Moreover, performance of ELM is observed to be the best, but on some occasions, SVM-QPSO performs on par with ELM.

Semantic Crossover Operator for GP based on the Second Partial Derivative of the Error Function

In recent years, a variety of semantic operators have been successfully developed to improve the performance of GP. This work presents a new semantic operator based on the semantic crossover based on the partial derivative error. The operator presented here uses the information of the second partial derivative to choose a crossover point in the second parent. The results show an improvement with respect to previous semantic operator.

Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database

In this paper we describe the genetic programming system GGP operating on graphs and introduce the notion of graph isomorphisms to explain how they influence the dynamics of GP. It is shown empirically how fitness databases can improve the performance of GP and how mapping graphs to a canonical form can increase these improvements by saving considerable evaluation time.

Diagnostic performance of anti-β2 glycoprotein I and anticardiolipin assays for clinical manifestations of the antiphospholipid syndrome

The objective of the present study was to analyse the performance of the tests for detection of anti-beta2 glycoprotein I (beta2 GP I) and anticardiolipin (aCL) antibodies for identification of clinical manifestations of the antiphospholipid syndrome (APS). Patients with systemic lupus erythematosus (SLE) as well as carriers of infectious diseases such as Kala-azar, syphilis and leptospirosis were studied. Particular interest was given to the presence of clinical complications related to APS. Anticardiolipin and anti-beta2 GP I antibodies were searched using an enzyme-linked immunosorbent assay (ELISA) assay. Clinical manifestations of APS were observed in 34 of the 152 patients (22.3%) with SLE and no patient with infectious disease had such manifestations. Antibodies to cardiolipin in moderate or high levels and anti-beta2 GP I were detected in 55 of 152 (36.1%) and 36 of 152 (23.6%) patients with SLE, respectively, and in 2 of 30 (6.6%) and 16 of 30 (53.3%) patients with Kala-azar, in 9 of 39 (23%) and 6 of 34 (17.6%) patients with leptospirosis, and 14 of 74 (18.9%) and 8 of 70 (11.4%) cases of syphilis, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratio (LR) of the anti-beta2 GP I test for the identification of the clinical manifestation of APS were, respectively, 29% [95% confidence interval (CI) = 24%-34%], 78% (95% CI = 73-83%), 15% (95% CI = 11-19%), 89% (95% CI = 85-93%) and 1.38. Regarding the aCL assay, the figure was 29% (95% CI = 24-34%), 76% (95% CI = 71-81%), 14% (95% CI = 10-18%), 89% (95% CI = 86-92%) and 1.26. As the validity and performance of the anti-beta2 GP I assay were similar to the aCL in demonstrating the presence of clinical phenomena associated with APS and due to the difficulties in performing as well as the lack of standardisation of the anti-beta2 GP I test, we suggest that the test for aCL should continue to be the first one performed when the presence of APS is suspected.

Hedging derivative securities with genetic programming

One of the most recent applications of GP to finance is to use genetic programming to derive option pricing formulas. Earlier studies take the Black–Scholes model as the true model and use the artificial data generated by it to train and to test GP. The aim of this paper is to provide some initial evidence of the empirical relevance of GP to option pricing. By using the real data from S&P 500 index options, we train and test our GP by distinguishing the case in‐the‐money from the case out‐of‐the‐money. Unlike most empirical studies, we do not evaluate the performance of GP in terms of its pricing accuracy. Instead, the derived GP tree is compared with the Black–Scholes model in its capability to hedge. To do so, a notion of tracking error is taken as the performance measure. Based on the post‐sample performance, it is found that in approximately 20% of the 97 test paths GP has a lower tracking error than the Black–Scholes formula. We further compare our result with the ones obtained by radial basis functions and multilayer perceptrons and one‐stage GP. Copyright © 1999 John Wiley & Sons, Ltd.

Performance of a nonisotopic DNA probe for detection of Chlamydia trachomatis in urogenital specimens

The Gen-Probe PACE 2 assay (GP), a nonisotopic DNA probe, was evaluated by using cell culture as the method of reference. Specimens were collected from 260 men and 482 women visiting the outpatient department for sexually transmitted diseases at the University Hospital in Rotterdam, The Netherlands. The prevalences of Chlamydia culture-positive men and women were 13.2 and 8.6%, respectively. Sensitivity values for the male and female patients were 70.6 and 92.7%, respectively. Specificity values for these groups were 98.2 and 97.7%, respectively. Sensitivity was significantly lower when the number of inclusions in cell culture was low. Samples which showed a discordance between cell culture and GP results were retested by the polymerase chain reaction. If the results of the polymerase chain reaction were considered as the points of reference, the sensitivity and specificity of both GP and cell culture could be calculated. The performance of GP for females was comparable to that of cell culture. In males, the sensitivity of GP was considerably lower than that of cell culture (77.2 versus 91.4%), while specificity was somewhat higher (99.6 versus 99.1%). Compared with cell culture, the GP is a relatively simple and rapid test that is suitable for diagnosing Chlamydia infections in urogenital specimens.

The Effect of Risk on Concept Acquisition

Thirty-six ninth grade Ss were randomly assigned to six treatments requiring concept acquisition with regard to various kinds of concept instances. Two groups received good positive instances (GP), two good negative and good positive instances (GN), and two poor negative and good positive instances (PN). One group of each set performed under risk conditions and the other under non-risk conditions. Risk was established by presenting S with money which was removed for incorrect learning. It was found that Ss using GP instances performed best and that risk interfered with the use of GN instances. Risk improved the performance of GP and PN Ss.